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Technology's daily show (formerly the Technology Brothers Podcast). Streaming live on X and YouTube from 11 - 2 PM PST Monday - Friday. Available on X, Apple, Spotify, and YouTube.
You're watching TBPN.
Speaker 2:Today is Tuesday, 11/25/2025. We are live from the TBPN Ultradell, the temple Of technology, the fortress of finance, the capital of capital. We had a we had fan yesterday was the Anthropic Claude four point five day. We had a lot of fun talking to Sholto about that. You should go check it out.
Speaker 2:We wrote a little write up. I collaborated with Brandon and Tyler to kinda give our thoughts on the state of the AI race with regard to, OpenAI and Anthropic and what makes Anthropic special. The things that stuck out to me I mean, thing that went viral was just the fact that apparently Dario goes around Slack and writes essays every single day. And everyone was like, give me the essays. Turn it into a book.
Speaker 2:Paging Stripe Press. We gotta get Stripe Press to turn it into a book.
Speaker 1:Yeah. That, but I was also thinking of potentially a risk factor for them of being like the Dario files, you know, disgruntled a disgruntled employee that Yeah. Saves them all. Then leaks them all. I imagine Because he even when he's on mic, he's known to say some things that he at times sort of
Speaker 2:People people I feel like people take you out of out of
Speaker 1:Out of context.
Speaker 2:Out of context a lot. Like like, he will say
Speaker 1:He's gonna say the final boss
Speaker 2:being taken contact. If this go well, we could lose 50% of white collar work or entry level white collar work. And and people will be like, Anthropic stated mission is to destroy jobs.
Speaker 1:Take your father's job.
Speaker 2:Yeah. Yeah. It's, it's rough. But, ramp. Time is money.
Speaker 2:Save both. Easy use corporate cards, bill payments, accounting, and a whole lot more all in one place. Timeline was in turmoil over the weekend and yesterday. We covered a little bit about the nucleus dust up on the timeline. Cremieux will be coming on the show at 11:45.
Speaker 2:And then
Speaker 1:Fast followed.
Speaker 2:Keon, the CEO of Nucleus, be coming on the show at noon. So we will kind of have both sides. Then we have, Joe Wiesenthal joining from Bloomberg. And, and then we have who else do we have today? Gracias.
Speaker 2:Gracias is coming on to break down, Project Genesis, which we're very excited Anyway, let's, run through, what other, news stories were at the top of the timeline while we pulled those up. Let me tell you about Restream, one livestream, 30 plus destinations. If you wanna multistream, go to restream.com. Oh, yes. The biggest news in tech in AI is that, the, Ilya Sutskever, Dwarkash Patel podcast has dropped.
Speaker 2:Do we have Hit the timeline. Do we have the opening clip? Because the opening clip is is iconic. It's it's it's, it's very funny. It's a it's bit of a hot mic moment for Ilya, and I think we should we should pull it up and, and play it because it has a fascinating, just insight into it feels very like, oh, this is where this is the real Ilya.
Speaker 2:He's not he's not even thinking that he's on camera, and he gives his real his real feelings. So let's let's play this from the very
Speaker 3:crazy.
Speaker 2:Listen to that.
Speaker 3:But all of this is real.
Speaker 1:Yeah. Meaning Don't
Speaker 3:don't you think so?
Speaker 1:Meaning what?
Speaker 3:Like all this AI stuff and all this Bay Area yeah. That it's happened. Like, isn't it straight out of science fiction?
Speaker 1:Yeah. Another thing that's crazy is, like, how normal this slow takeoff feels. The idea that we'd be investing 1% of GDP
Speaker 2:It's like AI. Hasn't even
Speaker 1:I feel like nervous. Felt like
Speaker 2:a big deal.
Speaker 1:You know? But right now, just feels like
Speaker 3:And you get used to things pretty fast turns out. Yeah? But also, it's kinda like it's abstract. Like, what does it mean? What it means that you see it in the news Yeah.
Speaker 3:That such and such company announced such and such dollar amount.
Speaker 1:Right.
Speaker 3:That's that's all you see. Right. It's not really felt in any other way so far.
Speaker 1:No. Should we actually begin here? I think this is an interesting discussion. Sure.
Speaker 2:It's one of the greatest podcast intros from
Speaker 1:the all time. Point of view. So good. So good.
Speaker 2:Anyway, we're not gonna watch the whole show.
Speaker 3:I think that's that's
Speaker 1:gonna be a new meta.
Speaker 2:Yes. Yes. I mean, you you can't you can't fake that. It's amazing. Also, it's just funny because, you know, he it's effectively getting caught on a hot mic.
Speaker 2:But I was joking. I was like, of all the things that you could say on the hot mic before you sit down, oh, okay. We're actually recording. His is just completely reaffirming everything we know about Ilias Setskware. Like, it's just completely the same like, okay.
Speaker 2:He's a he is a true believer. It's not like he was sitting down and being like, like, Nordcash. Like, we gotta go, on my private plane. I just sold so much secondary. It's crazy what's going on with this stuff.
Speaker 2:Like, if people really think this AI thing is gonna pan out, I'm making billions of dollars, and I'm I'm cashing out. I'm I I don't believe any of this stuff is real. No. He wasn't caught on a hot mic like that. He he his hot mic moment is like, wow.
Speaker 2:It's exactly like science fiction. Everything It's
Speaker 1:all real.
Speaker 2:It's all real. Yeah. Which is just, iconic. Well, you can go and, listen to that in the Dwarkash Patel RSS feed and on the YouTube channel and on x. He put the full thing up.
Speaker 2:It's ninety five minutes long. Tyler, did you have any other takeaways from your speed run? You're listening to it at five x.
Speaker 3:Right? Well, on x, can only up do up to two x. I was on that, so I I still have, like, ten minutes left. Okay. But, yeah, a bunch of good stuff in here.
Speaker 2:Does he pop the scaling bubble? Does he give a bearish take about Is over? At any point? While you're thinking about that, let me tell you about Gemini three Pro, Google's most intelligent model yet. State of the art reasoning, next level vibe coding, and deep multimodal understanding.
Speaker 2:Continue.
Speaker 3:So I wouldn't say he's, like, anti scaling, but he does kind of give this interesting take Mhmm. Which he he basically says that, like, now AI companies are like, there's too few ideas Mhmm. For the amount of companies and and for for the the scale that we're at Mhmm. Where he basically, like, you you can think of AI progress as being in these kind of distinct ages. Right?
Speaker 3:So he says, 2012 to 2020 was like the age of research
Speaker 4:Mhmm.
Speaker 3:Where you're trying all these, like, different ideas and and the scale of things is very small. Right? Like, to train the original AlexNet was like two GPUs to do the original transformer was like eight, maybe 64, but like, know, very small amount of GPUs. And then once we kinda figured out that that transformers work, we entered this age of scaling. Mhmm.
Speaker 3:And that's basically from from 2020 to 2025. And now we're basically at this point where, like, yes, you can keep scaling and models will get better. But even if you scale a 100 x Mhmm. Like, are we really gonna get super intelligence? It like, it'll get better on the benchmarks Yep.
Speaker 3:And they'll become more useful. But it's not like this he doesn't think that just raw scaling alone is basically what's gonna bring us there. I mean, this has been echoed by a lot of people. Right? This was, I think, Carpathi Carpathi said this where we still need a couple different kind of paradigms Yeah.
Speaker 3:For this to work. Yeah. And even he's like, this is even kind of what Sholto said yesterday, which is like, pre training is it's not dead, but it's like the reason that that Opus 4.5 was better is not just because they scaled pre training.
Speaker 2:Yeah.
Speaker 3:It's scaling generally.
Speaker 2:Yeah.
Speaker 3:But even then, like, the the scaling has gone from pre training and now it's RL. Yeah. And so we basically we need to find another paradigm. Yeah. And the way you do that is just doing, like, research.
Speaker 3:And and so he talks about SSI as basically being this, like Return to research.
Speaker 2:To research.
Speaker 3:Yeah. It it's small kind of training runs. Even though, you know, they only raised 3,000,000,000, which is, like, small compared to other Sure. To to other research institutions, The fact that they're basically putting it all on these kind of I mean, I don't know if they're moonshots, but they're these small training runs where they're doing experiments. Yep.
Speaker 3:And then they're gonna scale it up eventually. Yep. But they're not just basically trying to win the AI race by just scaling up and do the same thing as someone else.
Speaker 2:Yeah. Yeah. They're trying to find a new a way to actually bend the scaling curve, find a new scaling law, or find a new technology that, like, they they can scale against. I was thinking about, Ilya's talk at NeurIPS last year. He pulls up this chart of, the relationship between mammal the mammal's mass and the brain volume, and it's a pretty linear graph.
Speaker 2:And so, like, the elephant is a lot bigger than the mouse, and so it has a proportionally larger brain to its body volume. And and it's this perfect it's this perfect linear curve. I should I should just try and figure it out if I, I can maybe text it in. I took a picture of it, because it's a very it's a very cool chart. Here it is.
Speaker 2:Who where do I send this? The timeline? Let me see.
Speaker 1:Ship it.
Speaker 2:Share. Let me see. Timeline. Sorry. Boom.
Speaker 2:So, basically, the the mammals have this, like, very clear linear trend, but then the nonhuman primates are a little bit higher up on the chart, and they're just doing a little bit better. But then, hominids, the the actual humans have a different there's a very distinctly different curve. And so there's this interesting, like, it was making me think, like, like, maybe that's what we're supposed to see when we think about, yeah, this, this. It's like it's like when we say, like, straight lines on log graphs, when we say we are seeing scaling happen with the current architectures, which line are we scaling against? Are we are we actually scaling on the on the human curve, or are we waiting for divergence from that current scaling law?
Speaker 3:Yeah. He has this good quote where scaling has taken all the air out of the room. Mhmm. Right? Where, like, basically, like, we have more than enough compute to try these, like, different ideas Yeah.
Speaker 3:But they're just all going straight into to training the next big model Yeah. Using the next paradigm. And maybe it's slightly different. Right? You have a different way of doing RL or whatever, but it is still fundamentally the same thing.
Speaker 3:Right? And he talks about maybe continual learning is really the the better approach. Right? We we've we've been in this era of, like, having a pre training thing for so long that we think of, like, AI as, like, you train this thing and then you release it and it's, like, done. Yep.
Speaker 3:And RL's, like, a little bit different now because Yeah. There's this idea of post training and you can kind of integrate
Speaker 2:interesting thing was with with pre training, you use the whole Internet so you don't have to decide anything. You're just applying this algorithm to just all the data, all the compute, and there's no decisions. But then with RL, you have to decide, okay. We're putting in these math equations and we're maybe not putting in something else because we're actually creating the data and we're and it's not just this
Speaker 3:This is like this is maybe why we see these kind of, like, models that are super well. Yep. They do super well in evals, but not so much
Speaker 2:Yeah. Some of overfitting and
Speaker 3:And the reason is because the data that we choose is not the correct data
Speaker 2:Yeah.
Speaker 3:Because researchers are basically being reward hacked maybe Yeah. Into, like, just solving for benchmarks.
Speaker 2:Yeah. It's interesting. It's interesting to hear this like the conclusion is we need another breakthrough and then simultaneously consensus be but we're definitely going to get that breakthrough in the next decade. It's, like, it's hard like, these breakthroughs, it's hard to predict.
Speaker 1:Feel like it echoes a lot of even what Mike Newp has been saying. Like, we need new ideas. Yeah. Totally. Saying this for for months.
Speaker 1:I and
Speaker 2:But it's way it's way harder to predict the rate at which breakthroughs will arrive as opposed to, like, you can actually chart out, okay, the formation of capital, the time it takes to build a data center, how long it takes to, you know, manufacture a bunch of GPUs, rack them, run the training around. Like, that's much more predictable than, like, human came up with new algorithm. Like, that's sort of random.
Speaker 3:Yeah. And he he brings this up as as the reason why you see companies doing this because it's just if you're raising money, it's so much easier to to justify the raise by saying, we're gonna buy this data center Totally. And do this training run. Totally. It's gonna cost exactly much.
Speaker 3:Oh, It's very under right. Yeah. Then the model will be this good, and then we can use it to monetize this way.
Speaker 2:Totally.
Speaker 3:Where if you're just saying, like, oh, yeah. We're just gonna pay a bunch of, like, really smart researchers to do a bunch of research, and then they'll they'll figure something out Yep. That it like, you can't really Yeah.
Speaker 1:In some ways, it it feels like SSI is set up for, like, somewhat of a mini AI winter Mhmm. Or, like, at least riding the hype cycle down. Yeah. Because it doesn't sound like you're sitting there being like, we raised 3,000,000,000 and we're spending it in the next twelve months. It's like
Speaker 2:2.9 was that.
Speaker 1:No. Not not not
Speaker 2:No. No. No. That's the point. It's not.
Speaker 2:It's like equity. It's just sitting there. It's like, he can you you clearly pull back.
Speaker 1:I'm gonna give each researcher, all these different teams, like, shots on goal. No. I love it. We're gonna keep taking those shots until, obviously, he'd be able to raise, like, another $10,000,000,000 whenever he wants, especially if he has, like, a key breakthrough insight and they can be first to scale that.
Speaker 2:Yep. Well, let me tell you about Cognition. The they make Devin, the AI software engineer, crush your backlog with your personal AI engineering team. NVIDIA has posted
Speaker 1:They hit the timeline. They hit the timeline. Break this down for me, Jordi. They said, we're delighted by Google's success. They've made great advances in AI and we continue to supply to Google.
Speaker 1:NVIDIA is a generation ahead of the industry. It's the only platform that runs every AI model and does it everywhere computing is done. NVIDIA offers greater performance, ver Versatility Versatility fungibility than ASICs. Which are designed for specific AI frameworks or functions.
Speaker 2:That is a crazy thing to post.
Speaker 1:Crazy, crazy, crazy thing to post. You get stuff don't know, boys, but having the largest company in the world sending tweets to defend their main product is not very reassuring.
Speaker 2:Yeah. It's just an odd I feel like this would be so much better delivered. I actually don't have that much of a problem with the actual text here. I just think this should be delivered by Jensen with some nuance in a conversational setting. It just hits a lot different when this is in at exactly 9AM, like, clearly scheduled, clearly typed out in a document.
Speaker 2:You know? It's like
Speaker 3:Yep.
Speaker 2:It it it feels like a press release, which is just an odd odd thing when in when it should be you know, there should be an answer to a question which someone Bobby Cosmic in the chat was saying like, oh, the mainstream media is just now picking up on the Gemini three story. And there's articles in The Wall Street Journal and other places saying like, oh, maybe Google's back. Like, you know, buy Google. Like, it's very exciting. And and so NVIDIA feels feels the need to respond to that, but it's a lot different when it's actually a response instead of just like, we're putting out a press release.
Speaker 2:Like, who knows why? Like Yeah. As opposed to, like, Jensen saying, well, since you asked, you know, talk show host or news anchor or whoever he's podcast host, whoever he's talking to, Dorcasch, you know, whoever he's talking to, maybe us. We'd love to have him. I can ask him that question.
Speaker 2:He can defend this here.
Speaker 1:Yep. Well, the timing is is seems important because they are coming under a huge amount of pressure right now.
Speaker 2:There was
Speaker 1:an article in Yep. Errands this morning by Tae Kim.
Speaker 2:Yep.
Speaker 1:The headline is not what NVIDIA's comms teams would have liked Mhmm. It to be. The headline is NVIDIA says it's not Enron in private memo refuting accounting questions.
Speaker 2:That's a crazy thing to say. Of course, it's not Enron, but
Speaker 1:Let let me get let me get into the to the coverage. So Tay says, a series of prominent stock sales and allegations of accounting irregularities have put NVIDIA in the middle of a debate about the value of artificial intelligence and its related stocks. Now NVIDIA is pushing back in a private seven page memo sent by NVIDIA's investor relations team to Wall Street analysts over the weekend. The chipmaker directly addressed a dozen claims made by skeptical investors. NVIDIA's memo, which includes fonts in the company's trademark green color, begins by addressing a social media post from Michael Burry last week, which criticized the company for stock based comp, dilution, and stock buybacks.
Speaker 1:Burry's bet against subprime mortgages before the two thousand and eight financial crisis was depicted in the movie The Big Short, of course. Nvidia repurchased 91,000,000,000 shares since 2018, not $112,000,000,000 Mr. Burry appears to have incorrectly included RSUs. RSU taxes, employee equity grants should not be conflated with the performance of the repurchase program. NVIDIA said in the memo, employees benefiting from a rising share price does not indicate the original equity grants were excessive at the time of issuance.
Speaker 1:That makes sense. Barron's reviewed the memo, which initially appeared in social media posts over the weekend and confirmed its authenticity. Burry told Barron's he disagrees with NVIDIA's response and stands by his analysis. He said he would discuss the topic of the company's stock based comp in more details. Burry is, of course, now over on Substack.
Speaker 1:He's charging $380 a year. And if you are a permabear, I can't this is like Christmas coming early. Nvidia didn't respond to Barron's for a request for comment, but they also responded to claims that the current situation is analogous to historical accounting frauds, Enron, WorldCom, and Lucent, that featured vendor financing and SPVs. NVIDIA does not resemble historical accounting frauds because NVIDIA's underlying business is economically sound. Our reporting is complete and transparent, and we care about our reputation for integrity.
Speaker 1:Unlike Enron, NVIDIA does not use special purpose entities to hide debt or inflate revenue.
Speaker 2:There's no market It's like there's 25 examples of how this is not the same.
Speaker 5:I think
Speaker 2:you know why they're
Speaker 1:NVIDIA also addressed allegation that its customers, large technology companies aren't properly accounting for the economic value of NVIDIA hardware. Some of the companies use, we've talked about this, use a six year depreciation schedule for GPUs. Burry said he believes the useful lives of the chips are shorter than six years, meaning NVIDIA's customers are inflating profits by spreading out deep depreciation costs over a long period. NVIDIA's customers depreciate GPUs over four to six years based on real world longevity and utilization patterns. Older GPUs such as a one hundreds continue to run at high utilization and generate strong contribution margins retaining meaningful economic value well beyond the two to three years claimed by some commentators.
Speaker 1:So again, under fire on the TPU front and from the Michael Burry camp, but again, I think I think their their answers are totally valid. Matt, over on x said, had a post here. He said the TPUs equal bad for Nvidia Take is up there with the dumbest, maybe worse than DeepSeek as it completely misses what actually happened in the last six weeks. And I will remember who is who in the zoo, my view. One, demand for AI is bananas.
Speaker 1:No one can meet demand. Everyone is spending more. Google said just yesterday they have to double capacity every six months to keep up. Two, scaling laws are intact. He's referencing Gemini three.
Speaker 1:The flywheel is about to speed up. Somehow, the mid curve crew thinks this is zero sum competition. None of this suggests that. If you think the race is hot now, wait until you see what comes out of large coherent black well clusters. All the magic from the quote god machines is pretty much still hopper based.
Speaker 1:Lastly, a quick GPU TPU less than the cost and performance specs on the box aren't what you get in real life. And Google is going to get a fat margin too, doubled up. What matters is system level effective tokens to watt to dollars and TCO. NVIDIA GPUs have higher FMU because they are they're already embedded in workflows slash the ecosystem is massive. By the way, this is a good test.
Speaker 1:If you have an opinion on this topic, but you have to look up FMU, then perhaps curate better service. MRFU. What?
Speaker 2:MFU. MFU.
Speaker 1:You said FMU. Sorry. Sorry. The above effective token Watt gap also likely widens with Rubin. Add in that Jensen can actually deliver volume in a tight market, plus future flexibility, multi cloud capable, programmable for paradigm shifts, and he'll sell every GPU he makes for years.
Speaker 1:Mhmm. Google will too since everyone wants a second supplier and TPU is a fantastic chip, But this is as far from either or as it gets. The one benefit of this confusion is that it is likely to give Google a brief stint as the world heavyweight champion, the most valuable company. I would guess the Midwits put the strap on them in less than two weeks. So he
Speaker 2:the strap on them? What does that mean? Just like like like pile in? Is he saying just like so he so he is he it seems like he's predicting that that people will overplay the NVIDIA bear take and o Overplay the Google opportunity. Opportunity, and that will result in Google becoming the most valuable company in the world.
Speaker 2:And he uses the phrase put the strap on them in multiple Yep. In less than two weeks. Interesting post.
Speaker 1:In other news, David Sacks has hit the timeline. He says according to today's Wall Street Journal, AI related investment accounts for half of GDP growth. A reversal would risk recession. We can't afford to go backwards. We will the article is how The US economy became hooked on AI spending.
Speaker 1:Mhmm. And we will be chatting with in about an hour on this on this very topic. So we can get into a little bit.
Speaker 2:Well, before we move on, me tell you about Adio, AI native CRM. Adio builds, scales, and grows your company to the next level.
Speaker 5:You wanna read
Speaker 1:through Fact sheet from the White House. President Donald J. Trump unveils the Genesis mission to accelerate AI for scientific discovery. Today, and this is yesterday, today Trump signed an executive order launching the Genesis mission, a new national effort to use artificial intelligence to transform how scientific research is conducted and accelerate the speed of scientific discovery. The Genesis Mission charges the Secretary of Energy with leveraging our national laboratories to unite America's brightest minds, most powerful computers, and vast scientific data into one cooperative system for research.
Speaker 1:The order directs the Department of Energy to create a closed loop AI experimentation platform that integrates our nation's world class supercomputers and unique datasets to generate scientific foundation models and power robotic laboratories. The order instructs the assistant to the president for science and technology to coordinate the national initiative and integrate an integration of data and infrastructure from across the federal government. The secretary of energy, APST, and the special adviser for AI and crypto will collaborate with and private sector innovators to support and enhance the Genesis mission. Priority areas of focus include the greatest scientific challenges of our time that can dramatically improve our nation's national, economic, and health security, including biotechnology, critical minerals, nuclear fission, and fusion energy, space exploration, quantum information science, and semiconductors, and microelectronics. Next, harnessing AI for our national security and economic development.
Speaker 1:With the Genesis Mission, the Trump administration intends to dramatically expand the productivity and impact of federal research and development within a decade. So there's one more note here on strengthening America's AI dominance. Trump continues to prioritize America's global dominance in AI to usher in a new golden age of human flourishing, economic competitiveness, and national security. And so we will get into more of of this with Kratios.
Speaker 2:Yeah. I'm I'm very interested to hear how, like, how the public private partnership actually works here. There was a time when every basically, every cool technology was coming out of DARPA, coming out of the US government. The US government landed on the moon. And since then, you know, I I think a lot of people in technology have lost faith in the US government overseeing the development of technology.
Speaker 2:Even academia, I mean, the the people people think, like, you know, AGI will emerge from a private c corp. Like, that's where people believe that the best work will be done with you know, give Ilya Sutskever, give the best scientist $3,000,000,000, let him go cook. Like, that's the thesis currently in tech. This feels like somewhat of a rejection of that in some ways. There's obviously lots of different places where, having AI resources, having science and technology resources within the government make a ton of sense.
Speaker 2:But it'll be interesting to see, like, where are the, interfacing points between the two, between the two categories, the the public and private sector. Because by default, I think most people in our audience in technology, would would say, hey. Like, let's leave the, let's leave the space travel and the and and the AI research to the to the private sector. And, and and this is, you know, potentially a different direction, potentially just, very synergistic. So Yep.
Speaker 2:Be interesting to see where it breaks. Well, should we, run through the Astral Codex 10 piece on trait based embryo selection to tee up our discussion with Cremieux and Kian from Nucleus
Speaker 1:Let's do it.
Speaker 2:And go through that. So, this is from Scott Alexander in Astral Codex 10. He said, suddenly, trait based embryo selection. When a couple uses I, so in 2021, genomic prediction announced the first polygenically selected baby. When a couple uses IVF, they may get as many as 10 embryos.
Speaker 2:If they want one child, which one do they implant? In the early days, doctors would just eyeball them and choose whichever looked the healthiest. Later, they started testing for some of the most severe and easiest to detect genetic orders like disorders like Down syndrome and cystic fibrosis. The final step was polygenic selection, genotyping each embryo and implanting the one with the best genes overall. Best in what sense?
Speaker 2:Genomic prediction claimed the ability to forecast health outcomes from diabetes to schizophrenia, for example, although the average person has a thirty percent chance of getting type two diabetes, if you genetically test five embryos and select the one with the lowest predicted risk, they'll only have a twenty percent chance. So you get a ten percent bump there. That's nice. Since you're taking the healthiest of many embryos, you should expect a child conceived via this method to be significantly healthier than one born naturally. Polygenic selection straddles the line between disease prevention and human enhancement.
Speaker 2:In 2023, ORCID Health, founded by NOR, who we've had on the show, enter the field. Unlike genomic prediction, which, tested only the most important genetic variants, ORCID offers whole genome sequencing, which can detect the de novo mutations involved in autism, developmental disorders, and certain other genetic diseases. Critics accused GP and ORCID of offering designer babies, but this is only true in the weakest sense. Customers couldn't design a baby for anything other than slightly lower risk of genetic disease. You're basically just selecting out of what you already got.
Speaker 2:Yep. They're not editing the genes. They're they're merely sequencing them and then allowing you to select. These companies refused to offer selection on traits, the industry term for the really controversial stuff like, height, IQ, or eye color. Still, these were trivial extensions of their technology, and everyone knew it was just a matter of time before someone took the plunge.
Speaker 2:Last month, a startup called Nucleus took the plunge. They had previously offered 23 and Me style genetic tests for adults. Now they announced a partnership with genomic prediction focusing on embryos. Although GP would continue to only test for health outcomes, You could forward the raw data from GP to Nucleus, and Nucleus would protect predict extra traits, including height, BMI, eye color, hair color, ADHD, IQ, and even handedness.
Speaker 1:And it's worth noting that Nucleus is now being sued by genomic prediction.
Speaker 2:Even though they have this partnership?
Speaker 1:I I'm assuming the partnership is no longer. Yeah. Well, we can ask. Yeah. But I'm assuming it's no longer because one of, GP's cofounders left left the company to join to join Nucleus.
Speaker 1:Interesting. And allegedly turned off all the security cameras that the
Speaker 2:Is that that's metaphor? Or is that actually
Speaker 1:No. The lawsuit alleges that the that he turned off all the security cameras on his laptop.
Speaker 2:Not a metaphor for, like, you know, sharing a Google Drive of PDFs. You literally mean
Speaker 1:It's his last day at work.
Speaker 2:Okay.
Speaker 1:And he was allegedly, like, wrapping up.
Speaker 2:Okay. So he turns off the cameras allegedly, and and the implication is that maybe he was rummaging around, like, literally taking documents or something like that.
Speaker 3:That's at
Speaker 2:least what the timeline is.
Speaker 1:What the Accused the lawsuit alleges.
Speaker 2:Okay. Wow. That that that that's wild. I I did not know that that was a literal accusation.
Speaker 1:And then another part of it, apparently, Nucleus, it's new people at Nucleus were emailing the former co founder at his old email address evidence of them violating the the the agreement that they had. So Okay. Anyways, it's very, very, very, very messy. We can ask
Speaker 2:Yeah. There's like four or five companies involved in this
Speaker 1:And all of them are controversial because this is the most, I think, the most controversial probably, like, category that you can be in.
Speaker 2:Yeah. It's it's certainly up there.
Speaker 1:Health is already, like, one of the most controversial topics.
Speaker 2:Yeah. Everyone has an opinion on it.
Speaker 1:Health influencer they've gotten into
Speaker 2:Totally.
Speaker 1:Various debacles.
Speaker 2:Yeah. And also, there's just like the there's just it's so easy to throw I mean, in the same way that people are throwing Enron at at NVIDIA. Like, it's so easy to throw Theranos at any biotech company that's not, you know, that's accused of anything. And and also biotech, it's like it's it's pretty hard to understand the underlying science. It's not it's not a it's not as popular as, okay, like, does the website work?
Speaker 2:Does the business make money? You know? What's the cash flow like? It's way more complicated, and so Yeah. It it it does attract even more attention.
Speaker 2:So one of the other companies in the space is Heracyte, and Astral Codex 10 continues here. They enter the space with the most impressive disease risk scores yet, an IQ predictor worth six to nine extra points and a series of challenges to competitors whom they call out for insufficient scientific rigor. Their most scathing attack is on Nucleus itself accusing its predictions of being mis misleading and unreliable. Let's start with the science and then move on to the companies to see if we can litigate their dispute. In all theory in, in theory, all of this should work.
Speaker 2:Polygenic embryos polygenic embryo screening is a natural extension of two well validated technologies, genetic testing of embryos and polygenic prediction of traits in adults. So genetic screening of embryos has been done for decades, usually to detect chromosomal abnormalities like Down syndrome or simple gene editing disorders like cystic fibrosis. It's challenging. You need to we've talked about this before. You need to take a very small number of cells, often only five to 10, from a tiny proto placenta that may not have many cells to spare and extract a readable amount of genetic material from this limited sample, but there are known solutions that mostly work.
Speaker 2:And so the companies that we're talking about today aren't necessarily doing, like, the fundamental lab equipment development, building the machine, figuring out how to sequence data from the first it's more about the analysis that happens on top of the results.
Speaker 1:And the recommendations
Speaker 2:And the recommendations.
Speaker 1:Probably which which I would say is the most controversial part of this.
Speaker 2:I don't I don't know that any of them are recommending, hey. We think you should take you you we think you should pick this baby. They're more just saying, like, we think that according to the data, this baby might be tolerable a
Speaker 1:response. Risk fact. If you're giving if you're
Speaker 2:Yeah. But that's not a recommendation. Like, if I tell you this car is 700 horsepower and does zero to 60 in two seconds, and this one does 800 horsepower and does zero to 60 in two point four seconds, this one's faster in straight line, this one's faster on the curves, and then, like, you pick. Like, I didn't make a recommendation. I just told you the stats.
Speaker 2:Right?
Speaker 1:Yeah. But but from when you look at the these companies from a from what they're marketing
Speaker 2:Yeah.
Speaker 1:To consumers of of what of why you should care about the service Sure. And then the way that they deliver the information Yeah. If they're advertising, we can effectively advertising. We can help you have a smarter, healthier baby. And then they're saying like, hey, we think this direction is gonna get you a higher IQ.
Speaker 1:How is that I don't think
Speaker 2:it's a recommendation.
Speaker 1:It's not an explicit recommendation. Yeah. But I think people are trusting the service to try to get them what was marketed to them.
Speaker 2:Yeah. People want the data, and they want the data to be accurate because they're going to make a decision based on that. But, I mean, here, Scott Alexander actually gets into some of the, some of the complexity of, of the actual trade offs because there are so, most traits are polygenic, requiring information about thousands or tens of thousands genes to predict. These are too complicated to understand fully at current levels of technology, but some studies have chipped away at the problem and gotten to a partial understanding. Often, this looks like being able to predict a few percent of the variance in the trait to determine whether someone's genetic risk is slightly higher or lower than, average.
Speaker 2:And, so some people might genuinely want to select on a single condition. For example, people with a strong family history of schizophrenia might wanna minimize their chance of their children getting the disease. For these people, reducing schizophrenia risk by fifty eight percent while keeping everything else constant sounds pretty good. Everyone else probably wants a genetically healthy generically healthy embryo with low risk of all conditions. Exactly how this works depends on the customer's own value.
Speaker 2:Would they prefer an embryo with lower cancer risk to one that will have fewer heart attacks? Like, that's a trade off that you have to pick. And the exact benefits will depend on how parents make that decision. Genomic prediction and HEROCITE try to help by providing semi objective measures of which embryo is overall healthiest according to different conditions, effects on longevity, and patient rated quality of life for genomic, prediction. That's the embryo health score.
Speaker 2:This is, you know, that that's close to a recommendation. I think you're you're you're getting close. Yeah.
Speaker 1:And and Nucleus', subway campaign is have a healthier baby.
Speaker 2:Yeah. Yeah. It's it's the the the marketing claims are are a big, big piece of this. I think I think the scientific claims are are potentially, just as important, but, they're they're it's both. They're they're both understanding where the science actually is, both broadly and then also within the companies and then how it's marketed.
Speaker 2:Like, all of that is important, to to get, like, a complete picture of what's going on here. So, for Heracyte, it's a polygenic longevity index. They don't give exact risk reduction numbers for each disease, saving that saying that it depends too much on a couple specific family history, but say that most people gain one to four years of healthy life. When I test, it on a set of 20 embryos, the healthiest gets an extra one point six six years. And so how much would you pay to give your children an extra one to four years of healthy life?
Speaker 2:This is no longer a healthy an hypothetical question. Here are the costs. Genomic prediction is around $3,250. Orchid is around $12,500. Nucleus is around $9,249, and hairycite, $53,250.
Speaker 2:That is expensive compared to the rest, five times the price. Is it worth it? Well, if you're already doing IVF, the claimed risk reductions are accurate. You value your kid's health as much as your own. You have low time discount rate.
Speaker 2:You're well off enough that these aren't extraordinary sums of money to you, you're okay using expected utility calculations where a 50% chance of preventing x is half as good as fully preventing x, then I'll go out on a limb and say, yeah. It's obviously it's worth it. Consider genomic prediction, which costs $3,500 for five embryos and claims to lower absolute risk of type two diabetes by twelve percent. That implies that not getting type two diabetes is worth $27,000. Ask anyone dealing with regular insulin insulin injections, let alone limb amputations, whether it would be worth $27,000 to wave a magic wand and not have type two diabetes, it's not a hard question.
Speaker 2:And that's just one of a dozen conditions you can lower the risk for. Other ones, like not getting breast cancer, might be so valuable that it's hard to even attach numbers. So what about IQ? Six extra IQ points, which is Heracyte's estimate with five embryos, is about a quarter of the gap between the average person and the average Ivy League student. The benefits of of intelligence are hard to quantify, but it's been shown to have probably causal positive effects on income, mortality, and achievement.
Speaker 2:Probably the income effects alone make up for the cost of the intervention, again, assuming total parent child altruism and a low discount rate. So if we accept all of these claims and assumptions, the choice seems obvious. It it probably even accounts it's probably even obvious for governments to pay for all citizens to get these given how much they'd save on health care costs, says Scott Alexander. But in practice, it's complicated. Critics have raised both scientific and ethical objections to polygenic embryo screening.
Speaker 2:Most significantly, it's been condemned by various bodies, including the Society for Psychiatric Genetics, the European Society of Human Genetics, and the Behavioral Genetics Society. These their statements are not good. They tend towards vague language about how people are more than just their genes or how no genetic test can be perfect or how embryo screening is not exactly the same thing as some other form of screening, which has a longer history and more proponents. Although, quote, although in general higher scores mean you are more likely to have a condition, many healthy people will have higher scores. Other might other peoples others might develop the condition with even with a low score, says the Society for Psychiatric Genetics, as if they have just blown the lid off of some dastardly conspiracy.
Speaker 2:Screening embryos for psychiatric conditions may increase stigma surrounding those diseases. They continue an objection which, taken seriously, could be used to ban every form of medical treatment because if you take care of something, you remove them from the population that might increase the stigma, but we should still treat these. So he says, we will mostly ignore these people and try to imagine the implications of, the objections that mildly competent critics might raise, some of which will co coincidentally overlap with the content of the non hypothetical statements. So the big question he wants to answer is scientific objection the scientific objection around efficacy. Does this are we sure where this works at all?
Speaker 2:Are we sure this works? So a typical polygenic score is created by collecting thousands or millions of adult genomes, then matching genetic information with surveys about who has the trait slash condition of interest. Reputable studies then test these scores on holdout samples, adults who were not used to make the score, to see if they still accurately predict who has the trait condition. Polygenic embryo selection depends on an assumption that the scores which work in these kinds of retrospective tests will also work on prospectively on embryos. This assumption hasn't been formally proven in studies, which would require years or decades to conduct, but seems commonsensical.
Speaker 2:The strongest challenge to the application of polygenic scores for embryo selection comes from a recent body of research showing that most scores combine causal genetic effects with population stratification, and therefore can be expected to lose much of their predictive power when comparing two members of the same family. There is an increasing agreement in the field that unless scores are validated within families, headline results like decreases risk of x by y percent will be large overestimates. When I talked to company representatives, they all said that they took accuracy extremely seriously and had various white papers and journal articles where anyone could double click could double check on their methodology. But I attended an industry conference a few months ago, and the gossip level was comparable to a high school cafeteria.
Speaker 1:Minus the sex rumors most of the attendees were having their kids via IVF.
Speaker 2:Everyone had some story about someone being careless or fudging their numbers. Some of the conflicts broke out into the open on Wednesday when Heracite left Stealth and published a white paper and associated blog post. They criticized genomic prediction for reporting between family rather than within family results and ORCID for smuggling a term for age into their Alzheimer's predictor. Unsurprisingly, this makes it work better. What, we'll get to their accusations against Nucleus below.
Speaker 2:Note that this was recent enough that competitors haven't had time to air, their own criticisms of Harricite if this happens. And I'll try and keep you updated.
Speaker 1:And to be clear, this article is from around five months ago. Yes. And since that time, Nucleus has been accused of plagiarizing the the paper
Speaker 2:From Harasite.
Speaker 1:Discussed Right.
Speaker 2:From Harasite. From Harasite. Yeah. And then also accused of stealing IP from genomic prediction.
Speaker 1:So there's, again, bunch of different accusations. We'll let Yeah. Keyon.
Speaker 2:So yeah. Yeah. I mean, the the goal here is is to just give an opportunity for, you know, Cremieux and Kian to, to answer some questions, try and contextualize it, try and make their case to a broader audience. I they're you know, I've I've read through as much as I could I I can, but without actually getting in the lab, and rolling up my sleeves. I don't think I could come to a firm conclusion here, but I can certainly talk to them on this show and hopefully get some more information that the community can do with what they will.
Speaker 2:So Scott Alexander concludes this section talking about his strongest opinion of the scientific criticism. He says, authorities on all sides have cited Alex Young as an authority on how polygenic scores can be confounding or misleading. Last week, Alex Young revealed that he had been working with Haracyte while it was in stealth mode and endorses their research. Three, LOL. Probably that means Haracyte's products are okay.
Speaker 2:That serves as proof of concept that this technology can work and means other companies' claims are at least plausible. So lots of back, back and forth, and, we will be joined by with, by Cremio in just a few minutes. I actually need to, message him and make sure that he has the information. Is there anything else that you think would be worthwhile to, discuss before we hop on? Let's
Speaker 1:Yeah. And I can I can just go through? I mean, the original accusations came from an account called Sichuan Mala. Sichuan Mala. Yes.
Speaker 1:Who wrote an extremely lengthy blog post on on a bunch of the issues that they felt they had found with with Nucleus. Nucleus ended up firing back and saying that Sichuan Mala was or sort of implying that Sichuan Mala was funded by a competitor or competitive service as well as making those allegations with Cremio.
Speaker 2:Yes.
Speaker 1:They go into issues around potentially fictitious customer reviews, which we'll ask Kian about, AI generated blog posts, accusations of intellectual property theft, saying that the Nucleus origin white paper is plagiarized, saying it has a bunch of errors. Nucleus has responded already to Yes. A lot of this stuff.
Speaker 2:Well, our first guest of the show is here. Let me tell you about Linear, meet the system for modern software development, purpose built tool for planning and building products. We will bring in Kremio from the Restream waiting room into the TVP and UltraDome and have him set the table for us. Kremieux, how are you doing? Welcome to the stream.
Speaker 6:How are doing? Glad to be here guys.
Speaker 2:Thanks so much.
Speaker 1:Can hear me? Good as always. Looking good. Do you do you want
Speaker 6:By the way, I can go FaceTalks if you want.
Speaker 2:Let's do it. Let's do it. We can we we can show his actual video this time, which is great. We've had him welcome to the show.
Speaker 1:Hey. Hey.
Speaker 2:Good to see you.
Speaker 1:How you doing?
Speaker 2:What what actually kicked this off for you? Do you know Sichuan Mala separately, independently? Did you know that this was coming? Set the table for us. Like, why did Nucleus come to the top of your mind?
Speaker 6:So can I actually go back to Hereticon
Speaker 2:Please?
Speaker 6:With this?
Speaker 2:Yeah.
Speaker 6:Alright. So for about a year, we've told Nucleus about issues with their products. It's can I just actually give a big like, I I can model on this for a minute? I can tell you a lot of the details if you wanna go into it.
Speaker 4:Go right ahead. Okay.
Speaker 6:So one of the early things that really peeved a lot of us who are aware of how this tech works, is that Nucleus claimed to provide parents with information about rare variants based on microarray files. Their website's wording is incredibly ambiguous.
Speaker 2:Mhmm. So the excuse when I
Speaker 6:raised this to Kian in person was that they were referring to imputing a child's embryo or a child or an embryo's microarray based data with parental whole genome data. Well, this is not sufficient for rare variants like they claim it is, and it only works out very well, well in narrow, well behaved cases. It's not a clean substitute for sequencing an embryo or child. Mhmm. The rare variant information they can offer is limited and their claim is highly misleading because it sounds like they can achieve coverage of de novo rare variants and ultra rare variants reliably for children and embryos.
Speaker 6:But they cannot do this because of, like, crossover that happens during recombination inside the haplotype blocks you're using to do the imputations and because of mutations. They can't they can't even get high confidence coverage of rare variants more generally, which is what their big claim is about, in specific wording, with the imputation based methods they claim to be using. So everything they say has a huge error bar on it, and it's they shouldn't be advertising it, basically. It's something incredibly misleading. And it's a good idea So
Speaker 2:so so just to, like, actually zoom out, like, what do you think they are capable of doing?
Speaker 6:I think they are capable of microarray sequencing. I think they're capable
Speaker 2:of I mean I mean I mean in terms that you could advertise to a parent. Like, you could like like like, if Keon went to a prospective parent, the parent says, I'm doing IVF.
Speaker 1:What Yeah. Is this category even ready for large scale out of home advertising? Do you think do you think
Speaker 6:It it absolutely is. The issue is that Nucleus should not be doing it because Nucleus has produced scores that are invalid. They're incredibly invalid. Like for example, they used an ADHD score that can click included 12 single nucleotide polymorphisms. They claimed that explained 4% of the variants in ADHD, which means it's a pretty good predictor and you can use it to get some improvements in the margins.
Speaker 6:But 12 snips means that there's just no way. They could explain less than one percent of the variants and the best current ADHD polygenic score uses more than a million snips and explains about one percent of the variants. So they just basically lied. They made up these numbers. And Harriside had to go through and show that, oh, actually, a bunch of their numbers are made up.
Speaker 2:Yeah. But, I mean, how do you know for sure that they're I mean, like, that that claim, you know, the state of the art was was a million for 1%. Now it's 12. Nucleus is claiming 12 for 4%. That seems like a huge exponential, you know, growth in efficacy of that particular test.
Speaker 2:But, just an exponential progress, it is not necessarily evidence of, malpheasance. Right?
Speaker 6:This isn't progress. They've they've never been able to show that they can use 12 SNPs, and no one can. It's impossible. They don't explain this much variance. It's it's literally physically impossible.
Speaker 6:There's no it's not possible in any way. They should never have claimed it. They should never provided score reports to people based on it and they did. They provided customers with score reports that have to be fake. Not fake per se, but they have to be incorrect.
Speaker 6:They have to be wrong. There's no way they could stand up to scrutiny. What I'm saying is that after they made this 12 SNPs to 4% variance claim, people have looked and they've shown the latest ADHD polygenic score, which is more recent than what they've claimed to have on offer, uses more than a million SNPs and explains about 1% of the variance. It's just that's the state of the art. They are claiming to have better than the state of the art, with completely implausible parameters.
Speaker 6:It is impossible.
Speaker 2:Okay. So so so back to the original question, like, do you think they actually could offer, even if they say, hey. You know what? We're not we're not necessarily state of the art. We're partnering with a lot of different labs.
Speaker 2:We're standing on the shoulders of giants. We're using, the tools that are available. What is a reasonable claim that if they made it, you would be like, yeah. That sounds that sounds reasonable.
Speaker 6:A reasonable claim from Nucleus is that they are pulling polygenic scores from the polygenic score catalog, a publicly available resource that lists a bunch of different polygenic scores
Speaker 4:Yep.
Speaker 6:From different genome wide association studies. That would be reasonable. Yeah. But that is not why would you go with them then? They have nothing unique to offer.
Speaker 6:What they have offered that seems to be unique are claims that don't hold up to scrutiny or which are clearly plagiarized from one of their competitors.
Speaker 2:Yeah. Well, the I mean, there are plenty of there are plenty of services that are, like, you know, in you know, effectively wrappers around Quest Labs. And, you know, I get a better UI, and it tells me that my cholesterol is in the range. And, yeah, I know it's just looking up the range from the the data, but it has a nice UI and a reasonable billing system or whatever. And people pay for that, and they get you know, they make decisions about their diet based on that.
Speaker 2:And I don't think that there's anything necessarily wrong about Right. Providing something that's a commodity or not a scientific breakthrough as long as you're up to as long as you're honest about what you're doing and you're not inflating the results.
Speaker 6:Yeah. The problem is that they're inflating the results.
Speaker 2:Okay.
Speaker 6:The problem is that they are effectively making up the results. They have act they've in their latest report, they have claimed to basically match heresy. Not not claimed to directly. They've copied their very unique citations which no one else has made. Mhmm.
Speaker 6:They've copied their method and Yes. Copying their method is incredibly weird. You mentioned there that Scott Alexander noted that Alex Young is Yeah. Like seen as a big authority in this space. And it's true.
Speaker 6:Alex is seen as like the go to guy. Yep. If you wanna learn about family based sampling, trio imputation, if you wanna learn about within family validations or imputations or quality control, you ask Alex. Mhmm. That is the thing to do.
Speaker 6:And they apparently copied Alex Young's quality control pipeline. And it's very unique. So doing this is unusual. It's unheard of. It's not likely to have actually been done.
Speaker 6:It is like saying that you woke up one day and here's my morning routine. I woke up and today I was John Kukan. And I brushed my teeth exactly three times each time around and I went and prayed to my household god. I did like all sorts of things and it's just it's incredibly specific in a way that is very unlikely to be real. They've very likely just kind of mimicked exactly what they said.
Speaker 6:And they said they did it on additional data, but the results came up very close.
Speaker 2:Yeah.
Speaker 6:Yeah. Which is not likely. We have strong theoretical genetic reasons to expect that if they had this additional data that Herocyte did not, the results would have actually looked different. So they have all these signals that they didn't do the analysis they said they did.
Speaker 7:Mhmm.
Speaker 6:And lots of indications that they plagiarized. And when Sichuan Mala called them out, they responded. The response they generated was amateurish. It was kind of embarrassing because they admitted simultaneously to denying they did the plagiarism. They admitted to doing the plagiarism.
Speaker 6:They copy they admitted they copied things directly from Herrisite. They admitted they used resources that are unusual to use, and they effectively got the data from them. And they did nothing that was really unique.
Speaker 2:Okay.
Speaker 1:But they did a Oh.
Speaker 2:So so so copying might be, you know, looked down upon. In tech, people copy stuff all the time. There's you know, stories was copied into Instagram from from, Snapchat. Different different machine learning architectures are being copied constantly. Some stuff can be patented.
Speaker 2:Some stuff is can be trade secrets. Are we looking at anything that's that's that goes beyond just like, yeah. It's kinda bad form to copy, or or is this something that's actually, like, a a problem beyond that? Yeah. Would you would
Speaker 1:you be less angry if they copied it perfectly instead of, like, sort of copied it directionally?
Speaker 6:They copied a lot of it perfectly. And this leads to weird results because they should not have done that given the cohorts they used. They used separate data for their validations, so the results should have been different. They copied details that made it apparent that they were not using the data they claimed to or they were just budging the results. It has to be one or the other.
Speaker 6:There's no way they could have gotten the results they did with the data they did and the copying they did. The copying tells us that they lied about something somewhere along the way. There is something fishy here. And we don't know what the exact error is. We just know they have to have made an error because there's no way that the additional data they had access to was identical to all the data their competitors used.
Speaker 6:Mhmm. What would have delivered different results.
Speaker 1:Yeah. So so I wanted to ask they released open weight models, the origin models. Part of part of their part of their
Speaker 2:They did.
Speaker 1:Part of well, part of their pushback against Sichuan Mala's critique is that anybody can just download the models and play around with them. Have you have you downloaded them? Have you
Speaker 6:So you have to ask for access, and they do not give out access. We have multiple people go in and try and ask for access, they've not received it at all. And one person who asked for more information was told, stop contacting us. So, no, they are not open at all. They're open in the sense that OpenAI is open.
Speaker 6:They're not very open.
Speaker 1:Okay. Got
Speaker 2:it. Shifting gears to the marketing claims. What what, stuck out to you there is, is particularly in need of addressing?
Speaker 6:They very much need to address the fact that they seem to have fake reviews. So when they started Nucleus Embryo, they launched it in June. They weren't offering any sort of embryo screening services beforehand. And if they were, then it would have been how they would have had they have to specify what lab they use for all this stuff. It's there's a lot of details that should go into this that they can't actually specify because they didn't do that.
Speaker 6:So they claim to have had customers that have already been served by this. Well, as everybody knows, it takes about nine months to serve a customer in this at minimum. Yes. And, it is not baby
Speaker 2:in one month. It takes Yes.
Speaker 6:So I'd love to see these three month old babies that came out perfectly and were made their customers so happy. But I don't think they exist. I think they're not real. So why do they have these reviews? I don't know.
Speaker 6:And the reviews are also they have a lot of fake elements. There are some that are clearly fake. So they use stock images in these reviews to to show
Speaker 1:the customers colorify. Which to be clear, you can imagine a scenario where they use stock imagery and fake names and they put an asterisk and say, due to HIPAA compliance reasons, we're not just publicly displaying, you know, the names of any of our clients. But
Speaker 6:There's there's no issue revealing this stuff, and other companies do actually reveal customers. So Orchid has revealed real customers. I've been introduced. I've met, Harasite customers.
Speaker 2:Oh, yeah. Didn't Jason Carmen do a whole video with Noor in the first, in the first, Orchid baby? And this has been, like, basically making a documentary about that person's journey. Like, there's no, like Yeah. And and I feel like I see in drug commercials all the time, it'll be like, this is a real customer who loves this hair loss meds.
Speaker 2:And they're like, yeah. It looks great.
Speaker 1:Yeah. But And, like, there's regulation around harder to get it it's probably much harder to get somebody to opt into that than just opt in to generally providing Sure. A
Speaker 2:clear, clearly Yeah.
Speaker 1:Yeah. Yeah.
Speaker 2:I guess Is is that is that legit, you think?
Speaker 6:No. They still could not have had the babies in time. It doesn't fit with the time. The chronology doesn't work here. These customer reviews are not really physically possible, and I'd like to see an explanation from them because it doesn't make any real sense to me.
Speaker 6:Mhmm. They could be, I don't know, making some sort of representative review that they've maybe hedged in some fine print on some page somewhere, but I haven't seen it, and their entire site has been archived now. So if that page exists, they'll have to show
Speaker 2:it to
Speaker 6:us on the archive.
Speaker 2:One thing Jordi and I were debating was, this this big question of, like, is Nucleus making a recommendation or not? I don't know if this is relevant, but I would love your take on this. This idea of, like, you know, I see a I see an ad that just says, like, height is an 80%, DNA based or genetically heritable. And then you go into the dashboard, and it just says, here's the predicted height, and here's the predicted, you know, IQ. And then you make the decision.
Speaker 2:And it's not necessarily they're recommending one or the other. It's more of a diagnostic, and you can do that information what you want. Does that does that absolve them of some sort of responsibility there?
Speaker 6:No. It doesn't. So if you still provide wildly inaccurate scores, then, it doesn't matter what you're recommending. You are effectively just recommending something that doesn't matter. I mean, you are giving them incorrect recommendations.
Speaker 6:You have to give some range of uncertainty, within the best of your ability. You have to give them something that is to the greatest extent knowable, reliable. Mhmm. And they can't have done that. They've provided scores that they know they must know are incorrect.
Speaker 6:Mhmm. You can't explain 4% of the variance with 12 snips. It's not really feasible. It's there's no possibility of it really. There's also no possibility of getting high confidence coverage on rare variants to makes from the imputation methods they described.
Speaker 2:Mhmm.
Speaker 6:So they can't make parents certain about this stuff. Like they're saying lots of things that are that would require them to basically advance the science twenty years.
Speaker 2:Yeah.
Speaker 6:They would have to be leaders in innovations here.
Speaker 4:Yeah.
Speaker 6:And I just kind of doubt it. The people who are actually leading on the innovations here are Heracite. Orchid is doing so as well. They're doing a lot of Orchids whole genome sequencing of embryos is the only one in the industry available to do this. And Heracite's innovation is that they've made this stuff low cost for what they have admitted is a reduction in quality if you get PGT A based imputation.
Speaker 6:Now, another thing I do want to mention though is that, Nucleus might we're and still look I'm still looking into this. I'm collecting some patient reports. I found one from my friend Dylan. She got a report from Nucleus and she got one from Inviting. It was a whole genome sequencing thing done.
Speaker 6:And Nucleus and I did see the report. Nucleus said she had a a a Mendelian disorder, you know, monogenic disorder caused by one gene. And Invitae said she didn't have it. Okay. This is weird.
Speaker 6:So what's the inconsistency? We don't really know. Nucleus recently changed this result. Now per the law, you have to notify your customers if you change their sequencing results.
Speaker 2:Mhmm.
Speaker 6:This is a clear regulation. The CMS regulates this and there are that is a potentially major issue that they might be out of compliance with. And I understand that startups are often out of compliance and a lot of them fake it till they make it in terms of following the letter of the law. But I'm of the opinion that they really shouldn't, especially because this is serious tech with major implications for people, their families, and I mean, all future generations of their families. Mhmm.
Speaker 6:This is as I think Jordy called it bloodline optimization. And we have these rules in place for a reason.
Speaker 2:Yeah. You
Speaker 6:need to show you're abiding by them.
Speaker 5:But they Yeah.
Speaker 1:How much how much do the other players in in the category how much are they worried about Nucleus just kind of setting back the entire So
Speaker 6:I have gotten, it's on video. And because Kian tweeted about being in it, I'm allowed to say that, we were at a private conference, and I did lead a panel on this topic where Kian was one of the panelists and the heads of some other embryo selection companies were also on the panel as well. And, I will say that everyone was worried. Everyone was worried about one of the major missteps that actually has already been addressed by another one of the companies and the series of major missteps made by Nucleus that they have failed to address. Mhmm.
Speaker 6:I warned Kian about this stuff many months ago. I've warned him about problems for more than a year now, and he has simply not addressed them. They have they're still there on the website. You can go find them. I've archived these pages a few times, to see it.
Speaker 6:Are they getting to them? Are they getting to them? The answer is no. They are still making claims that are either not possible, not possible with the current tech, might be possible in twenty years, or just don't seem consistent with the evidence that they provided to their customers.
Speaker 2:Okay. Last question, and then we're gonna hop on with Kian. I'm a big believer in redemption arcs. You're obviously unhappy with, Nucleus' behavior in the, in the industry. What does redemption look like?
Speaker 2:What would Kian have to do or show you to, get back in the good graces of the industry in in your good graces?
Speaker 6:So the whole industry knows that Keon has been a problem for a while, and we actually, a lot of people have tried to give him a redemption arc already. Mhmm. They have tried to come to him. They have given him clear advice on what he needs to do. They have told him you need to stop making x y zed different claims.
Speaker 6:They have told him you need to offer scores that are vetted. You need to be open about your vetting. You need to be open about your sources. You need to qualify everything like the other companies do, but you haven't. He has been told this for a long time.
Speaker 6:I sent you some pictures earlier today. You can see the panel we're on, where clearly, like, this has been a thing that's come up a lot and we wanted to give them the arc already, but it came to this. It came to a person going online, a blogger deciding, hey, I'm gonna look into this after reading the various blog posts and saying, So to make up for it, I think they would need to be incredibly open and they need to apologize and they need to admit to what they did wrong And they need to say that they were out of compliance with CLIA rules and regulations and they need to say, hey, we might have missteps here or there. We didn't know we were doing this or whatever. Like, whatever it takes to be accurate, document everything.
Speaker 6:Mhmm. Tell us everything you've done. Tell us all the missteps. Don't exaggerate. Do not lie.
Speaker 6:Just be upfront with everyone and submit yourself to regulation. Not in the sense that you have to go and tell the regulator you want to like implement whatever new rules and regs, but submit yourself to openness. Be really open. Stop this whole thing about not telling us your methods, which they've done and Citroen Mala has documented that in the latest blog post. And give us your data.
Speaker 6:Give your data out. Stop provide like saying it's gonna be available upon request. Yeah. It doesn't matter if your competitors have it. Offer them offer better pricing or something.
Speaker 6:Compete on some other margin because we shouldn't have to compete on trusting you. I'm gonna say we, I'm not talking I don't have a company in this space, but everyone should be trusted. All the companies in this space need to shape up a little bit, and they need to be a little more open. And Kian needs to do that the most.
Speaker 2:Thank you for coming on the show and breaking it down for us. We appreciate you taking the time Yeah. And walking through all of that. Have a great rest of your day. Who knows?
Speaker 2:You might be on the show very soon Definitely. As this debate continues. So we really appreciate you taking the time.
Speaker 1:Thank you.
Speaker 2:Talk soon.
Speaker 6:Have a good one, guys. Bye.
Speaker 2:Before we bring you on Kian, let me tell you about fall, build and deploy AI video and image models trusted by millions to power generative media at scale. And we have Kian from Nucleus in the Restream waiting room. Let's bring him in to the TV pin ultra jump. Kion. Hi.
Speaker 2:Good to see you. Wish it was less dramatic circumstances, but, you know, it makes for good TV. And, we're happy that you're here, and we can chat about this. And, I mean, I'd love to just give you the floor. I'm sure you saw, you know, some of the early segments.
Speaker 2:Where do you think it's important to start? Where do you think it's most important to set the record straight, as a first point? And then I'm sure we'll have a bunch of questions.
Speaker 7:Well, didn't see what Kremu said. I was busy helping a patient. But I think the the key thing to remember is that Cremu and I, we are definitely aligned on doing great science.
Speaker 2:Mhmm.
Speaker 7:At the end of day, that's what we wanna do. We wanna serve the patient. We wanna do amazing science.
Speaker 1:Mhmm.
Speaker 7:I think what we're not aligned on is Cremu basically, for several months, has not disclosed that he's been affiliated with a competitor. And, you know, that wouldn't be so much of a problem unless they're basically concerting together. And so that's on the side of things. Well, honestly, that's, like, the less important thing to me. Yes.
Speaker 2:I agree. I think that's less important. I've I've so I I've I've seen him post positively about your competitors. I don't I I've not seen any proof that he's actually being paid or has equity in that competitor, but to me, it almost doesn't matter. It could like, every single post from him and Sichuan Mala could literally be from Nora and Orchid or someone who one of your competitors.
Speaker 2:You still need to address it. Right?
Speaker 7:A 100%. K.
Speaker 2:Cool.
Speaker 7:And so first and foremost, I'm gonna say that our science is completely public, and it's been completely public. So one thing that is, like, really important to say is that Yes. Anyone and by the way, we've, this point, have shared our models with over 15 different entities, which includes, by the way, people affiliated with our competitors, several of them.
Speaker 1:That means anything else we can get. Just to be clear. Yeah. I mean, Kermu said that a number of people that he's aware of have requested access to the models and not been given access and been told to stop reaching out. And so I do think I don't know if he
Speaker 7:was who's utterly inaccurate and false. There is not one person who has filled in the Nucleus origin type form, which is a type form, to fill in a type form that has not gotten access to our model weights.
Speaker 2:Okay.
Speaker 7:And by the way, that includes people affiliated with the competitor.
Speaker 2:Okay.
Speaker 7:And so I think what's really important here is
Speaker 2:Yeah.
Speaker 4:Yeah.
Speaker 7:The science is public. Mhmm. The message to the community is go and test it.
Speaker 8:Mhmm.
Speaker 7:In fact, our science is public. The competitor's is not. So what I would propose is they should make their science public, and let's have a third party independently evaluate the rigor, the quality of the science, and let's do it for everyone to see. Instead of he said, she said, they tit for the tat, you know, put the science out there.
Speaker 2:Yeah.
Speaker 7:Have a third party independently evaluate them. That is my message to our competitor. We are happy to stand behind our science, and we know that it's the highest quality science that can exist today. But by the way, Josh, that's not even the point either.
Speaker 2:Please.
Speaker 7:You know what the point actually is?
Speaker 2:What is?
Speaker 7:The point is about the patient. Mhmm. It's about having the empathy with the patient so they can know when they do embryonic selection Mhmm. They can feel comfortable and confident in the results. Yeah.
Speaker 7:And this Twitter back and forth, this tit for tat Yep. This oh, this person's race changed on the Nucleus landing page, it's ridiculous.
Speaker 2:Yeah. Yeah.
Speaker 7:It's really ridiculous. Well well And so that's my message.
Speaker 2:Speaking of the the the the patients on the landing pages, what
Speaker 6:about
Speaker 2:the what about the the chronology here? This idea that Yeah.
Speaker 4:The time.
Speaker 2:That that that there's a review of a baby with three months old, takes nine months to work with a baby, should have happened a year ago. Was the service available a year ago? How do you square that particular allegation that the the review the timing of the review just doesn't line up with what must have happened in the real world had they used your service?
Speaker 7:So there were several claims about the reviews. Yeah. Let me address each.
Speaker 2:Please.
Speaker 7:First and foremost, obviously, as a HIPAA covered entity, we cannot disclose patient name much less their picture.
Speaker 8:Mhmm.
Speaker 7:Okay? If a patient chooses to, they can publicly endorse the company, they can put their name in their picture. Sure. Otherwise, a patient can submit an anonymous anonymous review, and then we'll put that according to the landing page.
Speaker 2:Okay.
Speaker 7:And so maybe perhaps the people on the Twitter timeline, maybe they never run a company that involves any protections to the patients. Maybe they don't know about this. Maybe in, like, the broader tech community, it's, like, unfamiliar. If you run a software company, it wouldn't make sense necessarily. Just not disclose the patient name.
Speaker 7:And I'm gonna say too, John. This is really important.
Speaker 2:Yeah. Do you think you have to disclose the fact that you're using an AI generated image? Is that best practice, or is that legally required?
Speaker 7:You know, what I think we should do, though, is now that the community gave us this feedback is Yeah. We should update and make it more clear. Hey. This is clearly not a real picture. Sure.
Speaker 4:And this
Speaker 7:is both not a real name. That's reasonable.
Speaker 2:Yeah. Yeah.
Speaker 7:Okay?
Speaker 2:Yeah.
Speaker 7:Now fraud. This. That. Guys, really? Come on.
Speaker 7:Okay. We'll update it. We'll make sure that the picture and also the names are more clear. Yeah. But, again, we're a HIPAA covered entity.
Speaker 7:You can imagine when you launch an Embryo product specifically, people do not want their name to be affiliated with it. I mean, you have a nonaccounts that don't want their names affiliated with these things. Imagine a patient actually undergo underwent Nucleus' services. Yeah. Yeah.
Speaker 7:So now regarding the timeline thing, that's the second thing you mentioned. I wanna directly address that as well. Obviously, a company like Nucleus can start providing services to patients earlier than we publicly launch a product. Mhmm. Moreover, you would imagine the services that you provide to patients would be the ones that actually the the beta service that you provide to patients would be the ones that you'd have reviews for, obviously, they do the services prior to the company actually launching the services publicly.
Speaker 4:Mhmm.
Speaker 7:So that's it. That's the answer.
Speaker 2:So so you were you were using the service before maybe a year ago or something, then you announced the service, and that's why the the the
Speaker 7:We we have a question to do embryo analyses. Yeah. Probably three years ago.
Speaker 2:Yeah.
Speaker 7:I would wager that that, you know, that actually was probably one of the first times before any of these companies
Speaker 2:Yep.
Speaker 7:To actually provide a sort of this sort of services. So we didn't think about this for a long, long time.
Speaker 2:Yeah. Of course. Yeah. It it makes sense. It's a very logical place to go.
Speaker 2:It's also a very competitive, industry. There's a bunch of reasons why you'd wanna play in that space. What about the the del the delta or the perceived gap between the marketing claims? What's on the billboard? What's in the New York subway.
Speaker 2:I'm seeing 50% IQ, 80% height. They feel like bold claims. What's actually possible? What what can customers actually get from Nucleus today? What could they get a year ago when you were beta testing the product?
Speaker 2:What what I I wanna I wanna interrogate
Speaker 6:the question.
Speaker 2:The the gap there.
Speaker 7:So to be clear, there is no gap.
Speaker 2:Great.
Speaker 7:Have a healthier baby. Have a taller baby. Mhmm. Have a smarter baby. Mhmm.
Speaker 7:IQ is 50% genetic. Mhmm. Height is 80% genetic. These are just facts of the matter. Yeah.
Speaker 7:The the the the latter two are heritability estimates. They are what they are. Yeah. The former two are basically describing what you can do with Nucleus.
Speaker 1:Yeah.
Speaker 7:What what I think is interesting here, there's actually a broader commentary. Mhmm. Nucleus is bringing the science mainstream. We are taking it out of the little echelons of the rationalist community, the little echelons of the the the the the scholars going back and forth at it, out of the Twitter out of way, and we're bringing it to the actual people who will benefit and use these services. Mhmm.
Speaker 7:I cannot tell you when you actually talk to a patient, not somebody on tech Twitter. When you talk to a patient, they have no idea this technology exists.
Speaker 2:Yeah.
Speaker 7:And the first time they're discovering it is when they go and they actually see the campaign in the subway.
Speaker 2:Yep.
Speaker 7:And now I think it's personally good for the entire industry, right, where you actually bring broader awareness. It lifts everybody, us, our competitors, and makes this actually more and more into a space. It's very early. My my advice to our competitors is focus on serving your patients. Mhmm.
Speaker 7:Because at the end of the day, the market's huge, and this market is extremely in its infancy.
Speaker 1:Mhmm. And I and I and I think they would push back and say the industry can't afford to be sloppy. And I think that the
Speaker 7:I agree.
Speaker 1:The I think it's a fair allegation that some of the ways that Nucleus materials have been presented have been sloppy. Do you I guess one question I have is
Speaker 7:Gordie, what are you specifically talking about? What has been sloppy?
Speaker 1:Specifically, the like, the reviews the reviews are sloppy. I I I totally understand.
Speaker 2:Specifically using using an AI image or using a stock image with Not a clear that that this is anonymized because of HIPAA. If it just said 55. If it if it's set at the bottom and there are little asterisks that said anonymized because of HIPAA, I think everyone would be like, oh, yeah. That makes sense. Like, they made a choice.
Speaker 2:And I think that's, like, the first thing that I would count as, like, sloppy.
Speaker 7:That's that's fair.
Speaker 5:That's fair. Okay.
Speaker 7:And we're gonna update that. Do you do you think that, you know, that's proportional to the temperature on Twitter?
Speaker 1:Oh, I think I think this is Twitter's politically charged
Speaker 2:Yes.
Speaker 1:Category in technology. Yeah. And you can't afford to you can't like, basically, the industry as a whole, I don't think can afford to make a lot of mistakes.
Speaker 4:Right? These are people
Speaker 9:completely agree.
Speaker 1:These this is the gonna involve the health of of the children of all the industries, you know, clients. Yeah. There were allegations too that you guys had were sort of had updated a test result on the fly. I have no idea if this is true, but I saw the claim going around. Somebody had gotten a certain test result, and then it had been updated two weeks later.
Speaker 2:Yeah. What's going on there?
Speaker 1:What's happening? That's super interesting.
Speaker 7:Nucleus remember, guys, unlike these other players, we've served thousands of patients.
Speaker 5:Sure.
Speaker 7:And then we can go on our website right now and use our product. They can see our services. Right? I mean, I think it's really funny what's flying around when someone could just go and buy a DNA kit and see the product for themselves.
Speaker 2:Yeah.
Speaker 7:Okay. So the idea that Obi updated a model, we've updated models for the last several years. I mean, results will change. We make that very clear. And by the way, any embryo selection company, Nucleus is full stack.
Speaker 7:We do adult DNA testing analysis. We also do the embryo, and we also do a full end to end IVF experience. And Right? We're kind of multiproduct. But these models will evolve.
Speaker 7:One one point here is important John to mention. People have a very good intuition when it comes to AI that ChatGPT is gonna be better next week. Grok's gonna be better two months from now. The same expectation has to be communicated to the genetic optimization industry. Mhmm.
Speaker 7:The main limitation for building polygenic predictors are is data. Mhmm. It's a data problem. And so what's gonna happen is all the different polygenic predictors are gonna be approximately equivalent, okay, until we get more and more and more and more and more data or people get more and more access to data. That is the fundamental bottleneck of the industry.
Speaker 7:In other words, similar to actually the AI situation, all the value is gonna shift downstream to the application layer. The reason why the reason why people are so upset is because Nucleus has excellent science, rigorous science, and we have excellent marketing, excellent product, and we've served more patients than all the companies put together. And so Okay.
Speaker 1:But but in the but if but if somebody gets a result and
Speaker 7:Yes.
Speaker 1:They make a decision based on that, and then a few weeks later, you come in and you say, actually
Speaker 2:It was the opposite.
Speaker 1:It was it was different than what we said, but they've ultimately made a decision that they cannot correct. Is there a regulatory framework?
Speaker 2:Yeah. That's a tough that's a very tough situation.
Speaker 1:Is there a regulatory framework that requires you to communicate to patients that
Speaker 7:100%. Mhmm.
Speaker 9:We're basically CLIA certified of course. We're a
Speaker 7:CLIA certified cap accredited laboratory. Any single time an update is made, it'd be reflected in the physician report of the respective customer. Mhmm. And also, importantly, remember, there's a lot of disclosures, a lot of different consents people have to sign when they sign up for genetic testing services. One of them is, of course, that the results can and will be updated, and that applies to everybody in the industry.
Speaker 7:And that, by the way, applies to any lab developed test. The tests are getting better as more data comes in. Software improves. That is the nature of how these things go. That's why that Nucleus has been very upfront with me.
Speaker 7:We're very upfront if results do update or change.
Speaker 2:Yeah. Yeah. I'm I'm super yeah. Yeah. I mean, we were we were talking about, there there is a world, and this think this is why, the marketing is really, like, so important for what you do.
Speaker 2:There are so many other, industries where, if if, you know, if if I'm if I'm watching an if I see a billboard for Instagram and it says, like, the most entertaining images on the Internet and I download it and, like, I'm like, this isn't as entertaining as YouTube. Like, I feel like, yeah. Whatever. You know? It's not that big of a deal.
Speaker 2:But but the worst thing that could happen is is, you know, someone does nucleus with their their embryo. It's it's accurate, but there's a minus sign in front of everything. So instead of, like, the tall and smart one, they get the shorter, dumber one, and then they can never go back from that. And this is weird Yeah. Scenario.
Speaker 2:And so I I I do think that there's a I I I think that, that you're you're potentially correct that the the temperature on Twitter is is high, but it is a very high stakes industry. I think I think this is I think it is appropriate that that that you will just kind of need to deal with this for a while. I would love some background on, the this idea of the implications of of, of scores changing. I feel like that happened with twenty three and me. I feel like that was the promise of '23 and Me was that you do it, and then as more data comes in, you can opt in to extra studies.
Speaker 2:How did they solve that? Have you studied that business or any other previous, DNA testing businesses to understand how to actually wrestle with that issue of the changing results over time as more data is created.
Speaker 7:So there there's a there's a there's a couple things to unpack there.
Speaker 2:Please.
Speaker 7:The first is that you don't wanna be a widget. Mhmm. Okay? Fundamentally, 23 is a widget. Mhmm.
Speaker 7:They thought that with their data, they could be able to actually eventually mine drugs, which because of the limited nature of their data, it's actually not best for drug discovery. But on the whole genome front, maybe you could maybe you could argue, okay. That, you know, that won't be a problem if ever a company wanted to do that. But, actually, there's a meta point here about the genetics industry, which is I think and this is, you know, coming from me, which is I think that too often people focus on the genetic test. It's not actually about the genetic test, right?
Speaker 7:Usually people have a very specific acute problem they want to solve. In the IVF context, it's about, for example, having their best baby. So you'll see more and more patients are signing up for Nucleus to do IVF, and it's IVF that's full stack powered by our genetic stack. Because what's really unique about Nucleus as a business is because we've done the adult DNA testing, right, for for many years now, and then now we also do the embryo analysis. So we can actually build a new kind of IVF experience called IVF plus that is centered around giving parents as much information as possible into their embryos.
Speaker 2:Mhmm.
Speaker 7:And notice that shift there, John. You go from being a widget to actually trying to serve a process, a workflow that exists, and that if anyone who wants to have a baby has to undergo.
Speaker 8:Mhmm.
Speaker 2:One thing that Cremieux was kinda hammering that, I'm I I hope I don't botch was something about 12 SNPs versus a million SNPs. Previous data required a lot more genetic information. You were you Nucleus is making the claim that you could get just as much signal from much less data. Is that right? What is your reaction to, his his his take that, it would be impossible for Nucleus to derive such a strong signal about the impact of genetic information from such a small dataset?
Speaker 7:My response is the models are go are public. Mhmm. Go check them. I mean, the models are public. I will And to
Speaker 2:be clear, he also said that he tried to get access to the model and that he couldn't, but but, I mean, you're saying this lying about that. Okay.
Speaker 7:It it's a complete a complete lie.
Speaker 2:Okay. It is just false. So so so he's incumbent
Speaker 7:on line that he proved
Speaker 2:that he that he applied or something like that. I don't know. I doubt he took screenshots of his text.
Speaker 7:I mean, if he wants yeah. I mean, also, by the way, we'll give the report we'll give the weights.
Speaker 2:Okay.
Speaker 7:Just just go livingmynucleus.com/labs.
Speaker 2:Yep.
Speaker 7:Go on there. It says origin, open weight. Like, open weight. You know? Instead of all this debacle, all this Twitter nonsense Mhmm.
Speaker 7:The message to the scientific community, the message to Twitter is go check the weights. And not just that. Our models are public.
Speaker 2:Okay.
Speaker 7:Yours are not. Make your models public, and we can actually have a conversation then.
Speaker 2:What about the allegations of, of, plagiarism, copying from a different paper? When I looked at it, it didn't look like, you know, I I'm I'm not equipped to to to evaluate if it's a direct copy or not. Is is is it scientific best practice to stand on the shoulders of giants and pull from, you know, what the best research are doing even if they're at your competitors, or, with something else more sinister going on or maybe a mistake?
Speaker 7:I I think the thing to remember is, like, you know, a lot of research, like, you think about, like, the in AI context, right, it's like attention is all you need. Yeah. They will use that paper for
Speaker 2:some reason. Yes. The transfer paper has gone everywhere.
Speaker 7:Okay. Right? It's the same thing. What are you gonna say a Google stole like, OpenAI stole it from Google?
Speaker 2:Yes.
Speaker 7:Come on. You're not gonna say that because it's public research. And so it actually comes back to the fact that Nucleus is bringing this technology mainstream.
Speaker 1:Yes.
Speaker 7:Our campaign is succeeding in every metric. Sales are up. Sign ups are up. We have multiple articles covering the campaign. Mhmm.
Speaker 7:People are starting a national conversation as we saw on Twitter.
Speaker 4:Mhmm.
Speaker 7:And I think people want to try to tear Nucleus down because we have excellent science.
Speaker 1:Mhmm.
Speaker 7:And science, excellent science Mhmm. Is the first step to building a very successful biotech business. And this is what I think a lot of the armchair philosophers on Twitter don't fully grasp, which is in order to actually build a successful business, you need to have each and every single one of these components, Sean. It's very easy for a scientist that's never actually built a business, that's never actually tried to sell to a normal person, right, to say, oh, the marketing is extreme. Oh, the marketing is over the top.
Speaker 7:Oh, the marketing is this. The marketing is helping a patient identify a genetic risk that they would unknowingly pass on to their child. There was a patient recently who they were doing IVF with nucleus, and they identified that they actually had a gastric cancer marker colorectal cancer marker, actually. Excuse me. And that that marker doesn't just impact their health.
Speaker 7:It also impacts their future child's health. So what did they do? They chose an embryo without that specific genetic marker, and they took themselves precautions to make sure that they don't get cancer. And so that's what Nucleus is about, we're gonna keep serving patients.
Speaker 2:Yeah. Makes a lot of sense. Sorry to everyone we're having a little bit of trouble with the stream. This has been a fascinating conversation. I I I like the the gauntlet being thrown down on the next step here actually being get let's get the models in everyone's hands because that seems to be a fundamental disagreement here.
Speaker 2:You're saying that you'll give them the the model, give them the data. They're saying that they can't get it. Well, the next step out of this debate, I think that could silence a lot of the armchair philosophers as you point
Speaker 1:Do you do you care about rebuilding trust with the broader community on x? Because
Speaker 7:Yes. Absolutely. And who am tenured.
Speaker 1:Yeah. Yeah. And and then and then I guess, like, what what are kind of the what are the handful of things that you're committed to doing to to make that happen?
Speaker 7:A lot of things. One is the AI thing. I think, you know, we should fix that as mentioned. Right? Make it more clear that it's AI images that people wanna be under press under HIPAA.
Speaker 7:That's one thing I think we should do. Another thing is that, yeah, and this is what originally why we made the models actually public is because we need to be more clear that people can go and actually test and check this stuff.
Speaker 10:Mhmm.
Speaker 7:Right? In some sense, like, a company can do something, but if people aren't aware of it, that's also my responsibility as CEO. Right? And so part of reasons why I'm saying, hey. The models are public.
Speaker 7:Come come submit get to them is, clearly, there's a information gap there that, for whatever reason, wasn't filled in my nucleus, and we have to do better. And the last thing I think which is really important is sometimes, you know, on Twitter, this this one personally hurt
Speaker 2:me. I
Speaker 7:the the amount of time we've spent making the product in a way that people can try to understand where it shows the error error bars, for example, where you you can't full you can see that there's signal, but there's not a lot of signal. Or in some cases, there might be a lot of signal with something like height. Right? The amount of time and effort and product design and and and and and and and sort of, like like, science scientific communication specifically. It's been years.
Speaker 7:Nucleus has been around for six years. I've done this for years trying to get that right. Mhmm. When you see the embryo on your smartphone, it's easy to look at that and just write it off. Right?
Speaker 7:I encourage everyone to go on pickyourbaby.com, go to them to flow, click around, look at our disclosures, look at the way we present information. Right? It really is it's it's it's it takes a lot of time. It takes a lot of effort. Right?
Speaker 7:And I think that is something that I'm thinking about. How do we how can we better put the product out there? Because I think when people can't see something, when they can't see the product or they can't see the science, then they start ruminating. So that's what I really, really want to do, and how do we better kind of connect? And, also, honestly, I think I need to be also more mindful.
Speaker 7:I mean, clearly, I've inadvertently, I've pissed some people off, and that's understandable. That that feedback's taken in. Okay. I'll be more mindful because I really, really, really, really it's if nothing is more important to me than a patient coming to Nucleus getting the highest quality care in every sense.
Speaker 2:Yeah. Well, thank you for taking the time to talk to us. Thank you for taking the time to break all of this down. We are fighting through some technical issues completely unrelated to Somebody didn't
Speaker 1:somebody didn't want this interview to happen.
Speaker 2:Somebody didn't want this interview to happen. I don't know. But We will share your you taking the time to hop on and and and set the record straight, give your side of the story, and explain, what you think folks are getting wrong on the various issues here. It's an incredibly detailed and incredibly important discussion, and we really thank you for taking the time to talk to us.
Speaker 7:Thank you, John. Thank you, Jordy.
Speaker 6:Have a good rest
Speaker 1:of your day. Cheers.
Speaker 2:We'll talk to you soon. Let's go back to the timeline. We do have more guests. If you are tuning in because of that debate, The the chat is active, but we don't know the status of the stream. The, the the chat is saying that the stock is crashing, because, of course, we're having stream issues.
Speaker 2:I don't I don't necessarily think we gotta put this on us. You know? There's, all sorts of, you know, independent state actors that have attacked us in the past. We've had major outages from the hyperscalers. You know, NVIDIA put out a statement saying that they're not Enron, but that doesn't mean that they're not somehow responsible for our stream lagging in quality.
Speaker 2:Who knows? You have no idea what's going on, why our stream is is is having issues. All I know is that it's not our fault. That's for sure. There's definitely nothing that we did.
Speaker 1:We are says, Kian is now dodging the question about the Mendelian disease. He flagged for a patient and then Rizat
Speaker 2:Yes. On.
Speaker 1:This is illegal without notifying the patient. He's saying it's just a model update. This is not something you update on. Medellions are definite. You have it or you do not.
Speaker 2:Yes. Mendelions. Interesting. Well, we have Joe Wiesenthal, from Bloomberg joining. I'm very excited to get an update from him.
Speaker 2:Oh, he's here. Welcome to the stream.
Speaker 4:Thanks for having me. It's it's been too long.
Speaker 2:It has been too long. We're we're we're we're sort of, fighting for our life on the stream, but, the conversation between us should be fine. We had a very dramatic, debate, in this in the bio context. I don't know if any of this, bubbled up to you, but this, anonymous poster, Cremieux, is alleging that this company, Nucleus.
Speaker 1:Alleging might have you might have seen some subway ads. Have a healthier baby.
Speaker 2:Have a taller.
Speaker 4:Oh, I've seen these ads. I don't know if I've seen the ads. I've seen the photos of the ads. Okay. And I know that they're the subway stops that I sometimes go to.
Speaker 4:Yeah. But I actually don't know if I've seen the ads. I'm gonna look for one tomorrow morning. I'm gonna go to this the stop that I've seen those photos. I'll take
Speaker 2:my own.
Speaker 4:Yeah. We will verify my own photo.
Speaker 2:We were we were joking about this that there's something about New York subway advertising that's, like, uniquely viral. And and every company, matter where they're based, just wants to they they see New York only as a place to run out of home and then go viral. Yeah. Because this has happened a number of times. Friend.com.
Speaker 2:I'm sure you did did you actually see the friend.com campaign
Speaker 4:in person? I definitely saw it. And without fill, every single one was vandalized, period. There was not
Speaker 2:a single That's true? Every single one. A 100%
Speaker 4:a 100% of the ones that I saw were vandalized.
Speaker 2:That's hilarious.
Speaker 4:Zero exceptions.
Speaker 2:We they're
Speaker 4:all over
Speaker 2:the place. They were all over LA. There was one that it's it's it's right on the drive from the gym to the to our office, to to our studio. And but it's hilarious because it's a billboard that's directly up against a wall. So you can't see the full ad.
Speaker 2:You just see end.com, and it just is very ominous. Like, this is the end. And it's clear because the the buy was so broad that they didn't think that, oh, yeah. That one's actually not valuable at all.
Speaker 4:I love that. I love that they litter they just spammed real life. That's what I wanted. Right? They just they spammed the physical world.
Speaker 2:And it was getting worse and worse. They were they were spamming Los Angeles. Then I live in a suburb of Los Angeles, Pasadena. And then one day, I'm driving around my hometown, which is very quaint and sort of out of the loop. It's not it's not the San Francisco hubbub.
Speaker 2:It's not teapot. It's it's Pasadena. It's a very chill suburb. And I see a friend.com ad billboard, and I'm like, I can't believe you followed me here. It's following me everywhere.
Speaker 2:It follows me on the Internet, follows me to LA, follows me to Pasadena. I can't get away from it.
Speaker 4:It's like clicking on an ad. You know? It's like or something, and then you just get, you know, served that same ad over and over again, except this one is real life.
Speaker 2:I I do wonder if the if the rage bait, if the if these, like because there's these small campaigns from these, like, tech startups that are in one way, you know, I I I criticize them. We criticize them here on the show. But, you know, I I think that in some ways, are just, you know, pranksters on the Internet. These are young entrepreneurs figuring out how to get attention. I'm I'm somewhat sympathetic.
Speaker 2:But at the same time, I do see that there are, there are people that make political decisions based on this stuff. Have you been following, like, the tech lash and all of this, like, data center news?
Speaker 4:I've I've heard yeah. Absolutely. I've heard of it. I've heard that there's a bit of a a backlash brewing. Yes.
Speaker 2:How how real do you think it is? And do you think it's gonna be more power driven or water driven?
Speaker 4:Or I think it's gonna be very real. I actually think it's gonna be very I yeah. It could be all the I think it's very real. Mhmm. I mean, I really wonder who is in even in the '20, you know, 2028 or even 2026, who is going to run on anything that actually is like, oh, no.
Speaker 4:Actually, data centers are good. Yeah. AI is an important industry of the future. You know, actually, the power stuff has been overstated. The water stuff has been dramatically overstated.
Speaker 4:I have a hard time seeing any politician actually running on that case. It seems like anyone, Democrat or Republican, it feels like they almost have to be automatically against data centers for some reason. And I think you're right. Like, I think that there's people have some intuition. They don't like AI companies.
Speaker 4:They don't like big tech, whatever. And then they fill in whatever seems satisfying. So I don't know. I think the water stuff seems like the most out there and disconnected from reality, but all and so therefore, the people who are most disconnected from reality will probably latch on to the water stuff. Yep.
Speaker 4:The people who are a little more sort of, I don't know, normie in their views about how the economy will maybe talk about the electricity. And then people who just dislike the sort of broader effect of tech and all these different things, they're probably gonna talk about the slop and how it's ruining society, which maybe it is. I'm not really sure. But it does feel like there is something to your to your point, there's something for literally everyone to latch onto in the anti AI fight. Anyone can have their thing which resonates with them, in which case it's, like, hard to see where the constituency is to build these things.
Speaker 4:So I think what you end up is probably a lot of entities, you know, looking for places in the middle of nowhere in Texas where they can set up their own natural gas plant and their own gas turbines or something and, you know, stay stay off the grid as long as they can.
Speaker 2:We gotta get a politician who's just like, you know what? Like, this stuff's delightful. Have you seen a studio ghibli? I like a studio ghibli. I like a pseudo song.
Speaker 4:Yeah. There someone will like, who is it? Like, just even when you say that, though, like, it's hard to imagine who that politician is or what the case that they make. You know, so few people
Speaker 2:Yeah.
Speaker 4:Write today into I mean, I use some AI tool basically every day to look up something. You know?
Speaker 2:Probably Who speaks for us? Who speaks who speaks for
Speaker 4:Who speaks the constituency? Day I
Speaker 2:They do one deep research report every couple days, and they and they use the the the thinking models to answer some questions every once in a while, and they generate some funny images every once in a while. And then they kinda move on, and then they come back to it in a little bit.
Speaker 4:And then it's like, oh, they have a new they have a new thing out. Let me I'll run my battery of tests that I do with every new model. Yeah. The questions that I always ask. Yeah.
Speaker 4:Yeah. Yeah. It's pretty good. Then Yeah. Yeah.
Speaker 4:Pretty good. Pretty think it's gonna be it's a real it's it's gonna be really tricky politically. I think it and I really think it'll be huge because just to you know, the the labor market is soft. Yeah. So here is this and electricity prices are high.
Speaker 4:So and granted, we don't know what the conditions are gonna be in 2026 or 2028.
Speaker 1:Yep.
Speaker 4:But right now, you have people who are, you know, in the AI industry, obviously, many of them, in fact, talking about the potential for AI to displace significant amounts of labor. Who's gonna vote for that? Like, what how is that Yeah. Again, I could envision some world in which, like, human life is a lot better when we've been freed from many laborious tax Totally. Tasks.
Speaker 4:But in today or tomorrow or 2026, it's hard to see, like, what is the thing that gets people excited. Yeah. I mean, pre I asked about it.
Speaker 1:Pre Internet pre Internet, it would have been a lot easier for Silicon Valley to navigate Yeah. Navigate this tech trend this, like, technological cycle because you could have been going to the capital markets and saying, well, you actually wanna give me a $100,000,000,000 because I'm going to deplace, millions of jobs in all these categories, and we're gonna capture some percentage of that. And then and then you could go to the everyday people. You could go to the media and say, you know, we're gonna create super abundance for everyone. Yeah.
Speaker 1:And there won't be any jobs. And you're gonna you're gonna have an army of robots that that, you know, run your whole life, and it's just gonna be this beautiful utopia. Now Yeah. People go on one podcast, and they wanna talk about job displacement. And they go on another podcast, and they talk about Utopia.
Speaker 1:And the same people end up seeing both of them, and it just doesn't it doesn't work.
Speaker 4:I couldn't I couldn't agree with you anymore on this specific point. No. For real. I think this is, like, one of the defining phenomenons of our time, which is the there is no such thing as segmenting audience. And Yeah.
Speaker 4:This is a phenomenon that occurs across all sorts of different realms, whether we're talking about politics or Wall Street, etcetera. Historically, people talk differently to different groups, and that's just very normal, etcetera. And you tell one story to someone. If you can't do that anymore at all. Everything in any context is implicitly understood, including inter internal company communications.
Speaker 4:Right? Yeah. Where we expect everything to leak and you expect someone to any memo that you share. So internal com communications can't really have any candor anymore because that all reads as PR because that's expected to
Speaker 1:leak Yeah. And every single person running a lab has had something where six years ago, they they were on a mic saying confidently, it's very likely that AI will kill all of us on a long enough time horizon. Yeah. And then that resurfaces today.
Speaker 2:Yeah. And it's not Or or even worse, they'll say, like, one of my worst nightmares is that this happens, and that's why I'm working to stop that scenario. And then people just That's
Speaker 4:why I work for build it.
Speaker 2:The I mean Yeah.
Speaker 4:But this is a weird thing about AI specifically Yeah. Too, which is that we're sort of at this point where several technologies that we maybe we were really excited about at some point in the past years down the line, like, oh, we didn't really think or this turned out to be not so great,
Speaker 2:or we
Speaker 4:don't really love the effect that this is having on society and so forth. AI seems very strange and distinct from anything else I can think of in memory where from day one even before it really existed, the people invested in it and sort of working on it have talked about its downsides in frequently dramatic dramatic terms such as you're describing. So it's very different than any other technology where usually the downsides only become apparent years and years after they've sort of suffused and soaked into society. Here, they're talked about from day one.
Speaker 2:Okay. Last week, there were two headlines that I was trying to, turn into some sort of pithy phrase or or or headline. I couldn't really land it, but I'd love your feedback. So, NVIDIA beat earnings, and we got a jobs beat. And so I was riffing.
Speaker 2:I was like, demand for robots and humans through the roof?
Speaker 4:That's right.
Speaker 2:Is that what's going on, or am I misunderstanding the jobs numbers? Was that less impressive than people
Speaker 1:jobs report is canceled Yeah. And the GDP.
Speaker 4:So the, yeah. I'll say a few things. I mean, that's that jobs report is from September. Mhmm. It feels like a lifetime ago.
Speaker 4:You know, the other thing too is that although it did the pace of job creation for September did come in higher than expected, once again, job creation was actually negative if you include health care and social care work, which is a thing that I think I've talked about a couple of times when I've caught up with you guys. But those are the jobs that we would really like to see AI liberate us from. Right? Like, it would be really nice if you could actually have robots change the bedpans of seniors or other these things that are sort of low productivity jobs, jobs that for many people are are low paid, kinda miserable in many cases, etcetera. So I think what's going on, unfortunately, is that we're in this environment in which job creation overall for most sectors is pretty mediocre, including finance, including tech, etcetera.
Speaker 4:The one thing that keeps powering us forward are these sort of menial low pay jobs in health care, service sector, see taking care of seniors, etcetera. And I don't know. It feels like we're very long, very long until anything AI robot related is actually getting into that sector. But that would be the dream. Right?
Speaker 4:I mean, that's what that would be the dream to That was the original make make progress in that front.
Speaker 2:I mean, elder care was the original pitch of Honda Asimo back in, like, 2000 or 1999. It was like, yeah. This robot's gonna bring the meal to the to the old person in the sick bed.
Speaker 4:Wouldn't that be amazing?
Speaker 2:Makes makes a ton of sense. And and and there are to to be fair, there are some robotic, like, you know, with wheels on it, rolls around, does some stuff. But certainly not broad deployments by any means.
Speaker 4:Not not yeah. Not broad deployment. Not at the scale. And so what happens is we have this economy where we you know, the unemployment rate is still still pretty low by historical standards, although it's gone up a fair amount a little bit in the last year.
Speaker 2:Yeah.
Speaker 4:But there's just so much pressure being put on the existing labor force to care for the aging population. It creates some pretty serious strains.
Speaker 2:Yeah. How have you been tracking the just the AI spending bubble, this idea of, you know, massive growth debt coming into tech for the first time in a long time? I feel like a lot of tech people are so used to the venture capital model. Okay. Yeah.
Speaker 2:Might be a 100,000,000 at risk, but this is, you know, 1% of overall allocation. There's a bunch of LPs from foundations. It's very diversified. And if that company goes bust, that's fine because another company is gonna do great. Now we're looking at serious numbers.
Speaker 2:We're getting into trillions. There's debt involved. People don't know how to manage with debt and deal with that. How are you processing it?
Speaker 4:It was sort of a real wake up call to me when I started seeing people online post screenshots of credit default swaps on Oracle debt. Like, that was the moment where I was like, oh, this really has transformed from the sort of equity funded, free cash flow funded environment, which has characterized tech for, you know, over two decades, really going back to until the the telecom bubble. So as soon as you and I know these companies have debt. I mean, you see them. Apple has debt.
Speaker 4:They've had it for a long time. A lot of these debt issuance, though, in recent years have been more or less like exercises in cash flow management or optimizing taxes and stuff like that. Now it feels like, okay. Like, this debt is at a very real scale where I'm looking at CoreWeave credit default swaps, Oracle credit default swaps, etcetera. That is, to my mind, a signal of, of course, something's changing.
Speaker 4:Blue Owl, they're publicly traded. That's the private credit company that's gone in with Meta to do some data center financing. That stock, I think, has become a bit of a proxy for how people perceive some of the financing risk in that space. The deal that we have an episode coming out, I think, sometime next week, actually, where we talk a little bit about how the credit construction of these events. The founder of this company, Noetica, which does uses AI to examine credit agreements actually walked us through it.
Speaker 4:It's some fascinating stuff, but people are sort of looking at, okay. Who is the real bag holder here? What is the risk of, you know people are talking about, obviously, what is the risk if there's not as much value in these GPUs five years from now as we may have thought. And that to your point, that's just totally novel for tech in recent years. It doesn't feel like we've it's been so long since the idea of debt or leverage in that way has been part of the tech story.
Speaker 2:Yeah.
Speaker 1:What did you what did you make of NVIDIA sending out that report for the sell side over the weekend? Then and
Speaker 4:then It's again weird, isn't it?
Speaker 1:They had another post they had another post today. I'll just read it in case anyone's just tuning in this morning. Let's see if they've We covered it at the beginning of the show. Delighted by Google's success. They've made some great advances in AI and we continue to supply to Google.
Speaker 1:Nvidia is a generation ahead of the industry. It's the only platform that runs every AI model and does it everywhere computing is done. NVIDIA offers greater performance, versatility, fungibility than ASICs, which are designed for specific AI frameworks or functions. So again, not not like these are these are meant to be confident inspiring, but they come off the you know, they they have the opposite effect.
Speaker 4:It's really weird. The tweet like, I guess I sort of understood. Okay. So they sent out that note. You know, look.
Speaker 4:As I mentioned, over the last several weeks, for some reason, Wall Street has got really taken in with this whole conversation about GPU depreciation schedules. Maybe I think Michael Burry's been talking about it or something. Okay. Fine. Like, this has taken hold.
Speaker 4:I am sure this is the the type of thing where for every 100 people who are talking about this, maybe one knows what they're actually talking about. Like, I have no doubt that there's all kinds of noise out there, and so maybe it makes sense for NVIDIA to, like, oh, let's let's put out some information that we have. Like, I guess it's a little weird, but okay. Like, I I sort of get it given the degree to which this has just become a meme in the last few weeks. The tweet about Google is a little strange.
Speaker 4:Like
Speaker 1:Like, I I I should be
Speaker 4:Here is the here is the biggest, most powerful company in the entire world, and they're doing this sort of weird we're excited to see we're happy for your success.
Speaker 1:It me It's odd. It reminded me of Jensen's comment on the on the OpenAI AMD deal where it was like kinda snarky. He was saying something like, I'm kinda surprised they would they're so excited about their new chip. I'm surprised they would give away 10% of their company before they've developed it. So so again, to to me, I feel like when you're operating from a position of strength and confidence Yeah.
Speaker 1:You never you never talk about competitors from official channels. I had I I've given it I've given this advice very recently where like there's a a company that every time their competitor does something, they post about it. Guess that get guess guess that have a different
Speaker 2:quote tweet too. It's so much easier to just be like like, our esteemed our the the other members of our industry or, like, the other big tech companies would do it this way or, like, other handset makers or other smartphone makers. Everyone knows that you're talking about Google or iPhone or whatever you're you're comparing to, but trust us.
Speaker 1:In this case, company that they always talk about has a 100 times their revenue. And so and so it and so it screams like,
Speaker 6:it
Speaker 1:screams, like, we're obsessed with our competitor. But in this case, it's like the TPU is just, the first sign of an external
Speaker 4:Yeah. Right. You immediately, like, pounce on them and you're like you know what see? I I've been thinking. I mean, one of the funny things about Jensen and NVIDIA overall is you think about these other mega cap tech companies and these other ultra rich CEOs.
Speaker 4:You know, they've been dominant for in in most of these cases for, like, well over a decade. Right? Yep. They've been some of the most powerful companies in the entire world for over a decade, obviously. NVIDIA is sort of this weird case because, you know, four years ago, people were talking about, oh, this is the company that makes chips for Ethereum mining, or this is like, that was what how a lot of people talked about NVIDIA.
Speaker 4:I think even as, yeah, as recently as 2021, people were talking about, oh, NVIDIA's so it might
Speaker 2:Well, people don't remember. Before there was the mag seven, there was Fang, there and was M and FANG. And that was And what was the it was Netflix. It was not NVIDIA. It was Facebook, Amazon, Apple, Netflix, Google.
Speaker 2:Yeah. And then crazy to not include Microsoft. Right? Right. And they so they added Microsoft, they took out Netflix, and then they added NVIDIA and Tesla, of course.
Speaker 2:But, yeah, what I mean, what what a what a wild
Speaker 4:ride I've Like, what a run. I mean, obviously, like, NVIDIA's been an incredibly successful company, but it went from, like, a, you know, a pretty successful
Speaker 2:Yeah.
Speaker 4:Chip company to the biggest company in the world in a matter of few years.
Speaker 2:Yeah.
Speaker 4:Maybe there's something there. Maybe there's still a chip on the shoulder. Maybe there's still some culture of feeling like it's the underdog and something where it's like, yeah, it's like act like you've been here.
Speaker 1:Yeah. It's one it's one
Speaker 2:thing. So this starting to thing is real. Like, there's yeah.
Speaker 1:But so here's the thing. If you're a startup
Speaker 2:Yeah.
Speaker 1:And Google enters your market, I've seen a lot of founder or, like, a big company. If you get sure locked by Apple Mhmm. You're gonna hit the timeline and be like, I'm delighted by by Apple's new mobile app. We're we're delighted to continue serving
Speaker 2:the business. Validated the the the market. Yeah.
Speaker 4:They thank you for thank you, Apple, for validating our Yeah. But I don't think
Speaker 2:I don't think NVIDIA need this case.
Speaker 4:NVIDIA doesn't exactly need validation Yeah. At this point from a competitor.
Speaker 2:And the TV is a decade old, by the way. I can't
Speaker 4:Right. It's been around for a while. And all right. And all like, that, which is another sort of interesting dimension Yeah. Of all of this, which is, like, suddenly people wake up and, oh, it's not like to your point, I mean, we've people have been talking about the existence of Google's TPUs for a long time, obviously.
Speaker 4:Now there have been some question about the degree. What's the strategy here? Would they ever sell them? Will they rent them out? There have been obviously questions, etcetera.
Speaker 4:But it is funny how, you know, you get these moments where suddenly, you know, you get this one eighty over the last several months, weeks on Google, the Gemini three launch, of course, bolstering this idea. Oh, actually, they're in a good space. And suddenly, oh, and they also have these TPUs, which they've had and been working on for a long time, but nothing really changed. They've had them for a while. There's not some new breakthrough announcement announcement here or something.
Speaker 4:And so suddenly, NVIDIA feeling like it has to respond a little strange.
Speaker 2:Yeah. Yeah. I mean, it it it like, I I do think that, like, there's so much demand that it's a little bit ridiculous to just be like, oh, NVIDIA is completely over. But at the same time, like, it's never great when you go from a monopoly to a duopoly. Like, it's just that like, it's always nice to be in a less competitive market.
Speaker 2:And
Speaker 1:Yeah. Yeah. But it's And this whole year
Speaker 2:has been about AMD.
Speaker 1:AI is AI is literally half as transformative
Speaker 2:Yeah.
Speaker 1:As the AI bowls
Speaker 2:The consensus. Yeah.
Speaker 1:It doesn't mat like, you can have two players and the demand is so overwhelming that Yeah.
Speaker 4:And, like, NVIDIA's own sales are capped, right, by capacity and by production capacity. There's only so much, which is another sort of, like, interesting dimension that I'm, like, trying to get a better understanding of here, which is that, you know, again, it's not like search or AI or or chatbots, etcetera. There is the there are these constraining effects on the markets from how much fab capacity is at TSMC or how many some of this underlying equipment. So the ability of anyone to scale up dramatically and expand the overall size of the market is sort of tough at this point. I don't know exactly what that means, but it like, my guess is I my assumption, I don't would be that everyone remains pretty capacity constrained for some time.
Speaker 4:It does I don't think there's, like, a tons of tons of chips laying out there Mhmm. For the taking right now.
Speaker 2:Yeah. Give us an update on Odd Lots. Is people have been congratulating you on ten years. Yeah. Did the ten year date happen recently?
Speaker 4:The ten year date did happen. We didn't even you know what's funny? I think it was I think it was November 6. I got an email.
Speaker 2:November 6.
Speaker 4:So we have a party which you both are invited to. We have a party in New York City in December to celebrate our ten years. So we've been sort of That's right.
Speaker 2:You play the night vision sound.
Speaker 1:That's right. Fire me up.
Speaker 4:But so we were, like, getting ready for that. We've been doing some sort of ten year episode. We're talking to some big names and, you know, big big big picture thinkers and stuff like that. But I didn't realize the actual date until the morning of it. I started getting random emails from people inside the company congratulating me, congratulating us on a ten years.
Speaker 4:But it's pretty crazy.
Speaker 2:Let's have it gone 10 times.
Speaker 4:Yeah. 10 times. Wow. It's 10 times gone.
Speaker 1:There we go.
Speaker 4:That that's this has been the highlight, the 10 the 10 gong smashes. This has been the highlight so far of our ten year anniversary.
Speaker 2:Who's who's the most recent ten year guest that Yeah. Would that that was that exemplified that, like, bigger picture thinker?
Speaker 4:Yeah. Well, we had Ray Dalio on the podcast on Monday, which was a lot of fun. He told us about meditation. He talked to us about the importance of transparent culture, about the importance of letting junior staffers or junior employees at Bridgewater attack the senior employees.
Speaker 2:I loved his story about the first stock he ever bought.
Speaker 4:I know. I know.
Speaker 2:Hilarious. I don't know if he tells that constantly. I haven't listened to every He
Speaker 4:probably does. He probably does.
Speaker 2:Yeah. Such a good story. He's just like he's just like, I saw it, and it was I did. It was the cheapest stock he could possibly buy. Nominal stock.
Speaker 2:That was, like, price. Dollars a share. Yeah. He's retail.
Speaker 1:Think made
Speaker 2:a lot money. I mean, it's like the in in crypto when they're like, it's $0.00 $0.00 1¢ a token. Imagine if it's a dollar, and you'll be like, I have so much money.
Speaker 4:Can we talk about that for a second? It's really annoying with some of these crypto prices to have to, like, squint and see how many zeros there are. They need some reverse splits Yeah. I really think. Like, we need to go we need to, like, $1, $2.
Speaker 4:But, no, to your point. Right? It's it's basically for I don't wanna be insulting, but it's basically, like, the dumbest. Yeah. It's trying to attract the dumbest kind of trader there is.
Speaker 4:Totally. And you're like, oh, this is cheap because it's $1.01 millionth of a cent or
Speaker 1:whatever. You're still early.
Speaker 2:Yeah. I mean It's still early.
Speaker 4:I imagine if this were a dollar.
Speaker 2:I remember the doge to a dollar campaign. Yeah. Everyone doge to a dollar.
Speaker 4:That was a very powerful meme.
Speaker 2:It was
Speaker 3:very powerful.
Speaker 2:These things these things are real.
Speaker 4:I thought was gonna get there because I think it got to, like, 30 something century. I So was like, oh, it's like the it's definitely going to satisfy the meme. It never made
Speaker 2:was You're like, I thought it was gonna get there because I put my whole paycheck in it.
Speaker 4:I I really thought it was I was like, oh, it's obviously gonna go to a dollar of royalty.
Speaker 2:It did seem like the meme was gonna work, but it got close. Got close. Was a run. Jordy?
Speaker 1:Are you aware of a single person that has sold their primary residence in New York and is going to going elsewhere since the election? What's been the what's been the sentiment? Mhmm. I know a bunch of No. Former OnLots guests are on the transition
Speaker 4:Are in the are on the
Speaker 1:yeah. Which is cool because you guys have some insight into, like, how these people think and the public does. Mhmm.
Speaker 4:Yeah. I have not heard of anyone who is leaving New York City. It's interesting. There's a I don't know the name of the brokerage, but there is one of the brokers in New York runs these ads, speaking of outdoor ads in the taxis. And prior to the election, they're very scaremongery, and they were, like, talking about deals in Florida and all this, like, real estate that you could buy in Florida, etcetera.
Speaker 4:Anyway, after the election, I saw one of the ads this week, and it was talking about how JPMorgan just opened up its new headquarters in New York City and how all of the many employees they're gonna have there. So I guess now that now that the election is over, they can go back to selling New York City real estate because, you know, they didn't get the I don't think they got the out those brokers did not get the outcome that they were hoping for. But, yeah, we have some we have some past guests on in the transition team. Paul Williams, shout out to him, who I also play music with in my country music band, Light Sweet Crude. He's on the the housing transition.
Speaker 4:Kathy Wilde, who is the head of the partnership for New York City, which is the big organization of a bunch of CEOs, etcetera. That's, like, the most, like, sort of, like, diet in the wool, like, sort of you know, they're not a lobbyist group, but they represent the business community. Even she is in the transition team. She's also been on the podcast. So it seems like, you know, I've seen a bunch of people angry at some of the picks, happy about some of the other picks.
Speaker 4:Mhmm. It seems like he has built a he's at least with these selections, a little something for everyone, some moderate, some normies, some more radicals, etcetera. Enough for, like, everyone to be a little happy and a little a little concerned, maybe.
Speaker 2:Yeah. Yeah. I mean, it certainly seemed like that that there was that vibe But I of him with Trump that was very funny where they're kinda going
Speaker 4:Oh, that was crazy.
Speaker 2:Yeah. It felt like there was just like, okay. There's a lot of theater on both sides here. They're both they're all having fun. You know, they're not like, I can't even be in the same room as that person.
Speaker 2:No. So, you know,
Speaker 4:so I think that, like, for those of us not in politics is I don't know. It's, like, hard for us to imagine how these people who are, like, the way the rhetoric and then they, like, get together and they smile in front of the camera and, like, feels very weird. But, you know, they're just like they're professionals.
Speaker 2:I mean, NFL teams have rivalries. They shake hands at the end of the game. I think that's kind of the nature of these
Speaker 1:things, which is Yeah. WWE.
Speaker 2:Yeah. WWE. I I've always liked the the wrestling metaphor.
Speaker 4:The the thing is too is that, like, whether we're talking about the selections of people for the transition or the I think very wise choice by Mamdani to, like, try to be friendly with the White House or at least find some common ground is, look. There's some, like, pretty hard budget constraints, etcetera. It it the mayor the job of mayor is a management job. You know, the trains aren't gonna run themselves. The buses aren't gonna run themselves.
Speaker 4:The apartments aren't gonna get built. So there is a certain amount of, like, required between the budget constraints and just everything else. I think there is a certain amount of sort of forced pragmatism Yeah. That's probably at play here.
Speaker 2:Yeah. That makes sense. We'll let you go in just a minute. Alright. What's next on the economic calendar that you're tracking?
Speaker 2:What what what should we be looking forward to through the end of the year? Obviously, in our world, we're very excited about Black Friday. Gonna be tracking those numbers. Also, an interesting economic indicator. But what's on the top of your mind?
Speaker 4:You know, I think, actually, like, basically, all data through the end of the year is gonna kinda be garbage because, obviously, we're gonna get the restart of the data, and we'll get more timely jobs data and so forth. But all
Speaker 1:of that is gonna be
Speaker 4:affected by the shutdown.
Speaker 1:Mhmm. October, we are not getting anything from October.
Speaker 4:Right? We're not getting anything from October, and then November is going to be affected in large part from the shutdown. So those numbers aren't gonna mean anything anyway. And so probably the the actually clean report where we could say, okay. This is actually well collected data to the extent any data is there's all kinds of issues with collection and is not affected by the shutdown.
Speaker 4:So that's gonna come out in January about December, which is gonna be very strange. You know, I think the big development is so I think it's December 10 is the next Fed meeting. As recently as a week ago, it was looking like they were not gonna cut. The odds were below 50%. But a number of the FOMC members in the last several days have come out and said they're cool with the cut.
Speaker 4:So it looks like as of right now, we're gonna get a cut, but that is I think that meeting is the day before we get the November jobs data. So it's all gonna be sort of a mess, I would say, until early next year.
Speaker 1:Mhmm. Last question. How should people read into not getting data from the month of October? Should we say that, like, the the simplest explanation is employees were furloughed. We don't have we don't have time to go back and collect all the information.
Speaker 4:In this I think I my impulse is that the simple explanation is the correct one that due to the timing of the shutdown, the duration of the shutdown, it's, like, unrealistic or something like that as opposed to something nefarious. Mhmm. If it if there if if there continue to be more things, then, okay, then we see what's up. But I would say this pro I it's probably pretty straightforwardly linked to the fact that, you know, the the this the government shutdown. Yeah.
Speaker 2:I'm also gonna tell you about fin dot ai, AI that handles your customer support, the number one AI agent for customer service. Our next guest is director Michael Kratzios. He is the thirteenth director of the White House Office of Science and Technology Policy, and it is great to have him here with us on the show
Speaker 1:best call in setups we've seen.
Speaker 2:You look fantastic. Thank you so much for taking the time to talk to us. How are you doing?
Speaker 11:I am great. Thank you guys so much for having me. I have followed your, meteoric rise over the last year. I, I feel like I should be on this show much earlier.
Speaker 2:I yeah. We would have loved to have you, but, we're very happy to have you today because there's massive news. But I'd love for you to introduce it and actually set up the conversation. So please take us through the announcement, and, and then I'm sure we'll have a ton of conversation and questions to go through.
Speaker 11:Yeah. So I think maybe we can start with action plan that the president signed out in July. One of the main themes of the AI action plan essentially to win the AI race is all about how we can win in scientific discovery. The question was like, how do we do that? What's like the next chapter of using AI to drive scientific innovation in our country?
Speaker 11:Yesterday, the President signed an executive order launching what is known as the Genesis Mission. I think for a lot of folks that you guys talk to every day, you know this. AI has had this incredible rise over the last couple of years. It ultimately started first with large language models themselves, and those are where we scraped the totality of knowledge on the Internet and we're able to then create these models that can predict all sorts of things, the next word if you will. The next phase of it was all around coding and you've seen these great startups that are incredible at coding.
Speaker 11:Some are huge model builders, are awesome at coding too. But the big question that still remains is how do you apply this large language technology to scientific endeavors? How do you use it to be able to create new materials? How do you use it to create new microprocessors? How do you use it and tap it into all of this exquisite scientific technology and hardware that exists all around the world?
Speaker 11:What the Genesis mission tries to do is to bring all of the super valuable important data that the national labs have collected over the last seventy years and put it to use to train large language models to be able to dramatically, and I mean dramatically accelerate the pace of scientific discovery. So, is I would argue and I've said it before and I'll keep saying it, this is going to be the single largest marshaling of the federal resources of scientific discovery since the Apollo program. So, we're thrilled to kick it off, and DOE is gonna be the home for it.
Speaker 2:Talk to me about the relationship between, the public sector and the private sector. I feel like a lot of folks in our audience have said, thank you for your service. We loved DARPA. We loved when DARPA created the Internet. We love GPS.
Speaker 2:We love the moon mission, but we got it from here. We invented the transformer at Google. We invented SpaceX and the the rockets that go up and land, and we think, private industry has it handled from here on the research side. We don't need anything from the government. How do you think about is that just is this just a misconception and we actually need more original new ideas, research in a government setting, or is there more of a public private partnership that you think will play out here?
Speaker 11:I think it's definitely more of the latter. I mean, the reality is that when some of the initial projects were launched in the nineteen fifties, you think of Manhattan Project, that was an era where the vast majority of research and development in The United States was paid for and funded by the federal government to the tune of almost 70 or 80% of it was funded by the federal government. If you zoom ahead, sort of the seventy years that we are where we are today, the vast majority is done private private sector. Generally, The United States spends about a trillion dollars a year on R and D and about 80% of it today is done by the private sector. Now that being said, there is a critically important role for the government to play in that larger ecosystem, and it truly is an ecosystem.
Speaker 11:You have to have private sector, academia, and the federal government all working hand in hand to sort of make the very important basic research breakthroughs and ultimately commercialize those. The secret and the sort of unique special thing about the Genesis mission is the scientific datasets that exist at the national labs. This is a unique asset that is so valuable to the American people and to all of the scientific enterprise in The United States. The bottleneck, you guys know so well in so many of these AI endeavors, is how do you get the right data to train these models? For the early large language models, the data was just out on the Internet.
Speaker 11:You could use Common Crawl and scrape it. For the world of coding, you had lots and lots of coders and lots and lots of material that you could use to train those coding models. But for science, it's not that easy. You have silo data. You have pharmaceutical companies that have pharmaceutical related data.
Speaker 11:You may have chemical companies that have chemical related data. But what's so special about our national lab ecosystem is that it covers such a diverse and broad range of scientific endeavors. You have biologists. You have material scientists. You have chemists.
Speaker 11:You have people who are working on space all in the same national lab infrastructure, and that depth of data is so incredibly powerful in order to accelerate scientific opportunity and endeavor, and that's what the Genesis mission is all about. To your point about private sector involvement, the thing that we have been so excited about is the private sector is clamoring to be part of Genesis mission. We all are in this together. There's a desire to pair incredible supercomputing infrastructure and the GPU capacity of our greatest chip companies with the great datasets we have at DOE and everything in between.
Speaker 2:Yeah. The can you help me understand a little bit more how a lab might actually plug into the Genesis mission? Because we we've seen a lot of the labs say, oh, we wanna start working on science. So some of the labs have already. I mean, Google is a Nobel peace a Nobel Prize, right, for AlphaFold.
Speaker 2:Does that does that look like them interfacing directly with the DOE or going through a lab? Or how how does that take shape, do you think?
Speaker 11:So what DOEs ultimately the Department of Energy is gonna be creating is a platform for scientific discovery. Okay. There we're going to be making available the very valuable scientific datasets that can be used to run these large language models for science. As we've seen, OpenAI had a nice tweet thread about this project and how excited they are about it. We've seen lots of other companies already pursue this.
Speaker 11:Google of course with AlphaFold and the Nobel Prize that they've won there. So, we're seeing is all of these large language model builders or labs themselves want to partner with the Department of Energy so we can work hand in glove to accelerate the scientific discovery. The key is how do we Just zoom out a second and think about it. How do we 2x the ability of us to very quickly iterate on scientific experimentation? So, right now, if you have a hypothesis and you want to test it, how do we make that two or even 10x faster?
Speaker 11:How can we make it so that if we have an idea, we can send that idea to an AI powered Cloud lab and the test can be run behind the scenes as we're working on a second project. So that's the sort of, like, big level thinking that we wanna do to dramatically, dramatically accelerate the velocity and pace of scientific discovery.
Speaker 2:Can you help me understand how you think The United States is positioned geopolitically against our near peer rivals on the issue of AI in science? I'm pretty I I feel like I'm relatively up to speed on just the general capabilities of American image models versus maybe Chinese image models or, DeepSeek versus GPTOSS and the LAMA models. I kind of know where we're standing in just the general industry, the industrial uses or the the general uses of these LLMs and the AI, models that are coming out of America and China. How are you thinking about America's competitiveness on the science and research side?
Speaker 11:So we're in a lot earlier innings of that. That's a really good question. And I think what's unique about sort of AI for science is it has to pair this exquisite scientific physical infrastructure with the models themselves. So, you want to drive scientific discovery, you have to be able to pair what's coming off of telescopes, what's coming off of lasers, and all this stuff to be able to match them with large language models to be able to accelerate that loop. We're still in the very early innings of it.
Speaker 11:In outpace order for us and continue to keep our lead like we do have in some of these other places is we have to do something like the Genesis Mission. We have to wake up a country and say like, Look, where do we have the most valuable scientific datasets and how do we make those datasets available to our model builders to be able to create the necessary tools to pair the data coming off these exquisite scientific instruments back into these AI models? Think about it. For us, we want to win on fusion for example. Yeah.
Speaker 11:So, fusion, Google's already doing this, but there's a ton of companies around United States that are very heavily funded, that all have lots and lots of experimentation they want to do with these fusion reactors. The ability for us to be able to accelerate the modeling of that through the Genesis mission rather than each individual company having to this on its own can be really, really dramatic. So, back from a pacing standpoint, I think The US has all of these amazing instruments. It has the labs. It has the great private sector together, and what the Genesis Mission tries to do is bring that together in a way that's truly American, where each of us, as part of the ecosystem, can play the important role that we're best at with obvious commercial goals in mind down the road.
Speaker 11:And that's what's sort of driven this great discovery we've had for years, and I think we're gonna continue to see that in the years ahead.
Speaker 1:What role does academia play as part of this project in your view?
Speaker 11:So I think for us, academia has always played a very important role in pursuing early stage, basic, pre competitive R and B. As we think of all of the most critical areas of scientific endeavor, whether it be in materials, or in chemistry, or in mathematics, or in physics, or science, there's still a critically important role in that early stage discovery science. Academia can play a very important role there. They're the ones that have these theses and these ideas, these hypotheses to solve some of these very early fundamental problems that can ultimately unlock great commercialized solutions in the years ahead. So, academia and universities are and do want to be part of the Genesis mission.
Speaker 11:There's an important role for a lot of these departments, professors, and thought leaders to be part of it and to introduce their ideas and concepts of things that they want to test. What ultimately Genesis is going to do, it's going to create up to 20 grand challenges on some of the biggest scientific problems we face today, and we're looking for everyone. You can be in academia, you can be in the private sector, you can be in your garage, wherever you are. We want you to come with the best idea on how to solve those and be able to leverage the great infrastructure that the federal government has in its labs to solve those.
Speaker 2:How are you thinking about AI risk these days? I feel like, we've been on a total roller coaster from sci fi paper clipping scenarios to, some very real, geopolitical competition and issues with people maybe using these models too much, going somewhat crazy. There's been a wild ride that I think everyone's been on, and I'm interested to hear how you think about AI safety these days. Is the the nuclear analogy the most important? Is this a Manhattan project?
Speaker 2:How do you think about the role that the US government should play in the AI safety discussion?
Speaker 11:Yeah. You know, think as as I kinda look back and think about how the early conversations were when some of the big model lab builders came to Capitol Hill and talked about wanting to create kind of an IAEA for AI, I honestly it set the wrong tone and I think it set sort of the industry back for a while. I don't know how much you guys track sort of like global politics of AI policy, but for a good two years there, I think that sort of discussion on the global stage was, what are the worst possible things that AI could possibly do for the world and let's try to figure out if we as a collective world can find some sort of a global solution to solving it. Obviously, that's the wrong approach and everyone's backed away from it. The UK themselves that were touting their big UK Safety Institute have renamed it the Security Institute.
Speaker 11:We, Trump administration, renamed the AI Safety Institute or Department of Commerce as well and moved in a direction of innovation and adoption versus this nebulous catch all safety term. But I think to me, one thing I always think about and we always have to balance is, and maybe it's a little personal, but to me, I recently became a father in July. And I think a lot about the way that my child is going to grow up, the way that he is going to interact with this particular technology, the way it's going to impact not only the way that he grows and learns in school, but also the types of jobs that he's going to have and how he's going to enter the workforce. And I think there are very credible and real things that the American people are thinking about, about how this technology can be best used to improve their way of life and ultimately help them live a better and more fulfilled and more rich life. We at the White House are all about finding ways to encourage adoption of this technology.
Speaker 11:In order for that to happen, we have to have the trust of the American people, and trust is part and parcel of everything we're trying to do, Whether we're building out AI for educational reasons, or to improve the amount of energy that we have in The United States, or solve the biggest health crisis that we may encounter in the future, we want to build that trust. So, when these solutions are coming about because of embraced. And it's something we worry about and think about a lot, and it's something that a lot of our standards agencies are thinking about. How do you promulgate the right standards so that when these technologies are put into all these different industries, people trust them.
Speaker 2:How are you thinking about job displacement at this point? The models are so incredible. They're smarter than me at everything, and yet I haven't actually been able to drop them in as a coworker right next to me. And every day,
Speaker 1:we try to replace Tyler. We say, Tyler, replace yourself. Yourself. He's just too good.
Speaker 2:But there's still there's still, like, an ambient level of anxiety that something's coming, and so I feel like you you do need to be prepared. You can't write it off entirely. But I'd be interested to hear about how you're thinking about, the goals that you could even set around, transitioning people through jobs, how you think about the AI job relationship.
Speaker 11:There's a couple of things. I the first thing is about AI education. We have to prepare the future American worker to be able to fully leverage this technology when they enter the workforce. The President signed executive order in April where he prioritized K-twelve AI education. The First Lady has gotten very excited about this endeavor.
Speaker 11:We're running something called the AI Presidential Challenge, which is a challenge that we're rolling out across the entire country where we have students from all 50 states participating in it, and ultimately it's gonna culminate in a in a sort of competition here at the White House and at the end of the school year where we can show kind of how students are using AI to solve some of the biggest challenges they face in their
Speaker 2:local It's like the presidential fitness. I used to have to run a mile and touch my toes, and now now you have to use AI. That's actually
Speaker 1:great. That's a presidential vibe. We think it's
Speaker 11:so But I do think it's important because at the end of velocity of change that you see in how education is thinking about AI is so interesting to me. It's kind of like, and if you guys even remember like two years ago when ChatGPT first came out, every university out there was essentially banning it. You weren't allowed to use it. You were violating the honor code if you ever turned on ChatGPT, and now there's no college student in the country that doesn't use it. So, I think the pace of change in how these models are being used in education is just so, so dramatic, and we have to get in front of it because what we think an eighth grader is going to be doing with AI when they enter the workforce, it'd be very, very hard to predict.
Speaker 11:So, what we try to do mostly in the K-twelve space is not necessarily teach kids how to leverage this technology, but teach them about how the technology works. The term that was used in the executive order was demystified.
Speaker 2:This is
Speaker 11:really Like teaching both children and teachers like, where does it work well? Where does it not work well? Why is it answering questions like this? Why does it hallucinate? Why does it not hallucinate in these cases?
Speaker 11:You know? And I think the more people understand the technology they're dealing with, they'll be able to leverage it much, much better no matter where they end up in the world.
Speaker 2:Yeah. I I I absolutely love that because I feel like the I mean, we we talked about this, the GPT psychosis thing. There's there's a very big difference between understanding that what you are chatting with is a robot, is a bunch of math, and just being mystified by it. And the same thing with you know, at some point, every parent needs to teach their kids that, hey. The the explosion in that movie, they didn't actually blow up the house.
Speaker 2:You know? They didn't act that that's a cartoon. And now you you also have to do that with AI generated images.
Speaker 1:Something I noticed. Yeah. This was a major AI related announcement. Did not have a I searched command f for a dollar sign. We didn't find it.
Speaker 2:Mhmm.
Speaker 1:Is that is that intentional? Is that, like, part of part of your focus of, hey. The the the government can catalyze the right sort of like progress and activity without just being a a capital provider. We've seen so many, you know, announcements from this year that are really just fixated on the biggest, you know, the biggest number. And this feels like unlocking the sort of potential within the the the existing ecosystem that's that's not being properly utilized.
Speaker 11:Yeah. For the Genesis mission, I think congress actually appropriated some money to, the Department of Energy this summer and some legislation that passed to to drive some of these AI related efforts. Mhmm. And we've used that as kind of the down payment on kicking off this program.
Speaker 4:Mhmm.
Speaker 11:I think what you're gonna be seeing in the next couple weeks, which is which we're really excited about, is commitments from a number of large private sector players on what they are contributing and donating to the Genesis mission. I think what's key here is that what makes the American innovation ecosystem so unique is the ability for us to bring all pieces of the ecosystem together to drive innovation. You have one part academia, one part private sector, and one part federal government. Reason why and the feature about The US innovation system that allows us to be so successful and have been the home for the greatest scientific and technological breakthroughs for the last two hundred years is that free market approach to innovation, and I think that's what the Genesis Mission brings together and sort of highlights in the best way possible that we are in this together with all pieces of the ecosystem working together.
Speaker 2:There there's been a lot of worry about going too far, doing too much AI, too too too aggressive about the build out, too much debt. There was this back and forth about the backstop. David Sachs, of course, said we're not considering that. But, have you thought any more about how what the role of the government is in moderating the amount of, of, like, sort of private sector AI build out and how that should even interface with the government at all? Like, what is the framework that we should be using?
Speaker 11:I think we are very focused on removing federal barriers to folks that want to participate in the AI revolution. For us, what we see is that if private markets and if capital markets are allocating dollars in a direction that say like, Look, we believe that we will be needing this level of compute to drive our future AI demands. We want to make sure that the bottleneck to that deployment isn't some federal rule around permitting and allowing these things to be built out. I have faith in the way markets are allocating dollars right now and I leave it to those capital allocators to make the best decisions possible for that capital. What we want to make sure is that like we are not an inhibitor to innovation.
Speaker 11:That some arcane rules about how and when you can build some certain facility in a particular place are not the reason why the data center we really need isn't built out. Yeah. That's the role that I think the federal government plays, and one of the three executive orders the president signed the day that the action plan was released was all about this. How do we get the federal government out of the way to allow the the the build out of these as as quickly as possible?
Speaker 2:Yeah. What about the like, going deeper in the stack? Obviously, there's been news around Intel. There there's a very rational reason to understand the pry prioritize, you know, having American control of the entire AI stack. How how has your thinking evolved on, just this idea of having a full control over the supply chain in America?
Speaker 2:Is that something you're spending time on or you're thinking about or your thoughts have evolved on?
Speaker 11:We are. I mean, it's it's so critical. Back to the great day in July when we signed all of our executive orders. The the third executive order was all about exporting the American AI stack. Mhmm.
Speaker 11:And I think, you know, if we rewind, you know, into Trump one when I was the the CTO of The United States at that time, one of the the challenges that I faced was traveling all around the world and trying to convince governments that they need to rip and replace their Huawei infrastructure.
Speaker 10:And
Speaker 11:at that point, you know, I think there was a big lesson learned by me and by a lot of people who served in in '45 about, you know, what are lessons learned from that experience? You know, in that moment, the PRC had a technology that was good enough and was priced very reasonably, whether it was for subsidy or who knows what, but it was priced reasonably enough where everyone wanted it and it ultimately was deployed for a big technological shift with five gs. Now, you fast forward to where we are today, this next phase of AI is orders of magnitude more important than the five gs rollout. Right now, governments all around the world in very few short years will all be running some sort of AI stack. They will be having some sort of chips that will be running some sort of large language model, and on top of it, there'll be important critical national applications.
Speaker 11:Everything from the way that hospitals are running to the way that tax is collected, and we want to make sure that The US is the partner of choice for that AI stack. Right now, we're at a great spot. We have the very best chips in the world and we have lots of them. We have the very best models in the world and we have a competitive ecosystem that it seems like every other week they're leapfrogging each other. Then on top of that, we have the best applications in the world.
Speaker 11:So, we are so committed to exporting that stack. We want to create something that is so compelling and so exciting for governments and people all around the world that they will want to use our technology. That's what we are building here at the White House, our partners at the Commerce Department and at the State Department to get that exported all over the world from South America to Africa to Asia to anyone who wants it because we believe that the same benefits that all Americans are gonna realize because of our great technology, we wanna share that with the world.
Speaker 1:Yeah. Final question, a little bit of a wild card. I'm curious, are you thinking about humanoids as a category? I've been really concerned that we're gonna repeat what happened with DJI where we allowed a company to basically destroy our domestic industry and flood the country with cheap, very good very good drones, but cheap drones. And I worry that you know, I think you can buy a UniTree robot on walmart.com right now.
Speaker 1:It's not it's not a concern today, but if we allow the country to be flooded, I would be very concerned about it in the future, and I'm curious if it's on your mind at all.
Speaker 11:It is actually. It's funny you say that. We were just actually speaking about this week with a number of my colleagues. I think the it is challenging. I mean, was a large, well known, top sort of shelf research university that I saw one of their one of their, like, magazines that they published, and there was and they were advertising how great they were.
Speaker 11:On the front of it was two unitary robots. I was like, Come on guys. Honestly, we can do better as a country. We have been the home for Boss Dynamics for over two decades. I think to me, this is an opportunity where we should think about it in terms of the larger AI stack.
Speaker 11:If you start building from chips all the way up, the ultimate manifestation of all this is where a lot of these ultimately robots play out. It's this marrying of the physical infrastructure with the digital itself. I think we need to do a lot more as a country to be able to propel that industry forward to make it economical for the adoption to happen. It goes back to something I talked about a little earlier. It's a lot about trust.
Speaker 11:If you think about the dynamics oftentimes in the global marketplace, funny enough, the Europeans tend to be a lot more quick adopters or early adopters a lot of this technology just because of the issues that they have with some of their workforce. So, think for us, we want to create an environment where we can build these robots into our economic growth plans here in The US and think very critically about the way that we want safe, secure, and trusted technology used by Americans in America. If we see foreign companies that are not safe, trusted, and secure and are compromised, there's lots of tools that we have in in our arsenal to to to protect our ecosystem from it. And The US Government, for for example, banned DJI for use by by the federal government, then there's lots of other examples like that.
Speaker 2:Yep. Okay. Actually, question. Do you fish? What's the biggest fish you've ever caught?
Speaker 2:We'd like to ask that to everyone that joins the show.
Speaker 11:Oh, man. I thought that was coming. I I actually do not fish. So if you guys ever wanna take me fishing,
Speaker 8:I I am I am
Speaker 1:don't I haven't either. So we can we can go together and and figure it out on the fly.
Speaker 2:Yeah. Yeah. Well, thank you so much for taking the time to come talk to us
Speaker 1:on your busy day. Always welcome.
Speaker 2:On the Genesis Mission. We're very excited for this. And, have a great, Thanksgiving. Happy Thanksgiving.
Speaker 1:Happy Thanksgiving.
Speaker 11:You guys too. Let's do this again soon.
Speaker 2:See you. Absolutely. Cheers. Let me tell you about ProFound. Get your brand mentioned in chat.
Speaker 2:Can see reach millions of consumers who use AI to discover new products and brands. Let me also tell you about Turbo Puffer, service vector and full text search, build from first principles on object storage, fast, 10 x cheaper, and extremely scalable. Founder mode is right. We have Sebastian from Klarna in the Restream waiting room. We're gonna bring him in to the TVP in Ultradome.
Speaker 2:Well, how are you doing?
Speaker 1:See you
Speaker 3:again the last time. Long.
Speaker 1:The last time we hung out, it was just another it was just another day at work for you. Yes. You just stopped by. Nice seat. You you did your IPO and you jetted back home.
Speaker 1:Yes. But it's great to it's great to be back.
Speaker 2:Yeah. For kick us off with a review. What's it been like being a public company CEO for a couple months now?
Speaker 5:Well, we we said to ourselves on the management team, like, we're never gonna watch the stock price.
Speaker 1:Never ever.
Speaker 5:And then and then every day I
Speaker 6:was like, what? Why why didn't you go up? Fuck.
Speaker 5:You know? And then and then somebody, like, came to us, guys, just, like, put yourself next to all the other stock. And I was like, oh, yeah. It's moving the same way. Got it.
Speaker 5:Okay. Got it. Got it. It. It wasn't just us.
Speaker 2:Yep. So Makes sense. Well, big news, on Tuesday, today. Please, break it down for us. What's what's the news?
Speaker 6:No.
Speaker 5:I think it's you know, I think I was it's kind of funny because I like, about a year ago, I was, like, giving crypto a second chance. And I was always, like, you know, I was a little bit of the on the skeptic side over the years, and partially it's because, like, I was my LACMA test is, like, how is this gonna help my mom. Right? Totally. And and as much as, I'm getting excited about, like, financial revolution, you know, kill the central banks or whatever.
Speaker 5:Sorry.
Speaker 4:I shouldn't
Speaker 1:have said that.
Speaker 5:I'm gonna requote. You know, bring financial liberty to the world. That's the way. Yeah. And those things.
Speaker 5:The point is, like, that doesn't get my mom much excited. She's like, what? Can I just pay cheaper or can this be faster? Like, she doesn't really care that much
Speaker 2:about The noise in the industry was insane. I mean, it was so many, just regulatory arbitrage moments, so much, just, like, fraud and grift and also just, like, pumps and dumps and all sorts of just, like, memes and things that weren't outright frauds but had just, like, total was always there. There was always a little bit. Because then the technology was always
Speaker 1:and it was
Speaker 2:a little bit real.
Speaker 1:Reason. And I'm sure I I imagine, like, what like, I I'd love to understand how you how your thinking evolved on stablecoins over time. Yeah. Because back in 2021 I
Speaker 5:think what happened was some close friends of mine called Sequoia Mhmm. Said, like, Sebastian, you really have to
Speaker 2:take a second look at this.
Speaker 5:And and I was like, okay. Fine. I'll do it. And they introduced me to some amazing founders Mhmm. Among among them, Bridge
Speaker 2:Yeah.
Speaker 5:That we're now working with. And so I gave it a second chance. And I listened to the stories and I realized, yeah. Okay. So I've been wrong.
Speaker 5:Technology has now moved ahead. It's now fast. It's now efficient. It actually solves real real problems. Mhmm.
Speaker 5:And so we and then I wrote that on X and I was like, nobody's gonna care because we're like, we're the last fintech in the world. Yes. It's not gonna make any news. But it was surprising, like, I think over over a million people views on that on that post. And and since then, we've been just working hard on, like, how do we integrate this into our stack and what can we do.
Speaker 5:And today, announced that we're doing the Klono stablecoin Mhmm. Which is one of many things which we're doing with Bridge and Tempo, which is, you know, together with Stripe and the team over there. So so that's really exciting. But, obviously, you know, there's more to come. It's just that, like, we're we're testing the waters and trying trying out what will work for us.
Speaker 2:So, yeah, walk me through, what the first few implementation points look like. If I'm going and I'm paying and I'm on a checkout page, right now, I can check out with Klarna. At what point do I actually interact with Klarna coin, the stable coin? When does it actually come into the workflow?
Speaker 5:So so far, the the start of this actually is just that, like, we obviously wanna bring these services to the benefit of our consumers in in their day to day Mhmm. Ex you know, using a client. I mean, we have a big neo bank ambition. Right? And we have over a 100,000,000 users worldwide, but most of them will only use us for a single transaction.
Speaker 5:Thank you. Sometimes it's like, you know, a lot of those buy now collater, but actually over 20% of them are debit where people pay the full amount as well. So so it's it's a mix. And now we're trying, you know, doing we're trying to offer ourselves more advanced services, more neobank services. Right?
Speaker 5:So we have our card. It's pretty cool. Like, you know, we are now 3,000,000 active cardholders. A quarter ago, we had zero in The US. So exactly.
Speaker 5:I'm gonna drop a lot of numbers. Gonna get a
Speaker 3:lot of beeps.
Speaker 5:So so that was like yeah. So that's been great. But, obviously, we want to add peer to peer. We want to add the ability to send money and so forth, and then we'll be looking at different solutions. But but but what's interesting, I think, here is that, like, even though that's a natural next step of, you know, offering using Stablecoin for that because it's a very efficient way to send money fast and at at low cost.
Speaker 5:And we also actually realized that, look, I mean, we're processing over a $100,000,000,000 worth of volume every year, and we move ourselves quite large money between The US and Europe and so forth. And this may actually be very efficient even for our treasury department to use as a way to to move money. Right? So we've seen that there's a tremendous number of use cases, maybe more than we realized when we started looking into it that's exciting and that can drive you know, anything that obviously drives our efficiency will also allow us to offer services at lower cost and more value to our customers. So
Speaker 4:Can
Speaker 1:you break down specifically what's happening at each kind of level of the stack? So you have Bridge, which is, from my understanding, the infrastructure that you're using to actually issue the token. Then you have Tempo, which is the blockchain in which you'll be moving it around on. Is that and then and then you have, obviously, the the product layer, which is the interface that consumers will use to move around. Is it USDK?
Speaker 1:What what what is the ticker?
Speaker 5:I think it's USDK. I think you've described it pretty well. I was like, thank you. That's a good summary. I'm
Speaker 1:not Yeah. Yeah. Because I'm just trying to And then you also have there's a corporate treasury use case where you could you're saying you could use the same token internally as well.
Speaker 5:Yeah. I mean, yes. Exactly. I think also then people discuss a little on the merchant side, but but the truth is that we mostly today distribute through Stripe and Adyen and the big PSP. So most of the kind of merchant relationship happens directly with them.
Speaker 5:So to us, it's mostly what we can do on the consumer side. But I think there's more opportunities. I mean, this is
Speaker 4:just like, again, people are like, oh, why did you
Speaker 5:do it this way and not that way? Why didn't you use Solana or Ethereum? And why didn't you, you know, whatever. What about Bitcoin and so forth? And to me, it's like, yeah, but come on.
Speaker 5:This was just like one first thing that we now announced, and, obviously, we are working on more things and we wanna utilize these technologies to more use cases. And we have more things, but we are not yet direct yet yet to announce them and and talk about them. So more to come.
Speaker 2:Fantastic. Last question from my side. Who who do you think is or what you don't need to say a name of a company, but, like, what what type of, what type of player in the financial industry loses out most if stablecoins really take, off? It feels like at a certain point, we're just shifting take rates around. There's a lot of different transfer services that could benefit a lot from higher speeds and lower fees.
Speaker 2:Seems like consumers could benefit a lot. But do traditional payment rails suffer? Do government suffer? Like, what category really needs to be Well, I
Speaker 10:I think
Speaker 2:on their back foot right now?
Speaker 5:To me, it's really and I actually talked about this a little bit on our earnings calls as well is that I actually think, like, to me, I I put the whole crypto thing in this wider AI, change that's about to happen. Right? And if you if you look about it, both Fin and Tech have been extremely inefficient market Mhmm. Which is why you've seen the excesses in profits and excesses in, you know as I as I quoted there, like, you know, the Gourmet cafeterias used to be called culture and now they're gonna be called overhead. The the point is that, like, there's been this huge success because it hasn't really been that strong competition.
Speaker 5:And why has there been lack of competition? It goes back to kind of classical microeconomical theory, which states that if it's hard to compare two products, if it's if, you know, too many legal terms that are hard to understand and so forth, then people will be fooled and will take products that are less good for them. Right? And AI and new technologies brings a fantastic amount of transparency. You can just ask, compare these insurances, compare these banking products, what is the best one?
Speaker 5:Compare these credit products, which one is actually the best one for me. Right? So that's gonna change. The second thing is the major one, which is very connected to crypto, is switching costs. Mhmm.
Speaker 5:So the big reason banking isn't more competitive is simply because it's such a hassle to move. Yeah. You know, like, wanna bring all my stuff from this bank to that bank.
Speaker 2:Yeah.
Speaker 5:And and people just don't have that energy. Right? Like, you don't have the energy and all the accounts and the salary coming in and all that stuff. Right? So what happening is with technologies like crypto, with AI, and the and the combination of that, what you're gonna see is you're gonna see switching costs coming down to almost zero.
Speaker 5:Right? It's just gonna be much easier to move between different services. It's And just gonna put this massive competitive pressure on this industry. I mean, financial services make over $4,500,000,000,000 in profit. That's the profit pool that we're after.
Speaker 5:And then tech and advertising and tech is another, you know, $500,000,000,000. That's a trillion dollars in in, profit pool. And so what I think is gonna happen is you you just like if you are willing to be customer obsessed, efficient, you know, and with efficiency, operational efficiency, crypto plays a role because it can help you be much more efficient. You can move faster at lower cost and so forth. Then the players who take the advantage of these technologies are going to make a massive dent.
Speaker 5:And the the benefit, I believe, and may you can call me naive or you can call me, you know, optimist, but, like, I believe that the value of this is all these excess profits that we see in banking, they're gonna come back to consumers.
Speaker 2:Yeah.
Speaker 5:They're just gonna make consumers are gonna pay less for higher quality services. And some financial institutions will lean in and they will transform themselves and they will be more customer obsessed, there will be less marble offices, less beautiful, you know, buildings and all that stuff. And there will be more of just, like, waking up every morning just like a restaurant or any other business, for the sake. We actually wake up every morning and you're like, how do I bring my customers in? How do I make them happy?
Speaker 5:And how do I run my business so I'm operationally efficient? Right? Yeah. And that's a huge difference.
Speaker 2:And I
Speaker 5:think crypto plays a role in that. So I think that's what's coming for fin and tech. And if you're willing to be that customer obsessed and run those operational efficiencies and be smart and use these technologies, there's obviously tons of opportunity of growth and and and you can build trust with your customer base. But if you're gonna sit there and still continue making the kind of profits you are today and think that nothing's gonna change, well, eventually, you'll wake up. Right?
Speaker 5:Just like, you know, whatever airlines did when low cost airlines came in. You know, we've seen this over and over again. They're like carriers when the low cost carrier things came in. Like, it's it's happened before. Right?
Speaker 2:Yep.
Speaker 1:Absolutely.
Speaker 2:Well, thank you so much for taking the time to come chat with us. We will talk to you soon. Have a great rest your day.
Speaker 1:Get the update.
Speaker 5:Thank you.
Speaker 1:Good to see you. Talk soon. Cheers.
Speaker 2:Before we bring in our next guest, let me tell you about public.com investing for those who take it seriously. They got multi asset investing, and they're trusted by millions. I'm also gonna tell you about numeral.com. Let numeral worry about sales tax and VAT compliance. Compliance handled so you can focus on growth.
Speaker 2:We have David from 1Password in the Restream waiting room. Now he's in the t b p o TBPN Ultrafilm. Welcome to the stream. Welcome back. We have a big update for you.
Speaker 2:Since you came on the show last time, we onboarded the whole team on that one password.
Speaker 1:John, we were using it individually. There were some pass passwords being stored in the notes app. We corrected that.
Speaker 2:Yes. Yes. Yes.
Speaker 8:I'm glad I was able to shame you into into into action there. So
Speaker 2:Yeah. Yeah. This is really customer development, getting your hands dirty, rolling up your sleeves. You go on the podcast with 10 employees, you physically tell them, download my app. And it worked.
Speaker 2:It worked. It worked. You can But
Speaker 8:anyway One customer at a time. Thank thank you again for your trust both with your business and your, and your personal lives.
Speaker 2:We're yeah. We're we're very happy. It's been a huge upgrade, and I I I think it's gonna sail, to being a, you know, valued piece of infrastructure in this organization for many years. But we're also very excited that you're you've been on a tear. Your business is doing better than ever.
Speaker 2:Give us a little update. What what's new in your world?
Speaker 8:Yeah. So, you know, we we have a little announcement just to refresh some of the statistics of the business. So a couple weeks ago, so we are over $400,000,000 of ARR.
Speaker 1:And we're Woah. Known There you
Speaker 8:go. Love it. The spinning head.
Speaker 1:Spinning head
Speaker 8:We've done that. We've grown to that level profitably all the way from inception, which is really cool, you know, durable growth profile. Profile. We continue to be very profitable. We now we're known as a consumer app for for a long time, but
Speaker 4:Yeah.
Speaker 8:Now nearly 80% of our business is selling to business customers. Yeah. 180,000 business customers use the product. A 180,001 now because of you guys, so thank you for that. Yes.
Speaker 8:You know, we support over 1,300,000,000 credentials that are that are managed in our system. And we have, you know, over a million developers using the product. So, you know, we feel really good about the the trajectory that we've been on. We've also in that announcement, we also announced that we've we've added to the team. So we got new leaders driving ecosystem and and the revenue side of the business, enhance the the tech side as well.
Speaker 8:Yeah. We're really just setting ourselves up for the next chapter here. And, you know, as we chatted last time when we when we were together, we just see the opportunity around AI is is really something significant for us, and we're going all in.
Speaker 2:Yeah. I wanna talk about that because, it feels like there's is there a fight coming? Because credential management on the, developer tool chain side, the API keys, that's traditionally been a completely separate industry, a completely separate you know, I don't even know if you guys run into each other at industry conferences. It feels like a very different world. One's a developer tool.
Speaker 2:One's a consumer tool that you use with your family, then maybe you wind up using it at work. There's single sign on. There's all sorts of different ways to to manage, credentials. How much are they blurring? How quickly is this happening?
Speaker 2:How are you thinking about setting yourself up for the world where I mean, Sholto from Anthropic was on the show yesterday saying, we're creating a coworker.
Speaker 1:Digital coworker.
Speaker 2:Sounds like a digital coworker who needs some passwords every once in a while. Are they gonna get it?
Speaker 8:Absolutely. I think, you know, the traditional identity systems that have been siloed and and and sort of different parts of the puzzle and really hardwired in a big enterprises over the years. They don't really they're not set up to support this federated dynamic environment where applications spring up and agents need access that are very, very specifically scopes to what they're trying to accomplish. And then they need to be sort of tracked and managed and many times revoked. And so that system of identity and access management really doesn't exist.
Speaker 8:And we're in really good position to support that. And we're doing a bunch of things already to help people use AI tools securely. I'll give you a couple examples. So we were a launch partner with Perplexity's Comet Browser. I'm not sure if you've seen that.
Speaker 8:But then shortly thereafter, OpenAI and ChatGPT Atlas came out. And immediately, both they and we got besieged by a customer saying, I need to be able to use one password with Atlas. I'm gonna
Speaker 2:use this
Speaker 8:thing unless it's so we got on the phone with them, and we we started working together with them. And quickly, we made one password available as a browser extension on on Atlas with a little bit of a workaround. And then just today, we announced the release of a fully optimized, you know, onboarding experience optimized for the the the workflow experience and the Atlas browser as well. And so what we learned is, like, look, customers, they wanna use these tools, but they wanna be able to use them safely and securely, and they wanna be able to have trust. So that's what we've all always been about is bringing that trust to the table.
Speaker 8:And so we'll be wherever our customers need to be. Last time we were talking about the headless browsers around around a browser base, but, like, with Perplexity and Atlas, you know, our customers want to be able to use these tools without having to give their credentials over in raw form. So that's one aspect of it. The other is what's really interesting is, you know, we're moving from applications being developed by software engineers to being developed by everybody. And it's amazing how much of the agentic applications that are being created are not necessarily by by software developers.
Speaker 8:And so it's great. It's very powerful. The whole organization can figure out ways to leverage it. But again, if you need API keys to be part of the, you know, in in the environment that you're you're building or SSH keys, you you need to be able to actually have those things secured. And so our developer tools, they sync with AWS, sync with secrets manager at runtime.
Speaker 8:They allow you to to put a pointer to environment file that tools that we build so that your credentials are always encrypted end to end, fully track traceable, fully revocable. And so that's the beginning of what you'll see. And then, you know, where we're going from here, you know, discovery of agents, governance around it. How does it interact with the observability systems? There's a whole greenfield of things there that we're really well positioned to participate in and really help define the standards.
Speaker 8:So, you know, we're we're going for it. It's it's a very exciting time.
Speaker 2:How are you thinking about resiliency? Do you have any tips for folks building, you know, mission critical systems these days? It feels like we were fighting an outage with AWS at one point. Cloudflare went down. We don't have nearly the resources that you do, I'm sure.
Speaker 2:But what tips and strategies have you used? Because I feel like you're definitely gonna hear if, one password goes down. Right?
Speaker 8:Yeah. You know, look. We we, we are a Cloudflare customer. Yeah. Right?
Speaker 8:So we we our marketing site was down. Our service wasn't down. Sure. We or So, you know, we are using, you know, obviously, the redundancy and
Speaker 2:Yeah.
Speaker 8:And fell over procedures, we've got you know? We we come from a security centric approach. That's probably the what's differentiated us from a lot of the other players in the space. Like, security is job one and job 10, and, like, nothing else matters until we're sure that, everything we're doing is at the utmost security. So we've got a lot of resilience built into the way we do it.
Speaker 8:But I think just generally, people need to be aware. Like, it the threat profile is so much more hostile than it's ever been, and it's gonna get a lot worse. I'm I'm sure you did a bunch of of work on on the the disclosure that Anthropic put out around that. And it's not just I mean, Anthropic, you know, as you know, they they have, like, nation state level security, know, enforcement. They have, like, bunkers and all kinds of stuff that they gotta worry about.
Speaker 8:Right? Because they're they're, you know, hugely a big target. But but it's not just the biggest guys anymore. It's really anybody can be a a target because you can do really sophisticated social engineering at scale with almost no effort at this point, and it's gonna get worse and worse and worse. So the number one thing that people, you know, will expose is is weak credentials.
Speaker 8:Right? So it's another really good spot for us. Like, the credential hygiene is more important than ever. So whether it's you're using Atlas and you're a one password customer, great. Make sure it's connected.
Speaker 8:If you're not a one password customer, you should go get it if you wanna use Atlas. Right? And if you're a developer and you're building an application and you're not and you're hard coding credentials or SSH keys, into files, don't do it. Get a one password license, super easy to use, keeps you secure, keep everything ever locked up, and, you know, we'll maybe we'll get another new customer out of this.
Speaker 2:Love it.
Speaker 1:What's your timeline to a point in time where the average American on, let's say, a weekly basis will be sending an agent out to do something for them and the agent, needing to actually utilize the, you know, like, login infrastructure of the user. I'm talking about the imagining the workflow where my agent's doing something and I get a maybe a a one password push notification that's or I don't know exactly how the workflow would work, but saying, hey. I wanna do this. Do you approve it or not? And then I hit, like, yes.
Speaker 1:Like, basically authorize the agent.
Speaker 8:So that's exactly what's happening with Browserbase, for example, right, in the headless browsers that we're doing exactly. It's low friction user verification so that allows you to keep things secured. Look. We're seeing tremendous uptake on the you you know, Atlas was a really was enlightening to see how many people are actually trying to sort of utilize the browser and and have it do things on its behalf. Certainly, the other partnerships we've had.
Speaker 8:We're so early days on it, but I think when we're gonna hit this inflection point where people realize I mean, I'm starting to see how valuable in both my professional and personal life the tools can be and just shortening my day. And, obviously, you know, I wanna make sure I'm doing it securely. I think most people are gonna be in that mode before we know it. And so we just wanna make sure we're available for our our customers when they when those moments come so that they can do so securely.
Speaker 2:Last question. What's the biggest fish you've ever caught?
Speaker 8:Well, I'm more of a fly I'm more I enjoy fly fishing more than I do, like, deep sea fishing. You know, getting to sit on a big boat and hauling
Speaker 2:in marbles. Is the ultimate hack if you just wanna catch the biggest fish. Right? It's not
Speaker 8:somebody else catches it and you're trying to really yeah. My son my son prefers fly fishing, so I I
Speaker 4:You do fly fishing.
Speaker 2:He likes
Speaker 8:to catch a big bass.
Speaker 2:Where where is the best fly fishing spot?
Speaker 8:You know, I Utah.
Speaker 2:You like Utah?
Speaker 8:Utah and Montana. Utah, fish are a little smaller. Montana, little bit bigger,
Speaker 2:but,
Speaker 8:you know, two two really good spots and, you know, just just, you know,
Speaker 2:give us We're gonna become we we we're not we're never gonna leave this building, but we're gonna become fishing experts. We're never actually gonna Just through our guests. But just through asking every guest a little bit more of
Speaker 1:an Eventually, this will be a fishing show.
Speaker 2:I like it. I like it.
Speaker 8:Get yourself a guide. Go on a fly fishing trip. Take a take a weekend. Go to Montana. You'll you'll love it.
Speaker 2:Thank you so much for coming on the show.
Speaker 1:Alright. Happy Thanksgiving. We'll
Speaker 2:talk to you soon. Let me tell you about Vanta, automate compliance and security. Vanta is the leading AI trust management platform.
Speaker 1:One thing one thing that's cool, back in 2019, 1Password raised from Excel.
Speaker 2:And
Speaker 1:when they announced it, they said Excel will be investing 200,000,000 for minority stake in 1Password. And you don't you don't see that like positioning a lot. Yeah. But I mean, was a very minority stake, obviously. They they put in they put in about 200, think, at
Speaker 2:Mhmm.
Speaker 1:Was it 200 on 1 or 2,000,000,000.
Speaker 2:But Mhmm.
Speaker 1:Anyways, absolute beast of a business.
Speaker 2:Well, up next, we have Keller from Zipline. We're very excited to talk to him. There's some big news. The eagle himself. Yeah.
Speaker 2:Get that ready. First, I'm gonna tell you about Figma. Think bigger, build faster. Figma helps design development teams build great products together, and there's someone who built a great product with lots of talented individuals. Keller from Zipline.
Speaker 2:Will bring him in as
Speaker 1:soon as he's ready yet. But We can go over
Speaker 2:We can go over the timeline.
Speaker 1:Yeah. We have a post here. Somehow no. I'm gonna jump. Where you're going.
Speaker 1:Okay. Somehow, David Yulovich, former guest of the show said, turns out huge swaths of the BS on this platform that claims to be from The US is all foreign. Then this is Somebody appeal quoted and somehow the a 16 z account is based in Canada. I really don't
Speaker 2:It's very funny.
Speaker 1:I really don't know how this this is actually possible. I wanna see if it's been updated.
Speaker 2:I did check all of her accounts and I think we've been marked safe. I haven't checked actually most of the team, Tyler. I don't know. Maybe just secretly.
Speaker 1:I just know somebody I I have so many friends at Andreessen. I don't know how
Speaker 2:Why does Tyler's I don't know.
Speaker 1:None of them are Canadian.
Speaker 2:Why does Tyler's account say it's based in North Korea? I don't understand that.
Speaker 1:I know.
Speaker 2:Have you been to Pyongyang recently? Is that where you're going over the holidays? Yeah. You said you're leaving. This is misinfo.
Speaker 1:He goes, oh, I have a dentist appointment. I can't come in tomorrow.
Speaker 2:I can't come in. He's
Speaker 1:for a little touch base.
Speaker 2:Yes. Yes. What what what happened with this meta whistleblower sister situation?
Speaker 1:Don't know. Dell says I'd love to see
Speaker 2:TVP discuss the meta whistleblower story right now.
Speaker 1:Be feared. Do wanna come back to this.
Speaker 2:But we have our guest here, so we will bring in Keller from Zipline. Welcome to the show. From the floor. Fantastic setup.
Speaker 5:Best
Speaker 1:How are you doing? Comms team in the game. Good to see
Speaker 2:you. How
Speaker 11:are you guys?
Speaker 2:We're fantastic. You look great. Give us give us some updates. Give give us, what is the latest news in your world? Very excited for everything that we've been seeing in the timeline.
Speaker 2:I wanna go into all the jokes about, what what what happens if you shoot one of these down. But first, let's get the serious update. Let's get the serious questions out of the way.
Speaker 10:I mean, yeah, there's a ton going on. The thing we announced today is that Zipline just signed a $150,000,000 contract with
Speaker 7:the US state of government.
Speaker 10:Yeah. You know, to triple the size of our lifesaving autonomous delivery network across Africa. We're gonna go from serving about 5,000 hospital hospitals and health facilities to over 15,000. Add about a 130,000,000 people to the network who don't have access today.
Speaker 5:Fantastic. And the
Speaker 10:last cool thing about that is that that 150,000,000 comes with up to $400,000,000 of co financing commitments from the African governments themselves. Okay. So, you know, this is not this is not
Speaker 2:Just straight on the taxpayer. Yep.
Speaker 10:Yeah. Exactly. This is actually, like, encouraging investment in this kind of infrastructure.
Speaker 2:Yeah. So was this was this delayed because of the USAID pullback? There's been a lot of, like, back and forth on how much The US would be investing internationally, what would be happening. Has the dust kind of settled there and there's now time to actually go do a partnership like you just did? What's the kind of state of the union?
Speaker 10:Yeah. I mean, you know, obviously, earlier this year, that was like the first phase of a big shift in terms of how The US is interacting with, developing economies. I think this new vision that's now being talked about by the State Department of commercial diplomacy
Speaker 1:Sure.
Speaker 10:The whole idea is let's not, you know, let's not treat these countries as charity cases. Let's actually treat them as allies and trade partners, and the good news is these countries have been saying for a decade that they want trade, not aid. They're sick of low quality services provided for free by NGOs. What they want instead is high paying jobs Mhmm. Entrepreneurship, technology.
Speaker 10:And the thing is, like, that's what The US has to offer, you know? Like, we can deploy AI and robotics infrastructure into these countries in a way that will save lives and kind of turbocharge their economies.
Speaker 2:So a 150,000,000 from the US State Department matched with 400,000,000 from the partners internationally. 10,000 health facilities. How many actual drones is that? How are you actually thinking about scaling your like, what does this allow you to do? Are you gonna be staffing up, hiring tons of people?
Speaker 2:Is it just build another factory? Is it a dedicated factory? Like, walk me through how you plan to actually use this money over the however long you're planning to work on this particular, growth, initiative.
Speaker 10:Yeah. I mean, look, in a way, this is coming at the worst possible time because, as you guys know, The US business is growing really, really fast.
Speaker 2:Yeah. We see it
Speaker 1:all the time. Your hands
Speaker 10:for I'm here, yeah, I'm here on the manufacturing floor.
Speaker 8:Yeah. I mean,
Speaker 10:you can see, like, dock electronics happening over here, zipped platform two, zipped manufacturing, and then if we were to go straight behind the camera right now, we're just opening up a new 100,000 square feet of manufacturing facility that'll produce both the platform two technology as well as accelerate manufacturing for this specific contract.
Speaker 5:Yep.
Speaker 10:The you know, we'll we'll we're in total, this manufacturing facility is capable of building about 20,000 autonomous aircraft a year, and it's all happening in South San Francisco. So this is kind of this is the cool part of this compact, which is that, you know, this is not just a big deal for all these African countries that are now leading the world in terms of deploying autonomous infrastructure to save lives. It's also really good for The US because we are sort of securing US technology and manufacturing leadership for the decade to come. This is creating high paying jobs in The US, and it's accelerating all of our manufacturing efforts here.
Speaker 2:Okay. Let's shift to what's actually going on here. You know, we've we've seen the initial partnerships that have rolled out. What have you learned most recently about or what has surprised you about the the actual application of the technology, the adoption? Like, where are the underrated use cases beyond the the meme that I'm sure will follow you forever, which is the the private jet for your burrito.
Speaker 2:And so get ready for that one to be around forever. I mean, we just had Sebastian from Klarna on and he and his entire, you know, business, which serves all sorts of different, customer bases has collapsed to buy now, pay later for your burrito because they did a partnership with
Speaker 1:Burritos are powerful. I think it's actually a powerful. It's a bullish indicator if your business is getting burrito memed.
Speaker 2:It is. It is. But but, yes, where do you see the shape of The US business going? Where are the exciting developments these days?
Speaker 10:I mean, look, you know, on you know, Saturday, Zipline hit an all all time new record number of deliveries across The US. Then on Sunday, we blew that record out of the water by ten or fifteen percent.
Speaker 5:Mhmm.
Speaker 10:So, you know, it's like every day is basically a new record at this point as a company. I would say the most interesting things are it feels as though we accidentally, like, stuck a pipe into the Pacific Ocean. Like, demand is so vastly outstripping our ability to build capacity for this kind of service. And keep in mind, I mean, right now, you know, we deliver products in two to three minutes. So even from, like, when a customer presses a button to have something delivered to their front yard or backyard or front doorstep, is typically around fifteen, sixteen minutes.
Speaker 10:And so it is very magically fast. That results in customers changing their ordering behavior. Like, you know, a lot of our customers say they'll grocery shop once a week, and then they'll order from Zipline three to four times a week. So people are using Zipline more than the average Amazon Prime subscriber uses Amazon Prime. And not only that, but one of the big changes just since, you know, I was last on with you guys is that a lot of these restaurants are really accelerating.
Speaker 10:We're now doing 15 to 25 of deliveries from these restaurants that we've integrated with. So we are similar size on a per delivery basis to the big delivery platforms. And so I think, you know, maybe people still think, Oh, the technology is like sci fi. It's like years away, and it's funny sitting here thinking like, Wow. I mean, this is like completely normal in the neighborhoods that we are, that we're serving.
Speaker 1:Mhmm. Talk about the actual experience of getting, let's say, items from a restaurant. We had David Chang on. He was excited about drone delivery and the technology.
Speaker 10:I tweeted at you guys, and I Yeah. We're gonna we're gonna we're gonna try to get we're gonna try to deliver for him in
Speaker 1:Yeah. Yeah. And and specifically, he was saying he didn't think it would solve the the, like, delivering something hot from my point of view. If I'm used to getting something in twenty, twenty five minutes and then you deliver it in three minutes, like, that feels like it will be a material improvement. So I I I wasn't I didn't quite understand what what his point was.
Speaker 1:But what's the actual experience been like for people and and what what's kind of the average speed up in terms of delivery times that you're seeing?
Speaker 10:I didn't really understand what David was saying either. But look, like, you know, our comms team hates when I talk about this, but, you know, like, one of the first food deliveries we did, the customer badly burned their tongue Oh, on the
Speaker 2:food. Okay. Yeah. I can see why they don't like this.
Speaker 1:And I heard That's the restaurant's fault. Yeah. Yeah.
Speaker 2:It's kind of a bad
Speaker 10:actually, you know, we should make this like a core part of the marketing. Like, that is crazy that customers are so not used They're so used to getting like fries Yeah.
Speaker 2:That are
Speaker 10:forty five minutes old, and like ice cold and soggy and gross, and food that tastes bad and milkshakes that are melted, and we just put up with this shit, Like, we're completely used to it, and so, you know, I really think this is gonna, you know, in the same way that maybe David's expectations are gonna get kind of reversed, like it's totally happening with all the customers. When you can get something delivered and there's only, you know, two or three minutes from when the thing comes out of the oven to when it is delivered to your front doorstep, that is a way different customer experience. I think, actually, people are underestimating the difference in the quality of that experience.
Speaker 7:Yeah.
Speaker 10:Like, food tastes really good. It's almost like you're having an in restaurant experience
Speaker 2:Yeah.
Speaker 11:At home.
Speaker 2:I wonder so I remember when the delivery when the delivery boom happened and all of a sudden people were ordering way more food, and it was really like a TAM expander. There were obviously ways to get delivery. You could order a pizza thirty years ago on the phone. They would deliver it. But when it became an app and the market expanded so dramatically and people were starting to, you know, DoorDash and Uber Eats, like, every night, lots of people did this, the market grew, and it actually changed the nature of our food.
Speaker 2:And we got ghost kitchens, and we got these funny knockoffs. Like, there's in LA, there's Sugarfish, and then I saw one that was, like, sweet it's like they they will deliberately try and change the names as close as possible. And you get these, like, kind of restaurants that only exist because of the new technology. And I'm wondering what you think of the impact, if there will be a change in the nature of the food or the nature of the restaurants just because the, the the the delivery time goes down or because of the shape of the box. Like, if you can't do a massive, you know, six foot pizza, maybe, you know, some smaller prod, products like Emerge is like the dominant form factor.
Speaker 2:And and the restaurants conform first foot pizza, John? I don't know. The size of this table. I don't know. Yeah.
Speaker 2:Yeah. Yeah. I I you know, yeah, I the the kids' birthdays. You you see those?
Speaker 1:Yeah. They're pretty big.
Speaker 2:It's not six feet. It's not six feet. You get my point. You know, will there be restaurants that are like, okay. We're going all in on Zipline.
Speaker 2:We're thinking about developing meals from First Principles that fit for the best possible experience on the Zipline platform, and then that becomes, like, a new thing that actually changes our culinary experience?
Speaker 10:I mean, I you know, I'm not an expert, but I I have a bunch of, like, hypotheses, and, I mean, I would say a couple things. Like, first of all, I actually think we have to do a ton of, you know, design of the food now to make it work for a system that, like, is gonna deliver the food forty five minutes later in ice cold, you know? And, like and also, there's a lot of innovation that has to go into the packaging, because I don't know if you're familiar, but, like, 60% of food delivery drivers report eating some of the food that they
Speaker 1:They're like, but only when it's really good. Don't really good. Only when it's at my top five favorite restaurants.
Speaker 2:One one fry. One piece of sushi.
Speaker 10:Sorry if I'm sorry if I'm ruining it for anybody, but like, you
Speaker 9:know, the so we have
Speaker 10:to innovate on like tamper proof packaging. We have figure out like safety, and we have to figure out reliability, and some percentage of things just get picked up and then never delivered, and a lot of things actually, the driver will accept the order, but then actually just never show up at the restaurant, then they have to throw out the food, remake it again. So, you know, I think there's a ton of inefficiency and cost in the system that people just don't think about, but you do end up paying for in fees and, you know, all the crazy fees that get added on top plus tip. I think another big thing that's gonna change is that, you know, this technology is designed to be able to fly out to 10 mile a 10 mile radius. And typically, it's not cost effective to deliver something with a car more than like three or four miles.
Speaker 10:And so that means, you know, it differs on by metro and where we're talking about, but like, that means that these kinds of systems, for any given restaurant, you're gonna enable about 10 times as many customers to receive instant delivery from that location. That's a big deal, and it's a bigger deal actually for, like, mom and pop restaurants or kind of local heroes versus a really big chain like Chipotle that actually has a ton of stores. Yeah. And so I think, you know, especially when you think about a place like LA, for example, where you have a lot of these different parts of the city that are hard to reach, traffic is terrible, you know, it can take an hour plus to get delivery of food, You know, this technology is gonna be, like, transformational, and you can deliver a lot of, like, the best, most beloved kind of local hero brands and make it universally accessible. By the way, on the universally accessible front, you know, some of the cities we're serving in Dallas right now I mean, just one city that I was looking at statistics for yesterday, 46% of homes are ordering from zip line Woah.
Speaker 10:In that city. And so I think people don't appreciate yeah, exactly. I thought it was like a map error when I looked. You know, people talk about startups getting like 2% market share, 5% market share. It's like, Zip Line in a few weeks, Zip Line will literally have the majority of homes in our service area ordering from the service, and that is like that's not a joke.
Speaker 1:How are you so so clearly clearly, it's working. Clearly, customers like it. There's an insane amount of demand. How are you pushing the team to move faster? Because at at the same time yeah.
Speaker 1:I know I know you want to, you know, be be practical about the rollout and and not get over your skis, but at the same time, I mean, people people in our chat are anybody that that sort of knows it exists, they start to become angry that they don't have it in their in their Yeah. Area, and they I'm sure there there's people sending you messages all day long asking you, when are you gonna be here? When are you gonna be here?
Speaker 10:So, yeah, we don't we're we're gonna be announcing something very shortly. We just started talking about it internally, but we'll be announcing the next two metros that we're launching in q one and q two. So look for that in the next week or two. You know, we are we are then gonna start accelerating and adding multiple metros a quarter starting in the, second half of next year. So we are trying to move super, super fast.
Speaker 10:Hardware companies are hard in that, you know, you have to scale all these different parts of the business simultaneously. It's in the name. And also, it's like, you you know, you gotta make really sure that you don't accidentally bankrupt the company, and actually, the faster you're growing, the easier it is to back bankrupt the company. Totally. Because, like, you know, these numbers, when you're building 20,000 autonomous aircraft a year, the numbers actually start to get really big.
Speaker 10:You gotta make sure that, like, the hardware is validated and, like, you have, you know, sites that these that the hardware can go to and begin operating. You've to make sure that aircraft utilization is high. You have to make you know, there's there's a lot that has to move in tandem in order for the business to work. So, I mean, to put it into perspective, right now, flight volumes have been growing about 15% week over week for the last thirty weeks straight. We are now planning for next year.
Speaker 10:Yeah. We're planning for next year, and we actually just reforecasted the entire business, and we are planning to actually double our growth rate next year relative to what we were planning just at the beginning of this quarter. It's yeah. And I don't know how much I I can, you know they they you know, we are we are definitely anticipating, like, exponential growth.
Speaker 2:No. I feel like you've given us enough to do a More than 10. At this point.
Speaker 10:It's fantastic. Yeah. Exactly.
Speaker 2:Just just send it straight to Wall Street.
Speaker 1:I appreciate it. This has been So exciting.
Speaker 2:Congratulations again. It's always a great time.
Speaker 10:You guys gotta come to Dallas, I think. Yeah. I think it's probably at a point now, you know, when I was in Dallas last week, like, we were just hanging out at all these different, you you know, these different neighborhoods that are using zip line, and there were neighborhoods where I saw more Zips than I saw cars. Wow. And so I don't you know, it's funny how the, you know, the future's here.
Speaker 10:It's just not evenly distributed. Think there are, you know, certain parts of The US, people are like, oh, yeah. It's sci fi. Like, it know, it's totally goofy. Then there's, like yeah.
Speaker 10:Some metros where people are like, oh, yeah. Use it, like, three to four times a day. And by the way, these are, like, predominantly There's
Speaker 11:moms lot and grandmas.
Speaker 2:There's a lot of AI researchers that say that getting Waymo into DC will be will significantly update the administration's AGI timelines because they will just see robots on the street, and they will recognize that this is a real thing. And until you actually see it diffused in the in the world, it it's very hard. It's very abstract to just see reports. Oh, Waymo has a thousand rides or 10,000 rides or a million rides. It's like, what does that mean?
Speaker 2:But when you are walking and it's like, oh, seven Waymos in a row, and they're all driving fine, not crashing into each other. You get it.
Speaker 10:Even Tesla FSD. I mean, Same thing.
Speaker 4:You know,
Speaker 10:I was hanging out with my college professor, and he'd, like, had no idea what FSD was or that it was working. Because we've heard we've
Speaker 2:heard about it for so long, but it's finally here. So, yeah, very exciting. Here. Well, thank you so much for coming on the show. I hope you have a great Thanksgiving, and we'll talk to you soon.
Speaker 2:I'm sure you'll be back soon.
Speaker 1:Yeah. You'll be busy delivering turkeys. Whole
Speaker 2:turkeys soon.
Speaker 10:Small ones we can do.
Speaker 2:Small ones you can do. Okay. Great. I love it. Well, it's awesome.
Speaker 2:Thank you for talking to
Speaker 1:Great to catch up, Kelly.
Speaker 2:Have a
Speaker 1:good see you. Cheers.
Speaker 2:Before we bring in our next guest, let me tell you about Julius AI, the AI data analyst that works for you. Join millions who use Julius to connect their data, ask questions, and get insights in seconds. And I'm also gonna tell you about Privy. Privy makes it easy to build on crypto rails. Securely spin up white label wallets, sign transactions, and integrate on chain infrastructure all through one simple API.
Speaker 2:We have our next guest in the restroom waiting room, Royce ban Branning from ClearSpace. Are you doing, Royce? Welcome to the show. Good to have you. How are you doing?
Speaker 9:Thanks for having me. I'm doing well. How are guys doing?
Speaker 2:I'm doing well. Can you kick us off with just a a little bit of intro and background on you and the company? And and then I I you know, there's a whole bunch of questions that I'm sure we're gonna get into.
Speaker 9:Totally. Excited to dive in. My name is Royce Branning, cofounder and CEO of Clearspace, and we help people reduce their screen time. Our company, our mission is to build the missing intentionality layer of the Internet. Mhmm.
Speaker 9:We think there's a fundamental asymmetry in the war for your attention and we're equipping, the individual autonomous consumer in the market with the ability to steer their focus online and protect their family's attention online. K.
Speaker 1:So What's a perfect amount of screen time? Have you guys run the numbers? Is there is there is there an optimal
Speaker 2:Well, you know, Andrew Ross Sorkin asked Peter Thiel this in Sun Valley for his kids. He was like, you're on the board of Facebook. How long how much screen time do you let
Speaker 1:What did you say, like Zero?
Speaker 2:He said thirty minutes a week. Oh, yeah. Yeah.
Speaker 9:Thirty minutes a week is ambitious. I think that the ideal amount of screen time is probably a little bit less than whatever you're spending right now. Sure. We say we say that a calorie is not a calorie is not a calorie. A minute spent on a screen is not equivalent to another minute spent on a screen.
Speaker 9:Sure. But you wanna be increasing the the quality of the consumption. And usually, overall reduction in quantity ends up needing an increase in quality.
Speaker 2:Yeah. That makes a lot of sense. Mhmm. So how do actually do it? I mean, there are screen time functionality natively baked into Apple, the iOS.
Speaker 2:I'm sure Android has it too. Your business is still working, so it's not like you're getting steamrolled. But how do you how do you differentiate and
Speaker 4:how do deliver value?
Speaker 1:Do they have a is there any sort of misalignment to Apple's business with screen time? Because I imagine if they really incentivize people to use their screen less, it's like less apps that I'm subscribing to and less kind of potentially less act like they don't have a perfect incentive to make you Yeah. Use your phone less. They sell you the phone once but they're like take more pictures. Get those Totally.
Speaker 1:Get those iCloud subscriptions up. Yeah. Buy more apps. Spend more in that mobile game, etcetera.
Speaker 9:A 100%. Yeah. Yeah. We think we think Apple has every incentive to have a solution here, but maybe not. The the ideal incentive is to have an effective solution to helping people kinda control their screen time and reduce it.
Speaker 9:We think that it comes down to both visibility and control. Mhmm. So you have, like, a feedback loop that's helping people identify how much time they're spending on devices and, like, where that's actually going. I think the current state of screen time right now is basically, like, again, to use food if you only tracked calories that you consumed, not micro and macronutrients.
Speaker 2:Mhmm.
Speaker 9:So for the last two years coming out of YC, we've been primarily focused on a mobile app that grows people's awareness of how much time they're spending on devices and then allows them to add little bits of cognitive friction into the addictive habit loops that they use on different apps like social media. And that kind of starts to get them rehabilitating an addictive habit. But what we're actually working on now, and we just announced a few weeks ago, are screen time agents that sit at your network layer and can observe network traffic going to all your devices. And this is particularly useful both for individuals and for their families to think about holistically what it means to have the right type of content, the right time of consumption happening across all of their different devices. And that kind of breaks out of just Apple's ecosystem of what they allow us to see.
Speaker 2:Yeah. Yeah. That's interesting. How do you think about the responsibilities of different big tech platforms? We were just pulling up this article in CNBC about this whistleblower claiming that Meta failed to act to protect teens.
Speaker 2:Do you do you have a do you have a stance on, like, are the big tech platforms being negligent in in the in what they're surfacing to their users, or do you think it's more just, like, the natural forces of, you know, the economic incentives they're trying to sell ads? How do you how have you grappled with the various, like, dust ups in the big tech world over the like, what happens on these apps?
Speaker 9:Yeah. Yeah. I tend to think about no one is the boogeyman. I think actors are kind of following the incentives laid out before them. Mhmm.
Speaker 9:Our mission is really much to meet the opposite side demand. I mean, I don't know about you guys. Everyone I know hates their relationship with their phone. Mhmm. They hate how much time they spend on their devices.
Speaker 9:Mhmm. And I think what we're seeing is we think that actually equipping them to articulate that preference in terms of how much they're spending time on these platforms with technology that's sophisticatedly protecting their attention is gonna actually push back against how big of an intention economy scenario can actually be downstream from people just rampantly consuming content.
Speaker 2:Yeah. Yeah. That makes sense. So how do you actually, like, take me through a list of, like, the the walls that you run into. I mean, all the big tech platforms are, like, famously walled gardens.
Speaker 2:Somebody in the chat was asking, like, I would love to be able to use YouTube with no shorts, only like long form content. And I actually installed a an extension in Safari called Social Focus that allows you to do that. It it'll if you use the browser but if you're in the app, there's nothing you can do. It sounds like you're going higher at the network traffic level a little bit. But at the same time, I don't even know.
Speaker 2:Can you, at the router level, detect if someone's watching a short versus a long form video on YouTube? That feels like that would be obfuscated.
Speaker 9:Yeah. Yeah. That that gets a little harder to do, although we're constantly pressing at the edges of like what is possible around that. I mean Sure. We've definitely ran some experiments where you can kind of fingerprint what short form content might look like coming down the wire versus long form content.
Speaker 2:Yeah.
Speaker 9:And so there is interesting things that you can start doing there. But really robustly for the mobile app, we can basically just make sure that you're staying within healthy usage limits and that those aren't sliding out of control. Which when shorts go wrong, what really happens is they like pull you into a longer session than you want to be in. Sure. So there's not an easy way to do that, but different platforms have different rules like on obviously Chrome, on the MacBook, there's a way higher ability to to detect what type of stuff you're watching.
Speaker 2:Yeah. Yeah. It's I mean, it's tricky, especially as all the apps, like, collapse with AI. You could imagine I mean, right now, Sora and ChatGPT are are separate apps, but in many ways, they're, like, on the opposite ends of the spectrum. Like, I I want, you know, my my, you know, son probably spending a bunch of time solving problems in ChatGPT and researching things and, like, finding facts and and, you know, using it as a helpful assistant to understand the world, and probably very little time on Sora just, you know, sloughing it up.
Speaker 2:But Yeah.
Speaker 1:What what what are what are parents of teenagers actually doing specifically with ClearSpace? Like, how are they utilizing it? What are best practices? Our our kids are much younger, five five and below. So we've have probably another at least five five to seven years before this is even a conversation, but I'm curious.
Speaker 9:Yeah. The one some of the cool stuff that we've seen is people inviting their kids into, like, challenges as families. So setting up, like, incentive and reward systems. One of our most popular figures. Gambling.
Speaker 1:Gambling on screen time. Most Fight American
Speaker 9:fight one addiction with the other. We we we hear a lot of parents, like, set up family groups where they're doing a a challenge like a push up to scroll challenge where everyone in the family or squat to scroll, you have to earn every single minute you're gonna spend on social media that week with a physical exercise that we validate with like a machine learning verified
Speaker 1:No way.
Speaker 9:Push up or squat. And then whoever's in the lead at the end the week gets to decide where the family's eating out to dinner on Friday night. I think the most effective solutions we're seeing are kind of these, like, cultural pushbacks, almost, you know, community tile type stuff, like the practice of Shabbat in, like, the Jewish community where it's, like, twenty four hours, everyone's putting their phone away, and people love it. It's not this like negative, you can't use your screens. It's like everyone's kind of buying into a new fun thing.
Speaker 9:And we think ClearSpace is the platform that can empower you to do that like really quickly. You don't have to be a software engineer, know how to hack your router, know how to program all the phones. You don't have to buy a dumb phone. You can kind of still participate in the latest and greatest technologies while knowing that they're not completely zapping your entire family.
Speaker 2:Yeah. Totally. Well, congratulations on the progress. I know we didn't talk too much about the business, actually, more about the problems that you're solving. But, it's, yeah, it's a very interesting, industry.
Speaker 9:Thank you. I'm curious I'm curious for both of you guys what you're doing, about your screen time these days.
Speaker 2:Most of the time? I mean, I don't know. Because all my screen time is actually really low because I'm live streaming all the time. And do I count this? Like, I'm looking at a screen.
Speaker 2:I'm looking at you.
Speaker 1:The other thing I've always been frustrated with the dedicated
Speaker 2:is actually way lower than it used to be because I'm live, but that's content, and I am the content. And so it's a little bit murkier. But
Speaker 1:The other thing is I was always frustrated with screen time. I I'll I'll I'll give, ClearSpace a spin. But with the core screen time app, it would track, like, call hours as part of the screen time, right, which just makes zero sense to me because I'm, like, oftentimes, like, not using my screen at all. I'm just talking with somebody. And so, anyways, I I just always, always felt like, I don't I don't know.
Speaker 1:I I think I've always been more focused on spending time on you you talked about, like, all all calories are not, you know, created equally. But Yeah. Spending spending time doing the right things. But, yeah, the best the best thing I've found is just putting my phone far away and just staying away from it.
Speaker 2:Yeah. Last I spent eight hours in the maps app or something. It was just like Dang it. I I did a commute last Classic.
Speaker 1:Map maxing.
Speaker 2:It was my number one used app last week. I don't know what was going on. I was driving a
Speaker 9:lot like this. Putting the putting the phone across the room is what we call a classic, low tech solution to a high-tech problem.
Speaker 10:Yeah.
Speaker 9:We think we think there's an opportunity to basically deploy super intelligence
Speaker 2:Sure.
Speaker 9:At the network level at protecting your attention rather than exploiting. And that's like we think that's what people want and that's what we're bringing to them.
Speaker 1:I'm gonna I'm gonna really stick it to Apple and just start breaking my phone into pieces when I wanna use it less and then I gotta because I'm on the whatever. I get the the free replacements. Right? So I just go in the next day, get a new phone. And when I wanna some less screen time, just break it into pieces.
Speaker 1:That's the real low tech solution. But excited to give give ClearSpace a a spin and really glad you guys are working on this. Yeah. Very important that we we have the smartest people in the world trying to capture as much attention as possible, and it's good to have, you know, equally smart people working on on humanity's side here. So thank you, and great to meet you.
Speaker 9:Awesome. Great to meet you guys.
Speaker 1:Cheers.
Speaker 2:Talk to you soon. Let me tell you about adquick.com. Out of home advertising made easy and measurable. Say goodbye to the headaches of out of home advertising. Plan, buy, and measure out of home with precision.
Speaker 2:Oh, this CNBC story, Meta failed to act to protect teens. Second whistleblower testified. This is from 2023. So I don't know, why Adam Dell wants us to discuss this. Is there something new here?
Speaker 2:Because the the CNBC story links to a Wall Street Journal article, and I was like, oh, November 2. It's a little bit old, but it's 11/02/2023. And so I don't I don't know what I don't know what the news is here. Maybe there's something new. We'll have to dig in.
Speaker 2:But but we can go and and take a tour of the latest in Meta's world. The most recent thing that I saw was that they they beat the FTC case on the on the on the antitrust case that they were fighting. So things to be seem to be on the up and up. The latest thing from Meta on the like, is it safe for kids stuff was from Adam Masary at Instagram where he was saying he's going to try and make it PG 13. He was using the MPAA rating system, and I believe that there was, like, some pushback from the MPAA on whether or not they could.
Speaker 2:I was saying, hey. Meta, you're rich enough. You should buy the entire MPAA. I don't even know if you can. It's probably nonprofit.
Speaker 2:But, like, I want I want those ratings, like, in every app, like, just as a consumer because everyone understands it. You know what r rated means. You know what p g 13 means. You know what p g means. I can even tell the difference between g and p g now with the kids because Yeah.
Speaker 2:P g, there might be a little bit of a, like, a tense moment. It's just, like, emotionally charged. I I used to think PGG, it's the same stuff, but it's not. And so quantifying that using the using every movie as training data, pipelining that in, and then filtering every message that gets sent into Instagram, every post, hey. How would you rate this machine learning model?
Speaker 2:AGI god, personal superintelligence. Let's give every every Instagram post a a rating and then let the user decide, hey. I don't wanna see anything above p g 13. I don't wanna see anything r rated. I don't wanna see anything, g rated or or p g rated or anything above that.
Speaker 2:If you could set your threshold, I think that would be very useful for parents who want, parental guidance on the MediPlatforms. Okay.
Speaker 1:I don't know. We've had a bunch of guests back to back.
Speaker 2:We've also had some ads back to back. Getbezel.com. Shop over 26,500 luxury watches, fully authenticated in house by Bezel's team of experts.
Speaker 1:What's up? We gotta talk about the What do we got? The Cremieux Yes. Yes. KEON exchange.
Speaker 2:Yes. Yes. Yes. I
Speaker 1:I thought that Kermu was pretty pretty fair. Sure. I didn't I I think he could have gone harder. Yeah. I Keon said he didn't watch Kermeux's interview Yeah.
Speaker 1:That he was with a patient. I I wish that he I wish that he had Yep. Because it seems like this is one of the most important things on his plate right now is kinda getting getting beyond this. And, ultimately, we tried to bring up as many of kind of the key concerns as possible. To be honest, it's so it's it's technical enough that I don't that that it's it's we don't have the same power level in terms of kind of, like, pushing Kian on some of these issues Totally.
Speaker 1:And Sichuan.
Speaker 2:Which is why I think, like, the a lot of the debates will be done Yeah. Around the data in blog posts by scientists. But
Speaker 1:Yeah. And and and Keon's main point that I took away was sorry. Laughing at laughing at the chat.
Speaker 2:No, sir.
Speaker 1:But it was like people are angry that we have the best marketing and the best science. And I I believe that they have the most effective marketing in terms of capturing attention right now. But I don't have the confidence after that conversation that marketing should be happening at the scale that it is. Like, I just don't I didn't I didn't come away from that super confident that that that Kian felt like they've done anything anything at all that's that's wrong.
Speaker 2:Even even even if you just narrow it to what there is full agreement in amongst all participants on, which is that there were reviews that were anonymized and then not disclosed to be anonymized, even if it's just that, like, that is enough to you know, if you're a customer, be like, oh, like, this I don't trust this anymore. And it's a very, very high trust environment. It's a very trust critical environment. It's not, okay. Yeah.
Speaker 2:I'm buying a phone case and, like, they AI generated the the the like, an example of a person holding up the phone case. Like, that's not what this is. This is, like, life. It's bio. It's really important.
Speaker 1:People are selecting, you know, impact Yeah. We've talked about the child's life. Yeah. We've talked about it. And Yeah.
Speaker 1:I think that whatever happens
Speaker 2:It's really important to get it right.
Speaker 1:Yeah. It's really important to get it right. And ultimately, people that use the service Yeah. If they have an adverse experience
Speaker 2:Yeah.
Speaker 1:They feel like the service didn't deliver Yeah. Went wrong. They're gonna come back to this Yeah.
Speaker 2:So are there are there any posts that we need
Speaker 1:reach out to and said the fundamental problem with keyon subflexion is that even if the origin poly polygenic weights can be independently validated to have the predictive accuracies claimed in their white paper, none of that changes the fact that they, completely plagiarized heresyte, falsely claimed that origin is novel and has superior performance, made numerous errors from typos to substantive mistakes in their white paper, have a history of making literally impossible accuracy claims, in some cases inflated 2,000 x to an independent replication. Mhmm. These these are not
Speaker 2:What's up, Tyler?
Speaker 4:What are saying?
Speaker 3:Oh, I just there's you can continue. I I have another post. I wanna talk
Speaker 2:about it. Okay. Yeah.
Speaker 1:These are not just restricted to claims about technical accuracy. These are claims about ethics and morality for the vast majority of businesses. Maybe you don't really care that that much about unethical practices. Typically, that's fine. I mean, maybe Meta does shady stuff sometimes, but I still use Messenger.
Speaker 1:Maybe my local grocery store manager is a wife beater. Who knows? I still have to buy my groceries somewhere. That's
Speaker 2:oddly specific example. Is the example that we keep giving of, like, you know, will you go change your tires if you find out that the Bridgestone Tire Company is buying on, you know, a rival tire company, there are certain things where it's just like, the tires are working, like, you're okay with it. A lot of it depends on, like, is the criticism directly in line with the company's with the company's product? Like, if the if the if the CEO flubs a line and they miss earnings, but the but the product still delivers what it is. It's like they sell apples, the apples taste great.
Speaker 2:Like, you're fine. But when but when they're when they're making a claim about the actual product and then it doesn't align, that's where people really, really start to ask questions. So closing out here, it says, but we are talking about a company that will select your future child. How can anyone trust a company where the CEO's burst instinct when confronted with evidence based criticism is to make false accusation of shady conspiracy theories? And Mu follows up and says, if a company engages in malpractice, I e g plagiarism, providing products they should know are bad to customers, etcetera, is it water under the bridge if they can clean up?
Speaker 2:That's obviously a reaction to my question was, you know, is there a redemption arc in his mind? Somebody says Volkswagen can answer this question really well. I think that's because Dieselgate is what's going on with the is is is that in reference to? Yeah. Anyway
Speaker 1:Kermu also says Kian alleges that he's been working on embryo services for a long time. Again, that doesn't seem surprising. I don't I think this was always the the longer term vision of the company. Mhmm. But Kermieux says he hasn't been he hasn't been doing this with genomic prediction according to their lawsuit, which says in 2025, Nucleus sought to offer IVF products involving embryonic DNA testing.
Speaker 1:Because Nucleus could not do that work itself, it contracted with GP for GP to use its own embryonic genotyping products to provide test results for patients. Nucleus made overtures about acquiring GP, but soon it became apparent that Nucleus was looking for inroads to misappropriate yeah, again, these are just allegations that we can't really validate ourselves. But, again, didn't come away from that kind of more more confident in in anything, really.
Speaker 2:Yeah. The Typeform a lot of people are saying that the Typeform is down. Kean was, of course, saying that, like, he will release the models and that, you can go and get the the the you can get the the models and the data from the Typeform. It was down at the moment he said that, but Max Gil Glick, thank you for, your service doing that reporting in the chat while we were talking about that exact thing. Max says, it's back up now for what it's worth.
Speaker 2:And so Krumiu says that's good, and I certainly hope I just feel like the next the the the next turn of discussion needs to be, okay. We tested the models. We tested the data. We tested the claims at a at a higher level of rigor, I guess. Tyler, which post did you want to run to?
Speaker 3:Oh, it's at the bottom of the timeline. Szechuan model is also accusing Kian of using Chad filter during
Speaker 2:This has happened before. This happened before. So so when when Kian came on the show maybe six months ago, Growing Daniel accused him of using a a Chad filter while on the stream and, and went super viral. And and I was kind of like, oh, like, that's, that's, I don't know. I don't know how to, you know, even respond to that.
Speaker 2:That's a very silly claim. I I have no idea if this is real. I can't I can't tell at this point, on a Zoom call at this resolution. What do you think? Do you think this is real?
Speaker 2:Are you are you guys just cracking up? Because everyone does everyone think it's real? I don't I think
Speaker 3:don't that he used a filter.
Speaker 1:I don't think he used
Speaker 2:a filter. Filter either. Think he
Speaker 3:just grew a beard and
Speaker 2:I think he's just been mewing maybe.
Speaker 3:Maybe he's just photogenic.
Speaker 2:Yeah. It is possible that he just he just, you know, flexed his jaw muscles and, like, you know, has low body fat. I don't know. I I don't know. I I feel like it would be extremely high risk to run a a chin augmentation filter.
Speaker 1:This down for a second. I mean
Speaker 2:Because because you you know that's what happens. Right? When you're using, like, the Snapchat filter or, like, the TikTok filters, like, sometimes they pop in and out. And if they pop out, like, you're done. Like, people are gonna be immediately, you know?
Speaker 2:Let's see. Compare the first two images with the x.com profile. I mean, the x.com profile, that picture looks three years old, four years old. I think, on this one, Sichuan, like, you might be over your skis. I don't know.
Speaker 2:We we we need to we need to prove it. And then, yeah. People are people are really going back
Speaker 1:and forth. It's gotta get the nucleus test for the Gigachad test and and viewing viewing the results.
Speaker 2:Everyone's cracking up in the studio. We're having a wild time. Anyway
Speaker 1:In other news, this is actually insane. Apparently, according to X, I don't know if this is true, but the robbery that took place yesterday in which an armed thief posed as a delivery driver and robbed somebody for $11,000,000 of Ethereum and Bitcoin was Locky Groom that was targeted.
Speaker 2:Woah. What?
Speaker 1:Jay had
Speaker 2:No way.
Speaker 1:I I didn't realize that it was him, but absolutely terrible and traumatic. And yeah, when self custody goes wrong. But I'm glad he's glad he's okay and safe.
Speaker 2:Wow. An armed thief posing as delivery guy finessed his way into the $4,400,000 miss Mission District home shared by investor Lockheed Groom. Yes. Sam Altman's ex boyfriend and another tech investor named Joshua.
Speaker 1:Oh, okay. So it was not Lockheed, but Joshua?
Speaker 2:Gary Tan posted the footage panicked enough to delete it minutes later. Crypto security experts are now saying what everyone thinks self custody is great until someone shows up your door with a fake UPS label and a Glock. San Francisco's tech leader about to hard pivot into vault custody, private security, zero public flexing because this heist wasn't random. It was a warning shot.
Speaker 1:Very Chad GBT written. Mario Naufaul. Poor Paul. Anyways, very sad.
Speaker 2:Yeah.
Speaker 1:But glad Joshua is okay. I was confused for a second. That is terrible. Anyways, thank you for tuning in today, folks.
Speaker 2:Before we head out, I gotta tell you about 8sleep.com, exceptional sleep without exception, fall asleep faster, wake sleep deeper, and wake up energized. And I'm also gonna tell you about wander.com. Book a wander with inspiring views, hotel great amenities, dreamy beds, top tier cleaning, and twenty four seven concierge service. It's a vacation home, but better, folks. Thank you for taking the time to listen to the show.
Speaker 2:Thanks for dealing with our stream issues up and down. We sorted it out. The full Never happened before. Are posted. But, yeah, the full interviews will be posted.
Speaker 2:Obviously, RSS feed, YouTube, and the full Keon interview has made its way to the timeline. Obviously, there's lot a of debate. We will continue covering it, but not tomorrow because we're off and not Thursday because it's Thanksgiving. We will be back on Friday Friday. For Black Friday.
Speaker 2:We have a fantastic lineup of a bunch of different entrepreneurs, ecommerce, founders, brand builders
Speaker 1:Some of the most savage
Speaker 2:Operators.
Speaker 1:Ecommerce operators in the world. Cannot wait.
Speaker 2:It's gonna be a great time.
Speaker 1:A lot of friends. Have a wonderful Thanksgiving. We are thankful for each and every one of you. Thank you for being a part of this, and we'll see you Friday.
Speaker 2:Goodbye.
Speaker 1:Cheers.