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TBPN is a live tech talk show hosted by John Coogan and Jordi Hays, streaming weekdays from 11–2 PT on X and YouTube, with full episodes posted to Spotify immediately after airing.
Described by The New York Times as “Silicon Valley’s newest obsession,” TBPN has interviewed Mark Zuckerberg, Sam Altman, Mark Cuban, and Satya Nadella. Diet TBPN delivers the best moments from each episode in under 30 minutes.
Well, Anthropic's responded. We're gonna go through that proposal, the the the facts and the proposal for what happens next in the open, open model debate over whether or they should be banned, restricted, tested, limited in some ways, sued. Oh, there's a whole bunch of different possible outcomes, but we'll take you all through it. The Wall Street Journal is reporting that large companies are beginning to They have
Speaker 2:a large
Speaker 1:white pill. Yes. It is a large white pill.
Speaker 2:Has hit the front page of the journal.
Speaker 1:Yes. And I think people have been going back and forth on this. This is a story that's that's just getting digested by the tech folks, like the actual AI lab leaders who had predicted crazy job losses and are now not really seeing that. They're seeing productivity boosts and different diffusion taking time in certain places and there's new capabilities, but it's not exactly a drop replacement for a coworker, at least in in most scenarios. And that's what The Wall Street Journal is reporting.
Speaker 1:So let me set the table and then we can debate it a little bit. After roughly a year of cautious hiring, companies across technology, transportation, defense, and other industries now say they need more employees to work alongside AI systems. Total victory for both humans and AI. We're working together. Peace is possible.
Speaker 1:It's an example of of Jevan's paradox Jevan's paradox, when a technology makes something more efficient, demand often rises enough that total use and the need for people actually increases. For roughly the past year, many companies pointed to AI while announcing layoffs. This was a huge thorn in your side. I think you hated this more than anyone else. And you were right too because it did seem like it was just PR, spin, etcetera.
Speaker 2:Yeah. It was a way for CEOs and management teams to save their own ass instead of saying, you know, hey, we we over hired or the business isn't doing as well Yeah. As as we would like. Yeah. And we need to sort of basically settle down for a second and get our mojo back.
Speaker 2:Yeah. And there no one wants to say that but I I think one of my favorite posts was the and and obviously these circumstances are never great, but the the new CEO of Xbox came out and just was like very honest about the situation.
Speaker 1:Yep.
Speaker 2:And I think that more of that is necessary.
Speaker 1:Yeah. Also, there's a lot of firms where they once they get to 10,000, 20,000 employees, they might say, look, 20,000 might be the right number, but the bottom thousand people are not performing. We would like to lay them off and then bring in a new thousand people that are better fit for the company and the current trajectory that we're on, the current skills that we need. Maybe we need more salespeople
Speaker 3:And those bottom
Speaker 2:thousand people might be top 10% another company. Exactly.
Speaker 1:Yeah. So the narrative appears to be shifting. Companies like CSX, Alphabet, ServiceNow, Snap on, and consulting giant Booz Allen Hamilton have all recently signaled plans to expand hiring, particularly in areas where employees can use AI to become more productive.
Speaker 2:Yeah. Used to be somewhat of a flex if a company was like, yeah, we put up a role and we got 2,000 applicants.
Speaker 1:Yeah. Yeah.
Speaker 2:It's like, well That's true.
Speaker 1:And then also it's a little bit of a sign of like, oh, wow. They have a 100 openings. Like they must be like growing so fast, you know? So if but if it's just a prompt to say, oh, yeah. Put up like look at my organizational design and and add five roles for everyone because why not?
Speaker 1:Why not see who comes by? We're not we don't necessarily have to interview these people. So weird, weird dynamics, but we'll dig into it. So meanwhile, the latest weekly U. S.
Speaker 1:Jobless claims fell to one of the lowest levels in decades, underscoring the resilience of the labor market. The shift also reflects a more realistic understanding of AI's capabilities. Sarah Franklin, CEO of HR platform Lattice, says many companies initially assumed AI agents could replace entry level workers but are now recognizing that human employees remain essential. Just because you have coding agents doesn't mean you're not hiring engineers, she said, adding that Lattice is seeing renewed hiring among many of its customers, including for junior roles. Robert Half, CEO and Keith Waddle said, AI's effect on employment has been more benign than some have beard, adding that hiring demand continues to improve and market conditions are increasingly more supportive of business.
Speaker 1:And so I do think there was a little bit of like a successful SIOP AI is gonna be able to do everything. Where I do think there are some firms that were like, Yeah, maybe we shouldn't hire. Or because what if we get it wrong and we hire a bunch of people and then AI really does catch up and we don't need those people. That's silly. We shouldn't go through that whipsaw effect.
Speaker 1:And so people are going back and forth on that. Bryce Roberts
Speaker 2:Yeah. It's interesting. At least in at least in our organization, which is unique and and very niche and there's not that many organizations that are running, you know, a niche technology daily show. Yeah. I feel like a lot of what the the value that we get out of AI would historically been done by not super expert level freelancers.
Speaker 2:Right? These sort of like Upwork style Mhmm. Tasks that you would do historically, an idea for a funny song. Right? Yeah.
Speaker 2:I've paid to get a funny song made probably a decade ago online. Right? As just like joke and now you can just go to Suno and and make something like that. And and then there's other things like make a funny website. Right?
Speaker 2:I historically would maybe work with
Speaker 1:So you're saying that I should I should take down the five open roles I have for Celtic punk session musicians?
Speaker 2:Not yet.
Speaker 1:Because I was gonna five Celtic punk session musicians to constantly record Dropkick Murphy's covers for us
Speaker 2:Yes.
Speaker 1:Every day.
Speaker 2:And then perform Well, I'm the not writing writing stage. That you shouldn't do that.
Speaker 1:I'm actually closer than ever to hiring a full time Celtic punk band Recreate. Recreate songs.
Speaker 2:Codex and Guinness.
Speaker 1:Yes. I'm I'm closer than ever to doing that where that was not even on the road map a few years ago. Yeah. I don't know. It's good it's point.
Speaker 1:Yeah. There there's a lot of things that you are doing that you would never do with a full time employee. Yeah. They just sort of like fills the cracks and allows you to do more different things in your organization. But the core stuff is still like you want a person that's responsible and then you want them using AI.
Speaker 1:I don't know. Yeah. The Wall Street Journal breaks it all down, but we went through most of that. So Bryce Roberts, he's he's taking the other side of this. He says he shares a screenshot of a text message that says, we honestly aren't hiring a ton right now, AI backfilling most roles.
Speaker 1:Backfilling, is that specifically does that specifically refer to when someone leaves the company? You backfill them with AI? So you say, oh, someone quit. Like if there's Steve and Jim on two different on one team and Steve quits, you say, hey, Jim, can you just instead of hiring another person, just do twice as much work with AI? Is that what this person's articulating?
Speaker 1:I mean
Speaker 2:Yeah.
Speaker 1:Obviously, there's some companies that are like, yeah, we're not hiring anyone. We're we're going for the one person, $1,000,000,000 Like, I'm not gonna hire anyone. I'm just gonna use
Speaker 2:But that's rare. That Usually usually when your business is ripping, you're like, I can't hire great people fast enough. Yeah. And sometimes don't you have time to Yeah. Invest into various hiring processes.
Speaker 2:But Yeah. I would read into this text, the company is just probably not like ripping. That's my that's my takeaway.
Speaker 1:Well, Bryce Roberts says, RIP new grads. Matthew Prince over at Cloudflare takes the other side. He says, wrong strategy to stop hiring new grads. The right strategy, hire them and insert them into legacy teams to help them better adopt AI.
Speaker 2:And Cloudflare, of course, hired 1,000
Speaker 1:Something like it wasn't it was a crazy number, wasn't it? Yeah. Up there in like almost a thousand?
Speaker 2:Four digits.
Speaker 1:That's crazy. Let's play the latest good work, real. Watching reals now. This
Speaker 2:is last one we got is Bernie Madoff. Pretty
Speaker 1:good. Good gloves. That's from the eighties too.
Speaker 2:That's good.
Speaker 3:Yeah. Yeah. I've I've seen a few
Speaker 2:of these around before. Up next. Solid Sam Bankman Fried here. That's nice. That's really nice.
Speaker 2:That's really nice.
Speaker 1:I like that they actually printed these. I think he made balsa wood.
Speaker 2:This is balsa wood? Yeah. The
Speaker 1:acting is so
Speaker 2:Wow. Wait, John.
Speaker 3:This is a this is a vintage Zuckerberg. Mhmm. O five? This is a vintage o five Zuckerberg. Let's just check the back really quick.
Speaker 2:Oh. There it is. That is a patch from his Fruit of the Loom boxer briefs. You can tell by the smell.
Speaker 1:Is that real? What is that referring to?
Speaker 2:This is athlete, you know, put a piece of the jersey.
Speaker 1:Here's the jersey.
Speaker 2:This one. Yeah.
Speaker 1:Yeah. Alright. Up next. Leave it.
Speaker 3:Oh. Okay. Nice. Elizabeth Holmes. We do have two.
Speaker 3:Yeah. I believe. We have two, but a triple Holmes is what every good collector has
Speaker 1:True.
Speaker 2:In their arsenal. Alright.
Speaker 1:We have one.
Speaker 2:Last card? One one card left. Three, two, one. Oh my god. Oh my god.
Speaker 1:Oh my god. My god.
Speaker 2:Turn it off. Very funny. Very funny.
Speaker 1:What what it is funny how the the like business comedy canon has really solidified around like Elizabeth Holmes, Sam Beggenfried, Mark Zuckerberg. There's like a few names
Speaker 2:surprised they didn't have an Adam Newman rookie card in there.
Speaker 1:I don't know if Adam Newman is like a big enough name relative to
Speaker 2:That's true.
Speaker 1:Sam Bengen Frieden and Elizabeth Holmes. It's just interesting like the different the different names that have broken out that you can do a comedy sketch that's like, you know, it goes as big as as good work does because they get, you know, I think millions and millions of views on their stuff.
Speaker 2:Alright. Pull up this image Yes. From Manhattan this morning. We got sent this.
Speaker 1:We've been doing on the ground reporting.
Speaker 2:From one of our on the ground reporters in Manhattan. There's a company called Black Sheep that Got IO. That got 20 trucks and they're just driving them around Google's Manhattan office Yes. Saying, shame on you, Google. Return our $80,000.
Speaker 2:We had to dig in. We got very curious.
Speaker 1:I had no idea. They make sunglasses?
Speaker 2:They make $8 sunglasses that beat $350 sunglasses in NBC lab test.
Speaker 1:Okay. You wearing Black Sheep today?
Speaker 2:Which I wish. I wish. So Black Sheep makes direct to factory
Speaker 1:Okay. Factory direct prescription eyewear. Stop paying
Speaker 2:$5 for This five is from their own website. I'm reading They're saying direct to factory disruptor.
Speaker 1:What do mean? Which is
Speaker 2:not This is from their website. Where do mean this? On Black Sheep.
Speaker 1:I'm on blacksheep.io as well. It says factory direct Direct to factory? Look. I wanna send some eyewear to a factory.
Speaker 2:Direct to factory.
Speaker 1:I'll be sending it to them.
Speaker 2:Direct to factory. Yeah. So this company, they say direct to factory optical disruptor, Black Sheep launches 25 truck guerrilla campaign against Google in Manhattan. Okay. And then they're they're sort of, like, narrating their own guerrilla campaign.
Speaker 2:A fleet of twenty five minuteimalist LED billboard trucks surrounds Google's Chelsea headquarters after the tech giant weaponized an organic search glitch to pocket nearly $80,000 in ad spend following Black Sheep's viral NBC Today show debut. 25 LED trucks deployed, $77,000 drained in thirty hours, And then they're and then they're just continuing to market their own products. Very interesting strategy here. I think every marketer has had the experience of of having a campaign go haywire. Yeah.
Speaker 2:Very fascinating to take to take this route. Let's see how it works for them. If I were Google, I would say you can have your $80,000 back but you can never advertise on Google again because I just don't know how.
Speaker 1:I don't think Google would ban them permanently for this. This is ridiculous. But it you know, they're just gonna be like any other like, it's a self serve platform.
Speaker 2:But is it a good campaign?
Speaker 1:But what what actually happened? So they say, how it unfolded? NBC Today show segment airs. They test the retail subscription against Black Sheep's factory direct pair. National search traffic spikes.
Speaker 1:Hundreds of Americans search Black Sheep because they're seeing it on TV. The organic listing breaks. Google search engine redirected organic brand traffic to a dead end third party four zero four error page. And so with the organic route broken, users were funneled into Google's paid listings. So what is their claim?
Speaker 1:How is Google responsible for this exactly?
Speaker 2:Sounds like user error.
Speaker 1:Because, I mean, you do you do have some control over your Google search results based on the webmaster tools. You can index certain things. And then also, if you're noticing a four zero four page, you could like redirect it quickly. Yeah. But again, if this is happening all very fast
Speaker 2:They can use your air.
Speaker 1:Difficult. But, I mean, it is interesting because they're probably gonna get more than $77,000 worth of organic just from this. I mean, I didn't see the original campaign and I'm seeing this because this is hilarious. But this is like a is this they they shared an AI image with tons of these like shame on you trucks. But those are real.
Speaker 2:These are real.
Speaker 1:And are those minimalist or maximalist? Those seem maximalist to me. But maybe they're minimal.
Speaker 2:Minimalist, I guess, in the in the display of the Yeah. In the way they actually are leveraging the space on the truck But black and white.
Speaker 1:Truly underrated service area for stunts and advertising. Like, I this message is sort of like squabbling with Google over this like sort of odd scenario, but you can imagine someone using this for something much cooler and much more positive and not like this, you know, sort of unfortunate situation for them where they're dealing with the, you know, fallout of a Google error.
Speaker 2:Well, we wanna interview the truck drivers.
Speaker 1:For So
Speaker 2:if you're driving a black sheep truck around Manhattan today, reach out. For sure. Reach out. Nick, make it happen.
Speaker 1:Ilya said straight shot to SSI, so they better not be gearing up to release a work agent called Francois. Francois would be a very good name for for an AI agent. I like that. Do wonder Yeah. What they're going to be releasing.
Speaker 1:Has the SSI is going to release? Is that complete rumor? Because all all alias Yeah.
Speaker 2:Just said they would scale
Speaker 1:their research. Scale their research. Yeah. So that just means they've done a bunch of research. They have some sort of architecture that they like, some sort of flywheel and they're going to like use more compute and so that's why they're raising money.
Speaker 1:I don't think they said like, and we're gonna release it publicly. Yeah. But everyone's thinking like probably still LLM or something different? No one really knows?
Speaker 3:Yeah. I mean, think still broadly like generally LLM Who's
Speaker 1:God? Like, next level. There are levels to vague posting when you live a vague life. It's just like your entire life is vagary. Anyway, in other news, Recursive Super Intelligence signs a $410 complete deal with Amazon.
Speaker 1:So funny. And it's in the TechCrunch. It's in the header too. Of course, that is a typo. It says Recursive Superintelligence signs $410,000,000 compute deal with Amazon.
Speaker 1:Congratulations to Recursive Superintelligence. Throwing safety out the window. That should be the that should be the the tagline. Like, because there's already safe super intelligence. But we're just doing Recursive Super Intelligence over here.
Speaker 1:But of course, the company is doing very well. They merged from Stealth in May with $650,000,000 in funding focused on building open ended self improving systems and potentially compute intensive approach to AI research. This multiyear deal is meant to provide flexibility as the company looks to scale up those systems. Recursive's $410,000,000 outlay represents the bulk of the company's fundraising to date. But on a call with TechCrunch
Speaker 2:Hey, hey, hey. They still have a couple 100,000,000 left over.
Speaker 1:Founder and CEO Richard Socher emphasized that he expected it to be the first of many such deals. So is this I feel like normally when you see a like a compute deal signed, it's always like more complicated than just like we're buying this expensive thing. It's usually like we're we're paying that. I'm like, I it's we we used to be so like anti circular deal that now I just have come to I've been so normalized by them that I expect them every time. I'm like, wait.
Speaker 1:Wait. This is just there's no circularity here?
Speaker 2:There's no
Speaker 1:I would have expected
Speaker 2:changing hands.
Speaker 1:Yeah. Like, Amazon's investing in you and you're buying Trainium and bracking it. AWS did that are doing new campus and they're investing in this and that and you're investing in them. Instead, it just seems like it's a pretty vanilla deal. It's like they're just buying a lot of compute from Amazon.
Speaker 1:Great.
Speaker 2:Seems like it.
Speaker 1:Well, good luck to them. Very excited for what they're launching. Launching.
Speaker 2:Yeah. Jason, VP of Start Hups and VC at AWS says, part of the agreement is that we're gonna co develop him for a purpose built for these types of companies. So fingers crossed, but seems like we could get some some circularity.
Speaker 1:Yeah. Let let's hope so. Let me tell you about Railway. Railway is the all in one intelligent cloud provider. Use your favorite agent to deploy web app services and more while Railway automatically takes care of scaling, monitoring, and security.
Speaker 1:Fingers crossed. Well well, here's here's a deal that's somewhat circular. We got NVIDIA revealed as a tenant for a $50,000,000,000 data center that will use its chips. So they're the tenant of the data center that uses its chips. We'll talk to Tae Kim about this.
Speaker 1:CEO Jensen Wong deploys balance sheet to backstop growth of AI computing market. NVIDIA signed leases worth up to $50,000,000,000 for a massive Texas data center. That's very, very big. That's very, very big for a single site. A previously undisclosed commitment that shines a new spotlight on the Chip's on the Chip Group's growing role in financing AI.
Speaker 1:The nearly $5,000,000,000,000 company is leasing the entire one gigawatt facility that developer Hut eight is building, which will house hundreds of thousands of NVIDIA graphics processing units. So you have to imagine that once they have these, they serve something or wind up selling them. Like, these things change hands so many times. There's a lot of different ways that this could play out ultimately. But in the can we pull up the NVIDIA chart?
Speaker 1:Yeah. There we go. NVIDIA. Oh. Woah.
Speaker 1:Big candle today, up 3%, 5,170,000,000,000. Let's take a look at Apple. 4.99. They crossed five today. They're down little bit since they since they beat breached that.
Speaker 1:But they're neck and neck. Google is sitting at Yeah.
Speaker 2:Apple running the do nothing win strategy. Yeah. Jensen doing thousands of deals.
Speaker 1:They didn't even sign the open There are three companies that still, I believe, still haven't signed the open letter.
Speaker 2:Only three companies on the entire surface of the earth.
Speaker 1:There are three there are three major companies that haven't signed that NVIDIA open letter about banning open source and or not banning open source. Amazon, Apple, and Anthropic. Anthropic put out a post yesterday, very, very clear response, sort of outlining their view on Open Source, their stance. Apple and Amazon haven't signed in. They both have very physical elements in the world in the sense that they're not they're sort of unsloppable.
Speaker 1:Like, you can't vibe code an Amazon warehouse. Can't vibe code an iPhone. There are threats to those businesses, of course. And, of course, Apple should benefit from open source and so should Amazon because they'll be able to serve open models across AWS. But it's just potentially interesting.
Speaker 1:I think the Apple standing it standing back is more just like, look, we're not jumping on with this crazy open letter that everyone is signing. Like, we just have our own brand. We're thinking different. We're doing
Speaker 2:other Apple AI timelines, I would expect them to sign it in maybe a year or two.
Speaker 1:Potentially. These glasses have changed you. They turned you a new beast. Let me run through the three Anthropic proposals because it's an important response. So Dario Ahmaday, Anthropic's CEO, responded directly to that letter summarizing supporting open weight models that circulated over the weekend.
Speaker 1:So he makes three claims just to sort of clarify things that I think are important. One, he says Anthropic has never advocated for a ban on open weight models. Now, that's a blanket ban. There's obviously like, defining what a ban is and what an open weight model, what a distilled model, what a foreign model is, these things all matter. But he has come out and said, Look, we never advocated for a total ban on open weight models.
Speaker 1:Two, he says, Undergirding all of this is The U. S. Must beat authoritarian governments in the AI race. He points to China, but he identifies any authoritarian government. If they get really powerful AI, they'll come over here and steamroll us and you won't be free to do whatever you want to do in America.
Speaker 1:Three, powerful AI models may be misused to carry out cyber attacks or biological attacks. There are risks to having really, really powerful AI open source systems just running around. So, he's worried about those three things, clarifying those three points. But he makes three recommended actions. He makes three proposals.
Speaker 1:First, he says, Let's continue to sanction chips. Let's not sell chips to China. He says, we should not sell powerful chips or chip making equipment to China. So this has been debated for years. Like, going back to the Biden chip controls, everyone knows every different angle on this, the basics.
Speaker 1:I mean, there is a pretty good argument for chip controls even on purely geoeconomic competitive grounds. Like, even if you don't believe in the risk of authoritarian governments having powerful AI, even if you just think it's like fancy autocomplete, it's like, well, it's the engine of our economy and if you can slow down a rival economy, that's beneficial to you. Right? And so and there also seems to be basically unlimited demand for chips in America. So by restricting sales to China, that shouldn't actually hurt American chip companies all that much.
Speaker 1:But, yes
Speaker 2:Well, they just like, their argument would be we fully lose the Chinese market Yeah. Which is the second largest
Speaker 1:Yeah.
Speaker 2:Computing market in the world. No. No. Right? So so I think but but your the counterpoint to that is you were gonna lose it anyways.
Speaker 1:Yeah. And a lot of that, it stems from the fact that China China has been building an indigenous chip supply for decades. We've talked about going back to a whole bunch of their state led, state funded chip and fab processes. They've always been a few years behind. And so maintaining that gap, all else equal, is an advantage for The United States.
Speaker 1:The second point Dario makes is he says we should crack down on industrial scale distillation operations. This seems totally reasonable. Companies can set their terms of service and they have a right to maintain intellectual property with proper legal consequences for violations. Anthropic's been fighting distillation attacks, but according to them, it's not that effective. Dario proposes policy interventions to deter this behavior.
Speaker 1:And this is where I'm still not clear on what where that goes next. Like, what is the correct policy intervention? There's a like, policy intervention is a very, very broad thing. It can mean anything from, a tax, a tariff, a fine, a sternly worded letter, not getting invited to a golf tournament. Like there's so many different things that policy covers these days.
Speaker 1:Right? Where does this actually go? He says he doesn't want a blanket ban on open weight models, but it does seem like one possible policy intervention would be to sort of like ban, restrict or pressure open weights models that can be reasonably shown to have been distilled. So if there's someone who's just a perfect distillation, it just gets it just doesn't quite feel right, it's hard to quantify these things. We don't have a binary where you run some sort of algorithm and you say, Yes, this was distilled.
Speaker 1:Because you can distill half on Opus five and then throw in a little GPT 5.6 and then mix in some some Mistral and, like, just be distilling from all over the place, fine tune stuff, change the flavor, change the RL environment. There's so many different pieces of it. And, Tyler, you were making a point about Tinker or
Speaker 2:Yeah.
Speaker 3:Mean, so so the the Inkling model from Thing Machines, like, it used some synthetic synthetic data that was created with, I think, Kimi k 2.5.
Speaker 1:Yes.
Speaker 3:So, like, I does that count as, like, distillation? Like, probably not in when people usually talk about it, but, it definitely benefited from Chinese open source models. Yeah. So I wouldn't call that downstream of
Speaker 1:I wouldn't call it industrial scale distillation. Yeah. It's sort of downstream of industrial scale.
Speaker 3:Big gray area where Yeah. Like how do you actually define these things?
Speaker 1:Yeah. And so defining that is going to be what that's going to be the conversation that plays out in DC, like behind the scenes on the basis of this. And that's where the actual negotiation is going to happen between the position of NVIDIA and everyone that signed the letter versus the position of Anthropic and everyone who didn't sign the letter. They're going to sort of decide, Okay, well, if you can prove this, this and this and you can show us that your API was getting hit by these different things and you have a really solid report of what happened and then the model also sort of checks these boxes quantitatively when we do this eval, then maybe we will pressure it. And then what does that actually mean?
Speaker 1:You could go after the lab that committed the distillation attack with lawsuits, but that seems really difficult given the international nature of these attacks. So we're sort of back to where we started. Like, what can the government do that the lab can't? Like, lab should be looking at every customer and saying, Oh, this seems like someone who's trying to distill. They keep asking for basically what looks like a lot of training data.
Speaker 1:They're not acting like a normal user just being like, Build me a website. Okay. Third, he says, All sufficiently capable models open and closed should go through mandatory safety testing. So this was recently outlined by Demis Hassabis over at Google DeepMind as well. And it seems like the two companies are in alignment on this in particular.
Speaker 1:And it's a somewhat reasonable position, although the risk is that small companies who have safe models could that aren't distilled could get tied up in a review queue for years before they can release. Like that would be very, very annoying. If you're Recursive Super Intelligence, for example, and you don't have a Washington DC office and you're like, hey, we want to release our new model. And they're like, yeah, totally. Like you got to go through the review process, get in line.
Speaker 1:And then it's like every, you know, every trillion dollar company is there with a ton of lobbyists being like, we'll review our model first because we want to get out a week before the small startup. And that's the frustration of biotech, the FDA, anything that goes through approval. We've talked about this with the nuclear stuff. It gets very tricky. And so you want to avoid that and you don't want to wind up slowing down innovation that's happening on small scales and decreasing competition.
Speaker 1:Dario does do a good job of acknowledging upfront that he says, It would protect U. S. AI companies from competition, but that's never been my goal with anything that he's saying here. And so it's still worth working through what happens in a really adversarial situation. Like what if a foreign lab distills a bunch of frontier models?
Speaker 1:They're the most aggressive. They're just distilling everything. Then they jump forward a bunch in capability. They get a bunch of smuggled chips. They take all the restrictions off of cyber, all the restrictions off of bio, and then they just drop the weights on like a torrent, where they put them up on Hugging and Hugging Face is like, this is really crazy.
Speaker 1:No one likes this. There's lot of pressure to take it down. I don't know. But it's out there. Like, what does the government actually do?
Speaker 1:Like, the government probably pressures or bans, like, hosting the weights, maybe serving the model. You maybe won't be able to run it in American data centers. You go to the Neo Cloud and say, hey, this thing is actually bad. And I think people are divided on this because they see the current models not as actually dangerous, which is totally reasonable to assess that, yeah, it's not that bad. But like if there was a model that was like, yeah, it's actually just like killing machine.
Speaker 1:Like I think most people would be like, yes, I'm democratically voting to not serve that because it's just like it's an annoyance at best and like actually bad at worse.
Speaker 2:And the other big question is like how much compute do you actually need for it to be dangerous?
Speaker 1:Yeah. Totally.
Speaker 2:Is is like having some GPUs in the back shed gonna be enough? Yeah. Maybe for sufficiently advanced model? Yes. Yeah.
Speaker 2:Or do you need access to a ton of racks? Yeah. Ton of power?
Speaker 1:Totally.
Speaker 2:And then you do need to work with a Neo Cloud Yeah. In that
Speaker 1:And as soon as you're a US based company with a real data center with a bunch of NVL 72s in there, you probably have registration and, you know, all sorts of just like business registrations where the government can reach out to you and say, hey, we're actually really worried about this. Just like there are other things you can't host in a data center. There's all sorts of stuff that's illegal. Yeah. Yeah.
Speaker 1:Yeah.
Speaker 2:Exactly. Yeah. That's a That's a
Speaker 1:But you can't even just because you have a data center doesn't mean that you can, like, take an open source, you know
Speaker 2:You can't you can't as a data center.
Speaker 1:Oh, yeah. Open source Marvel. Like, they'll be the Or
Speaker 2:even even a, you know, a CRM company can't knowingly support, like, organized cart global cartel
Speaker 1:Yeah.
Speaker 2:That is like trafficking narcotics. Yeah. Right? You have you'd have to imagine like Yeah. That they have They have to vibe check balances.
Speaker 2:Their Maybe.
Speaker 1:So so so what what what's interesting is, like, what is the next step of that? So if there is a bad model, and and everyone agrees, okay. Yeah. We gotta not host this, not distribute this. Like, yeah.
Speaker 1:The weights are out there. People are trying to, like, sort of run it a little bit. But does it go offshore? Do we wind up in, the crypto scenario where there's, like, these offshore things and people are using VPNs to get access to it? Like, what level of aggression do you see from the US government in that scenario?
Speaker 1:It probably should be proportionate to, like, the danger imposed by the model. Like, if it's just a model that's, like, that's, like, annoying or, slightly IP infringes, but, like, no one's really being, like, I'm not I'm I'm canceling my Disney subscription because this new model will generate me Disney IP. Like, that's probably not like, okay, put up a crazy firewall. But if it is like the ultimate hack machine that's like stealing everyone's money from the banks, then, yeah, you are gonna put up the the firewall and sort of be much more aggressive. So I think the response will be in reaction to whatever the power of the models are, but it'll be interesting to go back and forth.
Speaker 1:Anyway, all in all, the letter clarifies a lot about the Anthropic position, so I think it's good that it came out. But it's still worth working through the game theory of like what happens down the line. Policy interventions is all we got here and I think it's still too generic at this point. I want to know like what policy looks like. I want to predict that.
Speaker 1:I want to understand what's actually being proposed. What people like, what people don't like. And so I think we'll learn more about this in the coming days. Mark Zuckerberg
Speaker 2:is in the Wall Street Journal opinion section Yep. With a new piece, The AI Future is for Everyone. Mhmm. He says, the history of democracy and economics has proved that centralized power stifles human potential. And it's quite long.
Speaker 2:I'm go let you guys read it, but let's head into the comment section. Let's get a quick let's get a quick reaction. Let's get a quick reaction.
Speaker 1:This is the Wall Street Journal. I think it'll be
Speaker 2:No. It it it looks relatively tame.
Speaker 1:It'll be tame.
Speaker 2:But, yeah, making a, you know, a a clear effort to position to to be the overtly there was a white space for a guy investing hundreds of billions of dollars a year in AI that is like says, hey, this is gonna be really great for everyone. Yeah. And I'm gonna help us get there.
Speaker 1:It is it is interesting. Like, Facebook does have some monopolies, but like, the competition for attention is constant and there are always sources outside. Like, they've never had a full monopoly on social media even with TikTok and Snapchat and LinkedIn and Twitch and YouTube and Netflix and the podcast feed and SMS and iMessage. Like, there are so many other platforms for disseminating information. Like, I I don't know.
Speaker 1:I I it's hard to jump straight to a critique here. But the key quote that Andrew Curran pulled out was that he said, In most cases, like cyber security, the history of open source software has shown that giving everyone full access to powerful systems will be the best way to protect safety and security over time. So he's firmly on the side of democratizing powerful AI. And he is yet another one. I imagine that they signed the letter.
Speaker 1:I've lost track at this point. You you can imagine that he did. Anyway, thank you so much for tuning in. The other piece of news is that Apple is launching Apple upgrade next week, then iPhone, iPad, Mac, and Apple Watch leasing slash subscription program. They said They're saying you will and you will be happy.
Speaker 2:We're launching our new program. You will own nothing and be happy.
Speaker 1:It's partnering with Klarna to launch in The United States at online and retail stores. It's now official. Leasing prices start as low as $20 or $17.99 per month for iPhone, $11.99 for Apple Watch, $24.99 for Mac, and $11.99 for iPad. So interesting. I mean, a lot of people are saying this is a direct reaction to increased prices for memory, increased prices for products.
Speaker 1:There was a time when an iPhone was a couple $100 and there were incentives to jump on a Verizon plan and you sort of amortize the cost over that. Those days are gone. Like, we're in the world of like a $2,000 iPhone. It's a significant
Speaker 2:with our Gongs.
Speaker 1:For people. Honestly. Gongs. You wanted a subscription Gong?
Speaker 2:No. I'm just saying there was a time when Oh. Our TBPN Gong was $200. Yeah. Now, it's in the tens of thousands of dollars.
Speaker 1:It's actually so expensive. Somebody A friend of mine texted me and was like, where do we get the Gong? Because I need a Gong. And I was like, I think you should start small. And this is not like you're you can't handle the big gong.
Speaker 1:I was more saying that like there is a joy to being on the hedonic treadmill of larger gongs. Like, you don't want to jump straight to the biggest gong. You want to start with a small gong
Speaker 2:And And work your way
Speaker 1:up. Work your way up because every gong that we've added has been so electric when we get I think
Speaker 2:it's time for a new one.
Speaker 1:You want an even bigger gong? Or
Speaker 2:I want one that's hanging from the rafters.
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Speaker 2:Cheers. Flashbang.