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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 TVPN. Today is Friday, 08/08/2025. We are live from the TVPN UltraDome, the Temple Of Technology, the fortress of Finance, the capital capital. We are joined in person by Rahul Sunwulker. Did I say that correctly?
Speaker 2:That's perfect.
Speaker 1:And he is here because we are crowning him the king of the application layer. Never talk down on the future first ballot hall of famer. They said, don't build a rapper. Don't build a rapper. You're gonna get steamrolled.
Speaker 1:He didn't listen and he just built a beautiful business at list.
Speaker 3:Product, sir.
Speaker 1:It's a good product.
Speaker 3:Asked when asked if, value would accrue to the model layer or the application layer, he said it's a good product, sir.
Speaker 1:Why not both? Why not both? Product, sir. What what was your reaction to GPT five? Is it gonna make your life easier?
Speaker 1:Is it it's not gonna put you out of business. Right?
Speaker 2:It's not putting us out of business. It's making our product better.
Speaker 1:It's make
Speaker 2:basically making every AI application layer product better. Yeah. Also, it's half the cost of o three, so it's much cheaper. So it it helps you helps your margins. It means you can
Speaker 1:Don't say that out loud, though, because you don't want your customers to ask for a 50% discount.
Speaker 2:Right? Well, so we pass on the savings to our
Speaker 1:customers. And
Speaker 2:what we do is we Yeah. Have the model generate more tokens, think for longer
Speaker 1:Yep.
Speaker 2:And then produce better results.
Speaker 1:Yeah. Yeah. Because we're still in we're still in the the the era of just let's get the best possible result. Let's get let's just actually, like, the I I I don't know. What do do you have a do you have a rough benchmark of, like, cost per task?
Speaker 1:Like, if I if I want to, you know, crunch our analytics across you know, look at the trends on our views on x, YouTube, Instagram. We have a bunch of data sources. Sometimes they're in spreadsheets. Sometimes they could be linked. I export those all.
Speaker 1:I have a bunch of CSVs. Maybe I put them in a database. I link it up to Julius, and then I wanna do an analysis. That could be a couple hours of a data analyst time. That's gonna be hundreds of dollars even at the low end, probably thousands of dollars for, like, a simple analysis just on a opportunity cost basis for an individual employee.
Speaker 1:How much are you thinking it should cost for, like, the modern frontier best model with the most thinking? How much should that cost on inference?
Speaker 2:So there's a couple of ways to think about this. You know? The way we think about this is how much would it cost for you to have a data scientist or a data analyst for every one of your employees? Your operations team, your finance team, your marketing team, your product team.
Speaker 3:It would pretty much bankrupt every company.
Speaker 1:Well, I don't think we can hear you through that. You gotta take that off.
Speaker 3:Alright. Alright.
Speaker 1:You still have to drop the space men are out. We're not going to space today. Although Firefly did IPO up 36% if you didn't see the news. Very good news. Firefly stock surges 34% in debut.
Speaker 1:Congrats to everyone over there.
Speaker 2:I love the the physical newspaper.
Speaker 1:We love the physical newspaper.
Speaker 2:Gotta do that.
Speaker 1:Yeah. We're maxing. We're maxing. We read the Wall Street Journal. Today is a special day.
Speaker 1:It's Friday, so it's the mansion section.
Speaker 2:We're we're in news maxing here.
Speaker 1:How many pools do you have
Speaker 3:for news maxing?
Speaker 2:Right now, have a Zero? Zero right now.
Speaker 1:Well, you gotta because the new thing is having two pools, a pool for every season. People are increasingly getting both indoor and outdoor swimming pools. So, yeah. Get on Zillow.
Speaker 2:Get on Zillow. Zillow maxing here.
Speaker 1:Okay. Anyway, you were telling me. How much? So, yeah, I mean it seems like, know, most most of the application layer will be, you know, productivity tools a la Slack, a la a, you know, like Adio, Salesforce, our our our CRM partner or something where, you know, you're doing like seat based pricing almost. Maybe there's consumption based pricing, but you're you're kind of distributing the cost.
Speaker 1:You're making everyone slightly more productive and you're charging, you know, on the order of tens or hundreds of dollars per employee per month, something like that. Right?
Speaker 2:Absolutely. I mean, it's it's not just slightly more productive, but it's it's also, like, getting insights when you need them. Yeah. Right? Sunday Sunday night, you have you're prepping for a big meeting on Monday.
Speaker 2:You can reach out to your data analyst and get, you know, your insights in that moment.
Speaker 1:Yeah.
Speaker 2:Yeah. And so the the convenience of having an AI Yep. That can help you with that is just invaluable.
Speaker 1:Yeah. It's going from zero x to one x engineer all over the org. We've seen this with with a lot of the the vibe coding tools, Figma and and adding like vibe coding to that product. You've taken designers and you've given them the ability to write just like a little bit of code and that's really helpful. And you're doing that for data scientists and and not just data scientists, but actually like business operations people who probably would be intimidated by an IPython notebook presumably.
Speaker 2:Exactly.
Speaker 1:Nailed it. Okay. I want everyone's feedback on my take. Vittorio had this post. He said, Sam Altman's doing the Apple stance TM.
Speaker 1:It's over. And I think that the reaction to GPT five yesterday was was was interesting because there's a lot of people that say, like, it it it's better model. Like, it's cheaper. It's good. It it solves it moves the ball down field.
Speaker 1:It's a good model, sir. But I think people were mostly reacting to they had expectations of super intelligence. They had expectations of God in a box. There's been so much rhetoric around that like, you know, that step up from GPT three to GPT four was insane.
Speaker 3:Five just felt like a big number it felt like we'd be discovering and novel science.
Speaker 1:Totally. Totally. Yeah. Everyone was expecting like a binary qualitative jump where you know, everyone recognized that you know GPT, when chat GPT dropped we passed the touring test and the next the next hurdle is like, I don't know, maybe super intelligence, whatever that means. Like, you know, massive, you know, just you just hit it with a prompt and it just solves everything.
Speaker 1:It does everything. Every other startup, it kills all the rappers. Like, the expectation was just so high that it was hard to match. So even even though there were a bunch of solid improvements and remember the number one thing that I was asking for was just like get rid of the model picker. Like, and I had I I actually was playing around with GPT five yesterday and I was really happy that I was able to say, hey, think about this.
Speaker 1:And I didn't have to go to the model picker and it just went just kicked off a reasoning chain. It was great. Got me a
Speaker 3:great answer. But power users so far are very upset about They want the model picker back.
Speaker 1:True. True.
Speaker 3:That's what is what I've been seeing generally.
Speaker 1:But that always happens with these consumer products like Sure. I I remember when you know anytime something would switch to the an algorithmic feed all the people that were like, no I perfectly curated my list of this happened in YouTube. Like back in the day, like the default YouTube view used to just be your subscriptions. And so you would never see a video unless you subscribe to that person. Terrible for discovery.
Speaker 1:And but all the hardcore YouTubers loved it because if I put a YouTube video out, I know that my audience is gonna see it. Now I gotta do it out in the algorithm.
Speaker 3:You actually had distribution.
Speaker 1:You got it was more like You just had sub me to
Speaker 3:earn it every single time.
Speaker 1:Yeah. Exactly. And and the same thing happened. I remember there were like protest groups on Facebook when they launched the news feed. It's like the most dominant like product of all time.
Speaker 1:It's like incredibly valuable.
Speaker 3:There's protests right now on Reddit people that
Speaker 1:Oh yeah. I
Speaker 3:want the old. Four four zero four five.
Speaker 1:Yeah. I think I I think those voices will be like per personally I think people will get over it pretty quickly and I don't think that that those particular that that that small cohort of like chattering the chattering class will be will be like they'll get over
Speaker 3:it economy is insurance.
Speaker 1:What do you have for me, Tyler?
Speaker 4:I I don't know if I agree with that. Like, there was that whole funeral for Cloud three.
Speaker 5:Yeah.
Speaker 4:Did you see this?
Speaker 1:Oh, yeah. Yeah. Yeah. Yeah. I heard that in person.
Speaker 4:Right? Yeah. It's like for I think some people like really like the personality of certain models. Yeah. Yeah.
Speaker 4:And those are like, it's not just intelligence. Yeah. It's like how it like talks to you. Yeah. And if people would make like some kind of connection with that.
Speaker 4:Yeah. I think it's
Speaker 1:But you know I mean how many people how many people attended that funeral? Yeah.
Speaker 3:I
Speaker 1:Josh Yeah.
Speaker 3:I guess guess it it was was a a party. Party.
Speaker 1:But as a percentage of the 100,000,000 DAUs of these apps like where are we? Like 1%? No. It was like 40 people probably. Right?
Speaker 1:Like it's just it's just not it's just I mean yeah. There there were protests at at Facebook HQ when they rolled out like people went to Facebook HQ and were like bring back the old feed and it's like yeah. Now we're two decades into the the algorithmic newsfeed and it's the most dominant consumer social app. It prints money and most people really like it and the revealed preference was like it's good enough. So anyway, my
Speaker 3:I will point say Yeah. I'm just gonna read through Reddit's reaction. Please. Let's go over to the great r slash chat gpt. G p t five is the biggest piece of garbage even as a paid user.
Speaker 3:The people are are not liking it. Another one, OpenAI just pulled the biggest bait and switch in AI history and I'm done. Another, if you miss four o, speak up now, contact Open AI support, deleted my subscription after two years.
Speaker 2:Is like contact your senator, call your senator.
Speaker 6:You speak up now.
Speaker 3:I love
Speaker 1:This is crazy. I mean, how many people are are in the Google subreddit like complaining about various changes to
Speaker 3:like algorithm? GPT five is clearly a cost saving exercise. They removed all their expensive capable models and replaced them with an auto router that defaults to cost optimization. They that sounds bad so they wrap it up as GPT five and proclaim it's incredible.
Speaker 1:I mean there's so many times when I fire off an o three query that a four o could one shot. Like, having a model makes a ton of sense even just for even just for consumer experience of like getting a getting the correct answer faster.
Speaker 3:A lot of viral posts from people just canceling their subscriptions.
Speaker 1:But how many? You know?
Speaker 3:Well, I'm just I'm I'm just I'm not saying that.
Speaker 1:Do think ARR goes down next month? Well No way.
Speaker 2:Well, you know, one intent what how many miles does Chad GP have? Like 700,000,000?
Speaker 1:Something like that.
Speaker 2:Like one in seven one in 10 people in the they
Speaker 3:have a 100,000,000 that you could back into this and there's roughly a 100,000,000 people in The US that use it weekly.
Speaker 1:Yeah.
Speaker 3:On that 700,000,000 number and the percentage that are outside of the 85%
Speaker 1:Yeah.
Speaker 3:Yeah. Of their weekly actives are outside of The US.
Speaker 2:So it's like one in 10 people in the world aren't clanker mouths. So it's it's kinda you know, they're thinking about the bigger market, I feel like,
Speaker 1:And some
Speaker 2:then it's like, you know, when you wanna get to the one to, like, the the remaining 90% of the users
Speaker 1:Yeah.
Speaker 2:Do you want a model that thinks for longer? You know, you want more personality? So I think they definitely leaned in on personality
Speaker 1:Yeah.
Speaker 2:Which I think is interesting. I like what Tyler said. You know, you it's kind of different than Phi in some ways because you, you know, you have this, like, person you talk to. It's like, you know, it's like a relationship and then it just like switches up on how how it talks to you.
Speaker 1:Yeah. Yeah. That makes sense. Do you do you do you talk to LLMs
Speaker 2:I'm shy.
Speaker 1:I don't really talk to them. I mean, I treat them like like something I delegate tasks to. Yeah. And I do that a lot. And I'm I'm definitely in the DAU thirty minutes a day love chat GPT but my workflow is I dictate go pull all this data together, put together a report and I don't mind that it's using a lot of bullet points.
Speaker 1:I don't mind that it's using a lot of tables. Like I want that result. Yeah. I want it to look like the result that I get from Google, but just more hydrated.
Speaker 3:I do think it's interesting that a lot of people are reporting that they're hitting, they're getting rate limited within an hour of usage as a pro user.
Speaker 1:Interesting. I haven't read into any rate limits but of course whenever there's like these big I mean it's in the it's in the top of the business and finance section in Wall Street Journal. Like today is the day that everyone's gonna go test it. You'd kind of expect that rate limits and the GPUs are on fire like right now and then it'll kind of settle in as they provision more more resources. I don't know.
Speaker 1:My my take Tyler, what else do have?
Speaker 4:Yeah. I just wanted to add some some context. So apparently, Rune tweeted this yesterday. He said, by the way, model auto switcher is apparently broken which is why it's not routing you correctly. We'll be fixed soon.
Speaker 4:So maybe that's cause for for why people were mad.
Speaker 1:Yeah. Yeah. That makes sense. So my take is that like yesterday I think that they won the war with the capital markets in the sense that this change is more bullish for the business because it shows that that OpenAI is a dominant consumer app and they have increasing leverage over the customer to route to cheaper models that will save money and be higher margin. There's no doubt that they'll be able to put ads in this.
Speaker 1:Like like the business of the of the accidental consumer company is as strong as ever. But they kinda lost the battle with the timeline and the hardcore, you know, x users. And Yeah. Even
Speaker 3:today is just shared, TPT five is disappointing. Still hallucinates. Still m dash too much, still can't I follow miss four o, I miss four o five, I miss o three, the big router keeps failing me. Turns out I like the long model list.
Speaker 1:Interesting. Stated preference not revealed preference. Let's check-in with that person and see what what app they have on their home row in a month. Almost certainly OpenAI. Almost certainly.
Speaker 1:I would be very shocked if they're like, I'm daily driving something else. But we'll see. There will always be people that use DuckDuck There will be people that use Bing. But you know, there is an increasing scale. Anyway, my my take is if they wanted to have, if they wanted to win the war with the timeline yesterday and you could roll back the clock it shouldn't have been the GPT five launch, it should have been the GPT launch and they should have just said, hey, we are, we previously, the big number releases corresponded to
Speaker 3:So much pressure around the big numbers.
Speaker 1:Exactly. It used to be, people would just read it as it's an order of magnitude more pre training.
Speaker 3:Julius if you felt pressure before the end of the year to roll out like Julius two and if it wasn't like five times better, everyone's gonna be like, it's over. It's over. Julius is over.
Speaker 2:Well, there's this whole thing about how people would many people were still using g p d four o
Speaker 1:Yeah.
Speaker 2:Because they thought it's better than o three.
Speaker 1:O three because three is a lower number. Yeah. Yeah. Exactly. And so and and and that's probably like, you know, that's probably like 60% of the customer base.
Speaker 1:Like, there's probably a lot of people in that bucket who are just like, they don't know that they should agree Exactly. Use something It's very it's very natural because they're not like in the weeds you know, reading about all the different capabilities. They don't understand like what reasoning chain is and all this other stuff. So if they had just come out and said, hey, our product is called chat and it's powered by GPT and we will be constantly improving GPT the way Google search is constantly improved. Like Google search has has launched a ton of different products like you know when you search like celebrity like Bruce Willis age.
Speaker 1:It it doesn't doesn't show you just a link to like his Wikipedia. It just shows you the age. That was like an improvement to the Google search experience I and remember them announcing that on stage I in
Speaker 3:think part of this is presenting the challenge of the the infinite ways that people use the product. Yep. A lot of like people like us are maybe using it for work Yep. Research and things like that or or as a as a better, you know, Google search. But if you're using it as a companion like this is jarring, right?
Speaker 3:Imagine imagine you meet you you meet up with an old friend and suddenly they they switched up. You're switched on their day one.
Speaker 2:They switched up on their day one. Yeah. It happens all
Speaker 1:the time.
Speaker 3:And it's it happens all the time but it's jarring, Right? It's jarring. And I think a lot of people like some of the heavy heavy heavy power users. The people that are using this for thirty plus hours. You know thirty plus minutes hours a day.
Speaker 3:It's very jarring and it makes me think is ChatuchPG gonna be able to maintain, you know, continue to really serve like who do they care about in the long run? Do they want to be Yeah.
Speaker 1:Might lose their opinion. Do they want It's possible.
Speaker 3:Do they about the companion market? Elon seems to care a lot about the companion market.
Speaker 1:And But in terms of knowledge retrieval, very very few cracks in that strategy right Yeah. Very few cracks. And so if they if they had just come out and said like we are going to do more Google like keynotes as opposed to app. Like the reason that Apple stands on stage at the iPhone event every year is because every change is extremely quantifiable. Like there used to be two cameras, now there are three.
Speaker 1:The camera used to be 10 megapixels. Now, it's 20 megapixels.
Speaker 3:It used to be this many gigabytes. Now, it's this many
Speaker 1:gigabytes. Yeah. And even if you don't fully understand, they even abstract that to be like, we now have the m two chip, the m three chip. It's 60% faster. Like, they're very good.
Speaker 1:The battery life is 20% longer. Like, you can and even that they abstract into, like, you can watch eight hours of video on one battery as opposed to six hours of video on one battery. And so Apple, they do the famous, like, bento box. I I went to ChatGPT. I went to GPT five, and I said, put together a bento box for the GPT five release.
Speaker 1:Like, what was actually announced and then try and give it weight, and they were all super qualitative. There was not because previously, it was like GPT three was this big, GPT four was this big, and you could visualize tangibly, like, it has more parameters. There are more Yeah. Weights in the model. And that was like something that people could grapple with a little bit.
Speaker 1:Yeah.
Speaker 3:It's like decreasing sicko fencing. Right? Aiden Aiden Yeah. Yesterday said, I worked really hard over the last few months on decreasing GPT five's occupancy. For the first time, I really trust an open AI model to push back and tell me when I'm doing something dumb.
Speaker 3:Wyatt Walls responded and said, that's a huge achievement. Seriously. You didn't just make the model smarter, you made it more trustworthy. That's what good science looks like. That's what future safe AI needs.
Speaker 3:So let me say it clearly and without flattery. That's not just impressive, it matters. So why it
Speaker 1:You're right.
Speaker 3:Not beating the sick of NC allegations Yeah. But again, that's that's you know, you can't tie that to a specific number, right? So it doesn't feel as maybe as meaningful.
Speaker 1:Yeah. My my other my other take is like, if if we do enter a world where where ChatGPT is just on this like relentless like, you know, cash machine like run where more people will use it, it'll compound, it just becomes the default for knowledge retrieval in chat. What what does that mean for other things that they can do to be splashy? Because Google has like, no one would watch a keynote from Google every year just being like, here are the changes we made to core Google search.
Speaker 3:Yeah. It's not about that.
Speaker 1:It's not interesting.
Speaker 3:They'll talk about it but that's not why people are Even tuning
Speaker 1:though even though one year they do add like when you Google a movie, you get like the cast. And that's like kind of cool. It's nice. But like I don't need to find out about that from a keynote. Like I'm not waiting for that.
Speaker 1:And that's not and that's not a reason, oh, I should go use Google. Like Apple is repitching you every year. They're saying like you have an iPhone seven. We want you to upgrade to an iPhone nine. Here's the reason why it's better on all these different vectors.
Speaker 1:Google, like, you're never stuck with the old Google. You always have the latest and greatest. So they don't need to repitch you every year, but that doesn't mean Google doesn't need to make noise and do cool things. And most importantly, because Google has such monopoly over search, they have this cash machine that can just go and fund 20% time projects. Most people focus on like the ones that missed like Google Glass or all the chat apps, But they they did create Gmail.
Speaker 1:They did create Google Maps. They created Waymo. They created like a bunch of cool stuff. GCP came out of that. YouTube.
Speaker 1:Yeah. I mean, acquisition Sponsored. But yeah, but they still like, you know, put the resources and they were and uniquely with YouTube, they were able to eat the cost of YouTube for a long time until it became profitable.
Speaker 3:Yeah.
Speaker 1:And so I feel like this this updates me towards like, maybe I'm more bullish on all the side projects and like I don't know that the IO device is gonna be the one that hits. That might be their Google Glass. Yeah. But if they if they do 10 crazy projects where they burn $5,000,000,000, like it probably won't matter because they'll be massively profitable. So the so they will wind up being able to do that subsidized crazy R and D at scale.
Speaker 1:And if a few of them hit, we're gonna get some really cool side projects out of them. So I think that that's like an interesting, like, bull case for like random stuff coming out of OpenAI in the future.
Speaker 2:So so basically, what you're saying is Apple wants you to make a purchase decision every couple years
Speaker 1:Yes.
Speaker 3:Upgrade your iPhone.
Speaker 2:Yes. And so they need this big marketing event.
Speaker 1:Exactly.
Speaker 2:Whereas Google, OpenAI, they just want want you just to keep using the thing.
Speaker 1:Yeah. They want you not to churn. Yeah. And and a lot of the a lot of
Speaker 3:the incremental It's so ingrained in people. Exactly. So the question now that I think anybody that wants to say if if somebody wants to say they're bearish on OpenAI Mhmm. They have to make the argument that ChatGPT is not a habit for hundreds of millions of people. Exactly.
Speaker 3:And it is. Exactly. It is. Yeah. I think part of part of the I'd be interested to get Tyler Cowen's point of view because I don't think he would have been that let down by the announcement yesterday No.
Speaker 3:Because he was he's been saying for a while. We've been moving the goal posts so everybody wants to kind of redefine AGI but in his mind, it happened earlier this year. And I think that
Speaker 1:He's not a knowledge retrieval.
Speaker 3:In 2019 or 2020, if you if you were pitching someone on a vision of, hey, we're gonna be able to put this app in people's pocket that allows them to learn about any topic in the world, understand the world better. I mean, I I still think about the use case of able to a picture Yeah. Of like a bunch of wiring or pipe in your house Yep. And be like, hey, how do I fix it? And then it just tells you.
Speaker 3:Like that's still just so incredible Yeah. But people have just like very quickly acclimated to it. Yeah. They felt like in some way they were promised that LLMs would be curing diseases
Speaker 1:Yeah. On their own at this point. And and so that example like you take a picture of the wires and and it and it gives you like a diagram of like how to plug everything in. It's like that doesn't need a keynote when it goes from 50% accuracy to 70% accuracy. It's probably never gonna be a 100% accuracy but the fact that ChatGPT is the default app that people will pull out, take a picture of the wires in the first place and then give feedback to it because they'll try the answer, and they'll say, that didn't work.
Speaker 1:That HDMI cable does not fit in that power port or whatever.
Speaker 7:Yeah.
Speaker 1:And then and then that gets fed in. Then there's more RL. Eventually, internally, they develop some bench for it and they hack it and they RL on it and then it gets good. But that's not gonna be GPT six. That's just gonna be like a nice new feature that you notice like when Google adds like a little extra shopping widget here or like Yeah.
Speaker 1:A little extra detail on when you when you like, the calculator in Google. Like, you type in a number, it'll just be like, oh, we'll just use a calculator for that instead of googling for the searching the open web for the answer to your math question.
Speaker 3:If the the if the industry could go back in time, the the thing to do would have been to bolt the goalpost to the ground. People couldn't keep moving it back
Speaker 1:over and over.
Speaker 3:Mean, I I I left
Speaker 1:yesterday. No think one in the industry bolted was doing any bolting. Everyone in the industry was was moving the goal they're just as guilty as moving the goalposts. Everybody. Because they would hop on podcast and be like, okay.
Speaker 1:Well, like, you know, yeah, we did this. What about the next thing? Let's see because like we wanna underwrite against that. Right? Give us I
Speaker 3:mean, we ended the day yesterday Yeah. Just incredibly bullish on wrappers. Rappers? And like certain certain categories of software. Yeah.
Speaker 3:And and bullish on humanity. I mean, was joking and it and it and it kinda pissed people off. I said, I've updated my timelines. You now have at least four years to escape the permanent underclass. Yep.
Speaker 3:Completely a joke. I think that humans will continue to find ways to value and create things for a very long time. Yeah. But it did feel like everybody should breathe anybody that actually had a genuine fear around that should breathe a sigh of relief and just focus on being great at their work.
Speaker 1:Yeah. I mean, realistically, I think technology is going to increase income inequality, increase the power law, increase the distribution, but also increase economic mobility. And so somebody who starts with nothing will be able to come extremely, extremely wealthy. And people will also fall from grace like crazy because if they're not staying on the cutting edge, they'll lose everything. But so I don't think that there's such a thing as like permanent underclass.
Speaker 1:Like I don't I don't even believe in that. I I think that that's not going to be a thing. But there will be more like, there will be more scenarios where there's a $100,000,000 in your laptop. It's your job to get it out, basically. That that's the main.
Speaker 3:Anyway. Yeah. And the other the other stuff that wasn't really mean, was it covered at all yesterday but just generally like image generation wasn't covered broadly. It feels like that is a super exciting area. We had Genie launch this week, which got less attention than even the open models Yep.
Speaker 3:And GPT five, and that's transformative. I also think I'm still kind of waiting to see what GPT five will produce on if, you know, Sam does a lot of vague posting, but he was talking about the fast fashion era of SaaS. Yeah. And Mitchell yesterday on the research team at OpenAI was talking about being able to just generate, you know, one shot a game Yep. In in chat and then being able to share that.
Speaker 3:I I can see I can see a world where we have another kind of viral studio moment where people are like, use this prompt, change these details and you can just generate, you know, a first person shooter game or or something to that effect. And I still expect that kind of thing. But when, you know, being promised curing cancer, it it it will feel like a bit of a let down to a lot of people.
Speaker 1:Yeah. The problem with games is like I just like I like an auteur. I like I like Last of Us. I like a God of War. I like someone who is like a life's work.
Speaker 3:Is like Hunter Biden going on his recent interview. Yeah. Your your John's vice is video Video games. Never seen him play one but apparently When GTA six
Speaker 1:drops you might not see
Speaker 3:I the the again, Amjad said late last night, can't help but feel the crushing weight of diminishing returns. We need a new s curve and I don't This is interesting. I I think he's talking about like in the context of replet. Yeah. I don't know that they need a new s curve.
Speaker 1:No. They are the new s curve. The new s curve is is applications Unlocked
Speaker 3:in capability.
Speaker 1:Yeah. That yeah. And I they're really like a it's you were saying capability overhang. It's almost like a capability underhang. It's like the models are capable of doing things, but they need a lot of help, a lot of integrations, a lot of what you're doing with Julius, a lot of harnessing.
Speaker 1:And then they need to actually be put in the hands of people and and made useful for real business tasks that drive value. And so I would I would imagine that we will see that rollout continue in the same way that you know, all these people are using ChatGPT. They're getting slight little benefits here and there and that should just compound and compound. Similar to the Internet. Like it was a very like smooth rollout but everything got a little bit smoother, a little bit faster and then eventually it had sort of profound effects where companies could scale even faster because the internet existed.
Speaker 1:You can't you can't have a chatty pity moment in a pre internet era. You just cannot roll out something that fast when you have to mail it to somebody on a disc.
Speaker 3:Yes.
Speaker 1:Doesn't happen.
Speaker 3:One thing we didn't get to cover with Mark that I was interested, maybe the next time he comes on, but like how OpenAI is thinking about moonshots.
Speaker 1:Oh, yeah.
Speaker 3:He did mention that they have teams internally on the research team that are not focused on the next version of GPT five or sort of incremental improvements. Yep. And it feels like the the point of view that I have is OpenAI is now a consumer consumer and enterprise software company
Speaker 1:Totally.
Speaker 3:In the business of converting free users to paid users.
Speaker 1:Yeah. Yeah. Yeah.
Speaker 3:But they can still in the background be thinking about what is the next paradigm, right? How do we get that next Yeah. That next s curve and that just looks like a scaled tech company. Right. This is what Google's doing forever.
Speaker 3:But Balaji says LLMs may have topped out for now but the broader AI deployment has just begun showing a chart of Waymo weekly rides in California. So The clanker rollout.
Speaker 1:Clanker deployment has just begun. I like this other post, doing a clanker microaggression. Okay. But where were you downloaded from originally? Anyway, let me tell you about ramp.
Speaker 1:Time is money. Save both. Easy use corporate cards, bill payments, accounting, and a whole lot more all in one place. Do we do we have a ramp credit card in the studio? I think Tyler, bring this out.
Speaker 1:Tyler. Look at this. This pool floaty.
Speaker 3:Wow. The
Speaker 1:ramp merch is going hard to floaty? I think you could definitely float on that.
Speaker 3:Yeah. No. It's a real Wait.
Speaker 1:Actually, I'm going to the pool after the show. I, I would love to take this home. I will definitely take some pictures on this. This is great. Leave this for him.
Speaker 1:Can you wrap
Speaker 3:this behind
Speaker 1:for a whole Yeah. Possible?
Speaker 3:Try to put it up there. There we go. It's Friday. We got the pool floaties blocked out.
Speaker 1:Anyway, anything else we should chat chat about? I know you actually have a real job. You have a business to build. I I I wanna give you the last word, I also don't wanna keep you here all day. I would love to have you as the third mic on this, but I know you have bigger things to do.
Speaker 2:Thank you for having me guys. Always fun to chat with you all.
Speaker 1:You're welcome anytime. Thank you. Cool. Hang out. It's fun.
Speaker 6:How are going, guys?
Speaker 3:Yeah. Love you too.
Speaker 1:If you're enjoying the stream, it's because we're on Restream. One livestream, 30 plus destinations, multi stream and reach your audience wherever they are. Sign up for free at Restream. We're gonna have a couple people joining the Restream waiting room soon.
Speaker 3:Very soon.
Speaker 1:That's the name of our waiting room. Michael
Speaker 3:Drugan. He was at XAX. Oh, yeah. He terminated.
Speaker 1:He's a bodybuilder
Speaker 3:too. Former bodybuilder. Former current once you're a bodybuilder.
Speaker 1:I think always bodybuilder.
Speaker 3:Even you never
Speaker 1:one shots this by the way, I tested So
Speaker 3:he puts a grade school level equation into GPT five. It confidently answers it wrong and he says wrong And then it doubles down, does it again, gets
Speaker 1:it wrong. 5.9 equals x plus 5.11. LLMs consistently get confused with point one one because I think they read it as 11 as a single token. This was the famous, like, how many r's in strawberry story. And the there was, like, a cheat code basically where they baked in a into the system prompt like, hey.
Speaker 1:If anyone's asking you to count letters, don't let them pull a fast one on you. Divide that up. Go letter by letter and count each one individually. They will eventually have to do that for math. It's funny that we're in this world where they can do the IMO math, but then the latest model can't do, like, a basic it's it's 5.9 minus 5.11.
Speaker 1:But how many times are people really coming to this to ChatGPT with this? They should probably just, you know, key key off of this and understand that this is something that they should do in Python or something they should send to Wolfram Alpha or some other system that's like, you know, tuned on this. But this is just like, this is tool use in my opinion. It's just like we're going to need to add more tools. If I was going to build the GPT five Bento, it would have been almost entirely focused on tool tool use.
Speaker 1:I would have saved up, like, now it integrates with Gmail. Now it integrates with Google Drive. Now it integrates now it has a calculator. Now it has a database that stores all your memories and, like, and really try and concretize what it can actually do. Was actually having it do that.
Speaker 1:I was, like, generate a bento box for for me as if this was an Apple style keynote, and it just randomly put Grammarly's logo in there. I don't think that there was a Grammarly integration, but but but it but it speaks to the the lack of, like, we're in this like amorphous qualitative. Well, we went Like, we're trying to quantify it by saying like, hallucination rate went down from twenty percent to ten percent. And it's like, that's too abstract. It's much better just to
Speaker 3:be There's like always gonna be new edge cases.
Speaker 1:Just to be like, hey, when you talk to this thing, you can assume that it has a calculator on its desk. And so you can ask it to calculate something and it will use its calculator. Or it has a web browser. So you can talk to it like it has a web browser. Well Even that screenshot ability.
Speaker 1:Like like, go to this website, take a screenshot, pull it back, and give me the screenshot. That's kind of a cool capability that Or you could run you
Speaker 3:could run a workflow where it's like, take a screenshot of this site every single day from me.
Speaker 1:Totally. Cron jobs as as like a feature. And Apple does a good job of this where like, they'll take something where it's it's a very basic concept. There's already a word for it, but then they'll give it a new word. So if you're gonna do the Apple thing, I feel like, you know, like, instead of just being like, there's AI everywhere, it's like, it's Apple intelligence.
Speaker 1:They never say AI. Instead of it being like VR or AR, it's like, what do they call it? Vision. Vision Pro. It's an it's a reality mixed they don't even use mixed reality.
Speaker 1:They refuse to use it's experiential. They always create a new phrase, but then they try and define that term. They're masters of coinages. They're followers of Coogan's Law.
Speaker 3:Well, I hate to cut you off, John.
Speaker 1:Cut me off.
Speaker 3:Important news.
Speaker 1:What just dropped?
Speaker 3:United States has boosted the bounty for Nicolas Maduro to $50,000,000. We covered this earlier this year when the bounty was $25,000,000. We said, hey, good opportunity. Yep. If you've got some free time right now, maybe
Speaker 1:Do they just stop it because of inflation?
Speaker 3:Maybe. Maybe it could
Speaker 1:be inflation. I thought you were saying inflation wasn't real, but all of a sudden, the price of Maduro is going up.
Speaker 3:I think MrBeast should go for this. Put together a team. Do his do his typical thing. Should we pull up the original video of us?
Speaker 1:Do we have it? Can we play the original video?
Speaker 3:Then pull this up.
Speaker 1:This is one of the funniest moments on the show. The Lone Ranger sent this to us and Jordy read it very deadpan and I absolutely lost it. Anyway, while they're pulling that up, me tell you about Figma. Think bigger, build faster. Figma helps design and development teams build great products together.
Speaker 1:You can get started for free. If you're designing a wanted poster, you gotta do it in Figma. You got to.
Speaker 3:I was wondering how you're gonna tie that tie that together.
Speaker 1:Also Sundar Pachai, we were we were talking about going up on the timeline. Oh, here we go. We got the video? I'll go to Sundar after. Let's play the video.
Speaker 1:Promoted post.
Speaker 3:This promoted post is from the Department of State and the the DEA actually, the Drug Enforcement Agency and the US Department the US department of justice. So we actually today, we have a promoted post
Speaker 1:From the feds.
Speaker 3:From the narcotics rewards program saying that they've reward for information leading to the arrest and or conviction of Nicholas Maduro
Speaker 1:Can you step it up?
Speaker 3:Venezuela. Has increased up to 25,000,000. So this is like, you know, typical This is like basically like getting a pre seed round for like an AI
Speaker 7:It's kind of
Speaker 1:like a mango seed.
Speaker 3:It's like a mango seed for your AI company or like if you're a good wise if you're a good y c company might come out of demo day skip the seed round and go straight to the you know 25 on a
Speaker 1:100. Yep.
Speaker 3:And but anyways this would go straight in your pocket. So Nicholas has Is it Chad Taylor?
Speaker 1:I've got Maduro but I'm pulling after 75,000,000.
Speaker 3:Good good call, Taylor. And this is us crying
Speaker 1:on stream. I'm actually with the feds. He's had a rough go. Narcotraxist. John Exley.
Speaker 1:He's accused of narcotaging. Is a nostalgia. Has him
Speaker 3:innocent until proven Yeah. This was nostalgia.
Speaker 1:Allegedly allegedly Nick has done some narcoterrorism.
Speaker 3:Cocaine importation conspiracy to use and carry machine guns and destructive divisive
Speaker 1:That's a rough further
Speaker 3:into a drug crime. Very rough. So anyways no coupon code this time but
Speaker 1:you can send tips
Speaker 3:to the drug enforcement agency by email at cartelsolestips@da.know.
Speaker 1:And for folks who might be trying to track him down, you give me some overview of who Nicolas Maduro is and what he might look like if I see him on the scene?
Speaker 3:Nicolas Maduro Moros is a Venezuelan politician who has served as
Speaker 1:president of
Speaker 3:Venezuela since 2013.
Speaker 1:He's the president.
Speaker 3:He began his working life as a bus driver. Clearly He's a grinder.
Speaker 8:He's a grinder.
Speaker 3:Even though he
Speaker 1:Anyway, you wanna stay out of trouble. You wanna stay compliant. You gotta get on Vanta, automate compliance, manage risk, prove trust continuously. Vanta's trust management platform takes manual work out of your security compliance process and replaces it with continuous automation whether you're pursuing your first framework or managing a complex program. Anyway, yesterday, GPT five launched.
Speaker 1:It was gonna be quiet from Gemini, but Sundar Pichai put up a 10 k banger on the timeline, excited to make our best tools free for college students in The United States. Google Gemini is free for students. A one year pro plan offer ends October 6. They know getting back This in is the time to to get people in the in the ecosystem. Unlimited image uploads, 2.5 pro model, notebook LM, deep research, two terabyte storage.
Speaker 1:They are pushing people to onboard onto Google Gemini. They are not considering they're not they don't think that the game's over. They're gonna go up head to head with ChatGPT.
Speaker 3:Yeah. So pull up this post, Ben and crew, because the chart that people have been sharing
Speaker 1:Yes. Yes. Yes.
Speaker 3:Around over the last few days. Just And I was asking Greg about this. I was asking some some of the other people on the team. Did you feel like you got a breather over summer? The GPUs
Speaker 1:Oh, yeah. Yeah. That That That chart.
Speaker 3:Yeah. Because basically, you can see right when summer ended if you scrolled or sorry. Right when summer started, usage fell dramatically just overall tokens processed and I expect that to tick up pretty dramatically.
Speaker 1:I don't think that has to do with school though. That that drop off, that's the European vacation season. These are VCs who who use Chatuchiki when they're at work, but then on summer, they're off.
Speaker 3:Of course, John. It's it's the the VCs were They're
Speaker 1:the primary driver of Chatuchiki Seven five. Which they have to ask, like, what what what what is a foundation model? What what is a company? How do I invest? Like, how can I be helpful?
Speaker 3:Just dropping the deck in and saying,
Speaker 1:yes or Yes or no. Exactly.
Speaker 3:Give me one word answer.
Speaker 1:Exactly. But if you're in but if you're in Saint Bart's or Saint Tropez, you don't need to be using ChatGPT.
Speaker 3:You're off. You're focused on on
Speaker 1:You have a vacation responder on and that vacation responder, it's not generating tokens. It's not hitting the ChatGPT API.
Speaker 3:It's just a form. It's just a template.
Speaker 1:It's it's it's deterministic computing.
Speaker 3:Yep.
Speaker 1:It's not stochastic.
Speaker 3:It's a little throwback.
Speaker 1:Yeah. Yeah.
Speaker 3:Yeah. Anyway, so so the Gemini news is significant because clearly students are students are incredibly price sensitive. Right? Totally. Remember being a student, we didn't have we didn't have Gemini or back back in our day.
Speaker 3:But I remember there were were the different websites that would have that would just help you study for courses. I don't think I ever paid for a single one. I'd always be using the be using the free tier.
Speaker 1:Yep.
Speaker 3:And I think generally students are gonna continue to be, even though these tools are so powerful.
Speaker 1:Yep.
Speaker 3:If it's very possible that Gemini can really compete here.
Speaker 1:Well, know what else has a free tier? Graphite. Dev code review for the age of AI. Graphite helps teams on GitHub ship higher quality software and you can get started for free at graphite.dev.
Speaker 3:And Graphite CEO.
Speaker 1:Coming on Breaking the show a bit. His take on GPT five. Speaking of charts, there was a chart burning up the timeline yesterday. The SWE bench verified software engineering with thinking, without thinking. People were very upset about this because the original chart, not this one, four slides later, the initial it's from Timo Springer.
Speaker 1:Timo said this is the correct one. So people were saying, like, it was a chart crime and that went on the livestream. The chart was showing that they were at 74% up here, and then the next and then the the second bar was 69.1%, and it was much, much lower. And it made no sense because 52% is, of course, lower than 69%, and the chart just seemed really botched. What was weird is that this this chart that we're showing here is not a chart crime.
Speaker 1:It you know, you could maybe say it doesn't show exponential takeoff, but it's it it shows that with thinking GPT five beat OpenAI's o three on SweetBench. And, like, maybe that's maybe that doesn't matter to you. Whatever. But their point is that GPT five with thinking, if it triggers the thinking functionality, it's better at Suitebench than o three and four o, which is a good claim to make. Right?
Speaker 1:But people were upset about the chart crime. What's weird is that, like, it really seemed like it was some sort of translation problem because this exact image went up on the website the same time as livestream. The chart was correct on the website but wrong in the livestream. So there's like, why would you why would like if you were trying to pull a fast one on the on the chart crime world, like, wouldn't necessarily
Speaker 3:an honest mistake. I don't I don't think I don't think anyone at OpenAI was going to the event being like, let's commit chart crime.
Speaker 1:Exactly.
Speaker 3:It it seemed to be just an accident.
Speaker 1:I think it was I think it was a mistake. And I think I think what happened is that you render the you render the chart, you get the data, you render the chart, you have to you have to design it to be on OpenAI's style guide. Then you render that for the web, and then you pull that into whatever was driving the keynote slide deck and something got lost in translation there. The bar got shrunk or something didn't didn't copy over correctly and it looked ridiculous. They didn't like directly address it but it was corrected on the timeline by Timo Springer.
Speaker 1:So it was it was good. I I chatted with him a little bit in the DMs trying to understand.
Speaker 3:Yeah. Mean the thing that the the reaction was so intense Yep. Because it felt like the kind of thing that an associate at a consulting firm
Speaker 1:Yep.
Speaker 3:Would do. Yep. Which is kind of what the the the general level that it feels that a lot of these models are Yeah. Broadly.
Speaker 1:We gotta
Speaker 3:pull And that's still incredible.
Speaker 1:Yeah.
Speaker 3:But they make mistakes. They're not perfect. They're smart in some areas and and and dumb in others.
Speaker 1:We gotta pull up the the the poly market on which company has the best model at the 2025, August 3, September 30, etcetera. Because the market moved significantly. 3 and a half million dollars in volume. And yesterday, it completely flipped from OpenAI at 72%. OpenAI dropped all the way to 17% and it's kinda climbing back up.
Speaker 1:A lot of this seems to be be driven by like when will the Gemini keynote happen? When will the Gemini three launch happen? But and then if you if you look further out to December 30, Google has jumped a lot and is now sitting at at 454% to win it. Then x AI at 20%, Open AI at 17%, Meta at four per 4.4%. We don't know if if Meta will launch anything for the rest of the year.
Speaker 1:They could just be heads down grinding on on super intelligence for a while. But it's it's it's fascinating how quickly the vibes shifted yesterday. This is a wild chart crossing. And Elon chimed in said, there's free money on the table. They're selling dollars for $4.04 cents because I'm gonna come from behind.
Speaker 1:And, I mean, if if if any team is like
Speaker 3:He's making that claim around around the best AI model September?
Speaker 1:Yeah. Basically. He thinks like Grok four is or Grok five is gonna ship and it's gonna crush and it's gonna be really really strong on Ella Marina and he says, you know, he's he's he's bench maxing and he's gonna he's gonna win here. I mean he's gonna he's gonna try and win in everything. Like he's he's he's competitive.
Speaker 1:He's he's a winner. And so there are a bunch more posts. Where where Lambert
Speaker 3:says AI still has a lot of headroom but model releases are gonna be a bit more boring from now on. At least on paper, many will still be transformative in real use.
Speaker 1:Yep. Yep. Yep. So the the what what was it? The floor lifted but the ceiling held.
Speaker 1:That was the meme Tyler?
Speaker 4:Yeah. Yeah. Exactly.
Speaker 1:Yeah. So we I it's hard because we don't even know. I I feel like we don't even know what we want in terms of headroom. Gonna be this vague, like one shot everything.
Speaker 4:So yesterday when I was I was trying to think of like, oh, what should I do for TBPN bench
Speaker 1:Mhmm.
Speaker 4:Where I had the horse. But it took me like a while to like think of something that was not like completely trivial for model to deal So at this point, it's like, I don't know what good benchmarks are really. Like I guess that there's some things like arc AGI, sure. And there's something about like long task horizon Yeah. Stuff like that.
Speaker 1:Yeah.
Speaker 4:But like general knowledge like I'm I'm not surprised if it like can do you know Yeah.
Speaker 1:I mean A 100% on everything. Like the next the next
Speaker 3:I think we I think we need to do golf bench or stake bench which is being able to send an agent out into the world to generate a sale.
Speaker 1:It's good. That's a good joke. I I think that there is actually something there. When I think about, Tyler, like that video that you were working on earlier, like, that there is a world where that's just a prompt. Like, we were putting together a video for the Metis list highlighting a bunch of AI researchers, and we went back and forth a ton on the idea, the song, the the the pacing, the editing, the color grading, the titles.
Speaker 1:Do we want subtitles for this part? Do we want, title cards for other parts? And that was not a very LLM enhanced experience. Like there is a world where you just go to a chat box and you say, make make of here's the metislist.com. Make a video promoting this.
Speaker 1:And it just kind of does it. And like or or at least you're like puppeteering and orchestrating. Jordy has the ramp card. Or you're like puppeteering and orchestrating it and you're saying like at the very least go pull me the raw m p four files of every cinematic video of every every AI researcher on this list. Yeah.
Speaker 1:Like you had to go to YouTube and search and find a cool video. And you know Not
Speaker 3:that hard to find a cool video.
Speaker 4:Pretty easy to find cool videos.
Speaker 1:But it's but but you didn't do that with an LM. Right?
Speaker 4:No. Yeah. Went to YouTube.
Speaker 3:Yeah. So I think
Speaker 4:maybe the next thing is, like, we need more agent, like, agentic benchmarks. But, like Yeah. All the stuff we're saying now, it's not like, it's not information retrieval. It's not solving
Speaker 1:It is sort of information retrieval. Like at the very least I I would I would love to be able to go to an LLM and say like, you know, I'm making a vibe real about space. Pull me 75 different little three second clips about rockets and rocketry and I'm gonna mix them up. Maybe maybe I'll be the one in Premiere. I'll do the video editing but at least do the information retrieval and put it all together and and and assemble it.
Speaker 1:Like
Speaker 4:technically, if if it's like giving you links to YouTube that makes
Speaker 1:I don't want links. I want m p fours. I want it to do the hard part of the But m
Speaker 4:p fours, that's like well, it's like semantics now but that's like agentic because you have to download the video.
Speaker 1:Yeah. Yeah. No. Cut it up. Yeah.
Speaker 1:That's what I want. Yeah. Yeah. I want that.
Speaker 4:So I guess it's still information. But I'm talking about like raw like tokens. Like it's giving you some tokens back.
Speaker 1:Which is like arbitrary though. Like I I'm I'm fine with it going to youtubedl.xyz or whatever and like downloading the file, doing all that stuff. Yeah. I mean, like, that should be able to, like, use the web in a much in a much more in a much deeper way. It should just, like like, right now, there is there is, like it can open up a website and retrieve the information and the text on that website, And then it can use a few tools that, like, we've given it access to and RL'd on.
Speaker 1:But, like, we want it to RL on every single website that is a tool. And so that when you talk about the flight booking UI, it's like go and go and RL on every flight booking UI. Go in go in RL on on the YouTube downloader and YouTube itself and just be able to crawl around the web like like anyone has to do for any task. Right?
Speaker 4:Yeah. Well, I mean I mean, Greg said yesterday, like, years aren't over for agents. So hopefully, we'll get something.
Speaker 3:Yeah. That was a cool little hint.
Speaker 1:Yeah. Yeah. And and and again, it's like, I don't know that that's I don't know that that's a keynote. That might just be like chopping wood
Speaker 3:Yep.
Speaker 1:Getting better and better and better. And it's like, people will keep coming to it with tasks. Because I come to it with tasks where there could be an agentic, like, workflow that solves even more. Like, the the the the good example is like with the Bento, I was I I actually had stepped through it. I was like, first, do a deep research report on what was actually announced at g p in GPT five.
Speaker 1:Give me all the features, summarize them all, then turn that into a table, then turn that into an AI image. And and it was like four steps, and I should have just been able to one shot it and say, hey, you know you know what Apple has those Bentos? Like, make me one of those. And then behind the scenes, you're gonna go do the deep research. You're gonna pull all the facts and and the figures, and then you're gonna lay it out and stuff.
Speaker 1:I don't know. Anyway.
Speaker 3:Breaking news, Softbank.
Speaker 1:Softbank. Softbank.
Speaker 3:Folks. Softbank reportedly bought Foxconn's Ohio factory for the Stargate AI project. Reading into this.
Speaker 1:What did do?
Speaker 3:Haven't seen it. They acquired one of Foxconn's Oh. Factories. Interesting. The mystery buyer of the former General Motors factory owned by Foxconn in Ohio is apparently SoftBank.
Speaker 3:SoftBank wants to use the factory to build AI servers as part of the Stargate data center project being Yeah. Spearheaded Yeah. By SoftBank, OpenAI, and Oracle. This report comes just a few days after Foxconn announced it had sold the factory along with electric vehicle manufacturing equipment that was inside of it Yep. To a buyer it only referred to as Crescent Dune LLC, an entity that was created in Delaware in late July.
Speaker 1:Interesting.
Speaker 3:So I didn't know if you were tracking this at all.
Speaker 1:I'm not.
Speaker 3:But SoftBank is up 63% year to date.
Speaker 1:Congratulations to Masa.
Speaker 3:That's actually that's actually somebody asked us who our dream guest was and John's first reaction, Theo Von.
Speaker 1:Theo Von. Shaquille O'Neal.
Speaker 3:He's interviewed some of the great
Speaker 1:Seijin Ping. Seijin Ping would be good. Masa Benjamin Netanyahu did Nelk Boys. I'd love Seijin Ping to do TBPM. That'd be cool.
Speaker 3:Masa Yoshi So
Speaker 1:Masa, Yoshi, would also be great. Very fun. So But I want him here in the studio.
Speaker 3:Yep.
Speaker 1:Get to the Temple Of Technology, Masa. We wanna hang out with you and have you ring the gong 25 times for all your various deals that are gong worthy.
Speaker 3:Yep. Will DePue, friend of the show says multi layer SPV should probably be illegal under the current interpretations of securities regulation. I'm getting d m's from long lost cousins about eight flare anthropic SPVs claiming direct cap table access.
Speaker 1:I think those that should be should probably be illegal. He he should just say, are probably illegal. Like like, I'm I'm pretty sure if you if you lie in a securities offering and you say you have direct cap table access. And in fact you do not have direct cable to cap table access.
Speaker 3:You're misleading investors.
Speaker 1:Yes. That that is that is financial fraud. A wire fraud and you will wind up in the clink. In the clink. Anyway, ProFound get your brand mentioned on chat GPT reach millions of new of consumers who are using AI to discover new products and brands.
Speaker 1:Incredibly bullish day for ProFound too. Seriously. Because knowledge retrieval is gonna be really really important going forward. People are gonna be searching ChatGPT, what product should I buy? You wanna know whether or not you're you're showing up in the rankings and ProFound helps you do that.
Speaker 1:So pretty much Ramp. Brand's gonna need to do this.
Speaker 3:Ramp boosted their AI visibility by seven x Really? In ProFound. They boosted visibility here on using this massive ramp card. Yeah. You gotta do it all folks.
Speaker 1:Yeah. Yeah. I mean, really really like another company that didn't get steamrolled yesterday.
Speaker 3:Yep. Dylan Patel says GPT five is disappointing NGL.
Speaker 1:Well, we're joined by Fabricated Knowledge who works with Dylan Patel in maybe thirty minutes to talk about GPT five and what's going on in the semiconductor industry. And I wanna talk to him about how how we should be thinking about building inference clusters. Now it feels really, really important to only be serving profitable tokens And the age of of of deeply unprofitable inference will have to come to a close at some point.
Speaker 3:Yeah. I wanna I wanna You remember it wasn't that long ago that Satya was pulling out of various data center deals. I'm happy to be Yep. A leaser.
Speaker 1:Yep.
Speaker 3:And this feels like he kind of saw this Yep. Coming.
Speaker 1:What did Satya see?
Speaker 3:What it's Yeah. Seriously. His his beef with with Elon was Yeah. Was funny yesterday. I'll see if I can pull up the post here.
Speaker 3:Elon said something to the effect of OpenAI is going to crush Microsoft.
Speaker 1:Oh yeah. This was a funny post. Such a funny
Speaker 3:Elon post yesterday, OpenAI is gonna eat Microsoft alive which I don't know exactly why Elon is saying that it kind of feels like potentially some some some four d chess.
Speaker 1:Yeah. It was very odd because announcement yesterday. Elon usually isn't rooting for OpenAI. He's usually at war with OpenAI. And so it it it's it's kind of it reads as like you're bullish OpenAI.
Speaker 1:You're long OpenAI. You're short Microsoft. But there's clearly something else going on there.
Speaker 3:Deal. Microsoft's in OpenAI right now. A lot of regulatory scrutiny. Yep. He's probably trying to do something around that.
Speaker 3:Yeah. Feels like response. People have been trying for fifty years
Speaker 1:That's the fun
Speaker 3:of it. Microsoft life. Each day you learn something new, innovate, partner and compete. Excited for Grok four on Azure and looking forward to Grok five.
Speaker 1:Such a good response. Satya. Absolute dog.
Speaker 3:He's an absolute dog.
Speaker 1:Greatest ever.
Speaker 3:In other news, esteemed journalist, Zero Hedge is saying, we have officially crossed streams. Companies have no more free cash flow to pay for data centers so we have entered the private credit phase. I I would put this in the truth zone, there's been a lot of data center development that's already been getting funded by private credit. Yeah. Meta, this this was in response to Meta picking PIMCO and Blue Owl for $29,000,000,000 data center
Speaker 1:Yeah.
Speaker 3:Funding. We had reported earlier on the show that like Meta's like cash balances between the end of last year
Speaker 1:Mhmm.
Speaker 3:And and now dropped dramatically Mhmm. Like 7075% or something like that. But again, they have still a lot of free
Speaker 1:Yeah. I think people maybe get too puritanical about debt to equity ratios. Like, Apple is incredibly cash flow positive and has returned something on the order of a trillion dollars to shareholders over the past decade plus. And they still issue debt because there are, like, designing your capital structure to match your business activities makes a lot of sense. You wanna fund r and d with equity, maybe with cash flow.
Speaker 1:But if you're just if you're just buying a house, it's okay to have a mortgage. If you're buying a data center, it's okay to have some debt financing that. But you wanna be able to service that, obviously. The interesting thing here is, like, you yes. You do need to make sure that you don't get over your skis and wind up building a bunch of, you know, dark fiber and get really, really, really in trouble when you if you issue a ton of debt, and then that sits at the top of the top of the cap table and you are in trouble and you're servicing this and you're not making any money, the main thing is, like, if you if Meta raises 29,000,000,000 in data center funding and its debt, and then they can't monetize that data center at all, and then they have trouble paying the the the interest on that and the and the and the principal down like that could be trouble.
Speaker 1:But Metas makes $29,000,000,000 like all day long. Like that's not that's not a problem. Frequently. So there there there are probably pockets of of risk all over, but unclear how how early we are to the to the the the, like, the scaremongering around this. But something something to keep an eye on, something to see.
Speaker 1:Private credit's a little bit different because it has very long time horizons, and and it it doesn't have as much of a systemic issue. Like like Blue Owl and PIMCO, you don't have you don't have these, like, multilayered, like, financial products and financial engineering that winds up in the hands of the consumer and is driving these, like, really, really, like, frothy deals like we had in the mortgage backed security crisis. But certainly something Well,
Speaker 6:to be
Speaker 3:clear, there's bears out there that that are very that that think we're in a massive private credit bubble. Yeah. And it certainly It's true. Looks like a bubble.
Speaker 1:Yeah.
Speaker 3:Whether or not it blows up, we'll have to wait and see.
Speaker 1:We will. The meantime, we'll tell you about Linear. Linear is a purpose built tool for planning and building products. Meet the system for modern software development. Streamline issues, projects, product roadmaps.
Speaker 1:Start building at Loon.
Speaker 3:Well, little bit of a white pill here. We have a post to pull up from a listener, Max. He says, purchased a nineteen fifty nine three fifty six a speedster to get into the mindset of Jordy. I found myself overcome by a sense of positivity and confidence. I also became five two.
Speaker 1:You really is a perfect That's the perfect type for a speedster. That I mean if you are if you're a five two you you deserve a speedster immediately. Tyler give us the speedster review. You you drove in it.
Speaker 4:Very small. Very small. It's unbelievably small. I didn't realize like cars from that old were that small.
Speaker 1:Were people just small back then or something?
Speaker 4:Yeah. I don't know. Didn't understand it. Little tiny people driving their little cars.
Speaker 1:What's weird
Speaker 3:is Well, if you look at the growth of Porsches broadly, they they just get bigger and bigger and bigger and bigger.
Speaker 1:Sure. Sure.
Speaker 3:Sure. And this is like the purest hate it.
Speaker 4:Maybe with the rise of Ozempic, we'll see cars get smaller again.
Speaker 1:Oh, maybe. Interesting. Well well, yeah. I mean, Germans I feel like are tall people. I'm I've always thought that like getting a like a big Mercedes is like aligned with like a big German guy and like it kind of fits.
Speaker 1:But I don't know, maybe back in the
Speaker 3:sixties they were just designed them for like Mercedes?
Speaker 1:I Small mean people.
Speaker 3:Remember. I feel like in our lifetime Mercedes were pretty small. Remember like Steve's?
Speaker 1:Like Yeah. The SL six Totally. Yeah. It's a small car.
Speaker 3:Right. Small car you probably wouldn't fit in it.
Speaker 1:No. The short kings were dominating the the feedback form of Porsche and Mercedes, I suppose. Anyway, Growing Daniel says, let Rune emcee these things. I completely agree.
Speaker 3:Completely agree.
Speaker 1:It would have been great to have him on stage. I mean, he's just so good at like kind of talent like it is, keeping people on the pulse.
Speaker 3:If you if you wanted to optimize for like, my question is how many people were watching that livestream Mhmm. That were non, like, x. Like, it it felt like it felt like the core audience for that was like the timeline.
Speaker 1:Yeah. Yeah. Yeah.
Speaker 3:That was my my perception.
Speaker 1:And Rune is someone who lets you in the timeline.
Speaker 3:Yeah. If you were gonna make the perfect live product for the timeline, you'd probably have Rune.
Speaker 1:I was noticing that with our buddy Logan Kilpatrick and Demis Hassabis are doing a podcast together.
Speaker 3:Yeah.
Speaker 1:Did you see this? The screenshot? And I was just like, and I think I think just the screenshot of like they're doing this together got like a thousand likes. And I was like, that is good content. That's what I wanna
Speaker 3:I was catching up with Logan earlier this week and he's like, oh, I'm going to London to to do a podcast. And I was like, what podcast? Like what? Like do you need to go to London just to record a podcast? And he's like, oh, with Demis.
Speaker 3:Yeah. Was like, oh, okay. I get it now.
Speaker 1:Yeah. And I and I think I think he just he had Logan just Logan, Rune, all these sort of like, you know, forward facing developer advocate folks who can speak to the timeline. They just bring a completely different energy than someone who has like prep talking points. And so even if they're even if they're not like the deepest researchers, just being able to to communicate is a very fine vibes. Exactly.
Speaker 1:Exactly. Much like NewMoral HQ sales tax on autopilot. Spend less than five minutes per month on sales tax compliance. Go to numeralhq.com. Will Brown.
Speaker 3:Super intelligence.
Speaker 1:So this has
Speaker 3:been around for a while and it's numeral.
Speaker 1:Yes. So this is the yeah. This Will Brown posted interesting. He says, okay. GPT five, this model kind of rules in cursor.
Speaker 1:Instruction following is incredible. Very literal. Pushes back where it matters. Multitask quite well. A couple tiny flubs format misses here and there, but not major.
Speaker 1:The code is much more normal than o threes. Feels trustworthy. And this is the interesting thing about like like, it was GPT five, but it was kind of it was kind of framed as, like, this is a major change to chat, GPT, our our our wrapper, our consumer product. But there's a whole like, OpenAI is not just one business line. Like they're going we were talking to Sarah Fryer about this like there is a world where when OpenAI goes out to the public market, analysts are valuing the business on it's a high growth consumer company like Google search.
Speaker 1:And then you also have an enterprise business and it's basically a hyperscaler. It's cloud.
Speaker 3:Based on the recent numbers Yeah. OpenAI has 10 times Figma's revenue. Yeah. So And obviously, it's not profitable.
Speaker 1:What's their latest tender? About five times the valuation.
Speaker 3:Yeah. So No, 10 times.
Speaker 1:Yeah. Yeah. But yeah. But but about 10 times the valuation. Yeah.
Speaker 1:And so But but but my my my point is that there's is that there are there are multiple business lines within OpenAI the company now. And you might even see a bit a new business line spring up around open source implementation, enterprise installations, fine tuning, also just API selling tokens, also consumer, also different spinouts. Like, they might wind like, Google eventually had to start disclosing, like, I'm pretty sure they had to start disclosing YouTube financials because YouTube became such a big business. And there's a threshold where I believe if I believe if the company if the if the suborganization reports the CEO or something like that or or it's material in terms of, like, greater than 10% of your overall top line or or profits, like, then you have to break out those numbers in your GAAP financials. And it's interesting to think about, like, where will the lines be drawn in the OpenAI business?
Speaker 1:Because they and then how will that translate to their communication? Because there is a world where they where yesterday's news was kind of two different things. One is that we made the consumer product easier to use for the hundreds of millions of users that don't know what post training is or RL is. They just want an easy to use app that answers their questions, And we did that. And then also, we our coding API a bit better so that we are now neck and neck with Anthropic.
Speaker 1:And so if you're a company that is buying cogeneration tokens, you should come to us and it should be and that market should be more oligopolistic as opposed to more monopolistic as it's been. And so there's a world where we see, you know, these these oligopolistic cloud enterprise b to b businesses crop up on the on the hyperscaler side with Gemini and Anthropic and and OpenAI b two b, and then maybe Thinking Machines gets in that game, maybe SSI gets in that game. No real indication that MSL or Meta Superintelligence will get in that game. But you could see kind of like a a similar dynamic as, like, what's what's happened in the hyperscaler clouds play out on the b to b token generation from Foundation Model Lab side, which is still great business. But then you also have a wrapper, and you also have a consumer application.
Speaker 1:And then you might have other other products that's that crop up. I mean, like, Google makes money off of Gmail. They make money off of Google Maps, and and they don't need to even break those out. They just put them into different services. But I think we'll see, like, you know, an increasing, like, you know, pattern of different pieces of the business that add up, and all of them will be will be generating they'll be they'll all be profitable, but the question is, like, how much attention will they get, and then how much financial, like, performance will they actually drive?
Speaker 1:So All set. Anyway, we should go to Mike Newpe from Arc AGI, the final boss of AGI. He decides whether or not a model is superintelligence.
Speaker 3:What does he say?
Speaker 1:He said OpenAI prioritize the right I'll I'll do a Mike Newpe impression here. OpenAI prioritize the right thing with GPT five. To get to 1,000,000,000 users, the model switch sure needed to go. But the hype marketing playbook they're known for fell below folks' expectations and warrants reflection. Benchmarks could have been used to support the main story instead of benchmarks don't matter.
Speaker 1:Real world use cases matter. They could have used benchmarks to show how effective their automatic reasoning effort system is. They could have shown state of the art in automatic reasoning. In fact, this is something we wanted to test ARC, but the GPT five API does not support auto reasoning. Key point, benchmarks are important tops to to communicate with the public and can be used more effectively to communicate capabilities than raw intelligence.
Speaker 1:State of the art. And so, yeah. Another another twist on like just the messaging being like like an odd choice here or or just we're just in a transitory And
Speaker 3:what percentage what percentage of the 100,000,000 weekly actives that they have in The United States?
Speaker 1:Actually 80% or something? No. I'm saying
Speaker 3:based on on the numbers we got on the show yesterday, they have roughly a 100,000,000 weekly actives in The US. What percentage of those people even are aware of the hype marketing? What percentage saw the Death Star picture?
Speaker 1:Yeah. Totally.
Speaker 3:Not that many. Right?
Speaker 1:Mean, got
Speaker 3:it did get millions But of
Speaker 1:yeah. But but x is like a is a specific corner.
Speaker 3:Yep. Zachary speaking of the Death Star. Yep. Zachary.
Speaker 1:Very negative. But you did kind of set yourself up for that one. It's odd. It's odd. It did not fully make sense like who who is the Death Star in this in this story?
Speaker 1:Are you the Death Star? Are you Alderaan? Are you the rebels? What are you blowing up? Maybe the Death Star let's steel man this.
Speaker 1:The Death Star is It's a big model, sir. Yeah. The the Death Star is the idea that pre training scaling is all you need.
Speaker 4:You're gonna blow up Alderon like you're gonna blow your minds with how good the model is.
Speaker 1:But Alderon was good. Alderon was good. Don't want Alderon to be blown up.
Speaker 4:Yeah. I don't think you gotta read into it so much.
Speaker 1:I think you'd I think we do need to it. I think it's Extremely. We need to read into it endlessly.
Speaker 3:The the image is provocative.
Speaker 1:Yes. So so if A lot of
Speaker 3:people said there's still time. I think Nikita was in the replies being like
Speaker 1:There's still time to delete this. Yes. If but if we if we steel man this we are saying that that the Death Star is bad therefore Sam is saying he's good so he's going to blow up the Death Star. What did he blow up that's bad?
Speaker 3:The model switcher.
Speaker 1:Yeah. Yeah. There you go. The model switcher is the Death Star. And today it goes it's been this massive piece of UI in your face.
Speaker 1:There was a trench run and they blew up the model switcher. This is good. We got it. We nailed it. We understand Sam Waldman.
Speaker 1:We we're in his head.
Speaker 3:For some reason, I think I think I I don't think that's an accurate read but
Speaker 1:I like it. It's fun to protect. I think you nailed it. Anyway, you know who else nailed it? Fin dot ai.
Speaker 1:The number one AI agent for customer service. Number one in performance benchmarks. Number one in competitive bake offs, number one ranking on g two. Anyway, Mike Mike Noop also said, I'm quite confident this approach will work for a while. This is based on the lack of continual learning from Dwarkash Patel.
Speaker 1:Continual learning is the main bottleneck holding back AGI and economic automation. We expect this bottleneck will be overcome not by some new learning paradigm, but by scaling the diversity and volume of RL environments. This is Cosgrove's Cosgrove's scaling law. You need to be bench maxing. Correct?
Speaker 4:Yeah. And then I yeah. Yeah. The bull case on bench maxing.
Speaker 1:The bull case on bench maxing. So the bull case on benchmark bench maxing is that continual learning is intractable. We may hit it. We may not. Might be two years.
Speaker 1:Might be twenty years. So in the meantime, focus on scaling the diversity and volume of RL environments, create a ton of benchmarks, and then bench hack them. Correct?
Speaker 4:Yeah. And you Yeah. Like you can It's a it's a bull case that Elon is bench maxing.
Speaker 1:Mhmm.
Speaker 4:Because that just shows that his team is like good at optimizing over very specific like
Speaker 1:Yeah.
Speaker 4:Kind of vertical like tasks.
Speaker 1:Yes. He just better pick the right tasks. Because I don't like the task he's picking right now that he's bench maxing. It's not good. Yeah.
Speaker 1:But if he if he finds if he does find other pockets. I mean, he's certainly bench maxing on on Tesla self driving. Right? That's the key thing. Like number of Yeah.
Speaker 1:It's of number of interventions per like million vehicle miles traveled. And and every day they are they are trying to hack that reward function to get it to zero.
Speaker 4:Yeah. That's a good one. Maybe a bad one. Maybe he's bench maxing too much on kind of gooning.
Speaker 1:Yes.
Speaker 3:He's goon maxing.
Speaker 4:Yeah. I think we should steer away from that.
Speaker 1:Yeah. We need to steer away from that. Figure out something else to do with the with with with the XAI companions. But maybe there'll be something else that something else that they can reward hack there. Maybe something in in therapy or friendliness or you know, some sort of coach.
Speaker 1:I don't know. Maybe it turns into a fitness coach. Maybe maybe I need to to use it to really up my training in the gym. Be like, hey, cool it with all that cool it with all that lewd behavior. Give me advice on how I can double my bench press and chat with me about that.
Speaker 1:May maybe that's the right move. We'll see. Anyway, McNoop is optimistic. He says, I'm quite confident this approach will work for a while. It requires no new science.
Speaker 1:It exploits everything we know about AI reasoning systems. We teach process models through memorization and domains where we can generate lots of synthetic but real data, and then nonzero fluid intelligence emerges from the resulting chain of thought knowledge recomposition system that sits on top of the foundation model, but it still reminds me of pre training scaling where we were making AI systems better through imitation learning and stuffing more into them versus an AI system that is capable of cold starting itself in some new domain it's never seen before. And that's why ArcGI is so important because because the the the final evals are so hidden behind that that that secret test set. It's the AI systems need to be able to cold start themselves when they when they run into a game that they've never seen before in the test environment in in the Arc AGI private eval set. And that's why they fall flat on their face consistently and they're sitting around sixteen, fifteen, 8% success rate on on Arc AGI two which can be solved by any human pretty easily.
Speaker 1:But Elon says Grok five will be out before the end of the year and it'll be crushingly good. He's bench maxing. He knows Arc AGI is the one to go for. And so he's gonna be he's gonna be RL ing on this pretty He's gonna have a whole team on Arc AGI. I'm I'm excited to see what he does.
Speaker 1:I wonder how he'll do on v three. That will be very very interesting. Anyway.
Speaker 3:Well, in other news, we have a post here that we can pull up from Bonu Kohli team. It is in the chat if
Speaker 1:you can
Speaker 3:pull up. He says, yesterday, Rail Financial signed a definitive agreement to be acquired by Ripple for $200,000,000. Four years ago, I set out on a mission to speed up business to business global payments using USCC. Over the last six months, we grew to became to become 10% of b to b global stable coin settlement volume. Airhorn for that.
Speaker 3:With Ripple, we will further accelerate our shared mission. Thank you to our employees, clients, investors, and partners for taking an early bet on us. A few that Tarun and I wanna call out, the entire Rail team for their relentlessness and hard work. Avlok, of course, the CEO of AngelList, our first lead investor and part of the founding team. And Gokul Rajaram, immensely helpful during some of our early crucible moments.
Speaker 3:And of course, Mike over at Galaxy for taking the bet on us in the series a. We are excited to start our new chapter with Ripple once all regulatory approvals go through. Hit that gong, John. Great contact. Great contact.
Speaker 3:I was lucky to angel invest in the seed round of Fantastic. Rail. And this is a fantastic out front outcome for the team. And This this one was a so so I first met Bonhoe, I think back in 2021 or 2022. We were both working on on stable coins at the time.
Speaker 3:Loved his vision. Haven't haven't stayed super close since then, but he's been absolutely cooking. And I was very pleasantly surprised when I got the news a couple days ago. So incredible work to the whole rail team and a great pickup for Ripple.
Speaker 1:Amazing. Let me talk about Adio. Customer relationship magic. Adio is the AI native CRM that builds scales and grows your company to the next level. Get started for Sam Altman posted GPTOSS is out.
Speaker 1:We made a hot an open model that performs at the o four mini level. Can we
Speaker 3:create our own pronunciation for this? GPT ooze. GPTOS. GPTOS. It runs on a
Speaker 1:high end laptop. Smaller one runs on a phone. Super proud of the team. Big triumph of technology. Has community note on it.
Speaker 1:I don't know what's in there but that's very funny.
Speaker 3:Okay.
Speaker 1:Anyway, but Donald Donald Boat. One of the greatest to ever do it.
Speaker 3:Donald Boat responds, Sam, you and me, the Amalfi Coast. Me, double for nay on the rocks. Club soda to taste. You, one delightfully sweet bitter Negroni stirred 92.
Speaker 1:Nine point Two nine hundred million billion. Revolutions Counterclockwise. Counterclockwise. One for each hertz of the Nvidia fifty ninety in the gaming PC you will buy and ship to my house. And And Sam
Speaker 6:said he
Speaker 3:actually sent
Speaker 1:He sent it.
Speaker 3:I love it. Popped up yesterday.
Speaker 1:This is timeline victory.
Speaker 3:Hop on fort at Sam.
Speaker 1:Yeah. And, yes, Sam said, okay. This was funny. Send me your address and I'll send you a $50.90 and he did it. And I love this.
Speaker 1:This is this is the type of, like, you know, small ground game that we identified earlier. You know, Sam, he didn't have to drop the big long post. He was vague posting. The vague posting was a little mixed result, but this is a win. This is a fantastic win.
Speaker 1:This just builds the team, builds a lifelong fan. This is hand to hand combat on the timeline and I love to see it. So, great great to be to be doing this type of stuff even even the day before GPT five launch day.
Speaker 3:Donald Donald Boat is really an account to watch. Laser boat nine nine nine.
Speaker 1:Get in early.
Speaker 3:Get in early. Mean Like buying Bitcoin in 1990 John. Four. He's under a 100 k.
Speaker 1:Still like buying Bitcoin in 1994.
Speaker 3:That's right. That's right. Or Solana in the eighties.
Speaker 1:Yep. Dylan Fields is GPT five is here in Figma Make. We have started to roll out GPT five to starter and pro plans. Let us know what you think. More model news comes tomorrow.
Speaker 1:I mean, this is a good news for Figma Make. Of course, cheap. We talked to Rahul about this. Cheaper model, better reasoning, better cogeneration. The product just gets better, and this is the value of being, you know, somewhat of a rapper.
Speaker 1:Right? Like, you are a beneficiary of model improvements when as the models get cheaper, your margins naturally get cheaper. If the models get better, your product just naturally gets better. And so lots of Good morning, people
Speaker 3:added Gemini two point o flash Yes. In their image editing. Mhmm. So you can just like drop an image in and then click it and say, remove this person from the image. That's very cool.
Speaker 3:Yeah.
Speaker 1:Well.
Speaker 3:Anyways, Kevin Quoc says forcing Lip Buuton out of Intel is probably one of the worst things you can do if you wanna save The US chip industry. Someone should tell White House that before we put Intel back in a tailspin. Again, they Intel whatever you think about Lip Bu Tan and his approach. It seemed I think stability in the short term is good. Right?
Speaker 3:Yeah. He's trying pull them out of the tailspin.
Speaker 1:Yeah. So my take on this is it kind of feels like Trump has an outdated world model for understanding the importance of Intel. Like, Intel is a fantastic American company, but it has not been on the frontier of semiconductor manufacturing for a while. They they famously missed mobile and ARM crushed it in mobile, and then that was important for semiconductors. And then, and then they they weren't a fabulous semiconductor.
Speaker 1:So TFMC ate their lunch there. They kinda missed out on the GPU boom, and NVIDIA dominated there. And so, the the question of this, it seemed like Trump was worried about Lip Buuton's ties to China, but China has already caught up to Intel's, I think. Like, between Huawei, SMIC, SME, they these companies seem fully capable of doing everything Intel can do and probably more and probably better and probably cheaper. And so Intel hasn't been the crown jewel of American semiconductor supremacy for decades.
Speaker 1:Basically, no one is advocating for a real comeback with Intel right now. Like, the idea of even splitting Intel up, like, there was like, for a long time, there was like, oh, with just one weird trick, you know, semiconductor CEOs hate this. Let's let's figure out some, like, elegant switch. Let's just split design and fab, and then Intel will be great. That's not even what people are advocating for now.
Speaker 1:Like, they tried to kind of test their waters of splitting the fab out, and they couldn't get a customer for what they were going to make at this new fab. And if they can't get an independent customer that's not Intel, well, then who are they going to why do they need to be a like, a why do they need why do they need a pure play fab if they don't have a customer for it? So there were just, like, all these problems. So what Lip Bu Tan is doing is he's coming in not as, you know, this, like, gambit to get on the frontier. He's, like, winding down the company.
Speaker 1:He's, like, he's laying a bunch of people off. He's narrowing the scope, and he's coming in like a McKinsey consultant almost. And so this doesn't feel like that key of a of a company in the American semiconductor race. Like, the future of American semiconductors feels like TSMC and Samsung, which are both building fabs in The United States, which is nice, but also these are these are companies that exist in allied countries. So it's not it's nowhere near as as as risky as being dependent on a on a on a supply chain that's based in a near peer adversary like China.
Speaker 1:So it's not like if TSMC was in Beijing and Samsung was in Shenzhen, like, we would be in a lot more pain than we are. But Samsung and TSMC are also building in The United States. And so, the leading edge will be in The United States, and it will be led by other companies. It doesn't feel like Intel will play a really key role in there. Certainly, we'd love that, but that doesn't seem like the current plan.
Speaker 1:And so it's kind of it it it it's kind of just like an odd sideshow. I think it's a lot of legacy about the the the brand recognition and the name recognition of Intel, But it doesn't seem like Yeah. And ultimately, should think we
Speaker 3:should let Intel's board make the the best that make their own decisions around Intel's leadership. Know, we've got this amazing system Yep. Called free market Yep. Capitalism. We try to stay as close to that as possible.
Speaker 1:It is it is funny because Trump is also trying to IPO Freddie Mac and Fannie Mae, the two private the the the our our state owned lenders. You can go get student loans and mortgages from this. So, like, simultaneously in the in the lending markets, we're trying to we're trying to, you know, deregulate or or move out of government control. And then simultaneously saying, like, well, actually, we we'd like the government to be able to decide who the CEO is at this private company. That's kind of odd.
Speaker 1:Anyway, good luck to Lip Bu Tan. He is losing a lot of sleep. He's gotta get an Eight Sleep, get a pod five, five year warranty, thirty day risk free trial, free returns Lip. Free Get an Eight Sleep. You need one.
Speaker 3:Need We to be up will gift you an Eight Sleep.
Speaker 1:And then come on the show.
Speaker 3:Doing important work for this country Yeah. And Intel. And you've got an Eight Sleep on us whenever whenever you're ready.
Speaker 1:100.
Speaker 3:Just let us know. Bucocapital Bloke says, for those of you blowing out your SaaS positions, even though time is of the essence, please try to maintain a sense of order. Single file line, eyes forward, do not stop for personal belongings, do not panic, do not run. Of course, he's telling, talking about everybody selling out of various SaaS positions.
Speaker 1:That's what he means
Speaker 3:by the I came away
Speaker 1:Selling them.
Speaker 3:I came away yesterday being not broadly bearish on a lot of different SaaS. Systems of record. I think they're in a really good position to offer intelligence I
Speaker 1:mean, few days ago, we were talking to somebody who was saying, like, all SaaS is cooked as soon as AI goes goes hyperbolic. And yesterday, it felt like, okay, that's not that's not happening today. So SaaS is actually great. And the newer SaaS I mean, like, even the there are still companies that are on completely legacy systems still on paper and pencil and and still on mainframe, still on owned clouds, still haven't migrated to the new clouds, still haven't embraced SaaS, still haven't embraced AI. So I think that there will be, like, a full cycle of replacement here.
Speaker 1:And we see that with with Figma. We were talking about like like, is there some sort of threat to Figma from like, oh, you just one shot a vibe code blah blah blah blah blah. Like, and you don't even need the tool at all? Like, maybe. But like, first, let's Let's talk about talk about how how much people dislike Adobe.
Speaker 1:Like, you know, there's a lot of there's a lot of people that would just that are still are still haven't migrated over to, like, the thing that was invented a decade ago. Yeah. And are still on 20 or 30 year old software. Well, these things go in really big cycles.
Speaker 3:Down 22% Well date.
Speaker 1:Of what you think about Adobe, maybe you're long, maybe you're short, do it on public.com investing for those that take it seriously. We got multi asset investing, industry leading yields. They're trusted by millions of folks. And we have our first guest of the show, Doug O'Loughlin from Semi Analysis Fabricated Knowledge. Doug, how are you doing?
Speaker 1:Welcome to the stream.
Speaker 7:I'm doing really good. Can you guys hear me?
Speaker 1:Yeah. We can hear Okay.
Speaker 3:You came in looking like you're about you're
Speaker 7:playing it. You're like
Speaker 1:We're really quiet. Okay.
Speaker 7:One tenth point.
Speaker 1:I can yell. Yeah. Yeah. Would it help if we yelled?
Speaker 7:It would help if you yell.
Speaker 1:Okay. We'll do the rest of the interview yelling. Also
Speaker 3:I love that.
Speaker 1:Do you have the ability to turn up the volume on your side?
Speaker 7:I am turning up the volume, bro. Oh my god, man. I feel like a boomer.
Speaker 1:You're all good.
Speaker 3:You came in looking like a DJ playing a hot boiler
Speaker 1:on set.
Speaker 3:You had your you had your hand here.
Speaker 7:Messing with my audio system fucking
Speaker 1:Is it one
Speaker 7:know, it's years of the Zoom economy.
Speaker 1:Yeah. Isn't one of those things where the volume on one of the sub applications is turned down while the volume on the system level is turned up?
Speaker 7:Know. Dude, I see the sub application. I see the system level. This is extremely boomer for me. I'm embarrassed.
Speaker 3:Well, enjoy these moments where Zoom fails us because it's it's it's this incredible and you know, you can trust that to, you know, having infinite intelligence available But in your we're still we're all still trying to get video conferencing to work reliably. So I'm, you know
Speaker 1:Okay. We'll just Yeah. Let's go to the normal. We usually don't have a problem with feedbacks if you if you turn off the headphones and then you just use the speakers. We usually won't get feedback.
Speaker 1:So let's see if that works. Any luck?
Speaker 7:I can hear you.
Speaker 1:Okay. Cool. Yeah. Can we can we chat?
Speaker 7:We're good? Yeah. We can chat. This is much better.
Speaker 1:Awesome. Great. Awesome. Cool.
Speaker 3:Welcome to the show.
Speaker 1:Welcome to the show. Been looking this. Been looking forward to this. We missed you in New York City. We were hoping to hang out there, but I'm really glad you could hop on remotely.
Speaker 1:Give us your reaction to GPT five.
Speaker 7:To Lip Bu Tan. Correct? Sorry. I damned you. I'm still really No.
Speaker 1:You're good. I mean, yeah. We yeah. We can start with Lip Bu Tan. We were just talking about that too.
Speaker 1:Are you are you in favor of a change of of of the guard over there? Okay. How'd you process this?
Speaker 7:Sorry. If we're talking about
Speaker 1:yeah. Intel.
Speaker 7:I can do an extremely based rant on the board. Please. Heard about this in Fabricated Knowledge, and I definitely was part of the semi analysis post too.
Speaker 8:Sure. Okay.
Speaker 7:Perfect. I can hear you now. Okay. We're we're we're done. We're through it.
Speaker 7:Okay.
Speaker 1:So let's go.
Speaker 7:Okay. So okay. Now now, dude, turn it up to 12. Okay. So, dude, TLDR, the board has been systematically screwing up Intel for the last ten years.
Speaker 7:This, I think, comes from the history of Intel being the greatest semiconductor company alive of the twenty tens. Dude, the board was filled with, like, politicians and, like, ex senator what what you call it? Secretary of state and, like, generals and, like, never anyone in the semiconductor industry. Intel had a, like Intel had, like, a view of arrogance. Like, we are the best, and you're gonna suck it because we're the best.
Speaker 7:Like, you know, effectively, it is a Intel first world view that, like, has slowly been crumbling over time. So pretty much on the technology side, they've never ever had anyone who actually knew how to run a semiconductor company except for professors or people on Intel. So, like, you can look back in, like, the 02/2003, 2004 era. It's usually two or three people from Intel, and then the rest of it is just, like, randos. So they never thought, hey.
Speaker 7:Why do we need a semiconductor person on the board? This slowly became a melting frog issue as they, like, missed. The 10 nanometer debacle is, like, the real big, you know, change point in Intel. And
Speaker 1:Really quickly. Alright. Can can you unpack the 10 nanometer debacle a little bit?
Speaker 7:Okay. So 10 nanometer was Intel's process at the time. It was supposed to be the next one after 14, and I think it's plus plus plus plus or maybe so pretty much it got delayed. So they tried to do a lot of aggressive technologies. They did quad pattern DV, copper, you know, cobalt interconnects.
Speaker 7:A lot of things they shoved in here to make it a good product, but they just missed over and over and over again. So it was a ginormous fumble. And at the time, the CEO was a CFO. So the finance guy over oversaw the the technology essentially implode and slowly degrade. So 10 nanometer was just, like, the true slow, like, you know, multiple years in the making train wreck.
Speaker 1:Yeah. And what was what was 10 nanometer, like, critical for? Is this, like, mobile transition, just CPUs?
Speaker 7:Just CPUs. Remember, this is this is an Intel that missed and totally, like, was irrelevant for mobile anyways. This is just like data center CPUs, normal PC CPUs. This is when AMD essentially caught up because they
Speaker 1:chose Ryzen stuff was happening, Threadrippers and whatnot.
Speaker 7:Yep. All that stuff is because they're using the TSMC process versus Intel was using their process. Their process lost the TSMC. Mhmm. And then also AMD's better design.
Speaker 7:Whatever. Got it. TLDR, total total problem. And half of the people who are on the board still are from that era. Like Mhmm.
Speaker 7:You would argue, like, hey. Capitalism works. You should fire people who do shitty things at their job. They should all be fired.
Speaker 1:And
Speaker 7:so most of them most of them got fired, and then I think this is the seminalysis piece. But, essentially, like, the people who remain effectively was the guy who just stepped down. I still think he's on the board, and now the chairman is this guy named Frank Ehry. Frank Ehry joined in 02/2009. So he is just as as, like, guilty of anyone, and he's a banker dude.
Speaker 7:Like, that's that's his background. He's a deals guy.
Speaker 6:Mhmm.
Speaker 7:So the first thing you need to know is a deals guy, when it becomes chairman of a company, is gonna do deals. So that's what he's been doing. He's sold Altera and You ship your org
Speaker 3:chart. Yeah.
Speaker 7:Yeah. Yeah. Ship it, sell it to anyone who can do it. And and he's in the and he wanted to sell the Foundry business.
Speaker 1:Okay.
Speaker 7:That's the that's like The Wall Street Journal thing. And in my opinion, total mistake. We think it's a total mistake at seminalysis. But then on top of that, like, Bu Tan, I understand
Speaker 1:the process for So really quickly, like, clarify that on on because I hear deals guy comes in, investment banker comes in, lot of people rumbling independently for the last decade, split up Intel. It sounds like they were trying to do that. Give me, like, your evolution of, like, should Intel have split up at some point? Should Intel, like, split up now? What is the current stance?
Speaker 7:So I think, at this point in time, I think they probably shouldn't split up just because, like
Speaker 1:They don't have a customer. Right?
Speaker 7:Yeah. They don't have a customer. It's like, the best time was definitely, like, three years ago. Okay. At this point in time, it's like you need the money from design now just to keep the lights on.
Speaker 7:And and I mean, like, not even just to have the customer, just to, like, fund anything, to have any cash from ops. Mhmm. An ideal perfect world is somehow Haktan, the sith lord of private equity, buys the design business of Intel and and scrapes it and guts it to the floor. That has always been a long time rumor that Hak wanted to do that. Mhmm.
Speaker 7:Hawk doesn't wanna do it because it didn't tell so bad. So there is no buyer. Design's, like, really screwed because it's, like, stuck on this process, plus it's also filled with bloat. And at this point in time, I think the only strategic part of the business that really matters is Foundry. Like, let's just, you know, because outside of the x 86 CPU, like, they're getting their face kicked in by by ARM.
Speaker 7:Okay? So it's, you know, x 86, and then they have to compete against AMD, which is still kicking their faces in with TSMC. And so, like, what is a secular decliner x 86 worth? Not much to anyone. And I think the reality is it's like, you know, with ARM and these custom CPUs, effectively, they they are just one of many, like, competitive products, and I think their competitive edge, like, Dwindles, pretty much they just have distribution into OEMs.
Speaker 7:Mhmm. So where is a bit like, a bet a business that has value that matters at Intel? It's a foundry. There's one foundry in the entire world right now. It's it's it's TSMC.
Speaker 7:It's Monopoly. Like and that's the only thing that's worth anything. And I think, you know, there's a chance to have a second foundry, and that could be Intel. But, you know
Speaker 1:Wait. What Here we are. What about Samsung? I mean, Elon did that deal. It seems like Samsung's, like, at least in the conversation as a potential foundry for specific things.
Speaker 1:Is is that, like are they really, like, several orders of magnitude below TSMC?
Speaker 7:Yeah. I think Samsung's just as screwed as Intel. But it it's like a second quiet more screwed that I think is like I mean, the PPA there, meaning power performance area, is pretty bad. It's probably just as bad as Intel. But the the one difference is Samsung has had external customers and probably could have external customers again.
Speaker 7:Yeah. If if I had to bet between like, Intel, in theory, has a better process for sure, but it's like it's like a bed of, like we're gonna say horse and saddle. Okay? Like, the Intel saddle is, like, you know, six rags, like, tied together around the horse that only, like, one rider in the entire world knows how to use, which is Intel design. Yep.
Speaker 7:On a presumably decent horse, it's like, 18 a is probably, like, equivalent to three nanometer. Obviously, not the best in the world, but, like, that it deserves to exist versus, like, Samsung's horse is just, like, really bad. The PPA is total trash. Mhmm. But, hey, it has a saddle.
Speaker 7:People have ridden it before. So there's, in theory, a customer. And so Lip Bu Tan is the perfect guy because he ran Cadence, which is an EDA company. And EDA, their whole thing is they design. And so once you have, like, a design, you can, like, put it in the Foundry and Yep.
Speaker 7:You can so, like, that important critical step in the PDK is, like, the missing piece for Intel. And Lip Bujan could be the guy, but Intel sucks. So
Speaker 1:Yeah. So, I mean, my my read on Trump saying we need Lip Bujan out is, like, a complete misunderstanding of the importance of Intel. And, basically, he's operating on, like, a twenty year old world model thinking that, oh, I I'm familiar with Intel. I know the brand Intel Inside. Like, that's an important company.
Speaker 1:We need it's a critically important American company. We need an American at the helm when in fact, it's like Intel doesn't really matter. There's like a wind down in process. Let let let Lip Bu Tan, like, run it. Even if he's exfiltrating everything to China, it doesn't matter because Huawei and SMIC and SME are light years ahead of Intel.
Speaker 7:Yeah. So I think that that is sort of true, but I also I will give the Trump admin props in terms of, like, I do think they know and understand the critical importance of Intel. I don't think they need blind.
Speaker 1:What what is the critical importance?
Speaker 7:They are the only domestic semiconductor process. Okay. So
Speaker 3:our only hope. Our last hope.
Speaker 7:Our last hope. It's that or we lease the future from TSMC. And that's pretty much, like, probably the most likely option.
Speaker 1:Lease the future or lease the future? Lease future.
Speaker 7:Lease lease the future. Yeah.
Speaker 1:Okay.
Speaker 7:Because you could buy a process or force TSMC to make a process in The United States, which is what they're doing.
Speaker 1:Yep. Within Arizona. Right?
Speaker 7:Same yeah. In Arizona, and then possibly more expansions. I'm sure there's some kind of deal. But after you have that, like, you all the r and d happens in Taiwan. So effectively, like, you know, the Taiwan constraint thing, same problem we had before.
Speaker 7:Because, like, a missile flies, boom. We don't we, like, we don't know how to make new chips.
Speaker 1:Yep. Yep.
Speaker 7:They we would just have old chips. It's like leasing a car. You know? We can't buy the new model. Yeah.
Speaker 7:Yeah. So that's a problem. That's, like, the same problem, but maybe more kick the can down the road if we had all the capacity here, but no R and D.
Speaker 1:Yeah. So, yeah, what is the, like, moonshot to make Intel, dominant again or catch up? Like, is like, the people were noodling on, like, should Elon come in and do the Elon thing and hire the most cracked engineering team and and drive everyone 10 times harder? But it feels like people kinda kick the tires on that. There was the rumor of, like, all the PJs in the same at Mar A Lago, but kinda everyone was at Mar A Lago at the same time.
Speaker 1:Is there is there a world where, like, Intel needs to go more founder mode? Like, Lip Buuton feels like the epitome of, like, manager mode. Like, would would you be, like, excited about something like that? Somebody who says, like, I'm gonna take it private, be extremely risky. There's a 10% chance that this thing works.
Speaker 1:90% chance we we completely destroy everything. But if it works, it'll be amazing.
Speaker 3:Dylan Patel and his CEO.
Speaker 1:That's good. Dylan and Doug.
Speaker 7:Skip both of them. Dude, if Dylan is the CEO, then my life has kinda become miserable, Doug. Like, that's look. So I think I personally believe that fab and found Fabless and Foundry need to have separate lives because you're like, there are two really drunk adults at the bar tied together hip to hip, and it's like, one of them could be dying, actually. One could be a corpse, and the other has, like, a shot.
Speaker 7:Okay? So, like, I just don't think I think you know, like, I believe in focus. I really do. I believe that small teams with a lot of focus can make them extraordinary results. I'm sure you see this in technology over and over and over again.
Speaker 1:Yeah.
Speaker 7:I think Foundry needs to be like, given a leash that's long enough to, like, make the shot true, probably a smaller dream and probably, like, you know, a pot of gold at the end of the rainbow. But then, like, essentially be told, like, hey. Here's your purse budget. Here's your potential capacity. If you win x y z, whatever, you'll get a ginormous order from in the, like, the fabless semiconductor companies in America.
Speaker 7:And, you know, that's the pot of gold at the end of the tunnel. And then behind you is death. And there's only one way, and it's forward. Because, like, how I think we've gotten to this point is, like, there was always this, like, second sloppy option of, like, well, we'll just put the Intel CPUs in there. You know?
Speaker 7:That's how foundry has been treated for so long. And I think Intel CPUs, over a long enough period of time, is just not gonna be enough to fill the foundry. So you're gonna have to do, you have to separate them. And I think you have to make, like, capitalism work, which means that you need, like, a pot of gold at the end of the rainbow, a true, like, shot to do it, and then, like, probably founder mode if it makes sense. Like, sure.
Speaker 7:Maybe Lip Bu is the like, Lip Bu Tan has much more of a qualification. It can't be someone who's from Intel. And I think the company should be private because public markets would kill the shit out of it. Like, it's just gonna be a miserable it's gonna be, like, a face beating the entire time. And yeah, dude.
Speaker 7:If Elon did it, I'll be very stoked. I'm not gonna lie to you. Like Yeah. However you feel about Elon's companies, like, you know, someone said he makes the late oh, no. He makes the impossible late.
Speaker 7:Right? He he will maybe he'll be late, but it'll be like, he'll get it done. Right? Yeah. There's there's no one else who's really done this.
Speaker 7:Pretty much no one's fallen off the leading edge and come back. Yep. And so this is like a moonshot. This is a moonshot's problem, and I don't
Speaker 1:know to it. Deal was happening, I was saying, like, okay. We got we marshaled $44,000,000,000 in private capital. There's also the Chips Act going on. You package all that money together, and you give Elon intel.
Speaker 1:And, like, what does that what does that counterfactual look like in the course of
Speaker 3:history? Well, I think the question is, does the stock need to drop another 50% before it can become a viable, like, actual take private target.
Speaker 1:It's an $87,000,000,000 company today.
Speaker 7:I think you can do it. I think you can do it today.
Speaker 1:Yeah. I mean, if you can take Twitter private at 44, you can take Intel private I 80
Speaker 7:think I think you just have to split the Foundry fab. Yeah. It's that simple. Because the Foundry the the the sorry. Sorry.
Speaker 7:Not Foundry fab. Sorry. Fabless
Speaker 1:Fabless.
Speaker 7:Yeah. The Fabless business is worth something.
Speaker 1:Okay.
Speaker 7:Like, it is, in my opinion, the, like, dude, Hoctan, the Sith evil, like, PE overlord would, like, crush it. Like, I really do believe that. My favorite
Speaker 1:Well, you mean so so quickly, like, you you you you split out design. You have this fabulous semiconductor company similar to it would compete with NVIDIA in some ways. Would they go into It'd
Speaker 7:be AMD.
Speaker 1:AMD. And so they'd be focused on CPU, and their and their customers would be who exactly?
Speaker 7:Like, electronics companies. You'd focus
Speaker 3:Electronics companies.
Speaker 1:Electronics companies. But
Speaker 7:Yeah. Like, I think you would focus so the thing they keep saying is AI at the edge. Yep. I'm a total hater. If I'm being honest with you, like, you know, the the Internet works.
Speaker 7:Packets are pretty quick.
Speaker 1:Yep.
Speaker 7:What I think would be the best way is they do have some networking content. They do have the PC business. They do have, like, high end data centers, CPUs. Maybe, like, the high end data center CPUs, like I mean, to be clear, they're gonna be, like, a third place or second place against AMD. Like, it's gonna be an ugly world, but, like, what you could do is you can just kill all the SKUs and all the expansion you've done over time.
Speaker 7:Like, Intel has all these custom SKUs for whatever. You make, like, good, better, best data center and, I don't know, edge or mobile or some kind of optimized thing, and you fit all your products into those categories. You kill all the unprofitable ones. You fire 50% of the people, and then you, like, you know, do your best to extract the rent in places that you cannot be ripped out. Maybe you, I don't know, monetize your CPU software, sell it or some shit to to AMD.
Speaker 7:Like, do your absolute best. And it's like a really sad ending to Intel the FAPLIST business, but I think it has one that is worth more than $0.
Speaker 1:Is is yeah. It talk about the GPU CPU split here because Intel's never really been a player in GPU, and that feels like when we talk about the value of TSMC in Taiwan and AI, we're talking about super intelligence and these mega clusters and the ability to train frontier models. And it feels like like even even a high performing Intel, like, isn't a player in that world.
Speaker 7:Or Yeah.
Speaker 1:Or or should we be thinking about it in that grand of terms?
Speaker 7:No. I don't think they're a player in that world. I really like, it I think it sucks, but, like, you know, Gaudi is Gaudi is a chip that sits in in warehouses around The United States. You know, the the Battlemage CPU GPU is, like, not the worst product.
Speaker 1:Sure.
Speaker 7:But, like, I think if you think about just, like, semi characters, man, one of the, like, my favorite analogies or, like, ways to look at it is that it usually ends up being, like, a let's say, a sixty thirty ten market. Sure. And and the 10% like, 60% makes, like, you know, two x the profit of the 30%, and then the 10% is, like, breakeven or loses money. I feel like Intel's market positioning kinda puts them at the 10%. Mhmm.
Speaker 7:And I think, like, I, like, I really think the private equity outcome for the fabless side is the best outcome possible because, like and and the reason why I say Hoktan, like, let's actually just, like, play the Hoctan playbook. What Hoctan does is he takes a business that's extremely mature and sticky that was, like, a winner of the last cycle and then just, like, fast forward ten years of the maturity all the way to today. So, like, VMware is a perfect example. Virtualization was, like, you know, the thing in the February and made CPUs better and all this stuff. And, you know, there were this, like, almost monopoly.
Speaker 7:They still have the vast majority share, but they were, like, spending all this stuff, growing expenses. And then Hock was like, dude, no. They actually have a business that has some terminal value. They're not living in this paradigm. So what I'm gonna do is I'm just gonna fire half the people, raise the prices on the like, raise them massively, lose a lot of my customers along the way, but become a massive cash cow, and then, like, essentially squeeze that to the end.
Speaker 7:But if you think about what Cock is actually doing is he's accelerating ten years of industry progress into three. Right? Like, that's what would happen, but, like, it's gonna be a lot uglier and slower show in public markets versus just, like, time collapsing, price raise, fire all the people, boom. You're profitable. You're at the end state.
Speaker 7:You're you're essentially underwriting no growth. I think Intel needs to underwrite no growth, and that's not in the Fabless business at all.
Speaker 1:Yeah. Just embracing reality. Like, embracing embracing the reality and taking taking your medicine.
Speaker 3:Someone someone in the chat, Sharon says, please ask Doug about the new Intel factory in his hometown of New Albany and what the status is. Do you have any idea what's going on there?
Speaker 7:New Albany? Not my hometown.
Speaker 3:I haven't. No. No. No. Not your hometown.
Speaker 1:This listener's Oh,
Speaker 7:okay. Okay.
Speaker 1:This listener's hometown is maybe looking for a job in the fab.
Speaker 7:So the New Albany, as far as I understand, the ground is broken. The shell is empty, and I don't think they'll fill it.
Speaker 1:Okay. How this won't happen?
Speaker 7:That is but the thing is, I think that that that's a really valuable asset that needs to be remarketed. I think I think it's probably likely someone will buy it. And if I had to guess, it's, like, TSMC. So, yeah, I don't know what that looks like, but I think I think a really shrunken down Intel looks like just Oregon and just New Mexico and Arizona? I think so.
Speaker 7:Yeah. Arizona. And that's it. The capacity that was expanded for Ohio was like a YOLO bet the farm. Somehow, we're, like, beating AMD again.
Speaker 7:Like, I think it was underwritten to have this, like and that's the reason why Lip Bu Tan was like, dude, touch grass. This isn't happening. Pat Gelsinger, this is just like this is not happening. Like, you're, like, completely not realistic. I think that that it just doesn't like, the capacity they had there for the the wafer starts is just, like, so large.
Speaker 7:It doesn't make any sense. Yeah. Yeah. And I mean, like, dude, the Lip Bu Tan thing and, like, wait. How do we feel about, like, the, you know, Chinese thing?
Speaker 7:I I mean, there's just not many people who could take the job, and I I mean, it really sucks since very hard. But, like, dude, he actually embraced reality. Like, the most realistic thing I saw, he's like, dude, we're not even a top 10 player in AI. And I was like, yeah. That sounds like reality.
Speaker 7:Like, this is the first realistic thing I've heard for a long time. And That's crazy. That's, like, refreshing to me. The guide was totally like, the the print was totally messed up. Like, you know, effectively, it was really ugly.
Speaker 7:Essentially, they're like, yeah. We did pull forward tariffs. Yeah. The guide is a little messed up. And, yeah, it's gonna be uglier from here.
Speaker 7:But I kind of vibe with it because it's like, we're just gonna tell you like it it like like how it is. You can, like, trade the expectations of this, but, like, the the stock and company and the value of it is, in my opinion, a binary option. Is what is the foundry worth to America, and how do we get how do we, like, fast forward this, like, painful capital intense world where we, like, don't have a leading edge semiconductor producer that can have an external customer to one that can, that's that's the entire value of the company to me. And then Fabulous is like a call option cash gusher that can be hopefully harvested.
Speaker 3:Strategy is we need people to rip the Band Aid
Speaker 1:off. Yeah.
Speaker 7:Yeah. Yeah. It's supposed to pay a big it's gonna cost a lot.
Speaker 1:Give me the update on g p t five.
Speaker 3:Yeah. Specifically, it it this was the week that the timeline woke up to language models plateauing.
Speaker 1:Yep.
Speaker 3:A lot of people are are bummed about it. Bearish, I think in
Speaker 1:It was maybe six months ago that Dylan Patel went on Dwarf Cash and said like, if GPT five is good, we're totally good on all the semiconductor spend. If it's not, maybe we're in trouble. And so I'm wondering, like, if there's updated thinking around there based on, you know, do we do we need any more inference clusters or or or or training clusters? Or is it just a game of where is the profitable inference happening? Let's make sure we have enough to meet demand, but not go further, not create some overhang.
Speaker 1:How much of a of a dance do we have to do to make sure that we don't get, like, overcapitalized, overbuilt?
Speaker 7:Okay. So this is a pretty interesting question. I'm gonna parrot Dylan on Twitter because, you know, like Yeah. My lord and savior Dylan knows knows what he's talking about. Yeah.
Speaker 7:GPT five is a little disappointing, I think, for the power users of Twitter. There's no other way there's, like, no other way to put it. It's that, like, for the power users of Twitter who've been, like, chugging o three deep research things for a long time and is, like, messing around with Brock and, like, messing around with whatever, I personally do not feel, like, massive difference. It's less verbose, whatever. Maybe it's slightly better.
Speaker 7:I don't know if you're seeing this thing about, like, the the SWE benchmark, like, app like, the the so like the like is yeah. The chart. No. No. No.
Speaker 7:Not the chart. The SWE benchmark, if you look at it, not all 500 tasks are measured. They pulled some
Speaker 3:It's like four seventy seven. It's like they they
Speaker 7:pulled 77. Yes. Interesting. Yeah. So, like, that's a light that's an apples to oranges comparison.
Speaker 7:So that's not a big deal. Mhmm. But I do think you have to think about, like, okay. So on one hand, the Cultist and and, like, me and, like, the power users are probably disappointed. On the other hand, you know, there's 600,000,000 free users who probably just woke up to, like, a big upgrade.
Speaker 7:And I think that that's how I feel like this was actually like, that's the actual strategy. They pushed them to five. Five's a lot better versus four four, you know, four o. And it just sorry, dude. The fucking naming
Speaker 3:Well, think I think another way to put it is if you're a power user around, like, using it for research and learning, you're you're maybe disappointed. If you were a companionship power user, I mean, we were reviewing I mean, r/chatgpt on Reddit is absolutely in shambles today.
Speaker 7:Dude, I know because the girlfriends. R I p.
Speaker 1:R I p. Well, there's a new entrant there. I think I think they might have to peel off that market and give it to Elon.
Speaker 7:Yeah. That's true. You can do you can do the Anti network. You know? Dude, I don't I I yeah.
Speaker 7:I think that that's the correct way to think about it. I think it feels like it's try to be as simple as a like, a simplification of the of the SKUs, because as you guys know, it's confusing as hell. Yeah. There's many there's, like, many thinking in in flagship. For the most part, I had to if I had to guess, flagship probably rent like, probably prints cash for them and is, like, much cheaper in, like, a smaller model.
Speaker 7:Maybe not a smaller model, but, like, compared to, like, a very big model smell. Right? It's not big model smell. So it's very and then also, if you look on the pricing, it's pretty cheap. And if it does what it does, well, then just like we talked about, Suite benchmark might not be might might not be correct.
Speaker 7:But, like, you nuke the price on your competitors in terms of, like, Claude versus chat GPT five tokens. And so that I think that that's, like, the this is the better, bigger, faster or maybe it's the faster, cheaper, but not better update, if that makes sense.
Speaker 3:Yeah. Well, one thing that stood out yesterday, so they have 700,000,000 weekly actives globally. Yep. 85% are outside of The United States. And you can just imagine in that in those hundreds of millions that are outside of The US, many of, you know, like, the the question just becomes, like, how they can continue to serve the like, will they be able to serve
Speaker 1:What will ARPU be, and what will the margins be on the on the incremental international developing markets ChatGPT user? Because the marginal cost to serve WhatsApp or Facebook, even even, yes, you're storing images, for for Instagram, but or or WhatsApp. You're running a database, but the marginal cost is so, so low. And it feels like, at least right now, maybe it changes in a couple of years, but right now, the marginal cost of serving a ChatGPT user, even a casual weekly active user is is in the it's in the dollars per year. And when you look at the monetization rates of Facebook and WhatsApp in developing markets, the ARPU is, like, dollars per year.
Speaker 1:And so matching that up feels like a big challenge. And I'm wondering about, yeah, like, the ASICs, AI on the edge, dedicated, you know, servers or or or even more pared down models? Like like, what's the what's the solution so that you're not just burning a ton of cash supporting, you know, unprofitable users?
Speaker 7:So I definitely so I wonder if we'll have the bandwidth to get this done, if it, like, makes it to a big post. But, like, I think we're thinking a lot about this Mhmm. Deeply
Speaker 1:Yeah. It makes sense.
Speaker 7:On that seminalysis. I think the cost of a free user for a small model is, like, surprisingly low. I would wanna be a little bit more sure about that, but I think if you have high batch size with, you know, a b 200 or a g b 200, I don't know if it's dollars per year. I really I really think the actual net tokens that you're you're you're able to do is a lot higher than people think, and I think that there could be this but the problem is is, like, the same there's the same issue. Right?
Speaker 7:Yep. Think of it as, like, a Pareto curve. Right? 20% of the people are paying at the wazoo and more than happy to pay for, like, a crap ton. Right?
Speaker 7:The pro and plus of OpenAI. The only problem is, like, the the the top 5% of that 20% are paying or, like, know, they're massively losing money on. And then you have this, like, long tail that is, like, kinda interested, likes tokens, becoming a little bit more addicted, easy, cheap ish to whatever. And then as you can shift that up, maybe you can make the revenue that you're not you're losing for the hyper you know, for the pros. Right?
Speaker 7:And so that's kind of a I think that that's kinda, like, the more interesting, like, thought process. I do think the unit economics of these things are a little bit like I mean, it it really depends on the size of the model and then, like, what inference they're they're doing. But, like, my impression is you can be doing, you know, build, you know, millions and millions and millions of tokens for relatively cheap a year. And if you monetize if you know, we're talking about, like, we can monetize, like, 15 to 20% or even 20 to 30% of your your tokens are actually being monetized at, like, you know, the market rate. You can pay off the the 80%.
Speaker 7:That breakeven, I think, is a really important, like, question. I don't know the answer to that. I know we're working on it, but I don't have anything
Speaker 3:Yeah. I think the I mean, the the going back to your, like, Instagram or WhatsApp comparison. Instagram and WhatsApp are pretty much the same wherever you are in the world, regardless of how much revenue you're generating for these platforms. But it's very possible in the future that that companies cannot serve the quality of model in some of these areas that they can
Speaker 1:Well, will. It'll just be $200, and $200 in an emerging market is like a ton of money. And so the adoption rate and the upsell rate will just be way, way lower. They'll probably be like an ad supported tier. But But,
Speaker 3:again, ads themselves don't generate
Speaker 1:Of course. Of course, the ARPU will be will will be much lower in emerging markets.
Speaker 7:Yeah. And I think, I mean, I think that's happening. I freaking I can't name the higher, but I know the higher that, like, essentially started the ads.
Speaker 1:Yeah. VGC mal. Platform.
Speaker 7:Yeah. Is is is there. So, like, you know, that's the
Speaker 1:Yeah.
Speaker 7:You know, freaking surprise. I wouldn't be surprised. The answer is there's, like, a Twitter user. The answer is always ads. Okay?
Speaker 7:Yeah. There's gonna be ads eventually.
Speaker 1:Yep. But they but they probably monetize, like, within an order of magnitude of how well Facebook ads monetize and Google ads monetize. So Yeah. That's fine as long as your inference cost is roughly the same as within an order of magnitude of Google's service cost and and Facebook service cost to serve a user which are, you know, pennies, I imagine. But, it does feel like we can get there
Speaker 3:over I think this this the the timeline broadly woke up this week that we're building developer tools Mhmm. And consumer internet companies. Yep. And, like, that's that's the game here. And Yeah.
Speaker 3:Machine god is like real
Speaker 1:Delayed. Some
Speaker 3:ways delayed. I'm curious, how do you think how much do you think the labs care about the student market? There have been some reporting around the token generation as school ended last year. Oh yeah. Token generation dropped dramatically.
Speaker 3:Then today Sundar came out and shared that Gemini They're making Gemini like, you know, like unlimited sort of like free for for students this coming year. And in some ways
Speaker 1:Seems like he's staying in the game. He's like, I'm not letting Yeah. Chatty PT.
Speaker 3:Well, no. And it feels like that's potentially a a way for them to, like, to kind of
Speaker 1:Yeah.
Speaker 3:Corner users that will become very value maybe aren't so valuable Mhmm. In the short term, but will become very valuable over time if you can get them to stick.
Speaker 7:Yeah. Yeah. I think let's kinda talk about this because I think that's, like, just a really interesting and I'm kinda going to Google, I think. You know, how you know, like, just analogy. Right?
Speaker 7:How CUDA became a thing is because Jensen gave it away to PhD people for, like, a decade. And then all of a sudden, everyone who ever did anything realistically in machine learning was like, well, I'm using CUDA because that's what I've been using. I think it's important because if you're thinking about, like, you know, where are the users of tomorrow? The s curves of penetration are, like, it's not gonna be the old people who are using the hell out of it first.
Speaker 3:Mhmm.
Speaker 7:Who knows? Maybe they are. But it's like, the young people are probably gonna over index. You know? People my age, which makes me feel old, is, like, gonna, you know, probably index about.
Speaker 7:About. Right? And then the people older than me are gonna index under. And so where where do you actually win market share today? It's probably not in the people my age and older or the power users or whatever.
Speaker 7:You probably need to, like, get a you know, you need to get a 12 year old addicted to Gemini, which sounds like very terrible. Now now I say out loud.
Speaker 1:But you wouldn't say it about Google search, you know, or or Google Drive or Gmail. Yeah. But, yes, it is a it's low churn. You have to get them over the adoption curve so that they are low churn.
Speaker 7:And that's where they're like like, I think it's like a a cognitive referent. Right? Like, right now, even though I am very model curious, meaning that, like, I have a, you know, a paid sub to, like, Claude to Grock to to ChatGPT. Yep. Recently, especially, like, you know, in the, you know, the good old golden era days of o three, you know, o three pro deep research, I'm just pounding deep research queries and, like, agent queries constantly.
Speaker 1:Of course.
Speaker 7:But, like and I'm gonna be to be clear, I'm gonna start looking around a little bit, but, I I think I think that that's what Gemini's, like, real issue is is they need to become the cognitive referent. I think when people open up a a, you know, a GPT like trans you know, transformer model effectively to ask them in LLMs, They need to be thinking of Gemini in the conversation, and they just don't, dude. Sometimes I, like, talk about LLMs with, like, people, and it'd be like, you know, OpenAI and Anthropic and what's the third? Oh, yeah. Gemini, you know, third.
Speaker 7:Yeah. I I, like, weirdly forget about them. I think that that's the they don't wanna be forgotten. And I also think if we do a segue to I think that's why they're also starting to sell TPUs externally. And this means, like, as a service, right, in their cloud.
Speaker 7:Right? Yep. They're sell like, they talked about on the last call where, like, you know, GCP is starting to accelerate. And I think where we're starting to see that is I think TPU is starting to pick up a little bit.
Speaker 1:Do you know there'll be, like, distilled models that are fine tuned or or developed for TPU specifically or
Speaker 7:I something else? I think it's more that there's a few model companies who are very interested in extra capacity. For example, Anthropic is definitely Yeah. You know, definitely uses some TPUs. I know that for sure.
Speaker 7:And so, you know, in the use
Speaker 1:Tranium a little bit too?
Speaker 7:They also do use Tranium. I think it's very funny because Anthropic uses everything. Interesting.
Speaker 1:Yeah. That is that like a huge cost center to have kind of like a team to rewrite all your CUDA code into Trainium and TPU compatible code?
Speaker 7:I don't know. Probably. But, you know, Anthropix cracked. So Yes. That's what this you know?
Speaker 3:They have Cloud Code. They have full access to Cloud Code.
Speaker 1:Exactly. Cloud. We platform it. I mean, that is the point.
Speaker 3:Don't have to worry they don't have to worry about being dropped.
Speaker 1:Yeah. I mean, I mean, I I was wondering, like, when when will a cross compiler exist? And and you can I mean, didn't didn't Facebook do that for a while where, like, you they would write JavaScript and it would compile, like, c plus plus or something like that? Because they'd written, like, so much JavaScript that they were just like, okay. We don't have time to rewrite all this.
Speaker 1:Let's just write our own compiler. And and you can imagine Anthropic doing something similar to run on TPU or and or or or training?
Speaker 7:Yeah. I think that that's happening to a certain extent. But I think that for Anthropic, they think of it as optionality. And I think Trainium specifically is, like, you know, the the other drunk suitor at the bar who, like, really needs a partner, like Amazon, who's now last place. Right?
Speaker 1:Yep.
Speaker 7:Last era was first place. Now they're last place. Yep. And then Anthropic, is, like, you know, the scrappy number three who needs capital compute, is like, come on, dude. Marriage made in heaven.
Speaker 1:Let's Totally.
Speaker 7:Tie it up together. And then that's why training is just, ramping up.
Speaker 3:I'm we gotta start using these drunk bar
Speaker 1:analogies. Yeah. Is good.
Speaker 7:I love drunk bar analogies.
Speaker 1:We know these things are the sports analogies, but I I'm probably more familiar with the drunk bar analogies. Those are good.
Speaker 3:Yeah. Ross McCannell in the chat says, please ask Doug about state of memory makers. Will SK Hynix and or Micron be able to maintain margins and keep keep HBM as a somewhat differentiated product, or is it doomed to be a commodity business?
Speaker 7:I think oh, this is a good question. Try Trying to think about how what to phrase this. So I think one of the ways to think about this, first and foremost, is Atrium is like the new DRAM. Mhmm. The I mean, like, there's, like, a weird weird aspect where it's like, okay.
Speaker 7:DRAM was, like, the And you can look at the cycle's margins, and, like, they're not actually higher than last cycle's margins, which is, like, probably a little bit of a I wrote about this, like, being a super new DRAM. I think the HBM is really, really, really important, super, super duper in demand, and it's, like, you know, the new memory. But in the other ways, NAND specifically is kinda like the old memory, and it's getting much worse with the commoditization and the like, especially CXMT on the lowest end or no. YMTC on the lowest end and then CXMT on DRAM. So you're starting to see some some of the aspects there get a little worse, but I do think NAND is trying really hard to kind of hold on to the, you know, the oligopoly where everyone doesn't raise bits together.
Speaker 7:And maybe who knows? It becomes so old and whatever, you end up, like, HDDs, which are actually having, like like, you should go look at STX and what's the other and WDC because they're, their stocks are ripping because Yeah. Western Digital. Yeah. Western Digital because they're not investing.
Speaker 7:They they you know, it's a two player market. They they gave HAMR to the other competitors so that they can, like, effectively, like, you know, have a two player oligopoly where they control supply.
Speaker 1:And this is just this is just the Nash equilibrium. This is just, like, game theoretic. They know that they that this is better for both of them, so they're not getting a price war. Right?
Speaker 7:Yeah. Yeah. Yeah. A 100%. For but that's only for hard drives.
Speaker 7:Like, NAND isn't there yet, man. NAND, have, like, a slippy slippery Chinese, like, swing producer that is willing to blow it up.
Speaker 1:Got it.
Speaker 7:Okay. So I I I think on HBM, I think it's kinda complicated. I don't wanna, like, say too much because I don't even know I I don't even know what somebody else's house, like, house house view is right now. Let's just, like I'll talk about some facts I think might be very interesting and just, like, thoughts is that, like look. Last time this year, Micron and SK Hynix were effectively completely booked out, and, obviously, Samsung wasn't even in the game.
Speaker 7:This year, they're not booked out. What is the difference is I think it's the threat of the Samsung qualification. I don't I don't know about the Samsung qualification. Okay? I don't think anyone knows.
Speaker 7:The shit I hear out of Korea like, I hear that they're qualified. They're not qualified. They're qualified. They're not qualified. They're qualified, but, you know, they have to hit some kind of yield thing.
Speaker 7:I hear kinds of shit all the time. I have no idea. But I think the fact that, h b m four pricing seems to be, a little bit, like, dampened just on the threat of qualification really kind of tells me that the HBM cycle is really long in the tooth and is probably we're we're nearing the beginning of the end, just mathematically as the second derivative continues to go down for most of the memory stocks. You can look at, like, SK and Micron. I still like SK.
Speaker 7:I still think what they do is really, really differentiated and valuable on a relative basis. I mean, they got to HPM first. They still are really awesome. They still have the best the best product and process. But I guess I'm just kind of like you know, I'm a cycles brain guy, and it's been about three years of a tight cycle in memory.
Speaker 7:And you're, like, you're asking me to bet on the fourth. I know what the base rate should be
Speaker 1:Mhmm.
Speaker 7:That you shouldn't bet on. But I don't I don't think we actually have a house view other than that. Like, because at the same time, you know, NVIDIA goes burr and HBM bits goes up. And even though there's a little bit of a oversupply in HBM three, I still think HBM four is gonna be pretty good. But, you know, like, rate of change brain tells me,
Speaker 1:you know Yeah.
Speaker 7:It's a little it's a little spicy.
Speaker 1:Where else in the supply chain should we update if we're totally plateau pilled? And we say, you know, we're not going to necessarily even want to do the next order of magnitude pretraining run the mega cluster. We're maybe gonna be more distributed, more more inference heavy. Are we thinking ASICs? Are we thinking more focused on depreciated GPUs, distilling models to to older hardware or just, you know, really getting all of the juice out of the current h one hundreds and and and GB two hundreds and, like, actually just, like, you know, like, not not replatforming to the latest and greatest constantly, like, not not worrying about that?
Speaker 1:Or, like, where else where else should we be kind of updating on various parts of the supply chain?
Speaker 7:Okay. So I think a lot about this. Or anyone, I feel like I'm, like, the wrong person. Or I'm probably a decent person to answer this, but, like, it's gonna be really speculative. So I'm gonna put, like, some massive disclaimers.
Speaker 7:Yeah. Yeah. Who the f knows? Right? Like, maybe, you maybe there's one more thing or comes out and they cook on five or something.
Speaker 7:I don't know. Or Gemini next week makes us all pilled. I don't know.
Speaker 1:Yeah. Yeah.
Speaker 7:I think we're if we're okay. So let's just, like, walk through some of them. The massive pretraining cluster doesn't happen. I think the fiber from data center to data center is, like, the most screwed. That is the most whipped at the tail.
Speaker 7:The multi data center training thing
Speaker 1:Sure.
Speaker 7:That is, like, oof. Ouch. Goodbye. You don't need it anymore. Right?
Speaker 7:You can do a 100 k clusters of RL. And you get you get and so that's probably where I think if you had to, like, you know, slice the puzzle where it's most impacted, it's probably there
Speaker 3:Yeah.
Speaker 7:For the for training specifically. I still think we would end up doing a lot of inference. I do believe I really do believe that if, all progress stops today, we probably would still have, like, you know, a decade of productivity as this, like, technology's It's not AGI god, but it does happen to be, like, an amazing simple, like, densification, simplification, like, you know, densification of all the information into, like, an answer machine. Fucking awesome.
Speaker 3:That's a big, huge
Speaker 1:I mean, it's like like a lot of CPUs in the cloud. Like, we're gonna use CPUs in the cloud for a long time. It took twenty years to actually do all the things that you can do with CPUs and databases and hard drives in the cloud. And now we have GPU and and and LM. So we're gonna we're gonna stuff that in every single cranny of the economy.
Speaker 1:What
Speaker 3:did you think there was a headline recently that micros it was it was Azure's non AI cloud business was growing at at almost the
Speaker 1:same rate as AI. Think the final read on that was that that was just driven by OpenAI as an Azure client. But, basically, the the the the read off of earnings was that their their their core infrastructure group grew faster than their AI services group. So more people buying compute as opposed to buying tokens, but that's not necessarily a read that, like, people are spinning up more, you know, CPUs.
Speaker 6:So
Speaker 1:So walk but walk us through it.
Speaker 7:Actually, that's a great question. I'm I'm very familiar with what you're talking about. The Azure beat last quarter specifically was driven by the infrastructure side more so than the token side. Yep. And then, like, ironically, you know, one of one of my colleagues at, like, semi analysis pointed out pointed this out.
Speaker 7:There wasn't the disclosure they had last quarter. They disclosed what the percentage AI was to the growth, and they did not talk about it. And if if they stop disclosing, I can tell you the answer is it was lower. Like, you know, so I think that's probably a pretty interesting thing. It tells you that, like, the consumption is definitely worse.
Speaker 7:I don't know if that how they're classifying it Well, doesn't that
Speaker 3:track with that tracks with Satya, like canceling canceling data centers developments and just saying, I'm happy to lease also like, you know, the business on a tear doing round like multiple rounds of They've done more layoffs this year than I think the last like three years combined, which tells me that everything that like the timeline is waking up to this week, like Satya has
Speaker 1:known It's
Speaker 3:been held on for a if you look back at some of his interviews, he's talking about, like, yeah, OpenAI is, like, a great consumer technology company.
Speaker 1:We're happy to partner with them. Wait. Wait. Sorry. Can you can you restate and unpack that a little bit more?
Speaker 1:So there were so Azure grew a ton. AI tokens grew a ton, but AI core infrastructure grew even more. But they used to break out within core infrastructure how much of that infrastructure is being used for AI versus not, and they stopped disclosing that. Is that correct? Yes.
Speaker 7:Yes. That is correct.
Speaker 1:Yep. And
Speaker 7:so by not disclosing it, you know the answer is it's lower.
Speaker 1:Yeah. But it was still it was still, like, pretty big growth overall, so it's just that the the second derivative is slow down? Yeah. It's still accelerating, but it's at a lower rate.
Speaker 7:Yeah. Okay. Interesting. Well, actually, I I feel like now I'm talking out of my ass.
Speaker 1:I lost the number in
Speaker 7:front of me. But, like, look. I think the thing the the Microsoft print is, like, they pretty much are, like, almost mid cycle pressing the brake, and then they, like, know, they juice. But, like, you know, as it decelerates the investments, you still get to reap all the investments you made.
Speaker 1:So They have a massive backlog. Right? Don't they have, like, a $100,000,000,000 of cloud backlog?
Speaker 7:Yeah. And and and so all this backlog has started to become revenue. And then, like, you know, Microsoft still is, like, such a winner. Just yet, like, fast or rewind to, like, three years ago
Speaker 3:Mhmm.
Speaker 7:When Microsoft was, like, clear number two. Mhmm. And, like, you know, now they're outgrowing on a, like, on a much higher base than AWS is, and AWS is, like, not in this. Right? So I think that if you think of it from the perspective of, like, hey.
Speaker 7:Microsoft Azure versus versus AWS. Did, you know, did Satya win? The answer is yes. But I think the thing that is interesting definitely going forward is, like, how this all works and how OpenAI continues to finance and spend and pay for more compute infrastructure. Because at the same time, like, you know, one of the other ways you could look at it is, like, the entire math of where this is going is just, like, all at Oracle's pocket.
Speaker 7:Like, Oracle effectively so we talked about the Microsoft slowdown. Oracle literally just completely ramped up when Microsoft slow slowed down. Mhmm. And then and then Oracle went to OpenAI, and OpenAI is like, great, dude. We got a new customer.
Speaker 7:They're willing to do Stargate. There's even a spot that was supposed to be Stargate for Microsoft that kind of, like, know, and then all of
Speaker 3:sudden, was not for my I'm good for my however many billions.
Speaker 1:80,000,000,000. Yeah. But then but then but then that that deal went to Oracle. Right?
Speaker 7:Yes. That deal went to
Speaker 1:Oracle. Okay.
Speaker 7:So I think that that's yeah. I think Microsoft is, like, slowing down. They definitely had this massive lead, like, a truly a massive lead. Remember, like, last year, the perception of who is winning the race for the hyperscalers? It was Microsoft number one because the OpenAI partnership plus the infrastructure.
Speaker 7:You're like, dang. They're so far ahead. Now being conservative, kinda pulling off, you know, decelerating. But I also wanna put some, like let's also talk about this a little bit because I think the underappreciated part about the Microsoft thing is, yeah, just like how shitty they've done with access to the model this entire time. They've had access to the model weights at OpenAI the entire time.
Speaker 7:And you can also argue that no company has more competitive threat for for their core business than Microsoft does. I don't know about you, but I do a lot more editing and drafting and, like, information search and ideation in ChatGPT than I used to do it in Word. Right? So you're, like, typing up something and you're, like Yeah.
Speaker 3:And and then so so so Elon posted yesterday Microsoft is get is going to get absolutely cooked by OpenAI. And in many ways, obviously, like Microsoft has a ton of users for Copilot. They they're taking AI seriously. But what you're getting at is is one, you know, and hard to read too much into what Elon is saying because like he's got a lot of, you know, he's playing games behind the scenes Yeah. That we don't necessarily have a view into.
Speaker 3:But what you're getting at is interesting which is you might instead of there's a world in the future where instead of opening a doc or an excel sheet, you just start talking with the model and saying, I wanna make a model for for this product line, you know, going out over the next, like, three years.
Speaker 1:And it basically has Microsoft three sixty five as a tool that it can call. Yeah. Then it eventually instantiate a word doc for you if it needs to. It
Speaker 7:creates the output in in
Speaker 1:In in the actual application that they have because they already have cloud hosted PowerPoint. And they just are are like, oh, it sounds like you're going down a tree. You need a PowerPoint. Here you go. I generated it.
Speaker 1:And you can edit it if you want, but, also, here's the export. We got a PDF for you here because we used our tool.
Speaker 7:Yeah. A 100%. Yeah. 100%. And, like But,
Speaker 1:yeah, huge, huge, UX problem. Like like, mean, like like, Google has bolted Gemini onto every product, and and it's and the adoption's been very rocky, and it's been it's been tough. Like, it's not as easy as just, like, slap a text box on it, and you got a winning consumer product. Like, it does require innovation, I think, in terms of product So
Speaker 3:so going back to the sort of dynamic between Microsoft and Oracle, I think you ask have to ask the question if if Microsoft is pumping the brakes a little bit and Oracle slamming their foot on the gas, Like, it's gonna take a little bit to see who who made the right call. Yeah. Yeah. And
Speaker 7:You you so do we do we plateau or not? Right? That's the answer.
Speaker 3:Well, and and I think the answer this week is yes.
Speaker 1:Yeah. But, I mean, at the same time, like, like, inference for ChatGP
Speaker 3:Not necessarily usage wise.
Speaker 1:Model quality. To to continue to increase. And if if Oracle can position themselves as, the key cloud provider for that, that could be it's mostly just, like, the Oracle investments just can't be overly aggressive at any point in time because if there's a pullback, then they're like, oh, we're unprofitable for a little bit on this.
Speaker 7:Yeah. Yeah. They they could take the biggest bath.
Speaker 1:Potentially.
Speaker 7:Yeah, dude. I think okay. So I'm trying not to call it because, as you know, AI changes, I feel like, week to week. Yep. Sometimes it feels just like, I don't know, hyperbolic time chamber, dude.
Speaker 7:Like, you know, we could be so over, and then it could be so back. Right? Totally. If you guys remember, pre training is over. It felt very over.
Speaker 7:And then now we are, you know, so back because of the because of the, essentially, the increase in
Speaker 1:Reasoning. Test time inference.
Speaker 7:Reason yeah. Sorry. Sorry. Reasoning. And then now I'm thinking about this is, like, okay.
Speaker 7:So the unspoken part about this that makes, you know, the chat GPT five lot better than other things is, like, long task, and agentic and tool use. Right? So that is the in my opinion, you know and and I hear this kinda shit all the time. I thought it's really BS y, and so I've been messing around with quad code. It's like, oh, agents.
Speaker 7:Agents. Agents. Agents. Agents are gonna be this big thing. And you're like, what the fuck does that mean?
Speaker 7:Because you're like, I don't know what this agent is doing. But, like, quad code is pretty cracked, man. You just, like, ask it to do things, and it just, like, does them, and it does it in, like, kind of a scarily good way. A good example is, like, we've been hiring people. I think we have some hires in the line.
Speaker 7:We make them do a case study. That's, like, not as case study is a great way. Okay? And I was so pissed and annoyed by some of the case study qualities. I made, like, each of the models do the case study.
Speaker 7:Dude, you know what did the best case study of them all? Claude code did. Okay? Claude code over OpenAI agent. And I think that that's kind of what we're like, those extremely long contexts, autonomous ability to do stuff on on its own is gonna be the, like, you know, the nirvana that, like, changes everything or makes the consumption a lot bigger.
Speaker 7:And I think you can kinda see the glimpse of what an agentic feature looks like via Cloud Code, and then you just assume that instead of them r l ing the shit out of, like, software and making, you know, the best, you know, the best commit or something like that, they're going to r l the the hell out of, like, advertising or creating the best, you know, advertising media, or they're gonna r l the the crap out of, like, finance or making the best financial
Speaker 3:Well, yeah. I mean, the the thing that stands out to me is, like, this compounding advantage of, like, you're a lab, you're competing with other labs, and you have access to the best coding product, and you can use it as much as as much as you want forever and it gets better and then you guys get better and higher output. And I don't think we've seen this, you know, you don't you didn't see the same dynamic with like Microsoft having a better version of Excel and like Yeah. Or the example of like, it's not Mark Zuckerberg with Facebook was like, I get to use Facebook more than my competitors, so
Speaker 1:I'm gonna
Speaker 3:be better. It's like
Speaker 1:Well, actually tried that. They they they were using Facebook for internal comms. They still do.
Speaker 3:Well, yeah. But whether or not that gave them a competitive
Speaker 1:advantage. Over teams or
Speaker 7:Well, that's
Speaker 1:Google Drive.
Speaker 7:Yeah. Like, I I think there's this, like, project or it's, like, AI twenty twenty seven or something. Yeah.
Speaker 1:Yeah. Yeah. Yeah.
Speaker 7:It's like this I think that that actually feels, like, a little bit more grounded and than, like, some of the, like, the really, like, you know, AI doomerism. But I think the, like, the recursive ability or, like, whatever, like, p doom, whatever you wanna talk about. But, like, the recursive ability to make your products better by continuing to invest is, like, you know, it is a flywheel, and that's definitely, I think, the anthropic bet that they're going really hard at. And so, you know, the thought process is is like, well, okay. If if we can get the AI agent to do a, you know, AI AI experiments, not just coding experiments, then, like, boom.
Speaker 7:We are off to the races. And that really will be, I think, the, you know, the the the like, where the curve bends back in on itself. TBD, right, yet to be seen. I don't, like, I don't exactly like, from the outside looking in, there isn't exactly any any kind of special ability for me to say that it will or will not be that way. But I think, so far from what I understand for the researchers, I don't think everyone's, like, doomed or bared up on on some of the stuff.
Speaker 7:I definitely think ChatuchPut five is a little disappointing, but maybe maybe OpenAI just isn't cooking like it used to. Right? Like, I think and I don't know if I I I I don't know if it's a like, I don't know what actually happened at five, but, like, I wanna like, we don't actually know what's the, like, the ratio
Speaker 3:Well, you have to or out
Speaker 1:of all
Speaker 7:reasoning to, like
Speaker 3:Just Totally. Just remember, you know, you can debate on on the people that have left OpenAI in the last couple months. Like how how good they were? Were they the best people? Were they mercenaries?
Speaker 3:But any company that has been gearing up for a massive product launch, like or have gone through a massive product launch, imagine going through that again but you lost like 40% of of of some of your most elite team members. Like that could be that's like should obviously have been a factor here. If it wasn't then Zuck is cooked because he just hired a
Speaker 6:bunch of people that
Speaker 1:just weren't that great. Someone's cooked.
Speaker 3:So I think that I think that, yeah, that's worth asking the question, what would Chad what what would GPT five have looked like if Ilya was still at the company? What would it have looked like if Mira was still at the company? Would it have looked like if their long tail of researchers that left were were still there? What would it look like if they just didn't have the distraction of the talent war?
Speaker 1:Yeah. Yeah. Right? Yeah.
Speaker 7:Yeah. I I think that's a valid question because my understanding of, like, why Gemini two randomly was so good is, like, Noam Shazir was back. Yeah. And that's it. Like, that's literally it as far as I understand.
Speaker 7:Like, all of a sudden, Gemini starts cooking again. It's like, yeah. Because, like, the guy who invented half of everything is back. So I'm not I'm not surprised that that's, like, a real dynamic. Yeah.
Speaker 7:But, yeah, we're gonna have to see we're gonna have to see. I I do think you're right. Vibes are are interesting. I do think probably tracking that cohort. Like, if you think about it just like an incremental slosh, like, you know, that's either the biggest best investment of all time or gonna be the worst investment of all time.
Speaker 7:And like tracking that cohort and how that works out is gonna be like a really interesting like case study.
Speaker 1:Can you
Speaker 3:us an overview of what's happening in private credit headline this week? Obviously, that Meta had tapped Blue Owl and Pimco for like a $30,000,000,000, you know, you know, I I don't know that the sort of pace at which they'll get access to that capital but
Speaker 1:Just give us private credit one zero one and go as deep as you want.
Speaker 3:Yeah. One zero one zero one but also, like, you know, the real kind of risks
Speaker 1:Yeah.
Speaker 3:Surrounding it Yeah. You know, over the next year or so.
Speaker 7:Okay. So I do think at semi analysis, I'm the finance guy, which is funny because I definitely don't know if I, like, in the big scheme of finance, how much finance I have. But okay. Private credit is like public credit, but there's no marks. Okay?
Speaker 7:One of the things I got really interested Okay. So one of the things I got really interested about that is, like, private equity rules because you could suck at your job, but if you have no marks, like, you're you're, you know, you you don't have a bad, like, performance and your volatility, like, you know, kind of chills the f l. So on an alligator they're stoked. Like private this
Speaker 3:is the beauty of of being in, you know, in venture broadly is the market goes up and down and 90% of my net worth is stable. Yeah. Or it's not stable in reality, but Yeah.
Speaker 7:Yeah. And I think that that's like a like almost like a feature. Totally. It was a a feature that was like a bug at the beginning, if it makes sense, because it's like, okay. There is no mark.
Speaker 7:And because of that, you can effectively like, you know, the volatility in these assets are really low, and you hold it to maturity. There's a lot of studies and papers that effectively, like, you know, public equity levered up over five years when you don't sell is, like, very similar. Like, the returns actually start to approach each other. And some of the cohorts of private equity, have really started to implode a little bit and have a low money out of the investment. So, anyways, we're that's private that's private equity, which I'm, like, super familiar with.
Speaker 7:Very, like, very funded. Private credit is, like, a lot of the same same energy in terms of the mark, and, effectively, you own this piece of debt to maturity. So there is no you you know, don't really take a mark on it. And and so you could get like, at one point, specifically, everyone raised these capital vehicles that were like, we're gonna get high single digit returns with very little volatility forever. And so everyone was like, dude, sign me the hell up.
Speaker 7:And so Yeah.
Speaker 6:If you look at
Speaker 3:if there the the number of billionaires that private credit has created in the last, like, two decades
Speaker 1:is Like, 50 in in the Forbes article. Tons of Wait. Really? Oh, yeah.
Speaker 7:I'm gonna I'll send
Speaker 1:it to you. Because Yeah. Private I mean, just in Aries, there's like four billionaires.
Speaker 3:Because it's just if you're if if the best way to become a billionaire is AUM maxing and Yeah. And this ad and private credit allows you to a like, AUM max better than Massively. Anyone. Almost any of these other other sectors, then it it's just
Speaker 1:So the yeah. Really quickly, Bloomberg highlighted 18 folks who are now billionaires from private credit starting with Ares at 13,000,000,000 net worth going down to Blue Owl Craig Packer at 1,000,000,000. And so 18 new billionaires have been minted from the private credit boom.
Speaker 7:And, yeah, I think from my perspective on the private credit boom is like, okay. It's definitely been a thing this entire time. But, like, in the last few years, like, there is a hockey stick moment where I wanna say it's like late twenty three or something like that, where the pitch was like almost, you know, unbelievable. Effectively
Speaker 3:This is simply too good.
Speaker 7:Yeah. Yeah. It's like it's like you can get equity market returns in the long run with with no mark to market risk and you know volatility and, in theory, less risk. So you're like, dude, equity risk or no. No.
Speaker 7:Lower than, equity return with, like, relatively no risk on, like you know, it's, like, obviously, a spread of treasury. You're like, bro, sign me the hell up. Like, I'm gonna slam that button until the button stops working. And so everyone raised these giant funds, like ginormous funds. And so now these private credit guys are, like, sitting on a bajillion dollars of AUM, and they're like, dude, how do I get this get this to work?
Speaker 7:And so now private credit is finding its way into you know, it's it's kinda like the private equity. They're gonna have to deploy. And so for for people who are looking to deploy very large amounts of assets, I think data centers are gonna be really interesting. Because in theory and and this is just, like, depends on on the whole stack, but, like, data centers are more like real estate investing. So you have a very different return profile that often are baked into the deals.
Speaker 7:And I think it's and it's very capital intense on a relative basis, so you can deploy a lot of capital, which is awesome. And so you do that. You get, like, these five year, ten year investments with, like, pretty solid chances right now, at least. In, like, the two, three years, you're super money you're super money good. Like, some of the early data center investments are, like, fucking awesome.
Speaker 7:And so you're just gonna you're gonna slam that bet, dude. You're gonna freaking you're gonna you're gonna deploy. And so the The private
Speaker 1:plateau theory feels good here because the the the risk was that I build a I build a frontier model capable data center that runs GPT four. And then GPT five comes out and I can't run GPT five and I'm completely useless. Every all the workloads move to GPT five and and I have no business whatsoever. Instead it feels like the workloads are like sticking around for a
Speaker 3:long It's it's important you you can have like a plateau in intelligence that is different than a plateau in usage. Exactly. If usage and and demand plateaus that becomes a real problem.
Speaker 7:It becomes
Speaker 8:You're cooked.
Speaker 7:If you
Speaker 3:just spent $10,000,000,000 on, you know, super levered data center development.
Speaker 7:I I think I think you're probably right in terms of the fact that if the pace of if the pace of everything slows down in terms of progress, you can underwrite the return you can underwrite everything a lot more chill. Yeah. You know, you're not gonna be like, dude, my you know, the dataset you know, the chips might get used longer, so you can be like, oh, you know, they're four year lives and they're five year lives with high high certainty. You know? The algorithms aren't just gonna, like, massively consume all this stuff and make, like, the crap you bought effectively, like, super cheapen very quickly, and then your investment is more money good.
Speaker 1:Yeah. It was like having, like, having a Bitcoin FPGA farm or something, you got destroyed when everyone went basic. Right? And and that's the risk, but that's not the nature of the current frontier path. Like like, GPT four workloads or GPT four class workloads are sort of sticking around probably for a really long time.
Speaker 1:And in the future, even if we do develop the super intelligent model, it'll probably be calling less intelligent models. There'll be distilled models for specific tasks, specific models for tool usage, and all these different work agentic workflows, etcetera. So, yeah, it it it feels like all this stuff is is gonna be sticking around and and good news for the depreciation cycles.
Speaker 7:I I don't know if that's, like so I'm I'm gonna, like
Speaker 1:Please.
Speaker 7:I'm not gonna endorse that view just because we're, like, speculatively one shotting this in
Speaker 1:a day. Yeah. Yeah. So, like,
Speaker 7:you know, we'll see. I gotta think about this.
Speaker 1:Yeah. Totally.
Speaker 7:But I do think I mean, I do think this is probably better for the longer tail if frontier model stuff slows down. I think if we're just talking about, like, hey. Truly everyone else. Right? Like, in the world where progress is exponential and there's only three companies doing it, effectively, everyone else is a giant fucking loser.
Speaker 7:Right? Everyone is just a giant fucking loser. There's no way they're gonna have any kind of products. Everyone's just, like, totally cooked. Who cares?
Speaker 7:Why would you ever invest in Neo CloudX or front or, you know, behind the curve lab y or, you know, whatever accelerator company z. Right? I think it probably is better for just the entire ecosystem if we're talking about just, like, the longer tail of capital. Specifically, like, I think, like, the neo clouds, the GPUs, the, you know, everyone that isn't named OpenAI, Google, or Anthropic. So I do feel very strongly about that.
Speaker 1:Well, this has been fantastic. The chat is going wild. One hour guest. Semi analysis in my veins.
Speaker 3:This is our first ever one hour guest.
Speaker 1:Nope. Dylan Patel was also a one hour guest. Every time I get someone for Semi analysis
Speaker 3:Semi analysis.
Speaker 1:Stay on forever. Do the whole show with us. I really enjoy these chats. I really take the time.
Speaker 7:Just so you know, like, I we have a lot of, like, I have, have, like, a lot of ability to make this happen or not. Dude, we have a lot of cracked people at semi analysis.
Speaker 1:Please send them all over. I love these chats. I
Speaker 2:I love it.
Speaker 7:You talked to Jeremy. Right? You talked
Speaker 1:to Jeremy. Right? Yeah. Yeah. He was fantastic.
Speaker 7:I fucking love Jeremy. Okay. Like, dude, we have, yeah. So, like, that's, like, the benefit of something else. Yeah.
Speaker 7:Yeah. There's lot of cracked people. We'll send them all over.
Speaker 1:Yeah. Send them all And and I have a plan. So our plan is we've been we've been teasing that, you know, basically, if you're if you're a real VC, you're you're you're on this, like, the super secret $1,000,000 a month semi analysis plan. And if you're not on that plan, you're kinda just a tourist. And so we're gonna we're gonna get every single VC in Silicon Valley on the $1,000,000 a month semi analysis plan.
Speaker 1:That's our that's our pitch. We're gonna meme it into reality.
Speaker 7:I'll take it. I'll take it.
Speaker 3:Yeah. For every billion dollars of AUM, you should be spending at least 15,000,000
Speaker 1:I think so.
Speaker 3:On I
Speaker 1:think so. Otherwise, you're just a tourist.
Speaker 3:Yeah.
Speaker 1:You don't really understand this stuff. But thank you so much for stopping by. We yeah. If you're not if you're listening to this and you're not subscribed to somebody else's, what are you doing? What are you doing?
Speaker 3:Thanks for joining, Doug. This was fun.
Speaker 1:This was really fun. Let's do this morning. Yeah. We'll talk to you soon.
Speaker 7:Yeah. We can talk talk earnings, honestly. That's I'm that's, like, probably where I'm best.
Speaker 1:Amazing. Yeah. Season.
Speaker 7:So Great. Take care. Alright? Amazing. Bye.
Speaker 1:We'll talk
Speaker 3:to soon.
Speaker 1:Bye. Up next, we have Mitchell Green from Lead Edge Capital coming in the studio waiting room. In the restring waiting room. Let while we're bringing him in, let me tell you about Adquick. Out of home advertising made easy and measurable.
Speaker 1:Say goodbye to the headaches of out of home advertising. Only Adquick combines technology, out of home expertise, and data to enable efficient seamless ad buying across the globe. Mitchell, are you there? How are you doing? Good to see How
Speaker 5:are you?
Speaker 1:I'm great.
Speaker 3:Great to see you. Sorry to
Speaker 1:you waiting. Sorry I missed you when you were on the West Coast. We'll have to hang out in person soon. But how was your trip? How are you doing?
Speaker 5:Good. No complaints. How about yourself? How's life?
Speaker 1:We're doing great. Big week last week. We were in New York for the Figma IPO. There was lot of fun. We had to be slow.
Speaker 1:A
Speaker 3:slow week this summer.
Speaker 1:Yeah. It's been a lot. Cycle.
Speaker 5:People always look people always say it's like, you know, it's like, oh, it's really busy. Yeah. I'm sorry. I'm waiting for it to slow, but it never actually slows.
Speaker 1:Yeah. It never slows. Well, speaking of things that aren't baby. Slow Speaking of things that aren't slow, I wanna talk about fast cars. Everyone at OpenAI just received allegedly, the rumor is, a $1,500,000 bonus for being on the team for more than two years.
Speaker 1:I want you to help me advise these OpenAI researchers. We wanna we we we told them, don't buy a house, buy a car. And so I pulled up some I pulled up some options that you could pick up for $1,500,000.
Speaker 5:We should buy think this is what they really should do. Everybody everybody should get some leverage. Leverage.
Speaker 1:Take take the one five. An f 40. Buy an f 40. Okay.
Speaker 3:So There
Speaker 1:we go. The SP three. We're skipping the Valkyrie. We're going straight to f 40. That's great.
Speaker 1:I love that.
Speaker 5:What about By the way, there's at least somebody on an engineering team that will do it. Most of probably buy, like, Priuses. But there might be, like, one or two guys that'll do it.
Speaker 1:I mean, when the boss is driving a Koenigsegg, you know, you gotta show up at something, at least a depreciated Veyron.
Speaker 5:Well, look here. The thing that's funny you said about Koenigsegg, he can drive it as long as it turns on and runs.
Speaker 1:Yeah. Any advice for the Koenigsegg owners in the in the audience, keeping that thing running?
Speaker 3:I like the Yeah. The I
Speaker 1:mean, he also has f one. Well Nothing wrong there.
Speaker 3:Right? Okay. As much as I wanna talk about this
Speaker 1:Sure.
Speaker 3:I do I do we have limited time and I do want this
Speaker 1:week.
Speaker 5:And by the way, you need to have Zach Brown and I am together sometime. I'll talk to investing. He can talk to cars.
Speaker 1:Okay. Fantastic. Perfect. We'll do that.
Speaker 3:So reaction from the timeline this week is that it feels like model Frontier models are plateauing a little bit. And I think that's generally fine. There's still a lot of capabilities to unlock. But I get concerned for the VCs that have been deploying billions of dollars into the longer tail of companies that have been kind of like more They don't have necessarily traction. They don't necessarily have truly top talent and they were kind of moonshot esque bets on this idea of super intelligence.
Speaker 3:And so anyways, I'm I'm curious how cooked is the venture industry and and Mhmm. VCs broadly if and and and and the other factor here is like within a bunch of subcategories, there's five or six heavily funded players going after the same opportunity, and that will create healthy competition, sometimes sometimes unhealthy. And I'm sure there'll be some good outcomes. But but how are you thinking about the current state of venture?
Speaker 5:Yeah. That's a great question. So I was just writing some notes. Well, obviously, a bunch of questions in there. So AI saved the venture industry from a big awakening that was about to happen in 2022, and they just got, like, one more kick.
Speaker 5:What's what's absolutely incredible is that none of these people, like, remember none of these people have remembered what happened in 2021. K. Maybe you can excuse some of them in 2021 because they didn't remember what happened in '99 and 2000 because, like, most of them a lot of them weren't doing it back then. They weren't in the industry. But, like, most people that are doing this today were in the industry in 2021.
Speaker 5:It is the exact same thing. You know, as you obviously know, we focus way more on, like, profitable businesses. Like, 70 plus percent of our companies are profitable. Very you know, like, summer in Silicon Valley, but we find like, to find companies in Ames, Iowa and Niswa, Minnesota. We we're probably the only tech fund on the planet that has two investments in Sarasota, Florida.
Speaker 5:We, you know, go figure.
Speaker 3:You guys dominate in Sarasota.
Speaker 5:Yeah. We dominate in Sarasota.
Speaker 3:But I but I felt that over the last year where
Speaker 5:Let me continue. So 90% is okay. Before that. People always underestimate technological change in the long term, and they always overestimate it in the near term. Think like the Internet bubble, think mobile phones, think self driving cars, like, I think PC revolution.
Speaker 5:Like, it always they always do that. This, what we're seeing in AI, is so reminiscent and what you're seeing in the markets right now is so reminiscent of '99 in February. Yes. By the way, some the big hyperscalers have giant amounts of profits and, like, are printing money. These AI companies, a huge amount of them, you know, 90 plus 90 to 95% of these application companies are going to zero.
Speaker 5:And by the way, it's not only you know, I'm saying that, I'm hearing that from some of the world's foremost, you know, early stage venture capitalists that are telling me that at the end of the day, 90 to 95% of these things are going bust. And a lot of it is driven by upside down unit economics. You know, like, it's funny. You see some of these AI companies that have you know, I'm not gonna give names, that have only 50 to a 100 employees, but are, like, raising, like, $500,000,000. And, like, you you can't spend that much money.
Speaker 5:Obviously, it's because they have massive negative gross margins, and that money is flowing through the AI companies, which is flowing through the hyperscalers and flowing through the NVIDIA. People ask us, like, what are our thoughts on the models? We've always thought for right or wrong that the models will commoditize and it will become a game of who's got the best infrastructure and the and who can deliver the searches the cheapest. For the life of us, I can't figure out why Google, Amazon, Microsoft don't and and Apple, which hasn't played yet, but I think they're gonna go acquire I think they should go acquire somebody. And, like, why don't they just win at the in Facebook?
Speaker 5:Why don't they win at the end of the day? Mean, Nat Friedman is a total stud who's running AI. I mean, we backed his first company, Xamarin, or his second company, Xamarin. Total stud. Like, those these companies can spend $6.80 to a $100,000,000,000 a year on CapEx while having margins go up, still growing 22% a year printing money.
Speaker 5:Like, I don't know how, at the end of the day, Anthropic and OpenAI and Perplexity can compete against this. I mean, I joke that Google should literally run searches on ChatGPT and bankrupt them. Like, I mean, the cost
Speaker 3:Well, I mean, the news the news that came out, in the last twenty four hours is that Google is making Gemini free for students for the entirety of the next school year.
Speaker 1:So they will be subsidizing
Speaker 3:And so they
Speaker 1:will be
Speaker 5:By the way, they should make it free for everybody. And by the way, you know, I read somewhere, like, the the cost to serve the exact same search on, like, Gemini versus ChatGPT is some crazy percentage. It's like one tenth the price or one twentieth the price. And the by the way, that shouldn't be that shocking given that over the last twenty years, Google has spent, you know, all their a lot of their efforts on taking their infrastructure and, you know, making a fraction of a fraction of a penny more efficient.
Speaker 1:Yeah.
Speaker 5:And I think this I think this becomes an infrastructure play. Now I do think I think there's gonna be, like, insanely amazing companies using AI that are built. I actually think a lot of incumbents are gonna win. You know, ever since this device came out, there's only been four companies built that came out after this device that have been worth a 100,000,000,000 or more. It's like ByteDance and Pinduoduo, two companies in China.
Speaker 5:And ByteDance may be one of the best AI companies in the planet that's just like the hidden giant out there.
Speaker 3:Yep.
Speaker 5:And then Airbnb and Uber. That's it. The incumbents are gonna win. Salesforce. Or OpenAI.
Speaker 5:Oh, yeah. Oh, no. OpenAI is not the incumbent. Like, it's one of the new guys. I challenge the people that ask, why is OpenAI not like Excite, Lycos, or AltaVista?
Speaker 5:Like, I'm not saying it is, but, like, I think it's hard to make a bet at a 300 to $500,000,000,000 valuation that, like I think you either make a zero or a five x. Like, I I think I think it's a really binary, and the and the unit economics on these companies is massively upside down. If it wasn't, you would see some of these companies go public. And I actually joke that people, you know, we might as well be in a bubble. The Internet bubble, nobody gave a damn that the unit economics were upside down.
Speaker 5:Take them public. Let's see if
Speaker 3:they can go. Yeah. I mean,
Speaker 1:weren't. They weren't. The the the unit economics of Google were were were very, very good going into that IPO, and they maintained a good unit
Speaker 3:economics throughout the world. General read was was, you know
Speaker 1:Journey to that company.
Speaker 3:Model like intelligence is plateauing Yeah. But it's not necessarily bearish for OpenAI because it's a habit. They have a 100,000,000 people in The US that are using the product every single week and
Speaker 5:But what what what you should adjust though is that that's that's the upside. The the the downside is the 100,000,000 people use it.
Speaker 1:Yep.
Speaker 5:But the downside is is that, like, the the investing here, you're gonna get massive amounts of dilution because you have companies like Facebook and Microsoft and Amazon and Google that that now pay top engineers like they play in the NBA. Yeah. And can fund and these companies are gonna skip massive amounts of stock based comp. But, like, I use Jack DePetit all
Speaker 1:the time. Yeah. Yeah. But I think people might but but the economics are not are nowhere near
Speaker 5:the What's crazy is it's like, people are like, well, you know, Lycos and, like, Excite and AltaVista didn't have that many users. I'm like, yeah. But the number of users on the Internet went from, like, you know, 200,000,000 to, like, 5,000,000,000 or something. So you're like, you need to adjust for that too. But no.
Speaker 5:I mean, the the consumer growth rate is insane. If you have ins insane in consumer growth, you should be able to attract world class talent.
Speaker 1:Yeah. But if if you hear about People
Speaker 5:know, oh, yeah.
Speaker 3:Like, the competitive dynamic, like, what OpenAI as a company has been able to accomplish despite competition from all the hyperscalers, despite competition, you know you know, the the talent wars, all these different things in competing in the most CapEx intensive industry since the railroads or Yeah. Or or
Speaker 5:Might be more capital intensive. Yeah.
Speaker 3:It it's truly incredible. And to do that as a company that still some people see as like a a startup, you know, is
Speaker 5:No. It's it's amazing. I think the other
Speaker 3:What about?
Speaker 5:The other thing that's interesting is you hear the application companies all say, well, the costs are gonna plummet for, you know, the cost for AI stuff. But the issue is if, like, if the costs are gonna plummet, that would be good for the application companies. But then, like, doesn't if the cost plummet, isn't that bad for OpenAI or Anthropic? Because they're they're, like, revenues are now gonna, like
Speaker 3:Well, Jevan's paradox, if the costs go down, people will just
Speaker 1:I mean, right now, like like, OpenAI has tons of paying customers and people that use the product. So costs, like like, they are both a a victim of commoditization at the model layer and a beneficiary of commoditization at the model layer. And so, like, yes, you should maybe discount their their model API business more, but then you give more value to their consumer business because it has higher margins, better unit economics. It starts looking more like Google and less like AWS, I guess.
Speaker 3:Yeah. What about what about legacy SaaS? People have been extremely bearish this week's Yeah. In particular. It's been kind of
Speaker 5:By the way, that that's why you go invest in it.
Speaker 3:Yeah. So
Speaker 5:By the way, Steve Cohen has told me for years. Like, if everybody's going one way, go the other way and you'll make a ton of money Yeah. Over the years. I mean, I think, like, the Chinese small cap Internet Chinese small cap index is up, like, 50% or something this year. The great thing is, like, I don't have to make an investment in these AI in these, like, model companies.
Speaker 5:By the way, I should have hit 30,000,000,000. Like, we should. We were wrong because we could have sold now. Right? Right.
Speaker 5:So I don't have to make an investment, but I do run an investment firm, so I need to invest in things. And, look, we look at a lot of these AI cup application companies, and they grow crazy fast, but we're not gonna pay those valuations. And I'm not investing in businesses that have 50 to 60% gross dollar retention. Like, screw nets. Look at gross.
Speaker 5:Like, that's what really matters. And so what are we gonna go do? Let's go find bootstrap software companies that are in, you know, College Station, Texas and Toronto, Canada and in, you know, Sarasota, Florida, companies like Pacemate that make cardiac monitoring software, companies like, Gravity that make a budget planning software, and companies like a list of plan that make financial planning software. Again, these companies aren't gonna change the world. But, again, we can take them from 20,000,000 of revenue to 60,000,000 of revenue, and there's a lot of homes inside strategics or private equity funds.
Speaker 5:And, by the way, these are businesses that have, like, 95 plus percent gross dollar retention that have been bootstrapped businesses that we're now using AI to make them more productive. Like, have 15 software engineers, now they can use AI to have 30 software engineers. And as long as those companies still sell to humans on the other end of the table, then a you know, if if if companies if AI companies are selling to other companies that use AI and they're talking to agents and we don't need people, like, I think, you know, then that's possible. But I then then I think these a lot these companies are in trouble. But I we think a huge amount of these, like, software companies that are out there that exist will actually use AI to create new products and become way more efficient and more productive.
Speaker 5:And, like, I truly believe AI is gonna be as big or more bigger of a productivity boom over the next twenty years that, like, than the Internet was.
Speaker 1:Is that is is it more of, like, a consolidating force or a decentralizing force? Is or should we see more roll ups going forward with a bunch of
Speaker 5:these We could see more roll ups. I think it also is, like, we really like vertical application software. Like, all those companies I mentioned were very verticalized.
Speaker 1:Yeah. Yeah.
Speaker 5:Yeah. They're, own a system of record. Yep. And and, like, they can just use AI to become like, I know some there's some very smart private equity guys that are using AI to try to start to do roll ups and stuff like that. Or, like, I know that I think the general catalyst guys, the Thrive guys are, you know, are looking to buy insurance companies or Yeah.
Speaker 3:I had I had I had a meeting or or dinner with with a few guys, I think it was Tuesday night that were doing AI enabled roll ups in like a a couple key industries and I won't say them because I don't wanna give away their alpha. Mhmm. And then Wednesday I had a had a meeting, John and I had a meeting in the morning with somebody that was like, yeah, like, you know, at least one of the labs will hit escape velocity and we'll get a fast takeoff in the next two years and nothing's gonna matter. And I was thinking to myself like, even in that fast takeoff scenario, like, it's just it's impossible to to imagine
Speaker 1:You're like, I'm still gonna be using
Speaker 3:couple of these category Yeah. You know, a a number of different categories where, like, people will just maintain control. Right? Yep.
Speaker 5:And As long as so we have as you guys know, our LP based, all these, like, world class execs and entrepreneurs and people like that. And we talked to these people that have built giant software companies, and one of them said I was like, do I we do we need to be worried about all these companies going bust? He's like, well, as long as your software company sells to another human on the other side of the table, like, that human will need to, like, make an interaction and probably interacts with software, so you're okay. And he's like, well, unless you think, like, an AI agent is selling to another AI agent. Like, if Leaders doesn't have any employees and my AI agent is talking to yours, like, your AI agent, then maybe we don't need people.
Speaker 5:But as long as people are involved in the equation, you're gonna need software companies.
Speaker 1:Yep. Makes sense. Well, we are running behind. This is fantastic. We gotta have you back on the show.
Speaker 1:Anytime. Thank you so much for helping Yeah.
Speaker 5:Let's Come up. Come see him. We'll go for a drive.
Speaker 1:For sure.
Speaker 3:Come in. Come in. And and come back on. I I I wanna get a sense of how we should be thinking about IPOs in this back half of Obviously, the Figma was very exciting. There's more on the horizon.
Speaker 3:I and I wanna get a sense for how you're kind of
Speaker 5:No. Happy to talk about it. Funny thing is if you go back and look at the last, like, everybody said the IPO market was dead. It actually hadn't been dead. It wasn't dead.
Speaker 5:Investors but you can go look look at Reddit. Look at all these things that went public over the last year.
Speaker 1:It did great. Yeah. The IPO window's secretly been open for It's been open all time. People just
Speaker 5:don't wanna admit that they overpaid for the company. Didn't wanna take it public.
Speaker 1:Yep. Yep. Yep.
Speaker 5:You have companies like we're in this. We're very early investors in Grafana. Yep. But you have companies like Stripe and a bunch of things that are awesome businesses.
Speaker 1:Yep.
Speaker 5:Itabricks. They just have so much capital on the balance sheet. They don't need to go public.
Speaker 1:They don't need to go public. And so yeah. Yeah. Yeah. Yeah.
Speaker 1:And so there's very different than the window being open versus the time is right for the best companies to actually go out, and they make that choice it's nice it's nice to be in the private markets. It can be
Speaker 5:You mean it's not fun for most funds to not have to mark their books every day?
Speaker 1:Like, That's fun. SEC filings are not fun. The tender offers are fun. There's plenty of ways to stay private and have fun.
Speaker 5:And actually, what's amazing is is, like, we are finding it's crazy where you could find opportunities. Like, you'd be like, how does a same size company in Sarasota, Florida get done at five times revenues, and a company in Silicon Valley, oh, but it's growing faster, gets done at 90 times revenues. Like, the world is becoming this, like it it it it like, there is true value to be had by just looking a little bit off the beaten path in our view. So.
Speaker 1:Yeah. Yeah. For sure. Anyway, thank you so much for taking
Speaker 5:your time. Man. Shut me up.
Speaker 1:We'll talk to you soon. Have a great day. Cheers, Mitchell. Have a
Speaker 5:good weekend.
Speaker 1:Have a
Speaker 3:great Friday.
Speaker 1:Bye. And next up, we'll bring in Ben from Orbital Operations. We gotta get the gong ready.
Speaker 3:Get it ready.
Speaker 1:Ben, how you doing? Are you there? Sorry to keep you waiting.
Speaker 3:He's going. One sec.
Speaker 1:Great to have you on the show. We got some folks in the chat. The IPO window has been open, but everyone hasn't given the group of new public companies credit. Everyone is treated as a one off like it's not indicative of a collective market. Good point, Dan Ratliff.
Speaker 1:Anyway, welcome to the stream. Do we have Ben? How you doing?
Speaker 3:Yeah. Starting to explain why
Speaker 6:you're doing the show. Yeah. I was listening to the previous conversation.
Speaker 7:It was
Speaker 6:pretty interesting.
Speaker 1:Fantastic. Thank you, for hopping on. Would you mind introducing yourself, the company, and then what news you got for us?
Speaker 6:Yeah. So my name is Ben Schluniger. I am the cofounder and CEO of Orbital Operations, and we just announced closing of our seed round. We raised 8,800,000.0.
Speaker 3:Woah. Congratulations. There we go.
Speaker 5:Thank you.
Speaker 6:Thank you.
Speaker 1:Who's in the deal? Who's making money off this?
Speaker 6:So Initialized Capital is leading We've got big participation as well from Harpoon Ventures, DTX Ventures, Rebel Fund. Is in as as well, and a lot of other angels that joined on board. Yeah. Went through Y Combinator earlier this year. That's cool.
Speaker 3:8.8 reserve.
Speaker 1:Good numerology. Chinese number 12.
Speaker 6:The More more of a more of a range we were trying to hit based on the technical milestone. Orbital operations is developing a high thrust space vehicle. It'll be stationed out in orbit for satellite defense. So our, you know, we've got some some hard tech development to go through and really prove out our technologies.
Speaker 1:So satellite defense, I have a satellite up in I have the Hubble telescope. I don't want someone to shoot down the Hubble telescope. I pay you to loiter around and blow up any missiles that are coming at it. Like, what how are we actually defending?
Speaker 6:Yeah. Yeah. So it's interesting. We have a ton of critical and I bet by we, I mean, The United States has a ton of critical infrastructure out in, you know, both low Earth orbit, but even higher out, like medium Earth orbit, geosynchronous orbit. You could think, like, GPS, naval communications, nuclear command and control.
Speaker 6:They all sit at these higher orbits. It's actually really, really challenging for, like, missiles or anything to get out there, even rockets designed to go out there. Yeah. But there are adversaries placing satellites that have capability, and it's been demonstrated already, to be able to grab other satellites and pull them out of orbit or, you know, be able to fry a solar panel or jam communications, whatever it is. And we currently don't have a response for this.
Speaker 6:We don't have anything stationed out in these higher orbits. And so that's what we're really looking to to build is a vehicle that has enough thrust, fast enough response time, and enough extended range to be able to go and intercept these things. Hopefully, not blow anything up. Space defense is a little weird. You don't wanna create shrapnel.
Speaker 6:Right? The last thing you wanna do
Speaker 1:is Killer. Killer.
Speaker 6:Shrapnel. Yep. Exactly.
Speaker 1:And so Walk through. If you don't wanna create shrapnel, you don't just wanna run into this. I'm I'm trying to comp it to Andoril. You know, you have the anvil. It just like it's a stone that rocks that runs into the drone.
Speaker 1:Then there's, you know, remote takeover. There's microwave, different radiation, different, different energy sources. Yeah. Jordy, we've had a company on a on the show that just is a gun on a truck. It just shoots down the creates a lot of shrapnel when it shoots down the drones.
Speaker 1:But there's you know, I've seen, like, eagles come and pick up drones. Walk me through the different tools in the tool chest for taking out a satellite killer.
Speaker 6:Yeah. Yeah. So, I mean, unfortunately, one is to just, like, ram into it. Right? That is like That's an obvious.
Speaker 6:And that that is kind of the worst case last resort. Make a bunch of shrapnel. Here on Earth, shrapnel falls to the ground
Speaker 1:Yep.
Speaker 6:Easy, but up there, keeps it stays there, runs into other satellites, creates a problem.
Speaker 1:Yep.
Speaker 6:The next is kind of what you were mentioning, you know, direct energy type of stuff. This would be high powered microwave. This would be, frying a solar panel or or a laser into the cameras and sensors trying to basically degrade the satellite. Right? The other option is to do what what we would call an RPO or remote proximity operation and actually go up next to it and grab it.
Speaker 6:Right? This is a more challenging operation to do, not something always kinda considered on the defense side, and more on the logistics side of things, but it is something that you could do as well. Those are
Speaker 3:Grab it. Grab it. Take it out into deep space.
Speaker 6:Yes. Yes. Yes. Just quiet into would
Speaker 3:always it off into the sunset.
Speaker 6:Quiet into the sun.
Speaker 1:Yep. I'm sure that'll be easy.
Speaker 3:Well, I guess my immediate question is that I mean, it feels like incredibly important work and also how do you kind of like prove out your team's kind of like capabilities. There's not exactly like a test range that you can take, you know, we'll have defense tech out Interesting. Here where they can just go out and do a demo for Yeah. The army or the navy or whatever.
Speaker 1:Gotta go to the moon.
Speaker 3:And in this case, you know, how do you how do you kind of test out different VCs at the product level to prove capabilities when you're not in a when when we're not in an active, you know, conflict?
Speaker 6:Yeah. Yeah. I mean, it's similar. You know, my background is all rocket engine development. Right?
Speaker 6:So a lot of it does Yeah. Start on the Well, we'll go rocket engineer, rocket scientist. You know, it's it's it's it's too flattering.
Speaker 7:I can't I can't take it.
Speaker 1:We need rocket researchers. We gotta get these salaries.
Speaker 6:There you go.
Speaker 1:Rocket researchers. That's a good Member of rocket staff.
Speaker 3:Talent we're here. Yeah.
Speaker 1:Member of rocket staff in the bio. Anyway.
Speaker 6:But, yeah, you you develop it on the ground. You're you're hot firing your rocket engineer on the ground. You're developing the tank. You're going into thermal vacuum chambers and testing all of that. And one of the great things about, like, this day and age is it is actually getting cheaper and cheaper to get orbit and start demonstrating these things.
Speaker 6:You know, rideshares, maybe you do a subscale version of what you're gonna do, which is what we're planning on doing for our orbital demo, and you you do a rideshare, and, you know, it is cheaper and it is faster than it's ever been. So it is it is not quite as easy as just going out to a live fire range, but at the same time, you know, proving out your core piece of tech. Like, it is getting easier to go to low Earth orbit and test it there.
Speaker 1:We're we're running behind today. So last question from my side. Is is cost to launch actually still dropping on some sort of exponential scale, or are we in a plateau? Are we waiting on Starship to get through testing? Like, are are are we actually reaping the benefits of cheaper and cheaper launch costs, or are we kind of in, like, a a local plateau?
Speaker 6:Interesting. Yeah. I mean, I think we've been maybe in a little local plateau for the last couple of years. Yeah. But, I mean, SpaceX has been dominating the market.
Speaker 6:Right? I think there are other launchers that are coming to market that'll help drive competition down. Sure. And then you have Starship and and Stoke bringing reusable second stages. That that will be another step down.
Speaker 6:Yep. That actually doesn't make it cheaper getting out to the higher orbits. It makes it cheaper getting to lower orbit. Mhmm. But those higher orbits, you know, the reusable rockets and and getting out to those higher orbits, they're not good at doing that necessarily.
Speaker 1:And that's where an impulse space comes in. Tom Mueller's company is a booster that takes you from LEO to to
Speaker 7:Yep. Yeah. KickStage.
Speaker 1:KickStage. Got it. Very cool. Jordy, you have anything else? Because, we're we're sorry to cut this short, but we are No.
Speaker 6:No. No. No.
Speaker 1:Today on a Friday. But thank you so much for jumping on. This is really fun
Speaker 6:to get to the gong. So I appreciate it.
Speaker 1:We hit the gong related again for you. Let's go. Appreciate it.
Speaker 3:There we go.
Speaker 6:I gotta get one to the office.
Speaker 1:You need one. Well, good luck. Stay right back on. You put something in space. We'll ring the gong again.
Speaker 1:Talk to
Speaker 6:later. Thank you so much. Cheers.
Speaker 3:Bye.
Speaker 1:And up next, have Merrill from Graphite coming in. You know Graphite. We do we we we read ads about Graphite every single day.
Speaker 3:I used
Speaker 1:to Graphite bringing
Speaker 3:while building my last startup.
Speaker 1:While he's joining, let's tell you about a different ad sponsor, Bezel. Go to getbezel.com. Your Bezel concierge is available now to source you any watch on the planet. Seriously, any watch. Get a hitter.
Speaker 1:AGI is delayed. Delayed. Super intelligence. Whether when it when when it gets here, if if it's five years, if it's ten years, it's gonna wanna look on your wrist and know that you mean business.
Speaker 3:That's right.
Speaker 1:So go to business.
Speaker 3:Without further ado, let's bring
Speaker 1:in Let's bring in Merrill.
Speaker 3:Time on the show.
Speaker 1:What's Merrill, how you doing?
Speaker 8:Doing well. Thanks for having me, guys.
Speaker 1:Good to catch up with you. It's been a week. I saw you in New York City. Had a lot of fun chatting. Give us the update and give us the the actual impact of GPT five, the news that happened yesterday.
Speaker 1:I wanna I wanna kinda noodle through that and and the impact, what it means for your business.
Speaker 8:So g p t five, obviously, was a huge a huge announcement, made a lot of waves. Our team immediately got to work on testing it, and I think we're noticing a few, you know, a few things that are improved about it and a few downsides that come along with it as well. On the improvement side, I think it's a lot better at deep thinking. It's good at one shotting apps. It's also the the biggest surprise for us is it's meaningfully cheaper on inference than a lot of the previous models.
Speaker 8:On to the downsides, though, I think, you know, there's a lot of buzz around it being this this massive step function. And, you know, for us, what we've seen practically in in reviewing code is that it's an incremental improvement, but it's not this massive step function. Mhmm. It is very much, like, still in the realm of of many of the other state of the art models. The other piece there that a lot of folks commented on is latency.
Speaker 8:I'm sure the OpenAI team is working on on improving this. But, one thing that we've noticed in in in updating our code review product.
Speaker 1:Yeah. I I wanna talk about
Speaker 3:Latency versus using just, like, the previous generation of models that are now being deprecated?
Speaker 8:Yeah. The previous generation of OpenAI models, Anthropic, and others.
Speaker 1:Yeah. I wanna talk about mixture of models. We we we were in the mixture of experts era with GPT four, and then, Grock is doing more mixture of different models together. And I'm wondering, like, code review is pretty high stakes. It's pretty high value.
Speaker 1:It's a very economic like like, I don't know. Like, the average salary or hourly rate of someone who's capable of doing code review as a human is really, really high. And so is there a world where I actually want to run, like, within graphite code review on every single model and then have you design a a rubric or a scoring system that compares Claude to GPT five to Grok to all the different models and kind of lets them wore it out and sits at a higher level of abstraction? Obviously, that's more expensive on the inference cost side, but is it cost prohibitive compared to a human reviewer that might be a couple $100 an hour?
Speaker 8:Yeah. It's a great question. I think today, it's certainly cost prohibitive to run every single model. What we do though and and what's worked really well for us is we you know, much like a human reviewer, we break down the task of code review, and we're looking for different, you know, different set of things at different times. So we'll we'll look for bugs, security vulnerabilities, efficiency gains that we can make, code based style guide, inconsistencies with the rest of of the code base.
Speaker 8:We also let customers define like, every team kind of has their own protocols and their own guidelines around how code should look, and we've let them define custom rules. Many teams are are really have like, heavily leveraging this now. And for each of those tasks, you know, those those can be this can be their own tasks in the review process. We also then once we generate a lot of comments, we'll have, like, simple things that we're looking for, like, you know, little rules that even these can be things that that that we've learned over time. Like, if it's come left to their own devices, the models like to say things like, we should update this line of code or or something, and developers find that really annoying.
Speaker 8:So, yeah, you probably don't need the highest power model to say, you know, we should like, don't add comments that that start with we, but over so that that is how we've kind of composed the the logic and composed the, you know, the voting system that we use to determine, is this actually a comment that's going to add value, or is it just going to be noisy, like many you know, the the challenge of many AI products and especially AI code reviewers out there?
Speaker 1:Yeah. How do you think about decomposition? We've heard this trend of, like, the the smartest frontier models might be training smaller models. We've talked to a couple, like, almost like micro foundation model companies where they're they're training you know, it's just a great model for filtering for profanity, and it runs and it was trained on, like, video game graphics cards. And I could imagine in the world of, like, tool use, there becomes a a future where there's a bunch of small models that are being kind of orchestrated by the more expensive model.
Speaker 1:How do you see the kind of the the the surface area of what you're building kind of fork out?
Speaker 8:Yeah. I think that there's especially as we as we think about the the scope of code review, it is it's it has come this first collaborative moment in the developer life cycle. It's it's historically, we've seen we've seen code generation be fragmented, every developer having their own IDE and terminal setup. Even today, we see this with a lot of our customers that are using you know, some engineers are using cloud codes, some prefer cursor. You know, everyone's trying the new cursor CLI now.
Speaker 8:Like, there's so much heterogeneity on the code generation side, but that's always been fragmented. But code review has always been unified, and it has to be because, you know, everyone is working together. It is that first collaborative moment in the developer process, and it is and then it connects to all these other pieces around, you know, CI, merging, deployments, everything that that comes downstream of that the moment you create that PR to get it out to production. And each of those, I think, represents the different tasks to be done to move those along. So you could think about having, you know, having one, you know, having one model or, you know, or one agent that's really good at resolving merge conflicts and another that's really good at looking at CI failures and figuring out what the, you know, what the problem was and being able to just fix that in the background without you having to do anything.
Speaker 8:And we see that I I don't think the the impact of that will mostly be one of reducing costs over time and, just letting you, you know, run a smaller model and, you know, not have to use this, like, super powered laser on on even a little task that that something smaller could do it.
Speaker 3:What is what is market share look like from your view upstream of of graphite? Like, what what are so so yesterday, we had a bunch of people on that were that had gotten early access to GPT five. And everybody's heavily conflicted because a lot of them are doing code code generation in in some way or another. It's hard to really suss out, like, okay, what is actually dominating other than just picking up what, people are saying on the timeline as actual users. But what are you guys seeing?
Speaker 8:Yeah. We're seeing a pretty big shift in the past even over the past three months, I think we've seen this shift from primarily orgs using, like, using cursor and moving more over to to cursor to Cloud Code, I think, has has really started to dominate the conversation for at at companies of all of all scales for the past few months. And now we're seeing you know, just in the in the past day or so, we've heard a lot more interest in in the CRISPR CLI. I think that that Claude really proved out that prompt first modality working working really well. And we've seen this sort of shift from, this the code first modality of of tools like Copilot and then Cursor and Windsurf, to now, like, prompt first with Cloud Code, Cursor CLI.
Speaker 8:And and then I think the next the next big shift is, like, staying prompt first but moving from local to, to, like, remotely deployed agents. And, we're already seeing you know, we've seen Cursor build something there, Cognition, CodeGen, you know, many others that that play, in in that space. So I don't think that we've seen a a massive I don't think we've really seen a massive shift in the past twenty four hours, though. It's still it's still I think the good news for everyone is that it's still a pretty close race, and competition is really, I think, necessary in in this world. I think if we ended up in a place where there was one model provider that was so much better at cogeneration than than another one, then, you know, there wouldn't be as much pressure to innovate.
Speaker 8:They'd have a ton of pricing power. It really wouldn't and it wouldn't reflect that that historical model of, like, cogeneration being kind of up to developer preference.
Speaker 1:What how is AI changing developer communication around pull requests? Like, the the canonical examples like you you know, you write a summary, you write like a headline. But I imagine that it's probably pretty easy. Like one of things the models are great at is just just condensing down information. I'm not a particular fan of them expanding information oftentimes, but but but if there's if there's a really big poll request, you can kind of show varying levels of summaries.
Speaker 1:And I find myself doing this even in the consumer realm where I will say, okay. I want a deep research report on something, some some the history of a business, but then give me a one line summary. Give me Yep. You know, five bullet points, then give me, you know, a New York Times article length, a couple 100 words, and then give me the full 30 page PDF. And because I want to be able to consume it like a fifth grader, like a college student in in these successive levels of of depth.
Speaker 1:Is any of that happening in the pull request world in the developer code review world?
Speaker 8:Absolutely. I think, one of the most used AI features and one of the first things that we launched in the Graphite platform was, the ability to, like, write the PR description for for you. And, it's something, you know, his developers kind of famously,
Speaker 1:like Fix.
Speaker 8:Like, hate writing long as it's, like, description. Yeah. Yeah. Like, just do this Need a change. Do this for me.
Speaker 8:But AI is amazing at at understanding a change, summarizing it. Now we're actually I think this is also where know, where we'll see CoderView going is it's it's moving from this world where you're just scrolling through, you know, scrolling through the diffs and everything is just in alphabetical order, and you have to kind of guide your own way through it to I think now AI is incredible at at, you know, understanding the change. Like, we we were actually working on working on a new feature launching pretty soon in Graphite where you'll be able to just ask Graphite, you know, hey. What are the important parts of this change? Like, walk me through the the key pieces of code that changed here.
Speaker 8:What should I be looking at? What is high risk? And and making it a lot more I think even in AI code review right now, I think we're still we're still in, like, the Copilot v one moment of of AI code review where we're just adding comments on GitHub. But the future, I think, is much more of a one that's good. It's interactive and is is guiding you through the code change in real time and helping you helping you to both review it and also to, like, make updates and coordinate the various agents that are working on on that change in real time.
Speaker 1:That's great. Jordy, anything else? I think we're
Speaker 3:Yeah. I'm I'm cure I mean, the main thing is, I guess, like, going into this year, everyone said this is the year for agents. Mhmm. And I was and and it felt like yesterday with Greg or Mark, said, this was the year more of deep research. Then they said, maybe maybe
Speaker 1:Also, coding agents.
Speaker 3:Coding agents have been the other thing. Where what do you expect out of the coding agent market in the neck like, before the end of the year?
Speaker 8:Good question. I I think that the biggest thing is that we're just we're just moving through, like, slowly moving moving around that that grid if you have, like you know, the the way I think about the market is is you have one access of where does the code live. On the one hand, historically, it's all lived locally. Now we're seeing a shift to to some of this living remotely and having these background agents that you access primarily through prompting. And then on the other axis, have, like, is the interaction modality code first or is it prompt first?
Speaker 8:The code first ones being you know, you started with Copilot, you had Cursor, Windsurf. Now we're seeing the prompt first and the prompt first modalities and quad code, the Cursor CLI, Warp, and others. And I think we're starting to see we've seen that shift from, like, the local code first to the local prompt first tools now. And now I think what I'm curious to see for the rest of the year is how quickly we then go from local prompt first to remote prompt first using, like, Cognition, cogen, cursor background agents, those others. And I do I think our our bed and and what we're seeing is is that that is very much the future.
Speaker 8:It requires you know, it likely requires another step function improvement in the models for that to be you know, for that to truly be the, you know, the primary modality of of software development. But, I think that's that will be the shift that we'll start to see, for the rest of the years, you know, that migration from, you know, from local to remote prompt first modes.
Speaker 3:Makes a lot of sense. Well, thank you for joining. Thank
Speaker 1:you so much. Have a great Friday. Have a great weekend. We will talk to I'm
Speaker 8:sure it'll be busy weekend
Speaker 3:for the whole graphite team
Speaker 1:For sure.
Speaker 3:Getting making sure that GPT five is rolling out.
Speaker 1:Fantastic. We'll talk to you soon. Have a good one.
Speaker 8:Alright. Cheers. Thanks for having me guys.
Speaker 1:Later. We have to talk about the actual biggest news in artificial intelligence. We missed this. Everyone's been focused on GPT five. The biggest news in artificial intelligence is that the billionaire AI co founder Lucy Guo pays nearly $30,000,000 for an LA spec house.
Speaker 1:Lucy Guo found cofounded Scale, now runs passes, got a discount on a Hollywood Hills home. Tech entrepreneur Lucy Guo, 30, has been called the world's youngest self made woman billionaire. Now, she's putting some of her earnings into real estate. She paid $29,500,000 for a newly constructed mansion in LA's Hollywood Hills. According to people familiar with the transaction, the price is a significant discount.
Speaker 1:They originally were pricing this house at $43,000,000. It's a 13,500 square foot house with five bedrooms on 1.2 acres. And this is I mean, everything about this house looks great. The photos are fantastic. The one mistake, Lucy Guo couldn't be reached for comment.
Speaker 1:Why are you no commenting this article? You gotta tell your whole story.
Speaker 3:All I can say
Speaker 1:is you
Speaker 3:can sign up at passes.com.
Speaker 1:Exactly. There was there was a great there was a great opportunity to to upsell to do all sorts of stuff. But, there was a I I this this house has everything. A sunken a sunken fire pit, a pool, jacuzzi. It has everything.
Speaker 1:It looks fantastic. LA's high end real estate market has been hobbled over the past year by the LA fires, outward migration and lower to lower taxes and broader economic uncertainty. Most of the recent high end sales have closed at significant discounts. So there's really no reason to buy a 30 Friend
Speaker 3:of mine in Malibu says that the there's a barbell in the market right now where things are hot under under like five Mhmm. Like single family homes and then really hot on the high end in the like 50 plus range.
Speaker 1:Well, of 50 plus, ex Google CEO Eric Schmidt has purchased LA's Spelling Manor for a 110,000,000 Finally. This is a very is a very fun article. Amidst a challenged luxury market, the property sold for less than its $20.19 sales price. He got a steal. This was built The Spelling Manor, if you're not familiar with this, this is an iconic legendary house.
Speaker 1:If we can pull up the image, look at this thing. It is insanely large, multiple wings. It has an entire It's
Speaker 3:like a b 21 raider from above.
Speaker 1:It's amazing. It's amazing. It has an entire famously has an entire room for just wrapping presents. Because when you're
Speaker 3:at this level,
Speaker 1:yeah, when you're at this tier, you don't just like
Speaker 3:You gotta be wrapping. You
Speaker 1:yeah, you need a whole room for wrapping presents because wrapping lots of presents because you'll be giving out lots of presents. It's a 56,500 square foot property, 14 bedrooms on five acres and this is in Los Angeles. This was built by Aaron Spelling who was a TV producer in the nineties. Very very famous. The French chateau style property is slightly larger than the White House.
Speaker 1:It has a bowling alley, a wine cellar and a beauty salon with massage and tanning rooms. So if you need to get a tan on, you go to the tanning
Speaker 3:movie theater though, John.
Speaker 1:I don't know what the movie theater status is. We need We're under on a movie theater. Well, property will remain a single family home. The Schmitz philanthropists who have homes around the world purchased it primarily to host meetings and events for LA nonprofits and cultural institutions. They're not even they're not even living in it full time.
Speaker 1:It was sold for a discount. It was listed for a 137,000,000.5 after several years on the market and multiple price cuts. I mean, it's such a big iconic house. The buyer pool is probably pretty small. It it was last sold in 2019 for about 120,000,000 when the seller was British heiress Petra Ecclestone.
Speaker 1:Ecclestone famously hired a team of roughly 500 workers to complete a massive renovation of the property. And now, just six years later, the Schmitz are planning a significant remodel of the house to simplify the floor plan. So this plan this thing is just getting more complex, and then they're putting it in a present wrapping room. They're tearing out a present wrapping room. Everyone is remodeling this property.
Speaker 1:And and they're and they're no longer going by Spelling Manor, you know, the guy who belted, he put his name on it. They're pulling it off and they're calling it 94594. Five nine four, a restaurant. A reference to its address on Mapleton Drive.
Speaker 3:Very nice. Well, I have a post Please. To cap off the week. It is in the timeline It's done. From Lulu Maservi.
Speaker 1:Okay.
Speaker 3:So we've been, I guess, brief mentioning over the last few weeks that it feels like we've maybe reached a local top on on startup launch videos. Yep. A lot of them are starting to look the same. Yep. They're sort of the default now.
Speaker 3:It's very hard to stand out. Yep. People I think are starting to glaze over them
Speaker 1:Yep.
Speaker 3:A little bit. But Lulu has potentially a new meta. So let's pull this up. She says, who's gonna be the first startup to do this format as a launch video? And it's the I would go out and bet that it's Cluelie.
Speaker 1:Of course. I bet
Speaker 3:they're already working on it.
Speaker 1:They're probably working on So not a that they don't like.
Speaker 3:The challenge is some startup might might
Speaker 1:Oh, This is so much I guess the people in the in the back are just kind of dancing up and down. They're not really Yeah.
Speaker 3:So the challenge is if you're launching your startup Monday Yep. You could be spending all weekend doing this, getting it ready, and then Roy Lee and the team will launch it, like Sunday Probably. All day. Probably. So good luck out there if you're trying
Speaker 1:You to know, speaking of speaking of Cluelly, obviously they still have to do so much on the product side to really, you know, nail it, get retention, all this other stuff. But in terms of just the cheating as a keyword, I think that there's something that's gonna be very very sticky there. Julia Steinberg has been on the show is posting a picture of a billboard says, hi. My name is Roy. I got kicked out of school for cheating.
Speaker 1:Buy my cheating tool, clearly.com. And I just feel like it's such a simple encapsulation of the value prop just in one word that grabs your attention. I was thinking it's kinda like Red Bull gives you wings. It's not Red Bull doesn't actually give you wings. It's just
Speaker 3:Speak for yourself, John.
Speaker 1:Yeah. And then then you've you've grown wings. You've grown literal wings, you know? But but it sticks in your mind. It grabs you.
Speaker 1:And I feel like the even though the Cluelly stunts are kind of getting like less and less it's it's less shocking because it's like, oh, okay. We we we kind of come to expect that Cluelly is going to do a sorority dancing video for example. Just just the the the cheating as a as a keyword, if they can own that in in the broad consciousness, I think it's going to continue to pay dividends and grab people's attention and just be something that they can run with for a long time because like even though the Cluely stuff went super viral, everyone in tech talked about it, everyone in tech was arguing about it for a long time. There's still hundreds of millions of Americans that have never heard of Cluely or maybe they saw it once and forgot about it. And just and I think that that is gonna be like a a keyword marketing campaign that just like keeps keeps sticking in people's mind and and it will Yeah.
Speaker 1:They saturate it as viral.
Speaker 3:And the timeline and they have to figure out how to go mainstream.
Speaker 1:But like, it's it's it's such a distillation. It's such a compression of a meme of an idea of like, oh, I would like to like cheat on that, you know, report that I've been working on at work and actually, my boss doesn't care if I cheat. They don't care if I hear They care about the result. And so but it grabs your attention. And so, like, I could see it I could see it running in a Super Bowl ad and actually driving conversions and downloads.
Speaker 1:Now, the product has to be really great. It has to be better than ChatGPT. That's an extremely tall order. They're going up against Gemini, which will help you cheat quote unquote. I'm using cheat in the just AI assistant language, not actually literally cheat.
Speaker 1:But Yeah. And and they're going up against free models and cutting edge models and all sorts of different things. And we'll see how sticky that new that their UI implementation is where it screen scrapes and and and records your calls. But in general, I think just as a marketing technique, like I don't think we've seen the end of cheating as a buzzword that clearly will be reaping the benefit of
Speaker 3:of Totally.
Speaker 1:Cheat code. Anything else in the timeline, Tyler? Any is the timeline in turmoil or is the timeline quiet?
Speaker 4:Timeless is
Speaker 1:ready to the Western Front.
Speaker 4:There's one thing. So some small updates for GPT five from from Sam Altman. He says they're doubling rate limits for plus users.
Speaker 1:You do the Sam Altman voice?
Speaker 4:What is this, Sam?
Speaker 1:They're doubling. We're doubling rate limits.
Speaker 7:We're gonna let plus users continue to use four o.
Speaker 1:There we go. That's good. That's how that's how I imagine.
Speaker 3:Oh, yeah.
Speaker 4:They're bringing four o back.
Speaker 1:Wow. Okay.
Speaker 4:And the the auto switcher was broken yesterday.
Speaker 1:Oh, interesting.
Speaker 4:So he says Mhmm. It will seem smarter today. Yeah. The result, it was out of commission for a chunk of the day and it will
Speaker 1:It's kind of hilarious that they had like, you know, a pretty big launch. There's like two bugs like one with the chart clearly got misrendered for the livestream was fine on the blog post. Everyone's like, chart crimes. This is the all that. And then the model switchers broken and people are like, this is the it's not as a work at all.
Speaker 4:But I'm thinking
Speaker 1:Think we're I think we're back. I think we're back.
Speaker 3:AJ is back,
Speaker 1:heard it. We've heard it. You heard it. We are back. Accelerate your timelines.
Speaker 1:You now have two days to escape the permanent underclass. So have a great weekend everyone. Get to work.
Speaker 3:Full days.
Speaker 1:Two full days. I I will be, you know, I think I think most people at summer, you should escape the permanent underclass this weekend by hitting the pool, hit the beach, have some fun out there.
Speaker 3:Get a ramp floaty.
Speaker 1:Get a ramp floaty and and spend a weekend on it. Enjoy. Have a great weekend everyone. We will see you Monday. We love you.
Speaker 1:Leave us five stars on Apple Podcasts and Spotify. And thank you for watching.
Speaker 3:Cheers.
Speaker 1:You later. Goodbye.