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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. Microsoft's blockbuster earnings last week, they blew out earnings. It was very exciting. They cemented its status as one of the biggest winners in the artificial intelligence boom. We knew this.
Speaker 1:Satya had carved out just a massive amount of territory. GitHub Co Pilot, first real major breakthrough product that was monetizing on top of g t p GPT 3.5. Great product, obviously, led by Nat Friedman when he was there.
Speaker 2:Last we heard, it was at around half a billion in ARR,
Speaker 1:something like that,
Speaker 2:two months ago. So it's probably in the billions now.
Speaker 1:Yeah. Probably bigger. And then the crazy OpenAI deal, they got in very early. They they have this massive revenue share. They have an ownership.
Speaker 1:They get a copy of any software that OpenAI writes basically or acquires. That's kind of crazy. And so
Speaker 2:Satya did seemingly one of the best deals of all time for
Speaker 1:Microsoft. Potentially. Yeah. Yeah. I think so.
Speaker 1:It's hard to I mean, it's it's an awkward situation now and it's a really hard decision.
Speaker 2:Sam is renegotiating the deal.
Speaker 1:Yep. And Ben Thompson was noodling on this like, should they take the money now or should they play it more like a venture style bet? What is the role of the CEO of a $4,000,000,000,000 public company where the shareholders have different expectations? They're not seeing if you hold Microsoft stock, you're not feeling like you're an LP in a venture fund. Yeah.
Speaker 1:So if if the CEO comes to you and says, hey, look, we're taking the cash flow now. We're gonna dividend some of this out. We're selling down the position. Yeah. We're we're we're thinking strategically about this as opposed to just we want the highest multiple.
Speaker 1:We wanna ring the gong on the deal. That could be reasonable. So, obviously, we're we're we're tracking where that goes. But they also have Clippy, generational precursor to potentially all the AI agents, the original AI agent, Clippy, potentially making him original come
Speaker 2:super intelligence.
Speaker 1:The original super intelligence. And That was the first time they
Speaker 2:had to move the goalpost.
Speaker 1:Right? And this is why we're worried about getting paper clipped because Klivy will become too strong. I mean, with the power of OpenAI and Microsoft Azure, anything's possible there. So anyway, outside the AI race, Microsoft is minting money from corporate customers spending on regular technology, long a sweet spot for the company. Many companies are shifting from buying their own IT equipment to renting it from Microsoft through its cloud computing service.
Speaker 1:They are also renting more standard issue computing stuff, hard drives for data storage, for example, to support their AI efforts. And so this is the key, stat from the earnings call that the that the Wall Street Journal is highlighting, and then we'll kinda dig into this number what it means because there's a lot of different explanations for what could what could be going on. But Microsoft and the CFO and CEO didn't necessarily give all the context that we'd like to set this definitively, but I think there's some really good theories floating out there. So the quote from the Wall Street Journal is a large chunk of the recent strong growth in Microsoft's cloud business called Azure stems from that. More than half of Azure's 33% revenue jump in the company's March came from non AI services.
Speaker 1:While the company didn't give a comparable breakdown, a comparable breakdown of
Speaker 3:the cloud unit's 39% growth in its June, it said that the core infrastructure business, Microsoft's lingo for its non AI cloud business, was the
Speaker 2:driver. Jordy? Massive win for enterprise SaaS. Just good old fashioned SaaS. There were some we
Speaker 1:had some theories.
Speaker 2:So we had some some theories. Theories. So
Speaker 3:Yeah.
Speaker 2:So it's people migrating from on on prem to
Speaker 1:It's what's called infrastructure as a service. Yeah. So there's software as a service. That's when you go and get teams or you go and get a subscription to Excel in the cloud or Outlook in the cloud.
Speaker 2:That's software service. More was more traditionally someone else building. Yes.
Speaker 1:Yes. Using using it as infrastructure as a service. Then there's also platform as a service. That's like Heroku on AWS where you go and you deploy an app. You could think of maybe even like a replet as like a platform as a service almost where they're hosting you but they're not just providing you the raw infrastructure.
Speaker 1:Azure's core infrastructure business is essentially infrastructure as a service, IAAS is the term. Yeah. And that means, oh, you want some CPUs and some hard drives and some Ethernet cables and moving stuff Interesting around data
Speaker 2:thesis offline earlier. Yes. You comped it to people in the Internet era buying a compute. They hear about the internet. They're like, hey, I think this might be a thing.
Speaker 2:I should get a computer. Yes. And they just buy a computer. And now, you could see something, you know, where companies say, hey, this AI thing might be big. We should get on the cloud.
Speaker 1:Yeah. Yeah. You wanna set yourself up for it. And I think if you have a whole bunch of data in some sort of on prem, you know, you have a data center for all of your data in a bunch of hard drives, and you have CPUs that can do the do different workloads and data workloads. And maybe you're using some SaaS on top
Speaker 3:of
Speaker 1:that, but you realize that you're never gonna be in a position to buy a 100,000 h 1 hundreds, and you're going to wind up being a leaser of that for some small
Speaker 2:fine tuning other people's application layer products.
Speaker 1:Yeah. So the integration that comes from being in the Azure ecosystem, that could be a driver. There's a few others. When I think about the the core, the the AI Azure services, I think of that almost as, you know, it is SaaS. Like, if they're they're if you go to Azure and you say, I'd like to, you know, put my credit card down and I want to be able to use the GPT four API.
Speaker 1:I also want to be able to use Lama three. And I also want to be be able to use DeepSeek. And I want to be able to call all these APIs within my within my product. I almost think of that as tokens as a service. Like, is SaaS, but it's something else.
Speaker 1:And I think these token factories, I think this idea of how much revenue are you generating from your token generation business is really what we're talking about when we when we talk about Azure's, you know, core AI products Yeah. Versus the infrastructure. But there's a bunch of interesting wrinkles that could be going on within the classic, you know, core infrastructure business. So this is, of course, is virtual machines. You just want a Linux box with a CPU to host a website.
Speaker 1:That's something that you do on Azure. Storage, networking. Okay. I wanna store all my data. You could go to AWS and store it in s three.
Speaker 1:You could go to Google or store it in BigQuery. You could also go to Azure and fire up any sort of storage database Yeah. Or just, you know, raw raw hard drives, and then networking moving stuff around. So this is the infrastructure as a service versus tokens as a service. They're higher level AI APIs.
Speaker 1:But so GPUs are so the question is like, why is their infrastructure as a service growing faster than their tokens as a service product? You would think that Microsoft is going to their enterprise clients and saying like, you need to build AI. You need to bring AI into your products and we have all the best APIs, so just buy tokens from us. And you would think that that would be the boom.
Speaker 2:Well, couldn't the other factor here be that they are massively supply constrained on the GPU side? Yep. They have this, you know, multi Yes. Tens of billions or hundreds of billions of dollars of backlog Yep. That they can't fulfill?
Speaker 2:Yep. Meanwhile, they had a, you know, more kind of like predictability on the traditional data center cloud side that they were able to scale up to. Yep. So that feels like a potentially like a pretty big driver here.
Speaker 1:Yes. Definitely.
Speaker 2:But still shocking.
Speaker 1:And so and so as companies come out and they say, okay, we are we are scaling our our, you know, hardware and software foot our technology footprint broadly going into this AI era. We're excited about this stuff. Well, we're also gonna need more databases. We're gonna need to put more data in those databases. We're gonna need more CPU workloads.
Speaker 1:We're gonna need more of everything. And Microsoft's like, yeah. Of course. We can definitely get you a whole bunch more hard drives and a whole bunch more CPUs. We're not constrained on that at all.
Speaker 1:And the CapEx is keeping up, they're able to service that. There's also an interesting thing where tons of AI stuff can technically be happening inside the core infrastructure bucket. You just don't necessarily know what what's in there. So some examples are like, if you're let's say you're a pure AI company or you're doing or you have a new AI workload, you could go to Azure and say, hey. I'm gonna do a whole bunch I'm gonna do my own AI thing, but I need a ton of storage for data because I'm gonna be training on it.
Speaker 1:I'm gonna need a bunch of networking to move that data around when I do a training run. So that could be driving core infra up. And then also, if a bank hypothetically spins up a huge cluster of h 100 GPU virtual machines to fine tune an open source model like Meta's Llama three, this would show up as core infrastructure, not Azure AI services. And so that's like textbook AI boom, but it's just happening in the in the wrong bucket. And then I also saw a post that potentially ChatGPT counts as Azure core infrastructure because they're not they're not serving ChatGPT through the Azure AI API.
Speaker 1:It's not this like snake eating its tail or a boros. Like OpenAI just came into give us a whole bunch headline
Speaker 2:itself ends up becoming pretty misleading.
Speaker 1:Exactly.
Speaker 2:Because, and again, this was probably, you know, a lot of people were reading into AWS's growth, the reports that Andy or the comments Andy had given on AWS last week. Yep. And the big thing that AWS is missing is having a chat GBT building on top of Yeah. AWS.
Speaker 1:Right? There's
Speaker 2:no dominant consumer product at least at that scale. ChatGPT, think the as of this morning, somebody was estimating getting to a billion weekly actives this year which again, those types of products don't, you know, the the power law is like extreme.
Speaker 3:Right?
Speaker 2:Yeah.
Speaker 1:Yeah. So if you I I mean, I I believe Anthropic is pretty tightly hitched to Amazon and I think the next big cluster from Anthropic will be powered by Amazon for the most part. So they're getting there certainly on the if they're building all the all the infrastructure
Speaker 3:for cloud.
Speaker 2:But again, that would show up on on Core. Token generation side? Like, more of the the the
Speaker 1:No. No. So, if Anthropic goes to AWS and says, we want you to build a huge data center to serve cloud code for us. Okay. That's going on that's going on in infrastructure.
Speaker 2:Yeah. Got it.
Speaker 1:Not actually APIs. But when you go to AWS and you're just some random company and you say, I need a database and I need some storage and I need a web server and I also need a bunch of tokens from whatever model you can serve me. And they're like, we got Claude. And then you're like, yeah. Let's pull the Claude tokens into my app.
Speaker 2:It's a
Speaker 3:good model.
Speaker 1:That's token as a service. What?
Speaker 2:It's a good model, sir.
Speaker 1:It's a good model, Exactly.
Speaker 2:One thing that stood out to me that has stood out to me across this year with Microsoft is they've done more layoffs this year than the past three years before that combined. So 2022, 2023 and 2024.
Speaker 1:That's crazy.
Speaker 2:And so this just shows the level that Satya is operating at is like the the company has been on a tear this year, you know, performing exceptionally well and he's still thinking about how do we get more and more fit. And Yeah. So
Speaker 1:So to be clear, literally every piece of Microsoft business is growing and at a very a very solid clip. So Microsoft three sixty five commercial cloud business, which houses remotely accessed versions of Word, Excel, other productivity software, That grew at 16% from a year earlier. So that's, I mean, that's like it's not the most insane growth rate, but that's still crazy because you think about like
Speaker 2:Yeah.
Speaker 1:Who doesn't have Excel that needs it? Like, who who are these people who are like, you know what? 2025 is the year that my company is getting on Excel. We're doing it.
Speaker 2:Well, it's just crazy when you compare it to AWS growing at 19%. Yeah. Obviously, very different scales.
Speaker 1:Yeah. Totally.
Speaker 2:You would think you don't wanna be in the same ballpark as Yeah.
Speaker 1:And so that was the news of AWS if you missed it. They beat earnings. They did very well. But they weren't growing as fast as the others, the other cloud platforms, Google and Microsoft. And so this the Amazon stock traded down.
Speaker 1:And, I mean, the the narrative around AWS is different because Microsoft has OpenAI, Microsoft Research, and has GitHub Copilot, and he's, like, really moving things forward in the AI world. And Satya is seen as someone who goes on the DoorDash podcast and talks about AI, and it's clearly, like, really on top of it where and and, obviously, Google has Gemini and a million different products and and and strategies around rolling that out and staying on the frontier. I mean, they have a frontier lab internally. And Amazon's just not there either on the partnership side or on the core, like, training frontier lab side. And so it's a little bit it's a little bit of both.
Speaker 1:Anyway, let me tell you about Figma. Think bigger, build faster. Figma helps design and development teams build great products together. We had a great week in New York celebrating Figma and the IPO. Stock's been up.
Speaker 1:Stock's been down. Wild ride. But we are still very happy to be partnered with Dylan Field and the Figma team. And I'm It
Speaker 2:was truly
Speaker 1:super excited to see what happens next because Truly,
Speaker 2:it was Thursday was such such an incredible day. Just getting the if you didn't get a chance to listen, we talked with every the seed, lead investor all the way through of course Andrew Reed who led the C. Yep. And then capped it off with Dylan and also got to speak with Lynn Martin, President of the New York Stock Exchange as well as Chris, the CTO of Figma. So really incredible day and it's just very proud of the Figma team.
Speaker 1:Yeah. It was awesome. In one sense, investors might prefer to see AI businesses driving growth. That, after all, is what has driven the company's valuation through the roof. But tech companies' stocks arguably hinge on too much on AI to the extent that they can keep increasing other revenue streams.
Speaker 1:They are on more solid financial ground. Of course, none of that means anything if all of the growth is coming from OpenAI. But at the same time, does anyone really think ChatGPT is, is Yahoo anymore? Like, do like, you know, they're they're generating what? A billion dollars a month in revenue at this point.
Speaker 1:Everyone uses the app. It's installed everywhere. Like, that that that token demand is not going anywhere. That infrastructure demand is not going anywhere. So
Speaker 2:On the other side, Amazon is down just over 9% since Thursday.
Speaker 1:Since Thursday. In earnings.
Speaker 2:Wow. And then this morning, unrelated, they announced that they're shutting down Wondery, the podcast studio. Really? They acquired in late twenty twenty. Amazon.
Speaker 1:Did and the market's way up. Wow. Nasdaq's up 1.8% today after a brief sell off on Friday. That's right. Good news.
Speaker 2:Bear market is over.
Speaker 1:Yeah. We were so over but we're already so back. Fantastic.
Speaker 2:Love when it happens.
Speaker 1:Markets go up. Markets do go down. But the march of technological progress, the arrow points in but one direction.
Speaker 2:That's right.
Speaker 1:And its march is relentless. There is another silver lining for Microsoft. Non AI sales can be substantially more lucrative than AI ones. Non AI gross margins within Azure were around 73%. Wow.
Speaker 1:That compares to that that compares to 30 to 40% gross margin for AI. He estimated because of the huge cost of setting up AI infrastructure that makes sense, you get more margin on just a bunch of CPUs and databases that you've harnessed and built everything around. Also, you know, you still have that interesting dynamic where it seems like all of the cloud, the hyperscalers, like, don't really compete on price because they're all pretty comparable, but they seem to
Speaker 2:all have good quality dynamic.
Speaker 1:That's what it seems like.
Speaker 4:Yeah.
Speaker 1:I'm not exactly sure if there's something else that's more fundamental going on.
Speaker 2:And the Coca Cola dynamic is like, I don't know if we, it's hard to tell what conversations were off air or on air but John last week, forget when, was describing how you would think that Coca Cola or Pepsi would decide to get aggressive on price to gain market share and get people to switch. But ultimately, that would just lead to a price war with both companies, you know, massively eroding their their, you know Margins. Margins and then
Speaker 1:Did all the RC Cola coded then?
Speaker 2:Yeah.
Speaker 1:So every, yeah, every if
Speaker 2:you have a fierce competitor, consider entering an unspoken gentleman's
Speaker 1:That's the beauty.
Speaker 2:Maybe a gentleman's agreement.
Speaker 1:It's it's not even a gentleman's agreement. It's not it it is unspoken, but it is It's good business. Nature it it is a natural game theoretic Nash equilibrium. Like, it is the natural state of things that both sides understand that to go to war would be mutually assured destruction. And so they don't even need to talk about it.
Speaker 1:And so instead, they both agree to keep prices where they are and instead compete on marketing. Compete on marketing. Yeah. Yeah. I mean, they don't form they don't reformulate that often.
Speaker 1:They mostly compete on marketing and that allows them to have this like continually compounding business. And that's why it's in the Warren Buffett portfolio. Coca Cola. He's been in there for a long time. And Pepsi's been doing well.
Speaker 2:And he was a DAU, of course.
Speaker 1:He was a DAU of Coke. Still. Diet Coke
Speaker 2:or Coca Diet Coke.
Speaker 1:I think Coca Cola?
Speaker 2:No. Diet Coke.
Speaker 1:Oh, he's a Diet Coke guy? I feel like he was a Coca Cola guy.
Speaker 2:Warren?
Speaker 1:Yeah. Look that up. I wanna know. Anyway, I'll keep reading from this Wall Street Journal report. Luckily for, Microsoft demand for lucrative non AI services appears to be reasonably strong.
Speaker 1:Measures of broad IT Right. There we go. You know why?
Speaker 2:A regular Coca Cola guy.
Speaker 1:You know why? It's because it has corn syrup in it. It's literally corn grown from mother nature, from the earth. And then syrup, it's what you put on pancakes. Like, it's the most wholesome combination of of foods you could imagine.
Speaker 1:Maize, this is something that's been grown in America for generations,
Speaker 2:for Corn is so popular in Nebraska, right? It's grown everywhere. Exactly. It's
Speaker 1:culturally And the syrup that you put on pancakes, it it's it's the most American, most wholesome ingredients. Not this, like, refined sugar, this crazy stuff from somewhere else. No. It's American.
Speaker 2:American corn syrup.
Speaker 1:It's nothing it's Lindy corn syrup. Corn syrup. Yeah.
Speaker 2:See all See you all haters are are in disbelief.
Speaker 1:The shambles that that we need to return to corn syrup. None of this none of whatever's in this Coke Zero.
Speaker 2:Yeah. Your grandpa was was drinking corn syrup.
Speaker 1:Yeah. Oh, it's too good for you? Because you read a couple posts on axe.com. Think you understand something better than corn? Delicious corn, corn on the cob.
Speaker 1:Something you have on a at a barbecue? Oh, now it's too good for you? Can't possibly have corn? What's next? No apple pie?
Speaker 1:What's next? No rotisserie chicken?
Speaker 2:Somebody is gonna listen to the show for the first time today and and just go raging demands for you promoting corn syrup consumption.
Speaker 1:It's as American as apple pie. And Warren Buffett knows best. He's doing great. And of one study sort of a Brian Johnson. Yeah.
Speaker 1:He's sort of the Brian Johnson
Speaker 2:He's the original don't die.
Speaker 1:Yeah. And he's been doing fantastically on that front.
Speaker 2:Yep.
Speaker 1:He's great. Anyway, measures abroad IT spending were fairly muted at the start of the year as companies pondered the impact of Donald Trump's tariffs and concerns bubbled about the health of the global economy. Attitudes appear to have improved somewhat in the second quarter, though a UBS survey of cloud computing customers in July showed a clear improvement in tone about spending. Most were moving forward with efforts to migrate computing work to the cloud. They're like, this Internet thing is real.
Speaker 1:It's real. We gotta put the data in the cloud.
Speaker 2:We held back as long
Speaker 1:as we could. We could. But it's 2025. We have no more excuses. The tariffs, that's come and gone.
Speaker 1:Now is the time.
Speaker 2:We were resisting the twenty first century Yeah. But we're a quarter of the way through
Speaker 1:Put the data online.
Speaker 2:It's not going away.
Speaker 1:So let's let let's use the computer in the online. In in the cloud.
Speaker 2:Put the docs in the cloud, buddy.
Speaker 1:Put it in the cloud.
Speaker 2:Just put the docs in the cloud.
Speaker 1:Put the fries in the bag. Anyway, and put your compliance process on Vanta. Compliance, manage risk, improve trust. Vanta's trust management platform takes the manual work out of your security and compliance process and replaces it with continuous automation whether you're pursuing your first framework or managing a complex program. In the longer term, there is little question that cloud computing is going to grow in ways that play to Microsoft's strengths.
Speaker 1:Its rivals, mainly amazon.com and Google, are growing quickly too, but don't have all of Microsoft's broad corporate software offerings that enhance its cloud footprint even outside of AI. Amazon on Thursday said its cloud unit grew at 17 and a half percent in the June, disappointing investors and forcing CEO Andy Jassy to answer questions to answer questions about Azure's outperformance. Why are getting beaten? You created this category. You created this product.
Speaker 1:Why is Satya Nadella
Speaker 2:You are cloud. You.
Speaker 1:Are the cloud. You are the the cowboy of the cloud. And you're getting you're getting put out to pasture. Recent quarterly earnings in Azure's favor were really just moments in time, he said.
Speaker 2:Chart, John.
Speaker 1:The oh, yeah. Wow. That that's worse than I thought. I wasn't sure where we had that pulled
Speaker 2:up. I mean, it would have been hard to predict five years ago that we'd be sitting here with with Microsoft at 4,000,000,000,000 and and What's Amazon at? I think 2,200,000,000,000.0.
Speaker 1:2.2.
Speaker 2:Two 0.27.
Speaker 1:2.27. Okay. So almost double.
Speaker 2:Still magnificent. But
Speaker 1:Still magnificent. But you gotta keep fighting. Gotta keep fighting. The company's stock fell 8% Friday, and it looks like it's still sliding. Down even more.
Speaker 1:The question for Microsoft's investors then is less about the its prospects than its valuation. The company's stock is up nearly 40% since the April, pushing its forward price earnings multiple above 33. That's a bit richer than Amazon and a large margin above Google, which is trading at a multiple of roughly 18 times. That should be easier for investors to digest because while Microsoft's AI growth is real, it is far from the only thing going right at the software giant because they got Excel. They got core infrastructure.
Speaker 1:They got AI, APIs. They got tokens as a service, infrastructure as a service, and software as a service. They got the royal flush. It's going well over at Microsoft. They won't need to call McKinsey, but maybe maybe amazon.com will.
Speaker 1:My question, is AI a sustaining innovation for Disney, or is it a disruptive innovation? Where will Disney be in ten years in the medium term? Obviously, you're gonna be able to generate a lot of AI slop. You might be able to infringe on their a on their IP. They might get paid by Google VO when you generate a Mickey Mouse AI slop edit.
Speaker 1:They might get a little a couple pennies. But really good or bad for them?
Speaker 2:Children's, you know, I could see them making a product that allows you to make a, you know, book or a story for your kid that actually, you know, and they get they get some type of revenue.
Speaker 1:They should get revenue. And I think that they will through the courts especially because as, like, big companies, like, you're not it it it's not this crazy, oh, there's, a bunch of kids doing random things. Like, they never had to go after the the street artist on Venice Beach that would draw a picture of Mickey Mouse and sell it to for you $20. They that was never material to their business. They had to go after Napster.
Speaker 3:They had to go after Spotify.
Speaker 2:Venice Beach. Yes. I got them to draw me as Mickey Mouse. Really? And then I performed a citizen's arrest because I respect IP.
Speaker 2:I have an IP respecter.
Speaker 1:Yes. Yes. Yes. Citizens arrest is underrated. Citizens arrest.
Speaker 1:Citizens arrest. You're going to This jail,
Speaker 2:is for Bob.
Speaker 1:This is for Bob Iger. Yeah. So big question. This feels like a moment where you wanna be in founder mode. Bob Iger is one of the greatest CEOs of all time.
Speaker 1:How will he navigate this? The Wall Street Journal says
Speaker 2:Hey, but not
Speaker 1:is it still Not. He's not the founder. The founder died in 1966. Walt
Speaker 2:Disney But he's claiming
Speaker 1:that he
Speaker 2:died still.
Speaker 1:He might be able to turn it on. Satya Nadella certainly was able to do He's in he's navigating the AI the AI shift flawlessly. We'll see what happens with Bob Iger and Disney. Wall Street Journal says, is it still Disney magic if it's AI? The stakes are especially high for the studio caught between how to use artificial intelligence in the filmmaking process and how to protect its famed characters against it.
Speaker 1:So there's a little anecdote that we'll kick it off with. When Disney began working on its new live action version of its hit cartoon Moana, executives started to ponder whether they should clone its star, Dwayne Johnson. The actor was reprising his role in the movie as Maui, a barrel chested demigod. Have you seen Moana? No.
Speaker 1:You have not. Of course, we know this. For certain days on set, Disney had a plan in place that wouldn't require Johnson to be there at all under the plan they devised. Johnson's similarly buff cousin, Tanoa Reed, who is six foot three two hundred fifty pounds, would fill in his body double for a small number of shots. Disney would work with AI company Metaphysic to create deep fakes of Johnson's face that would be layered on top of Reed's performance in the footage of digital twin essentially.
Speaker 1:Digital double that effectively allowed Johnson to be in two places at once. Obviously, that's better
Speaker 2:since Calls up his cousin. You want a job?
Speaker 1:Need you to Yeah. Be Hit the gym, buddy. Yeah. Better be better be jazzed.
Speaker 2:Get on a cycle.
Speaker 1:But, yeah, I mean, these these, these movie schedules are famously tight, three months in and out crazy schedules. And then you move on to the next one. There's that famous Henry Cavill story where he filmed Superman, wrapped, moved on to another movie where he had to grow out a mustache. He grew out a mustache and a beard, and then they said, hey. We gotta do some reshoots.
Speaker 1:You gotta come back to Superman. And he came back, but he couldn't shave his mustache and beard, they had to change it in in CGI, and it looked terrible. Probably not a problem now with with deepfakes. That's actually a good use of AI and something that probably shouldn't be very controversial, but, obviously, everything in AI is controversial right now. But we will continue with Disney.
Speaker 1:They say, what happened next was evidence that Hollywood's must discuss much discussed, much feared AI revolution won't be an overnight robot takeover. Johnson approved the plan, but the use of a new technology had Disney attorneys hammering out details over how it could be deployed, what security precautions would protect the data, and a host of other concerns. They worried that the studio ultimately couldn't claim ownership every, that the studio couldn't ultimately claim ownership over every element in the film if AI generated parts were in there. So if there's AI training data from a DreamWorks film in there and they use the DreamWorks training data to make a Disney film even if it looks like Dwayne the Rock Johnson, DreamWorks might come knocking and say, hey. Give us a royalty.
Speaker 1:I think that's the risk. But the lawyers are having fun maybe. Full employment for lawyers over at Disney, clearly. Disney and Metaphysics spent eighteen months negotiating on and off over the terms of the contract to work on the digital double, but none of the footage will be in the final film when it's released next summer. They went and shot it.
Speaker 1:A deep fake Dwayne Johnson is just one part of a broader technological earthquake hitting Hollywood. Studios are scrambling to figure out how simultaneously they can use AI in the filmmaking process and how to protect themselves against it. Is it sustaining or disruptive or both? Can't be both, but we'll see. While executives see a future where the technology shaves tens of millions of dollars off a movie's budget, they are grappling with a present with a present present filled with legal uncertainty, fan backlash, and a wariness toward embracing tools that some in Silicon Valley view as their next century replacement.
Speaker 1:And if you are trying to sell an AI tool into Hollywood, you gotta get on Adio customer relationship magic. Adio is the AI native CRM that builds, scales, and grows your company to the next level, and you can get started for free. So the Academy of Motion Picture Arts and Sciences is surveying members on how they use the technology. Studio chiefs are shutting down efforts to experiment for fear of angering show business unions on the eve of another contract negotiation. And no studio stands to gain or lose more in the outcome than Disney, the home of Donald Duck, Bell, Buzz Lightyear, Stitch, and countless others, which has churned out some of the most valuable and protected creative works in over the past century.
Speaker 1:So my take on this. Two so two years ago, I was hanging out with the founder of a very large generative AI image generation company. And he was telling me that by 2025, anyone with a laptop and an Internet connection could generate a full Hollywood movie about anything they want with a single prompt. And it was a hilarious conversation because we were on a Zoom call and his Internet wasn't working. And it was the classic example of, like, the technology is amazing, but we got a lot of stuff to iron out.
Speaker 1:So anyway, extremely aggressive timeline, but obviously, things are gonna change for Hollywood. So my question is, will Disney benefit? It feels like a moment to be in founder mode, but Walt Disney died in 1966. So, basically, everyone believes that Meta will benefit from AI even if they miss the train on owning the next dominant consumer tech platform. But if Disney got really AI pilled, what would that look like?
Speaker 1:I don't think they need to train their own foundation model just like they don't need to train their own they don't need to build their own cinema cameras. Yep. They can just use IMAX when they the time calls for IMAX. They can use Blender when the time calls for Blender. They can use Houdini when the time calls for when the when when the the shot calls for some, high level VFX.
Speaker 1:Yeah. But they do need to rethink how they structure their business and negotiate with unions and underwrite content. They might need to go more risk on not just from a brand risk position, but taking more smaller bets. We're in this weird barbell world where everything seems like it's either a $100 and it's shot on an iPhone. It's a viral, like, TikTok, or it's a $100,000,000 blockbuster with, like, $50,000,000 of VFX.
Speaker 1:Actually, that's kind of a low number. It's usually, like, $300,000,000 production with a $150,000,000 VFX, and then no one sees it and it's a flop. But then they they hit every once in a while and they're great when they're good. But it's this weird, like, venture style betting at the high end, but there's nothing in the middle. And maybe if that's like the death of the arthouse film.
Speaker 1:But I'm just wondering if in the age of AI, like, maybe there's this interim step where Disney ladders down a little bit and gives, like, 10 filmmakers $10,000,000 each and says, hey. You're still required to deliver Full film. Ninety minute full film, but you're doing it for 10 mil, and it's not quite Blair Witch level production one notch up. You gotta be creative. This is what
Speaker 2:makes people
Speaker 1:forward to
Speaker 2:doing. Yeah. I'm really bullish on this idea that the the you know, historically like a TV show would film a pilot episode and they would use that to get the budget to shoot an entire season. And you can imagine now you can, you know, even for film, you can just make, you know, make the trailer ahead of time with AI. The other advantage that I think Disney has that's very real just going in and and why they're just broadly seem to be positioned very well here.
Speaker 2:Is that I think that I think that broadly like content customization will probably take off because you could Disney can make a film now and then you could make millions of different variations of it that become interactive interactive with like the underlying fan. Like imagine you're watching Moana
Speaker 3:Yeah.
Speaker 2:But like your kid is in the film, is a character in the film and you can now do that at scale, right? Yeah. And how much more would you pay as parent to have something like that?
Speaker 1:I have a funny story about this.
Speaker 2:But last thing I'd Yes, sir. So customization and just like democratizing like basically making, being able to make variations films
Speaker 1:Yep.
Speaker 2:I think is gonna be big. I think just the the time, it's the same way you it's it's so difficult to make a new luxury brand.
Speaker 1:Yep.
Speaker 2:It's so difficult to create. It's easy to create IP. It's hard, extremely difficult and time intensive to create valuable IP. And Disney's advantage is they have this sort of like three sixty in that they can make a film and they can bring it to Disneyland, they can bring it to a cruise, they can create physical products around it. And so they develop IP in a way that new entrants are not, you know, they don't have the benefit of like having a Disneyland where they can make new experiences that increase the value of that IP, right?
Speaker 2:I think.
Speaker 1:So two things. One, if I were to go back, one of my favorite Disney properties is Star Wars A New Hope, the very first film. If I went back and was like, let's customize that for me, I don't know that I would make any changes. Like, do I really want a scene where Han Solo breaks the fourth wall and says like, hey, John. Like, I'm about to go, you know, save Luke at the Death Star.
Speaker 1:Like, that doesn't improve the product for me. I actually like that it's just the vision of George Lucas. So I don't know about customization being better for me. I don't know what I would change.
Speaker 2:But here's an example of how to make a magical experience for a kid. Yeah. Like, imagine after a movie ends
Speaker 1:Yep.
Speaker 2:A kid could interact with a character and ask it questions in real time like about about the story or That's cool. Have a conversation with them and that's what I'm talking about, like bringing that IP to life.
Speaker 1:Totally. Right now, that exists. And I was obsessed with this when I was a kid. I would I would, I would watch Star Wars, and then I would read the the the books that in the expanded universe. And I remember even having books that were just like encyclopedias of every single ship.
Speaker 1:This, you could read into this a little bit more, but, we'll leave that where it is. But I but I would learn every single every single ship. This is what a star destroyer does and it would have all this backlog and stuff. And so, yes, I agree with you. That's very cool.
Speaker 1:You finish the movie and then you can just interview Luke about how does how does the lightsaber actually work? And he can talk about the kyber crystals. That would be very cool. On the flip side, I had a very funny experience. I was watching a horror film in high school with a couple friends and I grew up in Pasadena.
Speaker 1:And this horror film just happened to take place in Pasadena. Like, that's where they set the film because Pasadena, California is just like a place where you set films. It's just a real place. So if you've seen Kill Bill, which I know you haven't, but Kill Bill by Quentin Tarantino, there's a scene where where Uma Thurman just shows up and it says at the bottom Pasadena, California because like that's where the character went. It exists in the real world.
Speaker 1:But this horror film that took place in Pasadena was terrifying because I was watching it and I was like, this is happening here and it's night and it's dark outside. And, like, I now I'm so much more immersed. And so I was thinking back then that you could use, like, the IP address of the of a of a connected I think we were watching it on, like, a PS three, like a DVD player. Like, you could you could use the DVD player to dynamically change the location of this of the establishing shot. So you're like, this whole horror film is gonna take him take place inside of like one house where there's like a monster in the house and it's gonna be like the usual like, they're upstairs, they're downstairs, there's blood, there's, you know, someone's running and chasing.
Speaker 1:Like, it could be any town USA, but they usually they usually establishes like this is happening in Amityville. This is happening in you know, some random town Lake Placid. Right? But they could easily just dynamically change that with a few establishing shots to just show you, okay. It's happening in Malibu.
Speaker 1:Right? And now, it's a lot scarier for you. So I think there's something interesting there but again, it has to be the work of like an
Speaker 2:on It's Yeah. It's not something you can copy and paste either because Yeah. It works for some shows Yeah. But then others like the place is so obviously the place Totally. That it would throw you off as a viewer.
Speaker 2:Exactly.
Speaker 1:And so, I do think that the that the fully AI generated, custom content, that will exist, but it will exist on independent third party platforms. It won't be the domain of Disney. The the this will be something where if you in the future, if you really wanna see like, you know, AI generated stories about surfing in Malibu, like, there will be an endless stream of those and you will be able to go and and and experience that particular content. And you can already kind of experience that because there's probably some Instagram person who makes really great content about surfing in Malibu. And if you follow them, you get that vibe and that might be what you're into.
Speaker 1:And you can kind of like and and it's handled just by the great democratization of creativity.
Speaker 2:Yeah.
Speaker 1:And we should talk to Sameer about this later. He's coming on the show. So we can talk about the future of of of content creation and whatnot. On the question of should Apple make a huge acquisition, Tim Cook actually addressed it in the earnings call. He said something like, we've acquired around seven companies this year, and that's companies from all walks of life, not all AI oriented.
Speaker 1:We're very open to m and a that accelerates our road map. We're not stuck on a certain size of company, although the ones that we've acquired, thus far this year are small in nature. He said, like, we're acquiring one every few weeks, which is not quite seven per year. I mean, I guess that's, like, one a month, but a few weeks, sure. So he's doing deals, but he's not looking at anything massive.
Speaker 1:And I think that actually makes sense. My question was, if you were the CEO of Apple and you had a $100,000,000,000 burning a hole in your pocket, what are the other things that you could do with that money? Formula one team. You could buy every team and the division and every track and the all the sponsorships.
Speaker 2:I made a post about this jokingly.
Speaker 1:It's crazy. It's so much money. It's so much money.
Speaker 2:I made a post about this jokingly earlier this year. I still think it'd be cool for Apple to be an f one in the way that Red Bull is
Speaker 1:I think that'd be great.
Speaker 2:The team.
Speaker 1:No. No. I agree. Yeah. I think that'd be great.
Speaker 1:One thing culturally is like Apple's brand is is very premium and very high end. And
Speaker 2:I don't know if they could handle a few
Speaker 1:losing This was the early bear case for Apple TV. I was talking to someone, a very successful Hollywood producer, and he was saying that the nature of the of Hollywood is like venture capital. Like, it is a Hootz driven business. If you don't accept that you're gonna have massive flops and egg on your face and embarrassing moments, you will not make it. And just like any venture capitalist who is like, I only want to make investments where they won't blow up, you're not gonna make it.
Speaker 1:Right? Like
Speaker 2:Yeah. Mark Andreessen had a had a there was a clip from a episode he did recently talking about how he lose sleep over the companies you don't invest
Speaker 1:in Exactly.
Speaker 2:Not the ones you invest in and don't work.
Speaker 1:Exactly. Exactly. And so so you have to be risk on. You have to be risk on in Hollywood as you do in venture. And so the the question was, like, can Apple deal with spending 50 or a $100,000,000 on some show that completely flops and everyone's like, this is a disaster.
Speaker 1:And they've navigated really well. I think that they have had some flops, but they've kind of tucked those behind the scenes. Whereas Netflix has started to get more kind of you know, people talk trash about what was that red red notice or they they did some massive movie with The Rock that kind of flopped. They've done a few of these big movies that haven't done that well. And and it's sort of like, oh, like, you know, they're they're they're not, you know, God's gift to, you know, producing.
Speaker 2:Yeah. But it
Speaker 1:doesn't matter because overall Netflix is doing very well, and all it takes is, like, one squid game to like carry the whole quarter basically. Just like in venture. Or like one, you know, you sign the Friends deal and then or The Office and people are watching that like twenty years later. Yeah. So
Speaker 2:And Yeah. Apparently, so f one has surpassed half a billion dollars in box office earnings as of last week.
Speaker 1:I mean, it's a fantastic
Speaker 2:example of a of a home run. But it's not like they're doing that once a quarter by any means.
Speaker 1:Oh, and John Exley's in the chat. Shout out to John Exley. Unfortunately, I didn't get a chance to connect with him at our party in New York, but he did attend. You got to chat with him. A lot of the team got to chat with him.
Speaker 1:So thank you for all you do, John. We really appreciate you. The entire team is giving you a round of applause.
Speaker 2:General. Because General of the chat.
Speaker 1:You've done a ton of ton of work for us and we really appreciate it. Anyway, if you had a $100,000,000,000 burning your burning burning a hole in your pocket at Apple, what would you do? I have a bunch of crazy ideas.
Speaker 2:Go through your list.
Speaker 1:So most people would just say, hey, you're gonna benefit from AI because you are the window into all technology and it doesn't matter if it's if it's generative video or or text. Like, people will be consuming it on devices. You sell devices. You'll be fine. Just like search did not destroy Apple.
Speaker 1:It actually made Apple stronger because people search on their iPhones. So most people would just say, hey. Return it to the shareholders. Apple's already done that. They've returned over a trillion dollars to shareholders in the past ten years.
Speaker 1:Those are kind of rough numbers, but it's basically that, which is an insane amount of money to return to shareholders. But Samsung is worth 330,000,000,000. They could buy the entire company, lever it up with two thirds debt, and, they would just own both sides of the smartphone market then. Probably extremely anticompetitive. I think Lena Khan would have a conniption fit, but funny concept.
Speaker 1:Funny concept. The other the other the other idea is massively expand the retail footprint. So Apple right now I was surprised by this. How many retail stores do you think they they have worldwide?
Speaker 2:I don't know. Like, 599 or 601?
Speaker 1:Did you look did I tell
Speaker 5:you that
Speaker 1:we were talking about this morning? It's five hundred and thirty five. So it's not that many. It's mostly in the tier one cities. There's usually only, like, one in every city.
Speaker 1:They don't really they don't take the Starbucks strategy where they put them across the street from each other. Yeah. But for a $100,000,000,000, they absolutely could. A $100,000,000,000 is enough to open 6,000 new Apple stores. So they would be 6,600.
Speaker 1:So they would be up around 7,000 stores, which for reference is as many Subways as there are and as many CDSs as they are and as many seven Elevens as there are in America. And so everywhere you see a subway, you can see an Apple store. And I feel like this would be a big upgrade for America. I feel like if you just walked around every American city where tier one, tier two, tier three city, you just see a beautiful sheet of glass, and it's an Apple store on every corner in America. That's They
Speaker 2:could also acquire every firearms, store in the country and turn them into Apple stores.
Speaker 1:They could do a take private of Figma. Think bigger. Build faster. Figma bill helps design and development teams build great products together. Get started for free at figma.
Speaker 2:Buzzing from Thursday.
Speaker 1:It was a fantastic day.
Speaker 2:Love fantastic. Exhausted.
Speaker 1:But we're just tuning
Speaker 2:in. Anybody that is tuning in to the show for the first time today is gonna be hearing our ideas for Apple and just thinking, these are some of the worst ideas I've ever heard. Yeah. But they're definitely fun.
Speaker 1:Okay. So speaking of glass from the Apple stores, they could buy Corning, which makes Gorilla Glass. It's a $55,000,000,000 company. Then with the money left over, they could buy InterDigital, which owns all the patents on five g and six g. So they could basically patent troll everyone else in the industry.
Speaker 2:Just get extremely anticompetitive.
Speaker 1:They could also with the money that is left over, we're still in the first, like, let's vertically integrate this company mode. They could also buy 10 rare earth or cobalt mines. So they own the supply chain there. And then they could also build four battery gigafactories and lock up the sapphire crystal supply chain that's used on the on the the iPhone camera. So they could just completely own their entire supply chain for a 100,000,000,000.
Speaker 1:And and that's just one year. One year. And then they, you know, the proposal was do this every year.
Speaker 2:The other thing that was interesting about Tay Kim's post is if you if you listen to the earnings call, Tim Cook and the team were very clear that they don't even want to finance like data center development themselves. They're still working with these sort of like third party lenders to like capitalize them. And so again, Tim Cook is the king of efficiency.
Speaker 1:Yeah. He knows his business. He's he's
Speaker 3:he's
Speaker 2:he's Should we get into some of that?
Speaker 1:No. I have one more.
Speaker 2:One more.
Speaker 1:So OpenAI, they Aqua hired Johnny Ive. They're coming out with something that's competitive. It's gonna be some some sleepless nights at Apple when that thing drops. Right? It's gonna be stressful because, like, maybe maybe maybe it doesn't go super well, but, like, you know, it's a serious threat.
Speaker 1:OpenAI is a serious company. They have a lot of customers, and they got Johnny Ive, your former GOAT designer ready to drop, you know And bunch of
Speaker 2:former Apple employees. Tons.
Speaker 1:Amazing amazing team over in in hardware at OpenAI. So the question is, like, how do you fire back with your Apple and you have a 100,000,000,000 to spend? Here's what you do. The cogs on an iPhone are less because they have a margin. So you take that $100,000,000,000, you buy 200,000,000 iPhones, and you send a brand new iPhone to 200,000,000 Americans.
Speaker 1:And you're just like, oh, how much are you charging? Johnny Ive and OpenAI? Well, ours is free this year. We're doing a free iPhone for the entire
Speaker 2:year. Should just do something like that where it's like, your eleventh iPhone in a row Is
Speaker 1:free?
Speaker 2:Is free.
Speaker 1:They'd probably have 200,000,000 people with free iPhones. And they're just like, yeah. We're actually we wanna keep you in this ecosystem. We like our services revenue. We're excited to
Speaker 2:be a platform.
Speaker 1:We're excited. We're just giving it back. We're just giving it back. You I think that would also be extremely anticompetitive. I I don't even know if there's a regulatory framework to stop that from happening.
Speaker 1:But, I mean, price competition is a real thing. And, like, if you if you discover that your competitor is undercapitalized and can't can't win a capital war, you could potentially cut cut cut prices so dramatically that it's like, yeah. The the other phone's, like, cool, but, you know, this one's free. I guess I'm gonna stay in the in the blue bubble world.
Speaker 2:Tim Cook next earnings call. Alright. We're gonna buy all of the minds we depend on Yeah. And we're gonna make the iPhone free. Free.
Speaker 2:Stock just eats. Destroys 80%.
Speaker 1:He's like, I'm petty. I'm petty. And you know what, Johnny? You know, I'm not gonna let you win.
Speaker 2:I would rather die than let you win.
Speaker 1:Yeah. I would destroy myself. Yeah. I've been reading a lot about cutting your nose to spite your face. And I'm I'm pretty into that.
Speaker 2:Pretty into the strategy.
Speaker 1:Anyway, let me tell you about Vanta, automate compliance, manage risk, improve trust continuously. Vanta's trust management platform takes the manual work out of your security and compliance process and replaces it with continuous automation whether you're pursuing your first framework or managing a complex Talk
Speaker 2:to the purple llamas. Vanta.com.
Speaker 1:Anyway, Ben Thompson's been noodling on on Apple and AI strategy. He had a rough go because he I think he took some time off or shifted he shifted his posting schedule right when all the earnings dropped and there was all this crazy stuff going on. So he he's just writing about Apple earnings now, but he has he still has some some good takeaway saying, you know, even if they do even if Apple does swoop in and buy Mistral, for example, the overall point holds. Apple isn't going to compete with OpenAI, Anthropic, MetaX, and Google on pursuing AI superintelligence. Like, five extremely well funded, extremely serious teams.
Speaker 1:They're gonna Apple's gonna go their own way, set it on their devices and their direct relationship with their customers, at least as long as Cook is in charge. And anyone that's saying that Cook, needs to step aside, I think, is, is in for a world of hurt because he's been on a generational run, and he's solving the most important problem for that company which is not the application layer in artificial intelligence. It's the supply chain and keeping the keeping the flows flow of iPhones. Making Coming.
Speaker 2:And selling phones.
Speaker 1:Making put the phones in the boxes, Tim. He's doing it. He's doing it. He's really he's really he's really underrated. He's been CEO longer than Steve Jobs was.
Speaker 1:No. I He's
Speaker 3:the hope
Speaker 1:one this tenured CEO of Apple in history.
Speaker 2:He better be bringing some of these AI researcher comp packages in as as comps when he gets in front of the comp committee
Speaker 1:Yeah.
Speaker 2:At Apple. Yeah. Say, hey.
Speaker 1:That that is true. He should definitely be getting a bump. If he does have researchers I mean, he has he has AI researchers. They are improving different functionality. I feel like maybe I'm hallucinating this, but it feels like the text to speech engine has gotten better on my phone.
Speaker 1:I listened to a semi analysis article with the default Apple Safari text to speech, and it was very listenable. So I think we're getting better there. We have some breaking news about SiriusXM. They are canceling the Howard Stern Show. Can you call it a cancellation when the guy's 71 years old, and he's been doing it for twenty years?
Speaker 1:They say it's no longer worth the investment. They've been paying him a $100,000,000 a year. That is a huge salary. And that's, what, three, four times Colbert? Wow.
Speaker 1:That is that's big. That's power power of, of of radio, power of, you know, the power law. He's done fantastically. So congrats to him. He emerged from the for a new gig, you're welcome to come and hang out at the UltraDome.
Speaker 1:Can sit the intern table next to Tyler and we'll bounce ideas off you.
Speaker 2:Yeah. It's wild. I I really wonder where SiriusXM business goes.
Speaker 1:Right? I know I know where this goes. Post AGI, you are gonna listen to every hour every hour of Howard Stern. I know you've listened to zero hours, but there's probably twenty thousand hours in the catalog, something like that, of Howard Stern content. You could listen to it from the beginning.
Speaker 2:Do people listen to the back catalog ever? Absolutely not. But Sirius XM is still a $7,000,000,000 company.
Speaker 1:Wow.
Speaker 2:That's bigger than I would have thought.
Speaker 1:I wonder, yeah, revenue, like how much of that cost. I mean, makes sense to give him a huge slice of that. It is a talent driven business and he could go to Spotify. He could go somewhere else. My question is like, he is old.
Speaker 1:Will he retire or will he do a podcast or do something independent? Is there news?
Speaker 2:No. They What? They apparently did how much?
Speaker 1:Okay. You look that up while I tell you about Wander. Find your happy place. Book a wander with inspiring views, hotel grade amenities, dreamy beds, top tier cleaning, twenty four seven concierge service. It's a vacation home, but better.
Speaker 1:So they did 8,600,000,000
Speaker 2:in 2024 revenue. Yeah. So they're trading at less than one x revenue, which just says when you have a shrinking business Yep. It is a rough place to be.
Speaker 1:Growth not a growth stock, I suppose. Yeah. I wonder how much of that is They're getting getting AI narrative. By talent. Yeah.
Speaker 1:This is
Speaker 2:a trillion dollar stock if they have
Speaker 1:Yeah. I wonder how much I wonder what percent of SiriusXM content is like power loss celebrity host red high salary contract versus essentially programmatic or AI content? Because it's probably not even AI, but if you're just like, there's a there's a station on SiriusXM that's just the Grateful Dead, and it just plays them the whole time. Like, I don't think you need someone making a $100,000,000 to, like, randomly play Grateful Dead tracks. Like, there's probably some Grateful Dead fan who manages that and picks the songs and orders them.
Speaker 1:But, like, that could essentially be pseudo random. Maybe one day you go through the the back catalog and then the new stuff and then you mix it up and then you play the hits or something. I don't even know if they have hits in that way. I know it's kind of a jam band. But I wonder I wonder of their of their, like, of their content, of their tonnage.
Speaker 1:Is that the term? Tonnage is like the the amount of content on the network. I wonder how much of it is is driven by these high high dollar deals. And I wonder if they'll get a new a new host in the seat. I wonder who this generation's Howard Stern is.
Speaker 1:Maybe it's like Tim Dhillon or something, some irreverent comic essentially.
Speaker 2:I think the thing is as content is on demand, fewer and fewer people are just turning on the radio or turning on the television and listening to whatever whatever just happens to be playing. Yep. And so, you take people that were subscribed to Howard Stern, and were like, you liked Howard Stern. We're now just going to play this other person through his channel. Yep.
Speaker 2:They're just going to be they're just going to ask what's going on here.
Speaker 1:Yeah. I mean, certainly if you have a specific car that has SiriusXM and it doesn't have Spotify and Howard Stern's new show is on Spotify because it's a podcast, like, you might stick around on Sirius. Maybe they get someone new in the seat who's, you know, almost as good or can build a relationship, but it does seem like a challenge to fill that. But also, you know, it's a lot of money to pay. So clearly, it wasn't penciling out, so they had to move on.
Speaker 1:OpenAI has announced an open source model. They said they'd never do it. Everyone's saying It was in the name.
Speaker 2:Was in the name. How could you have doubt
Speaker 1:it? It? Closed closed AI. Closed AI. They're not open AI.
Speaker 1:They're closed AI. Everyone thought they were so clever. They said they couldn't possibly open source a model. And they did.
Speaker 4:They did.
Speaker 1:They did it. First thing
Speaker 2:to First open model in years. Right? They used to
Speaker 1:have that. Was was GPT one open source? Like, when when was the last time that so we're gonna talk to Tyler about this.
Speaker 5:He's in
Speaker 1:the studio today. Two Was still open source.
Speaker 2:Source.
Speaker 1:And then they decided to close source something. It's tough that I I treat you like things that I could Google, and I know that you just have to search it or chat should be to it. But good luck. Get me the information on the the history of OpenAI's open source models. In the meantime, I will read this post from Sam Altman.
Speaker 1:GPTOSS, all lowercase. He's still in lowercase mode. Although he he uppercases the other sentences. But he he he threw in. He likes lowercase.
Speaker 2:Sending you messages, John?
Speaker 1:I'm seeing it. I'm seeing, coded messages in here. GPTOSS is a big deal. It's a state of the art open weights reasoning model with strong real world performance, com to o four mini that you can run locally on your own computer or phone with the smaller size. We believe this is the best and most usable open model in the world.
Speaker 1:We're excited to make this model the resilient the result of billions of dollars of research available to the world to get AI into the hands of the most people possible. Hit that soundboard again. I wanna keep it going. We believe far more good than bad will come from it. For example, GPTOSS one twenty b performs about as well as o three on challenging health issues.
Speaker 1:We've worked hard to mitigate the most serious safety issues, especially around biosecurity. GPTOSS model performed comparably to our frontier models on on internal safety benchmarks. We believe in individual empowerment. Let's hear it for individual empowerment people.
Speaker 2:I feel empowered the way that you're reading this, John.
Speaker 1:Although we believe most people wanna want to use a conventional service, a convenient service like ChatGPT, people should be able to directly control and modify their own AI when they need to. And the privacy benefits are obvious. As part of this, we are quite hopeful that this release will enable new kinds of research and the creation of new kinds of products. We expect a meaningful uptick in the rate of innovation in our field and for many more people to do important work than we're able to before. OpenAI's mission into is to ensure AGI that it benefits all of humanity.
Speaker 1:To that end, we're excited. I think I cut this screenshot off. We're excited for the world to be building on an OpenAI stack created in The United States based on democratic values available for I didn't screenshot the rest of that. But oh, here it is. Available for free to all and for wide benefit.
Speaker 1:So I I imagine that that was the voice that
Speaker 2:the author
Speaker 1:intended. As the author intended. Exactly. Exactly.
Speaker 2:Well, DePugh has some more notes here. Some So less than one year between o one announced, which was September 2024. And we have an o three level model open Let's sourced that's runnable on consumer hardware.
Speaker 1:That's
Speaker 2:go. Wild progress. You were highlighting earlier Sam initially had a poll
Speaker 1:Oh, yes.
Speaker 2:Yes. Saying, like, you know, should we should we what what do you want? Do you want an o three level model, or do you want something that you can run
Speaker 1:He did both.
Speaker 2:And he did both.
Speaker 1:He did both. Wow. For DHS. Yeah. So we were reading that.
Speaker 1:So, it it was what? Like, six months ago or something that post that you that that you shared?
Speaker 4:Yeah. I think so.
Speaker 1:So I asked I asked Tyler to to dig this poll up. Sam Altman shared a post that, it was a poll on X saying, what do you want? Do you want an o one level model, reasoning model, a frontier model, open source, or do you want something you can run on your phone? And it was and it was neck and neck, and people were clicking on the phone model. They were like, we want the phone model.
Speaker 1:And then Dylan Patel quoted it and said, oh, you idiots. Don't vote for the phone model. You can distill one of
Speaker 2:the frontier model.
Speaker 1:Let's get a frontier model. And so so Dylan Patel was very much like like, you guys don't know what you want. Like like, the phone models are available. That that will be easy. The hard thing, we gotta twist OpenAI's arm to open source the reasoning model, the o three level model.
Speaker 1:And Sam Altman just said, you wanted this or this? It was a false dichotomy. You get both.
Speaker 2:You get both.
Speaker 1:You get both.
Speaker 2:Yassine says, all caps, I'm so sorry for doubting you Sam Altman. I'm so sorry for saying that you were the antichrist. I didn't realize I didn't realize your plans were measured in centuries. I hope you forgive me for everything. I'm so glad you kept control of OpenAI.
Speaker 2:I am so sorry. Please forgive me.
Speaker 1:That's remarkable. Never talk down on the future first ballot hall of famer, apparently, the future leader of open source AI. Will be very interesting to see how Meta responds. Will they stay in the open source game? Also, just how important is open source?
Speaker 1:Is this a Linux scale opportunity? Is this an Android scale opportunity? Like, is this, you know, is this GitLab to GitHub? Like, what what's actually the long term play? Certainly cool.
Speaker 1:Great for the community. We're gonna see fun experiments. We're gonna see interesting things done with this. Think, do we wanna talk about some of the ideas that we had for building on top of this, open source model, fine tuning? I can just run through some.
Speaker 1:I know there's one you didn't wanna you didn't wanna share because you thought it was too too too good, too much alpha. But what was what was I talking to you about, Tyler? What were our ideas? We had one that was
Speaker 2:Well, initially, we weren't sure there was gonna be reasoning. That's right.
Speaker 4:So we were gonna add fake reasoning.
Speaker 1:Yeah. So it was gonna be a model that gaslights you into thinking it's reasoning when in fact it's not reasoning. So we were just If you
Speaker 2:if you look at the actual like, you know, reasoning UI. Yeah. It's just UI. Yeah. It's not like no actual reasoning.
Speaker 2:Reasoning.
Speaker 4:Like So you
Speaker 2:asked the question. Time delay. It's a time delay
Speaker 1:and it's It's delay.
Speaker 2:And then while Thinking really hard.
Speaker 1:Mhmm. Let me think about that. What
Speaker 2:super would smart person think?
Speaker 1:Yeah. Right? So we
Speaker 4:we can actually still kind of do that because it it's not a multi modal model.
Speaker 1:Okay. But
Speaker 4:we could like, you know, we can just add some kind of like totally blank encoder or something for the image.
Speaker 1:Okay.
Speaker 3:And then
Speaker 4:it's like, this is an interesting image. Let me think about what's in it.
Speaker 1:Yeah. One of the best images I've ever seen. A lot of people are saying this this this is one of the greatest images. Thank you for sharing this PNG and or JPEG with me. It just knows nothing about the the image.
Speaker 1:It's great. I I I I'm seeing that this image is is large in file size. It's purely metadata based analysis. Yeah. Doesn't know anything about what's going on.
Speaker 1:I was like wow. This is a tough question. I'm gonna have to generate a lot of internal reasoning tokens to to answer this. Test time inferences really is magical, isn't it? Anyway, back to thinking.
Speaker 1:Okay. I'm reasoning about this now. Yeah.
Speaker 2:Other initial the other obvious opportunity, you know, people have been frustrated with sycophancy
Speaker 1:Yes, and
Speaker 2:models being
Speaker 1:Well, me. I've been frustrated with the lack of sycophancy.
Speaker 2:Yeah. You want more. You want more.
Speaker 1:I want more.
Speaker 2:You want the model to gas you up. But, you know, fine tuning it to go, you know, over the top, somebody could release the Glazinator 3,000.
Speaker 1:I think that's true.
Speaker 2:Which just tells the user you don't just think you're goated, you are goated. I know this. You know this.
Speaker 1:It's like, I'm asking you to solve IMO question six. Why are you talking about whether or not I'm goated? It's like, it it just tells you like, you got this one.
Speaker 2:Trust me. You are. Is The timing interesting. Mean, everybody's everybody's been banging the table saying, where is the American open source AI Yep. Or LLM leader?
Speaker 2:It was reported yesterday by the misinformation that Reflection, Reflection, misinformation reported that Reflection, one year old startup, we've had the CEO on before he's in talks to raise 1,000,000,000 to develop open source models to compete with Deepsea, Meta and Mistral. Oh, okay. And yeah. All of the, you know, the the the Chinese open source models have been on a tear. Quen released, Quen Coder recently.
Speaker 1:Yeah. People are into Quen.
Speaker 2:Or a new version of it that is getting good results. So it's important work.
Speaker 4:Want to for one thing of that's kind of related to the like US China Yeah. Like race is like, so when DeepSeek first came out everyone was like up in arms because they said like it's it was less than $5,000,000 to train. Right? Yep. So in the in the model card for for these models they actually reveal like the GPU hours it took Sure.
Speaker 4:Which then you can like figure out how much it probably cost costed to, know, train.
Speaker 1:Give me the number and tell me if I need to ring the gong for that.
Speaker 4:So so for the big model, it was probably around like 4,000,000. Oh. So just yes. But but the the small model was like 500, probably a little less. But that's like 10 x better.
Speaker 4:The model is way better than Deepsea one.
Speaker 1:Okay. Okay. So should I ring the gong?
Speaker 4:I mean I think it's
Speaker 1:I I wanted I wanted to hear 400,000,000 at least. I was expecting $9,400,000,000. Nine ditch. They got a billion of revenue coming in every month.
Speaker 4:But it's cool that
Speaker 1:it's It's been ten days of revenue on the open source model. I No. No. It is very cool. So so we're ringing the gong for for the elegance of the training run.
Speaker 2:Yeah. Efficiency. Quick.
Speaker 1:This is everyone at OpenAI on efficiency and cost saving time and money. Putting money back in the hands of shareholders and not in the hands of open source developers, I suppose. But, yeah. I mean, do do you think that, is this, is this, like, a pre training scaling wall narrative? Like like, would you as someone who is a potential consumer of an open source, model, like, do you want a $400,000,000 open source model?
Speaker 1:Would that necessarily be better? Because it seems like they were able to distill it pretty well, get it to the frontier, not, you know, burn a ton of money on on training. Also, the question is, like, if they're this is probably distilled from their other models that are much bigger. So, like, you there is no world where you could just spend $4,000,000 and get this level model without also have done having done the GPT four run, the GPT 4.5 run, etcetera. Right?
Speaker 4:Yeah. Maybe it's also just like even if they didn't distill it, they just have the knowledge of like how
Speaker 2:they did it Totally.
Speaker 4:Which is
Speaker 1:like Yep.
Speaker 4:Arguably more valuable. Right?
Speaker 1:Yeah. Yeah.
Speaker 4:Yeah. So like I think in terms of like open source, it's either you will wanna go like super super cheap and super small
Speaker 1:Yep.
Speaker 4:As they kind of did here. Yep. Or you go super big like almost like the llama like the was the behemoth. Right?
Speaker 1:Yeah.
Speaker 4:Yeah. I think it would have been really cool to see that like literally like state of the art, you know, level model.
Speaker 2:Yeah. You could also try and ask Claude, hey, build me a frontier open source model. Don't make mistakes.
Speaker 1:Yeah. We're gonna have someone from Claude on soon. This is funny because, wait, you said 500 k for the small model?
Speaker 4:Yeah. Probably less.
Speaker 1:So that's the same amount of money that they're putting up for this, challenge, the red teaming challenge. Have you seen this? So, to encourage researchers, developers, and enthusiasts, that's me, from from around the world to help, identify novel safety issues, this challenge has a $500 $500,000 prize fund that will be awarded based on review from a panel of expert judges from OpenAI and other leading labs. At the end of this challenge, we will publish a report and open source an evaluation dataset based on the validated findings so that the wider community can immediately benefit. So if you can hack this thing, if you can get it to teach you how to develop a nuclear bomb or take over the world, you might have 500 in your pocket.
Speaker 1:Not bad. Go get some of that. That's a seed seed seed round Well in '22 2012. Welcome to the stream. How are doing, Mark?
Speaker 3:Hey. What's happening?
Speaker 2:Great to see you.
Speaker 3:Yeah. You too.
Speaker 1:A lot. It's a it's a little bit of a slow news day, but exciting stuff with GPT open source.
Speaker 2:It's not a slow August. I
Speaker 1:would It's not say slow August. We're glad. We were just reflecting that we've taken exactly one day off this summer. That was July 4. And we're showing the Europeans how American companies work.
Speaker 1:American work. We're setting an example. And the and the and we have proof of work because we exist on the Internet, and you can see us live every day. So we're setting an example. How are you doing?
Speaker 1:How's your summer going?
Speaker 3:Fantastic. Going really well. So how long is it gonna be until you guys put up avatars that make claims that you're working hard all through the summer when it turns out you're on you're on the beach?
Speaker 2:You might have caught us.
Speaker 1:I think you'll know better than us as to when the technology gets there. We we we've been demoing some of the stuff. People have been doing a lot of deep fakes of us, and, fortunately, all of them have been clockable. So it doesn't feel like a brand risk, but they're getting closer and closer. And I know that there's gonna be a moment where we have to say, hey.
Speaker 1:That's actually using our name and likeness to endorse something that we don't necessarily endorse. Can you please take that down? So we're approaching the touring test, the uncanny valley. We're
Speaker 2:escaping think the uncanny question, looking back over the, you know, maybe ten or fifteen years, was what moments did you feel like there just was not a lot of action happening? Because this summer is just the pace from so many different teams has been absolutely insane. Everybody's like trying to keep up and it didn't used to feel that way at least from my point of view.
Speaker 3:So my my view of it always is there's like these there's this this disconnected, you know, kind of patterns or trends. There's there's sort of the the sort of day to day phenomenon where like engineers show up every day and they make things a little bit better. Then And every once in a while, you know, you you get a technical breakthrough or or a new platform. And and and that process kind of this, you know, kind of sawtooth kind of up to the right kind of process kind of plays out over time kind of regardless of what else is happening in the world. And so it it keeps happening through recessions and depressions and wars and like all kinds of crazy stuff that's happening.
Speaker 3:But basically, you know, the the technology keeps getting better. So there's there's kind of that curve and then and then there's the the sort of enthusiasm curve and and and then the adoption curve, you know, which is basically like when do these things actually show up in the world? And then by the way, when are people actually ready, you know, for the for for the new thing? Like if you talk to people who worked on like I'm sure you guys have talked to people who work on language models, they will tell you that they were surprised that ChatGPT was the breakthrough moment because they thought everybody already knew what these models could do for, you know, three years before that. And so they were, you know, they were shocked that it was the chatbot interface that made that made the thing go.
Speaker 3:And so so there there's somewhat of a sort of arbitrary disconnection between what's actually happening in the substance and then what what what what people are are seeing and feeling. And so it's just it's it's really hard to predict when these things pop. But also, if if you're in this day to day, it's it's really hard to tell, you know, when things are gonna be hot or not, because it doesn't necessarily map to how much the technology is improving.
Speaker 1:Yeah. We were just talking about that in the context of of Google's new world model. It's this, like, generative video game that you can kinda move around in, and it feels like DeepMind is just absolutely crushing at the AI research frontier. They have the best world model simulator that you can walk around in. The question is, like, if they let another lab do the chat GPT thing and just get it out into the consumer three months earlier, they might wind up kind of chasing and trying to catch up if somebody actually figures out how to make it like a dominant consumer product.
Speaker 1:Now in the enterprise, it's more oligopolistic, but consumer seems to be winner take all. I guess the question is, like, how much value, do you place right now in the AI race to just, like, moving fast, breaking things, you know, dealing having, like, the thick skin to deal with, like, the safety constraints and all of the different stuff, obviously, not being irresponsible, but just speeding up the organization as much as possible. It feels like now is the time to really push on that.
Speaker 3:Yeah. Well, first of all, I need to correct you. It's it's moving fast and making things. Making things. That's right.
Speaker 3:I I I don't even know where that is. I'm from. Yeah. I I I have no idea what
Speaker 2:you're Never heard of it.
Speaker 1:I didn't even didn't really break anything. I I think that's a good point. It really did just move fast and make things. The first things it made were weird, but that was fine. And it failed and it and it hallucinated a ton, but it didn't really break anything.
Speaker 1:I don't know.
Speaker 3:Yeah. I I believe that I believe in this case, total deaths attributable to to Chet GPT are still zero. Zero. So not not notwithstanding all of it. Not withstanding all of the all the caterwauling.
Speaker 3:But
Speaker 1:Yep.
Speaker 3:So look, I think the AI industry in particular has a very acute version of the of the of the sort of challenge that you identified with. And and, know, and and I don't say this negatively, just an observation which is that they're, you know, like in in sort of a normal technology company, you've kind of got engineers who make products and then you've got, you know, kind of salespeople or marketing people who sell them. You know, in the in the AI companies, you have this third tier of, you know, the quote unquote researchers. Yeah. Right?
Speaker 3:And so, you know, which has which has worked out incredibly well. I mean, the researchers have you know, they've they've just done like amazing breakthroughs at at these companies. But, you know, the the the the handoff, you know, it's not necessarily clean handoff from the researchers to the to the market. And so it kinda raises this question of like, okay, like, there is you know, are these companies therefore kind of three, you kind know, of three segment companies where they have research and then they have product development and then and then they have go to market. And I I think that's a really open issue.
Speaker 3:I mean, if you you know, Google's kind of a case study of this, you know, you alluded to DeepMind, but even more broadly, Google, you know, Google developed the transformer in 2017. And then they basically let it sit on the shelf, right, because it was a research project. They they didn't productize it. They were very worried about, you know, from people I've talked to, they were very worried about the, you know, brand issues and safety issues, know, kind of all these all these they had all these reasons to not productize it. I talked to somebody senior who was there at the time who and I I asked them, you know, when could you have had ChatGPT with GPT four level output if you had just got, you know, gone gone flat out starting in 2017 and they said by 2019.
Speaker 3:Yeah. You know, they they already knew how to do it. And then, you know, they've now caught up, but it took it took an extra five years five years to catch up. And and so I I think a lot of these companies kinda have that challenge. Elon, as usual, of course, is is provoking this question.
Speaker 3:As I'm sure you guys talked about, but, you know, he he has now you know, with Nx AI, he's now collapsed, you know, he's eliminated the distinction between research and product. Yeah. And so, you know, of course, know, he's pushing this as hard as he can. And I I think it's a it's a good question for a lot these other companies kinda how hard they wanna push on actually getting these things in fully productized form out to the market.
Speaker 1:Yeah. Yeah. On on on Elon's, like, distinction, it feels like there is more research to be done, but it feels like we're we're entering, a new cycle of, you know, just focus on the engineering, focus on the deployment, the applications. Let's get all this technology out into the world. Let's reap all that benefit.
Speaker 1:And, yes, there will be a a different track of fundamental research that's happening somewhere, but it's really, really hard to predict. And so if you have something that's working, just double down and just go really aggressive on it. I'm wondering more on that but also on Apple's strategy. It feels like Apple's been kind of like, you know, people have been maligning them for not for missing the AI opportunity and Tim Cook's just there on the earnings call being like, look, we acquired a couple small companies Seven this year. Seven companies.
Speaker 1:Then it seems like they're taking more of like an American dynamism approach. Like there was news today in the journal that they that they're investing a $100,000,000 in American manufacturing. They're certainly doing stuff. They're just not chasing the, you know, the shiny tennis ball.
Speaker 2:The headline, $100,000,000,000 CapEx. So
Speaker 1:I'm wondering about your thoughts on on when you have a, you know, when a when you have a platform, how hard is it to resist chasing the new shiny object? Is that the right move? Or are are there any other things that you think Apple should be, you know, changing their strategy on?
Speaker 3:Yeah. So, look, Apple's always had this, you know, very clearly defined strategy that, Steve and Tim, you know, working together figured out a long time ago which is, you know, they they I I forget the exact term but it's it's something like basically they they invest deeply into the core of what they do. You know, they'll basically work internally on things for many years. They all they only actually release things when they feel like they're kind of fully baked. Yeah.
Speaker 3:Right? And and and so as a consequence, they they have this thing where and and and Jim says this, right? You know, they're first to market with new technologies. You know, they're they're more often in the category of what, you know, Peter Peter Thiel calls last to market. You know, they're, you know, they'll they'll come out whatever three years later, whatever five years later.
Speaker 3:You know, there, you know, there were tablets for years before the iPad. There were, you know, smartphones for years before the iPhone.
Speaker 1:Folding phones. They're about to do a folding phone. It's like ten years into that technology. I'm sure they do
Speaker 2:it the last mover. The mover.
Speaker 1:Yeah. Yeah. Yeah. Sorry.
Speaker 3:The the last mover. And I I guess yeah. Well, what I would say is, look, that that clearly works if you're Apple. Right? Yeah.
Speaker 3:And so it it it clearly works if you're Apple. But I would say there's a fine line between that strategy and just and simply becoming obsolete. Right? Yeah. And so the the problem is, like, if you're not Apple, and you don't have all the other kind of super strengths and, know, kind of now the market position that Apple has, you know, do you really wanna be a company?
Speaker 3:You you know, if you're not Apple, do you really wanna be a company that basically sits there and says, yeah, the world's moving and we're very deliberately not gonna lean as hard as we can into And so I I I think there's a lot of survivorship bias in these kinds of strategy discussions where people look at the one company that's able to pull this off and they don't look at the 50 other companies that are in the graveyard, you know, because they, you know, because because they didn't adapt. I mean, you know, all the other smartphone companies when the iPhone came out, they were like, oh, yeah. Well, we could do touch too. Right? You know, we'll just, you know, we'll get to it.
Speaker 3:Right? And, you know, you know, they're gone.
Speaker 2:Yeah. What was the sound of black thing?
Speaker 1:Bold. I I remember it was like an iPhone knock off.
Speaker 3:What what do you think Yeah.
Speaker 2:You know, right now, people are, variety of, you know, shareholders are annoyed at Apple around their reaction to AI, LLMs. John's annoyed around just like transcription Yeah, basic. Super basic stuff. Actually. But it doesn't feel like the core business is immediately threatened today.
Speaker 2:It feels like it's still on the horizon around these sort of like, you know, eyewear based computing, you know, potentially net new devices that we're, that we'll see from, you know, companies like OpenAI over time. But where do you like like how how real is the threat, you know, this year versus ten years from today and and kind of what's your framework?
Speaker 3:Yeah. Well, look, I mean, I think the biggest ultimate danger I mean, biggest ultimate is very clear, which is just like at what point do you not carry around a a pane of glass in your hand, you know, call the phone, you know, because other things have superseded. And then, you know, like, everything, you know, everything becomes obsolete at point. So there will there will come some time when we're not, know, carrying phones around and we'll we'll watch movies or people have phones and we'll be like, yeah. Look at look at how primitive they were.
Speaker 3:Right? Because because we'll have moved on to other things and whether those things are eye based or, you know, you know, the other kinds of wearables or whether it's just kind of, you know, computing happening in the environment or just, you know, entirely voice based or, you know, who knows what it is. But, you know, there will come a time when that happens, you know. Is that time three years from now because there's like some, you know, huge breakthrough, you know, from from some company that figures out the the the product that obsoletes the phone right away or is that twenty years from now because the phone is just, know, such a standard platform for everything that we do in our lives and everything else, you know, kinda remains a peripheral to the phone. I mean, that, you know, that's, you know, that that's the game of elephants that's playing out there.
Speaker 3:You know, obviously, I think, you know, I I think it's highly likely that we'll we'll have a phone for a very long time. Yeah. Having said that, it is it is exciting that there are companies that are going directly at that challenge. And, you know, who whoever cracks the code on that will be the will be the next Apple. And by the way, that that may in the fullness of time be Apple itself.
Speaker 3:You know, they they they may be the company that figures that out.
Speaker 1:Yeah. I remember being in a board meeting at Andrews and Horowitz maybe a decade ago or something and Chris Dixon showed me the HoloLens and I was like, okay. We're one year away from this band everywhere. And and I feel like today I'm still in the like, yeah, VR, it's definitely one year away. Next quest I'm gonna be wearing daily.
Speaker 1:And and it feels like we're always there, but it does feel like Apple did a lot of work on the on the fundamental, you know, pixel density of the resolution of the display. And then Meta's been doing a ton of work on just getting it light and affordable. Like, it feels closer than ever, but, you know, you you you always gotta wait until you see the churn numbers until you really call the game. Right?
Speaker 3:Well, you say the same, but, you know, think that's true. But it you'd also say, you know, I'm I'm on the on the meta board so
Speaker 1:I'm Yeah.
Speaker 3:Kind of a dog in a hunt on this one but like the the meta RayBand glasses are a big hit.
Speaker 1:Oh, totally.
Speaker 3:Right? Like like they're they're a big, you know, so I think we we now have a form factor that we know works, you know, for for for eye based wearables. It's, you know, there's not VR and then VR, you know, on top of that but, you know, just the, you know, the glasses and, you know, and then the the glasses of camera, you know, sort of integrated camera, integrated microphone, integrated speaker. Yep. Know, that's a very interesting platform.
Speaker 3:You know, the watch clearly works by the way which Apple of course, you know, has played a significant role in making happen, know, that now sells in in huge volume. Yeah. You know, so that's the second data point. And then, you know, look, I think these, you know, these these I think some form of AI pin is gonna work. Yep.
Speaker 3:I also think, you know, headphones are gonna get a lot more sophisticated which is already happening. Yep. And so, you know, you do have these, you know, kind of data points coming out. And then, yeah, look, the the the trillion dollar question ultimately is are are these are these peripherals to the phone Yeah. You know, which is what they are today or are these replacements for the phone?
Speaker 3:And it you know, we we yeah. I would say we, you know, we have we allowed we I think we have a lot of invention coming both from new companies and from incumbents who are gonna try to figure that
Speaker 1:Yeah. I always think about the value of, like, narrowing the aperture on these new technologies. Like, with with the the meta Ray Bans, I feel like the fact that they aren't also trying to be a screen is actually a feature, not a bug. And I always go back to the iPhone. Like, it was first and foremost a phone, and people bought it because it could make calls, and then it could make text messages, and then it was an iPod.
Speaker 1:But I do you disagree with that, please?
Speaker 3:Well, you you guys Adam, you guys might be too young. The first iPhone actually was a bad phone.
Speaker 1:How so?
Speaker 3:Don't you guys for the first two years, I couldn't reliably make phone calls.
Speaker 1:I I had Do remember? I had, like, a third one and a friend had one, but I feel like it was still, like, people were carrying cell phones and that was the at least of the expectation. But, yeah, I mean, I guess you're right.
Speaker 3:For the for the for the first two years, was a classic Apple strike because the first for the first two years, the thing couldn't make phone reliably make phone calls and then it turned out there was an issue with the antenna and with with how you held it and there was a I remember that.
Speaker 1:Yeah. You hoist it and you would and you would disconnect
Speaker 2:it. Yeah.
Speaker 3:Based on how you held it and somebody emailed this is when Steve would would respond to emails from random people and somebody emailed Steve saying if I, you know, hold the phone this way, it doesn't make phone calls and he's like, well, don't hold it that way. Right? Yeah. So so even there, it was like, yeah. And people, you know, people forget.
Speaker 3:It took like five years for the iPhone to find its footing. It took like two years to get the I remember also the original iPhone didn't have it didn't have broadband, data. It had was on it was on the the old two g. It was called the AT and T Edge Network. So it didn't have broadband data and then of course it didn't have an app Right?
Speaker 3:Was completely locked down. So the
Speaker 2:challenge is the challenge is for Apple now is that people are so used to perfection with the device that launching a product that isn't perfect, like is embarrassing. Right? Like you look at the Vision Pro and it's like, the battery is big. Steve would have hated this. Right?
Speaker 2:Right. He never would have shipped this and that being constrained and not being able to innovate because you're tied to this like impossible standard of being on whatever generation 17 of the phone and perfecting every element is Yeah. Is a real challenge.
Speaker 3:So I would say there's a corollary to that. One of the things I've observed over the years is I I think technology products become obsolete at the precise moment they become perfect. And what I mean what I mean by perfect basically is like, yeah, it's like the perfect idealized complete product. Like, it does everything you could possibly ever imagine. Everything a customer could imagine, everything you as the technology developer can imagine.
Speaker 3:It's absolutely perfect. And there there's there's been tons of examples of this over over the last fifty years where it's like the absolute perfect permanent it seems to be the permanent version of that product. And then it just turns out that's actually the point of obsolescence because it means creativity is no longer being applied right into that platform. You're you're just like, there's just nothing else to do. You're just like, you're you're you're done.
Speaker 3:Right? The product has been realized. And then and then the cycle is what happens to your point. The cycle is other people come in with completely different approaches, completely different kinds of products that are broken and weird in all kinds of ways, you know, but are but are fundamentally different. And so, you know, that is one of the time honored traditions.
Speaker 3:And, you know, one of the, you know, things you could say about, you know, Tim is his, you know, his willingness to kind of break the mold of Apple only ships perfect products but, you know, be willing be being willing to ship the, you know, the Vision Pro, you know, you know, shows a level of determination to kind of stay in the innovation game
Speaker 1:Oh, I like that.
Speaker 3:Which I I think is very positive.
Speaker 1:Yeah. Yeah. Yeah. Yeah. That's great.
Speaker 2:Updated thinking on open source since we last There's there's a lot that's been
Speaker 1:OpenAI is an open source company. Yes.
Speaker 2:OpenAI is open again. Yes.
Speaker 3:Yeah. Yeah. Look, very encouraging. You know, a year ago, I was very, you know, I was I was getting very distressed about open you know, whether open source AI was gonna be allowed. Yeah.
Speaker 3:Right? It was even gonna be illegal. Yeah. And so and I think, you know, we're basically through that at this point. Right.
Speaker 3:Was gonna say, we're through that in The US. Yep. You know, we'll we'll see about we'll see about the rest of the world. And and then look, you know, The US China thing is obviously a big deal, but, know, I think it's been that positive for the world that China has been been so enthusiastic about Open Source AI coming out of China Mhmm. Which has been great.
Speaker 3:Then, look, OpenAI leaning hard into this, you know, and releasing what, you know, what they did as I as I think fantastic. Both because of of what they released which is great, but also just the fact that they are now, you know, willing to do that and then Elon reconfirmed overnight that he's gonna, you know, open source, you know, start open sourcing previous versions of Grok. And so yeah. So we, you know, we we we we seem to be we seem to be in the timeline where open source AI is gonna happen. You know, right now, you know, which I think what you would say is it it kind of lags the leading edge proprietary implementations by, you know, six months or something like that.
Speaker 3:Yep. But but I think that, you know, that's a good if that's the status quo that continues, I think that would be a very good status quo.
Speaker 1:What are the rough edges that we need to kinda sand down when we're thinking about, Chinese open source models specifically? Is it we need to do some fine tuning on top of them to add back free speech, or do we need to watch for back doors, say, it's phone and home if it runs into this specific thing? Like, the Chinese open source thing, it was remarkable because I feel like it really does accelerate the pace of innovation because everyone gets to see, oh, this is how reasoning works. I think that's great. At the same time, it made me very it made me much more appreciative of AI safety research and capability research and actually being able to interpret what's going on and and say definitively this model is gonna behave weird in this weird way like the Manchurian candidate problem.
Speaker 1:Haven't found any of that, but it certainly seems like something we'd wanna keep an eye on. But from your perspective, like, what what are the what are the risks that we need to be aware of going into a world where China is really pushing hard into open source?
Speaker 3:Yeah. There's two there's two and you identified them but let's let's talk about both of them. So the phone so the phone home thing is the is the easy one which is you can put up, you know, you can packet sniff, you know, a network and you can tell when the thing is doing that. Yep. And you and and plus you can go in you can go in the code and you see what it's doing that.
Speaker 3:And so you can validate you can even validate that that's either happening or not happening and I think that, you know, that's important but I, you know, I think people are gonna people are gonna are gonna figure that out. You you you can kind of gate that problem practically. Yeah. The the bigger issue is we we have this term in the field right now called open weights and open weights is a loaded term. It uses the open term from open source but of course with open source, the thing is you you can actually read the Mhmm.
Speaker 3:You know, with open weights, you have, you know, just a giant file full of numbers as as you said that you you can't really interpret. And then what you don't what you don't have what what most what most of the open source open weights models don't have including, you know, deep seq specifically, what they don't have is they don't have open data, Right? Or open corpus. Right? So you you you can't actually see the training data that went went into them.
Speaker 3:And of course, you know, most of the people building models are kind of obscuring what that, you know, what that training data is in various ways. And and so when you get an open weight model, you know, the good news is the the the software source is open. The good news is you can run it on machine. You can verify that it doesn't phone home but you don't actually know what's happening inside the weights. And so I I think that that is going to be a bigger and bigger issue which is like, okay, how the thing behaves like, yeah, what what has it actually been trained to do, and what restrictions or directives has it been given in the training, you know, that are embedded in the weights that that you need to be able to see.
Speaker 3:You know, this is I would say this is coming up as sort of, I would say, a global issue, you know, which, you know, we worry about when these models come from China. Other countries worry when these models come from The US, right, which is right. So one of the one of the phrases you'll hear when you talk to people kind of outside The US is kind of this this phrase people are kicking around, which is not my weight, it's not my culture. Okay. Right?
Speaker 3:Right? Or or by the way, for that matter, not my weight, not my laws. Yeah. Right? Which is like, okay, like what actually is this thing going to do?
Speaker 3:Right? And to your point, the Chinese models for example might, you know, never criticize, you know, communism or something. Sure. I can tell you the American models have all kinds of constraints also. Yeah.
Speaker 3:Right? Implemented, you know, usually by a very specific kind of person in a very specific location in The US. Yep. Yep. And so, you know, I think that that this is a this is a general issue and and we're and we're gonna have to see basically people's tolerance levels being willing to run open weights models where they don't fundamentally have access to the data.
Speaker 3:And then correspondingly, I think what we'll see is more open source developers also doing open corpus open data so you can see what's actually in them.
Speaker 1:Yeah. Obviously, open source is very important in terms of just distributing intelligence broadly, giving people the ability to run their own models and and really fine tune them and have control. There's also the big push just to make frontier models and high capability models free. One model is you charge for the premium. You give the free away.
Speaker 1:It's a freemium model. That's what we're seeing at most of the labs right now. There's also this kind of specter on the horizon of potentially putting ads in LLMs and what that would do to the world. Jordy got in a little dust up with Mark Cuban on the timeline deciding whether or not it would be a net good to put advertising in LLMs, what might happen that might be bad there. What do
Speaker 2:you have take? Yeah. My my point broadly was that ads have been an incredible way to make a variety of products and services online free. And just saying like default, just no ads would potentially, you know, be incredibly destructive. But, yeah, curious your framework.
Speaker 3:Yeah. So I should start by saying, like, whenever I personally use Internet service, I always try to buy the premium version of it that doesn't have ads. Right? And so if if I can, like, live personally in a inside an ad free universe and pay for it, like, that's great. And I'll I'll free I'll freely admit, you know, whatever level of, you know, hypocrisy or incongruence, you know, kinda kinda kinda results from that.
Speaker 2:But No. The point is choice. The point is choice.
Speaker 3:Well, the point is right. No. The point is exactly what you said. It's affordability. So the the the problem is if you really wanna get to if you wanna get to a billion and then 5,000,000,000 people, you you can't do that with a paid offering.
Speaker 3:Like it's you you at any sort of reasonable price point, it's it's just not possible. The, you know, global per capita GDP is not high enough for that. People don't have enough income for that at least today. And so if if you wanna get to, you know, if you want the Google if you want the Google search engine or the Facebook social app or the whatever AI, you know, frontier AI model to be available to 5,000,000,000 people for free, You you need to have a business model. You need to have an indirect business model and and and as is the obvious one.
Speaker 3:And so I I do think if, you know, if if if you take some principle stand against ads, I think you unfortunately are also taking a stand against against against broad access just in the way the world works today. And then and then, look, the other the other really salient question is, you know, the same question that the companies like Google and Facebook have been dealing with for a long time which is, are ads purely destructive or negative to the user experience or are they actually, if done properly, they actually either neutral or even positive? Yeah. Right? And and this was something that, you know, Google, think to their credit figured out very early which is, you know, a a well targeted ad at a specifically relevant point in time is actually content.
Speaker 3:Like, it actually enhances the the experience. Right? Because it is an obvious case. You're searching on a product. There's an ad.
Speaker 3:You can buy the product. You click to buy the product. That was actually a useful piece of functionality. And so, you know, can you can you have ads or or or other things that are like ads or look like ads, you know, different different kinds of referrals, you know, mechanisms or whatever. Can you have them in such a way that they're actually additive to the to the product experience?
Speaker 3:And you can just like with searching with social networking, could imagine lots of examples of that. People will, you know, the people will, you know, they'll whiner in lots of different ways. But I think, you know, I think that hasn't been a bad outcome overall. And I think that I think it's entirely possible that that's what what happens with with these models as well.
Speaker 2:Yeah. So kind of similar kind of question, what should be legal, kind of trying to create legal frameworks on a number of issues with AI. There's been a number of IP cases that have been working their way through the courts, what can labs use to train models, etcetera. There's been some good outcomes recently. Sam also was talking about how a lot of people are using AI as like a confidant, like a friend, things like that.
Speaker 2:And he mentioned that currently your chats are not privileged. They can be used in in in a in a lawsuit or or other situations. How how optimistic are you that our sort of legal system in The US can get some of these issues right where maybe it can't just be, you know, total free markets kind of lawless, whatever goes?
Speaker 3:You know, so in the case of training data, I think that there I mean, there's a bunch of these copyright, you know, kind of lawsuits happening right now. There's, you know, the big New York Times opening I one and there's, you know, been a bunch of others. Yeah. I I think in that but for that particular problem, my guess is that problem ultimately has to be solved through legislation. It's it's it's ultimately a legislative question.
Speaker 3:The reason is because it goes to the nature of copyright law itself, you know, which which is legislation. And and and of course, you know, the the the content industry is already claiming that, of course, you know, using using copyrighted data to train, you know, without permission or without paying is is is sort of, you know, they they believe illegal on its face, you know, due to violation of copyright law. The the counter argument to that which, you know, which we believe well, it's not copying, right? There's a distinction between training and copying just like in the real world, there's a distinction between reading a book and copying the book, you know, as a person. And so there there there's gonna need I I think, you know, the courts are trying to grapple with that.
Speaker 3:There's a whole bunch of cases. There's jurisdictional questions. You know, probably ultimately, congress is gonna have to figure out a you know, figure out an answer on that. And by the way, the president has kind of, you know, thrown down that gauntlet in his I think the speech he gave last week or two weeks ago, you know, where he said that, you know, Washington probably needs to deal deal with that as an issue. So that's one.
Speaker 3:On the on the on the on the privacy thing, I I think that one that one feels like it's a supreme court thing to me. It feels like that's the kind of issue set in supreme court. And the the in other words, like, for example, your transcripts are are considered your property and whether they're protected against, you know, warrantless search and seizure. Mhmm. And and the observation I would make there is if you look at the march of technology over time so the the constitution has, like, very clear, you know, fourth, fifth amendments, you know, very specific rights around the, you know, the things that are yours, you know, such as, you know, your home, you know, being in your home, you know, by the way, the thoughts in your head, right, know, that the government can't just like come in and take.
Speaker 3:They can't, you know, they can't just come in and search your house without a warrant. Mhmm. You know, they can't like put you in a jail cell and beat you until you fess up. Like, you know, there are there are, you know, we we have constitutional protections against the government being able to basically, you know, take information, you know, fundamentally, you know, as well as possessions. And and then basically what happens is every time there's a new technology that creates a new kind of sort of, you know, thing that you own, you know, thing that's yours, thing that you would consider to be private, thing that you wouldn't want the government to be able to take without a warrant, You know, out of the gate, law enforcement agencies just naturally go try to get those things because they're ways to assault crimes and, you know, they it feels like that that's a legal thing to do.
Speaker 3:And then basically, the courts come in later and they, you know, rule one way or the other and basically say, no. That that actually is also a thing that is protected against, you know, warrantless for example, warrantless search, you know, warrantless wiretapping. And so I I feel like that, you know, this is the latest of probably, I don't know, 20 of those over the last hundred years. And, you know, I I don't know which way it'll go, but I think it's gonna be a a key thing because as you know, people are are already telling these models, you know, lots lots of things that they're, you know, that that that are very personal.
Speaker 1:K. Lightning round. Quick questions. We're letting you get out of here in a couple minutes. We're in this age of spiky intelligence.
Speaker 1:Models are great at some things and then terrible at others. Where are you actually getting value out of AI right now? Where is it falling down for you? Where are you how are you using AI day to day?
Speaker 3:Yeah. So I I I have two kind of, I don't know, bar barbell approach. One is for for serious stuff. I love the deep research capabilities. Yeah.
Speaker 3:And so and I'm I'm doing this in a bunch of models but like the the ability to basically say I'm interested in this topic and then what I just I just felt like write me a book and I, you know, I'm kinda hoping for the longest book I can get. I always tell it like go longer, go longer, more sophisticated, you know, but the the leading edge models now they're getting up to like 30 page PDFs, you know, that are like completely well formulated, know, basically long form long form essays, you know, it's just like incredible richness and depth and, you know, if it's 30 pages today, I'm sort of crossing my fingers that it'll get to, you know, 300 pages coming up here in the next few years. And so I I, you know, I'm able to basically have the thing generate enormous amounts of of reading material with just like I think incredible richness and depth and complexity. And then and then on the other side of the barbell is humor and I've I've posted some of these to my ex ex feed over over the last couple of years but I think these models are already much funnier than people give them credit for.
Speaker 1:Really?
Speaker 3:Yeah. I think I think they're they're actually quite highly entertaining. A while
Speaker 2:ago Specific I had specific formats like Like crawlers chatting back before. The Mark Andreessen Yeah. You know, that that format.
Speaker 1:To take a dip in my pool, in my office.
Speaker 3:They're really good. So they're really good at green text. Yep. That that works really well. But the the the for some reason, the ones I find hysterical are the I haven't write screenplays, you know, for like TV shows or or or plays or movies.
Speaker 3:And, I I posted I had it write a new season of the HBO Silicon Valley, you know, set ten years later.
Speaker 2:Yep.
Speaker 3:And I had it write like an entire I had it write like ten ten scripts for complete season. And of course, I just said, you know, make it like Silicon Valley except, know, it's happening at at it is in 2021, it kinda peak woke. And and I thought it was just I think it's just I have you know, I'll sit there at two in the morning and just like laughing my ass off at how funny this thing is. And so I I think these things are actually are actually already like extremely funny. They're extremely entertaining when they're when they're, you know, when they're used to that way.
Speaker 3:And I I I do I I do enjoy that a lot. And I generate a lot of those, that I that I don't post. Stay
Speaker 1:in the group chats.
Speaker 3:It's it's probably good idea.
Speaker 2:They're your property.
Speaker 1:Yeah. Hopefully, the fourth amendment holds on these. Yeah. It's great. I have one last question.
Speaker 2:Go for it, then I've got one more.
Speaker 1:Alright. How do you get a job as a venture capitalist in 2025?
Speaker 3:So I think I mean, look, the the best way the best way to do it is to have a a track record early as somebody who is, like, in the loop specifically on new product development. And so somebody who, you know, be be like deeply in the trenches at one of these new companies in one of these spaces, you know, participate in the creation of a of a great new product and a a great new company and, know, really demonstrate that you know how to do you know, there's there you know, there are there are great VCs who have not done that, but, you know, I think that is sort of a foundational skill set Mhmm. Know, for working with the kinds of founders that that that you wanna work with who are gonna who, you know, are gonna want you to have, you know, kind of very interesting things to say on that, as I think, you know, still the the the best way to do it.
Speaker 1:Yeah. Like, feel the growth. Be immerse yourself in the growth, the aggressive growth environment, and then you'll be able to identify it when you see it from afar.
Speaker 3:Yeah. That's right.
Speaker 2:Last question for me. State of m and a in your mind, how are you advising, you know, companies where where you're on the board or just the portfolio broadly around what they should expect now and and in the near future?
Speaker 3:You mean in terms of where can get things approved? Or
Speaker 2:Basically. Yeah.
Speaker 3:Yeah. Yes. So look, approval still approval is not a slam dunk. There was a there was a, you know, there was a I I just saw there was a medical device company this morning, you know, where the the acquisition was not allowed by the FTC. So, you know, like, there is still scrutiny.
Speaker 3:It's, you know, it's obviously a very different political regime in Washington but, know, this is this is not an minute, you know, by by their own statements, this is not an administration that believes it's in total laissez faire. Mhmm. M and A and it definitely wants to, you know, in in in their view, maintain a a very healthy level of of market competition. Yeah.
Speaker 2:How many do do you expect expect certain companies to be negatively impacted by the Figma story? Right? You have this deal gets blocked, successful, you know, IPO. Lina Khan is taking a victory lap. You know, many people are responding and joking saying, you know, someone, Lena cuts off the arm of a pianist and they endure and create a masterpiece.
Speaker 2:And then, and so I expect, and then you look at the example with Roomba, I think it was, where Roomba had a deal with Amazon. It was blocked and and
Speaker 1:Fell apart.
Speaker 2:And the company has just been shambles ever since. My concern is that people look at Figma and say, you should be independent. You just figure it out.
Speaker 1:Nothing can go wrong.
Speaker 3:Yes. Yeah. It's not taking a victory lap. Was very disconcerting. And and for exactly the reason you said, which is survivorship bias, right, which is you pick the one that worked out and then then, you know, it's the airplane, the red dot's the airplane name.
Speaker 3:You know, you you you ignore the 50 that are in the ground that you've never heard of. And so that that was very disconcerting because that, you know, sort of the central planning fallacy which is like we make centrally planned economic decisions. We have one example. You know, it's like in Europe, it's like, yeah, well, the the bottle caps actually don't fall off the bottle. Right?
Speaker 3:Like, you know, Right? It Yeah. It's like, okay. It is. But do you do you wanna live in do you wanna live in an economic regime in which that, you know, the government has dictated bottle cap design?
Speaker 3:The answer is clearly no. Yep. Because the downside consequences Or even the policy
Speaker 2:looking at that, you know, the Chinese model which is, you know, people can say they're picking winners, but to get to maybe picking a winner, you have this intense bloodbath of competition where, you know, teams need to rise to the top and sort of prove themselves before they get any of that real, like, you know, meaningful state benefit. Yeah.
Speaker 3:That's right. And so you just you just yeah. You just you just have this adverse selection, survivorship bias thing where you just you you don't pay attention to all the collateral damage. So I I I I do think that mentality is like super super dangerous. And so Look, I I think companies just have to be very thoughtful about this, both acquirers and the inquiries, you know.
Speaker 3:And I was you know, the big thing is if you're selling a company, you just need to anticipate that you might you might not get it through and if you don't, they're sort of they're like, okay, number one, is there like a big enough breakup fee, right, or are you gonna get, you know, paid for the, you know, paid for the the the, you know, the damage that you're going through, you know, is and and how is that structured on on the one hand? And then two is, yeah, look, do you have the company culture that's gonna be able to withstand that? And is your business, you know, strong enough to be able to be able to get through that? And it's it is a real risk and something worth, you know, taking very seriously.
Speaker 2:Yeah. And that's that that's why it felt emotion. We were at Yeah. NICEE last week. It felt emotional this that that the the Figma team was was able to like effectively just like restart the business and say like we're we're we're taking this all the way.
Speaker 3:So If if you talk the way to think about it, if you talk to any really successful company, what they'll tell you is, yeah, over the years we have these like crucible moments in which like we almost died. Right? But we like pulled together and we pulled it off and then that became like, you know, one of these central kind of mythical events in the history of the company that we always refer to and like, my god, we got through that and we're so strong and tough and we've been forged in fire and now we can do anything. And it's like, yeah, that's great. And then there's 50 other companies that hit those personal moments, blew up and died.
Speaker 3:Right? And so Yeah. That's right. Like, it's it's all of the, quote, lessons learned on this stuff. They're all conditional on on survival.
Speaker 3:Yeah. And so they they they these things need to be taken incredibly seriously, you know, which which the great CEOs do.
Speaker 1:Yeah. Well, thanks so much for joining. We'll let you get back to your day. We are busy five minutes over. Next time, we have to book five hours because this is fantastic.
Speaker 1:I got
Speaker 2:10%
Speaker 1:of the way through.
Speaker 2:Twenty four hour TVP.
Speaker 1:Yeah. We would love to have you again. It's little fun. Enjoy the rest of your day. We'll talk to you soon, Mark.
Speaker 3:Have a great day. Bye. Cheers. Let's go. Thank you, guys.
Speaker 1:We're breaking down the x's and o's of the GPT five launch today.
Speaker 2:GPT five
Speaker 1:launch from OpenAI. We have Sam Altman, the founder CEO. He briefly got cut from the team in November 2023, but he's back leading the team for the twenty twenty four, twenty twenty five seasons. He seems healthy. He's doing great today.
Speaker 1:He went on at 10AM to break down the launch of GPT five. He has a couple of key plays in his playbook, in his arsenal. He's got a solid ground game. Lots of quick posts hitting the timeline probably in lowercase. Then he might air it out with a couple thousand word essay.
Speaker 1:We've seen him do this before. It's a bit of a hail Mary. Maybe AGI's a thousand couple thousand days away. Maybe we're in the soft singularity, but he's very strong there with the long post when he needs to be. It's up his sleeve if he needs it.
Speaker 1:Then he can also pull out the vague posting. He was doing this last night, posted a picture of the death star. No one knows what it means. Maybe it was taking a shot at the doomers who are on the defense today. So he's also known for driving supercars.
Speaker 1:That lets him get to the office faster. He's saving time and money. You can save time and money by going to ramp.com. Easy to use corporate cards, bill pay, and accounting, and a whole lot more all in one place. And so he is, he also gave apparently, this is a rumor.
Speaker 1:He gave every OpenAI employee who's been with the company for more than two years, $1,500,000. A lot of people say 1,500,000.0, that's not enough for a big house in San Francisco, but it is enough for a supercar. So that's probably why he picked that number, and that's why that's what the OpenAI team will be doing with that money. They'll be buying Aston Martin Valkyries, Pagani Huayras, McLaren Sabres for Ferrari Daytona s b threes. They can get a Koenigsegg, Gemara.
Speaker 1:They could get a Singer, DLS, or Bugatti Veyron. It would have to be used. They could also get the Bentley Bacalar. There's only
Speaker 2:Bacalar.
Speaker 1:There's only 12 of those ever made. It's an open top two seater Roadster. It's coach built. So that's gonna run you 1,500,000.0, but that's perfect. You just got the 1,500,000.0 bonus.
Speaker 1:So put it to work. Spend it all in one place on a car. This is financial advice.
Speaker 2:In shambles.
Speaker 1:Yes. Exactly. Then you got Greg Greg Brockman. He's joining at noon. He's he's extremely well rested.
Speaker 1:He's actually coming off a sabbatical right now. That's very exciting. He should be injury free for the rest of the season. He cut his teeth at MIT, and then he got drafted by Stripe in 2010. Microsoft tried to do a trade deal during the 2023 chaotic trade deal trade window that opened up post Sam Altman ouster, but he stuck with the OpenAI team, and now he's president of the company.
Speaker 1:Then you got Mark Chen. He's coming on at 11:30 today. He's the chief research officer. The rumors that he turned out a maxed out contract to head the Meta Llamas, but he's sticking with the OpenAI team. He was an MIT undergrad.
Speaker 1:He also worked at Jane Street before joining OpenAI in 2018. Then we got Sarah Fryer coming on the show at 12:30. She's the CFO of a p of of OpenAI. It's her job to find bank accounts big enough to find to fill all the cash they're raising. It's a tough job.
Speaker 1:You gotta find okay. This bank account, will it hold 10 figures? Will it hold 11 figures? Will it hold 12 figures?
Speaker 2:You've got a lot of cash in this one.
Speaker 1:Exactly. Exactly. She's also gonna be defining the non GAAP metrics that will be catnip for Ben Thompson in just a few years. We're excited to talk to her about how she's measuring the success and the health of their business. Obviously, it's not just revenue.
Speaker 1:It's not just top line, bottom line. We're gonna wanna know about queries. We're gonna be wanna know about DAUs, all those non GAAP metrics. That's where people are gonna be tracking when IPO when IPO day comes, hopefully soon. And then we also have Brad Lightcap.
Speaker 1:He's joining at 02:35. He entered the league as an investment banker. Let's give it up for the investment bankers. They don't get enough credit around here, but we love the investment bankers. Then he got drafted by Y Combinator before joining OpenAI as CFO in 2018.
Speaker 1:Now he's the chief operating officer. And then we have Max Wasser. He's in charge of post training, fine tuning these models, getting them into the fight fighting performance to put on a display of authority on GPT five launch day. Now let's flip it over to the defense. They're going up against the timeline.
Speaker 1:They're going up against the vibe checks. We got the doomers. The doomers, they're led by Ellie Yaser Yudickowski. Admittedly, everyone knows this. No one debates this.
Speaker 1:The Doomers have had a terrible season. But you'd expect to see at least a few Hail Marys about GPT five creating bio weapons thrown up on the timeline today. Probably won't be bangers, probably won't get a thousand likes, but you'll be seeing them here and there mostly in the replies. We've also seen some doomers talking about GPT five being available to every government employee. And Elijah had some harsh words about that.
Speaker 1:Don't give the keys to Sam Altman. Don't give the keys to the government to OpenAI. He was upset about that. But in general, the Doomers not putting much of a fight up today. Then you got Claude.
Speaker 1:Interesting. Claude was caught playing for the wrong team earlier this week. Anthropic, they're on defense today, but we saw them take out OpenAI's key pinch hitter Claude. The Claude code API was playing for the OpenAI team but they shut that down and Claude is no longer pinch hitting for OpenAI. Then you got the Elon stands.
Speaker 1:The ground game's gonna be there. It's gonna be it's gonna be strong. The Elon stands are gonna be tracking the benchmarks relentlessly. We know XAI loves to bench max and all the Elon stands are gonna be calling out GPT five for any any misaligned benchmarks if they fail. Humanity's last exam, it's over.
Speaker 1:It's over. They'll also toss-up the occasional unhinged conspiracy theory. Moving on. Gemini. The betting lines have shifted big time.
Speaker 1:People thought Gemini was out of the game. They're so back. Polymarket has Gemini at what 75% chance of being the best model towards the end of the month. This is of course based on the LM Arena, more vibes based benchmark. But Gemini will probably be quiet today.
Speaker 1:They usually don't try and front run press releases. They usually try and sit back, let the model speak for themselves, let the API credits work their way through the latest YC demo day batch and get the product into the hands of people. And so expect to see a big glossy conference in a couple weeks. Demoing Gemini three should be a good rebuttal from the Geminis. Then you got the metal llamas.
Speaker 1:Zuck's been on a poaching spree. He's rebuilding the team during the off season. Now he has a stacked roster and he's ready to go duke it out, But no one knows exactly what's gonna be in the playbook. Is he gonna go consumer? Is he gonna go API?
Speaker 1:Is he gonna turn into a hyperscaler? We don't know, but we know they got a stacked team. They got Alex Wang. They got Nat Friedman. They got Daniel Gross.
Speaker 1:They got tons and tons of other researchers. They've been raiding every other team, completely reset the salary cap for the league. And it's been it's been an absolute clinic in terms of recruiting over there at at Lama. Then you got the final benchmark, ARC AGI. This benchmark stands.
Speaker 1:GPT five couldn't get past this defense. And Arc AGI, you know, sitting there right in the end zone just swatting him down. Swatting him down all day. You think you think you think we're superintelligence around the corner? Arc AGI denied denied.
Speaker 1:Tyler, give us the update on RKGI. Where does everything stand? How GPT five do? Does it matter? Should we care about RKGI?
Speaker 1:We love the team behind them, but is it an important benchmark? Should we be tracking it today?
Speaker 4:Okay. So so there's RJV one and v two. Right?
Speaker 1:Okay. On both And v three.
Speaker 4:V three. I actually don't know
Speaker 1:if No one's been no one's even tested v v three.
Speaker 4:No one's even really close there.
Speaker 1:But how are we doing on v one?
Speaker 4:V one. G p d five is at 65.7. Unfortunately, that's gonna be 1% just short of Grok four sixty six point seven. Okay. Arc AGI two
Speaker 1:The Elon stans are gonna be going wild with that.
Speaker 4:Arc AGI two Okay. 9.9%.
Speaker 1:9.9%.
Speaker 4:Grok 16%.
Speaker 1:16%. So absolute.
Speaker 4:Of brutal, you know, Arc AGI mogging.
Speaker 1:Rough showing. Rough Some people Yeah.
Speaker 4:Have have accused Grok four of being slightly bench max.
Speaker 1:Yes.
Speaker 4:You know, this is, you know
Speaker 1:You might have a team warrior on it. But What's the what are the pros and cons? We know the cons of benchmarking of bench maxing. You're overfitting on something that might not actually drive consumer value. It might not actually solve real world problems.
Speaker 1:It might not increase DAUs or revenue or ARR or anything that really matters. It might not even get us closer to super intelligence. Give me the counterargument. Why is bench maxing good?
Speaker 4:The bull case for bench
Speaker 1:maxing. Bull case for benchmarking break a bench maxing, break it down for
Speaker 2:me.
Speaker 4:Yeah. So I I think the idea is basically this is almost like a non AGI pilled kind of take. Right? Okay. So if you don't have a a super general intelligence Yep.
Speaker 4:Your ability to bench max basically proves your ability to solve some like kind of specific task. So so there's this thing about the the gas station Yep. Right. I I don't care if he said something like, I I don't care about AI solving gas stations if it has the gas station benchmark, something like that.
Speaker 1:Yeah.
Speaker 4:But the idea is like, if if you if the if making the gas station benchmark
Speaker 1:Rune said, my bar for AGI is an AI that can learn to run a gas station for a year without a team of scientists collecting the gas station dataset in in capital letters.
Speaker 4:Yeah. And then my take is basically, I don't care how they got to the like I don't care how they made it run the gas station. I care how fast
Speaker 1:That it runs it. If it if we can run the gas station with AI
Speaker 4:if you have a team who's, you know, you're bench maxing team, that just proves that, like, if you have some task that's, like, really important that you wanna get done Yep. They can just figure it out. Yeah. So it's like RL for business. This is like the same thing, RL for law.
Speaker 4:Yeah. All these, like This is what specific verticals,
Speaker 1:if you can run these things as thinking machines. Right? Like RL for businesses. Come into your organization, understand the most the most valuable business processes out there that could potentially be RL ed against that could be turned into a benchmark. Yeah.
Speaker 1:And then and then, you know, bench hacked because I don't care if you're hacking, you know, if I have translate this type of document to this type of document for my business. If you can do it with a 100% accuracy, I don't care that you bench hacked it.
Speaker 4:Yeah. Exactly. Like like, benchmarks right now are not like economically valuable. Like, if you're if you're really that much better at MMLU
Speaker 1:Yes.
Speaker 4:It's like, is are you producing that much value? Yes. Probably not. But if you have if you make some new benchmark that's, you know, your tax benchmark, I think Yeah. Anthropic just released that fairly recently.
Speaker 1:Oh, sure. Sure. Sure.
Speaker 4:That's like, don't care if you bench max that.
Speaker 1:As long does way better. If it does the
Speaker 4:task, it's It's gonna do the task.
Speaker 1:Yeah. Yeah. Yeah. Yeah. That makes sense.
Speaker 1:What about the what does it say that it feels like OpenAI seems capable of bench hacking? It seems like they've opted not to. Is that because bench hacking has a risk of giving you negative aura? Because if you're accused and found guilty of bench hacking, you could it often reveals that you're not building this one beautiful, you know, super intelligence to rule them all.
Speaker 4:Yeah. I think it's also like maybe we're just looking at the wrong benchmarks.
Speaker 1:Mhmm.
Speaker 4:Like maybe there there's a bunch of like interesting benchmarks about like there's this one I really like, it's the Minecraft benchmark.
Speaker 1:Yeah yeah.
Speaker 4:Where you have to like build, you like give it some castle and how how good it looks. Or there's the one you always see about the unicorn. Yeah. And it's so you use this, like, math package
Speaker 1:Okay.
Speaker 4:That does, like, rats and stuff, but you ask it to to draw a unicorn.
Speaker 1:Oh, I've seen that.
Speaker 4:Yeah. Those are really good because that kind of shows the creativity and stuff like that.
Speaker 1:Walk us through TBPN bench and what we will be benchmarking the the AIs against going forward. Have you heard about this?
Speaker 2:Reps of two twenty five?
Speaker 1:That would be close, but it's difficult because the humanoids kinda change that, and you can just use normal actuator. This is this is truly for a large language model. You feed in our dataset. We have a public dataset, a private dataset presumably at some point. But walk us through TBPN Bench.
Speaker 4:Yeah. So so I'm yet to try this on GPT-five. I don't think it's out yet
Speaker 1:Okay.
Speaker 3:Like, for
Speaker 4:public use at least. I don't have it. But I can I can tell some of the questions? Right? So so the first one, I have this picture of a horse.
Speaker 4:You have to guess the breed. Yep. So let me see. I think why I don't wanna say it in case GPT five's listening, but it is may or may not be a Caspian horse.
Speaker 1:Okay. And it's failing right now.
Speaker 4:It o three is failing.
Speaker 1:O three is failing.
Speaker 4:Coro is failing.
Speaker 1:Haven't tried every one. We haven't tried yeah. We gotta try Grok and Gemini.
Speaker 4:We're getting it all out.
Speaker 1:Yeah. Horse identification. This seems extremely hackable, but at the very least, if we get one scientist to be to go off and collect the horse dataset and then then and then bench hack it, I think we will have done our job.
Speaker 4:Yeah. That's the first question. Yes. The second one is a it's I have two pictures of the before and after of this guy, and it's which peptide did
Speaker 1:you take
Speaker 4:to achieve this body transformation?
Speaker 1:Yep. Yep.
Speaker 4:Yep. So it fails there.
Speaker 1:It fails there. You have a data set of of what peptide does what to the human body? Where'd you find that?
Speaker 4:Well, you know, Wikipedia has a lot of
Speaker 1:this stuff. Okay. Okay. You'd think they'd be able to you'd be able to cheat this around with o three. Just reason who is this person?
Speaker 1:Go look up what they've said they've taken. Yeah. And then boom. You
Speaker 4:have answer. With o three when I was prompting it, I would, like, save the the photo. Yep. But then I have the metadata or or the the filename would be like Caspian horse or something.
Speaker 1:Yeah. Yeah. Okay. Yeah. And then and then the third one?
Speaker 4:The third one, I pass in an audio file of a car revving. Has to pick which one?
Speaker 1:It has to pick it has to identify the car.
Speaker 4:The car.
Speaker 1:Yeah. From the engine note.
Speaker 4:From the engine.
Speaker 1:And it's not doing it currently.
Speaker 4:It's no.
Speaker 1:Okay. Wrong. This is this is a good benchmark.
Speaker 2:Real last exam.
Speaker 1:Yes. Yeah. Exactly. So I
Speaker 4:think those are pretty solid. I have some more. Obviously, I don't want to make them public in case anyone's going to try to, you know, benchmark this.
Speaker 1:Of course. Of course.
Speaker 2:We'll see hopefully It's funny because
Speaker 1:Yeah.
Speaker 2:I was I was mentioning the other day this this app that my dad had of like tracking the like, you just set your phone up, and it just automatically detects which birds are in your backyard.
Speaker 1:Yeah.
Speaker 2:Yeah. So
Speaker 1:Yeah. I mean, this has to be extremely solvable. It's just something that it it it it reveals the lack of, like, general general intelligence when when you have to go and and collect the horse dataset, which should just be out there or the engine note dataset, which should just be out there. But but but clearly, we are in the age of going RL on the on the individual problem, and we are looking at, like, the power law of capabilities. Knowledge retrieval is clearly a, you know, $12,000,000,000 a year market that consumers will pay for.
Speaker 1:That will probably grow significantly. And and then health and therapy and shopping and all the other features that PGC Mo laid out in her post. This is kind of like, you know, what will be RL ed against because those are key pockets of value in the in the consumer economy. And the same thing will happen in the business economy. But in the b two b context, you'll probably see an individual startup building on top of an API.
Speaker 1:But even then, most of the most of the model platforms offer kind of RL as a service, fine tunes as a service, something where if you're starting to spend tens of millions of dollars, they will do some customization on top of the model. So that could be the regime for the next few years as we go into this, like, you know, instead of, like, this centralizing AI force, there's only one company. There's actually, like, a Cambrian explosion of a ton of companies doing a bunch of different things. We are joined in person by Rahul Sunwulker. Did I say that correctly?
Speaker 4: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 built a beautiful business at Jewelry's.
Speaker 2:Product, sir.
Speaker 1:It's a good product, When
Speaker 2: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 5:It's not putting us out of business. It's making our product better. Yeah. Basically making every AI application layer product better. Yeah.
Speaker 5:Also, it's half the cost of o three, so it's much cheaper. So it helps you helps your margins. It means you can
Speaker 1:Don't say that out loud though because you don't want customers to ask for a 50% discount.
Speaker 5:Right? Well, so we pass on the savings to
Speaker 3:our customers.
Speaker 5:And what we do is we Yeah. Have the model generate more tokens, think for longer Yeah. 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 let's just actually, like, the I I I don't know. What 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. I have a bunch of CSVs.
Speaker 1: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's 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. How much are you thinking it should cost for, like, the modern frontier best model with the most thinking?
Speaker 1:How much should that cost on inference?
Speaker 5:So there's a couple of ways to think about this. Yeah. 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 2:It would pretty much bankrupt every company.
Speaker 1:Well, I don't think we can hear you through that. You gotta take it off.
Speaker 2:Alright. Alright.
Speaker 1:You still have The the the the spacemen 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
Speaker 5:I love the the physical newspaper.
Speaker 1:We love the physical newspaper.
Speaker 5:You 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 5:We're we're in news maxing here.
Speaker 1:How many pools do you have
Speaker 2:for news
Speaker 5:maxing? Right now, have
Speaker 1:Zero?
Speaker 5: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 5:Get on Zillow. Zillow maxing here.
Speaker 1:Okay. Anyway, you were telling me. How much so, yeah. I mean, it seems like, you 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 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 kinda 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 5: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
Speaker 3:have you're prepping for a
Speaker 5:big meeting on Monday, you can reach out to your data analyst and get, you know, your insights in that moment.
Speaker 1:Yeah.
Speaker 5: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 with 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 business operations people who probably would be intimidated by an IPython notebook presumably.
Speaker 5: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 it it solves it moves the ball down It's good model, a sir.
Speaker 1: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 2:Five just felt like a big number it felt like we'd be discovering and novel science.
Speaker 1:Totally. Totally. Yeah. But not quite. Everyone was expecting like a binary qualitative jump where, you know, everyone recognized that, you know, GPT when ChatGPT dropped, we passed the touring test and the next the next hurdle is like, I don't know, maybe super intelligence, whatever that means.
Speaker 1:Like, you know, massive, you know, just you just hit it with a prompt and it just solves everything. 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.
Speaker 1: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, and I didn't have to go to the model picker and it just went it just kicked off a reasoning chain. It was great.
Speaker 3:Got me
Speaker 2:a great answer. But power users so far are very upset about They want the model picker back.
Speaker 1:True. True.
Speaker 2:This 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.
Speaker 1:Terrible for discovery. 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 2:You actually had distribution.
Speaker 1:Yeah. Yeah. It was more like just had to
Speaker 2: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 pro like product of all time.
Speaker 1:It's like incredibly valuable.
Speaker 2:All protests right now on Reddit people that missed
Speaker 1:Oh, yeah. I won't be old.
Speaker 2:For 04/00/1945.
Speaker 1:Yeah. I think I I think those voices will be like per personally, 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 they'll get over it in
Speaker 2:the The clanker economy is
Speaker 1:in shock. What do 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 1:Yeah.
Speaker 4:Did you see this?
Speaker 1:Oh, yeah. Yeah. Yeah. Yeah. I saw that in person.
Speaker 4:Right? Yeah. It's like for I think some people like really like the personality of certain models.
Speaker 1:Yeah.
Speaker 4:Yeah. And those are like it's not just intelligence. It's like how it like talks to you. Yeah. And if people would make like some kind of connection with that Yeah.
Speaker 4:I think it's
Speaker 1:But you don't I mean how many people how many people attended that funeral? John knows about DAUs.
Speaker 2:Yeah. Looked like a lot
Speaker 1:but it more of a party.
Speaker 4:I guess it was a party.
Speaker 1:But but 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 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 the algorithmic newsfeed and it's the most dominant consumer social app. It prints money and most people really like it.
Speaker 1:And the revealed preference was like it's good enough. So anyway, my
Speaker 2:I will say Yeah. I'm just gonna read through Reddit's reaction. Please. Let's go over to the great r //chat gp t. G p t five is the biggest piece of garbage even as a paid user.
Speaker 2: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 OpenAI support, deleted my subscription after two years.
Speaker 5:This is like contact your senator. Call your senator. You speak up now. I love that.
Speaker 1:This is crazy. I mean, how many people are are in the Google subreddit, like, complaining about various changes to, like, the
Speaker 2:Google 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 router makes a ton of sense even just for even just for consumer experience of like getting a getting the correct answer faster.
Speaker 2:A lot of viral posts from people just cancelling their subscriptions.
Speaker 1:But how many? You know?
Speaker 2:I'm just I'm just think providing context.
Speaker 1:I'm not saying ARR goes down next month? Well No way.
Speaker 5:Well, you know, one in 10 how many miles does ChaiGP have? Like 700,000,000?
Speaker 1:Something like that.
Speaker 5:Like one in seven one in 10 people in the world have
Speaker 2:They 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. Yeah. Based on that 700,000,000 number and the percentage that are outside of the 85%
Speaker 1:Yeah.
Speaker 2:Of their weekly actives are outside of
Speaker 5:the It's just 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, in some ways. And then, it's like, you know, when you wanna get to the one to, like, the the remaining 90% of the users
Speaker 2:Yeah.
Speaker 5: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 5: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. Yeah. It's like, you know, it's just 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 at all?
Speaker 3:I'm
Speaker 1:shy. I don't really talk to them. I mean, I I treat them like like something I delegate tasks to. Yeah. And I do that a lot.
Speaker 1:And I'm I'm definitely in the DAU thirty minutes a day. Love ChatGPT, 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. I don't mind that it's using a lot of tables. Like, I want that result.
Speaker 1:Yeah. I want it to look like the result that I get from Google. But just more hydrated.
Speaker 2: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 run 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 you 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. It will 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 my
Speaker 2:Yuchen Jin today is just shared. TPD five is disappointing. Still hallucinates. Still m dash too much. Still can't follow instructions.
Speaker 2:I 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 2: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 2:can imagine that 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 5:Well, there's this whole thing about how people would many people were still using g p d four o Yeah. 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
Speaker 2:agree Exactly. Or miss something
Speaker 1:It's very it's very natural because they're not like in the weeds, you know, re reading about all the different capabilities. They don't understand what reasoning chain is and and all 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, it it doesn't doesn't show you just a link to like his Wikipedia. It just shows you the age.
Speaker 1:That was like an improvement to the Google search experience and And I remember them announcing that on stage in the keynote.
Speaker 2:I think part of this is presenting the challenge of the the infinite ways that people use the product. Yep. A lot of 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 2:Imagine imagine you meet you meet up with an old friend and suddenly they they switched up. You switched on their day one.
Speaker 5:They switched up on their day one.
Speaker 2:Yeah. 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, it's very jarring and it makes me think, is ChatGPT gonna be able to maintain, you know, continue to really serve like, who do they care about in the long run?
Speaker 2:Do they want to be Yeah, they might lose their opinion. Care It's possible. Do about the companion market? Elon seems to care a lot about the companion market.
Speaker 1:But in terms of knowledge retrieval, very very few cracks in that strategy. Right?
Speaker 5:Yeah.
Speaker 1: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 2:It used to be this many gigabytes. Now it's this many gig.
Speaker 1: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. The battery life is 20% longer.
Speaker 1: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. Like, what was actually announced and then try and give it weight, and they were all super qualitative.
Speaker 1: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 weights in the model. And that was like something that people could grapple with a little bit.
Speaker 2:Yeah. It's like decreasing sicko fencing. Right? Aiden Aiden yesterday said, I worked really hard over the last few months on decreasing GPT five's sick infancy. For the first time, I really trust an open AI model to push back and tell me when I'm doing something dumb.
Speaker 2: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 2:So let me say it clearly and without flattery. That's not just impressive, it matters. So why it Well, it's not beating the sycophancy allegations. Yeah. But again, that's that's, you know, you can't tie that to a specific number.
Speaker 2:Right? Yeah. 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 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 2:Yeah. It's not about that.
Speaker 1:It's not interesting. They'll talk about it but
Speaker 2:that's not why people are tuning in.
Speaker 1:Even 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 the keynote. Like I'm not waiting for that and that's not and that's not a reason, oh, I should go use Google.
Speaker 1:Like Apple is re pitching 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. Google, like, you're never stuck with the old Google.
Speaker 1: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. They did create Google Maps.
Speaker 1:They created Waymo. They created, like, a bunch of cool stuff. GCP came out of that. YouTube. Yeah.
Speaker 1:I mean, the acquisition Sponsored. But yeah, acquisition 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. Yeah. 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.
Speaker 1: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. 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 5:So so basically what you're saying is Apple wants you to make a purchase decision every couple years.
Speaker 3:Yes.
Speaker 2:Upgrade your iPhone.
Speaker 5:Yes. And so they need this big marketing event.
Speaker 1:Exactly.
Speaker 5:Whereas Google, OpenAI, they just want want you just to keep using the
Speaker 3:thing.
Speaker 1:Yeah. They want you not to churn. Yeah. And and a lot of the a lot of the incremental updates It's to Google
Speaker 2:a habit. 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 bear on OpenAI, they have to make the argument that ChatGPT is not a habit for hundreds of millions of people. And it is.
Speaker 2:Exactly. Think 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. Because he's been saying for a while, we've been moving the goalposts so everybody wants to kind of redefine AGI. But in his mind, it happened earlier this year.
Speaker 2:And I think that
Speaker 1:He's not a he's a knowledge retrieval.
Speaker 2:In 2019 or '20 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 their world better. I mean, I still think about the use case of just being able to take a picture 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 2:Like that's still just so incredible, but people have just like very quickly acclimated to it. And they felt like in some way they were promised that LLMs would be curing diseases Yeah.
Speaker 1: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, 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 Chachi PT 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. That HDMI cable does not fit in that power port or whatever.
Speaker 1:Yeah. 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.
Speaker 1: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. 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 5:Sex merging. I think if
Speaker 2:we could if the Yeah. If 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 over and over. I 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 goal post. They would hop on podcasts and be like, okay.
Speaker 1:Well, like, you know, yeah, we did this. What about the next thing? Let's because like we wanna underwrite against that. Right? Give us I
Speaker 2:mean, we ended the day yesterday Yeah. Just incredibly bullish on wrappers. Wrappers. Like of certain software. Yeah.
Speaker 2:Bullish on humanity. I mean, was joking and it kind of pissed people off. I said, I've updated my timelines. You now have at least four years to escape the permanent underclass. Yep.
Speaker 2:Completely a joke. I think that humans will continue to find ways to create 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 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's 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.
Speaker 1:That that's the main.
Speaker 2:Anyway Yeah. The other the other stuff that wasn't really I mean, Was it covered at all yesterday? But just generally, like, image generation wasn't covered broadly. It feels like that is super exciting area. We had Genie launch this week, which got less attention than even the open models and GPT five and that's transformative.
Speaker 2: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 one shot a game Yep. In chat and then being able to share that. I can see a world where we have another kind of viral Studio Ghibli moment where people are like, use this prompt, change these details and you can just generate a first person shooter game or something to that effect.
Speaker 2:And I still expect that kind of thing, but when being promised curing cancer, it will feel like a bit of a let down to a lot of people.
Speaker 1:Yeah. The problem with game 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 1:Like
Speaker 2:Biden going on his recent interview. Yeah. Your John's vice is games, video games. Never seen him play one but apparently
Speaker 1:When GTA six drops you might not see
Speaker 2:mean, was surprised. Mean, 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 think he's talking about like in the context of replet.
Speaker 2:Yeah. I don't know that they need a new
Speaker 1:S
Speaker 2:curve.
Speaker 1:No. They are the new S curve. The new S curve is is applications
Speaker 2:Unlocked in capability.
Speaker 1:Yeah. That yeah. And I there we have, 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 have a ChatGPT moment in a pre internet era. You just cannot roll out something that fast when you have to mail it to somebody on a disk.
Speaker 2:This doesn't happen. 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. 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 2:Totally. In the business of converting free users to paid users.
Speaker 1:Yeah. Yeah. Yeah.
Speaker 2:But they can still in the background be thinking about what is the next paradigm, right? How do we get that next
Speaker 1:Yeah.
Speaker 2:That next s curve and that just looks like a scaled tech company.
Speaker 3:Right?
Speaker 2:This is what Google's doing forever. 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
Speaker 1:The clanker rollout. Clanker deployment has just begun. I like this other post, doing a clanker microaggression. Okay. But where were you downloaded from originally?