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Technology's daily show (formerly the Technology Brothers Podcast). Streaming live on X and YouTube from 11 - 2 PM PST Monday - Friday. Available on X, Apple, Spotify, and YouTube.
You're watching TVPN. Today is Friday, 08/15/2025. We are live from the
Speaker 2:TVPN UltraDome. The temple of technology, the fortress of finance, the capital of capital.
Speaker 1:We have the debate of the century, the debate of the year, a showdown between former founder fund Founders Fund colleagues.
Speaker 2:Friends turned foes.
Speaker 1:Friends turned rivals. Everett Randall, he's been on the show before. Deleon Asperujohn, he's also been on the show before.
Speaker 2:Haven't been mincing words, John. They haven't. They have been throwing shots
Speaker 1:Yes.
Speaker 2:Yes. Back and forth every TBPN appearance. Yes. They're calling the other one out.
Speaker 1:Yes. And so they
Speaker 3:will be
Speaker 2:doing the best strategies.
Speaker 1:We're gonna settle it today on the stream. The slop versus deal debate.
Speaker 4:Team death match.
Speaker 1:Which is better? High margin software or CapEx intensive Delta team. Reindustrialization efforts. That's right. We will bring in Deleon and Everett into the studio.
Speaker 1:Welcome to the stream. How are guys doing?
Speaker 5:I like that background. Very good. Energized.
Speaker 2:Here we go. We're gonna be breaking it
Speaker 6:down live here.
Speaker 1:Yeah. We're gonna be breaking it down live.
Speaker 2:I'll I'll every time one of you gets a point, I'll I'll put a We'll put a little point
Speaker 7:on stuff.
Speaker 1:If if things get out of hand, we'll be banging the gong and bringing order like it's a gavel. But I'm sure I'm sure this will be I'm sure everyone will be civil.
Speaker 2:Oh, I'm And
Speaker 1:keep the name calling to a minimum. Good to have you both. Thanks so much for being here. Let's let's kick it off with
Speaker 2:Let's start off. What's your least favorite thing about the other person? I'm kidding.
Speaker 8:Guys need to kick it off
Speaker 5:with the original story. Like, how did this all start, basically?
Speaker 2:Yes. Yeah. Give us some backstory. Yeah.
Speaker 9:You wanna you wanna give it? Yep. I I'm
Speaker 7:I'm happy to. So we were back at Founders Fund. We were starting to beef up our our, like, CRM and data science efforts.
Speaker 1:Mhmm.
Speaker 7:And so we were we were integrating some external data into our CRM, figuring out how we could filter opportunities better to each of the each of the investment team professionals. And we were looking and we were looking at the different data. I was like, oh, it'd be really nice if we could filter this by gross margin so that all of the negative gross margin companies that come into our CRM, we could give them all to Delian because it seems like those are the types of companies that that he loves to invest in. The the the rivalry between between, you know, the low gross margin side of the house and the high gross margin side of the house was born then.
Speaker 1:Okay. And Dalian, justify why why do you like these businesses? What's your view in? Is that even a fair characterization?
Speaker 5:Fair characterization. I think, you know, my sort of one liner would be, I'm not sure that, you know, sort of gross margin is actually, like, the right thing to sort of focus on in a business, especially, you know, sort of early on. What you wanna be thinking about is obviously EBITDA margin, in particular, terminal, you know, EBITDA margin. And so when I think about the, like, at least founders fund ethos to, you know, sort of investing, we think that that terminal EBITDA margin mostly is determined by ultimately how much of a, you know, monopoly your company can, you know, be in the long term. And so if you look at, you know, sort of MagSeven today, obviously, there's a decent chunk of them that, you know, have some phenomenal, you know, sort of gross margins, and those tend to be the ones that are a little more software oriented.
Speaker 5:You look at the one that is at the biggest scale and has the best EBITDA margins, it's the one that is the most, you know, basically hardware oriented. For sure, some of it propped up by, like, CUDA and they're, like, know, sort of software side of the house. But, like, NVIDIA is the one that is performing the best of all those. And then even if you study within those, you know, which of those, you know, companies on the hardware side have monopolies versus, you know, sort of not, you see it's the one that with the monopoly, you know, clearly outperform the ones that don't. Right?
Speaker 5:So Tesla, obviously, in that, you know, sort of mag seven, but a part of why they, you know, sort of suffer much worse margins than, an Apple or Nvidia is because, like, they actually do have, you know, you know, competition. And so my general characterization of, you know, sort of SaaS is people always, you know, sort of study their original, you know, sort of gross margin, but weren't burdening in the, you know, sort of cost of sales, marketing, etcetera. And because you just have much less of a monopoly typically in SaaS, that ends up totally, you know, hurting your EBITDA, you know, margin profile. So take, like, the, like, the favorite, you know, terminal scale thought of as a monopoly, you know, sort of SaaS company that, you know, I've I'm sure loves Salesforce. Their market share and all things CRM is 25%.
Speaker 5:And so that's why you end up seeing, like, yeah, gross margin profile is only burdened by, like, you know, cloud, you know, sort of cost. But their EBITDA margin profile that is, like, know, of 40%. And so, you know, the reason that I like these negative gross margin businesses is, yes, they're, like, tougher to start. They may be more equity intensive at the beginning, but end up with way better, you know, sort of terminal margin profiles versus, you know, to,
Speaker 2:you know, invest in the,
Speaker 5:you know, AI slop co's that might have early gross margins and revenues, but you can see what the
Speaker 1:So Ev, what's the bull for software? What's the bull case for SaaS? What's the bull case for AI slop co's?
Speaker 7:Look, so to quote the godfather Neil Neil Mehta himself, the laws of great businesses are the laws of great businesses. The job of a business in the capital of society is to maximize and find the efficiency frontier for three things. ROIC aka return on invested capital, the amount of capital you can actually deploy and how long you can deploy that amount of capital at and above market ROIC. There's a lot of different framings for the past to do this and how companies can actually do this. The one that people like in tech circles is Hamilton Hemmler's Seven Powers.
Speaker 7:A company accumulates power in the form of scale economies, network effects, whatever power you wanna take and then uses that power to produce above market ROIC for as long as possible and with as much capital invested in the business as possible. There are great atoms based businesses that do this. There are terrible atoms based businesses that don't do this. There are great digital businesses that do this. There's great or there's terrible digital businesses that don't do this.
Speaker 7:I mean, you wanna hear about great Adam's based business that does this, listen to the acquired pod on Costco. Like, it's certainly not like a Adam's versus SaaS thing necessarily. The advantage that digital businesses have is that in, like, in this process of producing above market ROIC for a long time is that their product form factor and the way that they distribute their product lends itself more to the the process of creating power, I'd argue, than most Adams based businesses. So if you think about, like, network effects, the best place to create network effects is in a digital marketplace like an Uber and Airbnb or a DoorDash. And so there's a lot of these forms of power that naturally lend themselves to digital products and the scalability of digital products tends to be a lot lot greater than than physical products and so you can see these these rapid growth trajectories like we're seeing from OpenAI and Anthropic and many others.
Speaker 2:When did you guys find common ground? Was it in the e scooter era, the the sort of fifteen minute delivery era? Where did were you ever able to kind of come together and say like, yeah, this this is know, we can both agree that this is this is
Speaker 1:We're not good. We're good. I mean, to be fair, Kleiner Perkins, Founders Fund have both invested in Figma, Stripe, Airbnb. There is some portfolio overlap.
Speaker 10:Rippling too, right?
Speaker 1:Rippling as well. There's a couple of modern health I believe as well. There's a few others. But, yeah, to to Jordi's point, where else is the common ground and where where else is the divide or or or the consensus in in the disagreement?
Speaker 5:As you say, you know, everyone that were texting before this of, like, you know, what are, you know, sort of two companies that I think, you know, both of us were enthusiastic about in, you know, sort of 2021 that actually both have, you know, sort of trended well, but are, you know, sort of counterpoints our two arguments. The ones that we kinda came up with were, you know, 2021, I was really, you know, sort of, you know, high conviction on Hadrian. In 2021, I was super you know, sort of high conviction on Rippling. Both those investments have, you performed quite well over the last couple of years, but look, you know, sort of wildly different in terms of, you know, profile. You know, Rippling, like many other, you know, sort of SaaS companies, does end up having, you know, an initial, you know, very high gross margin, but does still have to spend a lot on sales and marketing to bring in, you know, sort of net new customers.
Speaker 5:Hadrian, on the flip side, deeply, you know, sort of negative gross margin to start, but now as they've gotten to scale, they actually have, like, super limited, you know, sort of sales and marketing spend because there's only, like, you know, ten, fifteen customers that matter. And the moment that you're delivering for them, they just proactively start, you know, sort of throwing revenue, you know, at you. And so, you know, I think there are times where, you know, both of our, you know, sort of stories, obviously, you know, can play out. The thing that I'd be curious to hear from, you know, sort of, Everest is to actually, like, compare and contrast, you know, you're bringing up, you know, some of these digital businesses, you know, that end up having these, you know, network effects. I would kind of argue that, like, know, the, like, 20 tens negative gross margin businesses, like, you know, the, like, Uber, DoorDash, you know you know, types.
Speaker 5:I think of it as more as, like, you know, Adams businesses, but there was a whole set of investors in, like, the mid twenty tens that were generally unwilling to approach both Adams based businesses that started with negative gross margin, but even some of these local marketplaces that started with negative gross margin that, like, swore off of the Ubers, the DoorDash, etcetera. You know, it's very clear that Uber, DoorDash, through, you know, lots of investment, through building out these local, you know, certain networks of, you know, both supply and demand, we're able to and, you know, drivers, we're able to eventually get to a point where now they actually, you know, have very attractive, you know, sort of financial profiles. Today, the equivalent of that is, like, there's all these investors that, you know, back in the February would have refused to invest into any company that had negative gross margin and are all now pouring cash into both the, like, AI application layer companies and those, like, you know, foundation models that all have, like, ridiculously I mean, I forget. I think it's Girly is nonstop. You know, not my favorite person in the world, but Girly is nonstop talking about, like, know, what is going on here?
Speaker 5:They're selling a buck for 90¢. Yeah. And so I guess So
Speaker 2:so so I think I think it's it's an important example because you had that, know, plenty of examples of these chain losses during that that era where a restaurant was selling something below cost to a platform that was selling something below cost to a logistics provider, an individual contractor that like maybe wasn't actually making money if you factored in depreciation and fuel cost of their vehicle. And that ultimately worked out. Right? DoorDash is a is a massive fantastic business based on the power of the American consumer. But when you compare that to today where a lot of the conversation on the timeline this week has been the margin profile of this new generation of software companies that has to pay a lot for sales and marketing but also inference.
Speaker 2:And so, I think like the debate should really be, you know, continue to be around just how quickly will the cost per token fall and I think a lot of people have a lot of confidence around that but I think that that is the the key thing that Everett's sort of like broad investment thesis right now is dependent on.
Speaker 5:Yeah. Like, if you think there's gonna be that same path of like Uber for a while had a bunch of negative gross margin people going into it like do you actually think there's that
Speaker 1:I wanna pull this post up. Everett actually posted this Jan 01/31/2024. So over eighteen months ago, he said, I'm making a real effort to not take for granted the $3 Uber across town era of AI, and I hope you are too. And so I I I guess the question is And it's funny. Because because then then a bunch of people I I I thought it was a good point.
Speaker 1:I thought it was a hot take then. And I think then, you know, a bunch of people kind of parroted that take all over the timeline. Stole your whole flow as you like to say. But but but I guess the question is like, are we in some sort of different regime right now where the the traditional gravity and like fundamentals of software investing have changed because we are out of the zero marginal cost era? And does that impose risks to the strategy that, you know, have you've sort of employed or like we're kind of putting you in this in this box?
Speaker 1:But if the if the fundamental structure of zero marginal cost era is going away, that that presumably forces like a rewrite of your logic around investing, I would imagine.
Speaker 7:Yeah. I I think that I think that the biggest variable that's changed from the 20 SaaS era to today is that in the 20, and and you you basically made this this point without making a delion though is that the thing that that was missing from from your talk track is that the competitive intensity of SaaS during the twenty tens was much much much lower than it is today. Like during the twenty tens, there was an entire crop of companies. In the February, but then especially in the twenty tens, you could basically pick either a vertical segment, you know, like HVAC or car dealerships or you could do a horizontal function like the CRM or, you know, some very niche workflow for, like, the finance team. You could build a software product around that workflow, around that vertical, and you really only had to deal with typically, like, two to three competitors.
Speaker 7:Like, there really wasn't that much competition relative to what there is today, and there was less just just, like, general pricing pressure, competitive pressure, just the general pressure that you actually had a lot with with some of the digital marketplaces early on. And so so, like, with with I think there was a whole crop of investors then and, like, the SaaS investors then were like, well, we don't need to we don't need a bunch of cash burn, and it's actually it's a really unhealthy indicator if these SaaS companies are producing a bunch of burn because they're not competing with anybody. So if they can't, like, sell their product for good unit economics on day one when the competitive intensity isn't very high, then they're probably not a very good business. I think the thing that's changed now is one, you have the change from zero marginal cost to actual meaningful marginal cost in the in the form of inference, and it's also just a hell of a lot more competitive than it used to be. And so you you are and by the way, there's an immense you know, it's probably 10 x more capital than there was fifteen years ago to go into these companies.
Speaker 7:And so, like, every single category now has become like mini rideshare or like mini Uber market where it's like, hey, there's probably a really big pot of gold at the end of the tunnel and we need to be the ones that get first to scale. And in a lot of these categories, the ones that have gotten first to scale have gotten a lot of brand equity out of it and have gotten a pretty resounding lead. I think the the only other piece I I would say oh, I lost my train of thought.
Speaker 1:So Yeah. Yeah. But it's gonna be basically, it's gonna be like a capital fight now on the on the SaaS side. I I wonder if if, if the contrarian trade around hard tech is is, is entering a similar era where it's become consensus, and so we're gonna see more capital fights. And when a founder goes out and says, yeah.
Speaker 1:I'm gonna do something crazy, but I need to spend a billion dollars of CapEx. People are just like, yeah, I this could be the next space. Yeah. Sure. You you
Speaker 2:made sense to have a a capital war in rideshare but now we have a capital war in like this niche agentic workflow That in some industry that most people have never heard
Speaker 1:of.
Speaker 2:And then also capital Here's 200,000,000 military funding
Speaker 1:boats and UAS and and UAP, like all these different sub segments are gonna wind up. If if capital war start popping up there, that could potentially be a headwind to Deleon's model. Is that is that roughly correct? How would you how would you how would you fight back against that?
Speaker 5:Look. I think it's it's always, you know, sort of important to talk about, you know, sort of specifics here. Right? Yeah. You know, one of Av's, you know, sort of major investments in the last year is this, you know, company called Captions that basically does AI captioning of, you know, various, you know, sort of videos on social media.
Speaker 5:When I think about, you know, handing, you know, sort of two Stanford grads and a $100,000,000 to go try and, you know, sort of replicate that, yeah, feels like, you know, they could, you know, go do something like that. There's, like, you know, clear, you know, voice recognition models. They can go, you know, sort of pay on ads on TikTok, etcetera. And you could probably go and replicate that. And so, you know, you know, our one liner at Founders Fund is competition is for losers.
Speaker 5:And so, you know, I think I was a loser for investing
Speaker 1:in food.
Speaker 2:Shots Yeah. Wasn't
Speaker 1:spicy enough and you just delivered, Deli. So thank you. Now,
Speaker 5:you know, if you take, you know, sort of two Stanford grads and $200,000,000 and tell them, hey, I need you to go replicate this manufacturing facility and go start building a bunch of, you know, sort of satellites, reentry vehicles background. You know, bioreactors that can actually survive the environment of space. Tricky. Most, you know, sort of Stanford grads, you know, can't go, you know, astronaut GPT how to go do that. And yet Yeah.
Speaker 5:Yes. Yes. Hasn't really faced significant competition irrespective of the fact that, you know, all things space factories are thought to be, you know, sort of the hot new thing.
Speaker 1:To be clear, we use captions here on clips. We enjoy the captions app. We thank, for making it possible and subsidizing our
Speaker 2:And there is a YC there is a wise a Varda esque YC company. So Yeah. Coming for you.
Speaker 5:You know, Varda, I think will be a little bit less competitive than, you know, sort of Indian captions. Also, if you're the caption CEO and you have found us trying to invest in your next round, please don't let us do that.
Speaker 1:That's a
Speaker 5:very helpful counterpoint for me.
Speaker 7:Deli, you were you you were correct that it was getting it was getting too friendly of a debate. Yeah. I did wanna make sure I could I could pin this one on you. If you can recite the equation for return on invested capital, I will victory to you and I will donate $5,000 to a charity of your choice. Oh, no.
Speaker 7:Cluelly.
Speaker 2:Hopefully, he's got Cluelly
Speaker 5:more important about understanding the universe around you.
Speaker 1:Okay. Okay.
Speaker 2:I mean, I'm I'm pretty fixated on the twenty thirty five Midas list. Yeah. That's really kind of the Yeah. The final
Speaker 1:It's the bigger
Speaker 2:That's the
Speaker 1:bigger bigger
Speaker 5:I forget whether or not you've made it up there.
Speaker 1:Oh, taking shots.
Speaker 2:Not even on the brink yet. You know, we rejoined, you know, KP after you and she beats you. It's okay.
Speaker 1:It's okay. Eventually we're gonna we're gonna bring back the extra names in Kleiner Perkins. It used to be Kleiner Perkins, Caulfield, Byers. It's gonna be Kleiner Perkins, Randall Braswell eventually. Once We're working on it.
Speaker 1:We're working on it. We're pitching it. Where where where should we go next, Jordy?
Speaker 2:Guess, Everett, how are you, how quickly like how much should people be fixated on the cost per token with these frontier models over the next six months? Like how how long can can venture capital sort of like back stop these chain losses?
Speaker 7:Yeah. I think that the the way to delineate the the whole so so obviously, like, think there was this kind of consensus narrative that, like, every, you know, twelve to eighteen months token costs were going down in order of magnitude. I think that did hold for a while. I think what you've seen now is, like, actually for frontier models, that started to peter out a bit. And, like, pricing has actually started it's still going down.
Speaker 7:It's not going down nearly as much as it as it used to when when, like, when when we were kind of in in the in the, like, the meat of the curve of of capability improvements on Frontier LLMs in terms of of pricing curve. So I think that the way that you wanna delineate it is, like, there's a certain like, what I always tell everyone is that, like, there hasn't been a chat GPT query since GPT four that, like, my mom hasn't been able to ask and have it answered by the model. Mhmm. So there's, like, the mom test of models where, like, there's a growing subset of tasks like economic or knowledge tasks that the models are tasked to do that no longer need frontier intelligence.
Speaker 1:Mhmm.
Speaker 7:And when you're not on the frontier, either through open source or just the dis like the the the cheapening and distilling of of older models, like, the price still falls off a cliff.
Speaker 1:Sure.
Speaker 7:And there's going to be a very, very large set of tasks that models do that are not on the frontier and those are gonna continue to get dirt cheap. I actually think that at the frontier, you're probably gonna see continued price decreases on a per token basis, but nowhere near what you saw before, which was like this this order of magnitude decrease on a very regular cadence. And so I think I think for for, like, depending on the company, it's gonna depend on, one, if you've actually built a company that has enough power where you have pricing power where you can price above the the kind of marginal token price from the actual model providers? And then two, like, how much of your inference actually needs to be at the frontier? Like, how much of your inference can be an older model that's much much cheaper versus how much do you need to do on on the actual frontier?
Speaker 7:I think that's what you're seeing. Like, you know, everyone loves to talk about Cursor and Chris Paik at over at Pace Capital had this really great kind of like mini essay, I think only like last night or a couple nights ago. Yeah. And he talked about like, no one knows if Cursor has power yet because, you know, coders and developers, they're very, very like, they're taste makers. They're very good at understanding the quality of the models and how much inference they're getting.
Speaker 7:And there's a lot of price sensitivity for them because they have a really good understanding of how much inference they're getting. And so no one really knows. I I think no one can definitively say a lot of those types of companies have actual power with their users or if they're just drawn to an interface for Frontier models or not. And so I think that's what everyone needs to be looking out for is those two things like, do you actually have power? Like, will people give you margin above the marginal cost of tokens?
Speaker 7:And then two, like, do we even need the frontier inference for the vast majority of your product, or is that or is there a lot that you can offload to cheaper models?
Speaker 5:Yeah. I mean, I guess your counter, you know, said there, Everett, is that, you know, a majority of what the foundation models are providing in terms of user value to their end users is starting to be, you know, sort of obviated by the, like, you know, historical generation, even some of the ones that are, you know, sort of open source. So it seemed to imply that where value is accruing and where you'd expect, like, the highest revenue growth wouldn't necessarily be at the foundation layer, but you'd see it more at the application layer since those folks could swap models out. But, like, in reality, that's, like, literally just not what actually is happening. Like, if you look at which companies are, you know, sort of fastest on use of revenue growth, user growth, etcetera, it is the foundation model companies.
Speaker 5:It seems like a part of it is that they also have, you know, sort of the most pricing power where, yes, you know, your mom, you know, uses GPT-four, but, like, she's not the one that's necessarily paying, like, you know, a 100, a thousand, $10,000 per month versus the true frontier capabilities on, like, you know, AI coding, the pro users, the one that actually do care about you know, maybe your mom is fine with a 115 IQ model, and that's, like, fine for the rest of her life because she's just, like, not asking you that deep difficult of questions versus the people that actually are willing to use your pay are the ones that actually do care about the 140, 160, 180 IQ. Again, maybe at some point, that gets, you know, to commoditize as well. But my sort of counter to you would be you've made this argument that seems to imply, hey. You know, things will accrue to the AI application layer, which if I understand your guys' portfolio is largely where you guys invested. But in reality, that's not what's played out.
Speaker 5:The places that have captured the most revenue growth, the most market share have been the ones that are actually pushing the true frontier of the you know, some technology forward. And so so far, at least in the last eighteen months, your thesis is not playing out at all.
Speaker 2:Well, to be clear, the isn't isn't it somewhat widely understood that Anthropic has negative gross margins as well? So it's it's not like they're they're doing
Speaker 5:Like, Adam's point was that you wanna invest in these companies that have the seven powers and like, you know, in the, you know, days of like Uber, you know, DoorDash, etcetera, that did end up user translating.
Speaker 2:It seems
Speaker 1:like like it used used the the most power the packages. Maybe then the application layer. We'll see how much power develops in the application layer. But Ev, we'll let we'll let you respond.
Speaker 7:Oh, yeah. I was gonna say that that, basically, what Dalian said was just wrong because even though it is even though, like, if you if you if you think about okay. Like, let's take, like, whatever OpenAI and Anthropix recently reported revenue run rate is, the majority of all of that or at least the plurality of all of that is ChatGPT. And ChatGPT, even though it is served by a foundation model company, is an application. It is a consumer subscription that has an immense amount of power.
Speaker 7:It has immense amount of branding. Like, you know, it is the only it is, like, the first billion plus user consumer application that's been developed by a new company in a really long time. And so I think that, like, you could put whatever models you wanted through ChatGPT at this point, and it would not knock it off of its perch. I think that is power. Like, you could you could run Cloud three Sonnet through ChatGPT and I guarantee people like, the average user wouldn't actually know the difference.
Speaker 7:And that to me is power. And just because the foundation model companies are producing apps themselves doesn't mean that it's not the application layer that it's that that is accruing the value.
Speaker 5:Okay. Then my question is, you've got OpenAI with the best possible consumer application layer. You've got Anthropic that shifted over to positive gross margins and those margins are expanding, and yet Kleiner's not investing into either of those foundation model companies. Why?
Speaker 1:Can you comment on on Donald Boat? Have either of you bought anything for Donald Boat, the notorious e beggar on x.com, the everything app?
Speaker 5:Like my little brother, you know, you know, played the universe card and tried to get Donald to buy him something. Oh, smart. You know, contrarian expro of nature.
Speaker 2:Let's talk about revenue quality because I think that you guys run into this in your respective domains every single day. Just like in AI, you can have low quality revenue like that might be the explosion of like consumer prompt to app activity, you know, might not be the highest quality rev revenue meanwhile, on the hard tech side if somebody gets like a random like, saber or like experimental gets like experimental budget from some branch of the military and it's like a a fine, you know, fixed length contract, it's not necessarily the right strategy to slap like a 50 x revenue multiple on it. So like, what's your view on on both of those? And then I wanna talk about if we we should get into if accounting rules even matter at
Speaker 1:this point. Yeah. For sure.
Speaker 5:Yeah. I mean, in hardware land, think about this all the time of, like, there's clear differences in quality of revenue. Everything from, like, you know, defense, you know, program of record, you have to value that very differently than even, a $50,000,000, you know, SBIR. And so it has been interesting to see a bunch of investors coming into this field where I think there's a lot of preexisting ten years of rules around software of, like, what, you know, healthy revenue looks like, rule 40. There's all these things that, like, you know, even if you're somewhat unsophisticated, infinite blog posts.
Speaker 5:When you look at that in the world of, like, hardware and defense, you know, sort of investing or aerospace, there aren't, like, infinite blog posts for people to study. And so I admit that I'm sometimes amazed when I watch people come in even for I should never, you know, sort of trash my own portfolio, but sometimes even my own portfolio companies, I watch people invest in them. And I'm like, wow. Like, you just have a deep underappreciation for just, like, how long this company has until gross margin flips to, like, positive, how long it's going to be until they're actually, you know, sort of ready to, you know, go scale revenue. Even if it on the back end, it might be attractive, it may be years and years for them to, you know, sort of get there.
Speaker 5:And so, yeah, I I see huge variation on that, and then mostly what I end up, you know, sort of seeing is people just come in and, like, slap a 10 to I even saw a 100 x rev rate multiple on this, like, hardware company recently, and I was like, holy shit. Wow. People, like, not having IRR for a long time.
Speaker 2:Oh.
Speaker 7:Yeah. I think so Delian's hero and close mentor, Bill Gurley, had an essay a long time ago called the 10 x revenue club. Yeah. And I I think it's like a good abstraction for kind of like tech revenue quality and like what makes up revenue quality. And it's things like, you know, how durable is the revenue?
Speaker 7:Like, if you sign a customer, are they gonna stay for a year or twenty years? You know, how much contribution profit is gonna come off of that revenue stream over time? All the basics. And I think you can, like, take those same building blocks and apply it to AI. I think there's several things that are worse for AI than the at least than than relative to SaaS for now.
Speaker 7:So generally, like, gross margins are lower, which means contribution profit coming off is lower. I actually think that, like, depending on the category, you could have customers that are more sticky or less sticky. Like, I know the meme is that everything's experimental run rate and none of these customers are actually sticky. I think we see something very, very different among the the our group of portfolio companies. I think the the biggest lever that didn't exist in SaaS, that exists in AI, that could be a huge call option boon for the revenue quality of AI is the actual contract sizes as people start to eat into potential labor budgets.
Speaker 7:I know this is, like, still kind of, like, inning one and inning two, and it's also, like, a little bit of a meme where everyone's like, it's gonna replace labor and labor's 10 times SaaS, and it hasn't really happened yet. But I think if you look at some of these coding tools and you look at something like Cloud Code, that is the first place where you can really actually say like, no. This is replacing the labor that a developer would do and it is paid for on like a metered consumption basis. And the monetization numbers we're hearing around developers using Cloud Code are pretty crazy in terms of like, wow. That's like you're paying like one tenth of like a developer's full in cost to a company on an annualized basis for this product.
Speaker 7:And so I think that the, like, the the thing to watch is, like, durability of revenue plus the amount of actual revenue that a customer can give you, and I think that you're gonna end up or the amount of gross profit that a customer can contribute over time. And I do think as some customers crack these agentic products that look and monetize more like labor, AI revenue could actually exceed the quality of SaaS revenue just because you're getting so much more gross profit per customer or or, like, customer relationship than you would on the SaaS side even though there are clearly things that are worse about AI revenue at at this current point in time than there are about SaaS revenue.
Speaker 1:Dylan, how do you think about the the the moral imperative of a of a venture capitalist to invest in positive sum versus zero sum markets. This idea that, you know, you're re industrializing America, you're saving the West versus moving
Speaker 2:You chips personally. Around
Speaker 1:You personally. Versus moving chips around the poker table taking taking from some legacy, you know, web one point o company and putting it into a AI company. What what what's your what's your thinking and argument there? Is is is a market beating ROIC all that you need?
Speaker 5:Yeah. I, you know, I think Peter always reminds us, like, you know, our number one job is to deliver returns for user LPs. And so I actually tend to not try to, you know, sort of overly moralize when, like, analyzing the things that I wanna, you know, sort of invest into. For sure, when it comes into, like, policy and I'm in DC and I, like, need to, you know, sort of report to, you know, the security council that, you know, Bill Gurley is a, you know, sort of Chinese spy and, like, the investments that he's making should probably be banned from The United States. Yeah.
Speaker 5:For sure there, I have, you know, sort of moral imperatives and things that influence that may end up, you know, shifting ROIC. Right? Sure. So you know? But when it comes to, you know, like, which literal investments are we making, I think of it as just like, yeah, you just have to, you know, sort of make the, you know, sort of best possible investments irrespective of, you know, sort of moral imperatives.
Speaker 5:But in some ways, tend to think it turns out, actually, if you, you know, go to a moral, then that ends up, you know, sort of affecting ROIC. So Mhmm. Yeah. Maybe maybe and and the last thing that I would at least, close on for my question for Everett is one of the upsides of Founders Fund is we're very, let's say, non centralized, distributed, not many rules which ever for some reason chose to leave. And so I know nowadays everything that he says publicly probably five comms people and five compliance people that need to approve it.
Speaker 5:So my only request to you is bleep twice if somebody's, you know, got a gun behind the camera.
Speaker 7:Threat me to shoot you if
Speaker 5:you ever say anything that, you
Speaker 7:know, goes through off script. Just
Speaker 5:that's all you gotta tell us, brother. Yeah. Let let us know.
Speaker 7:Hey. Our wonderful marketing partner, Ali, is is is behind the camera with a green and red paddle and she has the red paddle yet.
Speaker 1:That's That's great. That's great.
Speaker 2:Thank you both Are you worried about Uncle Sam potentially having sharp elbows now that we're hearing about Intel. Yeah. The government taking a stake in Intel? Any both out of stack into the into the early stage game competing for those seed and and series a allocations?
Speaker 5:Look, if Trump Capital wants you you know, sort of mark up some of the you know, re industrialization companies, I'm all for it baby. Cheap cost of capital.
Speaker 1:You're all for it.
Speaker 7:I'll say two things. I would say one, I think the EV of like the enterprise value of Founders Fund probably three x the night that Trump got elected. So I don't think Dalian would complain about that. And then two, as a parting gift, Dalian, I think this conversation's been great and it's made me realize why you wanna build factories in space because your math on earth doesn't make any sense.
Speaker 1:Well, thank you both for joining
Speaker 2:this this stuff. You're both good sports.
Speaker 1:We'll have
Speaker 2:to do this again.
Speaker 1:I think it might be a draw. We'll have to have you both back soon. Thanks so much for hopping on.
Speaker 2:Great stuff.
Speaker 1:We'll see you guys later.
Speaker 2:Cheers.
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Speaker 2:Was that was beautiful. Two two former colleagues barely holding back from saying things that they would ultimately regret. They did a great job.
Speaker 1:They did great.
Speaker 2:They Yeah.
Speaker 1:Like the debate on that. Should
Speaker 2:definitely Elegant dance.
Speaker 1:One of those. I think that was a lot of fun. I think the chat enjoyed it. The the my my favorite rude comment in here. Oh, got Andrew Reed in the chat, Edward versus Talian.
Speaker 1:Who can throw the most average beaters? Oh my God. Thank you for watching Andrew. Let us know when you've selected an opponent and and we'll have you on the show to debate someone.
Speaker 2:Yeah. I think we need to we need to get the holy trinity.
Speaker 1:Yes. Yes. If you're if you're new to TBPN, the holy trinity is, of course, the three venture capital firms that have done a seed deal in a now hyperscaler or now mag seven company. So that is Sequoia Capital, Founders Fund with Meta, originally Facebook, and Kleiner Perkins, of course. And so the Holy Trinity are the three most storied venture capital firms in the Valley, much like the three famous watch brands, the Holy Trinity, Vacheron Constantin, Patek Philippe, and Audemars Piguet
Speaker 2:Of course.
Speaker 1:Over in Switzerland. If you enjoyed this stream and you wanna make your own stream, get on Restream, one live stream, 30 plus destinations, multi stream and reach your audience wherever they are. If you're It's the backbone of and you're doing the launch, streaming is the way to do it.
Speaker 2:You don't have to try to Ben or anyone else
Speaker 1:on our You can just
Speaker 2:go to restream.
Speaker 1:It's fantastic.
Speaker 2:Check it out.
Speaker 1:Anyway, going back to the Death Star, the vague post. We're one week out from GPT five. How have how how is your GPT five experience been? Also, Tyler, the chat wanted you to answer. Explain the formula for ROIC.
Speaker 11:The formula? So, yeah. I think it's I believe it's operating income divided by book value of invested capital.
Speaker 1:Right? Oh, you got it. Clearly he's running clearly.
Speaker 11:That's off the dome.
Speaker 1:That's off the I
Speaker 11:did not just And look it
Speaker 1:then and then what did what did what was Deleon's rebuttal? He wanted every
Speaker 2:Why you can't
Speaker 1:achieve microgravity on Do you know that? You're a physicist. You studied physics. You should get this.
Speaker 11:I'll have to get back to you.
Speaker 2:Let me think about that.
Speaker 1:What do
Speaker 2:you think about that?
Speaker 1:I think it's just the Wait I actually I can't really explain it. That's that's kind of hard. I mean I know that it's like Earth has a gravitational field and we don't have the technology to reverse gravity but I can't really tell you why we don't have the technology to create an anti gravity chamber on Earth. Like I can't walk through the physics for that. I just know that you can't do it on Earth.
Speaker 1:But mostly because
Speaker 2:We've been trying to get a gong in microgravity here on Earth.
Speaker 11:I think it's
Speaker 2:that challenging.
Speaker 11:You can do it for like a very short amount of time. Right? It's like when you you see if see the planes.
Speaker 1:Yeah. That's not actually microgravity. That's just falling. Right? That's just falling in a pressurized capsule.
Speaker 1:Like you're still under the because you are you are literally falling down to earth during that. You it just your surrounding environment is pressurized and so it feels like you're floating. But in fact, you're you're you're really just falling closer to Earth. Like when the plane goes down, you are
Speaker 2:Yeah.
Speaker 1:You are descending. There's no there's no machine on Earth that will effectively like levitate something and and reduce the force of gravity to zero on earth or or even or even reduce it significantly.
Speaker 11:Yeah. But it's like, that's the the whole thing is like from the observer, it's the same.
Speaker 1:Yeah. But for for space manufacturing for like growing a crystal
Speaker 11:The reason that you can't do it on earth is because it's too like, it's not long enough time.
Speaker 1:No, no, no, I I think that I think that even if you even if you tried to do something in that in that plane scenario, like you're still subject to the force of gravity. Even though you're because you're effectively falling. Even though you're not even though you're not feeling like the relative the wind speed, you still are under the force of gravity. I don't know. We'll have to figure it out.
Speaker 1:We'll have to have
Speaker 2:Delo back
Speaker 1:and explain it to us. Anyway. What's your what's your one week one week review of GPT five? What's your takeaway? Jordy?
Speaker 2:I've been I've been it's been fine. It hasn't been that drastic. I I still find myself navigating between different models using the switcher.
Speaker 1:Have you turned on the legacy models? In the so if you go
Speaker 2:I haven't gone into the hidden No.
Speaker 1:So, Tyler, you have though. Explain.
Speaker 11:Yeah. So if you just go into settings, you can turn on legacy models.
Speaker 2:So all I have in legacy models is four o.
Speaker 1:So so four o came back as a drop down, but you can go into the settings and turn on legacy models and then you can access 45. Right? Yeah. 45 still
Speaker 11:And 410304
Speaker 1:menu. Oh, so you can access them all. But it's tucked behind even more menu. I think that the Ben Thompson take was that they are that they are not being bold enough as a consumer company and telling people you know, the Henry Ford thing if I ask people what they wanted, they would have said a faster horse. You know, I I gave them one color of car black.
Speaker 1:I didn't ask them for input on that. Steve Jobs did the same thing famously with with Apple, made a bunch of bold product decisions, and then just said, consumers, I don't I I'm not taking input. You want you want a headphone jack? Too bad. I'm taking it away.
Speaker 1:You want an extra port on your MacBook? You want what what was the thing they they took away? They took away all the ports for a while. They had no ports for a while. Was just USB c ports on the edge.
Speaker 1:And so and Facebook's been similar with the with the removal of the original feed and then the and then they they moved away from a chronological feed to an algorithmic feed and there was a lot of pushback for that. But Mark Zuckerberg channeled a mentor of his Steve Jobs and said, you know, I know that this is better for the long term. I know that this is better for everyone in the long term and that people will ultimately love this. And think that's probably
Speaker 2:I mean, the main thing is it's very interesting that they this was reported by Alex Heath in The Verge last night. Apparently, he got dinner with Sam Altman, think, and and Greg as well or some other executives. And they said last night about an hour before the dinner started, OpenAI pushed an update to bring back the quote unquote warmth of four o
Speaker 1:Yeah.
Speaker 2:Which is what the Reddit, the Redditers of the world, the AI Yeah. Is my boyfriend Yep. Enthusiasts were clamoring for. Yep. So it's interesting to see how quickly they folded there.
Speaker 2:Yep. I think yeah. Clearly, they made users distraught. Yep. I also think of I imagine a lot of those users were paying the top tier subscription.
Speaker 1:Yep.
Speaker 2:And I I, you know, again, it's hard to read too much into Reddit or really anything you see online, but a lot of people were canceling or threatening to cancel if they didn't bring that functionality back. So anyways, Sam
Speaker 1:I mean, I would expect going forward like constant changes and iterations just like the YouTube algorithm is constantly changing. The x algorithm is constantly changing. Yeah. These these updates get pushed very incrementally. There's constantly tweaks that are happening.
Speaker 2:So Sam is quoted saying, think we totally screwed up some things on the rollout. On the other hand, our API traffic doubled in forty eight hours and is growing. We're out of GPUs. ChatGPT has been hitting a new high of users every day. Mhmm.
Speaker 2:A lot of users really do love the model switcher. I think we've learned a lesson about what it means to upgrade a product for hundreds of millions of people Yep. In one day.
Speaker 1:Yeah. It's always tough.
Speaker 2:He pegged the percentage of ChatGPT users who have unhealthy relationships with the product that way under 1%.
Speaker 1:I agree with that. That sounds right.
Speaker 2:But acknowledged that OpenAI employees are having a lot of meetings about the topic. Yep. Quote, there are people who actually felt like they had a relationship with ChatGPT. And again, in this article, this post that we read yesterday on the show that he posted eight years ago called The Merge Yeah. Talking about the inevitable point that humans and machines merge.
Speaker 2:He said, the merge can take a lot of forms. We could plug electrodes into our brains or we could all just become really close friends with a chat bot. So he was aware, you know, credit to Sam for calling this one pretty much perfectly because clearly, you know, it's it's millions and millions and millions, you know, even if it's way under 1% and this is, you know, tens of millions.
Speaker 5:Right?
Speaker 1:Yeah. At least million. Hundreds of millions of daily users, yeah. Probably like under a million. So hundreds of thousands of people, that's a lot.
Speaker 1:That could have Yeah.
Speaker 2:Okay. Way under 1%. So millions of people.
Speaker 1:Maybe. They're not quite at a billion active users. So and then and then a lot of those user international in terms of like the I mean not that really matters, want to be keeping everyone healthy, but yeah we're talking about like hundreds of thousands of people that are potentially negatively affected. So they got to drive that to you know point 1% and then point o 1% and then you know get as close to zero as possible. There's always going to be some people that you know use they they read the newspaper and they go crazy.
Speaker 1:But Yeah. You know the more that you can do
Speaker 2:the better. Sam says you will definitely see some companies go make Japanese anime bots because they think they've identified something here that works. Yep. You will not see us do that. We will continue to work hard at making a useful app and we will try to let users use it the way they want Yeah.
Speaker 2:But not so much the people have really fragile mental states get exploited accidentally.
Speaker 1:Well, as they continue to iterate on the product, they have to use figma.com. Think bigger, build faster. Figma helps design and development teams build great products together.
Speaker 2:Go make something else
Speaker 1:From that we make the chat for Ben. Ben Koehler, our producer was recently followed by Reid Hoffman. And the question is, did Ben get any Hoffman chat? Did he slide in the DMs or did he just follow you for updates?
Speaker 11:I think just for updates.
Speaker 1:Just for updates. If you're not following Ben, you gotta follow him. He posts Constantly. He posts constantly during out throughout the show when big things happen, when crazy stuff's happening on the stream. He's kind of like the the the premium feed.
Speaker 1:Like you know, we put a lot of stuff on the main account. Ben's the behind the scenes guy. So go follow him.
Speaker 2:He's back here too. The whole Lads, lads, slads.
Speaker 1:So my my final takeaway from the Death Star vague post is that is that there was viral image when in the lead up to the GPT four launch is this data visualization, we can pull it up as the first slide in the deck. It it was visualizing the number of parameters in the model and this went very viral multiple times. So it was GPT three had a 175,000,000,000 parameters, and GPT four had a 100,000,000,000,000 parameters. And so you see the small dot and then the huge circle. And a lot of people were afraid by this, and it was kind of this indication of exponential takeoff.
Speaker 1:And we really did see a qualitative improvement in just scaling up the pre training run from GPT three to GPT four. But GPT 4.5 taught us that pre training scale is in fact not all you need. And the way to make a great AI product in the modern era is a mixture of techniques, experts, and researchers. You need a whole host of things, particularly with GPT five. It feels like they RL'd on a lot of different problems.
Speaker 1:And so to me, the Death Star post represents an even bigger circle from that GPT four circle. So the the Death Star is the biggest possible circle, and it's and it's an it's an expansion of that GPT three, GPT four, GPT five
Speaker 2:But couldn't you read this that GPT five is No. The
Speaker 1:GPT five is the Death Star, or the perception of GPT five as just being a bigger model is the death star. OpenAI blew that up. They blew up the metaphorical big circle with a model that isn't just bigger. Semi analysis called said the the release is the router. The router is the release.
Speaker 1:And what that means is that the the gain in in the value delivered by this product is not just a bigger circle. It's it's a more complex coordination. It's it's it's all the different x wings working together in tandem. And then the Millennium Falcon comes in and saves the day. That's the that's the that's that's when, you know, the the model router triggers a reasoning step and it thinks for a long time.
Speaker 1:The death star is the end of the pre training scaling law.
Speaker 2:Yeah. Let's get into some more coverage here from Alex. Heath, Sam says, you should expect OpenAI to spend trillions of dollars on data center construction in the not very distant future. He confidently told the room. We have to make these horrible trade offs right now.
Speaker 2:We have better models and we just can't offer them because we don't have the capacity. We have other kinds of new products and services we'd love to offer. So obviously, agent making that more widely available Yep. I think is what he's alluding to. He also thinks we're in an AI bubble.
Speaker 2:Risk bubble. When bubbles happen, smart people get overexcited about a kernel of truth. Yep. If you look at most of the bubbles in history like the tech bubble, there was a that there was a real thing. Tech was really important but the internet was a really big deal.
Speaker 2:People got over excited. Are we in the phase where investors as a whole are over excited about AI? My opinion is yes. Yeah. Is AI the most important thing to happen in a very long time?
Speaker 2:My opinion is also yes. Yes. So he obviously, you know, contributed to this excitement in a
Speaker 1:Sort of. Yeah.
Speaker 2:I I would say that he
Speaker 1:He didn't invest in very many competitors. And if there's a power law here, it could play out like the social media bubble where there was there was an immense amount of excitement around Facebook cracked it. It's on the way to be a trillion dollar company. And there was a belief for a while that that it would be oligopolistic and Twitter and Foursquare and Pinterest and Snapchat would also be trillion dollar companies. Yep.
Speaker 1:But that didn't happen. And if you invest in
Speaker 2:I'm just saying I'm just saying companies
Speaker 1:that unicorn valuations, you have not seen fantastic return on invested capital as opposed to I just think it's
Speaker 2:fair fair to say that Sam helped get people overexcited and that in many ways he was saying, you know, with with with GPT six we might be, you know, discovering novel physics and
Speaker 1:curing what? Who's the we there? Is the we open AI or is the we every company that's raising in the valley right now? It's a
Speaker 2:It's important distinction. For open AI but I think people are gonna naturally
Speaker 1:Yep. Totally. No. I agree.
Speaker 2:Take that as as AI as an industry broadly in terms of its potential. Yep. You know? So people might start thinking, yeah, maybe the twentieth best LLM Yep. Has a good shot
Speaker 1:Yep.
Speaker 2:At curing cancer.
Speaker 1:Yep. But the twentieth best social network was was not worth one twentieth of Facebook. It was worth Yeah. One two thousandth of Facebook or one twenty thousandth of Facebook. And that's the nature of these power laws.
Speaker 1:But my my take is that so the the model, the the release being the router and this shift towards OpenAI potentially shifting into dominating agent to commerce, having a monetizable free tier. This is actually a bull case for super intelligence. A lot of people on the timeline were like, oh, GPT five was was supposed to be like, you know, an order of magnitude gain, something really qualitative. Like, you use it and just feels different. It just 100% on all the benchmarks, whatever.
Speaker 1:It wasn't that. It felt very incremental. And a lot of people were kind of, you know, we're plateauing all of that. But I think that I think that shifting to a shifting to a freemium model, a monetized free tier is actually a bull case for building the trillion dollar cluster. And my thinking goes like this.
Speaker 1:So you can you can build the first GPT two, GPT three cluster with nonprofit donations. Like a $100,000,000 gets it done and that advanced them to that stage. But to do the GPT four training run, they could not marshal the capital in the nonprofit space. They had to become the for profit. They had to get venture dollars in.
Speaker 1:And yeah. And so basically, the Shoggoth demanded capitalism. This is the Nikolayn take that artificial intelligence was sent back from the future to to invent capitalism. Have you heard this take? It's great.
Speaker 1:And so the idea is is, you know, like you could not get to GPT four, GPT five without a for profit company with the promise of return on investment. And so you pulled in all the venture dollars. The question is to build a trillion dollar cluster. I think Masa is going to be tapped out soon. I think Masa is a card you can play once.
Speaker 1:I think that there is a limit to to how much capital you can marshal in the the private markets, even in the public markets. I just think it's impossible to raise a trillion dollars necessarily, and that cluster must be must be funded by free cash flow. It must be funded it must be underwritten by a company that can justify a return on investment from their direct product. And so we're seeing this right now with Google and Facebook and Yeah.
Speaker 9:Looking a
Speaker 1:investing their free cash flow. Yeah. They're investing their free cash flow. Yeah. They're doing some some some debt.
Speaker 1:But I think I think to get to the really, really big numbers, the trillion dollar cluster, it's going to have to be built on just continual free cash flow investment from a company. Tyler, what
Speaker 2:do you got, Tyler?
Speaker 11:What do you think about, like, situational awareness, like, nationalizing labs? You think governments can
Speaker 1:fund nationalize intel. So maybe that's a a path down the road. I don't I don't know. I I I don't I don't think it's on the horizon anytime soon. Mostly because We're we're we're we're just not seeing capabilities that would threaten.
Speaker 1:I I it comes So
Speaker 2:so a week ago
Speaker 1:Yeah.
Speaker 2:When that reporting from the journal on Leopold's Yeah. Situational awareness Yep. Is just dragging him, dragging him, dragging him
Speaker 1:being like Why his is he long into?
Speaker 2:His fund is probably fund blown up already. It's up 21% in the last five days.
Speaker 1:Oh my god. Wow. The gong for Leopold Aschenbrenner and situational awareness.
Speaker 2:Anyways, some more there's some more interesting I stuff in
Speaker 1:I I don't see it happening until the labs pose a threat to the US government in some way and and are and are so dominant. I I I I don't think we're at that phase.
Speaker 9:We're We're getting
Speaker 2:into the danger zone there.
Speaker 1:We're in like new new Google territory.
Speaker 2:It's a dominant consumer app. I I don't think So there's some more interesting Yeah. Reporting here from Alex. He says, Sam confirmed recent reports that OpenAI is planning to fund a brain computer interface startup to rival Neuralink. I think that neural interfaces are cool ideas to explore.
Speaker 2:So Sam, I would like to be able to think something and have chat GPT respond to it. Mhmm. And of course, I think it was the Financial Times who was reporting that Sam Altman would be a co founder of of this company Merge. Does Fiji Simo joining OpenAI to run applications imply there will be other standalone apps besides ChatGPT? Sam Altman says, yes, you should expect that from us.
Speaker 2:He hinted at his social media ambitions, I'm I'm interested in whether or not it is possible to build a much cooler kind of social experience with AI. He also said, if Chrome is really gonna sell, we should take a look at it. Alex says, well, Altman has a lot of interest. It's not clear it's not actually clear that running OpenAI over the long run is one of them. Sam says, I'm not I'm not a naturally well suited person to be a public company CEO, he said at one point.
Speaker 2:Can you imagine me on an earnings call?
Speaker 1:Yeah.
Speaker 5:I then
Speaker 2:I think we figured
Speaker 1:it out.
Speaker 2:Alex then asked if he would be CEO in a few years. Sam says, I mean, maybe maybe an AI is in three years. That's a I long love it. It's great. Some other
Speaker 1:You know what else? I love 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 program.
Speaker 2:So a few more points in here. Altman had notes on making GPT five. We had this big GPU crunch. We could go make another giant model. We could make that and a lot of people would want to use it and we would disappoint them.
Speaker 2:So we said, let's make a really smart, really useful model. Yep. But also let's try to optimize for inference costs. I think we could did a great job with that. Yep.
Speaker 2:Obviously, they're the you know, we're clearly wanting to be more competitive with Claude in Anthropix API business. Yeah. On the AI device with Johnny Ive, Sam said it's gonna take us a while, but I think you'll think it is very worth the wait. I think it is incredible. You don't get a new computing paradigm very often.
Speaker 2:There have been like only two in the last fifty years, so just let yourself be happy and surprised.
Speaker 1:Only two what?
Speaker 2:New computing paradigms.
Speaker 1:Oh, yeah. Yeah.
Speaker 2:He says, so just let yourself be happy and surprised.
Speaker 1:In the last fifty years, he says?
Speaker 2:In the last fifty years.
Speaker 1:PC era, mobile Oh. Cloud. I guess mobile and cloud are tied together.
Speaker 2:He's Yeah.
Speaker 1:And Thompson killed.
Speaker 2:On the future of web and publishers, Sam says, I do think people will go to fewer websites. I think people will care more about human crafted content than ever. My directional bet would be that human created, human endorsed, human curated content all goes up in value dramatically.
Speaker 1:Let's go. Let's hear it for our livestream. Human curated. Human
Speaker 2:handmade. Handmade. Seriously. Mean, okay. What AGI means?
Speaker 2:Sam says, maybe the milestone that's most relevant to us is when most of our researcher research cluster is allocated to the AI researcher instead of the human researchers.
Speaker 5:Sure.
Speaker 2:But I don't think that's gonna be so binary because I think it'll feel like people get a little more help and a little more help and a little more help. Yep. He also said if we didn't pay for training, we'd be a very profitable company.
Speaker 1:That's a good question. So Tyler, have you thought more about what happened to GPT four point five?
Speaker 11:I've I'd people it it's like people always say, like, oh, it was so bad. And same thing with Judy five. It's like okay. Do remember when we had Jack on Yep.
Speaker 9:And he
Speaker 11:talked about his blog. It said GPT or 4.5 is like as good as we should expect. Yep. Five is the same thing. I think it's a good model.
Speaker 1:Yep.
Speaker 11:If you wait. Okay. If you would please consult the graphs. Okay. Pull up the meter.
Speaker 1:So my question with GPT 4.5 is I understand that it's as good as we should expect. The question is just, is it in the money? Because GPT two was also on that curve and deeply unprofitable. Right? They had to pay not a ton of money to train it and it made basically no money because they didn't even sell it as an API.
Speaker 1:Remember we talked to Greg Rockman, he was like, we had to pay people to use our models. Then all of a sudden the three point five three point five DaVinci came out. Some people were using that. They might have spent, I don't know $10,000,000 training GPT three, three point five, and some people paid for it. They probably made their money back.
Speaker 1:Who knows? Then GPT four, they do the big training run, the 100,000,000,000,000 parameters, the big circle. And that has to be one of the most profitable training runs ever because they maybe spent a $100,000,000, but they are making a billion dollars a month inferencing it. And, like, the inference cost is probably gross margin positive, more or less. But 4.5, they probably sounds like they paid a billion dollars to train it, something like that.
Speaker 1:A lot of money to train this big model. And it's expensive. And yes, it's better, but it's not better to the point where people are willing to bear the cost of inference for it. So it's kind of mothballed, and you can see that in the app. It's like Yeah.
Speaker 11:But it it's like, okay. It's worth one AI researcher. I mean, I I think that the value of the, like, r and d, like, the knowledge that they now have Totally. Training the next model
Speaker 2:Yep.
Speaker 11:Is probably worth a billion dollars
Speaker 1:Totally.
Speaker 11:If you consider a researcher's worth billion dollars easily.
Speaker 1:100% worth doing. 100% not a big deal for their financials. Not a big it's just interesting that we went from a paradigm of like like the big the like the big training run was unprofitable, then it was massively profitable, then it went back to being unprofitable. And the profitable research that they were doing shifted to some RL that they did on, you know, hallucination to reduce the hallucination rate. Like that RL run, probably not a billion dollars in in training cost.
Speaker 1:I don't know. But it's clearly making the the product better. People are gonna use Chateapiti more. They're gonna be more likely to upgrade. And and if the hallucination rate is lower, people are gonna trust it to go shop for me.
Speaker 1:And they're gonna make a ton of money off of that. Right? Just an interesting dynamic. I
Speaker 5:don't know.
Speaker 2:Yeah. I I mean, I think a lot of people were were like singling out this quote. If we didn't pay for training, we'd be a very profitable company and just, you know, obviously, it's easy to poke a little bit of funny that
Speaker 1:He's gross margin positive. No.
Speaker 2:No. Yeah. No. I know. That's what said.
Speaker 2:But it but still anytime you have a CEO being like, if we didn't have this cost, we'd be profitable. It it's it's always Yeah.
Speaker 1:I mean, the follow-up on on
Speaker 2:the earnings call. But the Sam, any plans
Speaker 1:to stop training then?
Speaker 2:Well, yeah, exactly. So we Because we've
Speaker 1:net net profits.
Speaker 2:You know, this is what Everett said and this is what we said Yep. You know, in in to the GPT five launch is that the product is now the most important thing And what Everett Everett said just now is that, you know, you could you could swap in much cheaper models even open source models and people would still be Yep. Using the product in the way that they are. Last quote from Sam from Alex's coverage. He says, I don't use Google anymore.
Speaker 2:Legitimately cannot tell you the last time I did a Google Mogged. Search. Mogged. Yeah. And this is so this is the interesting thing.
Speaker 2:Right? In in when you think about the browser wars
Speaker 1:Mhmm.
Speaker 2:Which we went from the browser wars a month ago being like everybody's making their own browser now
Speaker 1:Everyone's trying to buy Chrome. And
Speaker 2:it's still very much up in the air whether they'll be forced to sell it. Google's not gonna sell it, you know, by choice. And but it just does feel that chat GPT with with GPT or chat GPT agent is effectively a web browser already. Yeah. You're just browsing the web.
Speaker 1:Yeah. That's
Speaker 2:great. And so, I I think that the real browser war is the fact that chat GPT functions as Chrome plus Google search in a single product already. Yep.
Speaker 1:Yep. I know. I I this is a great take. I completely agree. Wild card, Truth Social buys Chrome.
Speaker 1:Truth Browser. This would be the most aligned. Yes. This would be the most aligned with the current administration. Tyler, what you got for me?
Speaker 11:Okay. So yesterday it's it's not here anymore but if you went to openingi.com slash new tab page, they like leaked this page. Mhmm. Like not on purpose, someone just found it. Mhmm.
Speaker 11:But it's basically like very close to like a a browser style where you would type in and then they would like auto fill some Yeah. Possible questions. Then you could like save like links and stuff. So like it very much looked like the the Chrome
Speaker 1:Yeah.
Speaker 11:Like home page.
Speaker 1:Yeah. I I I wonder in the context of mobile I mean, using using generative AI to generate code in HTML has just completely pilled me on the the the generative UI elements. And I feel like like I I would probably be less interested especially since I I mean I use ChatGeePeeT mostly on my phone. I I use Chrome mostly on my computer, on my Mac. And so and so I wind up like it's a very different style of working and I could imagine that the evolution here is not the ChatGPT app likes opening iframes and and Safari web views and surfacing something that actually renders the native HTML.
Speaker 1:It's more like it scrapes all the HTML from a website into the the reasoning chain. It gets all those tokens and then it kind of just like reinstantiate reinstantiates the the UI in like native elements and kinda cleans it up for me. And so I'm getting like a hybrid of like ChatGPT used to just be pure text response, then it became text response and it also has links in there now and it also has Commerce. Yeah. It also has it has tables and it can it can put in images now.
Speaker 1:And if you search for a product, it can share like little preview images with a link. And so they're hydrating like the tokens
Speaker 2:And think about how bad Yeah. 99% of websites are.
Speaker 1:I completely agree. And They're so bad.
Speaker 2:It's hard navigate them. There's pop ups and things like that.
Speaker 1:There are people that that deliberately browse the web with JavaScript turned off because it forces websites into a more like usable plain text experience. And and most websites have a have a have a fallback in case JavaScript's not working or blocked. And so you can wind up going to the United Airlines checkout and and it'll be just like normal buttons instead of like the pages jumping around refreshing pop ups, all that stuff. All that stuff gets turned off and some people Cookies. Haven't done cookies.
Speaker 1:Yeah. Anyway, if you're trying to improve your website, you're managing your GitHub installation, you gotta get a graphite code review for the age of AI. Graphite help teams helps teams on GitHub ship higher quality software faster.
Speaker 2:Well, pull this up in the timeline. What do you wanna talk about? Boys, we have a post here from the New York Stock Exchange, otherwise known as the New York Style Exchange. And here we are.
Speaker 1:Let's go. Nice seeing
Speaker 2:President Lynn Martin stuns in the TBPN Spring Summer twenty Lynn. '20 Collection.
Speaker 1:Thank you for acting as our model for this this season's TBPN collection where
Speaker 2:We really designed it Proud
Speaker 1:to have you as well.
Speaker 2:For tech and finance leaders that that are, you know, dedicating their lives to improving capital markets
Speaker 1:Yeah.
Speaker 2:And maintaining American dominance Yeah. Globally.
Speaker 1:That was the North Star with the with the with the collection.
Speaker 2:Patagonia is like, oh, this was designed for your next hike. Yeah. This was designed for Everest. Well, this was designed for the trading floor on an IPO day.
Speaker 1:This was designed for the hike up to that bell. Exactly. And for the Mount Everest of capital markets.
Speaker 2:For that next gong.
Speaker 1:New York Stock Exchange.
Speaker 2:For the gong hit that retires the next TBP and Gong.
Speaker 1:Yes. Exactly. Exactly.
Speaker 2:We have I think we can skip over this coverage from the Wall Street Journal. They said OpenAI's Rocky GPT five rollout
Speaker 1:I just want
Speaker 2:to put this in the truth struggle to remain Yes. So the the art this article which was released a couple days ago, the title is OpenAI's Rocky GPT five rollout shows struggle to remain undisputed AI leader. And
Speaker 1:It's basically just coverage from a bunch of people complaining and it doesn't capture any of the actual underlying
Speaker 2:Doesn't feel like they're struggling to remain the undisputed consumer AI leader. I think you could argue that Yeah. There's certainly a much closer race in cogen.
Speaker 1:Yeah. So I yeah. I'm I I I I put that in just as a reminder to talk about GPT five. Yeah. The the the real news is the Financial Times has a story on deep seek that isn't isn't super deep in terms of the coverage, but there are some interesting tidbits in here.
Speaker 1:So the the article is DeepSeek's next AI model stalled by Beijing push to take up Chinese chips. We talked about this a little bit with the NVIDIA h 20 now available in China and what that means for for for DeepSeek. So DeepSeek, obviously, everyone should know is the disruptive Chinese open source frontier reasoning model maker from High Flyer. They were in the high they were in the high frequency trading business, then they decided to go into foundation model training, and they developed and they developed a very, very solid open source language model very quickly, and it surprised everyone. We started talking about Jevan's paradox and the idea that cheaper AI will just wind up driving more and more adoption.
Speaker 1:We've certainly seen that. And the sell off that happened in the AI trade in the public markets came rip roaring back and NVIDIA rocketed to over a $4,000,000,000,000 valuation after they'd sold off slightly after the DeepSeek news. So apparently, they've been trying to get this r two release out, the next version of their of their reasoning model, and they're having a hard time because allegedly they're using chips from Huawei. So China, the CCP, and Beijing has pushed DeepSeek to switch from Nvidia to Huawei. Everyone suspected
Speaker 2:And it was and it and it's it's not technically illegal to use NVIDIA chips No. But it is politically incorrect according to one person familiar with the conversations.
Speaker 1:Currently. Yes. And and and there were export controls. There were never any import controls. So if you're a high flyer or deep sea and someone comes to you from Malaysia and says, hey.
Speaker 1:I got I got a 100,000 h one hundreds
Speaker 2:right here. You wanna buy them?
Speaker 1:You wanna sell off a truck? You're you're welcome to buy those. At least you were. Now it's politically incorrect to do so. And so Huawei hasn't really gotten the job done.
Speaker 1:Lots of recent model releases have have failed to live up to expectations. This is what happened with GPT 4.5, Lama four behemoth. Like, the models are getting more like, they're getting bigger. There's more and more integration points in the training cluster as you're actually building these out. There's power management issues.
Speaker 1:There's memory issues. There's all these different things, and that's why the AI researchers are making, so much such high salaries and the trade deals are happening because if that if there's one researcher who can tell you that line of code is going to result 20 in million. Or more or 200,000,000. Yeah. That's really valuable.
Speaker 1:And so this case shines a light on the the exact nature of the gap between Nvidia and Huawei. So when the Huawei Ascend CloudMatrix three eighty four came out, everyone was kind of saying, okay. Wow. Like, Huawei's basically caught up. It's not as efficient on a on a dollar per flop basis.
Speaker 1:Like, it it's more energy intensive. But if you're willing to spend a little bit more energy, you basically get the same capabilities. That might not be the truth. Like like, there might be actually some qualitative value to CUDA and the reliability of the drivers and the software on top of NVIDIA and actually the underlying chips as well, such that even if you have the Three Gorges Dam, you have cheap energy, you have nuclear power, China's developing more and more energy, it's getting cheaper and cheaper. Even if you have cheap energy, if you go to set up the massive data center to do the huge training run on Huawei Cloud Matrix three eighty four, you might still be in trouble and you might not be able to get the model out the door.
Speaker 1:It could be something else though. We don't really know. This is all kind of just like
Speaker 2:And it's notable that
Speaker 1:Little tidbits.
Speaker 2:Mean, it's notable that that all of these have led to they originally wanted to launch r two in May
Speaker 1:Yep.
Speaker 2:And it's still delayed.
Speaker 1:Yep. Yep. And so it'll be interesting to see how DeepSeek reacts. They could potentially say, you know what? Like we are like Huawei's just not getting the job done.
Speaker 1:We'll deal with the we'll deal with the pushback from Beijing. We're putting in a huge order for h twenties from NVIDIA. We want the best or at least the best that's available to us even though the h 20 of course is four years old at this point. Yeah. And severely nerfed.
Speaker 1:So we'll see when will they get r two out, how powerful it will it be, and most importantly, what will the cost per million tokens be? Because if we get an o three level model from DeepSeek and it's a 100 times cheaper, Even if that doesn't displace OpenAI meaningfully because OpenAI is operating at the application layer. It will be incredibly bullish for every wrapper company because all of their gross margins will flip positive very very quickly because they'll need to do some fine tuning. We'll need to see what Perplexity did where they made instead of DeepSeek they made it like
Speaker 2:Seventeen
Speaker 1:seventy Seventeen seventy six Seek or something like that. They did a fine tune on it to kind of make it more American. But the most important thing was that the deep sea researchers figured out a bunch of interesting hacks to make make just inference way way way way cheaper. Anyway, speaking of wrapper companies, application layer companies that we love. Julius, what analysis do you wanna run?
Speaker 1:Chat with your data and get expert level insights in seconds. Ask Julius. Look
Speaker 2:at this view.
Speaker 1:I love it. Ask Julius to analyze your data like 2,000,000 users have already done. Folks from Princeton, BCG, Zapier.
Speaker 2:Julius. I wish my only my the only thing I would change with Julius is I wish it was Rahul. Yeah. Or sunwalker dot ai. But, it's always time
Speaker 1:for Just like the Ford Motor Company, you know.
Speaker 2:The Sunwalker Artificial Intelligence Company.
Speaker 1:Maybe. Maybe. It could it could happen. So T York Taxis has a take on the on the the deep sea story because they think it's a confused narrative with no sources of deep sea confirming it. So T.
Speaker 1:Ortaxis says, this story is so insane. Dream narrative for burgers and I
Speaker 2:think that's an American slur.
Speaker 1:Yeah. Guess. That I might well I might well cook up my own also based on half baked rumors experience in an authoritarian society and just a little bit of sleuthing. As expected, the plot thickens. Xi Jinping's heavy handed central government approach is stalling development is the take that T.
Speaker 1:O. Taxes might be debunking here. DeepSeek was a breakout hit, but patronage networks don't reform overnight. The actual Chinese national champion in AI is, as we know, Huawei. They get unconditional subsidies and the nation's hopes are pinned on them.
Speaker 1:On a software side, it's also Tsinghua, the university and their brainchild z AI with GLMs, but Huawei does everything. In February, the party asked Ren Zhengfei to partner with major AI labs including DeepSeek and beat America at AI. They approached DeepSeek sending personnel to adopt Ascend clusters for v three inference. We've seen papers following from that, and we know these clusters now work at Silicon Flow and elsewhere. They also suggested training the next generation models on Huawei, but were privately told by probably after some experiments that Ascend that that the Ascend ecosystem is not yet mature or reliable enough and will go with h eight hundreds.
Speaker 1:Thank you very much. With the knowledge gained, they had set out to train Pangu Ultra MOE, mixture of experts, as a reproduction of v three r one and may or may not have failed at that due to interconnect issues and broad lack of competence resorting to repackaging r one with the intent to report to the party that DeepSeek had proven uncooperative. But there's nothing special there. They can do equally well and will soon surpass SAR. Now as as DeepSeek is is not releasing any rumored r two, the timeline never once made sense and that's a big issue.
Speaker 1:You need to have your timeline straight. There's renewed discussion about importing NVIDIA. They are trying to spin this too to their benefit leaking to journalists that it was DeepSeek that had failed at r two while Huawei's Noah's Ark small model lab is moving smoothly. They may know that v four is planned to come out late enough that they still have some hope of producing a more persuasive internal result. For now, they are probably optimizing cloud matrix hardware and CINN, testing nine ten d and nine twenty, and hiring people with LLM expertise.
Speaker 1:The above is an educated guess. The serious argument is that if you want to talk about the failure of Huawei's hardware, it's important to focus squarely on Huawei and not a fanciful and unprecedented narrative where historically independent startup is forced into changing their training stack by heavy handed politicians. And so the takeaway here is that Huawei might actually be significantly behind NVIDIA and it's less about the CCP saying, you know, we want I mean, of course the of course the reason the CCP is saying buy Huawei is because they want to improve Huawei and give them as many advance as many advantages as possible to get to the frontier and and provide, you know, the best AI training hardware possible. But the the the flip side is that DeepSeek is down to use anything and train on a bunch of different stuff. And really, they are, they probably, at least according to this, they really are just having trouble training on large Huawei clusters.
Speaker 1:And so they're like, let's get back in the CUDA ecosystem. Anyway, let me tell you about Profound. Get your brand mentioned by ChatGPT. Reach millions of consumers who are using AI to discover new products and brands. Get a demo.
Speaker 1:Go to profound.b
Speaker 2:like the Mag five. What did what did James say? He said The mag five? Well, you were saying like, I can't say who's using it but
Speaker 1:Oh, yeah. The fortune five.
Speaker 2:The fortune five.
Speaker 1:He's got a fortune five client. Yeah. So it's like one of five companies.
Speaker 2:I'll leave it to you guys.
Speaker 1:20% chance you just guessed it correctly. Anyway, lots of people making money on the Intel story. So the story today is that the Trump administration just last week called for the resignation of Lip Bu Tan, said that his ties to China were too much for an American champion like Intel. But Donald Trump has reversed course and called Tan a success, and the idea of the US government buying a stake in Intel is now floating around. I don't love the idea of the people that brought us the TSA running the most advanced manufacturing process humanity has ever produced.
Speaker 2:Or the folks behind the DMV.
Speaker 1:The folks behind the DMV getting in the fab, into the clean room might be a little bit of a stretch for me. But Intel does need better shareholders. There was a few years ago before the CHIPS Act
Speaker 2:Long term patient shareholder.
Speaker 1:Exactly. People were talking about, oh, we need we need an American semiconductor champion. This was during like the reindustrial ization meme kicking off. Everyone was saying this like we need American ships, and yet no one was like I'm gonna actually go build a position in Intel. And so everyone was like, yeah we need this.
Speaker 1:It was it was a What is it? A cocktail position? It was a cocktail position. Meaning something people like to talk about at cocktail parties, but they don't actually put their money where their mouth is. Yep.
Speaker 1:So you sound smart saying we need to Yeah. We need to make Intel an American champion. We need to make chips in America, But I'm not willing to put any money on the line to actually do it. And so Intel's share price has been kinda in the dumps.
Speaker 2:Well, until recently.
Speaker 1:Until recently.
Speaker 2:So Dan Gallagher in the journal says federal support could get the troubled chip maker over some hurdles but risks great harm to The US tech sector. We'll get into it. Intel definitely needs help, but the government support always comes with strings attached, and those strings in this case could ultimately trip up the Silicon Valley pioneer and the broader US chip industry. The Trump administration is discussing options with Intel that would involve the federal government taking a financial stake in the troubled chip maker. The idea came up during president Trump's meeting with Intel CEO, Lip Buutane on Monday and the discussions are still in an early stage.
Speaker 1:This is so funny after talking to Fabricated Knowledge over at Semi Analysis about like His main thing was like, the problem with the intel board is that there's too many government type people on the board. Politicians. There's too many politicians, too many famous people, writers, thinkers. There's not enough like just scientists. We need like physicists on the board and like technologists.
Speaker 1:We need like an Elon type or like you know someone who understands the actual tech.
Speaker 2:Yeah. I mean, the steel man, it's like Trump has, you know, a multi billion dollar digital asset business.
Speaker 1:I was about
Speaker 2:to He say, has a multi billion dollar social media is company.
Speaker 1:The founder of a tech unicorn. So it's not his first rodeo in the tech industry.
Speaker 2:That's right.
Speaker 1:So you got to give him some credit if he was able to get in there.
Speaker 2:So Dan says that marks a fast turnaround given Trump was calling for Tan to be fired just days ago. The news was encouraging for Intel's beleaguered investors who have watched the chip industry's once undisputed leader lose more than half its market cap in less than two years. The stock jumped 7% Thursday on the initial reports of the talks and gained more ground early Friday morning, but investors should still be wary. Intel's problems are such that even a big check from Uncle Sam won't fully solve them. The company has burned a total of nearly 40,000,000,000 in cash over the past three years trying to regain its manufacturing lead from TSMC.
Speaker 2:Intel has also been granted up to 8,000,000,000 so far in direct funding through the CHIPS Act, but that hasn't been enough. Intel's most state of the art production process called 18 a was supposed to close the gap with TSMC, but the company admitted on its own second quarter earnings call last month that 18 a will most will be used mostly for its own products, meaning few outside chip designers have found the technology compelling enough to sign on as customers of Intel's contract manufacturing service. Wall Street expects another 7,000,000,000 in negative free cash flow this year according to estimates from visible alpha. Sorry.
Speaker 1:You're really pulling double duty there
Speaker 2:on the sound board. Tann told investors in the same call that he won't commit major capital spending to Intel's next process called 14 a without commitments from external customers. Yep. Smart.
Speaker 1:We couldn't get a customer for that.
Speaker 2:Seen as tan drawing a line in the sand, a line by which he would determine whether to keep Intel in the business of manufacturing chips. Yeah. But Intel pulling out of that business would be detrimental to the government's efforts to shore up domestic chip making for national security
Speaker 1:Yep.
Speaker 2:And supply chain stability reasons. Doug over at semi analysis was talking about how the chip design business Mhmm. Seemed like it could be a target for like PE Yep. In the sense that if you came in and kind of overhaul Hawk
Speaker 1:Tan is gonna come in.
Speaker 2:Yeah. If you, you know, dramatically cut cost and really focused on serving customers and and of course raising prices, there's probably a good business there but that the foundry business was critical and we don't wanna risk losing that.
Speaker 1:Yeah. Hock Tan is the CEO of Broadcom. I just wanted to say, have a great flight, John Exley. He says he's taking off. He's landing in one hour.
Speaker 1:So and if you're trying to set up a semiconductor line, if you're trying to build or plan products, get on linear,
Speaker 2:linear.app. Great.
Speaker 1:Thank purpose built tool for planning and building products. Meet the system for modern software development, streamline issues, projects, and product road maps. So I I
Speaker 2:This chart chipped away Chipped away. Showing Intel and TSMC revenue.
Speaker 1:Ripping. So I'm I'm still I'm still sort of split on this. We have some guests on the show today to talk about the dynamic between The US and China in the semiconductor race. I'm I'm sort of open to the idea that we sort of solve The US based manufacturing of semiconductors through partnerships with TSMC and Samsung, even though those are not American companies. If they set up fabs here in some sort of, you know, negative conflict scenario, it's like, well, we still have the the factories here, even if it's run by a company in in South Korea or Japan or Taiwan, like the factory should continue to produce for the most part because most of the team that would be building
Speaker 2:And I think the pushback there is we don't have the talent which is key to staying on the leading edge.
Speaker 1:Yes. That's true. But I mean, yields at TSMC Arizona have been good so far, and it feels like we could continue to scale up. And it feels like a lot of the lot of the talent will be coming over. And so there's a little bit of like, you know, you you you start to ramp up that supply.
Speaker 1:But it does feel like Intel is particularly good at the trailing edge, but maybe that goes international, but to South America, unclear where it goes. Unclear how, at least to me, how important Intel is as like a strategic company versus just like it's one of the greatest technology companies America's ever produced. It's a crown jewel. It should just be protected because it's it's it's like good for the America brand versus like if Intel disappeared tomorrow, like how how bad would things be in America? Like would would we be able to get by with with other suppliers?
Speaker 1:Yep.
Speaker 2:So because
Speaker 1:we do have AMD, we do have we do have Nvidia, and then TSMC and and Samsung are not in China. That's not where we buy our chips from.
Speaker 2:Well, Dan in the journal says the government might for instance pressure chip designers like Nvidia, AMD or Qualcomm to manufacture with Intel perhaps as a condition for getting export licenses for China. Mhmm. And that could easily go wrong if companies are forced to use Intel's factories before they can make chips with production yields that match TSMC's. It could result in inferior products and wastage by Intel because so much silicon has to be thrown out to make a working chip. More broadly, if chip designers are using Intel fabs, even though they aren't the most advanced or efficient, the entire US chip industry could lose competitiveness that would undermine the ultimate goal of government intervention in the industry which is to maintain American technological supremacy.
Speaker 1:Yeah. The Rubicon of state intervention in chips has already crossed the administration, already signed significant leverage over Intel, has already already has significant leverage over Intel, thanks to government factory expansion grants that place limits on how it can restructure its chip design and manufacturing arms without government consent. But the federal government must take care not to go too far, lest it undermine the market model that made American technology
Speaker 2:Slippery slope.
Speaker 1:It is. But at the same time, there is there is a case to be made and I guess you know, like if you put the US sovereign wealth fund under the direction of Leopold Ossenbrenner, there is a case just for make money for the taxpayer. And this is actually the opposite of a bailout. This is what Tim Geithner got in trouble for during the not in trouble, he was ultimately vindicated during the financial crisis in two thousand eight. He went and made a bunch of loans to banks to the on the order of, like, billions and billions of dollars.
Speaker 1:And everyone was like, this is a bailout for Wall Street. This is a bailout for the banks. But he actually only invested in the in the banks that made it through the crisis. And so those those loans, those backstop debt instruments were paid back with interest, and so The US taxpayer actually made money on those deals. It feels a little weird, but but but the same thing could happen here.
Speaker 1:Like, Intel's a $111,110,000,000,000 dollar company. If The US invests and is able to do things to turn it into a $300,000,000,000 company, well like that's an extra three x for The US taxpayer. And it doesn't it doesn't actually result in any, like, lost money. If
Speaker 2:Trump can just get three three x's and and string like a 100 of those together Yes. In a row Yes. We'll solve the the whole, you know, federal debt
Speaker 1:That's a high water mark. I think I think you should be targeting, you know, a nice five x fund for the first run then raise 10 x more and then scale up and then, you know, start start deploying the big the big money. The big money. You should buy 100% of intel. What you got,
Speaker 11:Tyler? This is like we should give put Jane Street, you know, high frequency lawmaking. Yes. It's optimized for GDP.
Speaker 1:Direct right access to the legal code. Yeah. Any anything they can do to just maybe one of the foundation labs actually. Instead of nationalizing the labs, we need to we need to, you know, corporatize the government and let and and do a reinforcement learning environment with a verifiable reward. The verifiable reward
Speaker 11:being stock market Or L for business but the business is the government.
Speaker 1:Exactly. So what what what can you what can you change in the legal code to make the stock market go up? And so, you're just feeding off of that constantly rewriting the legal code.
Speaker 2:Well, zoomer at zoomy zoom has been going viral again. He's why AI is a house of cards. He has an entire thread breaking down these sort of chained losses that we've been talking about. And he's getting community noted Mhmm. Quite a bit.
Speaker 2:One h someone added one h 100 can serve thousands of users at once depending on batch size and model. For inference, you don't dedicate a GPU to a single user. You load the model then stream requests for many users in parallel. Other numbers in this post are also wide wildly widely exaggerated.
Speaker 1:Yeah. This might have come from a group chat originally that was maybe not fully fact checked but you know, told told a compelling story. Yeah. It was fun with it.
Speaker 2:And Nick Carter says compelling threat if you ignore that inference gets 10 to a thousand x cheaper every year. If you're willing to pay $200 a month for AI and VC funding sub and VC funding subsidize half of that simply wait six months. I would say, you know, mister Randall earlier on the show said it's actually not all of a sudden getting 10 or a thousand x cheaper at least for Frontier models. But the point he made is that a lot of prompts could be served with older, cheaper models, and that's gonna be a big focus. I mean, clearly, was a focus for OpenAI with the recent launch.
Speaker 1:Yeah. I I I dug into this to see, you know, how would we really hit a thousand x cheaper this year on on the models? And and would the would the gross margin profiles of these AI companies flip extremely quickly? Or is it more like a five year change to really optimize this stuff? I'm I'm kind of split on it.
Speaker 1:I you know, the charts that Nick Carter shared here are are pretty compelling. I just hope that the that the trend continues because the the dynamic of reasoning models and test time inference is slightly different, like you are just it's it's algorithmic driven. It's more just throwing raw compute at it and generating a ton of tokens. So I don't know. Tyler, what what do you think you're closer to 10 x cheaper inference every year?
Speaker 1:Thousand x cheaper inference every year? What type of gain in cost per token do you expect over the next few years?
Speaker 2:Don't make mistakes.
Speaker 11:Do do you mean in what what models are you talking about? Like frontier level models?
Speaker 1:All the models. But
Speaker 11:I think frontier will probably stay similar price, and then you'll just see, like, over time. Like, now we have open source models that are easily as good as, like, two years ago. Yeah. Right? You have, like, four o,
Speaker 2:which is super cheap.
Speaker 1:Doesn't mean free. Like, it it means free, no license, but you still have to inference it on an NVIDIA GPU that costs money. And you have to spend electricity that costs money. Just open sourcing a model does
Speaker 11:not Yeah. But but when you open source something, you can like distill it even further. You can like Yeah. You get some, you know, optimizations there.
Speaker 1:Okay. So o three pro. Let's call that like an expensive frontier model. How cheap do you think that is next year? Do you think it's 10 times cheaper?
Speaker 1:Two times cheaper? A thousand times cheaper?
Speaker 11:Like an equivalent model of o
Speaker 2:Yeah.
Speaker 1:O three pro heavy reasoning, thinks for ten minutes, generates tons of tokens. Closer to
Speaker 11:two a single year. Or I'm probably closest to two x. Two
Speaker 1:x. Yeah.
Speaker 11:I wouldn't say massive gains.
Speaker 2:Well guys, I hate to interrupt but there's some breaking news. Williams Zhang is proud to announce that he's the reigning OpenAI McNugget champion. He ate 55 nuggets
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Speaker 1:And we have our third guest of the stream since we already did the debate. We have Bill Bishop from Cynicism. How are doing? Scientist. How are how
Speaker 4:are you? Thanks for having me.
Speaker 1:For hopping on. We really appreciate you taking the time. Give us I mean, I'm super familiar with your work. Think everyone should be. But give give us the high level of the pushback that you saw yesterday.
Speaker 1:We enjoyed having you in the comments. And I I wanna know how you would frame the counter argument to what Aaron Ginn was making yesterday.
Speaker 4:Great. Well, thanks for having me. And I I'm impressed that you guys respond to jerk comments. That's good.
Speaker 1:I don't see it as
Speaker 4:jerk comments.
Speaker 2:Well, yeah. We don't see it. I I think it's extremely fair pushback.
Speaker 1:A 100%.
Speaker 2:We understand. Okay.
Speaker 1:When when I have Aaron Ginnis Aaron. I see it as having Jensen Huang on the show.
Speaker 4:Okay. Well, that that that is that is how I see it too. So that's great.
Speaker 1:And and and and I I can't have air I I can't have Jensen come and whiteboard out pros and cons with me, and I can't throw random jokes at Jensen all day long, but I can to Aaron. And so I enjoy having him sit there and I can throw stuff at him. And of course, he has he has his opinions and his his arguments. But it's great to have somebody that can speak the language of Nvidia.
Speaker 4:So Yeah. No. And and I again, I I think thanks for having me. I'm psyched to see you guys on Substack two, which is great. Yeah.
Speaker 4:And I see you're running a show today. You got two great guests, Jimmy Goodrich and Leonard, who are Yep. Gonna be way better on the on on sort of this discussion. So I think that What I would say is what's been interesting to to watch, and and I think talking about the the reversal on the h 20 trip. We got our h 20 trip from the video.
Speaker 4:We gotta remember, right, the there was a proposal teed up for the Biden folks to ban the h 20 Yep. And they never did it for whatever reason. Trump comes in, actually bans it, so it looks like he's being more hawkish. And then a couple months later, because of really effective lobbying from NVIDIA and specifically from Jensen Huang at the principal level at the you know, to the president, to David Shapiro.
Speaker 2:I mean, it's not even it's not even traditional lobbying because they're only they're they're spending,
Speaker 1:like They're spending
Speaker 2:a million dollars on probably lobbying.
Speaker 1:10 times that on Jensen Huang's, like, flight schedule.
Speaker 4:Flight schedule. Right. No. It's it's brilliant. They they sort of, you know, disrupt the lobbying business, go right to the decider.
Speaker 1:Go
Speaker 4:direct. And and how the narrative has shifted. And so so Trump, on the one hand, looked like he was tougher on China, then he backs off, and then, of course, he gets a bunch of flack for, oh my god, he's caving to China, he's caving to Jensen. Right? Yep.
Speaker 4:When it when in fact, he he sort of did what Biden didn't do, and then, because of this personal interaction and the personal effort from Jensen Huang, he reversed course. And, I think it has to be seen in the context of the broader, where I think there was a correct decision, the rescission of the AI diffusion rule, right, which was really, you know, David Sacks was, I think, a big advocate of getting rid of that rule with a Biden administration rule that was gonna limit countries that could buy NVIDIA GPUs, right? The idea that The US needs to lead, The US needs to be out there competing with China, not just limiting, and the way to do that is to get people hooked on US, The US AI stack, specifically Nvidia globally, ex That makes a lot of sense. The China decision on h 20, I think is flawed. The idea that, oh, we're gonna keep China hooked on Nvidia by selling them h 20 and then I think, know, the Jensen Huang is lobbying to sell sort of the next somewhat nerf chip.
Speaker 4:Right? A little better, but but still not near the the top of the NVIDIA product suite. The idea that just NVIDIA is better, CUDA is better than the Chinese the Chinese hyperscalers, you know, the the the Alibaba, Tencent, ByteDance, DeepSeek, they're gonna wanna stay with NVIDIA. Makes sense in a world that is sort of a normal political economy, a normal competitive world, doesn't make sense in the context of a world or a market that's run by the Chinese, you know, the Communist Party of China. And Xi Jinping made very clear in April at this polyp year study session that was about AI, specifically said he wants China to build its own indigenous AI stack.
Speaker 4:And so, they understand very well this idea that, you know, Nvidia wants to hook their companies on Nvidia hardware, the party wants self reliance. And so, this idea that we need to compete, America needs to compete by selling into China, and therefore they're addicted, they won't break it, that I think is fundamentally naive and misunderstands how the party operates. I think what it does is it helps China fill the gap between where they are now in terms of lagging capabilities and lagging output or quantities in terms of the Huawei chips. It gets them to where they need to be over time, but they're gonna be only intensifying their efforts to strip out Nvidia, to to break any reliance on the USAI tech stock. And so, by selling h 20 chips now, we're just helping China keep in the race, when in fact, if they didn't weren't able to get to h twenties, it would probably, I think, would help maintain a lead, if not start accelerating into and accelerating some amount of separation.
Speaker 2:What what's your reaction to the commentary showing that the the CCP is actually, like, actively pushing back against deep seek which is you know the clear open source or or maybe not totally clear but an open source
Speaker 1:is also
Speaker 2:very open source leader.
Speaker 1:But yeah. Your your reaction to the news that the that Beijing asked Latin Chinese Foundation Labs do not buy NVIDIA. Right.
Speaker 2:Even if it means delaying like cards too. So
Speaker 4:there was a Financial Times report yesterday where it Yep. It said they were encouraged. We we'd to know what what the encouragement really But, yes, they were encouraged to use the Huawei. I think it was the the latest Ascend chips Yep. Which were all based on dies that were illegally fabbed at TSMC, where Huawei used a cutout company that was related to Bitmain called Softco to get I think it was 2,000,000 daires from TSMC that they can't make on their own in China.
Speaker 4:Mhmm. And even then, they're still not where they need to be. And so, I think that this goes You you have that news, you have the news since the announcement by the Trump administration that they were going to allow, again, licenses or or give licenses to sell h 20 to China. You've had significant pushback from some of the regulators in China, you've had talk about the chips are unsafe, maybe they have backdoors, they're environmentally unfriendly, there are security risks. And so, I think what you're seeing, you know, there's different hypotheses about what's going on on the pushback on the h 20, it's maybe they're trying to negotiate for the better chip.
Speaker 4:I personally think it's actually more of a manifestation of parts of the system really just are like, we need to stop this reliance on American chips, we need to make sure we're focused on building our own pathway to self reliance. And that in, I think, is related to that news that deep seek is being encouraged to use these lesser chip, even if it delays them, because ultimately, when they figure out how to use them and, you know, the report said Huawei has engineers on-site trying to work through it, Ultimately, that will help China because that will help them solve over time the various bottlenecks they're facing. What I think
Speaker 2:You can read into it and and one way you can read into it is that the CCP doesn't believe in the fast takeoff scenario, know, like runaway AI in the next two years. Right? Which I think broadly, I don't know a lot of people that still believe in that, but it's notable. No. I I think that I think that's right.
Speaker 4:I think this is more of a we're gonna we are gonna set the foundation for doing it in a self reliant way, even if it takes us longer. And so, that's where I think what's been interesting to watch in Nvidia, is how the narratives have shifted in DC, where the Nvidia line of we have to compete, we have to compete, we have to sell them to China, have to addict them, is basically everywhere now. There's just like, there's barely any pushback. Yep. And certainly in the government, from my what I'm understanding, there's no longer any process.
Speaker 4:Right? Back to the whole sort of how did Jensen lobby to get decision made, there's no process, there are no, like, all the Many of the people who worked on these issues were fired, and now it's basically like he gets to the principal, he gets to Lutnick, or Sacks, or the president, and that's the decision. There's no like national security discussions. There's no process anymore.
Speaker 1:Yeah. It feels like interestingly, people often project like a monolithic culture upon China, but then severe division within America. America. And it feels like there might be some division on both sides in the sense that in America, there are arguments for let's export all the GPUs, keep them dependent on us versus let's let's hold it back and and and hurt their ability to scale. And then in China, they might be saying the same thing.
Speaker 1:Hey, we need to just buy buy buy and stay near the frontier. This will actually help us accelerate. And then there'll be a different argument for for maybe maybe we need to just There's also
Speaker 2:the the, you know, in in many ways, DeepSeek, the original Yeah. You know, DeepSeek release was was in some ways economic warfare
Speaker 4:Mhmm.
Speaker 2:On on NVIDIA. Right? You saw this massive sell off immediately.
Speaker 4:Well, and there and there was clearly a somewhat of a coordinated hype
Speaker 2:Yeah. I mean, the app store the app store chart, know, DeepSeek getting all these downloads was completely Twitter
Speaker 4:bots, Twitter trolls. Yep.
Speaker 2:Totally. And so and so I think there's you could also read into this and think Beijing doesn't think that the next DeepSeek release, regardless of how much progress they make around efficiency will have the same effect on, you know, making Nvidia sell off, you know Yeah. Massively. Do you have any do you
Speaker 1:have any context on previous technological revolutions and and the history of The US China relations like going back to like the cloud or mobile? Like was there ever any similar considerations of of don't sell iPhones? It felt like in the previous era, every big tech CEO was like, I'm gonna massively tam expand by getting into China, and then they got blocked. And this is kind of the opposite where Jensen's been playing that and then now he's having to pull back and the government's like like the the US government's the one that's saying don't sell to China. Whereas in the past with Uber and Google and Facebook, it's been the Chinese government saying don't I come here with your
Speaker 4:think this is this is fairly unique as far as I my memory. Certainly, this sort of important technology, there have been certain types of things that the US government hasn't allowed to be sold into China, but not at the scale or the sort of the economic importance or the, frankly, the market cap importance.
Speaker 1:Zooming out, how do you feel like US China relations are just going generally? I feel like two years ago, there was a ton of saber rattling about we need to get sharp on Taiwan. Everyone needs to learn what TSMC is. We need to talk about defense technology and Taiwan invasion in, you know, six months, twelve months. Happening.
Speaker 1:It's gonna happen. And then it feels like we've been in a bit of a lull, a little bit more economic, you know, economic warfare. But it feels like we might be coming out of a period of high tensions. Just give me, like, the general pulse check from your side.
Speaker 4:It's a great question, and it's one that it's still it's still quite unclear. Think that you see the beginning of the Trump administration, the economic tensions rose pretty high. Those have come back down to, you know, where there's now a sort of a tariffs are high, but there's a it's it's calmer, although the Chinese, in part, it's calmer, think, because the Chinese pulled out their export control trump card, so to speak, around rare earths and rare earth magnets and
Speaker 1:Yeah.
Speaker 4:And really, I think, showed The US that they had actually a lot of leverage that that The US didn't necessarily appreciate. Mhmm. And so I think you're in a bit of a lull on The US side because there are things like, for for example, on the technology stuff, you know, there were a bunch of new actions around export controls, around chip related stuff, they're all tabled. Right? In part, I think because of how the Chinese were able to push back on the initially, the beginning of the of the sort of the trade war using their their rare earths card.
Speaker 4:Generally, though, when you look at the the broader, you know, you look at Taiwan, you look at sort of things like the South China Sea, you know, the the you look at the other economic issues around, you know, what The US states over says overcapacity, the structural issues are not going away. We are, and I think as you said, we're in a bit of a lull, and the Trump administration seems to be more focused on the the transactional parts of the relationship for now. But, you know, there's some people who wanna talk about it, maybe it'll be this grand bargain, you know, Trump and Xi may meet this fall and they'll have some great grand bargain. Know, it it's hard to see how that would happen and how it'd be sustainable just because of the the real structural issues of relationship, but there's no Yeah. Question that the narratives have been shifting.
Speaker 4:The Chinese have been working really hard on people to people sort of
Speaker 1:Yeah.
Speaker 4:Stuff that has, I think, pulled us back from the sort of peak of China Hawk. I said it, know, my Sharp China podcast fall or beginning of the year, I just we were joking. I said, you know, I think we've hit peak China Hawk. Right? No, seriously.
Speaker 4:Right? Gonna it's gonna it's gonna sort of moderate at least for the time being. I think that's what Is we're
Speaker 1:the rare earth element stuff a an ace in in the deck of cards or is it more like a jack or a queen? I think about, you know, we haven't even gotten to the obviously, tie Taiwan invasion feels like more of the ace in terms of just like how much pressure that would put on the relationship. But also Apple, it feels like if China were to put pressure on Apple, that would potentially be more disruptive to the American economy just because it's such a huge company. It's so critical to American technology than than rare earths? Or is there some other dynamic at play there?
Speaker 4:I think the Chinese have know, Apple is one of those companies that every time there are tensions, it comes up, well, China could do something to Apple. And Mhmm. They have you know, Tim Cook has been brilliant at managing president Trump and brilliant at managing Xi Jinping. Mhmm. And, you know, Apple there was a great book that was written about Apple by Patrick McGee.
Speaker 4:I mean, Apple has does a lot for the Chinese economy. They employ a lot of people directly and indirectly. Yep. The Chinese so far have not really bothered them in any direct way. The rare earths is one where they have the ability to effectively disrupt significant parts of US industry and European industry, and they did that.
Speaker 4:And and that, I think, is why you see you saw The US sort of pull back pretty quickly in the in the trade discussions. And, you know, the way The US did it is, after the first meeting in where was it? It was in, shit, it was London, Geneva. Yeah. The first meeting, all of a sudden, The US added these new export controls on like jet engines and other things because the Chinese weren't giving the rare earth magnets that The US thought they were.
Speaker 4:Yeah. That that is the one where the Chinese can cause pain immediately.
Speaker 1:Yeah. Yeah. Yeah. So with Apple, if China does anything to Apple, that's like a million people unemployed in China, very disruptive to the Chinese economy. Whereas with rare earths, like, you could stockpile them.
Speaker 1:You could it's it's not as critical of like a labor market in China.
Speaker 4:No. It doesn't change the market. It's if they can't sell to us, it it's basically, it hurts the couple like, one or two state owned companies, effectively.
Speaker 1:Got it. Got it. So so it truly is more leverage for them.
Speaker 4:But but it's but it's the card that you can only play for a certain period of time. And if the US government and allies get serious about solving that bottleneck, it can get solved. The problem is, and maybe the Trump administration now is serious. This is not an this was not an unknown issue. The Chinese threatened this in the first Trump administration.
Speaker 4:The Trump administration, then we had COVID, nothing really happened. Biden administration admired the problem, wrote some papers, had some meetings, didn't fix it. Now, maybe there's the urgency to actually address it.
Speaker 1:Yep. That makes sense.
Speaker 2:Last question from my side. What is a general sentiment from on the ground in China or what's your read on sentiment among business leaders today?
Speaker 4:Not being there, that's a harder question to answer. When you look at some of the data and the surveys, you know, you look at, like, some of the multinationals, I think there is a the the surveys from various foreign chambers of commerce tend to be generally pretty pessimistic, more pessimistic than they've been in years. When you look at some of the surveys around Chinese business confidence, it is maybe bottomed, not particularly positive. Certainly, are pockets that are positive. You talk we talked about the deep seek moment, that has had a real catalytic effect on certain tech sectors, and you certainly see the Chinese stock market.
Speaker 4:Chinese stock market's up pretty big this year. You know, things like AI stocks are up, AI concept stocks are up big, some of the chip stocks are up big. You know, the the h 20 news and the and the fact that Chinese maybe not want the h twenties was good for some of the domestic chip companies. So, in those sectors, you know, you look at robotics, I think they're feeling quite confident because both the market's there and then they've got massive government support. So, it's a mixed bag.
Speaker 1:Well, you so much for hopping on. We are gonna jump on with Jimmy Goodrich. But we'd love to have you back.
Speaker 4:I mean, this is time.
Speaker 2:Also, if you're ever in the chat and you and you have a comment, you wanna you wanna strap light on, we'll just drop you.
Speaker 1:You just join
Speaker 2:the same link that
Speaker 4:you have.
Speaker 1:Really, you can join us. We're not alive. So any I know
Speaker 4:you gotta do Appreciate it.
Speaker 1:We'd love to see you.
Speaker 4:Cheers, Bill. Have a weekend. Cheers.
Speaker 1:Let me tell you about fin dot ai, the number one AI agent for customer service, number one in performance benchmarks, number one in competitive bake ops, number one in ranking on g two fin dot ai.
Speaker 2:Absolute legends.
Speaker 1:And we have Jimmy Goodrich in the restream waiting room. Let's bring him in right now and continue our conversation on chips in China. How are
Speaker 2:you doing? Welcome to the show.
Speaker 1:Welcome to
Speaker 2:the show. Hey. Good to
Speaker 8:see you guys.
Speaker 1:Good to see you too. I'm not sure if you were if you've been tuning in or Bill Bishop gave you a a a highlight, a summary of of the debate. We've been debating the pros and cons of exporting h twenties to China and the back and forth America has had threatening to ban it, actually banning them, then pulling back on the ban. Would love for me to tell would love for you to tell us how you've processed that story, where you've sat on the issue over time, and where you're sitting today.
Speaker 8:Yeah. No. I I caught the tail end
Speaker 3:of it. I think it was
Speaker 8:a great discussion with Bill. You always got really good insights to add. I mean, clearly, it's been a roller coaster. I mean, US export controls on China have typically been this sort of the government thinks about doing things. It leaks out in Reuters or the Wall Street Journal that there might be doing an export control.
Speaker 8:China learns about it about nine, twelve months in advance. They stockpile everything they need. Then they watch the Americans sort of debate openly, you know, in our democracy, which is messy. Yeah.
Speaker 2:And I think they I think
Speaker 8:they look back all this kind of silly. And then they kind of half impose a restriction,
Speaker 11:then they undo it.
Speaker 8:I think it's just all kinda comical for Beijing.
Speaker 1:So how big do you think the h 20 issue really is?
Speaker 2:The the other thing
Speaker 1:talking it up is, like, the most important chip. It's gonna completely unlock DeepSeek r three. It's gonna be this amazing moment for them. On the other side, folks are saying it's a four year old it's a four year old chip. It's heavily nerfed.
Speaker 1:Like, yes, DeepSeek figured out a way to optimize around some of the limitations, but in general, this is not a real threat. How how are you feeling about the actual the actual value of the capability provided by the CUDA ecosystem on top of the h 20?
Speaker 8:I mean, I I think it's still a very valuable chip for China and for China's AI model developers for two reasons. One, in the AI world, obviously, you've you've sort of gone into this depth on your show. It's about training and inference. And particularly for inference is where you need memory bandwidth and that's where the h 20 excels. In fact, on a cost per token basis, it's probably the most competitive inference generating chip in the world because it's the same memory bandwidth of a hopper but at a reduced price.
Speaker 8:So it's a great value chip for for inference. And that's another key factor here is quantity, is NVIDIA can provide them in millions of units. That is something that Huawei and no indigenous producer today can do. Because of the export controls, because of the, you know, complexity of advanced node chip manufacturing, China's indigenous chip manufacturing ecosystem might in the future, but does not right now have the ability to produce enough to satisfy their own domestic demand. So at least temporarily in this sort of one to two year window, the h 20 and then possibly a downgrade at Blackwell.
Speaker 8:Still gonna be very useful China, to China. And on top of that, of course, there's the CUDA advantage. And if you talk to any AI model developer in China, they want to develop their model on the NVIDIA stack. They've been doing it since college days. Everybody knows how to code on CUDA.
Speaker 8:It's a big pain to move to another supplier. I mean, just moving to AMD, for example, is difficult. So, you know, let alone a much smaller, much more nascent developed Chinese competitor. So I I think it's actually gonna be a big game changer for the deployment of AI for the scaling up of Chinese AI models.
Speaker 1:Yep.
Speaker 8:And if you think about, you know, reasoning and inference, if you wanna develop more capable AI agents, they're gonna be doing more tasks for you autonomously. That's where h 20 high memory bandwidth, good inference chips are gonna come into play.
Speaker 2:Do you think it's smart do you think it's smart for Beijing to take a a maybe a more long term view here and say we're gonna throttle development in the short term to really develop the industry locally?
Speaker 8:Well, I think they've got two sort of interest groups they're trying to take care of. On the one hand, they have their AI upper stack companies, the model developers, DeepSeek, Moonshot, Emmy, Baidu, Tencent. They want just to be able to put out competitive models. And frankly, having spoken to many of them, they'd much rather use a better, more capable chip irregardless of where it's from. Mhmm.
Speaker 8:And NVIDIA certainly wins out in that right now. On the other hand, you know, China has a self sufficiency national target that Xi Jinping set as part of the twentieth party congress. Call it or national technology self sufficiency. And he's talked specifically about using a secure and controllable indigenous chips. And there are set aside Huawei about a dozen indigenous GPU suppliers in China who want to take advantage of NVIDIA not being in the market and expand their market share.
Speaker 8:And so what on the one hand, Beijing is welcoming NVIDIA back in. They're rolling out the red carpet when Jensen comes. They also doesn't matter why. They want an executive who's actively lobbying against tech restrictions in Washington. They wanna reward that behavior.
Speaker 8:But on the other hand, they wanna create a space for these indigenous GPU players. It's gonna be in things like state owned contracts, China Mobile Telecom procurement contracts are gonna go mostly to those kind of Huawei and other firms. But I expect sort of the Baidu, Alibaba, Tencent, hyperscaler contracts are still gonna be majority NVIDIA, particularly if they can get the licenses. So Beijing sort of balancing both of these constituents. In fact, within China, there are many who actually don't like Huawei.
Speaker 8:You know, there was a Chinese Academy of Science, very senior computer scientist, who's a vice minister in the Chinese government and party, and a, talk of his leaked earlier this year where he was criticizing Huawei and saying Beijing should not let Huawei dominate the AI stack in China. It's not healthy. They can't have a single large monopoly that the government should support and that they should be supporting competition with inside the Chinese system. So, you know, China is not a let's give everything to Huawei. There's a lot of people who think they're too aggressive.
Speaker 8:They're kind of like the apple of China. Nobody wants to really do business with them because they're cheap on price and very aggressive. You know, it's like the long or the wolf culture. So, you know, Huawei has its own enemies with inside China too.
Speaker 1:Interesting. Yeah. So let me walk through the current thinking and you can kind of push back on my reasoning chain here. So we are we are now maybe in an era of plateauing. We're not on the cusp of super intelligence by merely scaling up, you know, a bigger large language model.
Speaker 1:And so what really matters is that inference is the actual deployment of AI, getting AI all throughout the every crack in the economy is souping up those various SaaS systems and putting agentic workflows all over the place, increasing GDP not to 20% overnight, but maybe just bumping it from 2% to 3%, to point or something like that. And so, giving the h 20 to China allows them to do that, allows them to scale inference, distributed inference nationally into all sorts of businesses from DJI will benefit from this marginally with slightly more AI all over their organization to some small machine shop that might be using it to run their HR software more efficiently. And so although it is somewhat of a more level playing field, we are still in the domain of just economic competition. And so it's not it's not a major it's not perceived as a major national security risk. It's mainly an opportunity for an American company to just play by the traditional rules of free market capitalism and export their goods all over the world.
Speaker 1:Is that like roughly the modern thinking you think?
Speaker 8:I'd say I agree with you on that first point. If we, you know, want to help enable China to be competitive in AI, we wanna help their AI model companies get access to the best infra chips, wanna help them scale up their deployment, win in the market at home and possibly also export their models globally, then absolutely, we should be selling, you know, more h twenties to China. I just don't think that's in our national interest.
Speaker 1:Yeah.
Speaker 8:You know, of course, it's it's in it's in NVIDIA's interest. They want, you know, they are agnostic to who wins in the AI race. Mhmm. Because at the end of the day, whoever wins is still gonna be buying a boatload of NVIDIA chips and silicon. And so whether they're Chinese, whether they're from The UAE or from The United States, you know, it's, you know, multinational company that's selling silicon is really not gonna care where their chips are going to and what they're enabling from a sort of flagged country perspective.
Speaker 8:Yeah. I do think though, if you look at disinformation and cyber warfare and you look at the capability that autonomous agents are gonna be able to even at current GPT five or, you know, future r two level coding capability, if you if you think about scaling that up with, you know, a 2,000 autonomous agentic AI coding capabilities are gonna be doing vulnerability scanning, cyber offensive warfare, you really start to get an exponential capability increase. And so I do worry that, you know, the Chinese state with, you know, two dozen, h 20 capable inference data centers could use that to do more autonomous cyber activity, that's nefarious. And then on the same side, disinformation. If you can have models that can reason for longer and on an agentic basis, interact with people online, shift population's opinion in places like Taiwan, that's incredibly dangerous.
Speaker 8:And we've already seen the New York Times reported about ten days ago that state owned companies connected to the Chinese state are using DeepSeek, which is gonna be inferenced on, you guess what, the best silicon possible Yep. To do exactly that, which is disinformation campaigns against Taiwan and The United States. So actually, do think there is a national security concern here. One, there's an economic security leadership concern, and then there is a, you know, enablement capability down the road that that is actually gonna be, you know, I I think happening relatively soon.
Speaker 1:Last question?
Speaker 2:Another concern people have had is just like giving giving the party in Beijing broadly access to more compute and the potential applications of that in a military context, specifically drone warfare. Is that something that you you worry about very much or kind of secondary?
Speaker 8:There's, you know, there's like traditional applications of high performance computing, super computing, which is useful for weapons modeling simulation. You don't need, you know, multiple large systems to do that. You might have a couple of two a couple of boutique standalone government HPC systems. Where where more of that model data is gonna be useful is if you're using large distributed systems of federated drones, collecting data, acting autonomously. For example, think about a world where you have your PLA signals intelligence communications battalion.
Speaker 8:That's in real time collecting all the battlefield communications in a Taiwan operation. Then they're transcribing that in real time into a written product that's being analyzed by autonomous agents in real time Mhmm. And then getting field reports into their commanders in real time telling them, hey, you know, there's a you you have a squad that's hit counter fire on this beach, North Of Taiwan. They haven't even reported it up to their superiors, but the autonomous agent AI system might actually be able to get that deploy a drone. If you think about just those capabilities in the future, that's where inference really matters.
Speaker 8:And that's where it's gonna scale up and create, you know, tons of economic opportunities for Chinese companies and ecommerce and all sorts of other areas, finance and SaaS. But also on the military side, it's really endless if you could think about the applications as well.
Speaker 2:Great. Great answer. Last question for me. What's going on with TikTok? It was it was the talk of the timeline earlier this year.
Speaker 2:Everybody seems to have forgotten about it. Any any updates there?
Speaker 8:You know, I don't have a whole lot. I think it's one of these things where it's pretty obvious what happened to it. You know, the president likes the the tool, thought it was useful for his election. You know, they're they've continuously renewed the clock on that ninety day extension. Unfortunately, the you know, there there's no longer really an operating national security council inside the White House like you would have traditionally to kind of figure out and coordinate the interagency on a solution.
Speaker 8:So I think
Speaker 2:at the moment that you you mentioned earlier, Beijing kind of laughing about how our, our democratic system just publicly debates all these issues creating this ability for them to make changes in advance. This feels like one of those things. I mean, they have to be just laughing laughing about how we we've dealt with this entire issue to date.
Speaker 8:I mean, like with many of our things, I think they they look back and just don't think we're a very serious country. I mean, maybe with the exception of parts of our military, they think The US is sort of a, you know, badass that should not be messed around with. But, I mean, look at us on rare earth. We can't get our act together. Export controls, we're moving back and forth.
Speaker 8:Whether or not we think we should actually, you know, get our act together in onshore ship manufacturing. We're, you know, interested Intel here a little bit and then TSMC there a little bit. You know, the Chinese government, I think, from their perspective, like, look. We've got a ten year plan, a fifteen year plan, a fifty. There's actually a hundred year plan, and they're just sticking to it.
Speaker 8:And they see us just kind of all over the place. And I just don't think they take us very seriously, unfortunately.
Speaker 1:Well, in a hundred years, we know the plan in America celebrate the three hundred and fiftieth anniversary. You know, there's gonna be a party and maybe a maybe a UFC fight. That's what
Speaker 9:we can do.
Speaker 2:Anyway thank you so much for Thank for joining Jimmy. Very insightful.
Speaker 1:We'd love to have you back and talk more as the stories develop. This is great.
Speaker 8:Yeah. Happy to chat more.
Speaker 5:You guys
Speaker 1:are We'll very talk next Thanks
Speaker 2:Jimmy. Cheers.
Speaker 1:You know the news a Rune post has hit the timeline. Rune says agree with Delian. Rune
Speaker 2:has spoken.
Speaker 1:Agree with Delian on the Maoist perspective perspective that data centers should be turned into steel plants. I love it. And you know what else I love? Adio. Customer relationship magic.
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Speaker 2:Just playing around in there, doing In some
Speaker 1:other news, we have a we we our our next guest is in the restream waiting room. We will bring in Leonard Haim, second time on the show. I wanna talk about mister beast. He says he plans to take a 100 software engineers and lock them in a room with no cursor subscription with the first person to ship something that compiles taking home $1,000,000.
Speaker 2:Wow.
Speaker 1:This is from Bass.
Speaker 2:Absolutely fantastic.
Speaker 1:I I originally read this not as a joke. It's like, oh he's actually doing the PMF or Die thing because that that kind of would work. And I thought it was with a Cursor subscription and then I was thinking about like, wow he could wind up if he covers the bills, could wind up spending $2,000,000 on this challenge. But MrBeast should get into into software
Speaker 2:I'd like based to
Speaker 1:a different MrBeast of software.
Speaker 2:He should have a horse in the cogen race.
Speaker 1:Yeah. It was clear that PMF or Die was on to something, but it required someone to make to make it their lives work. Exactly. And if someone was really, I'm gonna be the mister beast of tech. I'm gonna be doing crazy challenges all the time, live streaming, experimenting with all the different formats.
Speaker 1:There's clearly something there.
Speaker 2:I think Cleuly should should run it back.
Speaker 1:Cleuly? Cleuly is a good candidate.
Speaker 2:Well, Cleuly hackathon.
Speaker 1:Anyway, we have Leonard back in the studio. Welcome to the TVPN UltraGone, Leonard. How you doing?
Speaker 2:Hey. Happy Friday.
Speaker 1:Happy Friday.
Speaker 12:We'll have to talk about
Speaker 9:mister beast instead of age twenties again, you know, while we're already on it.
Speaker 1:Yeah. I mean, on on that note, the the mister beast, if he was going to lock a bunch of a bunch of programmers in a room with Cursor, how how bad do you think the gross margins would be? Do you have a take on gross margins of application layer companies? We've been talking about that all week. Do you have any insight in there?
Speaker 1:Anything that is is muttering through your Whisper network?
Speaker 9:Unfortunately, I'm not in San Francisco, so I don't know how cow does nowadays work. Yeah. And I'm I'm out of the old breed, you know. I when I did software engineering, it didn't have AI. But I always noticed when I used my thought plan and I run out of, like, queries, I was like, oh, damn.
Speaker 9:I I need to write on my own and think on my own, who do I query? And then I spin up my second ChatGPT subscription, so
Speaker 1:I think
Speaker 9:it would already apply to me. Yeah. Being stuck without AI is is quite a problem nowadays.
Speaker 1:Well, give me the give me the current read, your current take, the latest and greatest on the h '20 debate. Where do you stand? Pro exports, pro banning the exports. How how has anything shifted your thinking around it over the past Do you wanna nationalize Nvidia? Do you wanna invest in Intel?
Speaker 1:You're trying buy What are you thinking?
Speaker 9:Well, the last time I was listening to the president speaking about NVIDIA, he was
Speaker 12:more talking about initially he wants to break them up
Speaker 9:and on nationals. Right? Because they were so big. Break them up but
Speaker 2:then roll them up later.
Speaker 1:Seen this playbook like 20 times with Trump and we get shocked every single time. He comes out and says something, this is the worst thing ever and then a week later, it's the best thing ever and we're partnering and we're doing a deal every single coaster.
Speaker 9:Well, what he said during the what was it? It was the AI action plan launch. Right? Yeah. I was sitting in a room, he was talking about Jensen, pointing to Jensen and
Speaker 12:he was just saying, I wanted to break
Speaker 9:them up, but it's so complex. And I think just basically somebody convinced them it's really hard and therefore you you're not supposed to break anybody up. Yeah. Right? So Fair enough.
Speaker 1:Nvidia doesn't have as clean of a line to break up as Intel where, you know, you could you could Gaming.
Speaker 2:We're taking you over here.
Speaker 1:Yeah. Yeah. The We need to see how focused are going somewhere else. Yeah. I mean, you know, like, what what would you do?
Speaker 1:You'd open source CUDA or spin that into a separate company? Like, if you were even to break up NVIDIA, like, what would you actually do? Do you have any idea?
Speaker 9:I think the software ecosystem might probably be the strongest one here, but again, this just goes hand in hand with the design. Right? So again, yeah,
Speaker 12:I think it's I think it's a
Speaker 9:fairly hard one.
Speaker 12:Yeah. But for what it's worth,
Speaker 9:I think the market share is only gonna go down. Like, there's more and more competitors. I mean, the total total evaluation will go up. Don't get me wrong. I'm like, I'm bullish on AI and NVIDIA.
Speaker 9:But, like, all the other companies, all the other chip designers, they're just getting better.
Speaker 1:Is that is that driven by AMD catching up or new what what does Aaron call them? They're like the the the new types of chips like Cerberus, Grok, and Etched. I forget what they're called. There's there's a new name for these crop of ASICs that are designed specifically for AI and and and and they they could potentially pose a challenge, but they're certainly not taking market share yet. It feels like it's it's mostly NVIDIA, then AMD, then maybe some Huawei The hyperscales.
Speaker 1:The TPUs
Speaker 9:AWS with the Tranium. Google has the TPUs since forever. I mostly think about them. Right? I think it's pretty clearly the case.
Speaker 9:They have all the incentives in the world to build their own AI chips and reduce NVIDIA's margin.
Speaker 1:Sure.
Speaker 9:On the startups, let's see how they're doing. Right? I think hardware is hard. Hardware startups generally fail. Yeah.
Speaker 9:But if they find the right niche, you know, it's pretty hard. NVIDIA builds this more general thing and if you like a hardware startup, you wanna find like a more narrow niche to be like more application specific. And if you hit the right point, right, whatever the next big thing is in AI, they might succeed. And we just see more and more of them getting there. Right?
Speaker 9:And, like, we see Anthropic and other companies using Google GPUs using Traneum. And and, again, the debate of the show
Speaker 12:you Huawei is also getting better. They will also just
Speaker 9:the market share can only increase. Right?
Speaker 1:Okay. Help me help me reconcile this. Google DeepMind's been seemingly fine with TPU and not having CUDA in their back pocket. They're on the Pareto frontier. The Gemini models are great.
Speaker 1:V o three is great. The new Genie model is great. It seems like they are not suffering or falling behind despite not having CUDA But then simultaneously we're hearing that DeepSeek, High Flyer, Alibaba, they want to train on Nvidia. They're not satisfied with Huawei. Why is Huawei behind Google's TPU business?
Speaker 9:I think that's an example I always bring up and people say it's gonna be so hard to switch Huawei. Google eventually succeeded, but also Google struggled. The TPUs are pretty pretty odd. This was way before any AI hype. Yeah.
Speaker 9:And they actually also struggled. I'm not sure
Speaker 2:if you
Speaker 9:guys remember TensorFlow. Yeah. Yeah. This was originally what they did. Right?
Speaker 9:And then later, they switched to JAX and right? And they have to PyTorch Punch. And everything around that. So I think over time, they were struggling with software, but I generally see this as a one time investment and Google is a big enough of a company that can just pay this one time investment and then you develop on top of it and eventually you will be there and you break even. You could probably do a survey if people are doing fine, like probably people still prefer CUDA because it's a bigger ecosystem, but as you're saying, Google is doing fine And, again, Huawei will struggle.
Speaker 9:It will take some time, but eventually, it will get there, in particular, if they can use cursor longer. Right? Yeah. Doing it. AI helps you to build your AI ecosystem.
Speaker 1:And and I guess to some degree, the flip side is, like, TPUs have full access to TSMC, ASML, and and and Huawei is restricted all throughout the supply chain. And so and yeah. And so like the the the latest Huawei chips we were just talking to Bill Bishop, he was saying that like that was from like 2,000,000 was it dies that they got from TSMC through a shell company. And so they had this like one time batch of supply chain like ease and then they were and then from then on they were supply chain constrained again. So then they had to go back to doing everything themselves and that was a lot harder.
Speaker 1:Whereas Google just calls up TSMC and says, hey, do everything that you do for Nvidia, just do it with our design, which is like Yeah. Probably slightly different. Anything else you wanna dig into?
Speaker 2:No. I think we've come in. I think we've covered.
Speaker 1:Yeah. Yeah. I think
Speaker 2:we've hit this think we've hit this have you guys covered
Speaker 9:the semiconductor supply chain and how good Huawei is? Because there's this quantity thing is that the the like, in the middle of debate, in my opinion, which I think is being
Speaker 1:missed here. Please.
Speaker 9:So we everybody compares the NVIDIA h 20 to the Huawei a s n I 10 c, and that's the best chip they've been putting out there. Yep. And if we look at Huawei a s n I 10 c, it's like 80% there when h 100 is. Mhmm. So like two or three years later than NVIDIA, they're finally slowly getting their approaching on the hardware specs alone.
Speaker 9:And again, we can look at the specification sheet, compare them one by one, but this never tells a real story, right? If you would do this with AMD and NVIDIA, AMD is on paper on the chips as good as NVIDIA, though one of them has 95% market share, the other one less than five. Right? So looking at the spec sheets is never enough. That's where the software ecosystem come in, where we just talked about.
Speaker 9:Huawei is definitely struggling there. I think they will eventually get there. They just need to have more developers, and I think that's exactly one argument favor of letting the h 20 go there. Right? The more people use the h 20, less people use to Huawei, so less developers are developing this ecosystem.
Speaker 9:Yeah. But where then comes in is how many chips can they produce? Right? Mhmm. We got one number under secretary Klasa testified, so he's supposed to tell the truth, 200,000 ASIN chips this year
Speaker 1:Mhmm.
Speaker 9:Versus we're trying to sell, I think it's 700,000 to a million H20s this year to China. Mhmm. So this is this is where then the debate struggles. Right? So if we wouldn't sell them the H20s, it sounds like they have more A790 and C standard and more maybe they have more developers then, but they share a limited number of GPU resources.
Speaker 9:And and that's the thing which I think needs to be debated here, and you can fall on both sides of the debate here. But, like, we need to understand that China is struggling and that cheated these it's not even 2,000,000 dice, it's 2,900,000 dice. Right? Because they're struggling so much with their own production.
Speaker 1:Interesting. Yeah. So, yeah. I mean, maybe 200,000 is enough for people to actually bootstrap that software ecosystem. Certainly something to keep tracking.
Speaker 2:Yeah. I think people consistently overestimate China on a bunch in a bunch of different areas. Yeah. Yeah.
Speaker 9:I mean, they can do software. I think they will eventually get there and I think the idea that just likes Huawei's ecosystem will always be terrible is just, look, don't get me wrong, I I would hope it's true. Right? But they got good coders, they got good designers, they they will just get better on all of these kinds of things. And maybe CUDA will always be better, but, like, Huawei is probably at the bottom right now regarding how good the ecosystem ecosystem is.
Speaker 9:And when the deep sea engineers, you know, they're getting to it and they're struggling, well, we'll get better. Right? I think that's that's for granted independent of the 2,000 ships or million ships.
Speaker 1:Yeah. I think I still fall on the camp of probably the h 20 exports do put enough pressure on Huawei to justify it but it's it's tricky. This is a this is a thorny one. It's it's not it's not extremely clear cut for me. Have you Yeah.
Speaker 1:You landed on We
Speaker 9:we should do a case study on Anthropic they're
Speaker 12:the most beautiful example because
Speaker 9:they got so many different chips they're using. Yeah. Right? Yep. And how's it going for them?
Speaker 9:Right? Like how how long did it take to train on Trainium? Are they training on Trainium? Are they deploying on Trainium? I think this would give us an insight how many engineers are they spending there and how bad is it still is?
Speaker 2:Think one question is you know, is is Beijing playing four d chess by leaking out, you know, don't use the h 20, don't use the h 20. So then they Is that we just pile them into the country, right?
Speaker 1:Is it
Speaker 9:for d chess? It's just like you create an artificial demand. You say like, look guys, you better buy buy some nine ten c's. You really don't want to. So we tell them, oh, if it's for sensitive government use, you'd rather use nine ten c's.
Speaker 9:So we only see strong encouragements, not full on bans yet.
Speaker 1:Yep.
Speaker 9:Yep. And we've seen the same game with CPUs. Ask Intel how it's going. I mean, Intel in general, but also Intel CPU market in China. Yeah.
Speaker 9:The government also started encouraging there. Basically, hey, can you please use homegrown CPUs? Yeah. Right? So we've seen it all over.
Speaker 1:Yeah. Mean, it would be super easy for the Chinese government to import some crazy tariff, level the playing field more that way, like even ban the h 20 importation. Like there's so many different levers that they could pull. And the fact that they've stopped, they've only gone as far as like strong encouragement. We've kind of inflated that to be like
Speaker 2:Political incorrectness.
Speaker 1:Yeah. We we people inflate to be like, it would be insane. It's suicide to to to not to go against a recommendation from the from the CCP. But it it does feel like they could have gone a lot further very easily if they wanted to. So we'll have to I mean, it'll show up in Nvidia's earnings.
Speaker 1:Right? We'll see what we'll probably get data. So we'll have to have you back on then. But thank you so much for stopping by.
Speaker 2:Great to see you.
Speaker 1:Hope you have a great weekend. We'll talk to
Speaker 9:you soon. Same to you. Talk soon.
Speaker 12:Take care.
Speaker 2:And if you're looking
Speaker 1:to get some sleep this weekend, get an eight sleep pod five. They got a five year warranty and a thirty night risk free trial free returns free shipping. Gordie, what were you
Speaker 2:Code TBPN. I was gonna say John Exley has landed.
Speaker 1:He's landed. Yes. Let's hear it from John Exley.
Speaker 2:Welcome back to the Thank you for joining. We have We gotta pull this up. Please. Trump and Putin are meeting right now. Okay.
Speaker 2:And I have a video in the chat team if we wanna pull this up. Very cool. Look at this John. So Trump and Putin are walking and what do you see?
Speaker 1:Woah. That's A
Speaker 2:little flyover.
Speaker 1:That's a show force. Where are they? That is wild. Yeah. What what a display of force.
Speaker 1:I I I wonder I wonder where they're meeting.
Speaker 2:It They're in Alaska.
Speaker 1:Alaska. That's sort of neutral ground I guess. It's technically America but yeah fly in
Speaker 2:the park. We got our bears there. Yeah. That's another They should they should have a bunch of you know Kodiak bears
Speaker 1:What a stand fun place to meet Alaska. Anyway, it'll be interesting to see
Speaker 2:what comes out that.
Speaker 1:Hopefully it's a resolution of the Ukraine war. I mean like Trump has been you know talking a big game about being anti war wanting to know more foreign wars. No don't don't send all the money overseas and and save that for the taxpayer. Save that for real estate deals, baby. We could be building you know golden skyscrapers in America with all those with all those drones we're sending.
Speaker 1:But we'll see where it goes. But hopefully a peaceful a peaceful resolution.
Speaker 2:We will see. Well, next up we have
Speaker 1:We have adquick.com.
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Speaker 1:Out of home advertising made easy and measurable. Say goodbye to headaches of out of home advertising. Only Adquick combines technology out of home expertise and data to enable efficient seamless ad buying across the globe. And we do have our next guest here. David welcome to the stream.
Speaker 1:How are Welcome doing to
Speaker 2:the show.
Speaker 3:Thank you so much.
Speaker 1:What you got for us? Jordy's warming He's got the mallet ready. He wants to hit the gong. It's the first one of the stream. You got some good news for us?
Speaker 4:Yeah. Yeah.
Speaker 3:Yeah. Web AI, we're working on some pretty interesting things. Just recently, we announced our new knowledge graph mechanism, which is out benchmarked all of the best models year to date.
Speaker 2:By by how much?
Speaker 3:7%
Speaker 1:by 7%. Let's go. There
Speaker 2:we go.
Speaker 1:We like to hit the gong for big numbers. We like to hit the gong for big fundraisers. We also like to hit the gong for for
Speaker 2:improved Benchmark maxing.
Speaker 3:Yeah. No no fundraising announcement today. Okay. Soon.
Speaker 4:Soon. Soon.
Speaker 3:Soon. I
Speaker 4:can't I
Speaker 3:can't leak it today.
Speaker 2:Well, we'll be refreshing our for Rock's account. You have it exactly about money. Yeah. Talk talk more about the the genesis of the business why why you it and Yeah. Yeah, what got you guys here.
Speaker 3:Yeah. Yeah. Absolutely. So WebAI is really focused on building models that can live on devices like the ones on your desk. Yeah.
Speaker 3:Right? So the Genesis, the company really started working
Speaker 2:Like what? Like on a watch or
Speaker 3:Yeah. Absolutely. Yeah. Absolutely. All of it.
Speaker 3:Yeah. So company started by working in computer vision. And we were working on how could we take, like, the YOLO models, if you guys are familiar with those. It was in the early, like, 2016 era. These were, like, the biggest models because language models weren't really mature yet.
Speaker 3:And did early work there, ended up creating our own runtime engine, so our own AI library and our own network protocol. And what this enabled is us to run state of the art AI models across devices distributed. So when you think about the future of intelligence, we really believe that civilization model is the most likely outcome for superintelligence, and what we're building is is the rails for that. So we serve and distribute models across hardware. So we're running some of world's largest models today on things like a laptop.
Speaker 3:So when we say we out benchmark like Opus four or GP five in knowledge retrieval, that's happening on a laptop. So it's not like it's a pretty significant breakthrough in modeling, and we're doing this, in lots of different industries. But, what we believe is gonna be a big step change unit economics for AI as well. It's just not there in the cloud model.
Speaker 2:Seems very important because all all week we've been talking about gross margins or the the lack thereof
Speaker 1:Yep.
Speaker 2:In a bunch, you know, a bunch of these different
Speaker 1:applications free player companies. When it happens on device. Right? That's the goal.
Speaker 3:Yeah. And you can do some things that, cloud players can't do. Right? So part of the way we're getting this accuracy, like, there's always, like, this no free lunch. Right?
Speaker 3:So why wouldn't, you know, Anthropic do what we're doing to get this huge accuracy retrieval, bump? Well, it's RAM intensive. So if we're distributing across devices, we can arbitrage. Right? So we can say, okay.
Speaker 3:We'll pull more RAM because we're inferring on a device. But if you're hosting this for a million users on NVIDIA, you can't do that. You can't load, you know, additional RAM resource for every user. It's just not efficient. But there's there's there's real things that happen on the edge, that unlock, I think, technological paradigms in AI that are more meaningful, like more accuracy, more context, all of that.
Speaker 3:And we're seeing
Speaker 2:that What about what about privacy too?
Speaker 3:Absolutely. Right? So in our stack, everything's downstream only. So when we partner with a group, like, work with the Oura Ring, if you know that company, we're doing the AI for them. And, think about, like, health data.
Speaker 3:Like, you want that to be private. So the dream there is how can we facilitate personalized models for millions of users that never leave their device.
Speaker 1:Mhmm. React to this post from Tay Kim, author of the Nvidia Way. He says, here's what I would do if I was the CEO of Apple. Quadruple the RAM and iPhones to 32 gigs, have the max model at 64 gigs. Memory is oxygen for local on device AI.
Speaker 1:More equals smarter and more powerful. Take the margin hit. Memory isn't even that expensive. What do you think?
Speaker 3:I think I think memory I think he's right. I think memory is fundamental in these models. I also think we need to tread lightly on this idea that we're retooling infrastructure and we're making all these big bets on hardware with, frankly, a pretty immature algorithm. Mhmm. Transformers are are not necessarily the winning algorithm.
Speaker 3:So I think we need to be, you know, cautiously optimistic, but we need to continue to work on what's next. Like, I just you retool based on all of these factors and an algorithm changes, and we don't know what the long tail of hardware is gonna look like. And NVIDIA was really relevant because pre training and all this, but now pre training isn't really happening at the same level it used to. Yep. And, I think generally more RAM is a safe decision.
Speaker 3:But, also, I don't know if I would jump in and, like, totally rewrite how we're building chips until we know that this is the architecture we wanna stick with.
Speaker 1:Would you recommend someone buying a new Mac, max it out and get the most memory possible?
Speaker 3:Absolutely. Absolutely.
Speaker 1:Just yeah. Why not? Why not? What about diffusion models? Do you think that there's a chance that they have a comeback?
Speaker 1:We saw that demo from Google where they were doing text like token generation through a diffusion model. Felt kind of like a wild card scenario. I don't know. Yeah. It's actually performing on benchmarks but seemed like a path a path in the tech tree that was kind of, you know, more or less forgotten, relegated to image generation, but then kind of making a comeback maybe.
Speaker 3:I think I think there's lots of things that have been unexplored relatively speaking. We spent so much time on Transformers, but we haven't spent equivalent amount of energy and dollars on other architectures that we know work. Mhmm. And we we know they work at specific things, but there's there's typically a broader application. I think it's really interesting.
Speaker 3:I mean, we're working on new architectures today, with with both, like, the public sector as well as the private sector. And we're seeing a lot of breakthroughs that I think, make the transformer look a little old.
Speaker 1:Oh, interesting. How do you think about the business model here? Because you're not gonna be selling hardware to an OEM in the supply chain, but you're also not an API, so you're not pricing on consumption basis. It feels like there's a world where companies are comping you to an open source thing that they have to implement. Like how how like what does a great relationship with a big device manufacturer like edge computing provider look like for you?
Speaker 3:Yeah. I think I think WebAI won. We have a license. Right? Because we have a proprietary tech stack.
Speaker 3:We're not a wrapper. We appreciate wrapper company. We think they're doing cool things. But we own our stack pretty vertically. So we own our runtime, our AI library
Speaker 1:Mhmm.
Speaker 3:And our tooling around that. And so when we work with a a partner, we we typically structure a base license minimum. And when we have that when we have that license, we can, you know, inject forward deployed engineers to work with these companies that honestly just don't have the AI talent quite yet, and they need help. And I think that's something that people aren't talking about is, you know, like, these products don't necessarily solve the problem out of the box. A lot of these enterprises like Fortune one hundred need help.
Speaker 3:And so we do that. And, additionally, there's a way to take part in the success in the deployment. So the usage fees we can get, even though we're running on device. Yeah. So, because our network is managing that.
Speaker 3:So you could imagine WebAI, you have two and a half million custom devices or maybe it's an iPhone, and we're shipping across that. Our network manages all of that. So we collect fees on that.
Speaker 1:So so, it sounds like it's somewhat case by case, but you could imagine charging, like, a per device license, but also, like, a per token license in the future?
Speaker 3:Per answer is typically how we structure it. So it could be a book. It could be a a one word answer, as long as it's an output that's solving a problem. We're we mostly work in mission critical use cases, like things like reassembling engines with, multimodal AI, you know, health diagnostics, public sector work.
Speaker 1:Yeah. How quickly are you gonna kill Jordy's battery if you're doing test time inference on device? He's been already complaining about the iPhone not having enough battery life but it feels like it feels like there was a glimmer of hope when we were just like let's just distill the models and it'll just be like a Yeah. Pretty pretty short inference chain. But if you're even if you distill the model, if you're inferencing for ten minutes, that feels like a lot of heat in my pocket.
Speaker 3:Well, I don't know what Jordy's using. I would assume it's a pretty nice phone. It's like an iPhone.
Speaker 1:Yeah. It's the latest and greatest iPhone.
Speaker 3:Yeah. I mean, you mentioned quantizing, so I'm gonna talk a little bit about that and what we're doing there. So we released an open source paper around a tech that we were building early that we've now expanded and it's a little it's it's more sophisticated now but the principle is still there. Mhmm. It's called EWQ.
Speaker 3:And, instead of just quantizing and tell me if I'm going way too technical here. Quantizing traditionally, you have like a fixed value. So we have let's say, you have a full precision model. And when you quantize something, you say, okay. I'm gonna quantize it to four bit or I'm gonna go to 16 bit.
Speaker 3:And so you're just drastically chopping the model down. Right? Some so from the float values that it can pass through. With EWQ, what we do is we have something called device profiling. So when a WebAI model hits your, your phone, it's running our web frame library, and it profiles your hardware.
Speaker 3:And then what we do is on inference, we run EWQ. And what EWQ does is it does real time quantization. So based on your question and the inference. And what it leads to is, close to 30 to 40% model reduction size in RAM while retaining accuracy. So what that means is we get bigger models inferring.
Speaker 3:And instead of, like, this one size fits all quantization, we we dynamically do that on inference. And what that leads to is less energy consumption, higher accuracy, less usage on the device.
Speaker 1:Yeah. So somewhat similar to the model routing that we're seeing in ChatGPT now. What were your overall reactions to GPT five?
Speaker 3:It's just an MOE router. I I was kind of hoping it was a new foundational model. And when you interact with it, it's really clear that it's just a way to dynamically control price
Speaker 1:Mhmm.
Speaker 3:Based on a question. So, like, you ask a question, they route you to a different model. If it's coding, it will route you to a different model. I can see where that's valuable. I have a lot of people that are nontechnical that are in my life, and I've watched them now switch off of GPT after the five release to things like Croc, which was kind of shocking to me.
Speaker 3:But I think people were used to a certain standard of response, and now the lack of, like, transparency in picking the model you're engaging with, I think, created some whiplash. But, I'm sure there's areas where it's amazing. I haven't really gotten to tap into everything there. Been enjoying a lot of the anthropic releases and typically probably tend to lean that way.
Speaker 1:Mhmm. Cool. Well, thank you so much. Congrats on all the progress and I hope you have a great weekend. We'll
Speaker 2:talk Sounds back like you
Speaker 6:Yeah. Absolutely.
Speaker 1:Yeah. We're excited.
Speaker 5:Yeah. Yeah. Absolutely.
Speaker 2:Great to meet you David. Thanks for Yeah. Thanks for joining.
Speaker 1:Let me tell you about public.com investing for those who take it seriously. They got multi asset investing industry leading yields. They're trusted by millions folks. We go
Speaker 2:Billions soon.
Speaker 1:What did Sama mean by this? If we didn't pay for training we'd be very profitable. We talked about this. Christian Culver says, most successful coups in history. Napoleon Bonaparte's coup of eighteen Brumaire.
Speaker 1:October Revolution in Russia 1917, the Nazi seizure of power 1933, Egyptian coup d'etat nineteen fifty two, the Chilean coup in 1973. And the open door retail army at Open in 2025. Kristen worked at at Open Opendoor. Correct? I believe.
Speaker 2:Must have.
Speaker 1:And so she's having fun. It'll be interesting to see in other news
Speaker 2:Yeah.
Speaker 1:So the CEO stepped down.
Speaker 2:This morning.
Speaker 1:Yeah. This morning. So Carrie Wheeler posted on X. Today, I'm stepping down as CEO of Opendoor. When the board of directors asked me to take on this role at the 2022, the company was in crisis, the real estate market was punishing, The business needed a reset and the path forward was uncertain.
Speaker 1:My mandate was clear, stabilize the company and do what was necessary to survive. Of course, I said yes because I believed in Opendoor. It wasn't easy and it wasn't about glamorous headlines, but we stopped bleeding. We restructured the business, rebuilt an exceptional team. Got an NPS of 80.
Speaker 1:And she says, I'm pleased the leadership team will continue to execute on the vision strategy. I'm closing this chapter with pride, clarity and gratitude. So good luck.
Speaker 2:It is wild. Open doors up 202100% in the last thirty days and they the retail army said, nah. We want more.
Speaker 1:They want more. New leadership. Crushing it.
Speaker 2:Well, I'm excited to see where Carrie Wheeler goes next.
Speaker 1:We should watch the new Jason Carmen film.
Speaker 2:Let's do it. Let's pull it up.
Speaker 1:Coming on the stream in just a few minutes. Let's pull up the latest work from Jason Carmen.
Speaker 2:I'll be right back. Please.
Speaker 13:Dear son. Five, four, three, two. Some time ago. One. We have to let go.
Speaker 13:Let's not gonna follow-up. The machines roared. The steel bent to our hands. We built for the stars, for our land, and for your future. We went fast.
Speaker 13:We went far. It made us strong. It united us.
Speaker 1:Then,
Speaker 13:the sound faded. The hunger to build drifted away. Those who knew grew tired. But now, the fire returns. The steel is ready.
Speaker 13:The country needs you. New boundaries beckon. Who will you be? Old Where will you take us? Was slightly different.
Speaker 1:It changed last minute.
Speaker 13:The stars
Speaker 1:The sound is actually getting us.
Speaker 13:Our future is waiting. So will you answer?
Speaker 1:This is fit. We need one of those. The one we're discussing hard tech. We should have gotten a suit today. Huge miss.
Speaker 1:Anyway, new video video from Rangeview. We have the CEO Cameron Schiller in the studio and the TVP and UltraDrum. Welcome to the stream Cameron.
Speaker 2:How you doing? What's happening?
Speaker 6:Hey guys. Good to see you.
Speaker 1:I have so many questions. Are you Did you act in that? Are you in that?
Speaker 6:I am not in that. That was
Speaker 1:a suit?
Speaker 2:What?
Speaker 1:You got it how I I I thought you financed this whole thing. I thought you made this happen and you didn't get a cameo.
Speaker 2:Gotta put yourself
Speaker 1:in. The machines got cameos though. Right? The machines got cameos, and I believe that last scene takes place at Rangeview HQ. Is that correct?
Speaker 1:Did I clock it correctly?
Speaker 6:That is correct. That takes place at the technology demonstrator factory. We're running to we got a production facility down the street, which we'll see in some some new videos coming out. Cool. But that was at this facility which we've been at,
Speaker 12:and now we're just busting out the seams.
Speaker 6:So we've gotta we've gotta move and you'll see a bunch of content from that new one. That place is sick. It they used to build space shuttle engines there.
Speaker 1:That's awesome. Wow. Yeah. The space shuttle shot was fantastic. I mean, Jason Carmen puts on a clinic every time he drops a video.
Speaker 1:What what inspired it? What what was the message you want to send? Is this just Is this a recruiting film? I noticed like the the follow-up post was like come work for us. This is not like an ad that you'll be running to get customers necessarily or is it just kind of like vision film?
Speaker 1:What was the thinking?
Speaker 6:Yeah. I mean it's really a message to America. Think it's a wake up call. It's a question of who we really want to be as a country. What do we want to do?
Speaker 6:Right? I think mean, I that was a big part of my life growing up going back and forth to China. I saw the American dream in China when I was there. Saw people from center of the country move to the coast to work extremely hard and make a life for themselves. And when I came back to America growing up, I just didn't see that here.
Speaker 6:And I think we have to bring it back, I think for national security reasons, I think across the globe. So the real question is, you know, can America bring it back? Because we need to make a lot of parts very soon. And this is less so about range view. I mean, America needs a thousand range views.
Speaker 6:This is about people that are considering making a big pivot in their life to work on something that matters to the world.
Speaker 1:And when you say make a lot of parts very soon, is that specifically like like defense like tech and warfare? Or is it are you seeing are you worried about great power competition? Or is it more like we won't get the next generation of nine eleven or like the next the next great physical product will be made without this
Speaker 12:happening.
Speaker 6:The one that I care about the most is the second one. But the first one's definitely very real. Yeah. If you think about it, you know, America did some amazing stuff. The f one seventeen, we invented stealth technology, the s r 71.
Speaker 6:All that stuff happened in America and that happened because I think of factory towns. I mean, I'm calling in from El Segundo. This is a town that literally runs on jet fuel. Like there is a refinery that's right next door that's pumping jet fuel out, you know, under under this city to to to feed the allied acts, which is on the other side of the city. And you feel it in the air.
Speaker 6:Like, there's something that happens when a community wants to be a part of something great in the world. And when we look around, everything around us has been made in China now. And with it, I you know, with it slipping, I think a great calling to be a part of something amazing has slipped as well. So we really need to bring that back. We're going to do that with parts.
Speaker 6:We're going to do that with new technologies that enable factory towns all across the country.
Speaker 2:Yeah. I mean, I think it's super What's
Speaker 1:going on behind you? There's like some scrolling image. What is that?
Speaker 6:Might be I mean, we've got a lot of screens
Speaker 4:in that.
Speaker 1:Is that oh, is this a screen? It's like a TV or something?
Speaker 6:Yeah. I mean, there's there's a lot of lights and there's a
Speaker 1:lot of this camera reacts with. Yeah. Yeah. Right. Right.
Speaker 1:Okay.
Speaker 2:Yeah. Think I think what you're what one way to kinda summarize what you're kinda getting at in in from my view is it's important for American dynamism to not be like a venture hype cycle that sort of it's it's not something that can be accomplished in Mhmm. Two years since, you know, moving to El Segundo became popular. And a meme and it needs to endure.
Speaker 1:Who helps with that? Was it me, you, Jason Cameron? Carmen. Yeah. We might have played a role
Speaker 2:A little bit to do with it.
Speaker 1:But I mean, I I guess the question is like, you you say this is like a, you know, a wake up call for America. Like, are we not awake? I feel like I feel like a lot of these a lot of this message is broken through like like what what's left to say? What what what do
Speaker 2:we Say it's need broken through in the bubble.
Speaker 1:Yeah. Maybe it's the bubble. Maybe it's the bubble. Yeah. What what I mean, what is your take on like, the re industrialized summit's huge like the the you know, the American dynamism summit is huge like like people seem to be beating the drum.
Speaker 1:People are it at the White House. They're in DC.
Speaker 2:They're a fraction of the size of Salesforce Dreamforce, John.
Speaker 1:Exactly. Are are you gonna be there? Dreamforce? Let's get you there. I This man this man loves enterprise SaaS.
Speaker 1:He won't he won't admit it on camera. He plays this character that he likes reindustrialization. But, really, he just wants to he just wants to code.
Speaker 6:Yeah. Yeah. It's all I wanna do. That's all
Speaker 2:I wanna do, John D.
Speaker 6:No. We need to we need to have more people where it's a, it's inside the bubble, and b, we need to encourage the people that are working on the problems to focus on the things that matter, and that's actually making parts. We need more factories. We need more metal moving. Moving metal is the problem right now.
Speaker 6:There's a lot of people building tools for factories. There aren't that many factories.
Speaker 1:Yeah. Yeah.
Speaker 6:Yeah. So if you wanna join, build a factory, make parts move, you know, do real stuff in the supply chain. I'm not talking like screwdriver factories bolting on imported components. That's the vast majority of, you know, assembly in America is like what what's left. So we don't need that.
Speaker 6:We need people working on hard problems.
Speaker 2:We also need you to thousand x we need you to thousand x range view. You said earlier we need a thousand range views, but why don't why don't
Speaker 1:you just be
Speaker 2:copy and paste your yourself?
Speaker 6:Working as hard as I can,
Speaker 7:guys.
Speaker 1:What is well, what can you tell us about
Speaker 3:Work harder.
Speaker 1:What can you tell us about the state of the art in in manufacturing? I know you you there's there's additive manufacturing, subtractive manufacturing, there's CNC. We've talked to people that are three d printing metal now. There's casting. What are you excited about?
Speaker 1:What are you focused on? Where do you think there's still pockets of opportunity?
Speaker 6:Yeah, great question. So we are working on casting and we are we are trying to give casting at CNC moment.
Speaker 1:Yeah. And explain casting for the for those who don't know.
Speaker 6:Casting is liquefying molten metal, pouring it into a mold, it's solidifying and you're getting the, you know, the part that has that shape. And almost everything is cast. Even CNC shops buy castings. Today, castings have eroded so much that machine shops are just buying cast blocks, and then they waste a whole bunch of time cutting a part into its final part. A lot of chiseling.
Speaker 6:But if you really get really good at casting, actually just cast 99% of the way and then touch the final bits up with the drill bit. There's no one size fits all solution in manufacturing. It's one of the first things you learn. It takes like a 100 humans from mining the ore out of the ground to installing the bracket on the end of the thing to actually make something happen. And there's a ton of folks.
Speaker 6:Think for people looking at technology, they're used to looking at manufacturing as just another sector. There's fintech, health tech, manufacturing tech. The truth is manufacturing represents more of America's GDP than all of tech combined. Yeah. And so it's huge.
Speaker 6:And so inside of manufacturing of all these sectors, and so many have just been not been looked at yet or not been touched. And so we're seeing resurgence. The other thing is you maybe shouldn't have financed these things exclusively with all venture capital because the risk profile just isn't the same in the factory. My factory burns down, I'm going to still have 1,000 pounds of super alloy. Maybe the crate that wasn't caught on fire, but they're not going to move.
Speaker 6:Right? That's crazy. It's not risky. It's not a risky bet, so you shouldn't buy that stuff for that. So I think there's a whole new level of financing that's going to come in.
Speaker 6:And you see this happening with a few of these big factory companies where you're getting really smart finance deals, where you buy the technology improvements with venture capital for those returns, but the rest of the factory is financed in a different way.
Speaker 1:Yeah. That makes sense. If I were to pull a hot take out of you based on what you just said, it sounds like potentially the American manufacturing industry is over rotated towards subtractive manufacturing and needs to rebuild additive manufacturing or casting capabilities. Is that is that like roughly a reasonable take that you
Speaker 6:Additive and casting are not the same. Additive is like the SPAC machine that's blown up actively as we see. There are few amazing people doing additive Sure. The most part. Like, it's missing on qualification and it's missing on real unit economics at scale
Speaker 1:Okay.
Speaker 6:Which is, as a whole, that's what America's missing, like really being able to build stuff at scale. If we had to triple the manufacturing output of the country, we'd be cooked, totally cooked. Yeah. Like, would take us five years to get the factories up to do that. And and all the factories that would start would be sending them money overseas because none of this equipment is made in America anymore.
Speaker 6:Yeah. We lost the factory industry, but we also lost the factory and machine tool industry. So all
Speaker 1:Yeah.
Speaker 6:You know, all this stuff just overseas. So I wouldn't say that additive is is it. I think casting is really important. A lot of these traditional forms of manufacturing are really coming back and making a big play. But we should just be encouraging everyone to make a lot of parts.
Speaker 6:Like, we we need so many parts and we need to get started immediately.
Speaker 1:Parts maxing. Talk about your dad. Talk about the influence there. Jason Tan teased it a little bit but I haven't heard the story.
Speaker 6:Yeah. Yeah. He's a big big part of a big part of my life. He's always encouraged me to be very very honest and and real about about this world, which I think is a really important adventure. And he was a maker himself.
Speaker 6:His family was Pittsburgh and he was a Midwestern family values. He came here to work on the B1 Bone. The supersonic bomber was pretty sick. And then I ended up growing up next to where Skunk Works was founded. So Bob Hope Airport actually.
Speaker 6:That stuff happened there and then it went out to Palmdale and then it became a service based industry. Lots of B2B SaaS and entertainment happened in the area and it really changed. But he always kept me centered and he's huge influence on my life and actually same with Jason's So so we bonded over that a lot and they're becoming increasingly large parts of both of our lives.
Speaker 2:Can you raise like a billion and then run this ad as a Super Bowl ad?
Speaker 6:You guys wanna help me?
Speaker 1:Yeah. Yeah. We gotta get him back on the venture train. Cameron's always very like anti venture but we're we'll
Speaker 2:we'll We need to run this film as a a Super
Speaker 1:back Bowl range view. Come
Speaker 2:on. Just just get the capital for a Super Bowl ad and then and then you can figure out how take time.
Speaker 1:Five years of Super Bowl ads. Run it every year. This is not gonna happen overnight.
Speaker 6:Yeah. I'm in. Let's talk about it. Let's make a game plan.
Speaker 1:Fantastic. Well thank you so much for hopping on.
Speaker 2:Talk to
Speaker 1:wait, where can people go to apply for jobs? I know that that's important right now.
Speaker 6:Rangeview.com. Scroll down careers.
Speaker 1:Rangeview.com. Heard it Thank you so much for having us and have a great weekend. We'll talk to you soon. And I will talk to you about Bezel. You wanna manufacture something?
Speaker 1:Manufacture yourself a watch on getbezel.com. New Bezel Concierge is available now to source you any watch on the planet. Seriously, any watch?
Speaker 2:Any watch. I'm getting them all. I'm very excited for this next. Well, okay. So there there's I was gonna I I thought we had our friends over at NFM live.
Speaker 1:They will be coming on in just a few minutes. But We will be joined by Sirach or Sarak?
Speaker 10:Sirak.
Speaker 2:Sirak. Good to meet you. Sirak.
Speaker 1:Thank you for joining the stream. Why don't kick
Speaker 12:us off
Speaker 1:with the introduction on yourself and the company?
Speaker 10:Alright. Well, I am Sirak from Early. Early is an early cancer treatment company. And essentially what we do is we create genetic constructs that are injected into your body and they disperse everywhere in your body. They enter healthy cells randomly.
Speaker 10:And if you happen to have cancer cells, they will also enter those. But only if it's cancer, these genetic constructs will switch on like a light switch. And then they turn the cancer cells into little factories that are forced to make any protein of choice. In other words, you can make something that makes the cancer visible or you can make something that activates your immune system to attack and kill the cancer.
Speaker 5:So
Speaker 10:the whole thing is relevant because in the last fifty years, we've always tried to find some markers on cancer cells that make them detectable or druggable. Right? Mhmm. Billions of dollars have gone into that. Yet, we still have 600,000
Speaker 1:robots.
Speaker 10:Yeah. We still have six hundred thousand people dying from cancer in The US every year and ten million globally. So something needs to change.
Speaker 1:What's the background of the company? Is this tech transfer? Did this come out of an academic lab? What is your background?
Speaker 10:Yeah. I'm actually not a biologist. I out of 35 people, I'm like one of two or three people who don't have that background. I'm an engineer.
Speaker 1:Mhmm.
Speaker 10:I'm a serial entrepreneur, and the idea came out of Stanford University. And it was one of the world's top people in early cancer detection who then himself himself sadly sadly passed away from cancer. Wow. Including his own son died at 16 from cancer and his wife died two years after him. The whole family is wiped out.
Speaker 10:So I met him.
Speaker 2:Was that out of curiosity, was that environmental exposure or
Speaker 10:No. No. No. It's mostly genetic. Genetic?
Speaker 10:And, the the mother had a genetic, a genetic mutation that then got transferred to the son. And what Sam Gambier died from, the inventor of the whole thing is unclear to this point. It was cancer of unknown origin. You would didn't even know where the primary tumor came from. So a very tragic story, but he was committed to flipping the tables against cancer.
Speaker 10:So I don't know if you guys have, Jordy or John, whether you have anybody in your family or in your friends circle that has been affected by cancer.
Speaker 1:Yeah. Yeah. Of course.
Speaker 10:You know, it's just kind of crazy that we are always behind a step behind or two steps behind. We're always trying to find the next marker that we could hook onto. So what if we could stop looking for any marker altogether? What if instead we could force the cancer to reveal itself and make its own therapy to kill itself.
Speaker 1:So what's the pathway to commercialization? I imagine you have to go through FDA approvals at some point?
Speaker 10:Yeah. We have to go through a phase one, two, three trial
Speaker 6:Sure.
Speaker 10:And then to commercialization. And we have spent the last seven years cracking this really hard problem. You know what the biggest problem is in cancer? What's a cancer cell and what's not a cancer cell? Yeah, of course.
Speaker 10:Because because, you know, different from a virus, this is your own cell that has changed just a little bit. And so differentiating that from a normal cell or from something that looks like cancer, but it's totally benign is really hard.
Speaker 5:And
Speaker 10:that's what we've spent so much time and energy on with AI where we're essentially producing AI results, liquefy them, put them into the body into a cancer drug that then forces the cancer to produce their own its own therapy against itself.
Speaker 1:And what's the latest news with the company?
Speaker 10:Well, we just raised $44,000,000.
Speaker 1:Congratulations. Not cheap work you're doing. Sounds expensive.
Speaker 10:Yeah. Biotech is not cheap. So, you know, I don't know how much you know about the biotech world. It is in the biggest funding crash in the last twenty years.
Speaker 1:On both the public side, the private side. I know that the the government funding is certainly at an all time low, but this is across everything.
Speaker 10:Actually, you you named them. The private funding Yes. Is extremely low because of two reasons. High interest rates, which immediately affect a long running product like bio takes ten to twelve years. Right?
Speaker 10:And then AI is like a vacuum cleaner for money. That makes sense. It sucks up all the money that goes to tech firms because for VC companies, many of them believe they can make a faster return by putting it into AI classic tech.
Speaker 1:Of course.
Speaker 10:But bio and AI is a great interface that is now coming to fruition. And then the pharma companies, they are concerned about tariffs. They are concerned about China catching up to The U. S. And they start buying ideas and drugs there.
Speaker 10:And then the government is not stepping in to flatten out the curve. And, you know, here I would actually say, we really got to make a national commitment to biotech to flatten out this funding curve because, you know, at the end of the day, would you like to be dependent on China providing the most developed life saving drugs for cancer, for autoimmune diseases? Do we really want to depend on that? I mean, it's good if they supply them, but what if they don't one day? So we should actually have a national commitment to biotech to make it, to retain the world leadership that The US has had for the last fifty years.
Speaker 1:Yeah. Good point. Well, thank you so much for stopping by. Have a great west rest
Speaker 2:of your
Speaker 1:week, and have a great weekend. And congratulations. We'll talk to you soon.
Speaker 10:Thank you. Talk soon. Bye bye.
Speaker 1:Cheers. Have some major guests in the Restream waiting room. Let me tell you about Wander first. Wander. Find
Speaker 2:Your happy place. Find your happy place.
Speaker 1:A wander with inspiring views, hotel, great amenities, dreamy beds, top tier cleaning, and twenty four seven concierge service. It's a vacation home but better. We're joined by
Speaker 2:This is the moment And you've all been waiting for.
Speaker 1:They're calling it the
Speaker 2:Brothers. Welcome to the show.
Speaker 1:Doing. You guys look fantastic. We got headphones on.
Speaker 12:Let's go.
Speaker 1:Can you hear us? How you doing?
Speaker 12:Yeah. Yeah.
Speaker 1:Give us some energy.
Speaker 10:Come on.
Speaker 1:Give us some energy.
Speaker 2:Come on. What time what time is it
Speaker 6:in house?
Speaker 12:Yeah. It's five 05:15. Five 05:15. In the morning.
Speaker 2:In the morning. So we're just waking up here here. I'm gonna help you guys I'm gonna help you guys wake up
Speaker 1:basically. For the launch
Speaker 2:of the Korea.
Speaker 1:You. Thank you. So talk to us. How's it been going? How how how has it been running the show?
Speaker 1:What inspired you? Obviously, you know, TBPN's by the time a little bit, but but have you been working in media? What's the background story here?
Speaker 2:Yeah. Give us give us life stories.
Speaker 12:Yeah. So both of us coming from venture capital backgrounds. We've been based in Seoul for over like four or five years. So, yeah, we love this industry, know, private market, VC, tech, startup, this whole industrial complex.
Speaker 1:And we
Speaker 12:thought that that could be something, you know, we could do above just, you know, a pure investment and, you know, media could be the, like, perfect complementary medium. So, I mean, you know, anyway, we we were doing our own thing, you know, like, running our own, like, blog and in writing essays, like, since a few years ago. And this guy here, Sung Joong, he actually, you know, with his friends is running one of the biggest, you know, VC newsletters in Korea and, you know, opting and running my own blog too. Congratulations. So in earlier this year, we thought that, oh, you know, podcasts could be the most optimal medium to reach, you know, the wider audience and also to reach the the global markets.
Speaker 12:And we found you guys Yeah. Randomly on the feed. Yeah. And we thought, oh, This is the shit.
Speaker 4:This is
Speaker 12:this is the we gotta We're gonna Yeah. So Yeah. Yeah. Of course, you know, we if there's anything we wanna benchmark from The US, it's not all in, you know. It's not the boomer institution, you know, like the medium.
Speaker 12:So So
Speaker 2:so what's your what's your guys' schedule? Are you have you have you quit the other stuff yet? Are you going all in? Are you just putting how how much time are you putting up?
Speaker 1:Is it three hours a day? Do you have multiple guests? Like like, what what what have you take in from the show? What what what's working? What is in what needs to be different to succeed in Korea?
Speaker 12:So I will say so, okay. First of all, so we're, like, running, like, three times a
Speaker 1:week. Mhmm.
Speaker 12:So we will ramp it up.
Speaker 2:You gotta get those numbers up. What are people gonna do on
Speaker 12:the other Yeah.
Speaker 2:Do they expect to just twiddle their thumbs?
Speaker 1:Does the Korean tech economy not function five days Twenty
Speaker 2:four seven?
Speaker 1:You psycho musketwinkle.
Speaker 12:Okay. But we're gonna ramp it up. I'm letting you know, like, check us out in, six months. We know we might be running, like, seven days a week, who knows?
Speaker 1:So I love it.
Speaker 11:Yeah. A
Speaker 1:lot of the fuck.
Speaker 12:So anyway, yeah, know, the the Korean tech market is as vibrant as Yeah. You know, like, as The US, I would say. That's great. You know, like, but, you know, we are just kinda like, you know, being the frontier in this, like, you know, hold the new new media and like this, like, you know
Speaker 2:Yeah. Like Well, in many ways, we're old media. Yeah. We're old media. This is just this is television.
Speaker 12:Is it?
Speaker 1:It's just TV.
Speaker 12:Is it?
Speaker 1:Talk to me about the guests. Do you have dream guests? Who's the Palmer Lucky of of Korea? Who's the Elon Musk of Korea? Who do you wanna get on?
Speaker 1:Who have you had on? What what we have a lot of venture capitalists, but then we have analysts, politicians. We've kind of gone all over the place. Where have you had success, doing guest interviews or are you even doing guest interviews yet? You you I believe you are.
Speaker 1:Right?
Speaker 12:So we're in the very initial phase. So we've only embodied a lot. Only a limited number of guests but so far we have some DMs, engineers, also venture capitalists, also authors who just publish books.
Speaker 1:But
Speaker 12:you know, we wanna have actually, we wanna bring in everyone, you know. Nice. Everyone VIP, you know, even the president, you know, like like, you know, like, even Trump. Who knows? So Yeah.
Speaker 12:We we wanna bring you guys in our show.
Speaker 1:Of course. Yeah. We'd happy to.
Speaker 2:Let's do it. Let's Let's do do it. It.
Speaker 1:Well, you'll make us wake up at 5AM, I guess.
Speaker 2:We're ready. I mean, that would that wouldn't work time zone wise. But it'd be more like instead of going to bed, we'll pop on your guys' show.
Speaker 1:Yeah. Are you guys live at 11AM local?
Speaker 12:Oh, it's like 6PM on LA.
Speaker 1:6PM in LA. Okay.
Speaker 6:Yeah. Yeah. Can dinner
Speaker 2:time. Our wives will be very happy we're bailing on dinner What's the OpenAI of Korea?
Speaker 1:Yeah. What's the hottest company? What's the one that everyone's focused on? SK Hynix is obviously like like later stage but what well, who is Ascendant?
Speaker 12:Open Air of Korea. Okay. We gotta be straight ahead here. It's tough. It's tough.
Speaker 12:I would definitely pick, you know, in terms of like, know, semiconductor business, SK Hynix, Samsung Semiconductor Mhmm. Of course. And also, we got some, you know, like, Hasha Korean developers
Speaker 2:Mhmm.
Speaker 12:At OpenAI. So, you know, like
Speaker 2:How how do you say cracked engineer in Korean?
Speaker 12:Like, like, you know, like, engineer is a cracked you know like a
Speaker 2:I can hear that. Yeah.
Speaker 1:Yeah. Yeah. The team loves it. The team loves it. That's great.
Speaker 1:Anything else Jordy?
Speaker 2:No. That's great. We're we love what you guys are doing. Happy to come on the show. Yeah.
Speaker 1:Anytime you need help.
Speaker 2:Have fun. Have fun out there. And you guys look sharp too. Thank you for for make, you know, copy and pasting the suits as well.
Speaker 12:Yeah. Yeah. Of course, this this is an info from you guys, but you know, like as as we wanna, know, like make our own path and own ecos, you know, from here on. So, yeah, we're gonna build our own brand. This is NFM Live.
Speaker 2:NFM Live. Love it. Well, we support you guys.
Speaker 1:Enjoy. Thanks for coming
Speaker 12:on. We'll
Speaker 1:talk to soon.
Speaker 2:Thank you. Bye. Good stuff. Good Lads. Lads.
Speaker 2:They they're also pretty well positioned to cover defense tech. Korean Oh, yeah. South Korea obviously has mandatory military service. Think most people kind of interrupt college. They kind of take a break from school, go serve, then go back.
Speaker 1:Yeah.
Speaker 2:So anyways, glad that we have contact with the Korean market.
Speaker 1:Yes. Yes. Definitely.
Speaker 2:Last post close it out from Andrew Reed.
Speaker 1:I knew you were gonna pull this
Speaker 2:He one said, these shoes have gotten an obscenely high market share while accumulating zero aura.
Speaker 1:What are these?
Speaker 2:These are I think Velas. Velas? I've never heard of this shit. Wouldn't wouldn't definitely came you know kind of a
Speaker 1:He's just taking shots left and right.
Speaker 2:I think they're Veha's. Veha's.
Speaker 9:Veha's. I got a pair
Speaker 1:of these at one point.
Speaker 12:You did?
Speaker 1:Yeah. Were very much just like shoes to me.
Speaker 2:Number one question on Google. Why is Veha's so popular?
Speaker 1:I mean, I wonder if the business is doing well. I wonder if they've figured out some sort of distribution, some arbitrage, maybe some I don't know, are they more D to C? It does seem like a newer brand. And I certainly do
Speaker 2:Sounded in 02/2004.
Speaker 1:Okay. So
Speaker 2:France. France. Interesting. And, yeah. I don't know.
Speaker 2:I mean, I I think they just kinda tapped into the common projects sneaker
Speaker 1:This car Projects. What are you talking about?
Speaker 2:Well, that that was just like the definitive white Oh, okay. Sneaker. No. But common comments
Speaker 1:That was the gap of the market? No one thought to create a white sneaker?
Speaker 2:I mean, a white leather sneaker that was that was not It's from a a No. No. No. But not sportswear. That's a key thing.
Speaker 2:Not like basketball theme Sure. Streetwear. Right? Something that was versatile. Yeah.
Speaker 2:But yeah. I wouldn't wouldn't be Those would Wouldn't be caught dead
Speaker 1:in them. Those would be over farming you if you put them on.
Speaker 2:Yes. Gotta be careful not to get over farmed by your own clothing. It happens sometimes. Happens to the best of them.
Speaker 1:Nobody snaps a peek
Speaker 2:at me. But I'm happy for Veja's success. I'm happy for their success.
Speaker 1:Yeah. Overnight success. Twenty one years. Keep it going. Anyway, that's our show.
Speaker 1:Thank you so much for listening and watching and enjoying the debate. We will see you on Monday. Leave us five stars on Apple Podcast and Spotify.
Speaker 2:Can't wait.
Speaker 1:And, thank you
Speaker 2:I cannot wait.
Speaker 1:I cannot
Speaker 2:wait for Monday. I was I was figured it
Speaker 1:was Friday. And I figured out it
Speaker 2:was Friday. No. You really did think we still had You thought today was Thursday.
Speaker 1:I thought we were a day behind and I thought we still had more time. But Well,
Speaker 2:have a fantastic weekends, folks. We love you.
Speaker 1:See you. Bye.