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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.
Welcome to technology brothers, the most profitable podcast in the world. Let's kick it off with a quote from David Senra. He is quoting sage advice from Lee Lou, Charlie Munger's favorite investor, and he says, you can compound knowledge faster than money. If you truly love this game, I would suggest that you don't take shortcuts. It might take longer, but it's more rewarding.
Speaker 1:That's what we're trying to do today, compounding knowledge.
Speaker 2:Let's go. More importantly than Li Lu, David Senter is not feeling super well right now. He's got a little bit of a cold.
Speaker 1:Send him a nice comment.
Speaker 2:Send him a DM or a comment and say, heard the technology brothers told me you were sick. I hope you feel better.
Speaker 1:Hope you feel better.
Speaker 2:And, let's get him back in action. The the RSS feed needs him at the top of its of his game. Desperately. Even though David on a sick day is is better than your favorite, you know, your next favorite podcaster Yep. On their, you know, best day.
Speaker 1:Yep. Yep.
Speaker 2:We still need him back in business.
Speaker 1:Speaking of next favorite podcasters, we got David Sacks here from the All In podcast. He still has the All In badge. He's monthly now, but he's still putting up huge numbers. He's got a great post here. He says, new report by leading semiconductor analyst Dylan Patel.
Speaker 1:You know we love Dylan Patel here on the show. Shows that deep sea spent over $1,000,000,000 on its compute cluster. The widely reported $6,000,000 number is highly misleading as it excludes CapEx and r and d and at best describes
Speaker 2:Hey. We're gonna just ignore CapEx Yeah. And r and d. And and every Hey. This is this is the most American
Speaker 1:thing you could do. We we pioneer this. They even stole the idea of faking your financials.
Speaker 2:Sam Sam Altman is actually pissed that they figured this out beforehand.
Speaker 1:This is just adjusted EBITDA. It all comes back to Masa and and Adam Newman. He pioneered the community adjusted EBITDA. DeepSeek puts up a fantastic community adjusted EBITDA, ripping out CapEx, ripping out r and d.
Speaker 2:And just ripping the American markets.
Speaker 1:I mean, that like, you know, you do take CapEx and r and d out of out of
Speaker 2:Psychological warfare.
Speaker 1:The point. Right? Yeah. And, and at best describes the cost of the final training run only. And so today, we have the semi analysis post here.
Speaker 1:Deep seek debates, Chinese leadership on cost, true training costs, close model margins, impacts, h 100 prices soaring, subsidized inference pricing, export controls, MLA. And so if you're not already subscribed to semi analysis, you gotta do it, folks. You gotta do it. It's 1 of the most embarrassing things that can happen to you in Silicon Valley. Getting caught looking at a at a, at a semi analysis paywall, Yeah.
Speaker 1:That's the way to get just kicked off a board these days. It's it's disastrous. What were you saying?
Speaker 2:Yeah. If you see a VC out in public, walk up to them, say pull up semi analysis right now. And if they hit the paywall, it's just very, very negative signal.
Speaker 1:So, oh, oh, so you're not raising the next 1? Like, you're you're you're retiring?
Speaker 2:Yeah.
Speaker 1:Cool. Enjoy Aspen.
Speaker 2:Yeah. Yeah.
Speaker 1:Enjoy Aspen. Picked out some good stuff. So, Dylan Patel writes, the deep seek narrative takes the world by storm. For the last week, DeepSeek has been the only topic that anyone in the world wants to talk about. Basically true.
Speaker 1:DeepSeek's daily traffic is now much higher than clawed perplexity and even Google's Gemini, which is crazy. But it makes sense.
Speaker 2:But is that the Chinese market? No.
Speaker 1:No. No. No. I I think in America. Because the the the the the traffic stats are always, aggregated by American, like, tracking pixels.
Speaker 1:Okay. But Gemini is super embarrassing because it's a Google product. They should be stuffing it everywhere, but it's so hard to get to, as we talked about before. But close watchers of the space, this is not exactly new news. We have been talking about DeepSeek for months.
Speaker 1:The company is not new, but the obsessive hype is semi analysis has long maintained that DeepSeek is extremely talented, and the broader public in The United States has not cared. When the world finally paid attention, it did so in an obsessive hype cycle that doesn't reflect reality. Classic Americans. We get pumped.
Speaker 2:Love it.
Speaker 1:We go to the moon.
Speaker 2:We get fired up.
Speaker 1:We crash. And And sometimes
Speaker 2:forget how to go to the moon
Speaker 1:for Sometimes
Speaker 2:few decades.
Speaker 1:Yeah. Sometimes you're the world's worst.
Speaker 2:Run it back.
Speaker 1:We run it back.
Speaker 2:Mazda stop.
Speaker 1:Yeah. Sometimes you're the world's worst man, and then you lose 99% of your money. That happens.
Speaker 2:We'll get to that later.
Speaker 1:Very American. We wanna highlight the narrative has flipped the last month when scaling laws were broken. We dispelled this myth. Now algorithmic improvement is too fast, and this too is somehow bad for NVIDIA and GPUs. The narrative now is that DeepSeek is so efficient that we don't need more compute.
Speaker 1:Jevons paradox is closer to reality. The models have already induced demand with tangible effects to h 100 and h 200 pricing. So you can just go look at the at the spot market for renting these, these GPUs, and you can see Jevons paradox in action today. And so
Speaker 2:it's a it's a it's
Speaker 1:a really strong market signal.
Speaker 2:Yeah. And Ramp saw this with,
Speaker 1:Oh, yeah. That's right.
Speaker 2:Their data. Right? As a cost per token drop, the the the actual demand for them increased spending on them increased substantially.
Speaker 1:Yep. And so High Flyer is the name No. They're a Chinese hedge fund, and they started using AI in trading. And they invested in 10000 a 100 GPUs in 2021. This is before the chip ban.
Speaker 1:They didn't do anything. Everything was above board, but Yeah. They got a big cluster. It was an interesting trip
Speaker 2:to Singapore they've taken.
Speaker 1:Since then?
Speaker 2:Yeah.
Speaker 1:Well, that's the thing is that they might not have needed to because they they they just they just built up so such a huge cluster. But it goes on to say they spent over half a billion dollars on GPUs with estimates pointing to 50000 hopper GPUs across variations. So there's the h 2 h 20, the h 800, which is the nerfed 1 with that memory bandwidth, which they got around, by the way, and then the h 100, which they can still get through the Singapore loophole, and a bunch of other places. You can buy, I think, a thousand or 2000 at a time. And so they, there is an interesting angle here, which is that they truly do have goated engineers on team.
Speaker 1:Yeah. Omega cracked, I think, was the the the the term, Dylan Patel used. They have a really crazy talent strategy. They aggressively recruit top Chinese university students offering salaries over $130,000,0.0. And I assume that's per year.
Speaker 1:Oh, per month? Yeah. I think it's per year. But in in America, some people are making that per month.
Speaker 2:Yep.
Speaker 1:Gotta get your money up. With flexible roles and unfettered GPU add access, staff count is a 50 and rapidly growing. And so they have, there's an interesting kind of, like, counternarrative to the whole, like, nine nine six grind it out, work really hard. They are much more like a research lab where it's just kinda people hanging out, trying stuff. There's really, like, you know, open minded, Try whatever you want.
Speaker 1:Don't worry about cost. Just run it. And it's and it's produced remarkable results. It's more of an error rate.
Speaker 2:Pushback because, from from folks on the DEI side just because there was no non Chinese employees. I think I think seem to have made that work.
Speaker 1:Yeah. Yeah. It's, we'll see we'll see what happens. Maybe there'll be some pushback.
Speaker 2:I expect the New York Times to come after them pretty hard. Yeah.
Speaker 1:I would imagine Taylor Lorenz is writing something right now.
Speaker 2:Yeah.
Speaker 1:So in terms of server capex, it's estimated at 160,000,000,0.0 plus almost a billion in operational costs. There's some estimates here. 10000 h 8 hundreds, 10000 h 1 hundreds with large orders of h twenties in progress. H 800 has the same compute as the h h 100, but less network bandwidth. The misleading 6,000,000 figure was widely circulated as the cost of v 3, but that doesn't include r and d hardware depreciation, repeated experiments.
Speaker 1:Actual total spend is far higher. But at the same time
Speaker 2:to break it down, r and d is the entire is the cost that they're spending on their team, which is undoubtedly 1 of you know, in the Yep. Like, I would imagine in the billions of dollars a year. Yeah. Based around
Speaker 1:I mean, they have $944,000,000 in operational costs. So, yeah, that's the the OPEX is probably the mostly is r and d and salaries. They have a 50 people making a million dollars a year. Yeah. And so right right there, that's a hundred and $50,000,000.
Speaker 2:That we know of. They also Yeah. Have have been aggressively lying, and now and now the truth is coming out a little bit. But Yep. We still don't know the full truth.
Speaker 2:Yep.
Speaker 1:Right? I I I think this is probably correct. I I'm I'm This
Speaker 2:feels this feels correct. Unbelievable.
Speaker 1:Yeah. And so it's easy to lean into this and be like, you know, Dylan Patel is saying it's not it's not 5,000,000 or 6,000,000. It's actually closer to 500,000,000 or a billion, and it's easy to be like, no. It's even higher. It's 50 bill and it's, like, probably not that high.
Speaker 1:But, but it is it is interesting. And so in terms of model performance, DeepSeq v 3 is the base model, while r 1 is the reasoning model. We've been through this.
Speaker 2:Yep.
Speaker 1:And they have a couple genuine innovations here. So these are the things that you you need to see. These are the buzzwords that are gonna be going out in the AI, you know, influencer space.
Speaker 2:So this weekend, start sprinkling them into conversations at home. Yep. They may they probably won't land, but you'll sound smart. And then come Monday, you'll be able to just sprinkle them in in the workplace and really start, you know, working them into the Yeah.
Speaker 1:You gotta let people know that you you use these words so frequently. You gotta use the abbreviation. So multi token prediction, MTP.
Speaker 2:And a Tokes. Tokes.
Speaker 1:Tokes. Tokes. Multitokes prediction.
Speaker 2:Multitokes. Multitokes. Of experts. Just call these perts. Specialized subnetworks, quote, unquote experts managed by advanced gating networks.
Speaker 2:Yep. You could say, oh, yeah. My my perts are gated.
Speaker 1:My perts are gated. I mean, the funny thing is that
Speaker 2:And real ones will know exactly what you mean. Yeah. And so it's a good way to filter out who's who's larping and who's who's really, you know, at the at the forefront of of these broader trends.
Speaker 1:Yeah. I mean, like, the, like, mixture of experts was was described in detail by George Hotz when GPT 4 dropped, and he was saying that there were some hardware limitations to how large you could scale the models. And so they were effectively training 6 or 20 sub models and then wiring them all together with this mixture of experts thing. And so I've heard that term before, like, outside of this. So that's not entirely new.
Speaker 2:Too much credit.
Speaker 1:But but it does seem like combining all of these are what allowed them to to to create a great model. And then multi head latent attention, MLA, you're gonna be hearing a lot about that drastically reduces k b cache memory 93.3% less, slashing inference costs, and that's obviously very important. And so at this point, v 3 is, reportedly passes GPT 4 o from May 2024, although AI evolves fast and many new models have also improved drastically since. And there's this reasoning shift going on where post training synthetic data like RL is getting cheaper than giant pre training runs letting r 1 click quickly match others like o one. Open weights advantage, DeepSeek is now considered the single best open weights lab beating out Metas Llama and Mistral.
Speaker 1:Although, Zuck had a few things to say about that. He claims that Llamathor is gonna blow him out of the water, and he's still investing in CapEx.
Speaker 2:And Zuck loves to deliver. Yep. He's done it many, many times. So that feels believable as well.
Speaker 1:And so
Speaker 2:He kinda has to too to to save face.
Speaker 1:Yeah.
Speaker 2:He's gotta drop drop something, like, truly competitive. Yeah. Not not just, oh, great. You have distribution, and you'll get users for it, but it's not best in class. With the amount that he's spending, which is something like 60,000,000,000 Yep.
Speaker 2:A year, he's gotta show results, as well as the meta executives that are all sitting there making 5,000,000 plus a year. Yeah. And, facing that pressure internally to perform.
Speaker 1:Yeah. I mean, people I you gotta go back in the timeline when Meta dropped the first llama model because I remember the exact same hype cycle happening where people were really rooting against Sam for a variety of reasons, and people were rooting for Zuck for a variety of reasons because he was, like, on this GigaChad arc. And there was this whole this whole narrative of, like, oh, Zuck, it would be a shame if I destroyed your entire company. Like, OpenAI is going to 0 now because llamas out there, and it's free, and you can just inference it. And then I remember there was a Rune tweet at the time saying, like, have you talked to that thing?
Speaker 1:Like, it's not that good. Like, he was kinda playing, like, defense. Obviously, it got better. And at this point, it's it's pretty good, but it had the same narrative as like as like, oh, if there's an open source model, it's game over for the closed source models. And that didn't really play out because there was obviously the app layer and then all the Yeah.
Speaker 2:Openizing. Clearly not just a model company. They're shipping products
Speaker 1:Yep.
Speaker 2:Against Yep. Against the underlying model.
Speaker 1:And they do seem to be able to stay six months ahead or so. So, you know, v 3 surpasses g 4 GPT 4 o, but GPT four o is almost a year old now, May 2024.
Speaker 2:And it's crazy already despite the the mind share dominance among outside of Teapot
Speaker 1:Yep.
Speaker 2:Is insane with chat g p d. Totally. Like, I talked to a founder yesterday, and she's like, it's acting as a cofounder for me. I'm, like, thinking out loud Yep. Talking to it all day long about what I'm building.
Speaker 1:Yep.
Speaker 2:And, yeah, she could go and use, you know, Walmart or any of these alternative products, and it's just, for some reason, it's not getting traction in that same way.
Speaker 1:Yeah. And so let's let's break down the direct comparison between r 1 and o one, DeepSeek's model versus ChatGPT. Again, I think a lot of the narrative of of DeepSeek just killed OpenAI was driven by the fact that it was free. It was free. Yeah.
Speaker 1:Exactly. And so a lot of people hadn't upgraded to the $200 model o o 1 Pro. And so they were just like, well, I'm not gonna spend $200. That's too much.
Speaker 2:There's this opportunity to make run that everybody saw as really bearish because US companies are spending
Speaker 1:And then there's the China dynamics.
Speaker 2:Dollars. Yep. And then there's the then there was the concern around, you know, a lot of people just trading against the news, not really trading against Totally. Kevin's paradox. Yep.
Speaker 2:Right? That's true. And, and then there's the cost of, like, okay. If you introduce a free product that's on that's better than
Speaker 1:Yeah.
Speaker 2:The free product of your competitor, what happens?
Speaker 1:Yep.
Speaker 2:But, consumer behavior is not always entirely rational.
Speaker 1:Yep.
Speaker 2:And especially in the context, I just don't see it's still hard for me to see DeepSeek, you know, becoming truly
Speaker 1:Sticky.
Speaker 2:Sticky and dominant. Right? Totally. Because ChatGPT among consumers is a very loved product. Yeah.
Speaker 2:And you can't underestimate consumer love because so many people have had magical experiences. If you go, hey. You can use DeepSeek, and it's better. But they're like, well, I already love I already love ChatGPT. Exactly.
Speaker 2:It does exactly what I want.
Speaker 1:And it's learned a bit about me. Some of my data's in there already. Oh, and I also there's a little share button. So when I generate something with ChatGPT, I can share the link that onboards
Speaker 2:to the The value for us, it's like, okay. For $200 a month Yep. We would happily, for the same service, pay $2 a month. Yep. So by telling us that we can get something that's comparable for free the value trade off is, like, not that significant.
Speaker 1:I only want the best, most cutting edge model that has the most features at a at a at any given time. But a lot of people aren't aren't in that boat. A lot of people do just want whatever's free. So, is r one's performance up to par with o 1? I wanna read this pretty much this whole paragraph here.
Speaker 1:On the other hand, r 1 is a is is able to achieve results comparable to o 1, and o 1 was only announced in Sept. 0. How has DeepSeek been able to catch up so fast? The answer is that reasoning is a new paradigm with faster iteration speeds and lower hanging fruit with meaningful gains for smaller amounts of compute than the previous paradigm. As outlined in our scaling laws report, the previous paradigm depended on pre training, and that is becoming both more expensive and difficult to achieve robust gains with.
Speaker 1:The new paradigm focused on reasoning capabilities through synthetic generation and RL and post training on an existing model allows for quicker gains with a lower price. The lower barrier to entry combined with easy optimization meant that DeepSeek was able to replicate o 1 methods quicker than usual. As players figure out how to scale more in this new paradigm, we expect the time gap between matching capabilities to increase. Note that the r 1 paper makes no mention of the compute used. This is not an accident.
Speaker 1:A significant amount of compute is not is needed to generate synthetic data for post training r 1, not to mention r l. R 1 is a very good model. We are not disputing this, and catching up to the reasoning edge this quickly is objectively impressive. The fact that DeepSeek is Chinese and caught up with less resources makes it doubly impressive. But some of the benchmarks r 1 mentions are also misleading.
Speaker 1:Comparing r 1 to o 1 is tricky because r 1 specifically doesn't mention benchmarks that they are not leading in. And while r 1 matches in reasoning performance, it is not a clear winner in every metric. And in many cases, it's worse than o 1.
Speaker 2:This was your actual user experience where you were trying it and you're and seeing, okay. This output is not on par with what I get
Speaker 1:from
Speaker 2:g p t.
Speaker 1:And and my prompt was not something that's baked into some math eval or physics test. Yeah. It was just, can you summarize this book in 5000 words? Did you give me 5000 words, and was it was it factually accurate or not? And o o 1 pro gave me exactly 5000 words, a little bit more.
Speaker 1:It's great. And deep sea gave me a thousand words. And it's like, what how how am I
Speaker 2:the test.
Speaker 1:It failed the it failed my prompt for whatever.
Speaker 2:Functional, yeah, functional test.
Speaker 1:Exactly. And then and then as a test
Speaker 2:This is again from a consumer standpoint. You're not gonna notice these small intricacies in terms of, you know, having the model, you know, run at 50 physics problems because you wouldn't necessarily wouldn't have been able to get any of them yourself. Right? So it's almost irrelevant. Yep.
Speaker 2:What matters is actually the output, which is what people want and what they're paying for
Speaker 1:Yep.
Speaker 2:Around specific problems that they need the model for.
Speaker 1:Yeah. And so and this doesn't even include o 3, the latest model from OpenAI that hasn't been fully released yet. O 3 has significantly higher capabilities than both r 1 and or o 1. In fact, OpenAI recently shared o 3 o three's results, and the benchmark scaling is vertical. Deep learning has hit a wall, but a different kind.
Speaker 1:And so then there's also the question of Google's
Speaker 2:Great great line Yeah. From Dylan.
Speaker 1:Google is cruising wall
Speaker 2:looks like a wall, by the way.
Speaker 1:Yeah. It's it's it's completely up into the right. It's fantastic. But it's on ArcGIS, SweeBench, and Frontier Math, advanced mathematics, like, things that most consumers might not even care about the benchmarks on, but are potentially good proxies. Because a model that can do insanely advanced mathematics might be better at, you know, generating a recipe.
Speaker 1:And so Google jumped into the game to very little fanfare. They did not really break through.
Speaker 2:Other Really struggling on the marketing front.
Speaker 1:Totally. And so, while there was a frenzy of hype for r 1, a $250,000,000,000,0.0 US company released a reasoning model a month before for cheaper. Google's Gemini Flash 2 o thinking. What a fantastic name, guys. I don't know why it didn't take off.
Speaker 1:You got 12 different words that no one knows what they mean.
Speaker 2:It's possible that Clippy is, like, no longer able to be trademarked. Yep. So Google should just take
Speaker 1:Clippy for its next model. Yeah. So the model is available. It's considerably considerably cheaper than r 1 even with much larger context length for the model through the API. And, again, I'm signed up for Gemini Advanced Pro Plus plan.
Speaker 1:I pay for it. I have no idea if I have access to Flash Thinking 2 o, and I have no idea how I would even go and find it. If I if I Google it, I'm gonna get the paper. I'm gonna get some tweet. Like, it's it's it's so hard to access Google's models.
Speaker 1:It's so embarrassing for them. Get it together, guys. Unreported benchmarks, Flash 2 o thinking beats r 1. I I remember Peter had a fantastic Peter Thiel had a fantastic, like, distillation of what's going on in AI where basically, all the different AI labs are you can think about them as, like, lemonade stands, and they're all obsessed with perfecting the formula for lemonade. And none of them are thinking about where to actually place the lemonade stand.
Speaker 1:And when you're running a lemonade stand, all that matters is that you're on the business corner. Location. Location. Location.
Speaker 2:Yeah. Yeah. Yeah. And and that and that's just what not even the corner. What neighborhood you're in.
Speaker 1:Exactly. Exactly. And and so you could you could imagine that at Google, they're like, Gemini flash thinking 2 o. We beat this benchmark. It's amazing.
Speaker 1:Everyone's gonna love it. It's like, that's not how products work, guys. Like, that's just not Got
Speaker 2:us.
Speaker 1:Like, no no one is like, I'm gonna go figure it out at some point, but it's gonna take me thirty minutes to find this product and figure out that I'm using it.
Speaker 2:Again, you don't you have access to OpenAI's reasoning model. So you can just use that. Yeah.
Speaker 1:Exactly. It's easier
Speaker 2:to access.
Speaker 1:Exactly.
Speaker 2:Your data's already there.
Speaker 1:Yeah. And then now in every single Google product, there's some sort of pop up saying, like, hey. Do you wanna use Gemini for this? Do you want Gemini to work on summarize your emails? And I'm like, well, which Gemini?
Speaker 1:You guys have 17 different products. And, like, how is it gonna integrate?
Speaker 2:I know. I'm I we're dealing with this email Yeah. Like, related bug right now
Speaker 1:Yeah.
Speaker 2:For TV, related to a new domain.
Speaker 1:Okay.
Speaker 2:And I keep I I everything is set up properly, but it's not working. Yeah. And I they just keep sending me the pop ups of Gemini, and I'm like, you know
Speaker 1:You can't get the basic, like like, level 1.
Speaker 2:Maybe I should actually try it with Gemini.
Speaker 1:Hey, Gemini. Fix this. Fix this. Fix this. Yeah.
Speaker 1:And so on reported benchmarks, Flash thinking 2 o beats r 1, though benchmarks do not tell the whole story. Google only released 3 benchmarks, so it's still an incomplete picture. We think Google's model is robust, standing up to r 1 in many ways, but receiving none of the hype. This could because of Google's lackluster go to market strategy and poor user experience. But also, r 1 is a Chinese surprise, which is
Speaker 2:Nobody expects
Speaker 1:huge advantage. To be clear, none of this distracts from, none of this distracts from DeepSeek's remarkable achievements. DeepSeek's structure as a fast moving, well funded, smart and focused startup is why it's beating meta giants like Meta in reasoning and releasing a reasoning model. And they did beat Meta, like, Llamophore is still in training. They haven't released a reasoning model, and it certainly would be cool if this had just baked itself into At
Speaker 2:least Zuck is breathing a sigh of relief knowing that they actually spent The money what? However many billions getting this model out.
Speaker 1:Oh, yeah.
Speaker 2:He's like, okay. We're not totally crazy. No. No. We're spending 60.
Speaker 1:And I think that's why the stock popped and earnings. I mean, earnings were crazy, but I think I think everyone was very excited about, like, his the his positioning on the AI infrastructure investment. And so DeepSeek has cracked the code and unlocked innovation that leading labs have not been able to yet achieve. We expect that any published deep seek improvement will be copied by Western Labs almost immediately. What are these improvements?
Speaker 1:We we covered a little bit of these, these training pre and post. V 3 utilizes multi token prediction at a scale not seen before. These are added attention modules which predict the next few tokens as opposed to a singular token. And so you can imagine, you know, the old version of autocomplete on the iPhone, it would say, you know, would you like to go to and it would have, like, breakfast or lunch pop up. But now you but, you know, you see some of these models where it's predicting 3 or 4 words.
Speaker 1:It's kind of like that, but baked into the model at a very, very low level. So it's just more efficient because it is it says, oh, yeah. After this sentence, usually, there's just this, you know, 3 words that go together. And and all of those go together. The added there are added considerations like doing FP 8 accuracy and training.
Speaker 1:We talked about this. Leading labs have been doing FP 8 training for some time, so that's a little bit overhyped. There's a lot of things where where people just went through the deep seek paper and everything that they were doing, they assumed was novel. And they were like, oh my god. They're they're they're they're they're using data to train it.
Speaker 1:Like, no one thought of that. And it's like, no. Everyone's using data. Everyone's scraping the web. Everyone's, you know Yeah.
Speaker 1:Like, running it on GPUs.
Speaker 2:Synthetic data side as well.
Speaker 1:Yep. And so,
Speaker 2:And did I don't know if this is gonna come up later in the show, but some, lab at Cal Yeah. Was able to generate a reasoning model with 450. Yeah.
Speaker 1:I love that.
Speaker 2:So anybody working on models out there, we're good for our $4.50.
Speaker 1:Yeah. We're good for our $4.50. So rather than decreasing overall investment, mixture of experts, which is, which is where 1 large model is comprised of many smaller models that specialize in different things, and this is an emergent behavior. Historically, MOE models have faced, struggles, about how to determine which token goes to which sub model or expert. Deep seek implemented a gating network that routed tokens to the right expert in a balanced way that did not detract from model performance.
Speaker 1:So basically, you're getting like, instead of activating the entire model, which is very expensive, requires a lot of energy, you're just accurate activating, like, 1 little section of the brain. But, despite concerns that MOE efficiency gains might reduce investment, Dario, over at Anthropic points out that the economic benefits of more capable AI models are so substantial that any cost savings are quickly reinvested into building even larger models. This is Jevons paradox. Yep. Rather than decreasing overall investment, MOE's improved efficiency will accelerate AI scaling efforts.
Speaker 1:The companies are laser focused on scaling models to more compute and making them more efficient algorithmically. In terms of r 1, it benefited immensely from having a robust base model, v 3. This This is partially because of reinforcement learning. There were 2 focuses here, formatting, ensuring that it provides a coherent output, and helpfulness and harmfulness to ensure the model is useful. As mentioned in the scaling laws article, this is what happened with o 1.
Speaker 1:Note that the r 1 paper, no compute is mentioned. This is because mentioning how much compute was used would show that they have far more far more jpe GPUs than their narratives and tests.
Speaker 2:Wouldn't have had billions and hundreds of billions wiped out of its market cap.
Speaker 1:Yep. And Dylan also says that, additionally, a portion of the data DeepSeek used seems to be data from OpenAI's models, which, of course, makes it easier because you're just cloning the outputs. And so you're you're you're you're optimizing against, like, a very set benchmark. If you want a GPT 4 model and you're training on all GPT 4 data or a lot of GPT 4 data, you're gonna get a lot closer to GPT 4 pretty quickly.
Speaker 2:Again is interesting because they would have had to spend a ton of money with OpenAI, right, which we've talked about before, the same thing that TikTok did to scale. Yep. They just spent billions on user acquisition Yep. On Snapchat and Instagram. Yep.
Speaker 2:And it's this weird dilemma that the other platforms get in where they're like, well, we'll take the billions now
Speaker 1:Yep.
Speaker 2:And even though we're gonna lose out on, you know, potentially billions later.
Speaker 1:Yep. And so, he he concludes with a with a with a couple different takeaways. DeepSeek's cut rate pricing may be 0 or negative negative margin, partially to gain market share and investor attention. And then he highlights Jevons paradox again, talking about, the AI race, is similar to semiconductor fabrication, cutting edge nodes, command premium margins, everything older quickly commoditizes. Yep.
Speaker 1:And that's like the story of TSMC versus Intel. The dynamic this dynamic spurs an endless cycle of scaling up new models and hardware investment benefiting chip providers like NVIDIA. There are exports restrictions. H 1 hundreds are fully banned. They've been replaced by h 8 hundreds.
Speaker 1:H 8 hundreds, I think, were banned, and then the h 20 was introduced. More stringent US bans may come. Depends where like, we haven't seen exactly how the government will react to this.
Speaker 2:It's a really funny dynamic that the the our government doesn't want NVIDIA selling them great chips. Yep. So why is it okay with them selling them any chips at all? Yep. And what you know, assuming that they can
Speaker 1:I mean, the steel man here is that if you're NVIDIA and you're Jensen Huang and you've been building this company that you control and own for thirty years, and for twenty nine of those years, the government has been telling you, go global? We want you to be as big as possible. Get those tax revenues up. Hire people. It's cool.
Speaker 1:These are our allies. The Internet's gonna make China democracy, and they're part of the World Trade Organization. So absolutely go manufacture over there, do business with them. We love this. We you know, we'll put you in touch with the the the Yeah.
Speaker 2:I totally I totally understand. Run pull you. Side.
Speaker 1:Like, that's kind of harsh. Yeah. And so unwinding that relationship
Speaker 2:is not And if and if if NVIDIA had a blanket ban on selling to China or any any countries Yep. In close enough proximity to China that they can act as a as a proxy Yep. It would destroy. I mean, it would it would wipe potentially trillions out of the out of the out of the market.
Speaker 1:See, I might actually disagree with that because I I I think you're right that they wouldn't be as high of a stock, but there's an interesting dynamic where the best time to deleverage from China was when there's insane demand in America. Yeah. And that's what happened during the AI boom in 2023, '20 '20 04/00 where Yeah. That's right. If there was ever a time to say, hey.
Speaker 1:We're gonna pull back in China. It's when it's when Elon Musk and and Oracle and Same old man needs same old man needs like, we will buy every single GPU you can make.
Speaker 2:Yeah. Yeah. So so, the Altman needs 2, he needs 2000000 GPUs just in Apple. Right?
Speaker 1:Yeah. Exactly.
Speaker 2:That's that's He'll
Speaker 1:buy them all.
Speaker 2:NVIDIA is gonna produce 6000000 total this year.
Speaker 1:Yep.
Speaker 2:Right? So just 1 guy
Speaker 1:Yep.
Speaker 2:It it could could potentially be a third of NVIDIA's.
Speaker 1:I need a
Speaker 2:And he's not buying those all this year. It's gonna be spread out over time. But I
Speaker 1:need a I need a steel hat to put on when I'm steel manning, because, again, the the steel man here of why would Jensen not wanna do that. Obviously, people have been, like, very critical of him not putting America First. But the flip side is, if you if you do say, okay. I'm only gonna sell to these crazy American AI companies, and then there's a bubble and it pops Yeah. You are more fragile than if you have a
Speaker 2:diplomatic in a it's not like The United States and China have declared war on each other. It's just this great power conflict that kind of moves along slowly, and everybody tries to
Speaker 1:kind of allies, not enemies. Dependent on so much. Totally.
Speaker 2:I mean Totally.
Speaker 1:And so, this is an interesting stat. I didn't I hadn't heard about this, but the Bank of China announced a 1,000,000,000,000 yuan, hundred and 40 billion US dollar AI subsidy. Let's ring the size gong for China.
Speaker 2:The 1 t.
Speaker 1:Hey. Size is size.
Speaker 2:No. Size is size.
Speaker 1:Size is size.
Speaker 2:Size gong does is is a nationalist Size gong wins for everyone. Yep. And if anything, we hope the the the ringing sound inspires 1 of our listeners to invest a trillion in something.
Speaker 1:Exactly. And so a hundred and 40,000,000,000 subsidy AI subsidy after meeting DeepSeek's founder. So the guy literally goes and pitches the government.
Speaker 2:This all seems very
Speaker 1:actually put
Speaker 2:up a hundred and 40,000,000,000, and he's like, yeah. Conveniently timed. Right?
Speaker 1:It's their Stargate.
Speaker 2:You have yeah. You have, Sam Altman gets Trump to do his press tour for him. Less than a week later, China meets with the DeepSeek founder and announces something very similar.
Speaker 1:Yep. But interestingly, this is the Bank of China putting up a subsidy of a hundred and 40 billion. Trump hasn't put up anything for other than just his name and and
Speaker 2:Yeah. Yeah.
Speaker 1:A a a couple minutes in the in the Sam aura
Speaker 2:Sam aura farmed him.
Speaker 1:He aura farmed him, whereas the DeepSeq founder gold farmed him, basically. So, the China has a goal of self reliance and advanced technologies, obviously, and this aligns with that. And so despite large GPU stocks, scaling to serve millions of new users is tough. Future export controls may starve them of advanced chips, and there's a big question about, was this an aberration? Will they be able to keep up?
Speaker 1:A lot of that's predicated on, can they, can they either get around the export controls reliably at a at an order of magnitude larger scale, or can they get SMIC and SME, their version of TSMC and ASML? Can they get those, chips up and running and start making competitive GPUs internally? Because if they can do that, it's game over. Like, they can they they could make a a billion chips. And with with something like a hundred and $40,000,000,000 of, like, 10
Speaker 2:world class at copying.
Speaker 1:Totally. And that's all they have to do.
Speaker 2:And and I don't even say that in a way to slight them. No. But that is historically what they've done
Speaker 1:over and over and over. Yeah. And they have ASML machines. They have t s s t TSMC machines.
Speaker 2:This is what entrepreneurs, you develop some hardware products or consumer product. You go to China. You see your factory. If you walk to the factory next door, they'd probably exact item Totally. Almost a 1 for 1 Yep.
Speaker 2:Within a year if you're actually really selling well.
Speaker 1:Yep. So
Speaker 2:it's just ruthless. They're good at it. I'm sure they're gonna have their own NVIDIA TSMC.
Speaker 1:Yeah. We'll see you
Speaker 2:in a few.
Speaker 1:Let's close with some of these conclusions. Efficiency does not mean reduced investment. This is Jevon's paradox. Cost savings from new architectures like mixture of experts spur more scaling, not less. Fast follower, deep sea lags top labs, but closes gaps swiftly with new paradigm reasoning.
Speaker 1:Their open source stance accelerates industry wide progress. Oh.
Speaker 2:Just a sec.
Speaker 1:Frontier capability commands premiums, but DeepSeek's low pricing disrupts incumbents, potentially forcing big labs like OpenAI to innovate even faster, and we're seeing that. You know, there's gonna be more pressure. Hey. Release o 3. Get it on the free tier.
Speaker 1:Get an ad product in there. Do something to bring this to the masses so you can cut stem the bleeding of people installing the DeepSeek app. Long term outlook, hardware demand isn't going away. Quote, more advanced AI, more GPU spending, more scaling. Export controls will likely tighten, but we're gonna need to see where this shakes out.
Speaker 1:I think, Jacob Helberg might be on the team that's working on export controls and tech, deals globally.
Speaker 2:We actually need a rack of GPUs on the set. Yep. I think we should get some h 1 hundreds Yeah. And just replace that cache with some
Speaker 1:A couple GPUs?
Speaker 2:With a with a couple GPUs. Yeah.
Speaker 1:Yeah. Great. And so we think the east versus west debate in AI models will continue, and the new paradigm is good for NVIDIA. Very interesting. So fantastic analysis from Dylan Patel.
Speaker 1:Highly recommend subscribing to semi analysis if you haven't already. It is a great resource, and we love to see deep dives on the timeline.
Speaker 2:A great poster too. Yeah. He's a great poster. Follow. Yeah.
Speaker 2:Follow him. DM him. The technology brother sent me.
Speaker 1:Exactly. Exactly. Comment on on his post. So, let's go to Drone Horizons. A great piece in Pirate Wires.
Speaker 1:Another another outlet that you should definitely be subscribed to. This 1 by GB Rango. Fantastic name.
Speaker 2:Great name.
Speaker 1:Pirate Wires says, drone horizons are deep dive on how drones will change the future, not just in war, but in everything from construction infrastructure and interplanetary space. The widespread adoption of UAV technology piggybacked on the inexorable AI surge could significantly retool both international power relations and the daily lives of regular people in a manner that few understand. Today in Pirate Wire's GB Rango systematically outlines the trajectory of inevitable drone developments that are going to permeate every pore of society from agriculture to medicine to policing and national security.
Speaker 2:And firefighting, which is particularly relevant to the last month we had here in LA.
Speaker 1:And so let's kick it off with GB Rango's lead, which is, a a little anecdote here. The stadium is a roar with 80000 raucous attendees and casts a short shadow in the midday sun. In the distance, peppered specks rise from nests unseen before gathering over the high horizon like iron filings in a magnetic field. Small payload drones, hundreds of them, race balefully forward. The orchestrate the orchestrated swarm twists and folds in hive like unison as it approaches its target.
Speaker 1:In response, nearer to the stadium, another group of drones ascend ascends in concert and rushes to meet its hostile counterpart. The confrontation is swift and casually anticlimactic with only a few city goers caring to notice the whir of propellers or the hissing and buzzing of the interceptor's high powered microwave pulses. The sky is clear once again, and the game goes on uninterrupted. The emergence and facile neutralization of drone threats is commonplace here in a potential future. This cross section of a shocking and interdependent future and those to follow are meant to demonstrate and warn of the transformational nature of an of an imminent drone age shift.
Speaker 1:Darkest thing. Pretty crazy. But I think this is 1 of those things where you see 1 side of the technology development, and you don't realize that there is the flip side that's countering it just as aggressively. Like, in 02/ or the or the, you know, the 02/, the if every day you were reading articles about email spam Yeah. And you had no knowledge about spam filtering and the fact that that was possible, you would be like, wow.
Speaker 1:Why would I ever sign up for email? Like, it's just gonna get worse and worse and worse. But, of course, it's an arms race, and there's anti drone technology, which I think we'll talk about as well. And so I'm not quite as black pilled as some people on this front.
Speaker 2:I also find it hard to imagine this future, if you put in the context of how dissimilar would it be if somebody launches a hypersonic at a stadium of people and we launch
Speaker 1:Yeah.
Speaker 2:You know, some type of countermeasure and stop it, that would be national news. Yep. So I would hope we don't experience this future because, and and and in this illustration, the stadium doesn't even notice. Right? But just very dark.
Speaker 2:But, this is, like, the threat, so it's worth, you know, really paying attention to.
Speaker 1:And there are, so he breaks it into 6 or 7 different sections. We'll give you a little tour of the article, and you can go read the full post on Pirate Wires. Says an infrastructure and agriculture. Infrastructure development will undergo drastic changes with the advent, and ubiquitous drone of advanced and ubiquitous drone technology. Construction site sites strangely devoid of human laborers, instead populated by powerful heavy lift drones, nimble inspector craft, and bipedal robots will be more productive, efficient, and safer than ever before.
Speaker 1:Gargantuan cranes with arms outstretched, fresh metal glinting through measured pivots rotate powerfully over the earth. He's such a good writer. This is why I I love this style of writing. It just takes you on, like, this this tour instead of just scratching the surface.
Speaker 2:Fact. Yeah.
Speaker 1:It's like it's really, like, pleasurable to reach
Speaker 2:the surface. Can you imagine the drones, you know, working this construction site? They run into an issue or they need some type of human intervention, and you're the human that's on call, and you get a call from this nice sounding robot voice. And they're like, hey, bud. Stuck.
Speaker 2:You mind stopping by the site for a few? We could really use a hand here. It's like a human voice. Yeah. And then, you know, hopefully, after you finish as a human, the the drones are nice enough to say, hey.
Speaker 2:Thanks, bud.
Speaker 1:Yeah.
Speaker 2:Probably won't need you anymore today, but, you know, appreciate you stopping by. Yeah. And, this is the flip right now. We tell, you know, we tell the models what to do. Yep.
Speaker 2:Eventually, they'll they'll tell us what to do.
Speaker 1:We are the APIs. Yeah. But, I mean, there is obviously, there's, like, there's the job displacement question, but the the flip side is, like, I think every almost every single time a major skyscraper is built, there is a single digit death toll from workers just because it's so dangerous. And you put 10000 people on a construction site for five years or something, and, like, things are gonna go wrong. And so there is a pretty significant opportunity to
Speaker 2:be able to press in oil and gas. Right?
Speaker 1:Yeah. Totally.
Speaker 2:On these frack fracking Yep. Every every now and then a video will go, you know, super viral. And it's it's an active, you know, fracking site, and then just that kind of action that's going on where there's heavy machinery whipping around. Super dangerous. Yeah.
Speaker 2:It's just super dangerous. So So
Speaker 1:he says in the agriculture world, in the coming age, farms will not sleep when the sun goes down. Drones will work around the clock to protect crop yields and monitor livestock. Rustic family barns sitting bare on flat plains will look like nocturnal beehives with luminous agents approaching for payloads before dutifully buzzing back into the dark. These small flying machines will fit will flit nonstop through thousands of crop road acres addressing issues like pest treatment, disease, and water shortage on the individual plant level. Very cool.
Speaker 2:And so We gotta get him to describe us
Speaker 1:Yeah. Preparing us. What a great writer. Seriously.
Speaker 2:John threw on his jacket.
Speaker 1:Yeah. And yeah. And this next this next segment on, emergency medical services was actually highlighted on Pirate Wires. Drone delivered organs should be standard protocol for transplants. And he says over 46000 organ transplants were conducted in The United States in 2023.
Speaker 1:Quicker transport times are associated with better patient outcomes. In and in the sort of major delay described above is is not unheard of. In 2023, a pro Gaza ceasefire protest on the San Francisco Oakland Bay Bridge blocked all westbound traffic for four hours. Three UCSF organ transplant deliveries were significantly delayed, 1 of which had to be rerouted over the Golden Gate Bridge. But, 1 transplant surgeon at u UCSF noted that 2 other large transplant centers in the Bay Area, Stanford and CPMC, were probably suffering from the same issues as well.
Speaker 1:Now while no known complications have been directly attributed to the protest, the proliferation of drone technology will completely eliminate the transport delay risks opposed
Speaker 2:Yeah. I mean, a lot of this stuff a lot of this stuff happens via helicopter now. Yeah. And there's even there's companies like Blade that actually have a really I think at 1, Blade's organ transplant business was bigger than their consumer business I had
Speaker 1:no idea.
Speaker 2:During I think it was COVID. Wow. Might have that off. But, yeah, this is actually a very big business already, but it's kind of funny to think about, you know, needing to fly in Oregon from 1 side of a city or county to another, and you just put it in a helicopter. Like, it's not the most efficient if you're just basically needing to transport the equivalent of, like, an ice chest.
Speaker 2:Right?
Speaker 1:Yep. He goes on to explain search and rescue, maritime efforts, larger boats serving as bases of operation for small drone swarms that can expand radially outward and aid in the geographic process of elimination. Larger, unmanned aircraft systems with multi day endurance will work in concert with these teams to survey vast area areas of open sea for survivors and identify points of interest. That just seems like a new capability. Yeah.
Speaker 2:But it doesn't seem like a job placement. Pilots that go go up in their planes, and they take turns just taking, you know, basically running.
Speaker 1:Yep. There's some sort of, like, grid search they have to do, but it's a funny path. It's not
Speaker 2:And they have to high up enough to get enough coverage Yep. In a world where you can send a thousand drones Yep. And almost instantly scan huge huge surface area.
Speaker 1:And so this would have been useful during hurricanes Helene and Milton, both of which struck in the and, drones were pivotal in the preparation for in response to these disasters. He goes on to explain that drones will have an impact on firefighting, which I think we discussed previously. Yep. And in America, Fire Department use of drones is almost exclusively limited to the realms of surveillance and intelligence gathering. In the wake of the recent Los Angeles fires, which have reportedly resulted in the deaths of at least twenty four people and re reeked over $250,000,000,000 of economic damage.
Speaker 1:This lack of progress what?
Speaker 2:Two weeks ago, it was at a hundred and 50 billion.
Speaker 1:So it's still climbing.
Speaker 2:It's still climbing. Yeah.
Speaker 1:Compounding this international delta is the fact that across all US public safety agencies, 90% of drones in use are designed and manufactured by DJI, a company that was recently added to the Department of Defense list of Chinese military companies. While that number is from a 2020 survey and steps are being taken to limit Chinese don't drone usage, the status quo remains largely unchanged. So he goes into talk about foreign dominance and how they can, how drones will be effective in the military, talks about regulation of drones and drone deliveries, as well as policing and the state, and finally, national security and war. National security, of course, is a paramount rev is a paramount relevance in the discussion of drones. The nature of war is changing faster than it has at any point since the post World War two nuclear proliferation, and drones are 1 of the major cruxes of this change.
Speaker 1:It is essential that America not rely on China for any segment of the defense supply chain, let alone UAS design and manufacturing.
Speaker 2:Yeah. And this goes back. I posted a while back, and it resonated. We needed a surrogate for domestic drone production.
Speaker 1:Yep.
Speaker 2:And the reason for this is that if we were in a conflict with China, they could produce presumably millions of drones a month, and we can probably right now produce. I don't know if we, like, needed to turn it on and
Speaker 1:produce locally.
Speaker 2:Yep. But, however, it would be a fraction of what China could produce, and the capability would not be there Yep. Which is just a terrible place to be in. Yeah. Like, a huge part of the reason that we we were successful in World War two was because we were able to turn on this massive, you know, manufacturing capacity and just out out, produce, our, out produce the competition.
Speaker 1:Yeah. This is interesting. He he ends with, space and visions of the future. Below the arcing of stars and spirited space adventuring of generations to come, the skies are clear, save the birds and an occasional transport drone passing silently overhead. Towering biohybrid buildings draped with verdant ivory attended to by swaths of assiduous airborne robo gardeners, looks as if they might have emerged in search of sunlight from the Earth itself.
Speaker 1:A period of peace less fraught with tension than its doctor Strangelove type predecessor has settled upon the world. This is not for want of bad bad actors, but for their inability to find secrecy. And he closes with, now with all of this having come to pass, there seems to be an almost palpable optimism, a sense that things can change, and that we have a significant say in how they change. A weird coalition between humans and their hive minded autonomous aircraft, once an unnerving prospect, now powers the world forward in ways that not even the most visionary among us could have seen in a crystal ball ball. This or something else entirely lies ahead of us.
Speaker 1:With courageous optimism, we step into drone filled horizons.
Speaker 2:So clearly, GB Rango should write some science fiction Yeah. Because we'll read it. So good. 1 thing that's interesting too, there's already technology that's been developed to make drones silent. So it's some element of of the Propeller design.
Speaker 2:Yeah. Propeller design. It's very crazy. Right now, it's actually nice that you can tell when a drone is. I've had situations where a drone flies over my backyard.
Speaker 2:Yeah. I got there and I I look up at it. I'm like
Speaker 1:Get out of here.
Speaker 2:Get out
Speaker 1:of here.
Speaker 2:Scram. Scram. Scram.
Speaker 1:Yeah. Get off my
Speaker 2:Not much you can do. But, imagine when they're completely silent. You're just you know, somebody could fly it over your backyard, on a on a on a battlefield. It's pretty terrifying to think about, you know, this kind of, assassin that can move it hundred plus miles an hour instantly, take you out without you even hearing about it. So very dark, but, it's a good time to get it.
Speaker 2:So so 1 thing I would say, kind of a call to action for the audience, it see there are a lot of new American companies taking on this issue Yep. Developing drones for all these different use cases. If you look at Augustus and Rainmaker, they're developing drones for cloud seeding and agriculture. We like, we could probably have ten ten to a hun you know, 50 x more drone companies attacking all these different areas. Everything from, like, the production down to the parts level Yep.
Speaker 2:All the way up through these sort of, like, app layer, product layer companies, for organ transplants, you know, or sorry. Not transplants. Transports.
Speaker 1:Transports. Yeah. And both of that. Yeah. That's right.
Speaker 2:Yeah.
Speaker 1:Cool. We'll go give it a read on Pirate Wires. We love Pirate Wires and highly recommend that you subscribe. It would be just crushingly embarrassing to get caught looking at a Pirate Wires paywall in front of someone in tech.
Speaker 2:Brutal. You don't
Speaker 1:want that to happen to you.
Speaker 2:Yeah.
Speaker 1:And if you ever run into Solana, he has the ability to just search your email in the database, and he'll now.
Speaker 2:Yeah.
Speaker 1:So you can't fake it, guys. Can't fake it. You gotta be real real subscriber. So let's go to Stratechery, breaking down more tech earnings from big tech, the hyperscalers. Microsoft and Meta earnings went live, and Ben Thompson broke it all down.
Speaker 1:And I know I don't
Speaker 2:know what day it was. We already covered Met a lot of Meta's earnings.
Speaker 1:So we can kind of rip through Microsoft and just give you a quick update for The Wall Street Journal. Microsoft's flagship cloud computing business experienced a slowdown in growth last quarter as constraints on data center supply once again weighed down results. Revenue for tech for the tech giants, Azure cloud computing division, which is closely watched by investors, grew 31% at the low end of company's per of the company's projections. Chief financial officer Amy Hood said Azure growth would again be 31 to 32% this quarter, a projection that disappointed investors. Microsoft stock was down 4 and a half percent in after hours trading.
Speaker 1:Fortunately, on public, you can get in on the after hours action now. Yep. They are allowing, after hours trading. So first off, Ben says, Microsoft said the AI growth was capacity limited, but would be rectified by midyear. It's nice to not have to be on the hook for that new OpenAI data center.
Speaker 1:But the bigger miss in Azure was somewhat obscure, but interesting in its own right. Basically, summarizing the Wall Street Journal, Ben says, Microsoft pivoted their scale motion. Think small and medium sized businesses in second tier geographies to be very focused on AI instead of boring old cloud migrations, and they didn't get many takers. So they're going to second tier geographies outside The United States Yeah. And they're going to small and medium businesses.
Speaker 1:And instead of saying, hey. You have this data on this old server. Let's get it on the cloud. They are now shifting to a model of saying, hey. Can we get AI installed in your team's integration?
Speaker 1:Can we get AI installed in, looking at all your data, running streaming analytics, looking at your enterprise? And that's a harder sell for a lot of businesses that are just, hey. Like, I kinda have I I'm running on vibes. Like, I'm the AI. I know if if revenue's down, I kind of know why.
Speaker 1:I don't necessarily
Speaker 2:email, like, to dig everything. See an AI have a power lunch.
Speaker 1:Exactly. It's a harder sell, apparently. That's what we're seeing. Could turn around. We never know.
Speaker 2:Yeah.
Speaker 1:So now they will go back to just selling actual cloud services and expect to see a revenue rebound. Count 1 for my thesis that bottoms up AI adoption will be a hard sell. And this is also why there's those private equity roll ups, VC backed roll ups that are Yeah. That are buying companies and then forcing them to use AI because it seems to be a hard sell from an outsider. And so you could always ask, hey.
Speaker 1:Why is Long Lake, rolling up HOAs and then dropping AI on top of it? Why don't they just build AI for HOAs and then sell into the existing HOAs?
Speaker 2:Yeah.
Speaker 1:Well, maybe the sales motion is very difficult. Maybe they want a new model. And so if they own the company Yeah. They get to do
Speaker 2:it with them. My HOA management company still runs on paper sent in the mail that has to be sent back to them and then processed. Yeah. It's like the easiest software integration to just allow online surveys.
Speaker 1:But if you And they haven't had that out.
Speaker 2:So imagine how many a HOA software companies have pitched them. Look. You could be way more efficient. You could save money here, all the stuff. Don't care.
Speaker 1:Yeah. And they say, oh, you're trying to pitch me some esigning software? How many employees you got? 50000? I'm not interested.
Speaker 1:Yeah. It'll be too expensive.
Speaker 2:Those numbers up.
Speaker 1:Yeah. Yeah. So on the flip side, Satya Nadella claimed good progress with Copilot adoption. We We are seeing accelerated customer adoption across all deal sizes as we win new Microsoft three sixty five Copilot customers. Once again, however, Ben says, there was no actual real number shared.
Speaker 1:I'd love to see them. Beyond that, I do wanna express gratitude for to Microsoft for introducing a new term new terms of art. Database fungibility.
Speaker 2:They're not getting pressed harder on that considering it's such a major element of their AI strategy, wouldn't the analysts kind
Speaker 1:of push? No. You can totally push back until the SCC says you gotta break out the revenues. You don't wanna share anything. This is the classic Google, YouTube, AWS, Amazon thing.
Speaker 1:Like, Amazon did not wanna break out AWS data. Because even though, like, you could hire someone from AWS and they could tell you, like, yeah, that thing was really profitable. That doesn't ring as true as everyday seeing the stock price and every quarter seeing AWS just print profit. And that gets Google and Microsoft off the couch. And they say, well, I know for a fact that that that AWS is massively profitable.
Speaker 1:We gotta build a competitor Yeah. Instead of just, oh, I've heard whispers that they're making lots of money. Yeah. Right? Very different.
Speaker 1:Because Bezos, that whole time was reinvesting all the profits, so it wasn't showing up. It was hiding.
Speaker 2:It's just tough because, I mean, on the on the Copilot side, they're selling into existing customers. Right? So it's an upsell Yep. Which is different than, okay, if you wanna go compete with them really on Copilot, in many ways, you have to own the underlying company wide Yep. People infrastructure to some degree.
Speaker 2:Right? Like, you need to own Teams so that you can upsell Totally. You know, the copilot for Teams integration.
Speaker 1:Yeah. So Sacca continues to get hammered with questions about OpenAI and the relationship there. And he says And
Speaker 2:they posted so so
Speaker 1:Yeah.
Speaker 2:Altman and Nadella Altman and Nadella posted a selfie together
Speaker 1:Yep.
Speaker 2:Trying to, you know, clear Hey.
Speaker 1:We're buddies.
Speaker 2:We're buddies. We're smiling. We're happy.
Speaker 1:It's not it doesn't count unless there's the the the the bar.
Speaker 2:Mogged Altman on TV. He said Yeah.
Speaker 1:The bar for, like, the the CEO to CEO selfie has gotten so high. It's like, I wanna see you doing jujitsu together. I wanna see a jersey swap. I wanna see that leather jacket on you. I wanna see I wanna see Siata in the passenger seat of the Regera in the Tony side.
Speaker 2:See shots of them Yeah.
Speaker 1:I wanna see Sam together. Hitting 200 miles an hour in that thing, and Satcha scared out of his mind. Yeah. Then I'll be like, okay. Yeah.
Speaker 1:These are boys. They're boys. They went to the track. They did a track day together, and Satcha trusted Sam to put up 5 g's in the corner.
Speaker 2:Satya let Sam ride his favorite thoroughbred.
Speaker 1:Exactly. Exactly. Yeah. It's not you can't just take a picture in a boardroom. It's just boring.
Speaker 1:It's boring. Step it up, guys. So Satya answering about OpenAI, he says, but to your overall point, I the thing I would say is that we are building a pretty fungible fleet. Right? Like, don't worry.
Speaker 1:We can move our fleet anywhere. We're making sure that all the right that there's the right balance between training and inference is geo distributed. We are working super hard on all the software up oppositions. Right? I mean, it's not just the software optimizations that come because of what DeepSeek has done, but all the work we have done too.
Speaker 1:For example, reduce the price of GPT models over the years in partnership with OpenAI, which is true. They've done a lot of optimization to serve GPT.
Speaker 2:Do we know exactly how much Microsoft owns of OpenAI? Because there was that 1 weird investment where they basically bought seemingly I I forget the exact structure, but they Yep. It was, like, 10 on twenty years.
Speaker 1:The way I think of it is, like, is, like, there's kind of 3 important parties around the table with the OpenAI for profit. It's, like, the, like, the founders, employees, like, the shareholders
Speaker 2:Yeah.
Speaker 1:The Microsoft, and then the nonprofit. And then the actual investors are, like, pretty small in that. But do you think about, like, those 4 things, and they're, like, roughly balanced? There isn't 1 person or 1 organization that has, like, outsized control. I think the whole meme of, like, it's it's entirely controlled by the nonprofit, or it's entirely controlled by Sam, or it's entirely controlled by Sasha by Sasha.
Speaker 1:Is maybe a little bit oversold, and it's a little bit more of a balance because Yeah. When the nonprofit conversion happened, there was, like, a big debate, and you get 4 people around the table. Oftentimes, if everyone has, like, roughly equal leverage to kind of veto, you kinda wind up with roughly equal positions. But I don't really know. Anyway, in fact, we did a lot more work in inference optimizations on it, and that's been key to driving.
Speaker 1:Right? 1 of the key things to note in AI is you don't just launch the frontier model, but if it's too expensive to serve, it's no good. Right? It won't generate any demand. So you've gotta have that optimization so that inference costs are coming down.
Speaker 2:Specific communication strategy where you keep saying right.
Speaker 1:Yeah. Yeah. Yeah.
Speaker 2:And it it makes you inclined to agree with him. Right?
Speaker 1:Yeah. Right. Yeah. %. I was watching some video of someone.
Speaker 1:Who was it? Someone on, it was Vivek Ramaswamy on Mad Money on Mad Money, with Jim Cramer. And he's breaking down this biotech deal. And every sentence, he starts with actually. He includes the word actually, like, 25 times in this interview.
Speaker 1:And so Kramer will be like, oh, like, why are you taking this, drug through, through phase 3 trials like it already failed phase 2? And he's like, well, actually, when we looked at the data, like, it actually outperformed. And so he's, like, really enforcing that this is, like, true. What he's saying is a fact. It's actually true.
Speaker 1:And he's just throwing that in, and I just picked up on it as, like, a rhetorical technique. Gotta watch out for these things, folks. It's important. We would never do something like this to you. We would never use rhetoric against you.
Speaker 1:Never. To get you to, buy 1 of our
Speaker 2:Just sign up for ramp.
Speaker 1:Just sign up for ramp.
Speaker 2:Actually.
Speaker 1:Actually. Which is actually, the greatest financial institution of all time.
Speaker 2:All time.
Speaker 1:Also, the fleet physics that we are managing. And also remember, you don't want to buy too much of anything at 1 time because Moore's law every year is going to give you 2 x. Your optimization is gonna give you 10 x. You wanna continuously upgrade the fleet, modernize the fleet, age of the fleet. And at the end of the day, you have the right ratio of monetization and demand driven monetization to what you think of as the right training expense.
Speaker 2:I like the use of fleet because it it does you can imagine that same language being used at Amazon where they're like, alright. Jeff, you have, you know, tens of thousands of these delivery vehicles. Like, the depreciation is insane. You're putting hundreds of thousands of miles on them, you know, every few years. Like, they're clearly depreciating massively.
Speaker 2:And so by positioning it as a fleet standpoint, it makes it slightly less painful that a lot of these GPUs will be worthless in three years. Yeah. Not worthless. People are
Speaker 1:like, yeah. I I I got a fleet of sports cars at home. I'm used to it. Yeah. Yeah.
Speaker 1:I've dealt with depreciation
Speaker 2:before. Buy the cars?
Speaker 1:I got an SF 90. You got an SF 90. Garage. Yeah. I'm down.
Speaker 1:I got a bunch of Ticons Yeah. In my fleet. I'm I'm sitting on losses. I've been
Speaker 2:waiting for The only thing that depreciates faster than GPUs is Ticons. Ticons.
Speaker 1:Some some people call them the GPUs of the car market.
Speaker 2:Yep.
Speaker 1:And so Ben summarizes this by saying, this is the exact opposite way in which Microsoft was talking about their data center investments in October 2023, where Nadella emphasized that Microsoft would have a durable cost advantage because they could build infrastructure for a specific model. So they were not talking about fleet fungibility at that point. They were talking about going all in on OpenAI.
Speaker 2:Ben doesn't forget.
Speaker 1:He's putting he's putting Satya in the truth zone. Zone. In the truth zone.
Speaker 2:And you know Satya's reading this being like, oh, I got it.
Speaker 1:He got me. Yeah. Yeah. I was trying to be a little sneaky. Like, a dead sneak caster techery.
Speaker 1:Yeah. Oh, no. Ultimately, though, that's not a criticism. Models seem to be well on their way to commoditization, and Microsoft has changed its tune appropriately. And so yeah.
Speaker 1:And they're hosting r 1 for free. And so, you know Wait.
Speaker 2:Microsoft's Microsoft is hosting r 1?
Speaker 1:Everyone's hosting r 1. No one is as much of a Djangoist as you. No one no one is that America First. Like, like, the whole the, like, the abstract concept of, like, it's bad to host the open source model, just like that didn't take hold at all as a meme.
Speaker 2:Yeah. Just I you know, imagine imagine Sam, you're you're posting the smiling picture with Satya. Meanwhile, he's
Speaker 1:But they host everything. They host Llama.
Speaker 2:They do
Speaker 1:a whole press release.
Speaker 2:I understand. I understand. Yeah. It's just
Speaker 1:that an Azure customer, you're like, I want all of them. Like, give me all the flexibility all the time on cost
Speaker 2:and stuff.
Speaker 1:Like
Speaker 2:They're hosting it on Azure.
Speaker 1:On Azure.
Speaker 2:I thought I thought it was an an integration in Teams or, like, Copilot products. Literally.
Speaker 1:It's like, if I go to Azure, I can get MySQL. I can get Postgres. I can get other databases.
Speaker 2:Like, yeah. Load it into Copilot. Let's go. Oh, no. Sorry, Sam.
Speaker 2:Sam's got the They might you know, the smiling face on. He's just
Speaker 1:crying and No. No. No. It's not that aggressive yet. But, and 1 more point of note, Hood, the CFO said, we talked a little bit about what were the main drivers, what which was 1 of the Azure commitments that OpenAI has made.
Speaker 1:And I do wanna say that, obviously, this is a big commitment. You'll continue to see OpenAI make commitment. So I wanna separate the concept that this is 1 time versus an ongoing relationship that will grow as they grow, which it absolutely will. That right of and Ben says that right of first refusal to OpenAI's AI build out figures to be a pretty handy tool for Microsoft. They can build capacity for their customers.
Speaker 1:And if they overbuild, well, guess they'll grab a bit more of OpenAI capacity to fill in the gaps. And so Satya, you know, getting a little a little An absolute dog. Words, but an absolute dog.
Speaker 2:He's he's nice with it.
Speaker 1:He's nice with it.
Speaker 2:He's nice with it.
Speaker 1:You know, he was the first hyperscaler big tech CEO to mention the metaverse before Zuck. He got to it before Zuck. He was like, yeah. We're really into this metaverse concept. Like, it's gonna be a big deal.
Speaker 1:We're gonna It's
Speaker 2:called teams.
Speaker 1:It's called teams. Yeah. It was like, you're gonna be if you're, like, an industrial company, you'll be able to create a, what do they call it, like, a clone of your industrial systems. So you'll be able to, like, walk around in virtual reality and see, okay. This machine is green.
Speaker 1:This machine's red. What let's diagnose it. And, called digital
Speaker 2:We're running out of Lucy.
Speaker 1:Digital twin. Yeah.
Speaker 2:The breaks.
Speaker 1:Fire up the Fire
Speaker 2:it up.
Speaker 1:Packaging machine, print more labels. Yeah. All all digital. And I think they have some products for it. I don't think the adoption's been great, but, it is just funny that he was early to the trend.
Speaker 1:He was reading Matt Ball. Yep. Another absolute dog. Okay. Let's move on.
Speaker 2:What is Matt Ball up to these days?
Speaker 1:Oh, he just put out a fantastic report on the state of video games, which we should dig into. Should dig into it. It's like a massive slide deck, and he just did an interview with none other than Ben Thompson, the absolute Absolute dog
Speaker 2:on dog action. It's a
Speaker 1:dog fight. It's a dog fight. When those 2 guys get in the ring.
Speaker 2:Yeah. Yeah.
Speaker 1:Yeah. Hot takes flying.
Speaker 2:Yep. It's
Speaker 1:great. Okay. Let's move on to Masa Yoshi sone.
Speaker 2:Hey, crack. I, I specifically ordered these, this morning. This is my favorite little Japanese soda. Fantastic. It's called the kimono
Speaker 1:Okay.
Speaker 2:Sparkling yuzu soda. It's made in Japan. It actually still has, all of the, it has some, westernized labeling in order to sell here, but they left the Japanese characters on the side too. So if you can read Japanese, you can dive in there. But these things are delightful.
Speaker 2:I thought it was a great way to kind of sort of kick off this overview of Masa Son's Masayoshi Son's, absolutely incredible career Yeah. And that we are blessed is still raging and
Speaker 1:roaring on earth. The ultimate size lord.
Speaker 2:The the gambling man. The gambling man. The gambling man. There's there's so there's, John had, covered Masa on on his YouTube channel in the past. But, in in diving into this, so we we looked at some of his research from that, and then I went back and, started listening to the audiobook, Gambling Man, which is an incredible overview of Masa's life and gets you really into, really into who this guy is.
Speaker 2:Everything, like, deep family history going back to his dad, his dad's family, his grandpa, their entire, trajectory going from Korea to Japan, back to Korea, back to Japan. Yeah. You know, going through a very tumultuous series of decades leading up to Masa being born.
Speaker 1:Well, let's start with some context of why he's in the news, and then we'll just kick it off with the proper intro. So Jeff Lewis has a great post here that we'll put up on the screen. He says, you only have to be really right once. Masa has been really right twice. Third time tends to be a charm.
Speaker 1:And so Jeff's going long, Masa. And, Hiro Onoda Capital says 25 at 03:40 post. This is the rumored OpenAI round, and it's a quote. He says, there are 1 business, guys. Bill Gates just started Microsoft, and Mark Zuckerberg just started Facebook.
Speaker 1:I am involved in, in a hundred businesses, and I control the entire tech ecosystem. Masa continued, these are not my peers. The right comparison for me is Napoleon or Genghis Khan or Emperor Qin, builder of the Great Wall Of China. I am not a CEO. I am building an empire, and that's the type of energy we love to see on the timeline.
Speaker 1:And so we got some photos of Masa, but let's kick it off with why you should care about this guy. He's back. He's in on, Stargate. He's ripping huge checks. He lost a ton of money.
Speaker 1:He was embarrassed by WeWork, but he made a ton back on on on ARM. He's rich. He's powerful, and he's firmly back in the game. And so why don't you kick it off with his humble beginnings in early life?
Speaker 2:Humble beginnings in early life. So he was born, on the 11th of August, in Tosu, which is the South Eastern part of Japan's Kyoshu Island. He is a third generation Korean.
Speaker 1:Zainichi Korean.
Speaker 2:Zainichi Korean, which which are ethnic Koreans that were at some point or another granted permanent residency or citizenship in Japan. So before going into that, he actually so going back to his his grandpa, I'll pull up some notes here. His, his grandpa and his, I guess, his great grandpa were a part of this sort of agricultural class in Korea. Yep. And so they were not seen as businessmen, but they were seen as people that sort of they were sort of aristocratic, aristocratic Jason.
Speaker 2:Their responsibility was sort of overseeing agriculture in Korea. And what's interesting about this is that his grandpa really internalized this, and so even though that aristocratic sort of, agricultural class was disbanded in Korea and they eventually moved to Japan, he always saw himself as above business, like, had a very negative view of business. He had a negative view of entrepreneurs, which is fascinating because Masa's dad, his grandpa's son, the grandpa's son, was very much an entrepreneur, and he went on to very much influence, Masa, in in, you know, in a big way.
Speaker 1:It's a real catalyst. Just do things to The
Speaker 2:real you can just do things guys. So rules, build whatever you can. So yeah. So going going back, Masa's dad was born in 1936.
Speaker 1:Mhmm.
Speaker 2:Their their, Masa, He
Speaker 1:was just 21 when he had Masa.
Speaker 2:Yeah. So has a kid very young. Masa's one of 7.
Speaker 1:A pronatalist going.
Speaker 2:So his his his yeah.
Speaker 1:Very, very
Speaker 2:much. And so, Mas' dad is living through, World War, you know, the sort of the end of World War two. Right? Sort of this Japanese reconstruction era. Yep.
Speaker 2:The Japanese were deeply embarrassed by World War two. Right? They went from this sort of dominant empire that stretched all over Asia to being forced back onto the 4 islands, and, they went through this reconstruction period. And so as the Japanese, were in a bad spot, they badly badly mistreated Koreans. Even during the war, the Koreans were, the men were forced to work in, like, coal mines and do these sort of tasks that that were basically slave labor, and the women were, like, concubines sort of sexual slaves.
Speaker 2:So very, very dark, history. And so this is this is what Masa's grandpa is, like, going through as as, like, an adult, basically. So he has a son. He has 7 kids, and Moss's dad even has, memories of American b 29 bombers
Speaker 1:Woah.
Speaker 2:Flying and bombing this, nearby cities that they were in. And Moss's dad has this memory of walking up and touching the glass of a b 29 bomber that crashed. Woah. But Mas's dad at the time, as a kid, he decided that America was awesome.
Speaker 1:Oh my god.
Speaker 2:He he says like, there's a quote. He says, they, he's like, at that point from that point on, I I thought America rocked.
Speaker 1:That was, like, the summary
Speaker 2:that, you know, not not word for word. That's hilarious. And so, after after the war, Koreans are being treated terribly. There was there was a lot of pushback. Many of them were asked to leave.
Speaker 2:Yep. If you didn't leave, you're forced into these sort of shanty, you know, ghettos.
Speaker 1:Japan's always been kind of a, like, light ethno state. Like, they've never been big on immigration. Yeah.
Speaker 2:They're kinda changing their tune now. But live there, but you
Speaker 1:you Yeah. It's hard to get citizenship there. The the population is collapsing, so things might
Speaker 2:change.
Speaker 1:But it's been rough. Even even being Korean, not even being, like, an American, like, who would really stick out.
Speaker 2:Yeah. And so,
Speaker 1:They lived in this illegally built shack on the railroad. You saw how this was in
Speaker 2:the wild. And so at 1, they go so Mas's dad, goes back to Korea to realize it's even worse there. There's, like, there's no economy. Yep. Then they decide they're gonna come back Yeah.
Speaker 2:To Japan. They get on a boat. They're it's like a it's a multi day crossing, typically. It's like a couple days. They the boat sinks
Speaker 1:Yeah.
Speaker 2:And they spend two days at sea just, like, drifting around and eventually get picked up, taken back to Korea, and then they finally make it back to Japan.
Speaker 1:Wow.
Speaker 2:And so, jumping forward a little bit, Japan at this point is still, like, a completely shattered economy. Right? They're rebuilding. They've lost so much, ground. Masa's dad, leaves school at 14 and is selling alcohol to basically support his family.
Speaker 2:Right? He's 1 of 7. He's trying to some food on the table.
Speaker 1:He's an illegal soccer business.
Speaker 2:So Masa yeah. Masa base Masa's dad starts a moonshine business. And at this point, his dad is a drunk, is beating him, like, frequently, very dark. Yep. And has, at 1, badly beats him because he was bragging Mas' dad was bragging to his friends about his business success.
Speaker 2:Right? He's like, I'm making moonshine. I'm making some bucks. His dad overhears it, ends up beating him for it. So Masa's born, ten years after the family gets back to Japan.
Speaker 2:Mhmm. They're completely at the bottom of society. So it's it's very much like Masa, by the time he's a teenager, his dad is kind of on top not not on top of the world, but they have a very flashy lifestyle. Yeah. But he's born while his dad is living with their family in the slums, and, they are pig farmers.
Speaker 2:Yeah. And they chose pigs for a few specific reasons that I thought were interesting. So they, 1, his dad had free labor because they have a big family and everybody's participating. They have free land because they're just living in this sort of, like, railroad ghetto, and the pigs just kind of roam around chilling. Yeah.
Speaker 2:The Masa's, grandma, who's a big part of raising him because his mom was very absent, takes, Masa around in a wheelbarrow picking up scraps of food to feed the pigs. So this is just like it's it's hard to even illustrate how rough of a situation they're in. But anyways, they pick he his dad picks pigs because they reproduce super quickly. Yeah. The pigs are just
Speaker 1:It's like very hustle mindset, but very limited opportunities and, like, low low class.
Speaker 2:Yeah. And so eventually through this sort of raising pigs, selling them off to be, you know, butchered for food, Masa's dad starts saving up some money. At 1, he has the equivalent of a hundred thousand USD, which was a lot of money back then. And, Masa, this this really gets into kind of understanding who he is. His dad starts to get into this thing called pachinko, which is this new form of gambling, which is effectively via slot machines.
Speaker 2:But it still is very much around, in Japan. So his dad just starts getting getting into the game a little bit. He's gone from pig farming to gambling.
Speaker 1:Yep.
Speaker 2:An an absolute dog.
Speaker 1:But he's on the casino side.
Speaker 2:He's on the house.
Speaker 1:Gambling to put money away. This
Speaker 2:is important. But he still has to take some pretty big gambles. So, anyways, these are picture like casinos and is not that dissimilar to what Vegas looks like today where it's just rows and rows of these machines and people just sit there. And, over time, he's sort of levering up. He's launching different, you know, parlors here and there.
Speaker 2:At 1, he takes a huge bet and spends $4,000,000 on a new, on a new club, they called it.
Speaker 1:You know.
Speaker 2:And it's called Lions. And so this was, like, the vast majority of the capital that he had available, so huge bet. And for the bet to pay off, he needed to get 5 to 10000 people per day game gaming in this in this facility, which is an order of magnitude more than his, like, best performing club. So it's it's literally the most, like, gigachad long move that a lot of people are like, you are absolutely crazy. And his dad is on record saying, I don't care if I go bust.
Speaker 2:And he even had contingency plans. He's like, if I go he's like, if I go bankrupt, like, we'll hit we'll go on the run. He's like, I'll run it all back.
Speaker 1:Wow.
Speaker 2:And so this is this is the environment that Maz is growing up in as, like, sub 10 years old
Speaker 1:Yep.
Speaker 2:Which is just crazy, crazy environment.
Speaker 1:Yeah.
Speaker 2:And so he launches this club. Yep. First two weeks absolutely flops. And he's, like, obviously freaking out, but wants to, you know, wants to really make a play. So he takes, like, a $350,000 loss in the first month.
Speaker 2:He's like, I gotta turn this around. He decides to he works with his engineers to make it so that the machines, like, pay out a lot more Yeah. And people start winning a lot, and he starts attracting this flood of people. And so the next month, he changes it, and he makes 350 k of profit.
Speaker 1:There you go.
Speaker 2:And then he the next month, you know, they're they're kinda messing with the machines. He loses it back again. So he's no the the the the sons are just, like, not afraid to, like, make it all, lose it all, make it all, lose it all. And, and eventually, he sort of slowly dials it dials it in. And so by the time Masa's, I believe it's 14, the family's now living this sort of dual lifestyle where some they have 20, members of the family that are that are working on the family business, but then there's also this sort of older generation.
Speaker 2:And so it's this weird dichotomy where the people that are working in the business are, like, driving, like, flashy cars and, like, really, like, living it up. Right? They have all these sort of casinos, and then the grandparents are, like, kind of still, around, but, like, very much still living in the past in some way. And so we can get more into Masa's, you know, life and career, but I think that's very important context because this sort of gamblers mindset
Speaker 1:Yep.
Speaker 2:And and entrepreneur like, high high risk entrepreneurship is 100% in his d DNA. It's all he knows.
Speaker 1:Yeah.
Speaker 2:So when people are were like, oh, how could Masa put $10,000,000,000 into, you know, WeWork and lose it all? It's like, well, he's lost more money than any other man in history. In the entire history of the world Yeah. In our in our sort of modern economy, he lost 4,000,000,000
Speaker 1:during the dot com crash. Yeah. The highest number ever.
Speaker 2:He was also the so he went from being the richest man in the world to to losing, like, 90. In history.
Speaker 1:Yeah. Crazy.
Speaker 2:So Yeah. And so I think
Speaker 1:through through the through the gambling business and through kind of their family growing, he meets this guy, Den Fujita, who is an entrepreneur who brought, McDonald's to Japan. And this guy is a psycho. He he has this quote. He says, if if the Japanese eat McDonald's for a thousand years, they'll grow taller, have white skin, and blonde hair. Like, it's like they'll basically turn into Donald Trump.
Speaker 1:I think it's so funny that the dude's just like, oh, yeah. Like, this is, like, Trump code this is Trump maxing, basically.
Speaker 2:Trump maxing.
Speaker 1:And so, Fujita acts as, like, a mentor to Masa and tells him, go study English, learn about the computer industry, and you gotta go to America. And so Masa has this outsider complex. He's like, you know, yes. I'm, like, the lowest rung of society. Yeah.
Speaker 1:My family's from this, like, destitute, you know, shack. And we're still looked down on as kinda like gamblers and, like, you know, lower class. But Yeah. But I'm keeping the name. I'm not changing my name, and I'm gonna prove that I can do it.
Speaker 2:No. And the cool thing so Masa's dad had a you know, I don't know the exact dynamic, but very rough relationship with an abusive father who's an alcoholic. Masa's dad is awesome, though. And, like, from a young age is training Masa and saying, you are the best. You are number 1.
Speaker 2:Anything you want, you can achieve. Like, it's it's honestly, like, I went from being I I was, you know, listening to this being, like, very emotional because it was so dark, and then it flips. And Masa's dad is is you can just do things. Yeah. Anything you can see in your mind, you can achieve.
Speaker 2:Yeah. And Masa really carries that into the rest of his career.
Speaker 1:Oh, yeah. Totally. So he goes to California at age 16, joins this college before entering high school, and he and he advances from sophomore to junior to senior in two weeks by just testing out of everything. And he spent two full years at the college, then transferred to UC Berkeley to study economics while also taking some computer sciences some computer science classes. And he has this idea where he needs to generate business ideas, and so he generates 1 new business idea every single day.
Speaker 2:He would've loved My First Million.
Speaker 1:Oh, yeah. My First Million or just, like, like, you know, your your path of just, like, building a deck, spinning up an idea, tweeting something out, and then being like, actually, this
Speaker 2:is a business. Sucks.
Speaker 1:Yeah. The idea sucks. Or but he was just throwing stuff at the wall. I remember in my first start up, we were, like, destitute, and we had a a wall of sticky notes. It's just like all the different business ideas.
Speaker 1:And some days, we would just pull 1 out and be like, can we build an MVP for this? And, like, eventually, it started working, which is great. Yeah. So he sells a patent, for a translation device to Sharp Electronics. So it seems like he does have some sort of technical background even though later on, he becomes deeply vibe based investor.
Speaker 2:He's just not an engineer, and he never identified as an engineer. He he he he is the jap Yeah. In the grand scheme, he's the the Japanese Warren Buffett. Yeah. So you should look at him as, like, a deal maker.
Speaker 1:Yep.
Speaker 2:Somebody that's seeing opportunities, putting people capital and ideas together Yeah. And doing it on a on a global scale.
Speaker 1:And so Sharp pays him $170,000,0.0 for that patent, which is crazy considering how young he is at the time. It's a huge windfall back for this was, before 1980. So this is in the He gets $2,000,000, basically. And so he immediately invested all in importing Space Invaders arcade machines, modifying the software and installing them on campus. And that makes him another million dollars.
Speaker 1:And then he founds a game software company, and he sells that for $2,000,000. So he has a bunch of, like, back to back hits really, really quickly.
Speaker 2:Yep.
Speaker 1:And and so then he returns to Japan, in the and he starts doing extensive research. So he's just kinda monk mode. He's made his money in America enough to, like, you know, buy some time. And he's just spending eighteen months doing extensive research. All of his relatives are like, this guy's doing nothing.
Speaker 1:But secretly, he was building a massive knowledge base.
Speaker 2:Yep.
Speaker 1:So he developed 20 metrics to measure potential business ideas, and the highest scoring idea for him was personal software distribution. And this goes into his deal making philosophy. He's not building the software. That's complicated. That's risky.
Speaker 1:He's just taking software that automatic that already works
Speaker 2:Yep.
Speaker 1:And just buying it for cheap and selling it to someone else.
Speaker 2:Distribution businesses have existed for years. Yeah. They're great businesses. You usually don't have to take on you don't have to take on too much inventory risk Totally. Until you get this sort of, toll booth style.
Speaker 1:Yeah. Not r and d heavy. Very bootstrappable. I know some people that own, food and bev distribution companies. That's true.
Speaker 1:They just print money, and they don't and they never raised any money. It's like this amazing family owned business. Yeah. And so, this, and and this also, like, just it's super aligned with his skill set at this point. Like, he understands what good software is, obviously, because he's built a game company, ran the Space Invaders thing.
Speaker 1:But if you think about, you know, you get a call from somebody who's, like, in their early twenties, they've already sold, like, 3 companies. Like Yeah. They're they have money. They're really, like, this crazy hustler with this interesting backstory. Like, you're gonna take that meeting even though they're young.
Speaker 1:Yeah. And so that's the ultimate alpha is just he's, like, such a hustler, has enough of a track record to get the meeting. And then it's like, oh, yeah. You're providing me a service. Like, I I need software to distribute through my stores anyway.
Speaker 1:So why not why don't I go with you?
Speaker 2:Yeah. And that's why when you know, because today, the younger generation of entrepreneurs really know Masa for going giga long Turbo long. On WeWork. Yep. And and but it
Speaker 1:But that's not the story.
Speaker 2:So fifty years earlier, he had his 20 metrics to measure business ideas. And so he takes massive risk. And oftentimes, there is a sort of vibes based analysis, which which which some of his his employees talk about. Right? But in general, he's 1 of the most well studied, well researched, most experienced dealmakers in history.
Speaker 1:Totally. Totally. And so
Speaker 2:And there's not like he does get some really lucky breaks.
Speaker 1:Yeah.
Speaker 2:But it's not necessarily luck. Right? Because he's taking so many crazy shots on goal.
Speaker 1:Yeah. And so he chooses the name SoftBank. Think about it as, like, a bank of software. It's not it's not actually a financial institution Yeah. But it kind of turns into 1 or a a huge fund at a certain point.
Speaker 1:And so he he hires 2 part time people in a small office. He's not afraid to hustle. And then famously, he would get an apple box because he's short and stand on them and and declare, in five years, we'll have $75,000,000 in sales, supplying a thousand outlets. And we'll be number 1 in PC software distribution. And the 2 employees were like, this guy's crazy.
Speaker 1:We quit immediately. Imagine giving a speech to your only 2 employees. Imagine we're like, Ben,
Speaker 2:this is going
Speaker 1:to be the most profitable podcast. We are going to crush it. We're going to be number 1 this year. And Ben just is like, I'm good. I'm good.
Speaker 2:I'm out.
Speaker 1:I'm out on
Speaker 2:that note. I'm out.
Speaker 1:Yeah. I mean, if he saw a stand on apple box, maybe that would be the trigger for that, but hilarious. And so, but he doesn't mind. He he grinds through it. And so he he books a giant booth the size of Tony Sony Toshibas at a Tokyo trade show.
Speaker 1:Even though he's, like, this small company, he's just sending it.
Speaker 2:So smart.
Speaker 1:It's so smart.
Speaker 2:So smart. He's
Speaker 1:standing out. This is this is the friend.com, Alvy thing. Like Yeah. He's he's doing the thing where everyone's like, no one would take that amount of risk, and then it got gets him a bunch of attention. And so he invited vendors to exhibit for free.
Speaker 1:And so he's like, I got this booth. I'll let you do it for free. I'm gonna advertise you for free. And he's just creating pulling forward value, basically. And so it feels like a flop.
Speaker 1:There's no immediate leads. But weeks later, Joshin Denki from Osaka contacted him. And, originally, this is hilarious because he made millions of dollars at this point. Yeah. And and they're like, hey.
Speaker 1:Why we're we're we're the software firm. Why don't you come and pitch us, and we'll see if we can do a deal? And he's like, I don't have enough money to afford a train ticket. Like, I I literally can't go.
Speaker 2:Yeah. So we I I would love to know how he's he probably did the most degenerate thing with all that cash. Of course. Probably going long, like Of course. Russian corn futures.
Speaker 2:Yeah. Just, like, uses it all.
Speaker 1:Yeah. I mean, he's investing it. I I I think he literally spent a ton of it on that trade show booth and just spending it on, like, you know, all these all these crazy long shots.
Speaker 2:Oh, yeah. You imagine in an era when when Tokyo's biggest software software trade show to actually get a booth the size of Sony's Sony or Toshiba? Might have had to spend
Speaker 1:A million bucks or something or yeah. A ton. And so, the the president of Joshin Denki, calls him and says, we need a dedicated software supplier. We want you to be the 1 to do it. And he says
Speaker 2:This is such an interesting time. Right? Because this is at a time where companies were r and d product companies, but they wouldn't do their own distribution. So to sell, they would just find a Yeah. Distributor that would be these primary sales channel for them.
Speaker 1:I mean, this was up until the Internet. Like, all the not this we're we're in 1981 or something. And, all the way up to 2000, you would have to go to, what was it, CompUSA or Best Buy or Fry's Electronics. And I remember buying video games on discs in Totally. Like, boxes, and you'd take that home.
Speaker 2:Why GameStop was a great business. Yeah. It's because the manufacturers Yeah. Or the the game makers didn't actually have
Speaker 1:And if you just think about it, like, there's, I mean, there's obviously some sort of power law where Best Buy is probably the biggest 1. GameStop's big, like you mentioned. But there are hundreds or thousands of individual small software box retail stores. Yep. And then there's also thousands of game companies and software companies and somebody making spreadsheets.
Speaker 1:You forget that before Microsoft can like, condensed all of Office, like, PowerPoint was its own company. I'm pretty sure Excel was its own company, and they, like, put all these together. A. Yeah. Almost all of that was through m and a.
Speaker 1:And and so at a certain point, if you're the guys who are, like, we're making presentation software, we're gonna call it PowerPoint or whatever. You're like, okay. We have some cracked engineers. We built it. It works.
Speaker 1:It's good. But, like, now we gotta sell it into different retail stores. Like Yeah. We have to have have a massive sales force. It makes per for perfect sense to disaggregate that and work with a distributor.
Speaker 1:And so that's what they do. And but, Masa gets this phone call, and they're saying, we need a dedicated software supplier for Josh and Denki. And Masa says, I have no product, no money, and little experience, but I have the greatest desire to succeed, and I will pour my entire spirit into PCs. Let's go. Let's go.
Speaker 1:Full size.
Speaker 2:So so 1 thing you'll know about Masa that that's important to know is from a very young age, he intensely practiced manifestation and visualization. So he would have loved LA in the 02/ because this guy, I'm sure he's a big feng shui, you know Totally. You know, enthusiast as well. But he he would in his view from from early in his career, if he could visualize it, he could make it real.
Speaker 1:Yep.
Speaker 2:And so that has kind of bit him in in, a little bit throughout, you know, the last few years where he'll just announce a a huge deal before it's done. Yep. And in his mind, he's like, I can see it in my mind. It's done. We're gonna do it.
Speaker 2:Right? And that bit him a little bit with WeWork because I'm sure when he was investing at WeWork at a $44,000,000,000 valuation, He just imagined a world where we work had office buildings, hotels, apartments, you know, all these, you know, campuses. Right? And so he's like, of course, this he was not analyzing it based on their Yeah. EBITDA at that time.
Speaker 2:It was entirely based on what he visualized. Yep. And he believed in Adam Neumann. In many ways, Adam Neumann was an amazing CEO from a storytelling, narrative, brand building standpoint. Yeah.
Speaker 2:Yeah. And so in his mind, WeWork was already a hundred billion dollar company, so it seemed like he's buying it for cheap. Right? He's like, you're the idiots. Right?
Speaker 2:Yeah. I mean because he could see it in his mind.
Speaker 1:Even even WeWork, like, it's not like WeWork people, people like to put WeWork in the same bucket as, like, Theranos, but it's just not true at all. Like Yeah. This is a benchmark company. Like Yeah. This was, like they were very much, like, a serious contender in Silicon Valley, whereas Theranos
Speaker 2:is a weird zombie. The thing the other thing with WeWork is the fundamental consumer product was amazing. Yeah. Do you remember walking into early WeWorks? I I remember being, you know you know, in college, probably going to my first WeWork, and I'm like, the coffee's free and good.
Speaker 2:Yeah. Like, that's amazing. Great. It was, like, a fun vibe. Everyone was friendly.
Speaker 2:Maybe it's not the highest productivity space in the world, but It
Speaker 1:was on it was on a megatrend of, like, more remote work, more distributed teams, more small teams, more startups.
Speaker 2:It felt like the the pricing Work agents Part of why the product was so good is because they were not selling it for what it costs to deliver. Totally. But it still was like, okay. At $400 a month, it'd be stupid not to get this because I'm getting so much value.
Speaker 1:Totally. Totally. And so Masa, the deal maker, comes out in full force with the Joshi Denki deal. He says, first off, you gotta break off other vendor relationships. You gotta go exclusive if you wanna be with me, but I will work extra hard for you.
Speaker 1:And then he also really pitches them on this idea that the software is key to them winning in hardware. So the idea is, like, if if Josh and Denki wants to sell a lot of hardware, they're gonna need the best software in their stores, and people will come for the software, and then they'll buy a new computer. And that and that and that virtuous cycle will drive value for Josh and Denki. He's not he's not wrong there. Like, that is a good pitch.
Speaker 1:And so he secures the deal, and he also importantly gets Josh and Denki to pay for product inventory covering Masa's shortfall. So all of a sudden, he doesn't have a working capital problem. And so even though he's very small and doesn't have a lot of, a lot of funding raised or anything, he can basically boost up.
Speaker 2:Joshin deserves, hopefully, Masa went back after all of this and was just like
Speaker 1:Got some warrants.
Speaker 2:Here's a boat.
Speaker 1:Here's a boat or something.
Speaker 2:You know, something to pay him back because it seems like Joshin just So made it a really risky bet.
Speaker 1:I mean, look at this growth.
Speaker 2:He's a 4 he was always a force. Force.
Speaker 1:Always a force. And so Masa takes, Masa takes SoftBank from $10,000 in monthly revenue to 230,000,0.0 in monthly revenue. And remember, there's no inventory cost here. So it's all, like, it's all, like, respectively software margins. Like, he doesn't have the work the working capital, like, the debt issues.
Speaker 1:There's no print comes up. He's printing. And so the IPOs in 1994 at a valuation of $3,000,000,000. And by the was SoftBank was Japan's largest distributor of PC software.
Speaker 2:He manifested this.
Speaker 1:And he was extremely wealthy, but far from done. Should we move on to the .com boom and bust? This is
Speaker 2:this is like we're just getting started.
Speaker 1:We're just getting started. Buckle in, folks. We got another hour at least on this, baby. So he moves to Silicon Valley in 1995. He sets up offices in Mountain View, seeing the Internet's enormous potential.
Speaker 1:And 1995, this is still early on the .com boom. It's not like he YOLO ed in at the top in 02/. Like, he did he did that also.
Speaker 2:He also did that.
Speaker 1:But he also got in early, and that was very, that was very valuable. And so the .com boom was in full swing. Companies were rushing to harness the web's explosive growth, but this was still pre IPO craze. Oh, raise, you know, go public with just a slide deck and a domain name. And so in 1996, he meets the Yahoo cofounders, Jerry Yang and David Filo.
Speaker 1:He offers them a hundred million dollars for 30% of Yahoo. It's a big stake. Typical VC funds at the time rarely wrote hundred million dollar checks because that could alone be 40% of the fund.
Speaker 2:Yeah. This is so normalized now, but Yeah. Yeah. The biggest funds back in the day were, like, a classic dollar piece of fun today.
Speaker 1:Yeah. Yeah. Yeah. Exactly. Yeah.
Speaker 1:And it just yeah. Just it it like, you would just raise from VCs for a seed round or series a, series b, and then IPO. Yeah. Google IPOed very early. Obviously, it was a different thing because they were cash flow positive.
Speaker 1:But, even even the money losers would IPO and use the capital markets, in the public capital markets to raise money. Exactly.
Speaker 2:Nowadays, when companies IPO, they're oftentimes Yeah. It's not even about the money. It's about the liquidity Yeah. To the shareholders.
Speaker 1:It's like, well, I raised a couple million dollars just from angels, then there were a bunch of there were a bunch of huge venture capital firms that could write a $20,000,000 series a check. No problem. Then there were growth funds. Then there were crossover hedge funds. Then I started just going to the direct LPs and being like, can I raise a couple billion from a sovereign wealth fund just directly in the private market, all before IPO?
Speaker 1:And that's why you see companies IPOing at 60 or a hundred billion.
Speaker 2:So listen to this quote. Masa gave the after he made this offer, he gave the Yahoo founders an ultimatum. He says, if you don't take my money, I'll invest in Excite or Lycos, which were competitors, and kill you. The funniest thing about make a death threats.
Speaker 1:The funniest thing about this quote is that he didn't even know who their competitors were. In the meeting, he asks, who do you think your biggest competitors are? And they say, probably Excite or Lycos. He's like, okay. Well, then if you don't take the money, I'm investing in them.
Speaker 1:Thanks for doing my DD for me. Ultimate deal maker. Didn't do any research. Still wins the deal.
Speaker 2:And so it's just it's just interesting because he breaks all the all the trends of he's exactly the opposite of of Warren Buffett. Totally. Totally. Right? Warren Buffett is is heavily researched, sort of slow, moving, builds these positions, you know, over time, make takes a position then starts marketing it, things like that.
Speaker 2:He's the opposite where where he's coming in, and he's clearly brilliant and gifted and a and a brilliant entrepreneur. But from an investment standpoint, he breaks all the rules. Right? He's not even doing market research before offering to do a hundred million dollar investment.
Speaker 1:Crazy. Take the huge competitors.
Speaker 2:Yeah. And
Speaker 1:just be like, yeah. Like you guys, but also I will kill you if you don't let me invest. And so, Yahoo accepts the hundred million dollar offer. They IPO in 1996, like, very shortly after this deal goes through and the share price soared on day 1. Masa made a hundred and $50,000,000 immediately.
Speaker 2:And Which again, at this point in time, doesn't really make a dent in his net worth. Right? Like, he he had taken SoftBank public Yep. At a $3,000,000,000 market cap. Sure.
Speaker 2:A hundred and 50 extra bones is not
Speaker 1:But a bad thing. Yahoo continued to rip post IPO No. No. No. I know.
Speaker 1:Way.
Speaker 2:And I I I'm just saying Yeah. Earl, I think you'll realize through looking at Moss'', the reason that later in his life, he starts to make these crazy side size lord, GigaChad Oh, yeah. Mega long bets is because he's had instances, like, later when he invests in Alibaba and prints tens and tens of billions of dollars Yep. You know that he wished he just massively sized up that position. Totally.
Speaker 1:Totally.
Speaker 2:And so that that leads
Speaker 1:to sort
Speaker 2:of 10, you know, 3 plus concentration. Yeah. Right now
Speaker 1:There's too many VCs who are like, yeah. I'm in this amazing company. I got a quarter percent. You know? Because I got I got diluted down logo
Speaker 2:at that point.
Speaker 1:And I and I got crammed down on this 1 round. I couldn't get to the ownership percentage. And and the founders only wanted to do a 10% round, and I only took 2% of it, all this stuff. But, I mean, Yahoo like, the wealth creation at Yahoo was is really underrated in the Silicon Valley story. Like, when I got to Silicon Valley, you'd meet a lot of Gen Xers, and a lot of them were like, oh, yeah.
Speaker 1:It was early at Yahoo. And then you're like, okay. This person's, like, cool and, like, kinda smart, but not, like, generational talent. You go to their house, like, $40,000,000 mansion in, like, Meadow Park because there was just so much wealth created from that IPO and a lot of liquidity.
Speaker 2:Yeah. And
Speaker 1:so it it was a huge, huge thing that led to, you know, a a rarefied air around anyone associated with Yahoo and then also just a kind of a Yahoo mafia that spawned and and built a bunch of companies. And it was kind of like the Facebook of the day, but it didn't didn't have staying power whatsoever. Yeah. And so it eventually unwound. But, so once he gets liquidity from that, he's he's hooked on deal making.
Speaker 1:And so from 1996 to 02/, he invests in 250 Internet startups.
Speaker 2:Generation run.
Speaker 1:Deal a week. Yeah. And he emphasizes And you know there
Speaker 2:were some weeks, you know, some weeks he probably did 5. Oh, yeah. And other weeks, he was back in his Tokyo pad.
Speaker 1:He's making calls. Okay. Yeah. What is it? Oh, who are your competitors?
Speaker 1:Okay. I'll invest in them. Okay.
Speaker 2:Yeah. 1 thing that's interesting, a lot of his career, you know, he he had his time in the valley, but a lot of his career, he spent working and living in in in Tokyo Yep. And just sporadically traveling to places like Davos, you know, or or California, things like that.
Speaker 1:And so he's basically just making a, he's not trying to pick winners. He's just trying to ride the Internet wave. So he's not not doing a lot of due diligence, enormous volume. And it's a good bet.
Speaker 2:He created the he created the Tiger goal a
Speaker 1:little bit later. Was the same thing. Tiger just timed it terribly. But, Marso
Speaker 2:Tiger actually did way more due diligence because they would hire, like, Bain Yeah. Consulting.
Speaker 1:It was still I mean pretty quick.
Speaker 2:Still, like, they were doing market research.
Speaker 1:Totally. Totally.
Speaker 2:Moss is just vibes Ripping. Ripping checks.
Speaker 1:And, I mean, we should do the Tiger story at some point, but they were very active in in Asia around this time shortly after this.
Speaker 2:And so
Speaker 1:Made a lot made a ton of money there.
Speaker 2:Mas is not just scaling the investments. He's scaling the firm. So he launches basically teams in South Korea, Japan, Hong Kong, Australia, India, Mexico, Brazil, over the world. So all all, you know, over the last, you know, decade, you've had VCs being like, oh, yeah. We're doing a lot in LatAm.
Speaker 2:Yep. We're doing, you know, we're doing stuff in India. We've got bets in Pakistan. And and, meanwhile, Moss has already been in all those places just spamming
Speaker 1:checks. Checks. It's great.
Speaker 2:Like you on the, you know,
Speaker 1:with the The dashing. Yeah.
Speaker 2:You know?
Speaker 1:Spam them. And so he makes $15,000,000,000 in just a few years, and he starts to double down once he meets Jack Ma of Alibaba. And so Alibaba's scaling. They need additional capital. Goldman Sachs, who is old, Alibaba's previous investor, was reluctant to keep funding it, didn't really see the massive potential there and was looking at more on a spreadsheet basis.
Speaker 1:And so Masa meets Chinese First mistake.
Speaker 2:Yeah. Ignore spreadsheets.
Speaker 1:For sure. And so he meets Chinese tech entrepreneurs, and he sees a glint in Mas' eyes.
Speaker 2:And one one thing about Masa is, like, you need to understand this run as he is a degenerate gambler because, like, he grew up in casinos. Yeah. Like, you know, these pachinko Yeah. Clubs.
Speaker 1:And he had so many wins.
Speaker 2:And his dad was fully comfortable with making, you know, going up a month and losing it all the next month. Just keeping it rolling.
Speaker 1:Yeah. Beta. Beta. Yeah. Beta.
Speaker 1:And so, they shake on a deal, 20,000,000 on a $100,000,000 valuation, but he winds up getting 34% of Alibaba, through as the deal progresses. And so, critical advantage here is that Masa sat on Cisco's board and saw router sales to China exploding, indicating massive Internet expansion. Yeah. So we got some insider intel, understood the market was growing, and went in, found a targeted bet, and ripped a check. What's probably missing from this story is that he probably wrote a hundred other $20,000,000 checks, and and none of them went went anywhere.
Speaker 1:But it doesn't matter because he got he got the elephant. He bagged the elephant. And so the .com crash was rough for him.
Speaker 2:Let's talk about the Alibaba investment Sure. Real quickly. So he turned $20,000,000 into a $72,000,000,000 position, which I think is I think is actually the greatest
Speaker 1:I think it might be.
Speaker 2:Yeah. Greatest venture bet of all time.
Speaker 1:Yep. It's hard to measure because I think, it sold off a ton during the dot com crash, but at the current valuation. And I and I think he still owns a a huge chunk of Alibaba. Right? Because that was 1 of the 1 of the positions that they were thinking about unwinding, to do the Stargate deal.
Speaker 2:Yeah.
Speaker 1:So interest rates rise in, 02/. The stock market plummets and many dot coms with shaky business models went bankrupt. SoftBank's market cap plunged 99%.
Speaker 2:Yeah. So so to be clear, so this was in March 0 Yeah. Of 02/. In Jan. 0, there he was giving a talk in Tokyo at this, like, very kind of cool underground, sort of, disco type club Yep.
Speaker 2:To all these and and the Japanese culture at the time was very much salary men. You know, you worked a good income, and it was sort of seen as boring. And so Masa got all these guys in a room, and and it's been described as being almost like a get rich quick scheme because he was pointing around the room being like, you're gonna be worth $50,000,000. You're gonna be worth a hundred million dollars. You're gonna be worth a hundred million dollars.
Speaker 2:And just, like, going around the room like that, and it really seemed like that. And he genuinely believed it.
Speaker 1:Totally.
Speaker 2:And, I'm sure many of those people went on to start, you know, important companies, but, he was he I do believe that at every market top Yep. He still believes, which is why he gets smoked. Right? He's not the guy he doesn't really
Speaker 1:No. He never sells early.
Speaker 2:He never sells early.
Speaker 1:Yep. Which is which is a drawback for a lot of big investors who have the ability to find fantastic entrepreneurs, see trends, but then they get pessimistic at the last second and say, ah, this must be capping out. I've made so much money. I mean, the whole benchmark Uber story, people are like, you know, maybe that was like they were like looking at, well, you know, we're each gonna take home a billion dollars individually. Like, This is retirement money.
Speaker 1:Maybe we gotta get out. Something like that. And there's a little bit of internal, you know, devil on the shoulder telling you, hey. This is this is too good to pass up. But even though he's losing so much money, he personally lost $70,000,000,000, which is a record at the time.
Speaker 1:Alibaba is surviving.
Speaker 2:Did we hit the size?
Speaker 1:Moment of silence.
Speaker 2:Moment of silence, but it's almost like losing 70,000,000 $70,000,000,000 means you made that much Yeah. Which should be
Speaker 1:self Gone. I've forgotten. Let's hit the size of Gong just a little bit. Boom. There we go.
Speaker 2:For the run up and the run down.
Speaker 1:And so, he he makes it through with the Alibaba stake, and then he starts launching more companies, Yahoo Broadband, Japan Telecom, Vodafone
Speaker 2:Japan, rebranded as SoftBank Mobile.
Speaker 1:And this was smart because he rebranded as SoftBank Mobile.
Speaker 2:And this was smart because he found the area of tech that had durable revenues. Right? People would pay for Yep. An Internet connection. They would pay for cell service, you know, things
Speaker 1:like And, disaggregated from the application layer.
Speaker 2:Yeah.
Speaker 1:So it doesn't matter if Yahoo wins or Google wins or Excite wins. If you own the broadband Yeah. Broadband demand's gonna increase
Speaker 2:the level. Still has a huge position in T Mobile. So there's certain positions as you just merge. You know, kept kept riding. But so the the chaos of the post 02/, you know, the the the actual, like, .com crash was because there were all these businesses that Masa was hugely invested in that were, like, dogs.com.
Speaker 2:It would be, like, basically, a service where you could buy dogs online. And it turned out that people were still just buying dogs from, like, you know Exactly. Regular kennels and stuff like that.
Speaker 1:So you can think about the as kind of, like, back to the basics, rebuilding with, like, the less frothy companies, riding the Alibaba stock, rebuilding, SoftBank backup. And then in 2010, he releases this thirty year vision presentation, and this thing is a bombshell. In it's a 33 slide deck with outsized predictions like advancements in artificial intelligence will surpass the human brain. Life expectancy in Japan will reach 2 hundred years, and a new era of hyper connected communication will be upon us. And so he his central philosophy is inform the information revolution will bring happiness for everyone.
Speaker 2:So I love that even today, he does
Speaker 1:Similar things.
Speaker 2:Well, he his his he's a master marketer Yeah. And salesman. Right? He's a deal maker, so he's gotta sell these deals. And he would even despite his limited English, he would know the simple words to say, information revolution to bring happiness for everyone.
Speaker 2:Yeah. Right? It's very sort of simple.
Speaker 1:It's very intelligible. It's not Yeah. It's not techie mumbo jumbo about scaling curves and h 1 hundreds and all this other stuff. It's, like And even even
Speaker 2:his more recent decks have these very simplified Yep. People they're they're so simple.
Speaker 1:People make fun of them.
Speaker 2:People make fun of them, but then they end up being correct.
Speaker 1:Yep. They do.
Speaker 2:In many ways.
Speaker 1:And so the Vision Fund is born on '20 in 2017. He conceptualizes it in 2016 during a flight to The Middle East. He wrote down a target of $30,000,000,000 then crossed it out in favor of a hundred billion.
Speaker 2:What did he say? He said life's too short to think small. Yeah. And so Just tripling the size that
Speaker 1:you raised. Just yeah. Let's go big.
Speaker 2:1 of the 1 of the greatest probably the greatest fundraiser of all time, Sam Altman's very good at fundraising, yet he still has to go to Masa to really get the job done.
Speaker 1:Yeah. Elon's great too, but it's a very different style of pitch, more driven by the science and and Yeah. The technology.
Speaker 2:So he has this famous, forty five minute pitch where he's, meeting with the crown prince, of Saudi Arabia, Mohammed Bin Salman. Mas in Mas' words, he says, I want to give you a trillion dollar gift. If you invest a hundred billion, I'll turn it into 1,000,000,000,000. So MBS, ultimately invested $45,000,000,000 on the spot, catapulting the Vision Fund into existence. They also add a bunch of other investors, Apple's in the Vision Fund, Qualcomm
Speaker 1:Foxconn.
Speaker 2:UAE UAE's Mubadala, you know, sort of sovereign wealth fund.
Speaker 1:SoftBank puts in 28,000,000,000. Yeah. The funny thing about this is that he goes to MBS and is like, you gotta invest a hundred billion to I'll turn it into a trillion. And MBS is like, that's crazy, but I'm still gonna give you 45. Yeah.
Speaker 1:It's like a total shit.
Speaker 2:But 45.
Speaker 1:I'm good for my 45. And it's funny because his original target was 30. He sized it up and still exceeded that with the first check.
Speaker 2:Yeah. And and and there's been this, idea in tech that Middle Eastern money is is easy to get.
Speaker 1:Yeah.
Speaker 2:And that perception is only because there's a lot of capital out there. Mhmm. These relationships take a lot of time. Yeah. I know I know a ton of of allocators that have had to go visit The Middle East 10 plus times before getting anything done.
Speaker 2:And so it's not like this was easy. You know, Masa made it look easy because he just rolled over there. He was thinking about doing 30. Crossed it out. He liked the the a hundred to a trillion.
Speaker 2:But this was, again, a very credible feat by itself. And then SoftBank commits $28,000,000,000 of the fund. What Masa has done historically, I don't know exactly, but he also makes venture investments using leverage, which is Mhmm. Kind of a tricky situation to get in because, 1, venture investments can go down all the way to 0.
Speaker 1:Yep.
Speaker 2:Right? And yet he still owes that money to someone.
Speaker 1:The cash flow
Speaker 2:that I lost with
Speaker 1:that payments.
Speaker 2:He would use, SoftBank's, you know, actual earnings to to help, back that up, but then also would lever up other positions. So he would raise debt against Yep. You know, some of his specific positions.
Speaker 1:All those stocks.
Speaker 2:And so all throughout this, even from, you know, from the to now, he's gone almost bust in, like, smaller ways that don't even make it into the story because he was just levering up, just going long. Like, he doesn't you know, I don't think this man has ever been short, you know.
Speaker 1:He doesn't have any middle of the road outcomes.
Speaker 2:Yeah.
Speaker 1:It's all 10 baggers or zeros, which is great.
Speaker 2:Well, in the case of Alibaba, you know
Speaker 1:10000 bagger. Yeah. So he focuses on AI, robotics, IoT, and consumer tech. He makes bets on Uber, WeWork, ByteDance, Didi, DoorDash, Grab, and then quirkier startups like Zoom for robot pizza and Wag for dog walking. And it's funny because 3 of those are companies that have been, like, oh, this is such a silly idea.
Speaker 1:It never was gonna work. He was so stupid for doing it. And then, Uber, ByteDance, Didi, DoorDash, Grab, all banger companies. Yeah. All very, very good.
Speaker 2:Yeah. And 1 thing you'll notice here, he does not, he has no issues investing cross border. So he has big presence in The US. He has a big presence in China. And so he's 1 of the few that's actually threading.
Speaker 2:I mean, of course, some American venture capital firms have have gone and and raised Chinese money or invest in China, but he's getting into the best Chinese companies, you know, ByteDance Yep. Didi, the the Uber of, China. Yeah. He's, and so really, he's a he's a, truly global deal maker. Like, there he can go into any room and make stuff happen.
Speaker 1:And he's really good at being the capital that bridges these huge deals. Like, I'm pretty sure the the Uber and Didi deal, like, having having SoftBank bridge those 2 companies and put money into both in, like, this interesting way Yeah. Is, like, what kind of facilitated that. And and and that's just like a wild card. It's kind of the same thing that's happening with Stargate where he comes in and all of a sudden, like, Larry Ellison is with Sam Altman, and it's, like, more of this, like, Avenger style team coming together.
Speaker 1:Yeah. Because there's so much capital on the table. Everyone's like, okay. Yeah. I'm I'm I'm marching to the same beat of this Yeah.
Speaker 1:Drum. Because he's at
Speaker 2:the top. Oftentimes has the conviction to make stuff happen that otherwise would have never been a part of history.
Speaker 1:Totally.
Speaker 2:Yeah. I I recently invested in a founder, who will go unnamed that took a couple hundred million dollars from from, Vision Fund Yep. During 2021. And the pressure that he faced immediate you know, immediately after investment to deploy it. Because in hindsight, he's like, how did I spend that much money in such a short period of time?
Speaker 2:Company ended up, you know, selling. It wasn't wasn't
Speaker 1:Good outcome.
Speaker 2:A good good outcome. Yep. But he just said the relentless pressure of, like, we gave you this money
Speaker 1:Yeah.
Speaker 2:A hundred x your business this year.
Speaker 1:There's also this interesting dynamic with SoftBank. I've heard from, some folks that have had SoftBank on their board that even though Masa might come in, there's this example with WeWork. He gave Adam Newman, the founder of WeWork, three billion dollars on the first meeting and told him to be crazier. So the CEO and Masa, they they they get together. They have a short meeting, and it's like the deal's done.
Speaker 1:But then SoftBank actually comes in and puts in, like, crazy infrastructure in the board. And so if you sit on a board with a SoftBank board member, there will be audit committees, compensation committees. Like, they run it like a
Speaker 2:Public. Like
Speaker 1:a public company, basically. And so a lot of investors, like, hate that because they're like, I'm used to having, like, a one hour strategy meeting with my boys. And now I'm, like, doing, like, paperwork, which I'm not down with. I just wanna let the CEO cook and just do it. Yeah.
Speaker 2:In many ways
Speaker 1:but it's interesting.
Speaker 2:And in many ways, early on, I think investors would say this is amazing. Vision Fund, you know, very early, just gave a company that I invested in at a $8,000,000 val valuation. They just gave them a hundred million dollars. Right? It's a crazy valuation.
Speaker 2:So the markup's great. Company's super capitalized. But then over time, it ends up being seen as more of a kiss of death because a lot of these companies, unless you were this generational outcome like Uber, or DoorDash.
Speaker 1:You really need to deploy that money.
Speaker 2:Yeah. And you're legitimately a phenomenal business that's that's already has some maturity versus something like, you know, Zoom, like the robot pizza company where there's tons of competition. There's clearly no real network effect. It's
Speaker 1:called the suicide round. I like that I like that terminology.
Speaker 2:It's great. Cuckoo.
Speaker 1:And there's been a few of them. They lost money on WeWork, obviously, which we've talked about. They lost money on Wirecard, the German payments processor, which just collapsed after accounting fraud. Greensill Capital melted down, and many vision funds started. Even
Speaker 2:know about Greensill.
Speaker 1:About Greensill.
Speaker 2:Greensell. Was it was it the fund they invested in?
Speaker 1:Greensill. I don't remember. I thought it was, like, housing or energy or something like that, and, it it was a big blow up. And so there's been a lot of those, but he's still in the game.
Speaker 2:Yeah. And it's tough. Like, the reason, you know, the reason why these rounds ended up being the kiss of death is if you're not profitable and you raise $300,000,000 and you spend it all Yeah. Then you're sitting on this massive preference stack. Nobody else wants to back the company because
Speaker 1:Yep.
Speaker 2:It's gonna be tough to get any money out unless, like, everything goes perfectly.
Speaker 1:And and the number is so big, you think, like, oh, wow. He gave Adam Neumann three billion dollars and, like, it basically went to 0. Like, that's so embarrassing. And then you realize that in 2021, posted an annual net profit of $46,000,000,000.
Speaker 2:Yep.
Speaker 1:It's, like, enough to cover, what, 10 of those investments, 15 of those investments Yeah. Without blinking. And so you look at the GP commit on the on the on the vision fund, they put in what? 26 or something. 28,000,000,000 on a hundred.
Speaker 1:Yeah.
Speaker 2:They could do that all day.
Speaker 1:They could do that all day. And it's just like he's just the numbers are so big. You can't get you can't analyze them like it's a traditional fund because it's backed by this organization that's just printing cash, printing cash from all of their holdings.
Speaker 2:But now I think their their actual net income is in the single digit billions. So that was a specific moment in time where they had a lot of things go right Sure. Which was just due to COVID and interest rates and
Speaker 1:But he doesn't quit. You only need 1.
Speaker 2:You only need a couple of months to make
Speaker 1:it all back. Yeah. That's basically what he does every single time. And so, in 2022, '20 '20 03/00
Speaker 2:This this history going back again to his childhood, he was conscious when his dad was willing to bankrupt the family to go when they were already super successful. Right? So a lot of people look at this and it's like, Masa, you're you've made all these amazing investments. You built 1 of the biggest companies in Japan. You've been the world's richest man.
Speaker 2:Why are you still taking on all this risk? Yep. And the answer is he's playing the greatest, biggest game that he can play. Right? Which is
Speaker 1:And so, I mean, you were right that, a year later in 2022, they announced a $27,000,000,000 loss. And so they lose money on Klarna. There's a Chinese tech crackdown, and so Alibaba and Didi get hammered by PRC regulations. Very hard to make money as a private investor in China, especially if you're, Japanese instead of Chinese. And then it it emerges in 2022 to 2023 that he personally owes SoftBank five billion dollars due to side deals gone awry.
Speaker 1:He's
Speaker 2:just ripping he's so he's got his main deals.
Speaker 1:And he's just like, he's
Speaker 2:got his
Speaker 1:side deals. And I'm like, oh, yeah. I'm good for it. Like, alright. I'll put this on the ramp card.
Speaker 1:Yeah. Yeah. Yeah. Yeah. Just just, just hit up SoftBank.
Speaker 1:They'll take care of this billion dollar loss.
Speaker 2:Yeah.
Speaker 1:And so Masa says Yeah.
Speaker 2:And this is this is evident of the way that he operates, which is he is such a force that he's traveling all over the world doing deals, committing to things, announcing things that haven't been actually finalized yet
Speaker 1:Yep.
Speaker 2:And then telling his team, alright. Just make it happen. So it's not shouldn't be that surprising to anyone that after the chaos of 2020 to 2023, he just happened to, like, owe his own company $5,000,000,000
Speaker 1:Yeah.
Speaker 2:Because of, like, some other stuff that probably didn't even make it into the news. You know?
Speaker 1:It's remarkable. And so he shook it off. He says, when it rains, you open an umbrella. And he's repeatedly insisted that he's embarrassed by the fund's performance but remains an unshakable optimist. And we saw that come back, and we didn't even get to arm.
Speaker 1:You know? He he turned, something like 100,000,000,000 gain. He's back in the game, and he is making AI deals now, ripping checks into OpenAI, working on Stargate.
Speaker 2:It's just
Speaker 1:He's he's just not going anywhere.
Speaker 2:He's so he's he's the deal maker tech mogul that has the he clearly has a very powerful, very well known in our center, you know, corner of the Internet. Yep. But if you actually go ask people that maybe even are in tech but don't really follow the game closely, they won't know him. Yep. And the story is just truly incredible.
Speaker 2:Grows up in not just poor, but, like, abject poverty living with pigs. Yeah. Like, he has he he said he has a consistent nightmare around waking up, you know, having these nightmares that he's smelling, that the pig sort of fumes. Right? And he wakes up, like Yep.
Speaker 2:You know, in in, in shock. Right? And so to go from that abject poverty to the richest man in the world Yeah. Made his was born in poverty, made his first million in America before he turned 20
Speaker 1:Yeah.
Speaker 2:Runs it down to 0 again Yep. Runs it back up, back down to 99% down, runs it back up. It's so funny. Man, Doesn't quit. He can't be broke.
Speaker 2:No. He's like, the he should launch a course. Yeah. You know, like, at this point, like, if he if he ever got down bad enough, he just could launch a course.
Speaker 1:Well, yeah. It's so funny because this week that, hacker news comment went viral that's like, entrepreneurship is like, throwing darts at the dartboard at a carnival. If you're middle class, you get 1 throw. If the rich kids get, as unlimited throws and the poor kids are working the carnival. And this guy has gotten so many throws and he came from nothing.
Speaker 1:Just completely
Speaker 2:validated that. Throws.
Speaker 1:Yeah. He just figures it out. And, it's funny because that always goes viral and people are like, oh, this is so true. Like, this hits so hard. I looked up the dude who posted it.
Speaker 1:He's never launched a startup. He's never even tried. Yeah. And so it's it's clearly just cope just being like Yeah. You know, oh, yeah.
Speaker 1:Like, I can't do it because, like, I'm too poor or something. And, like, clearly, there's a million ways to start the flywheel. And then once you're on the flywheel, you get extra shots because it's like Yeah. Oh, well, like, your last company didn't do well, but, yeah, you probably learned a lot, and you were CEO of
Speaker 2:entrepreneur a lot. When he was in that, nightclub talking to all the Japanese at that time, it was not normal. You know, venture capital didn't really exist in Japan in the same way it does in America. And he gave the stories, like, in America, an entrepreneur can start 4 companies. They all fail.
Speaker 2:And on the fifth one, they become a billionaire.
Speaker 1:Yep. Yep. There's so many stories
Speaker 2:like that. And so the thing the that's the the criticisms of the the risky governments and the and the just crazy
Speaker 1:Yeah.
Speaker 2:Risk tolerance are real. We're not, you know, this show is obviously for entertainment purposes only. But the thing that I think everybody should take away from Masa is that extreme radical optimism.
Speaker 1:Yep.
Speaker 2:And, he showed that.
Speaker 1:Be a deal maker. Yeah. It's really just a story of of deal making in my opinion. Like, it's it's it's it's so underrated.
Speaker 2:Tech mogul without seemingly ever written writing a line of code.
Speaker 1:Maybe in the very early days.
Speaker 2:Yeah. Like, when he was
Speaker 1:But very quickly moved to just how do I assemble capital effectively? Yeah. How do I put the puzzle together?
Speaker 2:Sam Altman too. This is probably why they they
Speaker 1:Elon Elon hired Gwen Shotwell to run SpaceX. Like, it's a fantastic it doesn't take away it actually adds to their, like, their abilities. It it's leverage. It's leverage for the team, for the mind. It's fantastic.
Speaker 1:Well, that wraps up our deep dive on Masayoshi Son and SoftBank. Let's go to a promoted post from
Speaker 2:your guys' Eve.
Speaker 1:Oh, yeah.
Speaker 2:Small note. Yeah. He's got 2 daughters. Don't know their relationship status, but brothers. Why don't you if you send send Masa DM on LinkedIn and say, hello.
Speaker 2:I you know, if if you would review my profile and you find me compelling, I would love an inner a warm intro to your daughter.
Speaker 1:There you go.
Speaker 2:And he's still he's married to his wife that he actually met at Berkeley still.
Speaker 1:So Wow. That's fantastic.
Speaker 2:Masa always gets the last laugh.
Speaker 1:He does. He does. Let's get a promoted post from Steve.
Speaker 2:I got a promoted post from my buddy, Steve, Simone. So yesterday, you sent me this, which was a Chinese drone light show. And can you actually play it? No. You can't
Speaker 1:play it. Play the video.
Speaker 2:We're working on on tech here at Technology Brothers. We wanna get to the point where we can play videos, but I will just share. So Ben, Benjamin Cracker Cracker?
Speaker 1:Who knows?
Speaker 2:Who knows? The Cracker says, how do you defend against this? Not a rhetorical question. And it's a video of these drone crazy drone light shows. Yep.
Speaker 2:Steve says, you don't. You have a robot do it for you. And so what ACS is developing, I'd I'd love 1 of these to put on top of my my g wagon. Yeah. But, he's developing this sort of autonomous, counter drone, gun that can, I've seen, you know, a bunch of demos at this point, but it can take out I
Speaker 1:think I just described it as ACS, gun on truck.
Speaker 2:Gun on truck. Yeah. Yeah. Yeah. They should really buy gun on truck.com.
Speaker 1:Gun on a truck.
Speaker 2:Gun on a truck.
Speaker 1:And that's the
Speaker 2:but, anyways, go check out ad Steve Simone and, check out their their turret. It's pretty awesome, the Bullfrog.
Speaker 1:Fantastic. We have another promoted post from, Ryan, McIntosh promoting our show and promoting an ad in Arena Magazine.
Speaker 2:Is also promoted post for Arena Magazine.
Speaker 1:And there's an ad for ramp in the ad for Technology Brothers in the ad for Arena Magazine posted by Ryan. By McIntosh. There's levels to this. Yeah. And so, we whipped up a an advertisement, full page, full bleed, beautiful, full color printed in the latest arena magazine.
Speaker 1:And
Speaker 2:why don't you why don't you read it the whole thing top to bottom?
Speaker 1:Sure. So I said, technology needed a podcast. Last year, we noticed a problem. While we were listening to the All In podcast on vinyl, we realized something shocking. It doesn't have ads.
Speaker 1:No ads for watches. No ads for private jets. Not even a plug for ramp. It's hurting the tech community, but the madness ends today. What if instead of focusing on audience size, a podcast focused purely on profit?
Speaker 1:What if instead of big political questions, it answered the ones entrepreneurs really care about? Should I get a Ferrari f 40 or a Lamborghini Miura? Should I upgrade from a Gulfstream to a BBJ? What's the best Aman property? Technology Brothers is that podcast focused, profitable, capitalist.
Speaker 1:Visit techbrospod.com today and add it to your, RSS feed.
Speaker 2:We before we dive into the rest of the timeline, we got some questions.
Speaker 1:Let's read these questions.
Speaker 2:Tyler Rongioni with a phenomenal suggestion. He says, get a medieval knight helmet for steel man arguments.
Speaker 1:Oh, that's fantastic.
Speaker 2:So much better than That's
Speaker 1:so good.
Speaker 2:So much better than
Speaker 1:Steel hat.
Speaker 2:Yeah. Than just a steel hat. I mean, we have our tinfoil hat, but the this the the medieval knight helmet is a good, opposite.
Speaker 1:Yeah. We need both of these clearly.
Speaker 2:And, anyways, just j, the letter j says, which 1 is the Technology Brothers' favorite, YOLO seed round or guac a round? I I think that it's the mango seed round
Speaker 1:or the suicide a round.
Speaker 2:Suicide. No. It's more of the suicide b too.
Speaker 1:Suicide b is typically what that
Speaker 2:does. 300000000. Just die. They just start
Speaker 1:a ball on people.
Speaker 2:I love I love a YOLO. I love a YOLO. I actually like when the first round is just 20. Yeah. You know, kind of like that incorporation round, 20 on a hundred.
Speaker 2:Those ones always work out great. For sure. Next question. Venturi says I think he's responding to Masa on steel making. I I don't know exactly.
Speaker 2:He says sales is massively more valuable than engineering, so Venturi's clearly mogging, the engineers listening. So feel free to duke it out in the comments. But in Masa's case, he probably had way more impact on the world by being a deal maker. He he might have been a top 10% engineer, he's a top point o 1%.
Speaker 1:Yeah. I I think he it's clear that he did the eighty twenty on the computer science thing, took the classes, got really pedaled on technology, and understood how exponential curves will affect the future of the world and humanity. And he can still think like a technologist while not actually needing to lead a tech company, be a CTO, be a programmer, do any of that. But he understands the science at a deep enough level, which is important. But
Speaker 2:Yeah. He's still not using that knowledge for diligence though.
Speaker 1:Yeah. Truly viable. And I mean, we have company we have friends that buy small companies where people say, oh, did you do, like, technical due diligence, look at all the code? And they're like, no. I looked at the Stripe account because if the if the customers are paying, that's evidence that the code is working.
Speaker 2:Yeah. Or just use the product yourself. Exactly.
Speaker 1:Is it
Speaker 2:a good product?
Speaker 1:Is it a good product?
Speaker 2:I know there's this has been happening with with really smart sort of AI ML trained engineers that are now building products at the app layer. Yep. Oftentimes, they know so much about the actual technology but can't translate it into products
Speaker 1:that people love. Like, oh, cool. Like, your training and inference cost is so low. That's amazing. But, like, what's your product sense like?
Speaker 1:Are people actually using it? Did you get viral market fit? Yeah. Exactly. Exactly.
Speaker 2:Azar says, should companies stop paying dividends to reinvest their dollars into custom letterheads? Yes. Obviously. You need to have custom letterheads. We're working on it here.
Speaker 2:We're actually, you know, behind I got some letterheads. Our own actual stacks of paper even though we're sort of evolving. I
Speaker 1:got the business cards. We need TB business cards. I got some personal stationery. I need some TB stationery for sure.
Speaker 2:Hanil Patel says, I'm planning to do my master's at Berkeley in civil engineering.
Speaker 1:Should I in this. Let's test it. Masa.
Speaker 2:Should I do it? He's an international student. He says he wants to go become a founder or break into founders fund. Both good options. Hopefully, you get well, you definitely have the first option, founders fund.
Speaker 2:It's tough tough to get in, but, we have at least 50% of this podcast, works for founders fund. So if you're listening to it, that's a good start. I you know, if you wanna be a founder, doing a master's in civil engineering might be awesome.
Speaker 1:Sorry. It depends on what you wanna build.
Speaker 2:Be a huge distraction.
Speaker 1:It could be a huge distraction.
Speaker 2:So if you wanna, you know, go into that field, and I'm sure there's a bunch of really crazy cool opportunities to apply, like, modern technology within that. So I don't think it's a bad idea, especially if you're inter you know, not a US citizen and you wanna spend time in Berkeley. I mean, so many
Speaker 1:Yeah.
Speaker 2:Berkeley is doing a bunch of cool stuff in AI. I don't know if it's in the timeline, but they I mentioned it earlier. They were able to create a reasoning model for, like, $450. So just being in The Bay Yep. I was born in Berkeley.
Speaker 2:It's a funny, funky town, but you're right there next to
Speaker 1:San Francisco. Going to The Bay. I guess the question is, will this pull forward finding a really, really valuable idea? And sometimes being in a master's program can be a conduit to industry where you might identify a big problem and identify customers. Sometimes you can bootstrap that without that, you know, on on the resume.
Speaker 1:You could just go work straight at a company and realize, oh, this stuff's way broken. I gotta spin this out and build something. Yeah. So there's a bunch
Speaker 2:of Yeah. You're probably gonna have to go from your civil engineering masters to work at a company to truly just figure out. So the question is, can you just go straight to the company Yep. And get those learnings? But starting companies is not a race.
Speaker 2:There's just so many examples at this point of people that started their first company at 40 years old, and they needed all that experience to Yep. Get to the point where they had the knowledge. 1 2 more questions. Do the technology brothers have a favorite pen or pencil brand from Azar again? I actually don't.
Speaker 2:My handwriting is terrible.
Speaker 1:Not lost. We promoted on the show before.
Speaker 2:I'm using a Bowery hotel pen here. Okay. But But also hire a calligrapher. Yeah. For me, it's just gotta go higher.
Speaker 1:Full time.
Speaker 2:Sergio says, do you guys publish anything in the paper form, or do you have a website? Yeah. We have, techrosepod.com and a new website that is already in the works with a new domain that we're excited to share soon. And then we don't do anything in paper yet. We're experimenting Auction these off.
Speaker 1:Are valuable.
Speaker 2:Kids' books. We've talked
Speaker 1:about random tweets.
Speaker 2:We talked about making a book that's just, why you shouldn't use leverage Yeah. And then it's just
Speaker 1:Blank.
Speaker 2:A hundred empty pages. Love that. But, but, yeah, we we stick with, Arena right now. That's our magazine of choice. And, and
Speaker 1:And Colossus. Colossus.
Speaker 2:Yeah. Of course. So thank you guys for the questions.
Speaker 1:Fantastic. Well, let's go to Grant. He says, substituting three hours of daily scrolling through x.com with three hours of playing Factorio while listening to the Tech Bros pod gets me up to date on the news I care about plus teapot bangers of the day while destroying biter biter nests and juicing mining productivity. I have a similar hack for work. Instead of writing code for eight hours like a pleb, I spend five minutes writing GitHub issues for Mentat.
Speaker 1:Alt tab and spend ten minutes expanding my green circuit board, then flip back to GitHub and review PRs. Mentat is the fastest, most capable AI agent for coding that plugs directly into your GitHub workflow. Log in at mentat.ai for $30 worth of credits free and redirect your engineering talents toward expanding your base.
Speaker 2:Brilliant brilliant post. Talks about the show. Yep. Talks about the content. Yep.
Speaker 2:Puts an ad in it.
Speaker 1:I love it. I love it. This is peak 1
Speaker 2:post, you're gonna have a ton of different content in your post including ads. So love to see it.
Speaker 1:Well, we got another we got another promoted post by none other than Lulu Meservi. We got a fantastic opportunity. She says, wanted a founding engineer to join Rostra to work with me on a novel tool for founders. Like a Waymo, you will be fully self driving. Like the media's portrayal of a Waymo, you will go through walls if it's the shortest path.
Speaker 1:You will choose your own tools for the job, but experience with LLMs with tool use will help greatly, especially if it involves building long chains of structured and unstructured outputs. You are creative and tasteful with a strong sense of style and vibes. You have a finely tuned cringe detector and ability to read the room. If you believe you are the person to do it, apply at the link below. Fantastic job opportunity.
Speaker 1:If you're looking for your next thing, hit up Blue.
Speaker 2:I mean, that's actually the craziest opportunity that I've seen in a while. Yep. It and and, truly, if you're, Omega Cracked, go apply for that, or DM us, and and we'll let you know if if we think, you know, you'd be a good fit. Lulu's phenomenal, and the kind of companies you'd be building products for are legitimately some of the best founder mode companies in the entire world.
Speaker 1:So Totally.
Speaker 2:Crazy opportunity.
Speaker 1:Well, we got some personnel news. We got some breaking news here. Scott Belsky, after seven years at Adobe post acquisition of Behance, he's shifting gears over the coming months and jumping into the fast evolving world of filmmaking and storytelling, a long time passion. He's joining a twenty four, an independent studio he has long admired as a partner, and he will be kicking off a few special projects within. Fortunately, he'll remain in the extended family of Adobe and look forward to working with them as a future tech partner.
Speaker 1:You wanna break it down, Jordan? What else you got for me?
Speaker 2:This is absolutely massive. I can't you know, if if it's non obvious, he's going to work on AI within a twenty four.
Speaker 1:Yep.
Speaker 2:He doesn't necessarily say that explicitly, but a twenty four is 1 of the, you know, greatest, film, you know, production media companies in the world. Yep. Josh Kushner also made a big investment in eight twenty four, Sizelore that we've talked about on the show before. And, I'm just so excited to see what comes out of this. This is
Speaker 1:It'd be fantastic.
Speaker 2:Exactly you know, for so long, it feel you know, we live here in LA. Yep. For so long, it feels like Hollywood has just been so behind the times in terms of actually innovating. They obviously there's, you know, a massive sort of CGI industry here. Yep.
Speaker 2:A cottage industry around LA. But, the opportunities of applying generative AI to filmmaking are so obvious, yet we still need the best talent in the world to actually implement that and make that happen. So Scott going over to a 24, he I imagine he's gonna build out a massive, you know, team of really bright technologists that are going to allow generative AI to actually, compete with traditional filmmaking Yep. Which is going to be incredible for consumers.
Speaker 1:Yep. Period.
Speaker 2:Absolute dog. An absolute dog.
Speaker 1:Belsky on the move. Stay tuned for what's next.
Speaker 2:And, yeah. This is massive.
Speaker 1:What a pickup by a 24. You love to see it. Well, we have another massive announcement breaking here on the show. You definitely haven't seen the tweet before. Eleven Labs has raised a hundred and $80,000,000 series c to give every AI agent a voice.
Speaker 1:Let's go. Oh, with authority.
Speaker 2:With authority.
Speaker 1:You'll love to see it. The past year has been about building the foundations of AI audio. Now they are focused on making speech the standard for how we interact with technology. Yep. And so if you haven't checked out Eleven Labs, they have some fantastic abilities to turn text into audio that sounds perfectly human.
Speaker 2:Here's a homework assignment. Download a transcript to this show all three hours. Put it into Eleven Labs. Generate it in some exotic sounding voices.
Speaker 1:Give us Irish accents.
Speaker 2:Irish accents like
Speaker 1:The majority Scottish.
Speaker 2:Make me sound like Pat old Patty Collison.
Speaker 1:Yeah. I wanna sound like
Speaker 2:And, it's interesting some of these models Sean Connery.
Speaker 1:Put me in a Sean Connery voice, please.
Speaker 2:Please. Some of these, you know, voice generation tools have some limitations. Yep. They let you do Irish, Scottish voices. They don't always let you do Japanese.
Speaker 2:Japanese. Unfortunately. Which is unfortunate. We were
Speaker 1:trying to generate some
Speaker 2:of the MASA 11 can do a MASA, you know, adjacent voice Yes. That we could leverage because we have a lot of uses for that. For sure. And we would we would happily pay a few million bucks a year to get access to that voice.
Speaker 1:Fantastic.
Speaker 2:But congrats to the Eleven Labs. Congrats to
Speaker 1:the Eleven Labs team and everyone involved in that deal.
Speaker 2:There was some cheeky secondary in there.
Speaker 1:Hopefully. Let's go to an evolving story. This is heartbreaking. Late yesterday, if you were watching the show, we gave mass brother of the week We did. For his amazing work putting up a swing in a public park in San Francisco.
Speaker 1:He says they took the swing down. Apparently, fun is illegal.
Speaker 2:That's insane.
Speaker 1:Isn't this crazy? That's insane. And the picture is of someone, like, with the government saying no swings.
Speaker 2:It's like, hey. We know somebody's actively breaking into your car right now just, like, 10 feet over there.
Speaker 1:We're gonna swing down. This is the priority. How it's it's just so bad. It's so bad. It is the perfect symbol of everything that is wrong with the government prioritization here.
Speaker 1:It's it's really just so ridiculous. Just, the mass brought joy to the world, went viral, and is it was immediately shut down by the long arm of the law. And so, mass, please don't go full Ross Ulbrich mode. Keep things legal. Maybe there's a way to get through this.
Speaker 1:We'll get the swing back up. Maybe a petition. Maybe we'll go viral. Maybe we will upend the entire San Francisco government, but we'll do it entirely legally, and we won't need to, create a massive, illegal drug network to do it. Great.
Speaker 1:Let's go to Jason Yenowitz. He says, Tether, thirteen billion net profits last year. Every financial institution will read this and ask, why don't we have our own stable coin? So I don't know that much about Tether. I know there's been, like, rumors swirling, but the Tether organization seems to be on a tear.
Speaker 2:Yeah. So they've had a lot of, people that sort of question their business. Right? It's sort of this they they control tens of billions of dollars of assets. I don't know the market cap of USDT USDT, but whatever it is, if they have a hundred billion dollars in market cap Yep.
Speaker 2:That is a hundred billion dollars of basically cash Yep. That they have Yep. On their balance sheet.
Speaker 1:And so They invest that in treasuries, so they earn some interest rate. Yeah. They give you some of that,
Speaker 2:but they keep a little bit. Of it. That's generally the business model. It's a
Speaker 1:good business
Speaker 2:model. Yep. And so Everything
Speaker 1:can be in the flow of money. It's easy to
Speaker 2:just take a little slice. And so Tether has been also pretty aggressive on the m and a front Yep. Making you know, if you're doing anything sort of adjacent to them and getting traction, they'll probably make an offer, and they they make, typically control offers. So they'll say, we wanna buy your business, but we want 51%.
Speaker 1:Yep.
Speaker 2:And, so they've been on a tear very under the radar. They don't have as much hype because nobody's printing, you know, thousand x returns off of Tether. Yep. They did have some crisis points where if you remember after after all the FTX stuff
Speaker 1:There was a lot of questions.
Speaker 2:That USCT was trading at less than a dollar, which a lot of people were like, this is free money. Yep. But Deepak did not
Speaker 1:not chaotically. It wasn't down at 10¢. It was down at, like, 99¢ or 97¢ or something.
Speaker 2:I think it got even more than that at 1. But, It's rough. But but, yeah, still, they were you know, people were
Speaker 1:But for those people, it was free money.
Speaker 2:But the interesting thing is because it it's an international organization, there's not as much, there's not necessarily you know, the FUD around Tether has been, are they just sort of taking a dollar and printing $2 on chain or something like that? But they've weathered every storm to date, and and we'll see what happens, and, absolutely meteoric numbers.
Speaker 1:You love to see it. Should we hit the size going for that? Little 1?
Speaker 2:Little 1. 13 billion in net profits.
Speaker 1:Pretty good. Let's go to Varunam Ganesh. He says, if you're not subscribed to Pirate Wires already, you really should. Missing out on bangers like these. From Riley Nork, he says, in the wake of Trump's recent executive order renaming the Gulf Of Mexico after its namesake superior northern neighbor.
Speaker 1:I said what I said. Google Maps announced it would indeed rechristen the ocean basin as the Gulf Of America, but don't pop bottles on your boat just yet. Right after the change was announced, Google reclassified The US as a sensitive country, a label reserved for nations with strict governments and border disputes like China, Russia, and Iraq. In other words, they're virtue signaling. Google wants to pretend they're here for text vibe shift, but behind closed doors, they're rebranding Trump's America as an authoritarian dictatorship.
Speaker 1:Bold strategy for a company with an ongoing antitrust suit, a laundry list of foreign governments that want to rob them blind, and a president, their only real hope against those governments, who famously, to borrow your phrase, sensitive to public ridicule. Good luck. And the reason,
Speaker 2:I just like this ad copy.
Speaker 1:I love it. Sharing this is because there's some fantastic ad copy, which we love to highlight sponsors. We love to pass through ads when we're reading content. If it has ads Sponsor acknowledgement. Sponsor acknowledgment.
Speaker 1:It says Warp fixes this. If I run the FBI, we're shutting down headquarters on day 1 and reopening it as the Museum of the Deep State. Kash Patel's words, not ours. Here's the thing. Your business has a deep state too.
Speaker 1:It's called the HR department. You know, the bureaucratic overlords who bury you in paperwork in pointless meetings. Warp shuts them down cash style by automating payroll, navigating state tax compliance, and making in international contractor payments effortless so founders can focus on building, not busy work.
Speaker 2:1 of my portfolio companies got kicked off of rippling with with 0 notice, and Warp got them live again the same day.
Speaker 1:It's great. You love to see it.
Speaker 2:Love to see it.
Speaker 1:Let's go to Balaji. He's talking about our favorite topic, technology brotherhood. He says, we need the tech bro. Massachusetts equals tech. Virginia equals bro.
Speaker 1:The synthesis is greatness. Lift weights, yes, but train weights too. And I agree. He goes on to expand on the analogy, doing a little bit of Coogan's law here. Coinages, Balaji, fantastic coiner.
Speaker 1:He loves coining.
Speaker 2:Big coiner.
Speaker 1:Big coiner, Bitcoiner, and
Speaker 2:big coiner. Base.
Speaker 1:Coin base. Coinages. All of the above. To explain, Virginia's time ended long ago, and today is just another US state, but it was originally the home of the masculine, noble, and brave cavaliers. Massachusetts' time is now ending too, but for almost four hundred years, it was a center of higher learning.
Speaker 1:That's why Harvard and MIT are there. They these were 2 of the most important American colonies. In a sense, they compete and cooperate every hundred years. In the they fought back in in in England itself. First, the cavaliers, the moosed for Virginia, then the round heads migrated to Massachusetts.
Speaker 1:But where does he learn this stuff? I've never heard those terms before. Roughly speaking, the cavaliers were right and the round heads were left, and the English Civil War was over the same themes of hierarchy versus equality. In the they worked together to beat Britain and found The United States. In the their descendants fought in the civil American war.
Speaker 1:And in the 19, they worked again together to win World War two and found the American empire. Now in the 2, they are fighting once again over the same themes of hierarchy, red versus equality, blue. Even if the geographic center of red has been displaced somewhat to the South and the geographic center of the blue has been dispersed across the Northeast. Others have written about this as well. See the fourth turning, Turchin, Yarvin, Walter Russell Mead, Albion Seed, and Scott Alexander's review.
Speaker 1:My view is that red and blue will unfortunately smash each other to pieces over the next several years, and then the gray will have to pick up the pieces. Gray is tech in its modern incarnation of the tech bro. Tech is the intellectual successor to Massachusetts as the migration of to the Internet of Harvard's best proves. Bill Gates, Zuck, and Paul Graham all moved away from Harvard in the literal sense. And of course, Larry Page, Steve Jobs, Vitalik, and many other college dropouts moved away from Harvard in the metanomic sense.
Speaker 1:But in its more recent Techbro incarnation, tech is also becoming the virile successor to Virginia. Elon, Zuck, and Palmer Luckey are examples of Tech Bros respectively becoming leaders of men, packing on muscle and getting serious about the military. Amazingly, this synthesis, the Tech Bro, did not exist years ago, but it was memed into reality by blue attacks and the and has the balance that blue and red both lack. Train weights, yes, but also lift weights. I think this synthesis, the tech bro, will be crucial to what follows.
Speaker 1:After all, the tech bro founded America. Let's see what they found next. What do you think?
Speaker 2:I don't wanna say anything at all because I feel like it would take away from that dramatic powerful prose.
Speaker 1:It's been I
Speaker 2:think he nailed it. Yeah. If, if I had to fight in the culture war
Speaker 1:Yeah.
Speaker 2:I would want Balaji to be Mind Napoleon.
Speaker 1:Yeah. Mind Napoleon. I love it. It's great. I I think, I mean, we literally worked out today.
Speaker 1:We it was leg day. I'm super sore. And then we dove into semi analysis and talked about training weights and and AI semiconductors for an hour. And that is the fantastic dichotomy of the tech bro that is so enjoyable and wonderful, and I think value creative as well. And it's interesting because, during the the the when tech bro was a slur, we could have just said, no.
Speaker 1:It's actually fine. It's fine to be a programmer and and lift weights and program. Or a programmer. There just wasn't enough, like, mimetic or social, like, power to actually have a post like this that everyone says, yes. I'm on board.
Speaker 1:It took Coinbase. It took
Speaker 2:And now you have people like WordGrammar who did 1 of the best analyses of, the DeepSeek research paper. Yeah. He's an amateur powerlifter.
Speaker 1:Oh, he's jacked.
Speaker 2:And I would actually push him to say, you know, keep being a professional programmer Yep. But become also become a professional powerlifter.
Speaker 1:Like
Speaker 2:that. Don't limit yourself.
Speaker 1:He's diced?
Speaker 2:He's he's diced. He's diced. He's jacked. That's fantastic.
Speaker 1:We'd love to see it.
Speaker 2:Follow word grammar.
Speaker 1:Well, let's go to this post by Andre. Funny meme. I I like this meme format. It's Sydney Sweeney and Ana de Armas recently had a spontaneous exchange about which characteristics would constitute a sixth generation fighter aircraft. Sydney, no standing vertical tail surfaces, the ability to operate AI enabled drone wingman, Anna.
Speaker 1:But those will be first fielded in So drones alone would not constitute a sixth generation fighter. Sydney. Well, fifth gen, sixth gen, these are marketing terms, not technical classification. Northrop Grumman is calling the b 21 Raider. Anna says, a heavy payload strategic bomber.
Speaker 1:Sydney says, a heavy strategic payload bomber, the world's first sixth gen aircraft. Also, China doesn't recognize the same designations at all. They recognize the j 20 and the f 35 only as fourth generation fighters. On us is, okay. So what else?
Speaker 1:Adaptive cycle turbofan engines, open system software architectures, suborbital flight. Sydney says, l m a o. I wouldn't hold my breath on that 1. And, just a great way to deliver a little bit of information. I definitely learned a little bit about, fourth, fifth, and sixth generation fighters from this.
Speaker 1:Hadn't heard the terms, vertical tail surfaces before, adaptive cycle turbofan engines, but now I know to go look them up. So thank you for turning it into a meme.
Speaker 2:Ready for Yeah. I love when any new video just, like, merges on the Internet of a potential Oh, yeah. Sixth gen fighter, and then everybody just, like, breaks it down in a million different ways. And you just get 1 thread and learn a lot about fighter jets and about 20 comments.
Speaker 1:And it's just it's so fun. It's so fun to learn about this stuff. So we got a post from Kyle Simani, huge investor in Solana. He says, Polymarket parlays. Who's building this?
Speaker 1:And the reason I wanted to highlight this was because six months ago in Oct. 23, I said, does Polymarket allow parlays? Because I want Lando Norris in Mexico City, Four rate cuts, Trump Rogen over two hours, and US confirming aliens exist. I would have lost this parlay, but I could have made a lot of money if they had that product. I did talk to the Polymarket team about parlays.
Speaker 1:It's very hard from, like, the crypto perspective on the back end to actually implement it, but it would be very fun. And I and I on the on the Pirate Irish podcast, I talked about the the Coogan parlay, which was, you bet whoever does whatever whatever presidential candidate does the longer episode of Joe Rogan will win the, the popular vote and the and the national election.
Speaker 2:Oh, right.
Speaker 1:Because, basically, I was saying that, like, I I was predicting that this would be the podcast selection and that and that now that three hour podcasts were on the table, it was really gonna be a battle for attention. And whoever could be in the ears of more Americans for longer would drop the
Speaker 2:and authenticity. Totally. Totally. Which you cannot hide
Speaker 1:Yep.
Speaker 2:Your true self beliefs, etcetera Yep. Across three hours. An hour Totally. You can hit talking points Exactly. Have your notes.
Speaker 2:But by hour we know this. By hour three, you're just
Speaker 1:The real that's when the real Jordy comes out. Yeah. That's when the real Johnny
Speaker 2:comes out.
Speaker 1:The real dog. Yeah. Yeah. You gotta put the By
Speaker 2:hour three, your dogs are yeah. Your dogs are barking.
Speaker 1:Yeah. And, and so, yeah, there was a lot of debate over, oh, Trump's too old. He couldn't last two hours, three hours on Rogan. There was a whole poly market for it. And then, obviously, Biden, people were saying he couldn't do Rogan, but then Kamala, they were like, well, she's gonna go and call her daddy.
Speaker 1:That'll be really big. But her caller daddy experience was, I think, like, her appearance was, like, maybe an hour, maybe slightly over, and it just wasn't as viral because it wasn't as long. It wasn't as deep. And I think that really hurt. I really I I think I do think that really changed the election.
Speaker 1:Let's, skip this next 1. Did you see this, the Derek, Die Workwear, the watch guy getting in a fight? This is
Speaker 2:pretty fun. Share this. Alex this. Alex broke it down. So, basically, Derek, Derek Guy at dye workwear posted a handful of watches that he was, thought were for were interesting as as well as a belt.
Speaker 2:Somebody quote quote quote, quote tweeted it and said, if you ever need a reminder that this society deserves to be destroyed, it should come from the fact that absolutely anyone cares in the slightest about any of this, nonetheless, are willing to pay many years' salaries for some something you can get for $5. So this guy's basically saying society should be destroyed because people like nice things. Yeah. They go back and forth a little bit. Derek immediately responds with a bunch of evidence that the guy that quote posted him, who actually has a lot of followers, is a, pedophile Convicted.
Speaker 2:Convicted sex offender. And, and this guy
Speaker 1:is astronomical.
Speaker 2:And so and this guy
Speaker 1:5000 likes to just 0 likes.
Speaker 2:Yeah. So this guy actually has the audacity to respond and tell Derek, one of us will be remembered for trying to save millions of innocent lives. This is the same guy who said society should be destroyed.
Speaker 1:Yeah.
Speaker 2:And the other will be remembered for embodying why this society doesn't well, your only god is luxury. You're emblematic of absolutely everything wrong with the society, and says and Derek says, I like watches. You're on a watch list. This is
Speaker 1:such a good time. Ratio again. You know, we talked about
Speaker 2:I I think this guy
Speaker 1:He's a fantastic poster. He's a fantastic poster.
Speaker 2:Anyways, the guy he's going back and forth with, should delete his account. Generated generated a bunch of regretted user seconds. Oh, totally. But at at least Die Workwear managed to turn it into entertainment for the rest of us.
Speaker 1:That's fantastic.
Speaker 2:Anyways, absolutely brutal. Brutal.
Speaker 1:Highlighting that Alex Cohen. Cohen. We appreciate you. Let's go to Andrew McCallop, friend of the show. He's been on before.
Speaker 1:He says, how embarrassing must it have been for all these car manufacturer dynasties such as Ferrari to get completely dominated by a caffeine wrapper company in f 1? We're talking about Cat
Speaker 2:Bull. Cat Bull is just a wrapper on caffeine.
Speaker 1:And they've and they've crushed it. Max Verstappen's an absolute beast. The car is
Speaker 2:Obviously, it's not Red Bull manufacturing the engine, but it's a lot of the energy and the brand of Red Red Bull definitely comes through with the team. Yeah. And And the budget
Speaker 1:and stuff.
Speaker 2:Yeah. Did you see Lewis Hamilton just crashed in the Ferrari
Speaker 1:for his
Speaker 2:first time? I mean, he's fine. Yeah. But it was a practice run.
Speaker 1:Okay.
Speaker 2:Crashed.
Speaker 1:Well, he's
Speaker 2:he's he's he's to start we might have to start live
Speaker 1:live streaming Yeah. F 1. I think that's the real failure mode for the show. You know, people always criticize, oh, all in all they used to talk about tech. Now they just talk about politics.
Speaker 1:I think if this show goes down the drain, it's gonna be because it just becomes an f 1 show, and we're just talking about sports all the time. Yeah. Just sports all the time. And everyone's like, didn't they used to be talking about tech? Like, why are they covering the NBA finals?
Speaker 2:Somebody somebody a, friends a friend's company told us, very recently that they were, it'll all go on on name, but they're like, we're working on this, you know, partnership with this athlete. Turns out to be a very famous athlete. Neither of us knew who they were. We're like I was like, is that, like, an actor or something?
Speaker 1:This is part of Golden Retriever Maxing. I'm getting into sports because the politics stuff is too much. It just rots my brain, and I wanna be able to just chill out and just
Speaker 2:Rip parlays.
Speaker 1:About the game. Yeah. Rip parlays. Exactly.
Speaker 2:I wanna be very smart. Ripped a parlay.
Speaker 1:The first one's gonna be electric when it hits. What if you hit it on the first try? You're gonna be addicted for life.
Speaker 2:Awesome.
Speaker 1:Yeah. Let's do it. Awesome. Speaking of ripping parlays, we got Ross Ulbricht to update from our deep dive most recently. He lost $12,000,000 on pumped out fund.
Speaker 1:Hilarious that he has $12,000,000 to lose. No. No. No. No.
Speaker 1:No. No. No. No. No.
Speaker 1:No. No. No. No. No.
Speaker 1:No. No. No. No. No.
Speaker 1:No. No. No. No. No.
Speaker 1:No. No. No. No. No.
Speaker 1:No. No. No. No. No.
Speaker 1:No. No. No. No. No.
Speaker 2:No just accidentally nuked the price of a pump fund coin sent to him while trying to provide liquidity to said coin. And so what happened is somebody basically made a coin, like a free Ross coin or some type
Speaker 1:of
Speaker 2:coin that that ripped because, obviously, the vast majority of of Ross's biggest fans are are heavily involved in crypto. And, so anyways, they then sent him a lot of the token because they're like, hey, this is your token. And then they he made a sort of technical error in terms of trying to actually he was from what I can tell, he was trying to, support the the the project basically by adding liquidity to it, which presumably would have made the the price go up. But, he ended up blowing, more yeah. $24,000,000, which was which was effectively, I don't know exactly how it works, but some type of bot that's entire job is to
Speaker 1:find coins.
Speaker 2:No. No. Like just find new traders like whales. Yeah. If you're if you're a super talented software engineer, you can write code that just sort of it's the same similar to high frequency trade trading.
Speaker 2:Right?
Speaker 1:Yep.
Speaker 2:And so, anyways, basically, wealth transfer of $12,000,000 from, from him, error, the wallet that that he controls to, this bot. So the bot did well. Everybody else got smoked.
Speaker 1:Good day to be a bot.
Speaker 2:Good day to be a bot.
Speaker 1:Yeah. Maybe consider going digital.
Speaker 2:But it's but somebody I I saw people in the comments saying he's he's a little rusty. No. But but but even in the era, even when he even during the height of the Silk Road, he would there were coins
Speaker 1:flying around every He's this is part of the course.
Speaker 2:He would lose 10,000 Bitcoin in a day and just shrug it off. He'd be annoyed. Yeah. I'm gonna fix the code.
Speaker 1:I'm gonna kill the person that did it.
Speaker 2:Just a little bit.
Speaker 1:Or try.
Speaker 2:You're gonna order the hit. You're not necessarily gonna Or
Speaker 1:try to try to do it. Let's go to Luke Metro. He says AWS GovCloud is safe, y'all, because breaking news in a major reversal, Amazon is ramping up ad spending on x after pulling much of its advertising, spend more than a year ago. And this is I wanna cover this because this is a major narrative violation. Like, after Elon bought x, all the all the advertisers pulled out, he told them to f off.
Speaker 1:It was very dramatic. And there was this question about, like, okay. Are they gonna be able to get the premium side running? Like, is the business model gonna change completely? But advertisers are coming back.
Speaker 1:We're set I I'm setting up, an advertising, program with them, for Lucy, and they've and they brought a ton more advertisers on. They just did a deal with Visa. And just in general, the vibe shift is is perfectly timed because people realize that, yeah, there's a lot of valuable people on x, and it's worth reaching Do
Speaker 2:you remember aft after the whole ad crisis?
Speaker 1:Yeah.
Speaker 2:All the advertisers were things like, buy these Donald Trump socks.
Speaker 1:Yep. You know?
Speaker 2:It became, like, the bottom of the bottom
Speaker 1:of So bad.
Speaker 2:Of just, like, people that will, like, pay for any type of
Speaker 1:But then quickly, I upgraded to x premium plus pro plan or whatever, and I never see any ads now, and it's actually lovely. It's it's totally worth it.
Speaker 2:I don't know. I kinda miss
Speaker 1:Kinda miss the ads?
Speaker 2:Seeing an ad here or there.
Speaker 1:Well, if you see a good ad, screenshot it, send it to us, and we'll read it on the show. Yeah. Yeah. As long as it's in a 5 star review. Yeah.
Speaker 1:So, peak journalism, this is this is just hilarious. Everything I say leaks, Zuckerberg says in leaked meeting audio. You'll love to see it. Absolutely banger. Get it on the back of your archive.
Speaker 1:Very funny. It is it is interesting. Like, there's there's some sort of shift that happens as companies scale and get more media attention, and it obviously matters a lot more if it's consumer and it gets clicks. I'm sure this is the case at all the Elon companies no matter how small they are. A reporter will be dedicated to, like, the the Elon Musk beat or the SpaceX beat or, you know, the the Meta beat.
Speaker 1:And they'll be like, yeah. I was at the Wall Street Journal for four years. I was covering Meta. And so I cover their earnings, but I also cover any press release, and I'd be talking to employees all the time just trying to get information on what's going on. Oh, telling a story, trying to get clicks, also just doing good journalism sometimes.
Speaker 1:Occasionally, it happens. And, and it's funny that this leaked. It's almost like he baited this out. Yeah. Like, he knew it was gonna leak, and so he just said that because it's hilarious.
Speaker 1:But it really it really must be so weird to be Zuck. And that's something I'd never seen an interview hit on is, like, what is your life like? You're this, like they made a movie about you when you were in your twenties. Like, very few people get a biopic by Andrew Ross Andrew Sorkin. Yeah.
Speaker 1:No. Andrew Sorkin is the Aaron Sorkin. Aaron. Aaron Ross Sorkin is the is the journalist. Yep.
Speaker 1:And so just just a bizarre life, but he's living it to the max, getting jacked, wakeboarding, and doing UFC. You love to see it. He's he's grinding on. And to end on some really positive awesome news, we got a post from Adam Singer.
Speaker 2:I thought this was amazing. When people talk about the I feel like it's so often about the markets Yeah. Just looking at charts. But this is the folks. We can go on a carnival that's a mini Disneyland on the water.
Speaker 2:Interesting. We got spirits here.
Speaker 1:It's a I
Speaker 2:call it. Planes going Mach 1. We're catching rockets with chopsticks, and it's all out there in the open. We should celebrate it. We're also working on some very cool stuff with Adam Yeah.
Speaker 2:Which we'll announce soon in the AdQuick team. Mhmm. But look. We have, seven minutes until the market's closed.
Speaker 1:K.
Speaker 2:Let's do it. Just got the notification from public. So Cool. That's our time to, call it for today, and I cannot wait for Monday.
Speaker 1:Yeah. So thanks for watching. Go leave us a 5 star review on Apple Podcasts and Spotify. Please do both. Leave an ad in your review.
Speaker 1:Leave us 5 stars
Speaker 2:2 ads that way.
Speaker 1:And stay tuned for the next 1. We'll see you Monday. Thank you, folks. Bye.