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Technology's daily show (formerly the Technology Brothers Podcast). Streaming live on X and YouTube from 11 - 2 PM PST Monday - Friday. Available on X, Apple, Spotify, and YouTube.
You're watching TBPN. Today is Monday, 04/21/2025. We are live from the Temple Of Technology, the Fortress Of Finance, the capital of capital, the institute of iron. The Hall Of Hypertrophy. We wanted to kick it off with a post from my good friend Sahil Bloom.
Speaker 1:He's been on the show before as we highlighted his book, but this one hit hard, especially today. He says, here's the truth. If you're half in, you're actually all out. Even 90% in gets you nowhere. There's something magical in the last little bit simply because so few are willing to do it.
Speaker 1:That's where you unlock new levels to the game, and it does not take talent, just courage.
Speaker 2:Well, you're certainly being courageous today, John. Thank you. Congratulations.
Speaker 1:Yeah. Big news. I'm all in on TBPN. I am entirely in. I'm completely in TBPN.
Speaker 1:Full time. The announcement went out today. Fantastic experience as an entrepreneur in residence at Founders Fund. It was a great two year, two
Speaker 2:year Incredible run.
Speaker 1:Run. Incredible run. Fantastic team over there. They're really gonna be suffering. They're they're they're they're just kicking off a new $4,000,000,000 fund.
Speaker 1:It's gonna be rough. But, you know, I think they'll be I think they'll be okay.
Speaker 2:Management fees on a $4,000,000,000 fund should maybe be able to find a replacement
Speaker 1:Yeah. EIR. Yep. Yep. For sure.
Speaker 1:For sure. But honestly, I mean, fantastic team over there. Founder mode. Founder mode. Super close with everyone.
Speaker 1:And of course, we have Delian as a regular on the show Trey is coming back. He's gonna be one of our first in person guests soon. We're getting Scott Nolan talking about general matter soon. So, obviously, the teal bucks will still be flowing. We're not getting paid directly by Founders Fund anymore, but we are getting paid by Ramp, our sponsor, and one of a major Founders Fund position.
Speaker 1:That's right. So it's all one hand washes the other over here in tech media. Remember, we are 100% corporate backed. That's right. We'll never ask you for a dime.
Speaker 1:And, yeah. So, if you're a company and you want to sponsor us, hit us up because
Speaker 2:That's right.
Speaker 1:We we love our sponsors. Anyway, speaking of sponsors, the market's in turmoil. If you're trying to get in on the action, head over to public.com, investing for those who take it seriously. They have multi asset investing, industry leading yields, and they're trusted by millions. The big news today, stock market is Mogged.
Speaker 1:Absolutely mogged as the trade war escalates. Global markets tumbled amid renewed US China trade tensions and an unprecedented clash between president Trump and the Federal Reserve. Now there's a rumor that, president Trump threatened further tariffs on China and even raised the possibility of firing Fed chair Jerome Powell alarming markets. I'm
Speaker 2:sure We'd have to have a very long moment of silence for Jerome if that were
Speaker 1:to happen. Apparently, the the the the the rumor, going around in the media is that, the administration reportedly explored options to fire Powell after Trump lambasted the Fed, spurring fears about Fed independence. And so, yeah, the Fed is supposed to be independent.
Speaker 2:We we definitely don't we don't comment on
Speaker 1:politics, but
Speaker 2:it really is funny to, you know, come out, with this tariff strategy Yep. And then be, like, looking for somebody to fire Yep. Who's important. Yep. And, like, fire the guy who's like, what did I do?
Speaker 1:Yep. And so the Fed has the ability to lower interest rates when they're doing, I think, new auctions. But they aren't always doing new auctions. We talked about this with a buddy of ours who said that the Fed actually has not that much control over the long end of the yield curve be and they try and do different things to, yeah, the ten year is, like, the really important signal. That's the one
Speaker 2:that you're to finesse it.
Speaker 3:You can
Speaker 1:try to
Speaker 2:finesse it. Gonna do its thing.
Speaker 1:It's gonna kinda do its thing, and that's the that's the economic indicator that a lot of people have been tracking. In fact, some Trump, appointees had said that lowering the tenure was a goal for this administration, and the opposite happened. The tenure rose. That's right. And that means, you know, potentially higher higher higher mortgage rates, less affordability, maybe house prices come down because interest rates go up.
Speaker 1:Sometimes that that happens. But in general, it can be it can lead to a lot of turmoil economically, and it's not where Yep. It it it wasn't the stated position of the of the of the administration. And so now they're maybe looking for someone new to step in to take over and potentially work towards lowering that interest rate. But there's only so much you can do.
Speaker 1:It is a free market.
Speaker 2:S and P 500 and the Dow fell sharply with US stocks down over 10% year to date. This moment of silence.
Speaker 1:Moment of silence.
Speaker 2:This moment of silence is brought to you by Ramp. Go to ramp.com. Tech shares led those losses after companies like Nvidia a warns another war. Export restrictions to China would quote unquote, chisel billions off their sales. We talked about this last week.
Speaker 1:The Nasdaq today alone is down three and a half percent. It's it's a big I mean, it's not 5% like it was a couple weeks ago, but it's not great. They're calling it the sell America trade that picked up back picked back up on Monday. We've been saying this bull market for short selling.
Speaker 2:Bull market for coining? But I would prefer people don't create a coinage around
Speaker 1:sell America. Sell America. No. No.
Speaker 2:No. Don't like that And like it. I like it. But it was the trade over the last few weeks. Yeah.
Speaker 2:There's been a flight to safety. Gold has been on a record run Yep. Which has accelerate accelerated amid the uncertainty. Yep. People are just looking to avoid volatility.
Speaker 2:Bitcoin has also been interesting thing you wanna talk about. Decoupling.
Speaker 1:Yep. No. I I mean, it's it's been like a back and forth narrative because Tyler Winkavoss posted, hey. For the first time, Bitcoin's not trading in lockstep with the market. So the market sold off, and Bitcoin didn't sell off as much.
Speaker 1:Normally, they're highly, highly correlated, which is something that was theorized not to be the case if if Bitcoin really does become this, this asset of last reserve, this store of value, this go this digital gold. But now after looking at the market from, and, of course, he posted that, and immediately, Bitcoin moved in lockstep with the, which is kind of just like it it it's it feels like if you post something, like, very, conviction led like that, you're just gonna get destroyed by whatever market does.
Speaker 2:I think, who's the the partial sports guy? Dave Portnoy
Speaker 1:Dave Portnoy.
Speaker 2:Was posting about Bitcoin. A lot of people, you know, decoupling. Lot of people said it, oh, could be, you know, a sort of bad signal that Dave Portnoy is bullish.
Speaker 1:Yep.
Speaker 2:But Bitcoin's down 7% year to date, but today, it is up almost 2%, which is pretty meaningful.
Speaker 1:You wouldn't expect that given how much the Nasdaq has sold off. Typically, they move in lockstep. So it'll be interesting to keep to to follow that story. We're going to do a whole crypto day on TBPN, bring on a bunch of founders and investors and just general crypto folks and try and get to the bottom of, like, what is cryptocurrency? That's the question I wanna answer.
Speaker 1:Like, I I know it has something to do with, like, numbers and money. But you've never seen it. I've never seen it, so I wanna bring on some experts. We're gonna bring on some people that run public companies, some people that are billionaires, multibillionaires, and we'll ask them, like, what is this whole crypto thing about? And that should be very informative.
Speaker 2:Yeah. For for me,
Speaker 4:at least
Speaker 2:On a more serious note Yes. Interested to see where crypto goes from here. Right? There's been a cool down in the meme coin market.
Speaker 1:Yep. The pump dot fund chaos seems to have subsided.
Speaker 2:Yeah. That We've seen that twice now. We saw this with OpenSea, you know, was doing, I forget, you know, hundreds of millions of of net income a year. I think at its peak, pump fund was doing the same thing. Yep.
Speaker 2:OpenSea's volume fell off a cliff, unfortunately. We'll see what happens.
Speaker 1:They were in my YC batch. We should get them on the show. I'd love to know kind of like they have a lot of money. They have a lot of talent. They're they're clearly planning their next act.
Speaker 1:I wonder what that would be. I think that, you know, a lot of people have written them off, but that might be wrong. Maybe they'll come back and do something else. There's there's so there's clearly opportunity in crypto if you have a lot of money and a lot of, you know, hardcore developers to build something. You can build something entirely But there's
Speaker 2:a possibility that they need to completely reinvent themselves.
Speaker 5:I agree.
Speaker 2:But that can also be a trap. Sometimes the second that, you know, a company reinvents themselves Yep. The the old the thing that they were originally working on rips again.
Speaker 1:Yep.
Speaker 2:So who knows what happens with NFTs.
Speaker 1:Yeah. I mean, NFTs specifically were always one of those things where I was I was willing to to buy the narrative of, like, this is a digital art house. This could be the next Sotheby's. But their valuation was, like, 10 times 10 times what Sotheby's was or something like that very quickly. And so Sure.
Speaker 1:They guarantee being, like, a museum. Like, I think at at the height, like, NFTs were the volume was higher than the fine art market. Well that has hundreds of years of of experience.
Speaker 2:So so two reasons for that. One, same thing happens in the art world where if you discover an artist Mhmm. And you buy up their works before they Yep. Get into Sotheby's and and these big auctions and galleries, etcetera, you can buy incredible pieces of art for thousands, you know, single digit thousands. And then the second, the reason for the volume is that it's very hard to have a, you know, $200,000 piece of art change hands six times in a day.
Speaker 2:Yep. But that was happening with Cryptopunks. That was happening with, you know, Bored Apes and many many many many other projects. So
Speaker 1:Oh, well. Well, let's move on to the legacy of Pope Francis. He passed away, I believe, this morning. In fact Yeah.
Speaker 2:It was interesting. It was
Speaker 1:so sudden that The Wall Street Journal, the print edition, does not mention his passing away. It mentions that yesterday, thousands in Saint Peter's Square on Sunday were treated to a surprise Popemobile trip, drawing cheers and applause as Pope Francis continues his recovery from double pneumonia. He also met with president vice president J. D. Vance.
Speaker 1:And this was getting me emotional because, like it's pretty, I mean, I don't know that this is the case, but it feels like they did this because he knew that he was maybe not going to make it very much longer. So Potentially, yeah. It was like his last opportunity to go and see everyone and it's just brave. I don't know. It's it's beautiful.
Speaker 1:Anyway, The Wall Street Journal has an has an, an obituary, of course, and I think we should read through a little bit of it and give some background on who this man was. So he was elected the '20 two hundred and sixty sixth pope in 2013, and it marked a series of firsts. He was the first Jesuit pope and as an Argentine, the first from outside Europe. His legacy as pope Francis who died on Easter Monday, at age 88 was disappointing even on the priorities he set for his papacy. Pope Francis was known for urging concern for the poor in the best Christian tradition.
Speaker 1:He called for a clergy of shepherds who have the smell of their sheep. Interesting metaphor. That is priests and nuns who shared the suffering of their neighbors. He made support for the weakest among us the rhetorical centerpiece of his papacy. He brought a public informality and openness to the Vatican.
Speaker 1:Alas, Pope Francis believed ideologies that kept that keep the poor in poverty. One of those earthly dogmas is radical environmentalism, which isn't about keeping the earth clean for human beings, but keeping the earth itself and treating man as the enemy. Interesting. So the Wall Street Journal is kind of coming for him a little bit on this, saying he shouldn't have been as much of an environmentalist as he was, which is interesting how how much the vibe has shifted. And we'll see where this goes the next with the next pope.
Speaker 1:In one of his writings as pope, he cited air conditioning as an example of harmful habits of consumption that will lead to mankind's self destruction. He didn't seem to realize that escaping poverty requires greater energy consumption, which is something we've we've touched on with a lot of the founders on the show. Obviously, Augustus Dorico is is religious, but then also says that, you know, it is it is our job as as stewards to terraform and make the make make the planet safer and healthier
Speaker 2:for all lot of evidence that if you enable humans to live in cooler climates, even just indoors Yep. That can, you know, be quite positive for health. Yeah. Yeah.
Speaker 1:His papacy was marked by anti Americanism and not merely against Donald Trump. He seemed to believe that Latin America is poor because The United States is rich. That's a recipe for stagnation and despair because the real reasons so many in Latin America languish in poverty are at home, lack of rule of law, business government collusion, protectionism, other barriers to human flourishing. Some attribute his hostility of free markets to his Latin American background. Born in Buenos Aires, Pope Francis at a young age was made the provincial the provincial superior for the Jesuit order in Argentina during the time of the military junta.
Speaker 1:This was a hard line to walk, and some of some of his order accused him of unfairly being too friendly with the regime. Argentina, for much of his life, was dominated by Peronism, a brand of left wing populism named for Argentine president Juan Peron. When he looked around, he saw corruption and the rich doing very well as their fellow countrymen languished in poverty. Perhaps it was undeniable that he confused Argentini Argentina's Corporatism with capitalism, which is a common mistake. It makes it makes a lot of sense.
Speaker 1:Less forgivable was his deal with Beijing as the pope that gave the Communist Party influence in the choice of bishops. Conditions for Catholics in China have worsened, though the Vatican has renewed the kowtow several times. The Vatican has stayed silent on the plight of publisher Jimmy Lai, who is China's best known imprisoned Catholic. Unlike his two immediate predecessors, John Paul the second and and Benedict, Pope Francis was from the progressive wing of his church. He punished, traditionalist bishops who disagreed with his direction, and he has populated the cardinal ranks with fellow progressives.
Speaker 1:The irony is that progressivism is most popular in places like Europe where the Sunday pews are empty. The church is thriving in Africa among younger younger Orthodox Catholics in the West, and among younger Orthodox Catholics in the West looking for meaning in life beyond material consumption. The cardinal who will choose the pope's successor will determine which future they want for the church and the world's 1,300,000,000 Catholics. Fascinating. Yeah.
Speaker 1:Interesting to see the Wall Street Journal kind of wrestle with his legacy in a in a in a tasteful but critical way. That was interesting.
Speaker 2:One thing that he did is he got the Popemobile. He did? To go electric.
Speaker 1:Wait, really? He saw the electric That's a g electric g wagon?
Speaker 2:It's an electric g wagon. So it's
Speaker 1:No way.
Speaker 2:The car that he was in yesterday for
Speaker 1:I had no idea. Because there there is a new there is a new g wagon that's electric, but they
Speaker 2:they electrified old g They're using the G five eighty base.
Speaker 1:Really?
Speaker 2:Which makes a lot of sense. You're in crowds. Yeah. Let's not, you know, omit
Speaker 1:Let's flex on everyone with our G Wagons. Is that what you're saying?
Speaker 2:That wasn't what I was saying, but
Speaker 1:Yeah. Being
Speaker 2:electric makes
Speaker 1:lot of sense.
Speaker 2:But The new of course,
Speaker 1:were a
Speaker 2:lot of memes because JD JD Yeah.
Speaker 1:Saw him right before.
Speaker 2:Had a visit yesterday.
Speaker 1:Again, it makes sense if the pope is sick, wanna go visit him before he's sick. Anyone saying anything else is is being a little silly in my opinion.
Speaker 2:Put on the tinfoil hat.
Speaker 1:Put on the tinfoil hat. Anyway, there was an interesting article, an an op ed by Roland Fryer in The Wall Street Journal that I wanna go through, the economics of polarization. Are you familiar with Roland Fryer? No. Fascinating.
Speaker 1:So he's an economics professor at Harvard. Very outspoken, very, he's been a little controversial. There's like a, there's a back and forth. He was kind of attacked. But he came up with a bunch of behavioral economics kind of foundational research.
Speaker 1:One of the most controversial things was that you should pay kids to do their homework. So basically, like, an economy for children. Yeah. But but he but he studied it and found that, it was like one of the greatest motivators, just paying kids to to do work.
Speaker 2:It makes so much sense. Would you not want to drill into a child's head that if you work hard, you will be rewarded?
Speaker 1:Yeah. Totally.
Speaker 2:Because that's sort of the lesson Yeah.
Speaker 3:Of life.
Speaker 1:Yeah. Yeah. No. A %. Hundred %.
Speaker 2:My This started mowing lawns, picking weeds around.
Speaker 1:Yeah, I was listening to Palmer Lucky on Tetragrammaton with Rick Rubin yesterday and he was saying that he built like the largest collection of VR headsets and then he also built a massive gaming rig with six monitors and top tier computer hardware. And then that's what inspired him to go into VR and start Oculus. And I was just and he was like, yeah. And I paid for all this, like, doing, like, little odd jobs and, like, side hustles as, like, a kid. And I was like, yeah.
Speaker 1:But I'm running the math. And I'm like, if you're spending if you're spending, like, $40,000, like, you're pretty good at those side hustles, Palmer. Like like, you were working hard. Like Yeah. Yeah.
Speaker 1:Yeah. It's very different than
Speaker 2:like white hat hacking
Speaker 1:Totally. Things like that. I don't even know if it's that. Think anybody just had like a like a true grind size for like not just mowing lawns, but like mowing a lot of lawns. Because most kids, you know, if they have like a side job, it's like $200 a month or something.
Speaker 1:It's not it's it's not enough to get you to like a $20,000 investment in like a gaming PC very quickly. Yeah. Like for me, it was mostly like make some money and then go buy like a single video game for $50. Or some candy. Some candy.
Speaker 1:Exactly. This is the usual stuff. But it seemed like Palmer really got the economic flywheel going.
Speaker 2:At early age.
Speaker 1:But it makes sense because, like, he's very entrepreneurial. It would make sense that he'd he'd be making a lot of money. Anyway, Roland Fryer, just published some research on the economics of polarization that I think is fascinating. There's this big question about, you know, America seems more polarized than ever. What is driving that?
Speaker 1:And, the the the the subhead here is people tend to interpret ambiguous information as confirming whatever they believed to begin with. And so, we'll we'll read some of this article and and go through it, but it's, it's interesting to see, like, where else will this take place and where else can this potentially be exploited or or or mitigated depending on your your goals, I suppose. So nothing throws America's divisions into stark relief quite like having Donald Trump in the White House. But mister Trump is an effective but mister Trump is an effective polarization as much as a cause. We've been growing apart politically for decades.
Speaker 1:And so he gives some data to kind of back up this claim that, the political division in America is not driven necessarily by Trump. Trump is like a product of it. So he says
Speaker 2:And a catalyst in many ways because he's Totally. Extreme.
Speaker 1:Yes. Right? Yes. Totally. And so, nowadays, 85 of Democrats, but only 30% of Republicans think the government should ensure that everyone has health care.
Speaker 1:So health care used to be a little bit more bipartisan. That, it the the gap has grown 24 points during the last two decades. Then there's some other stats here. The government has too much power when they poll people on that. 73% of Republicans say, yes.
Speaker 1:The government has too much power. Only 31% of Democrats say, the government has too much power, and it's a 51 shift. In fact, during the George w Bush administration, Democrats were more likely to say that the government has too much power. And then there the the split on whether abortion should be legalized team's has power. Points.
Speaker 1:Yep.
Speaker 2:The other team has too much power.
Speaker 1:Yep. Yep.
Speaker 2:Which I agree with.
Speaker 1:Yeah. Yes. Yes. Yeah. 100% of people agree that they don't have enough power, I think.
Speaker 1:And then, on global warming, the split is 33 points. On abortion, it's 30 points. And so, lawmakers have also become more polarized over the last fifty years, and there's even polarization over why this happened. Some data suggest Republican politicians pulled to the right, but conservative notes that the but conservatives note that the government has moved sharply to the left. And so, 52% of Americans said that Democrats had moved too far left, while 35% said the Republicans had moved too far right.
Speaker 1:And so everyone is saying, oh, the Overton window is shifting. I haven't changed. Everyone else has changed. It's a very common refrain. Even seemingly nonpartisan measures such as the consumer sentiment index reveal polarization, Republicans had more positive views than Democrats about their economic situation during the first Trump term, and then this flipped in 2021.
Speaker 1:So they're like, oh, yeah. Like, I'm doing pretty well economically. Like, I got a job. Inflation's not too bad. And then in 2021, they're like they're they're like, oh, like, it's terrible.
Speaker 1:Of course, like, COVID's in there. There was really inflation. There was stimulus. All sorts of stuff happened. But, of course, people are more likely to report that, like, you know, I'm doing better if my guys in the big in the big house in the White House.
Speaker 1:How can two people observe the same information and come away with starkly different conclusions, and why do views on factual questions such as the cause of global warming or the strength of the economy break down so neatly on ideological lines? And so Roland Fryer tells this anecdote about, his wife and how this this, like, inspired him to run this test, essentially. So he says his wife is a great driver, but she blows the horn way too much for his taste, which is hilarious. So any slight perceived or real, and you get a loud honk if she is behind the wheel. One morning when we were commuting, a car pulled pulled past her on the highway and veered just slightly our way so that its tires drifted into our lane.
Speaker 1:She honked. I tried to reason with her. His driving was within the usual margin of error. What an economist thing to say. It's like, this is this is totally within one standard deviation of driving abilities.
Speaker 1:Like, you shouldn't you shouldn't be honking. Yeah.
Speaker 2:Could be a lot
Speaker 1:Yeah.
Speaker 2:In certain circumstances.
Speaker 1:So her response, she says, I've kept myself from many, many accidents by being a proactive hunker. And so Mhmm. They observed he says, we observed the same incident, but we drew opposite conclusions and each became more convinced we'd been right all along. Is this consistent with rational thought, and could it explain why Americans have become so polarized? As soon as she dropped me off on campus, I ran to my office to tell a fellow economist this anomaly I had observed.
Speaker 1:Was my wife irrational? Was I? Or did we need to think about inference and decision making a bit differently? I first confided in Matthew Jackson who specializes in social networks. He seemed as perplexed as I was because he knows my wife.
Speaker 1:He offered up several interpretations that would make her seem more rational. Finally, he relented, and it became one of the guiding examples for us to think differently about how humans process information when there is uncertainty. In the simplest version of the model they deployed, imagine that the truth is either a or b. Climate change either is or is not caused by human activity. There's no gray area in between.
Speaker 1:The death penalty either deters crime or it doesn't. No one really knows the truth, but we start with a prior belief about how plausible a or b seem. Each person observes a series of signals, information that's that suggests the truth might be a or b. Some signals are ambiguous and come off as a b rather than a or b. If you were fully rational, able to set aside prior beliefs, you'd store the information in a sequence.
Speaker 1:A b, a b, a b, a, a, a, b, b, like that. So Yeah. So when there's a confusing signal, you just think it's both. But and and if you add that up, that sequence that he describes, it's three points for a, three points for b, and three ambiguous signals. Like, the signal doesn't doesn't lean one way or the other.
Speaker 1:But if you tend to align unclear evidence with your previous expectation, you would come away thinking your original instincts were right because you'd you'd count all the AB signals as A if you're on, like, team A originally. And so now you think the evidence falls on your side by a two to one margin. So you would count up six As, you would ignore the three Bs in the ABs, and you would have three Bs. So you'd be saying, hey. Six to three.
Speaker 1:I'm seeing a pattern here. Further observations of the world entrench this view rather than correcting it because future ambiguous signals will have the same skew. Our our main mathematical result demonstrates that if a large enough share of experiences are open to interpretation, maybe the guy who drifts into your lane until you honk is an example of the horn saving lives, or maybe you're an average he's an average driver who never posed a threat, then two agents who have differing prior beliefs who see the exact same sequence of events can often end up polarized with one person being absolutely sure of a and the other of b. And so they they ran an experiment online with 600 subjects modeled on a 1979 paper by Charles G. Lord.
Speaker 1:First, present precipitants were presented with questions about their beliefs on climate change and the death penalty. They read a series of summaries of research about each topic. After each summary, we asked participants if they thought the summary provided evidence for or against the topic on a 16 scale. After all the summaries were presented, we repeated the initial questions about their belief about on the topic. There was a very significant correlation between a subject's prior belief and his interpretation of the evidence.
Speaker 1:More than half of our sample exited our experiment with more extreme beliefs than at the start, even though the evidence presented to them was neutral. That is wild. The discouraging implication is that in a world where information is plentiful, people will become more divided, not less. That is true, even if they all see the same information, which they don't because they can choose between Fox News or MSNBC. And it's true even if our widening divisions prove deeply unhealthy for our country.
Speaker 1:And that's why you gotta turn off Fox News, you gotta turn off MSNBC, and you gotta only watch TBPN. That's That's the only option. But there's so much to talk about here.
Speaker 2:And we promise to validate your preexisting beliefs
Speaker 1:Yes.
Speaker 2:With data.
Speaker 1:Absolutely. Absolutely. I thought this was interesting because this goes back to the debate around Facebook. So when there was increasing political polarization, it was kind of blamed on Facebook for funneling people into extreme echo chambers. Right?
Speaker 1:They called them what were they called? I forget. I I I forget the name. There was like some buzzword for this for this like, you go down like a rabbit hole on YouTube and you start with like
Speaker 2:And this was pre algo feeds even in the way they are today. There Yeah. There of course, there were algorithms that would decide what content to serve you, but it wasn't it was still heavily based on the social graph
Speaker 1:Filter the following the term I'm
Speaker 2:looking for.
Speaker 1:Filter Filter bubble. And so you would search for, like, you you you would start to search like, you know, what to do after college? How do I get a job? And then you would land on, you know, a Jordan Peterson video that was just, you know, about how to live your life, make your bed, right? But then Jordan Peterson also had conservative views.
Speaker 1:And so you would go from the general life advice into his conservative views. But and then he's not really that extreme, but then there'd be someone else who was recommended who was like just political, less life advice
Speaker 2:Yeah.
Speaker 1:And a little bit more extreme, and then a little bit more extreme.
Speaker 2:Make your bed with an American flag. Exactly.
Speaker 1:And and and so people would go down these these filter bubbles, and then pretty soon, everything they would be seeing was there. Yeah. Zuck made the argument that, you know, we haven't seen political polarization in other countries where Facebook is very active. And so he was saying, maybe this is more of a reflection on America than than Facebook as a product because the usage data is really high. I think his example was like Malaysia or Indonesia or something, and and their and their society wasn't as polarized as America.
Speaker 1:Yeah. But I think it's interesting that that that that it's merely it's potentially merely the the explosion of information that creates division. And if you if you're just exposed to if you're literally living in a cave, you're less part isan. Like, it's kind of it's kind of interesting. Yeah.
Speaker 1:So I yeah. I mean, I I I don't really know where where all this goes. Like, does it exonerate Facebook and the social media platforms entirely? Clearly, there are some platforms that are, like, extremely skewed and biased. That's kind of by design almost.
Speaker 1:Yeah. But it's interesting to dig into, at the very least, you as an individual need to understand if you're interpreting those a b signals, those new those those neutral evidence points as
Speaker 2:I think it also
Speaker 1:adding to your side.
Speaker 2:I think it also applies to the last few weeks with the tariffs. Right? Yep. People are like, oh, treasuries are selling off. Oh, gold is gold is ripping.
Speaker 2:Bitcoin is ripping. And everybody's seeing sort of the same set of information but applying different beliefs to it. Somebody might say, you know, gold is ripping, you know, people are, you know, basically shorting the dollar. They're short the dollar. They're short America, so they're buying gold.
Speaker 2:Yet, every financial crisis for the most part, people tend to buy gold because it's seen as, you know, more stable and and predictable and and a true store of value.
Speaker 1:Yeah.
Speaker 2:Same thing with with treasury selling off. It's like, okay, if you're in a trade war and there's this complex geopolitical, you know, dynamic and t bill yields are are ripping Mhmm. Because foreign governments are selling them. Well, there there could be a lot of other reasons other than purely just sell America. America's over, the dollar's done, that kind of And so, yeah, it's
Speaker 1:It's hard to yeah. It's hard to balance all the different signals. But if you're looking to get in on the action with some gold, why don't you buy a gold watch on Besra? Go to getvesra.com. Download the app.
Speaker 1:Pick up a Rolex Day Date.
Speaker 2:A lot of people think, oh, I should buy gold. Yeah. I'm gonna go get some gold bars.
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Speaker 2:Not financial advice.
Speaker 1:Not financial advice, but Truly. Truly. Speaking of things that are somewhat related to fashion, robots are having trouble making Nike sneakers. This is an interesting story in the context of like re industrialization. Trey Stevens had a art has a piece on Pirate Wires all about the importance of robotics and automation in the reindustrialization story that we should go through or talk to him about.
Speaker 1:But I thought this was an interesting, interesting discussion of, like, okay, if the tariffs are here to stay and we are trying to boost US manufacturing, what what can we learn from Nike's move to Asia historically? And so Yeah. Trump is betting that the tariff the threat of tariffs in on low cost countries in Asia will pressure American companies to bring back manufacturing and jobs to The United States. But high US labor costs mean companies would have to find a way to replace human workers with machines. For some industries, that's proved surprisingly difficult.
Speaker 1:Indeed, a years long effort by Nike to shift part of its manufacturing from China, Indonesia, and Vietnam to North America illustrates how tough it is for US brands to wean themselves off of the flexible low cost contract manufacturers that use armies of laborers to churn out an array of products for consumers. Yeah, I mean, of the interesting things about the push in Foxconn where they bring in a million migrant is that you can't really do that with robots. Like the CapEx, there's no fungible flow of robotics yet that you could say,
Speaker 2:hey, we just Yeah, can imagine a world in the future where you bring in a hundred thousand on demand robots for a, you know, a a sprint Yep. A seasonal sprint. But that world also feels
Speaker 1:Pretty far.
Speaker 2:Ten, fifteen years away. Right? It's hard to imagine it happening in
Speaker 1:Yeah.
Speaker 2:Three years, right, or on the timeline that the tariffs are on, which is the most pressing issue.
Speaker 1:Yeah, yeah, yeah. It's not something that a company can think like, Okay, these tariffs are going to affect our Q3 results. How do we automate everything? So this this actually started a decade ago, and it feels like we're still a few decades out from the robotics automation of, footwear manufacturing. But back in 2015, Nike poured millions of dollars into an ambitious effort to partly automate what has always been a highly labor intensive industry that's making shoes.
Speaker 1:At the time, rising labor costs in China and advances in manufacturing techniques such as three d printing opened the possibility of finding a new way to make shoes that would rely on fewer workers. Have you have you ever seen Zellerfeld? It's a three d printed shoe We showed the CEO on. I've I've met him at a at a party once. Seemed like a good, and I think the company's doing very well.
Speaker 1:But they've but they've been, obviously, like, small because they're a startup. But it'll be interesting to see about where where he thinks that will go.
Speaker 2:Yeah. But this is interesting because even as far back as 2015, Nike won was trying to think about bringing production back to North America Yeah. Localizing it, And it hasn't exactly panned out.
Speaker 1:Yep. Yep.
Speaker 2:Which puts them in a tough position. Right? Because they're like, hey, we're getting tariffed and we've also been made a good faith effort to do this and it didn't pan out. Yeah. Now here we are kind of stuck between a rock and a hard place.
Speaker 1:Yeah. So, the the shoe Nike partnered with this company called Flex, an American manufacturer that helped Apple set up a complex factory in Texas to make Mac Pros. That's the one that there was that picture of Donald Trump cutting the ribbon. The goal was to make tens of millions of Nike sneakers at a new high-tech manger manufacturing site in Guadalajara, Mexico by 2023. The plant would still include thousands of workers, but far fewer than are needed in Asia to make the same number of sneakers.
Speaker 1:If successful, the project could be a model for production in The United States according to some involved in the effort. Nike's competitors also sense an opportunity to rethink manufacturing built around massive Asian factories where armies of cheap skilled laborers stitch fabrics and glue soles to shoes on hand. It feels less modern, more like a Ford Model t production line combined with a Middle Ages cobbler's bench, said Kevin Haley, the executive vice president of innovation at clothing maker Under Armour in 2015. He pledged to use automation to make shoes in Baltimore in a project he called Project Glory. Love it.
Speaker 1:Good name. But, you know, it's rough. Adidas also got in the action. They launched speed factories in Atlanta and Germany with high-tech manufacturing that's quickly spit out shoes, heralding a new era in footwear creation. They wanna move out of China and Vietnam.
Speaker 1:They have the technology to do that differently, said Mike Dennison, Flex's then president in 2016. Nike's effort was the boldest. The company aimed for large scale automated production on under a decade, which it said would save on labor costs and allow it to deliver new models of shoes to Americans faster. Tom Fletcher, who oversaw the project for Flex, came into the effort feeling confident having just built a highly complex Mac Pro factory for Apple in Austin, Texas. You would think that making shoes would be easier than making Mac Pros, and yet they ran into some trouble.
Speaker 1:At the time, Apple had been looking to bring some manufacturing home. Flex pushed to rejigger production lines and use automation, trying to find as many ways as possible to minimize human interaction. That experience came in handy. Tory?
Speaker 2:No. It's just interesting. Flex has not exactly performed despite despite the boost in interest in localized manufacturing
Speaker 1:Are you looking at the stock?
Speaker 2:Yeah. They're they're they're
Speaker 1:How big is the company?
Speaker 2:Very large company already. That's 30,000,000,000.
Speaker 1:30 billion.
Speaker 2:I'm guessing one of 30,000,000,000 of revenue. I'm guessing one of the reasons for this is I bet their supply chain yep. They're they're they've still got despite, you know, making efforts to help onshore, they have quite a bit of exposure to Asia.
Speaker 1:Everyone does these days. If you dig deep enough, you're gonna find some some tariffed goods in your supply chain no matter who you are. So the machines were supposed to build the upper part of the shoe, knit fabric and add logos and glue the sole. I I talked to somebody who was doing some outsourcing of the upper in China, went over there while the tariffs were there. Yeah.
Speaker 1:Very chaotic. And, yeah, just like a very a very rough go, big culture clash moment. And so these efforts ran into trouble. The robots struggled to handle the soft, squishy, and stretchy parts that are integral to shoemaking. Shoe fabrics also expand and contract depending on the temperature.
Speaker 1:While in shoemaking no two soles are exactly alike. So, yeah, I mean, if you consider, like, the benefit of automation on a car production line is that, like, some of these parts are too heavy for people to lift, so you have to use a machine. And then it's the same it's the same stamped, metal every single time. And it's dangerous and it's also just the exact same way. And then there's also welding going on.
Speaker 1:And shoes are much smaller and more fine grained and then obviously
Speaker 2:more malleable. Yeah. It it everything about making electronics is about perfect precision. Yep. Right?
Speaker 2:It's making sure that, you know, a a component has a specific spot within a device Yep. And you need make sure that it goes there. Yep. That
Speaker 1:actually You kinda don't want a human on that.
Speaker 2:Yeah. You can imagine that that being harder for a human to do very consistently. Yeah. Consistently. But if it means like, hey, we need to put, you know, this string in in this hole and then that hole and over here feels very difficult for a robot to do, you know, entirely reliably.
Speaker 2:Yeah. All these things all these things always sound trivial. Yep. Hey, we're going to make a robot that makes shoes.
Speaker 1:It sounds so easy, honestly.
Speaker 2:Yeah. It doesn't sound it doesn't sound as hard as it is in practice. Right? That you have Nike doing
Speaker 1:I think it's I I I would imagine that Crocs are fairly automated because it's kind of
Speaker 2:just like pour three d printing.
Speaker 1:Yeah. Pour the the the polymer in a mold Yeah. And you're good. Just kind of like, you know, melt it together. But for something as complex as a Nike shoe that has a sole, a logo sewn on, there's I mean, even even just lacing a shoe, like, that is incredibly difficult That's what I'm saying.
Speaker 1:Task for a robot. Right? And they come laced. Like Yeah. Like, the you have to poke those through.
Speaker 1:It's hard for me sometimes.
Speaker 2:Shoes don't lace themselves.
Speaker 1:No. You're trying to do something very precise, and then it gets a little colder or warmer and the mature and the material changes on you. We did not anticipate that. As a result, factory production never became as automated as envisioned. Production increased, the factory personnel swelled to 5,000, about twice as many as originally planned and costing more than a similar workforce in Vietnam.
Speaker 1:Task after task proved challenging to automate, like the delicate work of gluing soles to the upper part of the shoe. If you didn't lay it the right way, there would be a noticeable twist of the shoe, a misalignment that aesthetically means it would fail quality tests. A central product was also the huge variety of shoes Nike produces. For decades, American consumer companies have given designers nearly unlimited freedom to dream up the coolest products and relied on Asian manufacturers to deliver them. And unlike cars or iPhones, shoe models are changing all the time.
Speaker 1:Yeah. Mean, you think about some of the, like the How It's Made episodes that clearly are heavily automated, it's very much stuff like, you know, even like food manufacturing. It's like every Cheeto is gonna be the same. They're just gonna go in like slightly different sized bags. And you can just imagine, you know, all that going down a conveyor belt.
Speaker 1:A little bit trickier when you're assembling a shoe where, you know, they're all different sizes. Yeah. I mean, we talked about all the
Speaker 2:options. Right?
Speaker 1:It's crazy. It's
Speaker 2:plastic bag Yeah. And then something needs to go in it Yep. Fill it up, and it moves down. Yep. It's like far more easy than a shoe which has I mean I bet the average Nike shoe has
Speaker 1:I mean, sell a lot of individual components. Yeah. They sell a lot of them. But when you think about the SKU complexity, I mean, what are they? Like, 20 different sizes of men's shoes just for a vanilla run if you just wanna be able to reach everyone from, like, a size four to a size fourteen something.
Speaker 1:Like, you're you're in
Speaker 2:a very custom typically 23 parts to a shoe.
Speaker 1:23 parts to shoe. Each one of those needs to be different for the size. Color
Speaker 2:lining top.
Speaker 1:And the color needs
Speaker 2:to be eyelet, quarter, quarter over And the materials. Lamp, outsoles, tip, laces, swoosh.
Speaker 1:Wow. It's like a miracle that these even exist, honestly. Yeah.
Speaker 2:And then the sizing thing you were talking about, it's like, great. You get it working for one size. Is it gonna work when you need to do
Speaker 1:The next size. Triple XL or yeah. Size fifteen. Feet. Okay.
Speaker 1:It's fine. It's no big deal. So automating manufacturing means designing simple products that machines can undertake over and over. Electronics manufacturing uses hard, standardized materials, as you mentioned, allowing machines to replicate the same step millions of times. You'll have to make sacrifices from how to design the to the complexity of the materials and models you work with, says the former Nike executive who oversaw the project.
Speaker 1:That goes against what the consumer wants. They want an incredible diversity of product. And, we I mean, we see this in cars. Like, the the the Tesla Model three, Model s, like, they look very similar. Even the y and the x look very similar.
Speaker 1:They often come in the same colors. There aren't that many you don't really see that many with, like, oh, this one has fender flares. This one has wings on it. Like, all that stuff would be completely aftermarket. It doesn't come from the factory that way.
Speaker 1:Yeah. Versus, you know, a more a more mature company like Mercedes sells like like a wagon version of the of the e e four Right? The e 63. They also sell convertibles of the c series. They sell long wheel based versions.
Speaker 1:They sell SUV cars. Electric versions. So For
Speaker 2:example, the the q eight is the same as the Cayenne. Yep. It's the same as the Urus.
Speaker 1:Yeah. Yeah. Same powertrain. Right?
Speaker 2:Volkswagen. Yep. And so it's, basically the same car
Speaker 1:Yep.
Speaker 2:With, a different exterior and a different exhaust and, like,
Speaker 1:sell cars. Want that. Consumers want that. And and so so, I mean, Elon's found a way, and we'll go into the Tesla story later, but Elon's found a way to convince people in mass, at least during the height of the Tesla boom, to, you know, say, hey. Yeah.
Speaker 1:It's gonna look like every other Tesla three, and you're gonna get lost in the parking lot probably, but it has a summon feature. It has the best self driving. It's electric. It's super cheap.
Speaker 2:Found a new way to differentiate.
Speaker 1:Exactly. So it's like these appliance cars. It's like moving it to the iPhone. Nike, if they really wanted to go all in on automation, they should have found a way to make a product that is as ubiquitous as the iPhone with as little standard or as much standardization as Just kidding. Hammered today?
Speaker 1:Hammered down 10%.
Speaker 2:No. 7%. But they're suffering from the trade trade tariffs. Tariffs, but then also
Speaker 1:The lack
Speaker 2:of a naturally aspirated broader tech sell sell off. Yeah. Yeah.
Speaker 1:And, yeah, I mean, still no news about a gated manual. Right? That's right. And so that's gotta hurt
Speaker 2:the stock. We're kind waiting on. That. Ferrari's coming back,
Speaker 1:by the way, with a manual. They're doing a manual V eight.
Speaker 2:Did they name it yet?
Speaker 1:I don't know. No, all they said was that we are committing to a manual ICE, like no hybrid car.
Speaker 2:They heard the vibe shift.
Speaker 1:Well, saw what happened with Porsche. Yeah. Because Porsche launched the ST, which was really great. And then the R, I believe, was was manual as well. And so they said, like, there are certain collectors that just want manual, like, more analog cars, they're willing to pay for them.
Speaker 1:And it makes sense for a Ferrari. They make a ton
Speaker 3:of Yeah.
Speaker 2:I was trying to think about it. I was trying to think, what is the desire a highly desirable car that is a hybrid or electric?
Speaker 1:LaFerrari.
Speaker 2:LaFerrari? I don't think LaFerrari is a hybrid.
Speaker 1:I'm almost positive it is. Is it? Yeah.
Speaker 2:You're right. You're right. Mogged.
Speaker 1:Mogged. Nine eighteen Spider hybrid.
Speaker 2:Yeah. The Spider too.
Speaker 1:Two nine six.
Speaker 2:But
Speaker 1:Hybrid.
Speaker 2:I guess I could have made
Speaker 1:a lot precise decisions in
Speaker 2:the last few years. Right?
Speaker 1:We haven't In the last few years, what? I mean, there's a new nine eleven that has a hybrid. So I think it'll sell pretty well. What else? Who else?
Speaker 1:It is the is the latest w one from McLaren.
Speaker 2:Yeah. Yeah. I'm sure that is.
Speaker 1:That's gotta be hybrid. Right? Every everything's hybrid now. Anyway, let's get back to Nike. At one point, it took the Flex team eight months to figure out how to automate a way to put the Nike swoosh on a shoe, only for Nike to move on to a new shoe line for which the method Nike developed no longer worked.
Speaker 1:So there's just this cadence of like new shoes, have to have new new new styles. They said it would have been easier to mass produce uncomplicated shoes such as ones with a machine knit upper part and matched with simple molded bottoms, but Nike was unwilling to put limits on its design and expected manufacturers to produce whatever new shoes their teams dreamed up. Manufacturing, in a lot of ways, did not have an equal seat at the table. And that's interesting because, obviously, the manufacturing of the iPhone is deeply integrated into the company, and they drive the manufacturing optimization that happens at Foxconn. This is the whole debate about, are they transferring too much IP?
Speaker 1:But you know that you know that the the the iPhone team is thinking about what is available on the camera side, how does that fit in, and then how can they build software on top of that. And that vertical integration has really led Apple to have this integrated approach that creates a fantastic product. Feels like Nike was very much still in the mindset of like,
Speaker 2:let's
Speaker 1:How could we
Speaker 2:design the phone so that it would be insane to not get a case? Oh, what if we made it so the camera, like, primary use cases of the device protrudes across the back so it doesn't sit flat? That is brilliant.
Speaker 1:So by 2017, Flex's investors were balking at rising costs of the company with some questioning why an outfit that makes electronics was involved in shoe production. Flex and Nike wound up the project
Speaker 2:I actually think it's smart. Yeah. It's like, who's done really advanced scaled consumer product manufacturing? Okay. They've done it in electronics.
Speaker 2:Yeah. Probably a better, generally a safe bet.
Speaker 1:Yep. But it
Speaker 2:wasn't safe enough.
Speaker 1:And so Flex and Nike wound up the project by early twenty nineteen. By then, Under Armour had stopped mentioning to its investors Project Glory to make shoes in The United States. That year, Adidas, which had also faced challenges producing complex shoes with robots, said it would close down production in Atlanta and Germany. It shipped its speed factory technology to suppliers in Asia. The three shoemakers stuck with their original offshore locations, Vietnam, China, and Indonesia.
Speaker 1:Even after pandemic era factory shutdowns showed the risk of having such a concentrated note of production. Adidas, Under Armour, and Nike, they are not talking to the journal about this. But, now China, Vietnam, and Indonesia are in Trump's sights. They got they got huge tariffs on them, and, there will be an army. Howard Lutnick, said that the administration wants labor intensive industries to return to The US.
Speaker 1:He actually said that there will be an army of millions and millions of millions and millions of people screwing in little, little screws to make iPhones. He says, we're gonna make them here.
Speaker 2:That's a word for word quote. Word for
Speaker 1:word quote in a recent interview with CBS.
Speaker 2:Alright. I threw my how to make iPhones book in the trash.
Speaker 1:Nope. I need to go take it.
Speaker 2:Try to get it out. Need to
Speaker 1:go find
Speaker 2:the dump that they took it to. Yeah. You gotta get it back.
Speaker 1:The threat of new tariffs is pushing some to ask whether Nike or others will ultimately have to reconsider efforts to automate manufacturing and bring shoe production back to The US. People think it could still be done, although it won't be easy. You need some deep pockets and some patience because it's not gonna happen fast. But, yeah, we'll see.
Speaker 2:You know what aren't patient?
Speaker 1:Who?
Speaker 2:Tariffs. They're hitting They're hitting right now.
Speaker 1:Right now. But if you wanna track the tariffs, head over to Polymarket. I'm sure there's a bunch of great markets on what's happening in the tariff world. And if you're looking to cut costs because of tariffs, head over to RAMP. Time is money.
Speaker 1:Save both. They got easy to use corporate cards, bill payments, accounting, a whole lot more all in one place. Let's move over to the next story. Man versus machine as China shows off humanoid robots in half marathon. It's pretty crazy.
Speaker 1:Somebody came up to
Speaker 2:us in
Speaker 1:the gym this morning and was like, you guys are talking about this. Right? And we were like, oh, I actually hadn't heard this. But, it is in the journal. China the Beijing half marathon featured a road race between humans and 21 different robot models and showed how far robots are from mimicking people.
Speaker 1:Good example of why it's difficult to make shoes. It's also difficult for robots to run-in shoes. Yeah. They're both having trouble. Been saying,
Speaker 2:would like to see a humanoid robot drink 12 beers and play 18 and call it work.
Speaker 1:Exactly. Not happening in this year. Not this Not this
Speaker 2:Not this
Speaker 1:So, the Tian Cancun a humanoid robot, runs across the finish line of a half marathon in Beijing. So let's run through this. Metal asphalt. Metal met asphalt in a ho in a half marathon that featured thousands of human runners and 21 Chinese humanoid robot models. Saturday's road race involving human runners and a score of robots in Beijing has been billed as a showcase of China's cutting edge technology.
Speaker 1:I gotta say this is extremely cool for the robotics industry, and we should be doing this here. I mean, saw this with No.
Speaker 2:I posted do you remember I posted? We need a we need a humanoid x games. Right? I want to see humanoids
Speaker 1:doing Yes. Surfing.
Speaker 2:I want them to see
Speaker 1:Do the three sixty. Do the ten eighty.
Speaker 2:Any, like, athlete that Red Bull sponsors Yes. Humanoid robot companies should be saying, hey, we're gonna get our humanoids to go cliff jumping Yep. To go bungee jumping to, you know, do it, you know, I I wanna see like Yeah. You know
Speaker 1:We we really gotta have the one x the one x founders on, Neo, and a bunch of the other humanoid robotic founders on to talk about, you know, all our crazy ideas and force them to to do it. Big
Speaker 2:wave surfing.
Speaker 1:Big wave surfing. That seems like the Turing test for humanoid robotics because
Speaker 2:If you can get very embodied AGI.
Speaker 1:Also, I mean, I imagine these robots are pretty heavy. Like, you gotta Yeah.
Speaker 4:That's a
Speaker 2:real test. It's a triathlon. Right?
Speaker 1:You swim? Yeah. Swim? You swim? Humanoid robot that swims?
Speaker 2:That's crazy. How's your battery gonna hold up in Good luck. An hour in saltwater?
Speaker 1:Yeah. Yeah. Is a is a honey stinger gonna take you across the finish line? I don't think so. You're gonna be recharging for an hour, robot.
Speaker 1:So it's a 13 mile race, first of its kind.
Speaker 2:The interesting is the size difference. Everybody just assumes humanoids will be, you know, six foot. Yep. They had four foot humanoids
Speaker 1:in there. Four foot humanoids. Okay.
Speaker 2:Guys running around.
Speaker 1:So China has want has said it wants the country to be a world leader in humanoid robots by 2027. They are well on their way based on what I've seen. Chinese authorities have lavish support such as subsidies, talent bonuses, and tax breaks on robotics companies. In reality, the race
Speaker 2:telling me that for the first time.
Speaker 1:They know how to do some central planning over there.
Speaker 2:Yep.
Speaker 1:You know, say what you will about capitalism. But
Speaker 2:back to back
Speaker 1:five year if you look into subsidized industries, there's now their model that seems to be working pretty well. Yep. In reality, the race showed how how both how quickly and smoothly some robots are able to run, but also how far away humanoids are from still being from being able to mimic human activity. Running is a bay very basic ability of human beings, says the chief technology officer of the Beijing Humanoid Robot Innovation Center, which developed one of the robots. China is making a major push to produce more and more sophisticated robots in part to raise the automation level of its factories.
Speaker 1:Oh, they actually put the, they actually put the robot in Skechers. That's really cute.
Speaker 2:It's interesting too. So these weren't autonomous. Right? There's people following behind the robots actually driving Teleoperating basically. Driving them with a joystick joystick.
Speaker 2:Like it's an RC car.
Speaker 5:Yep.
Speaker 2:But still very incredible feat.
Speaker 1:Okay. So the first one the first robot off the mark was the Tian Kung Ultra, five foot nine. Hey.
Speaker 2:There we go.
Speaker 1:Gotta put you on the truth zone. They're not four feet tall.
Speaker 2:No. It's five nine. Six feet. Yeah. Yeah.
Speaker 1:Yeah. Five nine, a hundred and 15 pounds humanoid
Speaker 2:Ideal build.
Speaker 1:Featuring a pitch black head and sporting an orange tank top. Three people accompanied it to help control the robot. The race is the culmination of months of training. They had to navigate the course's flat and hilly roads and maneuver around six left turns and eight right turns according to the organizers. Developers had to train the robots to keep their stability and balance to avoid falling over.
Speaker 1:The organizers initially planned to cut off the race at around three and a half hours, meaning that the minimum average speed was 3.7 miles per hour. Developers said the humanoid robots can typically operate for no more than two hours on a single charge of their batteries. The faster they run, the shorter the distance they can cover. Components and parts could easily break while running, so developers replaced plastic parts with metal and used extra strong but costly materials. One company trained their humanoids by connecting the robot to a fitness machine like metal stand to prevent it from falling.
Speaker 1:Tiankeng Ultra was developed by the Beijing Humanoid Robotic Innovation Center, a research institute also called ex humanoid and formed by robotics firm UBTECH, electronics and electric vehicle maker Xiaomi, and the local Beijing government. It could run an average of six miles an hour and could handle hills, stairs, grass, and sand, set a profile
Speaker 2:on Impressive. Yeah. This is this makes you think there we have a number of American humanoids, Boston Dynamics, One x, Figure, Tesla Optimus. There's a bunch. Right?
Speaker 2:Yep. But we actually should have way, way more. If this is gonna be very important technology, we should have 20 plus, you know I agree. Venture backed companies sort of vying for this. Right?
Speaker 2:They don't all need to raise hundreds of millions or billions of dollars, but it's an area that we should be, you know, probably investing more in.
Speaker 1:And so as they're running the race, Tian Kung Ultra falls down because the battery failed. The robots were allowed to swap batteries, and they changed the battery three times on this particular robot. Wound up finishing the race in, the human male champion completed the race in one hour, two minutes and thirty six seconds. That's pretty fast. Followed by thousands of exhilarated human runners.
Speaker 1:Some were exhausted, resting nearby to catch their breath. After two hours forty minutes and forty two seconds, Tian Kung Ultra was the first robot to reach the finish line. A large crowd of spectators, including government officials was were eagerly awaiting the robots. In the end, only that. Tian Kung Ultra and Little Rascal n two were able to meet the original cutoff time.
Speaker 1:The organizers extended it to four hours and ten minutes so that more robots could finish the race. So the humans still got it, but, I mean, you look at the you look at the trend line here. I think in a couple of years, they're gonna be crushing this. Yep. I I I see no reason why.
Speaker 1:It feels like a lot of it's probably battery technology. Like, maybe they keep swapping the battery, and that's fine. But if they can really find some sort of battery breakthrough, that's going to enable more power. And like running in a straight line and some slight curves here and there, that doesn't seem like as even as much of a challenge as like assembling a Nike shoe. Right?
Speaker 1:It seems pretty simple. So they should be able
Speaker 2:to win this pretty Now, helicopter carrying a bunch of batteries with an extension cord. Extension That humanoid is sprinting.
Speaker 1:Unstoppable for
Speaker 2:sure. 50 miles an hour.
Speaker 1:Unstoppable for sure. Anyway Very impressive. Should we move on to some big funding news? Yeah. Grunz lands valuation around 500,000,000 as supplement startups boom.
Speaker 1:You're familiar with this company. I was less familiar. I saw
Speaker 2:Austin Breese. I'm not super familiar. Yeah. Them a little bit just because I I I had been aware that they had I had heard about their first year numbers and it was kind of unbelievable. Yep.
Speaker 2:Like, was a lot of companies have got to the their gross revenue, I think, in their first year is what best in is the run rate that companies will best in class companies can sometimes get to at the end of their first year, but they actually, like, did it Yep. In that in that year. Wasn't. Yeah.
Speaker 1:So clearly, founder's an absolute dog.
Speaker 2:Yeah. Was it Austin who was talking about just science with it?
Speaker 1:He says, Grunz was the most obvious billion dollar idea hiding in plain sight. AG One is a $600,000,000 revenue business. The founder of Grunz was like, what if I took AG One and put it in a form factor that is easier to consume and doesn't taste like SHIT. Easiest billion dollars anyone will ever make.
Speaker 2:I don't know that I
Speaker 1:I I don't know enough about the company that
Speaker 2:I I mean I can tell
Speaker 1:you me.
Speaker 2:Probably exactly why it's working so little nominative determinism. The founder's name is Chad.
Speaker 1:Okay.
Speaker 2:So that probably has had something to do with the success. But, yeah, the idea of taking
Speaker 1:Is he the points guy or something? People are saying he's like a points guy? I don't know. He says he's founder of Grunz Daily. Previous Stanford GSB.
Speaker 1:He was a summer's partner summer part Summit Partners, and he's on the board of Ruggable, Doctor. Squatch, Brooklyn, and Solo Stove, and Seven Moore. So, like, really, really great scaled up consumer products companies. I've seen the I had a friend who was applying to work at Ruggable and the economics of that business were fantastic. Are you familiar with Ruggable?
Speaker 2:Ruggable is one and then Doctor Squatch is also very under the radar. I think that's gonna be a massive outcome.
Speaker 1:Yeah. I mean, seeing this with the Ridge Wallet guys. Like, there's there's increasingly a divide between like like, good idea gets market attraction, but the real killers come in and optimize the business and just actually get the full value out of the company or or out of the market. So throw in Chad a follow. But let's read through some of the, the information article on this.
Speaker 1:So investors are on a health kick looking for new ways to tap into the fast growing brands in the nutrition sector. This includes pouring money into selling into startups selling supplements, particularly those that offer new ways for people to load up on vitamins, protein, and other ingredients. Latest example is a two year old gummy supplement startup, Grunz, which raised fresh cash at at an up to $500,000,000 valuation in recent weeks. According to people briefed on the deal, their monthly sales were roughly 10,000,000 earlier this year. They recently added kids products as well as a sugar free version of its adult gummies and a fresh influx of cash nearing nearly 10,000,000 according to securities filings.
Speaker 1:Wow. Really low dilution, if that's 10,000,000 on 500 post. Not bad. Not bad.
Speaker 2:They're making they're making plenty of money themselves. Yep. One thing, the American consumer has always been undefeated Undefeated. But is especially undefeated in the context of gummy
Speaker 1:Oh, everyone loves a gummy anyway.
Speaker 2:Gummy Creatine. So many different Gummy Protein. With Create. Yep. I was initially I I talked to Dan Yep.
Speaker 2:Right when he was starting Create and I was a little bit skeptical around kind of the market that he was going for. I'd taken Creatine forever. Yep. But he was the first company that that I'm aware of to put Creatine in gummy format.
Speaker 1:Yep.
Speaker 2:And I talked to him like two months later. It was like so obvious that the the business was was just working phenomenally well. And he's been knocked off a bunch of times since then. But fortunately, there's an interesting thing in the gummy space where there's always been issues with quality in the supplement space. Yeah.
Speaker 2:Dan was talking about that. Specifically in gummies. In creatine.
Speaker 1:I I watched a YouTube video about this separately and then Dan posted about it. How some, you know, mass monster bodybuilding guy tested like 20 of the top Amazon creatine and they really lot
Speaker 2:of them had zero creatine.
Speaker 1:Like, yeah, like point o o o 1% of the label claim is wild.
Speaker 5:Yeah.
Speaker 1:Anyway, I mean, Chad, if you're a real Chad and you're serious about growing this business, get on Numeral. Go to Numeral HQ sales tax on autopilot. You know you're gonna have to be paying sales tax on this stuff all over America. You can spend less than five minutes on per month on sales tax compliance.
Speaker 2:That's right.
Speaker 1:Anyway, I wanna keep digging into this a little bit, and then we'll move on to the next story. So they have other hot brands include Create Wellness. That's our BOY, a line of creatine gummies, which tapped into the muscle building supplements growing popularity on social media to raise 5,000,000 in series a funding last fall. The brand has launched in retailers and is on pace for around 25,000,000 in annual revenue when it raised fresh cash. Let's hear it for Create Gummies.
Speaker 1:Damn. Good job. The rise in popularity of weight loss drugs is also providing a
Speaker 2:marketing
Speaker 1:tool. Too. Unilever's in the What's the, Oh, oh, it was in that deal?
Speaker 2:Yeah.
Speaker 1:Oh, that's awesome. With brands claiming they enhance weight loss or pro or help with side effects of the drugs. Gruens, for instance, has run digital ads.
Speaker 2:I had to just look that up. I thought I was leaking. Yeah. He he did announce it last year.
Speaker 1:Oh, good. Good. I was
Speaker 2:like, wow. I just broke your your fundraise, Dan.
Speaker 1:Sorry about No. No. It's in the information already. Yeah. And so, Gruunz has run digital ads targeting people taking drugs like Ozempic who wanna keep getting appropriate nutrients as their appetite fades.
Speaker 1:That makes sense. Whenever you're on a cut and you're in a caloric deficit, whether it's caused by Ozempic or just, you know, keeping yourself hungry because you're trying to get diced for summer, you you want to maintain enough protein enough and enough hypertrophy training and hard training so that you don't lose muscle mass during that cut.
Speaker 2:Micronutrients too. Micronutrients what Coons is doing.
Speaker 1:Yeah. Yeah. And so they sell a monthly supply of gummy vitamins for $79 or 59 for monthly subscribers. They say the products pack more than 60 vitamins, minerals, and other ingredients into one serving, It markets its gummies as cheaper, more convenient version of popular greens powders, which are made of powdered vegetables and fruits mixed together into water smoothies.
Speaker 2:So Did you ever hear about this company, Goly? Yeah. Goly?
Speaker 1:What's that for gut health?
Speaker 2:The apple cider vinegar gummies? Yeah. Are they really big? They have they are large. They do hundreds of millions of annual revenue.
Speaker 2:Wild. I think they've been somewhat unsuccessful in terms of like capturing kind of enterprise Okay. Value around it. That said, just to give you a sense of the scale, they have 364,000 reviews on Amazon. So they sell
Speaker 1:300,000 reviews.
Speaker 2:Yeah. Wow. So run the numbers on what percentage of their customers you think have left an Amazon review.
Speaker 1:Yeah.
Speaker 2:And then you can get a sense of of their scale, but it's in the hundreds of millions of annual revenue. So again, Americans are buying billions and billions and billions of dollars of vitamins
Speaker 1:and minerals. Great reviews? Eight Sleep. I got an 81 last night. I'm getting up on the routine quality and time slept was a little bit lower, but go and get a pod four ultra five year warranty, thirty night rice thirty night risk free trial, free returns, free shipping.
Speaker 1:Go to 8sleep.com/tbpn.
Speaker 2:Last night, autopilot made adjustments to boost my deep sleep by 42%.
Speaker 1:Fantastic.
Speaker 2:Thank you, autopilot. I actually went to bed later than I would have liked because I was watching last night.
Speaker 1:Oh, you watched the Nathan for You?
Speaker 2:It's not Nathan for You, but
Speaker 1:it's Yeah. Yeah. Yeah. I love it. Was it good?
Speaker 2:Honestly, almost was texting the the team Yeah. Because he basically recreated the entire an entire airport Yep. In in the episode just to for
Speaker 1:one of these commercials. That's gotta have it. TV.
Speaker 2:Which hopefully we're signing the lease on today. Yep. We've been in diligence for a while. But we're gonna have to just like recreate LAX if we, you know, if we want, you know, to reach Nathan Fielder levels.
Speaker 1:He he's been on a fantastic run. I've enjoyed everything he's put out. The old Nathan for You episodes are iconic. And it's very rare to have business and comedy work
Speaker 2:so well aircraft safety.
Speaker 1:Amazing.
Speaker 2:So Can't wait.
Speaker 1:I'm I'm enjoying Last of Us, although it is terrifying. It's essentially a horror film and it's not ideal for the deep sleep, I think. So I might try and push that to, you know, maybe Saturday afternoon.
Speaker 2:It's so funny because because White Lotus ended.
Speaker 1:Yep. HBO likes to keep the dread really And my
Speaker 2:wife like, oh, I'm very I'm I'm happy that we're not gonna like be having these crazy cliffhangers and, like, scary scenes right before bed. And then Nathan Fielder's, like, sitting there, like, walking through, like, the history of, like, every terrible, you know, aircraft Yep. You know, accident. And it's just, like, extremely stressful. Yep.
Speaker 2:So go check it out.
Speaker 1:Go check it out. I mean, in in the world of Hollywood, the name of the game is getting an Emmy or a or an Academy Award. It's Emmy season coming up and breaking news, we're gonna be going for a daytime Emmy and we're gonna get a billboard. We're gonna get a billboard
Speaker 3:On Adquick.
Speaker 1:That for for your consideration billboard. If you've been if you've ever been driving around Los Angeles around Emmy season, all the shows have, you know, all their accolades up on the billboard. We're gonna go to Adquick.com. Out of home advertising made easy and measurable. Say goodbye to headaches of out of home advertising.
Speaker 1:Anyway, let's go to some timeline. We got our guests joining in twenty four minutes. We got a great lineup. We're gonna start showing you the lineup during the show. We're working on some new graphics packages, but we got David Tisch from Fox Group, Mike Vernal from Conviction, Ed from, Machina Labs, and then Will is coming on from Morgan Stanley.
Speaker 1:We'll be talking about, what's going on in the venture market, what's going on at the early stage, mid stage, what's going on in AI investing both at the foundation model layer and the application layer. I'm excited for the set of conversations, but let's run through some timeline posts in the meantime.
Speaker 2:We got a post from From Josh. Actually, Lulu first.
Speaker 1:Oh, you wanna do Lulu first?
Speaker 2:This is gonna be a nice little surprise for you. Please. Michael and Ben and Scott, if you can pull it up.
Speaker 1:Let's see.
Speaker 2:Is it is it in the Vanguard chat? No. It's just in the main chat.
Speaker 1:In the meantime, why don't I tell you about Wander? They just launched Wander Malibu Vista. It looks fantastic. You can see the ocean from that thing. Find your happy place.
Speaker 1:Book a wander with inspiring views, hotel grade amenities, dreamy beds, top tier cleaning, and twenty four seven concierge service. It's a vacation home, but better.
Speaker 2:If you stay in that wander, let know and go outside in the backyard and start yelling, I will be able to hear you.
Speaker 1:Wait. Really? Is that close? Yeah. That's amazing.
Speaker 2:You'd have to yell pretty loud, but I think I
Speaker 1:don't think our listeners will have a problem with that. Yeah. With all the creatine and
Speaker 2:All the tea.
Speaker 1:Working out that's going on in our in our community, I think they'll be fine. They'll be able to belt it out. But man, what a beautiful little what what is that? Driveway, but it's circular. Looks really beautiful.
Speaker 1:I don't know. I'm excited.
Speaker 2:Here we go. Lulu says, if Kugen does the eyebrow while describing your business model, congratulations, you're gonna have a decacorn. She she identified a specific, I guess. So founders, this is something you can read into now if you are if you are if if Kugan is talking about your business, just pay attention.
Speaker 1:He's I don't know. Underrated when he's trying to express
Speaker 2:He's subtly signaling something and in this case, it's very positive.
Speaker 1:It's very fun. Yeah, what a journey. Five years ago, bored during COVID, saw a bunch of people. A lot of people already had podcasts, lot of people had Substax. I was like, I want to do something different, but I think it's good to get, just be noisy on the internet Yeah.
Speaker 1:Because you're not really going to happy hours anymore during COVID, there's nothing going on. Why don't I start yapping on YouTube? And the first year was really, really slow. I think it took almost a full year to get more than like a hundred views on a video, like 50 episodes in
Speaker 5:a row.
Speaker 2:So good.
Speaker 1:And it was just like, it was cool. I I mean, for me, I didn't understand any of the stats. I didn't have any benchmarks because I was like kind of the only person in tech. Eventually, Gary Tan was doing stuff, but he was so big, I wasn't really like comping to him.
Speaker 3:Yep.
Speaker 1:And so I'd just be like, oh man, like I broke a hundred views on this video. Like, it's a banger. Like, this is great.
Speaker 2:So many people would have
Speaker 1:And I was just like fired up about But I enjoyed the process of it. And and I was like, I did a lot of motion graphics, spent a lot of time in After Effects. I remember I did a video on breaking down Varda, and I built a three d model of a satellite that was like wildly inaccurate based on like what they actually do. But they hadn't announced what they were actually gonna do yet, so I was just like, it looks like this. And it was just wildly wildly inaccurate, but it looked really cool and that's what matters.
Speaker 1:It illustrated the idea of of them launching a satellite and then, bringing it back down. And, yeah, the first time I met Deleon, was in Miami at Heredicon. He was like, oh, yeah. You made, like, that video about about Varda. We actually sent that to our real production team and said like, make this but like for us.
Speaker 1:Yeah. Was like, oh, that's great. I'm I'm I'm helping out. What what a fun one.
Speaker 2:And then took you five years to realize you just wanted to do a news To Newsmax.
Speaker 1:Newsmax. You just
Speaker 2:always be Yeah. Always be Newsmaxing. Alright. We got a post here from Josh Pacini who I have did a call with Oh, weeks ago. Cool.
Speaker 2:Early TBPN listener.
Speaker 1:This quote tweeting Annie. She says, name a better dopamine hit than running. I'll wait. And he says, getting a post read on TBPN. Well, congratulations, Josh.
Speaker 1:Today's your day. You got your post read on TBPN.
Speaker 2:Josh also has a very cool AI startup focused on automating drug development. Oh, that's So if you wanna work in that space, go hit him up.
Speaker 1:Yeah. You know what's funny? On one of the previous shows, were talking about startup names and we were saying that, you know, there's this new boom in the American Manufacturing Company of America or Advanced Manufacturing Company of America, Allen Control Systems, the San Francisco Compute Company, the New York Compute company, the New York browser company, whatever. And we said, all of those are done. There's no more alpha there.
Speaker 1:We gotta go back to the dot l y's. And He
Speaker 2:did delivered
Speaker 1:on a Sunday afternoon. He drops his What an absolute launch video at 2PM on a Sunday. What a funny time to launch.
Speaker 2:On Easter Sunday.
Speaker 1:Clue Lee is out. It's the old school dot l y. We're getting back in the l y game. I love it. Clue Lee is out cheat on everything and, has a very, like, very formally produced, like, really refined cinematic launch video with some great motion graphics in there.
Speaker 1:We're gonna have Roy join the show tomorrow to break it all down. But massive launch, 4,300,000 views, 16,000 likes as of the time of the And Chad Byers got in the deal, snuck a check-in, and he breaks it down, the Cluely manifesto. We want to cheat on everything. And interesting that he's using We. I guess he's already deeply involved with this company.
Speaker 1:Normally think about him as an investor, but this is clearly something he's really excited about.
Speaker 2:Not sure the round
Speaker 1:He said
Speaker 2:was announced yet, but
Speaker 1:No. No. It it is. No, it is. Yeah.
Speaker 1:Yeah. 5,000,000
Speaker 2:Okay.
Speaker 1:Deleon said that that he that they raised. Maybe Deleon leaked it, but then that's not on me. But Yeah. Chad says, we want to cheat on everything. Yes.
Speaker 1:You heard that right. Interviews, exams, sales calls, meetings. There's if there's a faster way to win, we'll take it. We built Cluely so you never have to think alone again. It sees your screen, here's your audio, feeds you answers in real time.
Speaker 1:While others guess, you're already right. And, yes, the world will call it cheating, but so is the calculator. So is spell check. So is Google. Every time technology makes us smarter, the world panics, then it adapts, then it forgets, and suddenly it's normal.
Speaker 1:Activate golden retriever mode. This is golden retriever mode. You don't need to know anything. You just sit there and it clearly answers every question for you. He says, but this is different.
Speaker 1:It isn't just AI just AI isn't just another tool. It will redefine how our world works. Why memorize facts, write code, research anything when the model can do it in seconds? Founder node. The best communicator, the best analyst, the best problem solver is now the one who knows how to ask the right question.
Speaker 1:The future won't reward effort. It will reward leverage and being a golden retriever. So start cheating because when everyone does it, no one is. Interesting.
Speaker 2:Amazing. I'm pumped to have Roy on. And Very fun. Little fun fact. Yep.
Speaker 2:Ben made all of our sound effects with his own voice. It is. So That is true. If
Speaker 1:Yeah. If you like this if
Speaker 2:you like the voice,
Speaker 1:shout out to Ben, our producer.
Speaker 3:Could've been
Speaker 2:the voice actor.
Speaker 1:Speaking of the other Ben, let's go to Ben Stiller.
Speaker 2:That's right.
Speaker 1:Sinners, he's posting about Variety. Sinners has amassed
Speaker 2:He's putting Variety
Speaker 1:in the truth Okay. We'd like to see that. A founder. He's going founder mode because he's, you know, he's he's a producer. He's the founder of many movies.
Speaker 1:Sinners has amassed $61,000,000 in his global debut. It's a great result for an original r rated horror film, yet the Warner Brothers release has got a $90,000,000 price tag before global marketing expenses, so profitability remains a way a ways away. And he says, in what universe does a $60,000,000 opening for an original studio movie warrant this headline? It's a good question. I don't know.
Speaker 1:It's not that crazy because, I mean, when when when big studios put hundreds of millions of dollars before behind a behind a film, like, they're typically hoping that they recoup all of that, like, on day one. Right? So Yeah. I mean, it doesn't seem like Variety is being, like, crazily negative here. And they did kind of couch that in like, you know, they got a ways to go to get profitable, which is like maybe factually accurate if the price tag really is 90,000,000.
Speaker 1:But it seems seems cool. I haven't I haven't seen the movie. But I don't know if I'll have a chance to go see an r rated horror film. That seems hard to rally the troops around. But have you watched the trailer or seen anything about sinners?
Speaker 2:I don't watch horror films.
Speaker 1:No? Too scary. Might throw off your sleep Yeah.
Speaker 2:And we're in a knockout knockout. Can honestly say I've never watched a full one. I just don't I don't get
Speaker 1:What about the classics? What about Scream or Cabin in the Woods?
Speaker 2:I'm also not a movie person. I've seen like three movies.
Speaker 1:Movies. Wolf of Wall Street, Wall Street, Wall Street two. Those are the three movies that we've The
Speaker 2:ones that matter.
Speaker 1:Scarface, Goodfellas, Godfather. No. You haven't even seen those, have you?
Speaker 2:I've I yeah.
Speaker 1:Not not quite. Have you seen Wall Street too? No. Have you seen Wolf of Wall Street?
Speaker 2:Yes. Okay.
Speaker 1:And you've seen Wall Street?
Speaker 2:We've more
Speaker 1:than three Have you not seen Wall Street?
Speaker 2:No. I haven't. Oh
Speaker 1:my god. American Psycho?
Speaker 2:I have seen that.
Speaker 1:Okay. Good.
Speaker 2:But I read the book first.
Speaker 1:Okay. Yeah. Yeah. That's weird. The book is weird.
Speaker 1:The book
Speaker 3:is weird.
Speaker 1:The book is Anyway, should we go to Jim Simons on the only rule he focused on in trading? Goat. He says we'll we'll pull up the video, but he says something like, never doubt the computer. It's pretty great. Can we pull this video up?
Speaker 1:It was
Speaker 2:probably never trusted trading decision that was made before ripping a heater.
Speaker 1:Oh, yeah. He's a big smoker. Yeah. Jim Simons. Big smoker.
Speaker 1:In case you're not familiar, he's the worth $31,000,000,000, 50 fifth richest person in the world. He's the founder of Renaissance Technologies, a quant
Speaker 2:No longer with us.
Speaker 1:Famously, there was a market crash. Everyone asked them, what did the what what was going on at Renaissance? What was your team doing? Wow, the market was crashing. And they said, we were at a movie.
Speaker 1:Amazing. They're just Crazy. Yeah. They're just like, what are we gonna do? The machine will handle it.
Speaker 1:Anyway, we're ready to play the clip.
Speaker 6:The only rule is we never override the computer. No one ever comes in any day and says, the computer wants to do this. That's crazy. We shouldn't do it. You don't do it because you can't you can't simulate that.
Speaker 6:You can't study the past and wonder whether the boss was gonna come in and change change his mind about something. So, you just stick with it and it's and it's it's worked.
Speaker 1:I mean, this is the story of like, is Lee Sedol Move 37. If Yeah. If if the AlphaGo team had said, hey, we think this is an error. We're going to override what the computer's doing. They would have thought that they were more likely to be least at all because it was a novel move that had not been considered by humans before.
Speaker 1:And in fact, move 37 was very important in that game.
Speaker 2:It's interesting too to think of it in the context of if you interject and insert human decision making Yeah. You're actually taking away from the program's potential success in the future, which could more than make up for a one time mistake. Right? Yeah. Like, there could be if, you know, the Renaissance team, if a computer does something that loses money effectively, but then the next time it does that thing, it it makes it back 10 x.
Speaker 2:Yep. Right? Like, was it actually an error?
Speaker 1:Gambler mindset in the computer. Yeah. You're only one computer aided trade away from I mean, it literally worked. You made $33,000,000.
Speaker 2:90 9 percent of computers
Speaker 3:right quit
Speaker 1:right before they hit a big
Speaker 2:hit a hundred x.
Speaker 1:Just imagine it has like a side internal thought, and you're just like, expand the reasoning on this one. And it's just like I'm feeling hot. I'm so do.
Speaker 2:I got a hot hand.
Speaker 1:I'm so do. Yeah. It's great. I mean, I wonder where else that philosophy has a potential impact. Like, we saw this with the debate over social networking where there was there was a there was a question about, you know, the the algorithmic social feeds feed people confirmation bias.
Speaker 1:They feed them content that they enjoy. They feed them brain rot sometimes. Maybe the steward of the network, Zuckerberg, who has essentially complete control over Meta, should step in and say, you know what? I'm gonna dial back the brain rot or I'm gonna dial up the you know, turn down the news, turn up the entertainment, turn down the, you know, the turn up the educational content. There's a bunch of things that, in theory, could could could, you know, feel right, but maybe the end state is just step back and maximize your LTV.
Speaker 1:Who knows? I don't know. I have a hot take on this, which is like the LTV is just like if you actually think about the true LTV of a user of Facebook, it can actually drive a much stronger and more valuable outcome as opposed to optimizing for ARPU, which is a one year metric.
Speaker 5:Yeah.
Speaker 1:So if you're optimizing for a one year metric, you're gonna try and sell someone, you know, like gambling, mobile games, anything that just pulls money out of their pocket and potentially gets them distracted from creating value in the in the society. But if instead you focus on what is the true lifetime value of this potential Facebook user for five decades, for their entire life, well, then it might actually be valuable to instead of trying to get some kid to play Candy Crush and spend all their parents' money on Candy Crush tokens, instead, send them a bunch of educational content. Get them really pilled on capitalism. They go build something really valuable. They make a bunch of money.
Speaker 1:And then you can run advertisements on them for Rolls Royce and Lamborghini. Or or they'll
Speaker 2:spend more And you're gonna spend more on on meta ads.
Speaker 1:Maybe. Maybe. Maybe. So and so there there there's an interesting theory where where like, what what are we saying when we when we when we say the kids are suffering from brain rot? What we're really saying is like, they will not contribute to society.
Speaker 1:They will not become economically valuable.
Speaker 2:But maybe they go and become slop farmers.
Speaker 1:Maybe. Yes. If they pull themselves out of the slop by their own bootstraps, it's possible. Of course, it's possible. It's possible.
Speaker 1:But I do think that there's something interesting where if you think about it from an ultra long time horizon, it can actually be economically efficient.
Speaker 2:Our quarterly, you know No. System will allow for that type
Speaker 1:of launching thing about Zuck, maybe, doesn't need to think in quarters. Right? Yeah. He doesn't need to. And so I'm I'm I'm optimistic that that that someone like Zuck could take a really, really long view.
Speaker 1:Also, I mean, think he has kids. I think he has a a very good, strong moral framework, so I think he might just optimize for that naturally. But I do think that there's an economic model to optimizing for long, long lifetime value, education, and human flourishing, economic flourishing, even in the face of declining ARPU in the short term.
Speaker 2:I would love to think that Zuck is thinking of themselves as, you know, of of Meta as operating digital railro railroads. And he's like, you know what? We're gonna, you know, we're just gonna invest in delivering educational content to our children for the next five to ten years. We're gonna get them really excited about, you know, learning and science and
Speaker 1:Because we will make more money in the future. That's the key It can't just be purely altruistic. Yeah. It has to be, no, this is the right move for the shareholders. But it's gutsy and it would never fly if you're optimizing the next quarter's return.
Speaker 1:Anyway.
Speaker 2:I had a post on Saturday Yeah. Relevant to Facebook. I said, someday you're gonna look down and realize that the good old days are over. X will be like Facebook, your group chats won't be popping and your phone will just feel different. Don't let this time slip away.
Speaker 2:You need to increase your screen time now before it's too late. And funny enough, that thought came to me on a Saturday when my screen time is the lowest. The lowest. And but it it did we I I've had this sense over time that that Twitter and X are just sort of Lindy Mhmm. And will kind of always be here.
Speaker 2:But it's very possible that X goes away at Facebook at some point. And then we're just we're just the boomers on Facebook just all, you know, yelling at each other and arguing.
Speaker 1:We'll become like a TikTok reaction stream. Yeah. Or whatever's next.
Speaker 2:You always always gotta move on.
Speaker 1:We're going to WeMe. We're going to WeMe. It's on the come up. Talked about WeMe. It's the future.
Speaker 1:Yeah.
Speaker 2:The FTC says that WeMe is Facebook's, you know Biggest competitor. Biggest competitor.
Speaker 1:Or one of the top two. One of Snap and then WeMe.
Speaker 2:Snap and WeeMe. So we'll see you on WeeMe, folks.
Speaker 1:Yeah. We really gotta chase that down. We gotta we gotta get that seat.
Speaker 2:I'm gonna let you do this next one.
Speaker 1:Okay. So, Wardall says, you need to be dad maxing. You need to be waking up at 05:45 on a Saturday to hit the gym and then coming back to wake up your wife and kids by blasting creed while making breakfast. You need to be dethatching your lawn. I don't even know what that means.
Speaker 1:You need to clean your car and then stare at it in the driveway for half an hour. You need to be telling your kids that Jerusalem belongs to those who worship Christ. You need to be treating Easter Sunday like Super Bowl Sunday. You need to be absolutely maging childless heathens with peak dad power moves as God intended. Very funny Easter post.
Speaker 1:Obviously, there was a lot of like he is risen posts that went viral over the Easter Sunday, but I thought this one was was very funny. It is something that happens naturally. You start waking up earlier and earlier in 05:45. That's five minutes later than I wake up, actually, if I look at my alarm. 05:40, on the Ashton Hall grind.
Speaker 1:Anyway, Sam D'Amico, friend of the show. He's been on, he runs Impulse Stoves. He had a good take about, aliens that I wanted to share. He says, I remain convinced that the best evidence that the US government has not recovered crashed alien spacecraft is that, one, that would be the coolest thing ever, and two, someone would have to share it in a group chat with the boys. And he is, of course, sharing a screenshot of, secretary of defense, Pete Hegseth, is said to have shared attack details in a second signal chat.
Speaker 1:The defense secretary sent sensitive information about strikes in Yemen to an encrypted chat that included his wife and brother, people familiar with the matter said.
Speaker 2:So send that headline to your wife and just say us.
Speaker 1:Us.
Speaker 2:Us. I was trying to do that earlier, but kept getting paywalled by the New York Times. The failing New York Times wouldn't let me screenshot the headline
Speaker 1:Yeah.
Speaker 2:Of an article.
Speaker 1:Yeah. Just take the screenshot from this. It's great. We we we got a nice clean screenshot here from Sam. Yeah.
Speaker 1:Very funny. I I actually think this is a great take. But we should have Jesse Michaels on the show to give us the latest and greatest in the world of UAPs, UFOs, and and, alien aircraft because and spacecraft because he has gone way deeper. And and regardless of what you think about aliens, I think that Jesse's done a great job of finding interesting stories, interesting historical anecdotes, interesting anomalies. And even if you remain unconvinced after spending time with him, you will be entertained and you will feel like you are talking to an intellectual, not, just a crazy conspiracy theorist.
Speaker 1:And so, huge shout out to Jesse Michaels, one of the best to ever do it. We grew up on YouTube around the same time. Anyway, let's move on to Atlas Creatine Cycle. He says they should have a four twenty for creatine monohydrate.
Speaker 2:So true.
Speaker 1:I love it. Willow Brand says ten six because ten grams a day and six looks like a g. Oh, okay. Ten g. I get it.
Speaker 1:So true, king. People are into creatine right now. A lot of debate over whether creatine
Speaker 2:I have fifteen milligrams
Speaker 1:grams.
Speaker 2:Grams.
Speaker 1:Not milligrams.
Speaker 2:Sorry. Yeah. Your max. Those are big scoops. Yeah.
Speaker 2:Yeah.
Speaker 1:Yeah. Big scoops. Yeah. It's a little sandy, but you gotta get it down. The creatine, it seems like, know, maybe it's a fast bargain, but it's great.
Speaker 2:It's the best hair loss.
Speaker 1:It's the best hair loss supplement in the world.
Speaker 2:Yeah. A lot of people talk about hair loss supplements, thinking that there are supplements that, know, encourage hair growth. You
Speaker 1:know, Joe Rogan's bald?
Speaker 2:Yeah.
Speaker 1:He looks strong. Maybe it's the creatine. Who knows? Maybe it's genetics. Maybe it's a million other things.
Speaker 1:But, yeah.
Speaker 2:You never know.
Speaker 1:You never know.
Speaker 2:It's worth it. Worth the risk.
Speaker 1:Anyway, we we got four minutes. Let's do a couple more posts. This one by David Haber over at Andreessen was interesting. He says, in any fast growing organization, one of the best feelings as manager or CEO is having someone who works for you that I call safe hands. It's this implicit sense that you can delegate a task, project, or line of business and trust that the person is going to execute with quality.
Speaker 1:We've talked about this before with, like, the levels to employ to different employee skill sets, the pyramid that Sean Puri outlined. SafeHands isn't just about competence. It's about proactively communicating when issues arrive, acting as an owner when problem solving, and operating independently without the need for micromanagement. Importantly, SafeHands isn't tied to seniority. It's just remarkable how inconsistent it is across an organization.
Speaker 1:When you whenever I find someone who is safe hands in my prior company, especially junior folks, I pour responsibility on them. Many of these individuals stretched far beyond their original roles and became leaders at the company with several now successful entrepreneurs. It's one of the most common conversations I have with founders I work with, especially in the series b plus stage as they're beginning to bring on executive leadership for the first time. Do you know do you feel like you have safe hands across every functional unit of your business? How much leverage do you feel you're getting from your team in those areas?
Speaker 1:Every CEO instinctual instinctively knows the answer to these questions, and finding your safe hands is a key step towards scaling yourself and the company. And Matt Grimm says, I call this, folks you can turn your back on and they're insanely valuable. In fairness, I didn't come up with that phrase. One of those types who reports to me told me and I'm shamelessly stealing it.
Speaker 2:Got it.
Speaker 1:Jordy, what's your No.
Speaker 2:I think oftentimes, you know, in this case, David and and Matt are founders. Oftentimes, founders end up getting credit for the the things that these sort of safe hands roles end up doing.
Speaker 1:Oh,
Speaker 2:totally. And so Matt is is
Speaker 1:a But that's the goal. You have to hire these people. And then also train them. And then take advantage of them. And
Speaker 2:know, back them when they go out to do their own thing.
Speaker 1:Absolutely.
Speaker 2:Well, before we have David, we gotta talk about Eric. Eric Thornburg.
Speaker 1:Oh, Speaking of Andreessen, Eric Tornburg has joined Andreessen Horowitz as a general partner. Fantastic news. He'll be on the show tomorrow to break it down for us. Very excited to talk to him. Been a good friend for years.
Speaker 1:Talked about media. He's been in the podcasting space for for, well, like, multiple years now, built turpentine, done tons of interviews, and, one of the greatest networkers in human history, I
Speaker 2:think. Probably.
Speaker 1:He knows everyone and he will If
Speaker 2:a child of the internet He
Speaker 1:will just throw you in a group chat with the world's most important people randomly. And I'll be like, why am I in this? But thank you. This is interesting.
Speaker 5:Yeah.
Speaker 1:Yeah. Great guy.
Speaker 2:Anyways, very excited for him
Speaker 1:For sure.
Speaker 2:And and the firm and very excited to talk with him tomorrow.
Speaker 1:Anyway, let's bring in our first guest, David Tisch from Box Group. How you doing, David?
Speaker 4:Hi, guys. How are you? Doing great. On having a a new job today.
Speaker 1:I do. Yes. Thank you. Yeah. I I'm I'm taking it from part time, fifty hours a week, to full time, hundred hours a week, but it's only up from Are
Speaker 4:you hiring?
Speaker 1:We are. We are hiring. Always.
Speaker 4:How do I how do I pursue this?
Speaker 2:Yeah. The the VC to full time news anchor Right. Pipeline. You know, once you've done it all in venture
Speaker 1:Yeah.
Speaker 2:You know, like you have, the natural step is When
Speaker 4:you when you start in this industry, I feel like that's the ambition, a daily show that you can pontificate across the whole industry.
Speaker 5:Yes. We're hoping to achieve
Speaker 2:We're hoping to recruit you to be, you know, once a week, drop in. We will be your podcast.
Speaker 1:Yes. You're gonna have is this is actually like, jokes aside, like, the way that you, like, work for us is that, when news breaks, you bring it to us. When, when when something happens that you have an opinion on, you come on the show and you talk to us. And and I
Speaker 4:that's the the venture capitalist way to we don't have
Speaker 1:news. We don't have
Speaker 4:things that happen. I feel like you are really, clinging to your audience.
Speaker 5:What about,
Speaker 1:like, the most complex and naughty geopolitical conflicts? I feel like you guys as a class are, like, the best in business.
Speaker 4:Overqualified to talk about it.
Speaker 1:Oh, okay. So did you do you wanna stay away from politics?
Speaker 2:Alright. So let's start with let's start with tariffs.
Speaker 4:Yeah. You know?
Speaker 1:Let's start with tariffs, Iran, China, Russia. Let's just go down the list.
Speaker 4:Day in the market. Everything's great here.
Speaker 1:Everything's great. Everything's great.
Speaker 4:Have you heard about the accordion effect to early stage? Because that's our famous early stage line of, like, whatever happens in the latest stage market, it's like an accordion all the way to early stage. So it reverberates over the course of, you know, three to five years. Sure. So we will not ever be impacted because the accordion basically never reaches early stage because something else will happen in the macro before then, which is a really nice don't ask
Speaker 2:us There's liquidity, so you can't panic sell. Even even if you wanted to, you can't.
Speaker 4:It can't. That's a that's a that's a third accordion ripple.
Speaker 1:Yeah. Yeah.
Speaker 4:There's liquidity. I mean
Speaker 1:I mean, that like, there's no better example of that than we have SVB crisis, Interest rates go up. It's the death of venture. We're hearing about, oh, GPs are gonna be giving back LP capital, but then, well, well, well, would you hear about this AI trend? And all of a sudden, it's time to rip checks.
Speaker 4:Saved us all. Saved us all.
Speaker 1:Would have
Speaker 2:thought? Wait. Yeah. What wasn't there this was sort of before my time, but there was a whole chatbot era. Right?
Speaker 2:Wasn't there like Chatbot being one. Yeah. Free AI was like it was supposed to be the thing. It was sort of right. It was just didn't have the the underlying tech trend.
Speaker 2:Is that right?
Speaker 4:I feel like the tech wasn't there, but also the branding of chatbot to ChatGPT isn't that different. But magically different from a outcome and sort of adoption curve. If you look like the automated chatbots, I think is what they were called for that moment in time, they all fell on their face because they weren't interesting enough, good enough. They were, like, preprogrammed answers. And then OpenAI releases, in essence, just an advanced version of that in many ways from a consumer positioning, and here we are.
Speaker 4:And so you are like, the idea of chatbot was right in how you're interacting with the tech. The tech, to your point, just wasn't good enough.
Speaker 1:Yeah. 90% of chatbot founders quit right before they strike the bag.
Speaker 2:Right before they sell the open AI.
Speaker 1:I mean, I I I don't know if I've actually we we we should find some chatbot founder who stuck it out.
Speaker 4:No. Hugging Face.
Speaker 1:Hugging Face is the one.
Speaker 4:Yeah. That's right. Hugging Hugging Face is the winner. They were in a boot camp for chatbots.
Speaker 1:No way.
Speaker 4:And pivoted from a chatbot into Hugging Face. So that's your answer.
Speaker 1:That's amazing. Yeah. We gotta have it's it's Clement on the show?
Speaker 4:Yes. Right? Yeah.
Speaker 1:We gotta have him on. That'd be great. So, yeah. I mean, to get a little bit more serious, like like, how are you processing this year? What are you actually excited about?
Speaker 1:What is fatiguing you in Venture these days?
Speaker 4:We have our annual meeting tomorrow, so I'm in the middle of practicing our our script on the market, I can
Speaker 1:just try it. Please. I love AGMs.
Speaker 4:Yeah. The, you know, the the pre Liberation Day, post Liberation Day market speech is is is different in some way, but you really, like I don't know. You're investing at the earliest stage of a journey and trying to attach two people starting a company with big long term ten, fifteen year ambition to some moment in time macro or what today feels like an incredibly volatile macro where you actually can't even understand what stability looks like or a new framework like. It just it's impossible. And so the day to day job here is we meet people, we get really excited about what they're working on, we give them money, and we wait five, ten, fifteen years to see how that all plays out.
Speaker 4:So the the investment moment of investing in an early stage company feels totally decoupled from the macro of what's going on. The macro does impact the companies you invested in years ago as they come to market for more money, as they figure out their, you know, revenue retention. But the sort of day to day volatility, I don't think has an impact on our day to day job of funding great people, starting big ambitious visions.
Speaker 1:Do you think that there are going to be stories from this, tariff cycle that are like what happened in COVID where everyone was like, Airbnb was particularly hurting as a start up. I mean, I they they were public at the time, but they were I still think of them as like a YC company. Right? And it found it it seemed like that the the story of Airbnb was like, COVID was a transformational moment for them, and they emerged like a stronger company than ever. Do you expect that to happen to any start ups, maybe in your portfolio or just out there in the market that are getting beat up but might emerge stronger than ever?
Speaker 4:So so, like, if you isolate tariffs, that has a Sure. Impact on a subset of companies Yeah. Very outside of software in many I think there's software companies that involve logistics and shipping that definitely are impacted, but I don't know that the, like, come out of the tariff is a predictable framework. Like, what does that actually mean? Do we get to free trade in reality?
Speaker 4:Do we get to some equilibrium? Is this China only that we're talking about? And I think within there lies a very hard to foresee, again, point of stability, whereas at least in COVID, if you said we return to a normal world, that was a more predictable endpoint. If you assume, you know, early in COVID, was wait two weeks and then the world will start again, and then it was some longer period. But I think there was an appreciation for what coming out of it could look like.
Speaker 4:Whereas I think right now, you're in, like, the creation period. Harder to to guess. Yep. You know, the the easy guess is, like, American manufacturing windfall, but that feels like a big stretch, like no one's building a factory overnight. I feel like that happens in other parts of the world, not here.
Speaker 1:It does feel like it could be a catalyst the American dynamism companies, the re industrialized companies that have been placing that bet and kind of hoping for just a little bit of a boost that you can see a lot of like, oh, that series a company went to series b like a little bit earlier because of this And then that was enough to get them over an awkward hump, build some real infrastructure out and kind of like realize the vision.
Speaker 2:Well, I think I've
Speaker 1:been like cautiously optimistic
Speaker 2:about some
Speaker 1:of the wins from this.
Speaker 2:If you're a super early stage investor, which which Box Group is Yeah. And then you're trying to time markets by being like, oh, there's tariffs. Let me make a bunch of supply chain related or manufacturing investments. But then the company is not gonna mature for five to potentially ten years, so it could be a totally different environment. And and one example that that was relevant, we had the CEO of Astronis on last week, which I imagine you invested in like over at least over five years ago.
Speaker 4:Thirteen years ago.
Speaker 2:Thirteen years ago?
Speaker 1:Overnight success.
Speaker 2:And overnight success. Oh, and and that's like a good example of like you couldn't have you you thought that space was gonna be important at the time, and you like
Speaker 4:You knew. It's actually we're we're early stage VCs. We knew. We didn't Crystal Ball.
Speaker 1:You knew Crystal
Speaker 4:Ball. Obviously. Yes. No. I mean, like, if you think about AI, we're we're the earliest investor in a company called Clay.
Speaker 4:And Clay created a vision, had a product, and it was in need of AI for it to work, and and it wasn't created yet. And so if you watch this seven year overnight success, it clicked when the underlying technology caught up with what the go to market product was. And I think you see that a lot of the times that the founders who are early in a space and can see it through and wait for the world to come to them while they're sort of pushing the world to get there, that's where a lot of that magic is. And I think Astronis or Zipline, again, fourteen years ago we funded Zipline Wow. Is is another example.
Speaker 1:We are huge Zipline shills now that we talked to the founder. I mean, what an incredible story.
Speaker 2:Left yeah. Left that conversation. We were basically like, would
Speaker 1:invest in Buy at any price. Yeah. Yeah. Because, I mean, he he it's not just that he's been grinding it out for so long, but I feel like if you watch the launch video, like, he paints the it's the opposite of the Black Mirror vision. It it's a very positive vision of the future, it's something that yeah.
Speaker 1:Job's not finished. He's gonna be doing that for twenty, thirty years easily. Like, there's so much to do, and and now it's just a matter of manufacturing scale, economics, all the basic stuff, but, like, he's got the drive.
Speaker 4:We went to his office Yeah. On a recent trip to San Francisco, and I probably hadn't been in his office in in a decade.
Speaker 1:Yeah.
Speaker 4:And we walked in and it was just like this jaw dropping American built Crazy. Hardware software combo Yeah. That you've like, you walked out of there and said, this is the beginning of a Yeah. Another fifteen year vision.
Speaker 1:Totally. Totally.
Speaker 2:Was there was there, you know, looking back at at these companies like Zipline, Astronis, was there ever a trend over the last whatever fifteen years that you set that you were tempted to go all in on? Because I imagine there was a lot of investors of that era that said, oh, is so cool. I'm going all in on it. Climate tech is so cool.
Speaker 1:I'm gonna Buy a do this. Let you know
Speaker 4:instant delivery. Just NFTs.
Speaker 1:Just NFTs. Yeah.
Speaker 2:Yeah. Was the one. That was the one.
Speaker 4:No. I mean, we're generalists. We are founder driven. We find people who have their own vision. I think us as a firm, we should never be in charge of coming up with ideas.
Speaker 4:That's not our job. Our job is to give people who have dreams capital and support to help them. John, your company, I think, is the single most heavily debated internal decision we'd ever made at Box Groove. Yeah. From a moral standpoint, we had to, like, decide if it was good or bad.
Speaker 4:Yeah. And so that was interesting. So we almost pivoted into drugs. That was an opportunity for us. But no, I like, the world pivoted to AI.
Speaker 4:Right? So I think two years ago, we were saying, like, 30 to 40% of the companies we see talk about AI or are oriented around AI. Last year was, like, 90, and this year it's a 70%. You you don't meet non AI companies right now. And if they're not AI first, it's we're attacking an industry by bringing AI to it Sure.
Speaker 4:Which is slower and stale. And I think that is a forced all in versus a sort of opted all in.
Speaker 1:Does does do the different business models that seem to be emerging, does that change the way you're underwriting these investments? I'm thinking about highly CapEx intensive businesses where you're just expecting a ton of dilution, or we've seen some companies that are kind of just doing, like, private equity style roll ups, but they're raising from venture capital. And I imagine if you're not careful with pro rata or how you're sizing your bets, like, it it could it could turn out to be like, oh, we really didn't get the full bite at the apple. But is that something that even matters to you, or is it just like back the founder, we'll figure it out?
Speaker 4:Private equity roll ups in venture always ends well. Definitely. Always. Yeah.
Speaker 1:Yeah. I mean, we we we like to say private equity is not a mature business, and so there's lots of opportunity for tech people to come in and disrupt No.
Speaker 4:They figured no They
Speaker 2:they don't
Speaker 1:take it seriously.
Speaker 2:In that area.
Speaker 1:Famously not famously not cutthroat. Famously not cutthroat.
Speaker 4:They're happy to leave all that money on the table.
Speaker 1:Yeah. Exactly. Just just dollars on the floor for VCs to come pick up. Right? Jordy?
Speaker 1:Yeah. Sorry.
Speaker 2:No. No. No. I I I was more how how was has there ever you know, it feels like over the last two years, call it, there's been more of these sort of roll ups than ever before. Was there was there another did was there another kind of, like, general, like, market wide crack?
Speaker 2:Or was it just sort of, like, individual areas and opportunities I
Speaker 4:struggle to think that the way to build companies is to replicate another company that's succeeding. In these moments, what you tend to have is one winner and a bunch of followers that don't win. And so can there be a single version of a roll up? If you look at Andoril, they're great at acquisitions. That's a different phrasing of the word roll up.
Speaker 4:Roll up is either we're gonna buy a bunch of things that are the same size or we're gonna buy, like, one big thing and then tuck in some other smaller things around it. So I think unpacking the nuance in these words is more important than assuming a general, like, success across a a wide variety of companies. I think the, like, moment in time where you probably saw fast followers or fast movers win was in the on demand business. Right? When Uber trained the world that you could touch something on your phone and something in the real world would happen, it unlocked, like, a a behavior across the world that was very different.
Speaker 4:Right? And that was this this phone to real world connection that I think opened up a ton of other businesses. I don't think they all worked, but I do think that that was a horizontal opening versus a business model innovation that has been used in other industries or financial industries and then applied in venture.
Speaker 2:Yeah. The idea, the the classic sort of like accounting firm roll up, when I look at that, it's like, when it's been two weeks and my like CPA is not like on it or like is not, you know, like, clearly, like, you know, is busy with other clients. I'm like, it's not like I wanna switch immediately, but I'm pretty quickly. And so the idea that you're just gonna buy, like, 20 accounting firms and then slap AI on it and not have like 90% churn is just interesting. But
Speaker 4:have you tried AI? I mean, it's pretty good.
Speaker 2:Yeah. Yeah. Yeah. It's pretty you know, it's only gonna get it wrong Yeah. 5% of the time and that's gonna cost you millions.
Speaker 2:But
Speaker 1:yeah. This is a topic that Jordy and I have been debated, and it's kind of related to Uber opening the mindset of, like, this delivery boom. Chat GPT rappers, it's been derided as a term. We've now seen the Versus Code fork wars. But it looks like there's a chance that OpenAI buys Windsurf for 3,000,000,000.
Speaker 1:And I've been going back and forth with Jordy about this. Like, is this game on for m and a in the wrapper market? Because if OpenAI, who has, you know, great team, lots of money, can't, like, build it and they wanna buy it, then do do we see Anthropic? Do we see x AI buying stuff? Do we see Amazon?
Speaker 1:All all of the Mag seven buy stuff. And then maybe even, you know, you get into some of the just Fortune 500 companies that wanna buy startups. And so I I I'm in this weird scenario where I've I've been somewhat accepting of the idea that a a rapper might not be a power law outcome, but everyone involved in Windsurf, if this deal goes through, will do very well. And so what is your take on on that market and and does this shift? My
Speaker 2:take was broadly that, like, this is highly strategic for OpenAI, but that doesn't mean every rapper, even if they have a lot traction revenue is like suddenly strategic to a wide range of buyers. Right? Sure.
Speaker 4:I think I think in my in my fifteen years doing this, the thing I've under asked or I overrated was the amount of M and A that would happen. I think if you go back in the early growth of, like, this era, if you look at, you know, anything from, you know, Facebook and and before that, Google, Yahoo, Twitter, on their way up, they bought tens, if not hundred plus companies. And a lot of that was for stock. And it was stock that appreciated post acquisition, incredibly valuable for both the company and the founders who sold. And I think if you look at the next wave of startups, a dramatic decrease in m and a because instead of buy, you build.
Speaker 4:And the acqui hire didn't prove out to be the best use of equity. A lot of the the decision of buy versus build became easier as as you thought about where to innovate. I think in sort of getting at your question, I hope we're entering a period of m and a. I think the easy way to rationalize it is the valuations of some of these companies that you mentioned are so big that they can afford to buy companies for substantial amounts that might actually align with the founder of the the acquired's expectations. And I think that's where one of the other mismatch was happening is that the the company that wanted to buy another company was just not able to hit the price, and so they didn't happen.
Speaker 4:And so I think one way to rationalize it is whether it's the the big seven or the scaled AI companies have big enough valuations to go out and buy things for numbers that will hit a founder's expectation, which I think would unlock, you know, a lot of a lot of positive things in this ecosystem. One is liquidity, but two is, like, there there isn't really an answer to how do things end right now for a ton of companies, and m and a is the piece that's been missing to me the most. It gets less discussed. And I think Fortune 500 companies need to modernize. Right?
Speaker 4:And we saw that pressure ten years ago when you heard, like, all the non tech companies are gonna become tech companies, then the public markets punish you on a quarter by quarter basis, and it's like, forget that. We're not gonna do any of
Speaker 2:that. Yeah.
Speaker 4:But I think today AI might be such a dramatic forcing function that smart big companies need to move quickly to get ahead of the curve. So optimism
Speaker 2:Is that buy versus you you mentioned, you know, these super acquisitive companies maybe fifteen years ago, and then that changed. Do you think that was a factor? I mean, you guys basically Plaid was built out of your guys' office. There's a lot of there's been so much infrastructure built during the Plaid era. Do you think that that was part of the calculus for some of these bigger, you know, companies that would have been acquirers, but they said, hey, like, we could buy this tech and then maybe try to integrate it or we could get this team and and do it or, hey, this infrastructure exists and we can just build it.
Speaker 4:You so many factors go you like, the biggest one to me is that the government didn't want big tech to buy more companies. And so if they were gonna buy companies, they had to be, like, the biggest ones, not this like, they were gonna fight the regulatory fights on big companies, not on small ones, and that dried a lot of it up. And then I think the valuation expectations was the other friction. When a startup decided they were worth a half a billion dollars and the potential acquirers wanted to buy them for a hundred million dollars, that was no longer interesting. And so it just it decoupled rationality from playing out in the m and a world.
Speaker 4:Right? You have to have, like, a buyer and seller meet on price in order for the deal to even get going. And I think that's where the biggest gap was. Plaid sold. Right?
Speaker 4:Plaid sold and the government stopped it. And I think that that was, you know, to me, a interesting moment in the government getting involved in something that was debatable. And I think it also tells big companies, like, don't waste your time trying to get these things through, and that slows down a whole wave of potential M and A.
Speaker 1:Interesting. I don't know if if the M and A market relates to what you're seeing on the LP side, but we've heard that there might be some fatigue from LPs on what's going on in Venture. But at the same time, it feels like that David Goggins meme where, you know, Venture just keeps on chugging no matter what. You're going to the AGM. What what are you seeing broadly in terms of LP appetite for ever bigger venture funds?
Speaker 4:We're a small, adorable seed fund based in New York City. So I we are not we are not responsible to answer that question. I think our like, your job, if you take LP capital, is to give them back a lot of money one day. Yeah. And I think if you haven't, you you owe that to them.
Speaker 4:And so at some point, the patience should run out, and I I appreciate that. I think the challenge is the time for liquidity in early stage venture has gotten pushed significantly from where it was more predictable a decade or two decades ago. You could say seven to ten years on an early stage fund and mean it. Today, I think you say seven to ten years, and you're like, by that, I mean, like, twelve to fifteen. Yep.
Speaker 4:And that that's a substantial difference.
Speaker 1:Yep.
Speaker 4:And I think you need to align with your investors on what that timeline is because it's in a rational timeline. Like, the people we fund, if you go back fifteen years, they were, like, pre elementary school for the most part. Right? Like, if you look at the young founder that you're investing in today, a fifteen year timeline is two thirds of a life. Like, it's an irrational number.
Speaker 4:And so these, like the go in motion of making an investment to the return the fund to LPs timeline is so decoupled from, I think, a psychological standpoint that, your stakeholders are just dramatically, unrelatable.
Speaker 1:On that on the topic of, like, young founders, how has the early stage market evolved? There's a it feels like there's a lot new a lot more products. Like, YC is bigger than ever, but then there's also Z Fellows. There's different fellowships. There's people that are just giving away money to people to, like, go try a start up and then maybe I'll invest later.
Speaker 1:And obviously, the Thiel Fellowship's kind of like a scaled version of that, but there's a lot of other, you know, initiatives. How has that changed your strategy? Has it changed your strategy at all? And kind of like, what what does the early stage market look for you look like for you today?
Speaker 4:I think there, like, there's always been these splashes of noise. Mhmm. And very, very little like, if you go back again, I'm old, and so I've been doing this through these micro waves of change in the early stage market, very few products stay where they are. They move in different directions. They either get later.
Speaker 4:So if you think about new entrants as as funds into the early stage market. Most of the ambition is to become a bigger fund. And in doing so, you become later by nature of scaling
Speaker 1:Yep.
Speaker 4:Your business. And I think on a product side, you're only as good as the product you're offering. And so what has been amazing to me about YC is they've just continued to compound quality of the satisfaction to their customer. They are not free, right? You're giving YC equity.
Speaker 4:And yet, if you look at, like, the happiness factor, the the NPS or whatever cheesy acronym you you call reviews, but, like, people go to YC because other people who went to YC loved it, and they think it was entirely worth it. And so I think the products that get invented need to live up to the cost. And if the cost is free, like nothing is really free. And so what comes with that freedom? Is that attaching to a brand?
Speaker 4:And if you attach your company to a brand, is that a good thing to have done, or is there some negative externality that comes with that? And so I think and it's probably not the endpoint for the the products that are offering free capital to be free forever. I would assume that's a hard thing to scale. And so I think you have to just, like, as a company aligning yourself with the brand, the trusted brands have proven to be trusted for a reason, and the the new ones need to earn that. And I think there are some that have been around long enough where you find good examples of quality coming from them, and those are the ones that I would tend to trust You've
Speaker 1:been in the game for a long time. Can you tell me the story of your first investment ever?
Speaker 4:Yeah. Our Box Group is named after our first investment. Really? So it's like a combination. So the first investment's a company called Boxy.
Speaker 4:It was a Roku competitor. We were in their seed round as a adorable check. I didn't wanna write my name as an angel investor, so I created an LLC called Box Group to invest in Boxy, which made me feel bigger. The box was like a cool nightclub in the city at the time. It felt like felt like a cool word.
Speaker 4:I've looked with Aaron Levy. He registered box.net, like, two months before I did
Speaker 2:Box group Oh, wow.
Speaker 4:Which I'm bitter about. So at some point, he'll sue me and it's all over.
Speaker 1:But he's been on the shows too, so he can come on and debate you for Yeah. Well, it's
Speaker 4:collab we're all collaborative in this anyway. No no competitors. So, you know, Boxy gets funded, followed on by Fred Wilson. I'm like, my god. I'm amazing at this.
Speaker 1:Yes. Yes. Yes.
Speaker 4:I gotta read that guy's blog. This is so cool. And then General Catalyst came in, and then Avner, the founder, went in front of congress to, like, fight the cable companies. It was, like, an amazing first investment to to, like, see the narrative of a startup. They sold to Samsung, and they're they were built into, the Samsung smart TV technology.
Speaker 4:But the idea was right, and the timing was challenging.
Speaker 3:Had to
Speaker 4:fight every single battle on behalf of the people that came after them, and I think that that was a a really good lesson.
Speaker 2:Is is do you see you have a ton of portfolio companies.
Speaker 4:Too many, probably.
Speaker 2:Too many, I'm sure, to to manage. Do you see and and Casetext is one of them, which is an interesting example because that was a company that no one Nine year overnight success. Yeah. Exactly. I'll hit the overnight success.
Speaker 5:Overnight success.
Speaker 2:But are you seeing that across
Speaker 4:Can we get a sound board for our like meet companies meetings?
Speaker 1:Oh, definitely should.
Speaker 2:Yeah. You should.
Speaker 1:Handshake deal.
Speaker 2:Yeah. Handshake deals.
Speaker 1:Raise your forecasts.
Speaker 2:Yeah. Yeah.
Speaker 4:There's an internal bingo that we run that every time they say buzzwords, we
Speaker 1:We're preempting.
Speaker 2:But how do Exactly. How do you think of AI in the context of the portfolio broadly? Are there are there a bunch of examples where it's kind of creating new momentum in the business or, like, tons of new opportunity? Or and, you know, I look at this like, you know, I have 50 odd personal investments
Speaker 4:All of them will work.
Speaker 2:All of them will work. I'm sure they've all been marked up. So so I'm sure
Speaker 7:That's what
Speaker 4:this employer website told me, which I was like, oh.
Speaker 2:Yeah. That
Speaker 4:could be 98% isn't
Speaker 2:it? 98% hit rate. Yeah. But but, you know, how often are you seeing it sort of create momentum versus momentum just being something that once you lose it, it's really hard to kind of get it back if you're not getting, you know, sort of lucky?
Speaker 4:I mean, CaseText is like the most amazing story. What a grinder into just being early in the right way. And I think to Jake's credit, he was always like the smartest person in the room and figured out how AI could come into what they were building in a differentiated way and, like, split a team off, built a product, got to market first in an industry that was ready for it. And so I think it's this and he landed, like, he landed an outcome that he changed his life and changed the team's life. And I think, like, a unique story.
Speaker 4:We're now, like, three years past that, you're early to the game. And so if you haven't figured out how to take your stale product or your product that's maxed out and begin to reenergize it, it feels like you're a little late. There are those stories. And I think Clay is the other side of it where it it AI happened and Clay benefited from sort of the the speed of it and now is running. But I think within the portfolio, there are companies that benefit from pieces of it.
Speaker 4:And whether that's on the cost saving side or the growth side, I think you can find examples of of everything. But it's within the verticals that I find the most interesting momentum just being recreated. Right? It's it's companies that are servicing customers, and in some way, if they can be the deliverer of AI to an industry that can't get it themselves, that's a really big opportunity. And I think CaseText sort of represents that.
Speaker 2:Yeah. That makes sense.
Speaker 1:It's awesome. Thank you so much. This is a I came on here to
Speaker 4:promote something.
Speaker 2:Oh, Let's
Speaker 1:go. Us that The
Speaker 4:Howard Stern of of tech. And so when you go on Howard, you have to promote like the late night shows,
Speaker 3:you have to Please.
Speaker 4:We have we have a conference that we're putting on with Union Square and first round in Locks in New York called Founders NYC, and it's foundersnyc.co. It's free, which is different than most conferences. It's for people who want to start a company. We got the founders of Datadog and Mongo talking to each other on stage.
Speaker 1:That's To
Speaker 4:me, a collection of all the the big, great early companies that were built and scaled in New York coming on stage to just, like, sort of create the community effect of of building here. Awesome. And so if you Yeah.
Speaker 2:Do you wanna take a do you wanna take a victory lap on NYC? Just generally. No. No. I'm I'm just saying when you when you started BoxGroup It was of people make it maybe maybe
Speaker 4:No one had heard of we're like the the, you know, pioneers of New York City. Had heard
Speaker 1:of New York City
Speaker 4:before. Was that era No.
Speaker 1:But it was true about tech. Right?
Speaker 2:The amount of the capital concentration in New York City right now is Yeah. Incredible.
Speaker 1:It's like it's never been more
Speaker 4:We're we're like the pioneers that discovered Miami in the era. Yeah.
Speaker 1:Yeah. No, no, no, no.
Speaker 4:Look, I think New York's a home for people that want to win. I think whatever you do in New York, it's like an incredibly harsh environment. And in order to stand out and win in New York, you have to fight friction. No one cares. Right?
Speaker 4:And that's what's actually fascinating to me about tech in New York is, like, if you went on a subway or to the restaurant nearby, nobody cares what you're doing. Like, no one cares about your business. No one cares about tech. And I think that friction creates people to have to fight a bigger fight here. Yeah.
Speaker 4:Because there's not momentum. Like, there's not somebody pulling you up and saying, like, we're all in this together. And so I I think the community here is is just like people put their head down and grind, and it's produced some real success, and we're excited to put it all on stage.
Speaker 1:That's amazing. Well
Speaker 4:Thank you guys very much for
Speaker 2:having me.
Speaker 4:I'll see you tomorrow.
Speaker 2:Yeah. We'll see you back. We'll see you back here.
Speaker 1:Bye. Talk to you soon.
Speaker 4:Bye. Cheers.
Speaker 2:That's fantastic. Humble giant.
Speaker 1:Yeah. Overnight success himself. Yeah. Well, next up, we got Mike Vernal coming in from Conviction. Very excited to talk to him.
Speaker 1:We'll bring him in from the waiting room now. Mike, are you there? Can you hear me? How are you doing?
Speaker 3:I'm good. Thanks. How are you two?
Speaker 1:Doing great. We're fantastic.
Speaker 2:Great to
Speaker 1:have you. Yeah. It's a Thanks
Speaker 3:for having me.
Speaker 1:It's a wonderful Monday. I hope your Easter was well. If you celebrate, I hope your weekend was great, and I hope you're off to a great start of the week.
Speaker 3:Thanks. It was great.
Speaker 1:Yeah. Fantastic. Yeah. I I mean, I'd love to kick kick it off with just, a little bit of a little bit of background on your career and then what you're excited about today, and then we can kind of go from there. Does that sound good?
Speaker 3:Yeah. Sounds great. So let's see. My career. I've been I've been an investor for the past decade, kind of an accidental investor.
Speaker 3:Never aspired to this, but I I I sort of I spent fifteen years operating. I was at Facebook for many years and decided to give it a try, and it's been great. So I've been an investor for the past decade. I am, like I'm very motivated just by, like, individual founders and folks that I find compelling, and so, like, a pretty broad set of companies. So, like, a mix of consumer and like SaaS and hardware and infrastructure and some others.
Speaker 3:Some of the larger companies are companies like Rippling and Notion and Vercada and Clay and a couple others.
Speaker 1:Yeah. Just heard about Clay Yeah. Tisch. What was the what we, yeah. We we we we just heard about Clay.
Speaker 1:David Tisch from Boxster Design.
Speaker 3:Of Of
Speaker 1:saying, about how Clay was this, you know, overnight success that took seven years, as they usually do. I'd love to know the story of the first first investment that really made you catch the bug. Obviously, you were at Facebook for a long time, but then, at at some point, you were like, I got a knack for this, and I'm gonna take it more seriously.
Speaker 3:You know, I made a handful of angel investments before I, like, formally became an investor. Sure. But they were I think in retrospect, they're actually, like, they're they're pretty reasonable. Like, I only made a handful. I I probably made, like, seven or eight.
Speaker 3:One of them was Notion, which is probably the best of the bunch, but, like, Wealthfront. It was, like, Notion and Wealthfront and this company called Human Interest, which is like a four zero one k provider and a couple I know the CEO. Say again?
Speaker 1:I I I I'm like randomly friends with Jeff Schneebly who runs the company now. It's a fascinating story because it was a YC company and then Yes. He came in as a as like a founder mode CEO, but he had like like his background I mean, I I love him, but it's like not super he's he didn't start the company. He has a MBA and I believe he has a PhD and he's almost like a manager mode type of guy, he's been fantastically successful with the company, and I'm just the biggest fan. Anyway, sorry.
Speaker 3:Yeah. No. No. Exactly. Exactly.
Speaker 3:But I I think none of them really motivated me to do it. It was more I so I was lucky enough to join Facebook when I was relatively early, like, few hundred people, and I was there for eight or nine years. And I I led a mix of sort of product and engineering at the company. And I was my wife and I had our first kid, and it was the first time that I'd I took, like, six weeks off for paternity leave. And it was a little bit of a it was, like, the first chance to catch my breath in eight or nine years, and I was trying to figure out, like, what I wanted to do next.
Speaker 3:And the obvious thing would have been to stay at Facebook, and Facebook is was and I think still is just one of the most amazing companies out there. But I've gotten to know a guy named Brian Schrier at Sequoia, and Brian was Brian had actually backed two of my close friends at the series a, a guy named Matt McGinniss, who's now the COO at Rippling
Speaker 2:That's right.
Speaker 3:And Steve Garrity, at a company called Hearsay. And Brian, had kinda said if at some point you decide to pop your head up and do something else, you should come come talk to us. And so one thing led to another, and I ended up at Sequoia. And it was a little bit of an experiment to just see if investing was would be fun and interesting. And as it turns out, it is both fun and interesting.
Speaker 3:So
Speaker 2:How did you you know, people talk about quote unquote operate you know, investors love to say if they've spent, you know, two years at a company, they love to say they've had operating experience. You had some very real operating experience at Facebook. How did you feel how did you feel how how durable were the learnings from the true operating experience versus finding sort of common truths about the way to do business and the way to build products and teams that, you know because because because I've found, like, for example, like, the influencer marketing that I maybe did in 2016, like, no longer works. Right? And Mhmm.
Speaker 2:But yet there were things that I learned in that era that, you know, still use Right? So how do how do you kind of delineate like, you know, sort of like a higher level of abstraction? Yeah. Higher level sort of these sort of Lindy ways of doing things that are durable and valuable to communicate to entrepreneurs that you back.
Speaker 3:Yeah. It's a great question. I will say one thing that I think I learned that still applies and one thing I had no clue about, which I didn't learn until, like, the investing side of things. I think one thing one thing that's underrated, maybe it's not underrated, about Mark at Facebook is he's incredibly patient. I mean, I guess you kinda see it.
Speaker 3:I think he's, like, spent $80,000,000,000 so so far on, like, Reality Labs.
Speaker 1:Yeah.
Speaker 3:But I think, you know, he is he is at the same time both, like, patient and impatient. I I mean, everyone talks about, like, the move fast break things, and I think there is, like, I think, like, a very strong bias towards action and just, like, getting getting stuff done. But he also, like, from a first principles perspective, kind of if something should work, like, something logically makes sense, he will just keep playing it out to try to to, until there's, like, new data that suggests that it that it is wrong, which I think explains a lot of the Reality Labs investment. And I think, like, I think one thing that's underappreciated about, like, a lot of great companies maybe it's appreciated. I don't know.
Speaker 3:But, like, they take a long time. Like, I mean, some companies are really fast and off to the races, but, like, you know, Figma was, like, four or five years before it started to work. Notion was, like, four or five years before it started to work. Clay was four or five years before before it started to work. I think Airtable, like, was founded in 2010 and didn't really sort of break out until maybe 2017, '20 '18.
Speaker 3:I mean, all this sort of the PLG companies, you know, everyone's everyone says they, like, wanna be a PLG company, which to me is like, yes. I want to be a high growth company. That is a
Speaker 2:I don't wanna have to do sales. I wanna grow quick quickly without doing sales too.
Speaker 3:Yeah. Exactly. Exactly. It's like, I also wanna be born rich and handsome, but, you know, what are you gonna do? The it's it it takes I mean, these companies just take a lot of big time, and I think I think if you've operated for a while and you've seen how like, if you visually understand patients and, like, if you're if you're doing random stuff or if you're, like, literally, there's no hope, then you should probably throw in the towel.
Speaker 3:But in lot of cases, if you're doing the right thing and it just hasn't hit yet, you just kinda sort of you gotta play out another, play out some more cards. And I do think I've observed a lot of financial investors having a like, if it's not up into the right three months in, it's like, oh, man, we made a mistake and, like, what the hell are you doing? Or I was talking to your founder recently who has, like, a financial investor on the board now, and they were like, your competitor is, you know, at 5,000,000 in ARR. Why aren't you at 5,000,000 in ARR yet? Which is like, I I get it on one level, but on another level, like, you just gotta I think I I think you gotta make sure you're doing the right thing and sort of doing it in the right way.
Speaker 3:So I think that was one lesson that definitely carried over for operating, which I I think you kind of don't have until I think it's correlated with people who have done it and and sort of understand the the messiness of building something. I will say conversely, at both I mean, was at Microsoft before Facebook, and in both cases, you're pretty insulated from, like, the market you're operating in. Like, I think once you get to a certain scale, the you're you're kind of just thinking about how to build new things for your existing customers as opposed to how to really, like, start in brand new markets. And so I had no real intuition for how to, like, evaluate a business and whether it was a good business and or a bad business and if it was how to think about the like, I there were obviously sales and marketing teams at both Microsoft and Facebook, but you don't really build an intuition for how to, like, attack a new business category, I think, unless you worked at a start up. So that that was all new to me.
Speaker 2:I have a question. I've I've heard founders bring up the example of Figma as a company that took a long time to get a product out into the market and get, you know, traction. It was what was like four or five years until the first million of ARR. And I've heard founders use that as a reference point and be like, we're doing the Figma thing. Like, it's gonna take a while.
Speaker 2:And I'm like, no, you're not. They were doing something that was like fundamentally, you know, very technically difficult leveraging a new technology when there was no not a they were operating in a space that maybe wasn't hot for different reasons like, you know, sort of cloud design collaboration, you know, you you had I'm sure there was other players, but they had sort of four years to be
Speaker 1:Multiplayer wasn't a trend.
Speaker 2:Multiplayer wasn't a thing. They sort of created that. So what what would you say to founders that that tell you, you know, oh, yeah. We're doing this, but then you look at the market and you say, well, you have four or five other companies that are have sort of more advanced feature sets maybe and and are high you know, it's highly competitive. And I feel like that having the opportunity to do the Figma thing is like a luxury of being, like, very early
Speaker 1:to that. You gotta be Dylan to to earn that.
Speaker 3:Yeah. I mean, I I don't think yeah. If anyone came in and said it was gonna take, like, four or five years to build Figma, I don't one, I don't think anyone would build Figma. Two, I don't think anyone would fund Figma. I I think there's an element of like, you you have to I think you have to be moving quickly in the short term.
Speaker 3:Like, anyone you know, sometimes founders will come in and say I mean, what is it? It's April, and they will be like, oh, yeah. We will be ready to launch at the end of the year. And unless you're, like, taping out silicon or something, that that scares the crap out of me because, I mean, I know there's a lot of time between now and the end of the year. Yeah.
Speaker 3:And so I I think you want someone that is just, like, iterating at an insane clock speed and, like, learning at every iteration. And I though I think those iterations have to be pretty fast. But, like, sometimes you just don't know when it's going to start to catch. And so I I know the Figma story lasts well than than some of these others, but it's you know, you're just talking to David and you
Speaker 2:you Oh, Notion Notion's a good example too, right? Yeah. Gonna say that they were toiling away, you know, doing some, you know, in in relative obscurity till they found the thing that really was magical.
Speaker 3:Yeah. One of my favorite set of videos, you can find it online, is there's like a Notion product demo from I think late twenty thirteen. And it's this it's like this low code, no code environment. There's all these blocks. There's like a Stripe block so you can, like, drop payments in.
Speaker 3:Like, it's a pretty, it's a it's a pretty wild demo, because you see, like, the through line from today to what it was back then, and it's clear, like, all all the ideas are basically the same. It's like this canvas, and it's got blocks, and you can drop all this stuff in. But, of course, like, the first iteration was, like, wildly complex, and no one, no one really used it other than, like, a handful of, like, diehard folks that that that that figured it out. And so, of course, like, the rethinking of it was, okay. We'll make this an, like, an insanely great note taking app and then go from there and note taking to Ricky and the like.
Speaker 3:And I Notion's an interesting example because I think, there's, like, incredible stubbornness on the vision. And I think, like, what Ivan has been trying to build has, like, not changed in twelve or thirteen years. But there was, like, a lot of flexibility on tactics, and it was like, okay. This thing didn't work. Let's try it again.
Speaker 3:Let's try it again until something caught. And I think that's kind of the like, the the the art of it is, like, have a really clear vision of where you're, like, what you're trying to build over a five to ten year window and then but just move insanely quickly and be willing to, like, constantly change tactics.
Speaker 1:I've been super Makes sense. Excited about the idea of a email client built ground up around AI. Yeah. It seems like an obvious startup idea. We saw, like, the the Mailbox era where Dropbox bought mailbox, and there was a new email client startup every few years.
Speaker 1:Now we're in this dangerous territory where, you know, you have a company like Notion where founder mode CEO at the helm, plenty of resources, clearly not asleep at the wheel, understands what AI is capable of. But as a as a product manager or just a user of email, how do you think about AI in the context of email? What are you hoping for? I have an idea in my head of what I want, but I think I might be wrong, just because that's the nature of these things. So how would you break down that problem?
Speaker 1:How do you think about AI email?
Speaker 3:Yeah. I think actually, this is one I've I've thought a decent amount about. Actually, in the beginning so if I go back, like, two years ago, two and a half years ago, my, like, theory of the world of, like, where what what would be interesting to invest in was there's kinda, like, three levels of the stack. There's kinda, like, the foundation models at the problem. There's all at the bottom, there's, like, dev tools and infrastructure in the middle, and then there's, like, applications at the top.
Speaker 3:And I was, like, generally pretty pessimistic on the dev tools and infrastructure space because I think it's just moving really quickly. At the app the application layer seemed like the obvious place to invest, and you can kind of subdivide the application layer into, like, I would say, like, head, torso, and tail or, like, horizontal and vertical, however you wanna split it. And I was actually pretty skeptical at the time. It like, it was clear to me, like, I should not be writing my own emails in 2025 or to, like, a very small degree. Like, there is a massive amount of corpus.
Speaker 3:I've had in, like, a Gmail account for twenty one years at this point.
Speaker 1:Yeah.
Speaker 3:Like, it should just be able to write every single email for me. But it's 2025, and I'm still writing my own emails. Like, it it maybe gives me, like, two word completions. Yeah. And I think I have two two conclusions from this.
Speaker 3:One is, like, the large tech companies are just, I think, way too risk averse to build anything good here.
Speaker 1:Yeah.
Speaker 3:Like, I I like, this Google App must be able to build this. Like, it it's just it seems like a very trivial problem. I assume, like, the risk of me accidentally saying something really offensive in email is just too high for them to launch anything here. Yep. And so I like and I think that's kind of true writ large.
Speaker 3:Like, there is also, like, there is not a great assistant experience yet. Like, Siri is still pretty bad. You can get like, the Meta AI assistant is actually pretty good if you're wearing, like, the Meta glasses, but you have to wear the glasses to use it. And so I actually think the horizontal, like, experiences are addressable by startups now because I I think the big tech companies are just gonna be too conservative. And then in terms of, like, the experience that I want, I mean, I I don't actually want I don't really want I'm, like, pretty good at email.
Speaker 3:I'm, like, I'm I'm a very diligent person. I, like, go through all of my emails. I get a lot of them. Reading them is, like, pretty fast. I don't need it to be summarized.
Speaker 3:If someone sends me a really long email, like, I'm probably not gonna read it anyway. Like, I don't need it summarized. Like, it is a negative signal if you send a very long email. Yep. The the hard work is replying to them, and if something could just give like, read the thing and, like, write exactly what I was gonna write, that would be an amazing experience, especially if that worked on mobile because, like, composing on mobile is a total pain in the ass.
Speaker 3:Yep. And so I'm amazed someone hasn't built that yet. It it doesn't seem like, there seem like there are a lot of hard problems out there. That does not seem like the hardest problem. And so I'm I'm I'm surprised.
Speaker 1:Yeah. We're I mean, we're seeing a lot of, like, bolt on AI narratives in the public markets. Are you seeing, the AI narratives take hold in the fundraising around like scale ups, growth stage companies that aren't AI native companies, but they make so much sense in the context of of AI?
Speaker 3:I don't know. That's a good question. I, like, I think AI is, like, very core to Notion, for instance. And so I think Notion has, like, a has, like, a very deep advantage here. Mhmm.
Speaker 3:And I think it's just, the next evolution of Notion. I think I don't know. I don't know if I have enough data points on this. I mean Sure. The thing about AI in my view is, like, it is not to I never went to business school, so I may get the definitions of all this wrong.
Speaker 3:It's a layperson's understanding. But, like, in the sustaining versus disruptive innovation, I think AI is, like, pretty clearly a sustaining innovation in almost all cases. Sure. I think it, like, might be disruptive to Google.
Speaker 1:Yep.
Speaker 3:And so assuming, like, a scale up is still competent and can still build new product, I think they can just kind of, adopt this stuff as opposed to being disrupted by it.
Speaker 1:So Yeah. This is the, Salesforce for mobile was just Salesforce.
Speaker 3:Yeah.
Speaker 1:Yeah. Yeah. And so, yeah, you could imagine that Salesforce AI winds up working potentially or at least they'll they'll hold on to that for a while. But it it is a fun time because at least at at the very least, it's like a new battle for everyone to fight out. Like, you know, the Gmail team needs to pay attention because Notion's coming for them.
Speaker 1:I love to see it.
Speaker 2:Do you recommend sabbaticals?
Speaker 1:Oh,
Speaker 3:yeah. I most definitely do. I had never so I had like worked continuously from when I was 14 years old. I, like, worked at a startup in high school and college, and then I took off, like, a week between college and Microsoft and, like, three days between Microsoft and Facebook and a week between maybe it was ten days between Facebook and Sequoia. I took off almost two years.
Speaker 3:I I say took off because I I kept, like, 15 boards, and so I was on, like, thirty hours of board board meetings and one on ones a week. But it was still amazing. I got to, like, play baseball with my kids almost every day. Now they're pretty good at baseball. I knew nothing about baseball, and so now I know something.
Speaker 3:And I was I I think I was terrified that I would just be, like, irrelevant after taking some time off, but I don't know, maybe I am, but it was like, it was it was very
Speaker 1:Still got it.
Speaker 2:Still got it.
Speaker 3:It was amazing. And I I just like I would rather like getting to hang out with my kids is like the best thing in the world, so.
Speaker 2:I feel like saying that you're on a sabbatical allows you to release the FOMO, which like as an investor, there's probably no stronger force. Right? Yes. It's like the founder wants to talk and
Speaker 1:Oh, should probably take this call.
Speaker 2:Why why why conviction and why why partner with Sarah? I have a bunch of like, you know, guesses but I I'm assuming you could have basically gone anywhere, you know, any firm, you know, raised 500,000,000 out the gates on your own, you know, what whatever. So curious to hear.
Speaker 3:Well, I've known Sarah for a long time, almost a decade. Though I I recently discovered that she sent me, a LinkedIn message in, December 2016, which I did not see until, like, two weeks ago. Amazing. But I I I thankfully ran into her in other contexts. And I think my my theory on I I had spent a bunch of time thinking about emerging managers and, like, what is the right strategy for starting a new firm.
Speaker 3:And I think I I think one thing that is underappreciated or maybe I I certainly underappreciated for a long time is the degree to which, like, venture firms you know, there's this funny thing where, like, people who work in venture kind of get, like, a little bit ruffled when you call their thing a company instead of a firm because it's not a company. It's a firm. Yeah. But you know what? Like, firms and companies are, like, first cousins and they're they're all just organizations.
Speaker 3:And I think that, you know, if you're doing a startup, generally, you don't say I have an exception to this, but generally, don't say like, I'm just gonna go, like, build the next Google, like that that seems like a kind of crazy thing to do. You like, you start off with a market that seems kinda small. You dominate that market, then you expand to, like, the next tier of market and then the next tier of market, and suddenly you you build something gigantic. And I think the same thing is true in venture. Like, it's hard to just go out of the gate and be like, I'm going to be the next gigantic global multistage firm.
Speaker 3:I think you gotta, like, pick a market and go dominate that market and then sort of expand from there. And if you look at over the past, like, ten, fifteen, twenty years, the folks that I think have done this well, it's like Matt at Paradigm with crypto. It's Mickey at Ribbit with fintech. I and so I you know, AI was clearly gonna be
Speaker 2:A thing.
Speaker 3:The most important thing over, the next ten or twenty years. And so I think building a firm focused on AI and intelligent software and becoming the sort of preferred partner for founders in that category and then expanding from there seemed like the optimal strategy. And I think that's very much the founding thesis of conviction, and I think, like, Sarah and Pranav and the team here were off to an amazing start. So I've known them for a while. I think the thesis makes a ton of sense, and it's really fun.
Speaker 3:I think, like, one thing that is underappreciated in venture back to this, like, firms versus company thing is, like, venture is fundamentally predicated on the idea that there are things that, like, a two year old startup can do that, like, are hard for a fifty year old company. But then when you, like but venture is, like, not always that introspective about itself. So I I think there is a belief that there are things that, like, a two, three, four year old startup that is in founder mode can do that maybe a thirty, forty, fifty, sixty, seventy year old venture firm cannot.
Speaker 1:So so so when's the IPO? I know Hey. The Jason's going out. General Catalyst, we're hearing rumors about.
Speaker 2:Conviction. I'd
Speaker 1:I'd like to see that
Speaker 2:with you for How have you what's your broad I'd I'd love to give you a few minutes to talk about enterprise adoption of AI. Mhmm. We talked last week about how Johnson and Johnson had basically piloted, you know, 30 plus different AI tools.
Speaker 1:Wasn't it like
Speaker 2:600? Have been like 300. I might have it off by like an order of magnitude. It was like they basically tried hundreds of tools across different teams.
Speaker 1:It was called like a
Speaker 2:thousand basically culling, you know, culling, you know, a bunch of stuff that was cool but didn't quite work. What are what are you seeing as somebody who is, I'm sure at times, a big buyer on the other side at at Facebook?
Speaker 3:Well, I mean, certainly, there are there are things that are working, like, obviously, Cursor Cursor is working in a gigantic way. I think Harvey is working in a gigantic way. Decagon and Sierra seem like they're they're doing really, really well. I I I caught some of the conversation you were having with David right before this and you guys were talking about rappers a little bit.
Speaker 4:Mhmm.
Speaker 3:I like I I don't love the term rappers and to me there's like back to like the bottom, middle, top thing, you can kind of like if you're gonna build an interesting company, I think you either have to attack it from you have the handful of researchers that can literally push the state of the art forward, which is like maybe eight organizations in the world, or you know and understand and, like, love and can serve a type of customer better than anyone else in the world and just, like, build down from the customers. You're either, like, building up from the technology or building down from the customer. And so I I mean, I think that the companies that are working, I think, just, like, deep just have really good taste and, like, deeply understand what their buyers, like, what the cuss the customers need and are figuring out how to, like, adapt the technology to that. And then I think there's a bunch of folks that are, like, not or kind of, like, hypothesizing what people might need but don't don't, like, viscerally understand it either because they haven't worked it or they're just, they they haven't figured it out yet, and I think that's the stuff that is probably churning.
Speaker 3:But, I mean, I think it's kinda standard at this point in the cycle. Like, some things things are working, some things are not. I think more things will work. I think the defining characteristic will be, like, a deep focus on the customer, like, the the buyer and, like, building a great product for them.
Speaker 2:Do you expect big tech broadly to get more and more acquisitive? We were talking with David too around, you know, just this era maybe ten, fifteen years ago when you had companies buying, you know, a single big tech company, even a Twitter would buy many many many companies and it was probably healthy for the ecosystem broadly. And then, you know, now, you know, on the show last week, we spent a bunch of time talking about, you know, the FTC's, you know, what they're doing to Meta around something that happened, you know, many many, you know, over a decade ago. But I'm curious, you know, what what's your outlook on on m and a?
Speaker 3:I mean, hope so. I mean, I think all the I think it all got shut down just due to government action, and I think, like, misplaced government action. I mean, I I I think there hasn't really been anything interesting on the consumer front in over a decade, like, probably I mean, if you ignore TikTok, and TikTok has, like, a million asterisks, next to it. There I mean, it's basically ChatGPT, I guess, and ChatGPT is obviously super interesting, but there haven't you know, if you look at the 02/2008, '2 thousand '9, '2 thousand '10 era, there was Instagram, there was Snapchat, there was WhatsApp, there was Uber, there was Lyft, there was DoorDash, there was Instacart, and part of that is just like the mobile phone and obviously, like, all the change that that ushered in. But I I think part of the problem is especially starting around maybe it's probably 2016, '20 '17, there was just this crackdown on the ability to do acquisitions by big tech.
Speaker 3:And, I mean, especially for consumer, consumer has the this property that, like, very, very, very few things are going to work. But, if it works, it works really big. But if it doesn't work, it's often, like, really talented entrepreneurial founders that can then either, like, take what they've built to a larger company and adapt it for that or work on something outside that larger company. And if you shut down the outs for those consumer companies, like, eventually, people just stop funding them. So, like, every year, some venture capitalist is like, this is the year that consumer is back, and I just I don't think consumer will fully be back until either there's, like, some massive platform shift or, like those companies can get acquired.
Speaker 2:Speaking of speaking of consumer, I'd be interested to get your thoughts on consumer agents. I was talking with a founder last week that had an idea for a consumer agent in the insurance space, and it was a great idea. Seemed like it'd be a very, very valuable product. And I knew right I basically explained my point of view is that even if OpenAI is not explicitly saying that they're they're gonna do this specific use case. The sort of natural evolution is that at some point, you will be able to use OpenAI to do a series of tasks like he was describing.
Speaker 2:How do you think of the con do you see opportunities in consumer agents broadly or given the foundation model's sort of emphasis on the application layer and building consumer products that it's sort of a dangerous path to be building on?
Speaker 3:Yeah. I thought for a while, there seems like there's some intrinsic tension between between being a great research lab and being a great product company. Like, the with the exception of OpenAI, like, most of the other folks haven't shipped that much product. Anthropic is starting to ship some product, and then OpenAI has had some complexity over the past couple of years. I I think I don't know.
Speaker 3:I think there may just be some, like, intrinsic tension between being great at research and great at product, and I think that is good news for founders that are building, like, horizontal products. And so I do think I mean, this is kinda like the email thing. There's no there's no great, like, AI assistant yet for people, and it seems like it is a thing that is possible to build. I think the more general purpose you are, like, if you were building something literally for multiple billions of people, I think the higher the likelihood that you're, like, in a really square dead conflict with the foundation model providers. But I think I mean, this goes back to the, like, building down from the customer.
Speaker 3:If there's some set of customers you can go build for that is even hundreds of millions of people, I think I know, like, a a company a a lab like OpenAI has like, they have so many important things to work on. Like, there has to be and I have incredible respect for for OpenAI. But it's like, if you have some strict stack ranking of the teams within OpenAI, like, only 10 problems can have, like, the top 10 teams on it. And so if you're any if you are doing anything after, the top 10 problems that they have, then you're, by definition, don't have one of the top 10 teams working on it. That seems like an opportunity for a startup.
Speaker 2:An opportunity. Yeah.
Speaker 1:Well It's a great conversation.
Speaker 2:I have a lot more questions.
Speaker 1:Yeah. Yeah. We'd love to have you back soon because I mean, you can just talk about everything that's going on. It's amazing. We really appreciate you taking the time.
Speaker 1:So Yeah. Thanks so for
Speaker 3:having me. Okay. Cheers.
Speaker 2:Have good one.
Speaker 1:We'll talk to you soon.
Speaker 2:Bye. Bye.
Speaker 1:Next up, we got Edward Mayer from I'm gonna mispronounce it. It's I think it's Machina Labs. I got it wrong the last time I tried to pronounce a word like that. But we'll hear it from him. He's got a bunch of a bunch of interesting topics and he is going to talk to us about a bunch of stuff.
Speaker 1:Let's bring Ed in and then we will have him introduce the company so I don't mess anything up and we'll go from there. Ed, how are doing? Hey, guys. Good to see you.
Speaker 2:What's going on?
Speaker 1:Would you mind just, kicking off a little background on the company? Maybe how you pronounce it. It's Makena Labs. Right?
Speaker 7:Yeah. You're right. Makena Labs.
Speaker 1:Fantastic. And, yeah, just give us a brief overview for the listeners.
Speaker 7:Yeah. For sure. You know, I think MakiLaz's response to something that maybe actually Peter Thiel said once. Right? Mhmm.
Speaker 7:I I I'm I don't wanna butcher it, but it was along the lines of, like, you know, we wanted flying cars. We ended up getting, you know, 40 characters. Right? Which kinda comes down to the cornerstone of, like, okay. Software develops really fast.
Speaker 7:Mhmm. Hardware doesn't. I think, you know, some people interpret that as a, you know, something that says, oh, look. We don't have as much glass doing the hardware side. But reality is there's a lot of technological challenges in terms of, building building hardware.
Speaker 7:Right? So what we're trying to do at Machin Labs is just making that much easier. Right? You know, if you're a software developer, you know, two people can develop a program, you know, rent server from AWS, Amazon, deploy it. If you wanna build a hardware, you pretty much have to go build a factory.
Speaker 7:Right? Yep. And and that's why development timelines are, like, seven years, nine years. So what we're doing at Makena is we're using robotics and artificial intelligence to build the, basically, what we call the robotic And it's a robotic system that can do different types of manufacturing operations, and it's powered by AI. Basically, it can figure out how to pick up different tools, do different types of operation to make different types of parts, physical parts, without anybody having to program it or having to handhold it or build tools for it.
Speaker 1:And can you talk about, the specific kind of, like, first instantiation of the thesis? I saw Justin Lopez over at, Base Power posting, and it looked like he used a picture of your warehouse. Is that you guys? Is that right?
Speaker 4:That is
Speaker 1:us. Oh, yeah. And so he breaks he breaks the new, the new manufacturing space down into three categories, manufacturing SaaS companies, make parts for other people companies, and change the way the part is made companies. And, which which one do you guys fit in? I think you're in the third.
Speaker 1:Right? The way the part is made. Developed a way to make stampings, complex geometry form sheet metal parts without dyes. And so, can you break us down, like, what is actually going on when this massive robotic arm is, like, pushing into this metal? Explain why this is important, how it works.
Speaker 7:Yeah. So we wanted to build a system we call the Robocraftsman. Right? And the idea was, like, where do we get started? And we started sheet forming.
Speaker 7:Sheet forming is largest metal processing sector today. I think it's, $280,000,000,000 industry. You know, most of the metal parts you see day to day are sheet metal parts. Like, you know, you're sitting in your car or you're, like, you know, you're in the sea of sheet metal. Every other car body is sheet metal for sheet metal parts or aircrafts or basically sheet metal cans.
Speaker 7:But today, it takes a very long time to get your first batch of parts in sheet metal world. Right? And then you have to go make dyes, put them in giant stamping presses, like four story tall buildings, and then stamp your your, you know, your parts out. So our first kind of application of being sheet forming, we have two robots that form, you know, start from a flat sheet of metal between two robots. They have these giant fingers that are super strong, but they can basically push and pull on the metal that form it into a very complex shape without the need for any any dyes or tooling.
Speaker 7:Basically, you know, you get your from idea to to the first part in matter of hours. Right? It's similar to how a potter forms a clay ball with their fingers. They're coming into the sheet, they form it, and and and shape it into different shapes. So, yes, it's a new paradigm, a new way of doing manufacturing, but it doesn't stop there.
Speaker 7:We're already doing, like, trimming. We're already doing slotting, hole making. So the robot can literally pick up another tool, figure out what it need to do with it to do the next operation, and does that. So today, less forming. It does a lot of subtractive work like trimming, hole making.
Speaker 7:It also does a lot of QC.
Speaker 2:Are you do you get worried there's been a ton of there's been an explosion of new manufacturing startups over the last couple years, you know, long since you guys started the company, many of which promising to automate with robots the creation of various products. We covered earlier today on the show just how hard it is to, like, manu for Nike to manufacture a shoe. Right? Which sounds somewhat trivial. Like, you know, humans have been make doing them for years.
Speaker 2:You should be able to maybe we should be able to do it with machines. But then in practice, it's like there's so many different factors down to temperature. Out of all, you know, when you look at manufacturing broadly or I I'm I'm assuming you have some type of framework for evaluating whether something like can be automated to the degree that people would like to see out of manufacturing or or areas that, you know, are basically shouldn't be touched. Right? Like, something like like shoes, which have infinite sizes and a bunch of different factors.
Speaker 7:Yeah. I think it's like a combination of, like, three things, like, market size opportunity and how how technology ready it is to to to be to be kinda disrupted. Right? So but, also, I think there's a lot of conversation around automation that that is in the previous paradigm. I think for now, for the first time, we have this concept of element, this concept of we can actually reason very complex sequence of operations Mhmm.
Speaker 7:As long as we can train the robots on that sequence of operation. So it comes down to what data do we have available to train the robots. We already figured out, okay, you know, neural networks, LLMs, these, transformers, if you give it enough data, it can actually they're in a very complicated complicated task. The real key was, okay. What where do we generate enough data?
Speaker 7:Where do we have enough data to train it?
Speaker 1:So it means and and, unfortunately, for a
Speaker 7:lot of manufacturing tasks, the data is not out there. Right? You cannot train a very complicated model on it. For, you know, for ChatGPT, the Internet had trove of free data that you could use to create a very complex, kinda chatbot. For us, coming up with right sequence to make car doors, or shoes doesn't exist.
Speaker 7:Yeah. So the key is, can you actually provide a solution that can scale with limited amount of data, with human intervention and limited amount of data so you can deploy it in the field and get enough enough traction so we can have now enough data that comes from your machines to train your model.
Speaker 1:Can you talk And that's why we went after Sheetform. Got it. Can you talk a little bit about the n, the NVIDIA announcement today? That's very exciting. Seems like it might be a little bit of, a side quest, or or is this, like, in the critical path to, you know, mass, mass production?
Speaker 7:Yeah. No. NVIDIA's today announcement was was a kind of little fun thing. NVIDIA's an investor in us.
Speaker 1:So Oh, cool.
Speaker 7:Fundamentally, they are very interested in what we are trying to do, you know, being able to capture data from physical phenomenon and build models that can manipulate the physical world. Cool. But I think we work with their artists in residence. It's actually those OpenAI's artists in residence that we work with NVIDIA collaboratively
Speaker 1:Fun.
Speaker 7:To really turn in just the artist speaking to a system into a piece of art. Right? So Alex, the artist that would work with us, basically spoke what he wanted to build, what sculpture he wanted to build, And the full stack of generating the code, running the robots, all were done autonomously. So from speech, from intent, all the way to the physical part That's without anybody ever touching anything.
Speaker 1:I love that. I I was I was when the when the Studio Ghibli moment happened, I was taking some photos of, like, my kids' playsets, Studio Ghiblifying them, and then immediately I wanted to print them out because I wanted to have some sort of, like, physical instantiation. Just showing the phone was, like, not satisfactory. So the idea of, like, speaking words and then getting like a sculpture out, that's that's sounds really awesome and futuristic. Yeah.
Speaker 1:Yeah. Go.
Speaker 2:How there's a lot of investment in humanoid robots
Speaker 1:Yep.
Speaker 2:Lately. Many of those promising to revolutionize manufacturing, replace human labor, automate the production of lots of things. As somebody who's been doing it with robots since 2019, how how do you think of that form factor in the context of manufacturing?
Speaker 7:Yeah. Actually, Super Bowl Super Bowl is on on on HeroX. Right? I think the question is, to to your point, is it gonna be is the first application gonna be in in manufacturing? I don't think so.
Speaker 7:Right? I think the biggest problem, if you wanna, like, think of a start up as, like, what do you need to derisk first? The first thing you give an example of, like, Nike figuring out how to do the shoe manufacturing. The first thing is actually intelligence. We have kinematic frameworks for a long time.
Speaker 7:You know, we could do what humans does in terms of kinematic freedom with industrial robots. We can actually do it more precisely with higher force with industrial robots, which was what we need in manufacturing setting. So the missing piece really was intelligence. We're kind of a little bit intelligence first. Right?
Speaker 7:We don't need to solve the joints. We don't need to solve people walking around, like robots walking around and, you know, having the human form factor. If you solve the intelligence, you have enough kinematic frameworks, which is industrial robots, to do what you need to do. But that being said, I think, you know, humanoids is huge opportunity, maybe not in manufacturing, but but downstream in homes and all other places that that that that can consume it.
Speaker 2:What is what is the, you know, I imagine you guys are a beneficiary from some of the tariff stuff in some way, but on the actual machine side, are you are, you know, you and the industry seeing challenges of like, you know, how much of, like, the actual robots that you guys are leveraging are are sourced, outside of the country and Yeah.
Speaker 1:Chris at Hadrian was saying, like, yeah. My CapEx goes up by 10%, but the Demand my demand is getting way, way higher. So what's been your experience?
Speaker 7:I mean, that's true. I mean, like, what we can what we do here so so the the challenge is for a lot of work that we do, and especially in the defense, aerospace defense, there is no industrial base. We have to do it. So demand is always there. Now 70% of our bomb is off the shelf, and we intentionally tried to do that so that we can actually finance it easily.
Speaker 7:Right? Use, you know, multi pusher pairs off the shelf equipment so that we can easily finance the full hardware stack. That being said, you know, a lot of the hardware that we use is either produced in America or it's in very, like, allied countries. For example, robots are produced in in in Japan. Mhmm.
Speaker 7:So the tariffs are a little bit more digestible there. But that being said, you know, we are one of the very few manufacturing companies that are, like, doing almost software like margins. Mhmm. So there is enough room for us to to be able to absorb that cost and still, you know, have a very high value, high margin business.
Speaker 2:Interesting. Is the idea on that note, is the idea you know, we've sent we've seen some investors kind of, you know, strictly software investors kind of poke fun at at VCs that are investing in manufacturing, you know, expecting software like margins and and there's sort of this sense that, well, manufacturing hasn't, for most things, hasn't historically had software like margins. You're seeing it today. How how do you think about the margin profile for advanced manufacturing over time even, you know, even in things that are, like, non chips. Right?
Speaker 7:Yeah. Yeah. So so so it's it's it's interesting arbitrage. I think there's a lot of people thinking about manufacturing solutions in different ways. I think you can think of it as automating what traditionally has been done, and I think that's usually end up being very low margin.
Speaker 7:Right? But if you're creating something new that, you know, has some kind of arbitrage on either labor or has some kind of arbitrage on equipment, right, in our case, whereas you don't have to make dyes. Right? And a dye a single dye for, you know, a car door can be up to a million dollars. Right?
Speaker 1:Mhmm.
Speaker 7:So for us, we're faster, but we get rid of that asset. So it allows us to have the, you know, at the same cost parity, have higher margin. But I think, yeah, down the road, the margins could erode, and that's why we're thinking about it as a platform. Right? It's a robotic system that can be forming today.
Speaker 7:Tomorrow, it's gonna be your next operation. It's gonna do bending. It's gonna do hemming. It's gonna do forging. Right?
Speaker 7:So you're constantly expanding the capabilities of the system, which allows you to sustain a very, larger volume business, as some of the margins of the older processes kind of erode. Right?
Speaker 3:Mhmm. Makes
Speaker 1:sense. Yeah. Last question. You you mentioned that you might have a Golden Dome take. We did a little deep dive.
Speaker 1:There wasn't a lot to dig into. I'm curious. It doesn't seem like it would interface with your business too much, but maybe you just have studied the industry. So what do you think is going on with the Golden Dome?
Speaker 2:He's making an actual dome.
Speaker 1:Dome. Yeah. Make a physical gold to
Speaker 2:go over The United States.
Speaker 1:I would love that.
Speaker 2:If you like the blue, get you know, enjoy the blue above us while you can. It's gonna just be all gold soon.
Speaker 1:Yeah. Yeah. Yeah. That's right. I mean, there was,
Speaker 7:like, people were talking about how it's, competing with a Golden Dome at Nordame, which is, like, an actual thing Yeah. In terms of the name naming conflict. No. So why do we actually fit into this paradigm? We we work a lot with the missile manufacturers, manufacturers, right, and manufacturing components within the body of the missile for them.
Speaker 7:Hypersonics is one of the main enablers of how we can actually have defense against some of these missile attacks.
Speaker 1:So Yeah. Yeah.
Speaker 7:For hypersonics, you need to start processing very complex materials. Mhmm. Materials that were traditionally very hard to to process. Think of, like Makes sense. High temperature alloys, like nickel
Speaker 1:Yep.
Speaker 7:Titanium. And and because of our robotic process, low cooling manipulates the material, we have way more control Mhmm. To process the material without getting to failure. For example, we can form titanium sheets without tearing it at room temperature, which is traditionally not possible. Right?
Speaker 7:So I think there's a lot of interesting opportunities there for us, and we're exploring with our, you know, with our primes
Speaker 1:Sure.
Speaker 7:That we work with. But, yeah, I mean, the whole concept of Golden Dome is gonna be interesting. You know, what I've heard last is it's gonna be 7% of the DoD budget in the next two, three years, right, once it becomes pro programmatic. Yeah. So that's that's what I what I've been hearing.
Speaker 7:Obviously, next year, we're looking at, like, I think, 20,000,000,000 on the missile defense. But over long term, I think the plan is roughly 7% of defense budget. So it it's gonna be a huge opportunity. And, obviously, I say something that's probably very necessary for me. But, yeah, we can dive into details, but I don't know how much time we have.
Speaker 1:No. No. No. I mean, I I think we'll have to have you back on when there's more details that emerge and we actually get, you know, a a deeper dive into how the, how the program record evolves, what the subcontractors might be looking at. Right now, all the all the names parties are no comments, so there's not too much to dig into for good reason.
Speaker 1:But it'll be super interesting to see how this, pans out. Jordy, anything?
Speaker 2:No. This was great.
Speaker 1:Yeah. We gotta have you back on soon, but, congratulations on all the success, and, I'd love to come see the the machines in action in person. Yeah. It was really amazing.
Speaker 7:Yeah. We're, like, we were half an hour away from downtown, so Downtown LA. Oh, awesome. What's a new Yeah.
Speaker 1:That'd awesome.
Speaker 2:It. I wanna I wanna do the show with with a robot.
Speaker 1:I want a robot to make us a bigger gong. Yeah. Yeah. Biggest gong possible.
Speaker 7:Gotta make it happen. We gotta make it happen. That's a success. We actually do very easily.
Speaker 1:I yeah. I can imagine. It's a perfect it's a match made to happen.
Speaker 2:Our people will talk to your people.
Speaker 1:Yeah. Our people will talk to your people. This is fantastic.
Speaker 2:Thanks for coming on.
Speaker 1:Thanks so much, Ed. We'll talk to soon. Next up, we got
Speaker 2:William Brown
Speaker 1:coming The
Speaker 2:idea of, like a like a 20 foot gong is very appealing to me.
Speaker 1:Very appealing. That you could have watched be made from the raw material.
Speaker 2:Yes.
Speaker 1:Be be perfect. Be perfect. And I mean, you could actually etch different things into it. There's so many cool things you could do with that technology. It's very, very awesome.
Speaker 1:Anyway, welcome to the show, Will.
Speaker 5:Hey. How's it going?
Speaker 1:Good to have you on here.
Speaker 4:Thank for having of
Speaker 1:your of your posts for a long time.
Speaker 2:One of the top many people have said one of the top post poster of
Speaker 1:the year. I think potential poster of the year, for sure. He's been burning up the timeline. Jordy, where where should we start?
Speaker 2:I mean, I have a bunch of I have a bunch of stuff that
Speaker 1:Let's do it.
Speaker 2:We can go through. I mean, we can just dive
Speaker 1:into it. Do you wanna give a brief intro on yourself and and who you are before we
Speaker 2:just Maybe we should start there.
Speaker 1:Start talking about the timeline?
Speaker 5:Sure. Yeah. Sounds good. I'm Will Brown. I'm a researcher at Morgan Stanley.
Speaker 5:By the way, nothing I say here is Morgan Stanley opinions. This is all me kind of just, like, sharing my thoughts.
Speaker 2:Sure. I think.
Speaker 5:I am a researcher. I work a lot on stuff related to LMs there. My background was in reinforcement learning theory. I did my PhD at Columbia. So I've been in New York City for a while.
Speaker 5:Big fan of New York City. Great things happening here all the time. And, yeah, I also just like like talking about the stuff on the Internet and, like, participating in the open source community. There's lots of, like, cool either projects or code bases or papers or models always coming out. And, I a lot of my job is, like, needing to know all that stuff and being a liaison essentially, like, from the Internet to the company where, like, people want to understand, like, okay.
Speaker 5:What's the latest model for x y z that I should be using? What's the right open source toolkit? Especially because, like, at a big regulated company, we need to understand the landscape, especially for things that are, like, downloadable off the shelf without needing to, like, onboard a vendor. Like, some things you onboard a vendor for, but it's also, like, a much heavier lift. And so, like, we need to, like, map the landscape of, like, what's the right tool for the job for everything LM related.
Speaker 5:And so that's a large part of what I do. And it was also, like, my excuse for being on Twitter all day.
Speaker 1:That's great.
Speaker 2:It's a great excuse.
Speaker 1:Where do you wanna start?
Speaker 2:Where, aside from x, like, where where are you getting signal without giving away without giving away all the alpha? Because I imagine, like, you know, by the time Dourkech has, like, done a podcast on something, like, you know, it's been the the information read the papers. You know, disseminated. It's not necessarily alpha.
Speaker 5:There's a surprising lot of alpha still on x just from places where you don't like like I said, there's places, I have not found much alpha on LinkedIn. Group chats, the Anons Yep. The open source, like GitHub discussions. Lots of really good stuff is buried in like a GitHub issue or like a feature request where someone's like, hey, this thing would be cool. Yeah.
Speaker 5:And these ideas are just all over the Internet, but you gotta like know where to look for them.
Speaker 1:Yep. That makes wanna talk about I I wanna talk about humor. You actually posted about this like a month ago or two months ago. You said it's interesting that 1,500,000,000 parameters is all you need to crush math competitions, but you need, like, 15,000,000,000,000 to make the model be funny. Maybe humor is the right measure of true intelligence.
Speaker 1:And for a long time, my eval has been tell me a funny joke. And every time there's a new model, it's tearing up x. And I ask her to tell a funny joke, it's always the worst joke I've ever heard. It's kind of an anti joke. But but but is that just a lack of of, like, of labeled data essentially?
Speaker 1:Or do you think there's something more, more, like, innately human to the idea of humor?
Speaker 5:I mean, I think humor is, like, really hard and it's also very hard to it is very hard to label
Speaker 1:Yep.
Speaker 5:But I think it's also really hard to like, okay. This is like a a big debate topic. Sure. It's like, would it like, I think people kind of assume, oh, just, like, train it on funny data. Yep.
Speaker 5:But, like, the things that make things funny are really subtle and pretty buried. I a friend of mine, coworker actually, did this experiment where he, like, he tried to, like, have one model be a judge of, like, is this funny or not? Yeah. And what they do is they, like, lean into things that feel funny, and then the results were actually kind of funny. But what it ended up just doing was swearing more.
Speaker 5:So, like Yep. If you swear a lot, models think that's funny.
Speaker 1:Mhmm.
Speaker 5:And so there's all these, like,
Speaker 1:kind of
Speaker 2:cheat
Speaker 5:like, there's a lot of cheat codes.
Speaker 1:Sure.
Speaker 5:And RL and training these models is, like, the path of these physicians is to find a cheat code. But, like, real humor, like, the people that to be really funny, you have to be really smart. Like, think of, like, your favorite comedian, like, Norm or Larry David or, like, all these people are, like, really smart. You can tell from the way that they compose jokes. Like, there's, like, an attention now.
Speaker 5:Like, attention is in, like, transformer attention of, like, ideas that need to combine in a very sparse, like, precise way to make a good joke. It's like, you can't just, like, shove things together. You kind of gotta thread the needle to make a joke land. It's not a very coarse mechanism. And so I think,
Speaker 2:like Yeah.
Speaker 5:GPT 4.5 is, like, ginormous model, trillions of parameters most likely. And that like, there's more room in the model to have these, like, little sparse connections materialize as you go through layers of the transformer. I just haven't seen anything like that come from a smaller model.
Speaker 1:How scale pilled are you based on the results from 4.5? Are you off to the races? Scale is all you need?
Speaker 5:Or Like you're
Speaker 1:Lawson pilled or what?
Speaker 5:I'm very RL scaling pilled. Like, I'm not big transformer pilled, really.
Speaker 1:Sure.
Speaker 2:Like
Speaker 1:training wall real?
Speaker 5:I think we don't like, is if there's another hundred trillion tokens of data sitting out there ready to train on, go for
Speaker 1:it. Yep.
Speaker 5:I don't know like, one, I think is, like, people should do some math and math about, like, how long until big GPUs are readily available. And it's it's, like, gonna gonna be a while before people can really run, like, even DeepSeek r one with, like, easy resources. Like, you can Sure. You can kinda do it on one node, but, like, the quality bump over things that are much smaller is just like like the we're hitting diminishing returns on capital investment is a lot of it. Like, they're taken out of the API because, like, the they can sell other things with the same GPUs and make more money is part of it.
Speaker 5:Like, it's a lot of compute to keep a model up like that. It's slow. Yep. And the things that it's better on are, like, not that economically viable. Mhmm.
Speaker 5:And so the sweet spot appears to be in this, like, between, like, 30,000,000,000 active parameters and or parameters total and, like, couple hundred maybe. But, like, I don't know that, like like, when Meta releases this Behemoth model, I don't think anyone's really gonna run Behemoth
Speaker 1:Sure.
Speaker 5:For, like, their day to day stuff. Yeah. It's just probably not gonna be worth it.
Speaker 1:So, I mean, given that, you know, Tyler Cowen's calling o three g AGI, like, the the the economic results of these, like, big but not crazy big models seems to be pretty good, running on a node. Should we be talking more about, hey. It's good enough. Let's bake it into an ASIC. Let's just bring down the inference cost to basically zero like we did with Bitcoin hashing and whatnot.
Speaker 1:Like, is that the conversation we should be having? Or should
Speaker 5:we I mean, think that's been that's kind of been how, like, Crocs or Ribus Anova are, like, playing that game. Yep. And I I think, like, those businesses make a lot of sense. Like, they can kind of say, okay. This version of a transformer, we're gonna be in this ballpark for a while.
Speaker 1:Yep.
Speaker 5:We can bake that into our plans a little bit. I think what's the next way, 2025, like, people have been saying you're the agents, but, like, what I think that means is agentic RL. Like, we're realizing RL works. Like, the reason o three is good is because it's trained to use tools. The way you train a model to use the right tool for the job is reinforcement learning, and they've said as much.
Speaker 5:Like, deep research, reinforcement learning. People have been throwing, like, random tools at models for two years, and it only now works. Even when the models are the same like, GPT four was a bigger model than a lot of the models that we are using now. It had just as much training data, but it was not or at least doesn't seem to have been RL ed in this specific way. And so that's kind of like my bet is, like, people are going to really want to train models to be agents, and I think you can get that to work well with a pretty small model.
Speaker 1:Does that mean, like, a flourishing of RL'd, big transformers for different tasks, or are we still searching for, like, the god model that can do everything all at once?
Speaker 5:I mean so okay. I think there's a a couple leaps we need to have models that can do everything all at once for, like, a super long amount of time. Mhmm. Like, my I tweeted something about this. Like, my what I I'm happy to call o three ten minute AGI.
Speaker 5:Mhmm. And I think, like, framing AGI in terms of, like, length of time it takes a human to do a task is, like, more reasonable than, like, a global framing.
Speaker 1:Like Sure.
Speaker 5:There's an a bar of, like, drop in a place for a human that we are, like, definitely not at yet, like, for general jobs. But most things a human can do in ten minutes, you can, like, get o three to do that pretty well. Mhmm. And so
Speaker 2:That's a very
Speaker 5:Like, think those even
Speaker 1:like that.
Speaker 2:Even, like, a web like, make a website in ten minutes. Okay. You have a good human designer is like It might be a probably could whip something
Speaker 1:up pretty
Speaker 2:quickly. Yeah.
Speaker 4:But But
Speaker 1:not like an entire design system that works together across all the different websites. Yeah. Makes a ton of sense. So so so seems like we're transformer maxing. We're RL maxing.
Speaker 1:Is there a new paradigm that you're excited about, program synthesis? Are we bringing back symbol manipulation at some point? Like, what what are we gonna pull from the tool chest to make this thing go to the next level?
Speaker 5:I mean, I think it's just tool calls. Like like, I think when people say program synthesis, like, we're already there. Like, o three is program synthesis, but the the programs are, like, JSON and Python.
Speaker 1:Yep.
Speaker 5:Like, you can do a lot with that. I would have I did some tests on, like, RKGI problems where you give the screenshot to o three and it can like basically figure it out in ten minutes of like zooming in and looking at the thing and then writing some code to see if it like reproduces the thing and like, it doesn't nail it, but I would've they haven't released the benchmark, but I would guess it'll do reasonably well. Yep. We reported as much.
Speaker 2:What are you seeing around AI adoption in finance broadly? I feel like we've been promised like, you know, somebody can just press a button and generate the deck and like generate, you know, 20 page investment memo and and are are are are these types of, you know, deep research style tools being used extremely heavily already or is there just even a greater now that they're being used, you know, hey. Let's go spend our time talking to, you know, three times as many experts so that we actually get proprietary kind of insight into the into the business?
Speaker 5:Great question. And I think there's a couple different answers I have. One is that, like, on one hand, we at least have been pretty, I think, fast at certain things at adoption. Like, the day GPT four launched, Morgan Stanley had integrations because we had been working on it and these were like we had press releases for these of like, we are ready to go. And so there are certain things where, like, initiatives can happen where effort comes together to make a thing ready to use.
Speaker 5:But the like, there's a long tail of smaller tasks that you do that you there's not a drop in replacement for. If there's a vendor, it would take a long time to onboard them, and it's not going to really solve the problem right away. And you could build something from scratch if you put a few people on for a few months, but, like, engineer your hands are, like, few and far between. And so I think the deep research is an example of a product that I would say, like, works really well for the thing it's built for. It's doesn't quite, like, do other stuff super well.
Speaker 5:Like, if you wanted to give you a table of, like, 50 very precise things, it's gonna make some mistakes there because the report format has a lot more room for, like, swap Yeah. Without it seem like seeming like notice to be bad. Mhmm. The PowerPoint Mike Microsoft PowerPoint Copilot is not great. It's not a thing that I have heard many people say saves them enough time.
Speaker 5:Mhmm.
Speaker 2:And you Yeah. Do you have do you have any takes on enterprise AI adoption broadly? We were talking, I think late last week about how Johnson and Johnson had tried hundreds of different tools. Like, they went through the effort to just like try a bunch of stuff because there was a top down mandate and now they're just like cutting probably 90% of Yeah. And so all the startups that were like, yeah.
Speaker 2:We have a
Speaker 1:Pilot with J and J. It's going great. Like, they won't churn. Well, 90% of them just churn maybe.
Speaker 5:Yeah. I mean, like, most of these pilots are very much intended to be churned. Like, they're not they're very much in a they're not being rolled out broadly. They are coming through in a kind of walled off environment for people who are, like, gonna be the beta testers. Yeah.
Speaker 5:And so, like, we have a crew of people who, like and I'm involved with this as well. Like, there as new stuff comes, like, online, we test it out. We give it feedback. Most of these do not convert, because, like, we're very willing to, like, try stuff, in terms of taking the call, in terms of, like, looking at a demo, but actually making a thing be part of, like, the company wide workflow is, a pretty heavy lift. Think of, like, onboarding a cloud provider.
Speaker 5:Like, lot of the reason like, maybe this is, like, one reason cloud providers have the margins that they do is because, like, moving clouds is really hard. Moving all your stuff from, like, AWS to Azure is a pain. I think especially in regulated industries, like, a lot of software onboarding faces the same sort of hurdles, where you can't just, like, bring it in and use it. You gotta, like, go through a whole process. And some companies are have kind of planned for that and some have not.
Speaker 5:So, like, one example is I think, like, a reason that Windsurf has been successful as a Cursor competitor is they lead they've leaned way harder on enterprise than Cursor has. Like, they have really designed for enterprise integration, whereas Cursor really has not.
Speaker 2:Do you was the Windsurf news surprising to you at all or was that just obvious OpenAI cares about coding and they should have a sort of dedicated enterprise, you know, coding
Speaker 5:I mean, it makes sense. Yeah. I think, like, to me, it felt like the a sign of there being some more friction with Microsoft. Because, like, originally, it was like, oh, they already have that as Copilot.
Speaker 1:Sure.
Speaker 5:And so this to me seems like them move taking a step away from Microsoft. But, I mean, this is just speculation. Yeah. It does make sense that it's Cursor and that is Windsurf and not. Oh, I mean, they did try to buy Windsurf supposedly.
Speaker 5:True. Like, I'm I'm a Cursor user. I think it's great. I haven't seen anything that really sold me on, like, go move to Windsurf. I'm sure it's fine.
Speaker 5:It's just like the bar to, like, switch for me is, like, I need a thing to have a a feature that's, like, killer that the other one doesn't have, and I have not, like, seen that yet, but I'm sure they have plenty of good stuff.
Speaker 1:What, now that we're, like, a couple months out from the deep seek moment, what is your takeaway? Is it something around kind of the the optimization of of of the inferencing these models, or, how how have you processed, that news now that we're a few months out?
Speaker 5:Yeah. I mean, they're, like, incredible engineering. Like, think a lot of their open source releases have really, like like, since r one, they've released a lot of code and details on their inference stack and training stack.
Speaker 1:Even seeing Sam already posting, like, hey. If you work for a high frequency trading firm, like, come work at OpenAI. And I read that as, like, oh, they wanna optimize their models now.
Speaker 5:Right. I think the some of the big players have realized they didn't have to that much. Like Of course. DeepSeek is serving all of China on 2,000 GPUs. It's kinda silly that Anthropic can't like, has to have the warning about, oh, we have high limits.
Speaker 5:Please try again later for, like, their paid users. Like, that's whereas, like, the deep sea chat is literally free anywhere. And so I I think some other people probably are working on upping their, inference efficiency game, but it's also, like, hard, because it's very model specific. Every model has some quirks, and you gotta optimize around that. It's hard to, like, have things be reliable and fall tolerant.
Speaker 5:So you And then also just
Speaker 1:So you think you can't just port back, like, FP eight? Wasn't that one of the, things or, like, the the the mixture of experts blocking, all those different things? Like, it seemed like there was some stuff that where it was, like, week two, we were getting, you know, analyses, and I was like, this will probably be open sourced and ported to Lama and all the others, like, pretty quickly. But has it played out differently?
Speaker 5:I mean, to me, the surprising thing was not any individual one thing. It's that each of these is maybe, like, a 30%, fifty % gain, but they have, like, ten, fifteen of them that all stacked.
Speaker 1:Sure.
Speaker 5:And so getting all of these to stack nicely is what's hard.
Speaker 1:That that's interesting. That's a great take.
Speaker 2:Yeah. That's interesting. What are you expecting out of Alibaba and and Quinn? Yeah. Three.
Speaker 5:Oh, I I mean, I'm really excited. Like, they make, I think, still the best model suites for, like, doing research. So, like, I do almost all of my experiments on Quyen models just because they have a bunch of them. There's, like, so many versions. Like, for every different model size, there's, like, seven different versions.
Speaker 5:There's, a code one, a math one, a multimodal one, an audio one, a base, and struct RL. Like, they really are optimizing for user friendly, like, open source model ecosystem Uh-huh. In a way that Lama was doing last year. This current year, we'll see if they can get their act together.
Speaker 1:So are they are are are they also, like, RL pilled at this point and and and moving
Speaker 5:away from this point? Like, they have a they have a reasoning model. The the reasoning model is not as impressive, like, but it's it is a pretty small one. It's like a 32,000,000,000 parameter model that, like, does well on math competitions. Cool.
Speaker 5:I don't know that anyone has really bitten the RL bullet in the way that DeepSeek did early and then OpenAI has been doing lately. Sure. Where they're really kind of betting like, OpenAI seems to be essentially betting on scaling up RL as the path. Yeah. And that it's not just longer reasoning, but it's reasoning integrated with system interaction.
Speaker 5:And
Speaker 1:I Sure.
Speaker 5:Like, that's kind of the drum I've been trying to beat for a while. Like, lot of the open source work I've been doing is around, multi turn tool calling RL. I think that we need better ecosystems for that. There's, like, very like, there's starting to be more tools you can go use, but for a while there was just nothing that supported this. Everyone was very RLHF pilled
Speaker 1:Yeah.
Speaker 5:For too long.
Speaker 1:Well, what what do you think is going on with Llama four? Did they just miss the memo about RL or, is there something else at work?
Speaker 5:I mean, doing this stuff at a huge company where a lot is on the line is hard, and it's way easier to do nothing than something.
Speaker 1:Sure.
Speaker 5:And Meta also, like, doesn't have to print money off of their models. Like, they don't, like, I think one analogy that I've been giving people is, like, why did Amazon not win NLP? They had, like, 10,000 people on in the Alexa team Sure. In, like, 2018.
Speaker 1:Yeah.
Speaker 5:And they have just now released, like, okay language models. Yeah. And they're really betting on Anthropic to drive their revenue there. Yeah.
Speaker 2:How are you thinking about the trade war in the context of the data center supply chain, and is that even in do you pay much attention to that, or is it kind of you're busy enough on on the model side?
Speaker 5:I do follow it. Yeah. I mean, I tend I listen to Dylan Patel talk a lot of stuff. He's great. Semi analysis.
Speaker 5:It's hard for me to, like, give a real take. I don't think think I think it's, like, important to keep an eye on. There's a lot of pieces of the supply chain, that will get I mean, it depends on what happens. Like Yeah. It's gonna get messy for sure, probably.
Speaker 5:But I I don't have, like, a a hard stance.
Speaker 2:You should become a VC, and then you can just give us Yeah.
Speaker 1:Yeah. Exactly. Yeah. He should he should flip over.
Speaker 2:No. I just think it's funny, like, in a year, we'll be like, bro, we were worried about the wrong Transformers.
Speaker 1:Yes. Yes. Yes. For sure with the energy thing. For sure.
Speaker 1:I I have one last question. How's the culture at Morgan Stanley? I mean, seems like talking to you, you sound like a Silicon Valley Founder, but you're at, like, a company that's, like, over a hundred years old. Is are are you part of a new guard, or has Morgan Stanley always been this way and you're just the first to kind of post about it?
Speaker 5:What's it like working there? I'm definitely, like, the first to, like, read a lot about it, but, like, the team I'm on has been around for maybe like, it's like a machine learning research team where we try to we try to be like a version a finance version of, like, an MSR or a Bell Labs where we are, like
Speaker 1:Sure.
Speaker 5:Off keeping up with the research. We write papers. We publish. We go to conferences. That's so sweet.
Speaker 5:Tend to we kind of hang around as, like, expert consultants. That's awesome. Advise on a lot of efforts throughout
Speaker 3:the company.
Speaker 5:And so the company has definitely been, like, betting on machine learning for a while.
Speaker 1:That's
Speaker 5:awesome. I think we are, like, probably ahead a lot of of a lot of, like, the quant firms in terms of the how early we were on realizing deep learning was important. And I think we've done a pretty good job at, like, keeping up with and following the, like, L and craze. Like, we were we partnered with OpenAI before ChatGPT.
Speaker 1:Wow. Wild.
Speaker 5:And yeah.
Speaker 1:That's amazing.
Speaker 2:Well, this was great. No. I was fantastic making a regular thing.
Speaker 1:Yeah. Yeah. This is fantastic. Yeah. I I definitely wanna have you back when there's a new new model release or something or a new paper For sure.
Speaker 1:Published. I
Speaker 5:I'm so excited to follow. If I can do a quick plug. In June, I will be at the Air Engineer World's Fair in SF giving a talk as a follow-up to my previous one.
Speaker 1:Very cool. I think we're going there. We'll see
Speaker 5:you there. Oh, sweet. Awesome. See you there. Yeah.
Speaker 5:And then also, I am doing a course of some kind soon, official announcement pending, but you really wanna like
Speaker 1:Just how to get rich quickly?
Speaker 5:Agents and RL stuff. Okay. Yes.
Speaker 1:So And
Speaker 5:so if you DM me your email, I'll put you on the list for more info.
Speaker 1:That sounds awesome. Awesome. Good luck with it. I'm excited. Cool.
Speaker 2:Yeah. This has been great.
Speaker 1:Yeah. Thanks so much.
Speaker 5:Talk to soon Thanks.
Speaker 2:Thanks for coming on.
Speaker 1:See you. We'll talk to you later. Bye. Bye. Should we go through some timeline and then get out of here?
Speaker 2:Yeah. You're a timeline addict.
Speaker 1:There's I mean, there's so many posts and we don't have enough time. There's so much in the Monday is always a stack day because you have a whole weekend of posts to catch up on. Of course. Adam Morancon says, you're coding at the bar. I'm drunk at the office.
Speaker 1:I respect that. I love that. Aiden says, the most the people I'm intellectually respect the most have quite lopsided output input ratio. They write, build, create more than they read, study or absorb. Geniuses are not sponges, they're volcanoes.
Speaker 1:I like that framing. That's interesting. But I'm I'm kind of going backwards. I like this one from Telmudic. The first time I heard of the GOMAD gallon of milk a day diet, I laughed my I laughed.
Speaker 1:There's no way I'm halving my milk intake for a diet. Gomad, what are you cutting? The idea that he's doing two gallons of milk a day, hilarious to me. Right. Timeline in turmoil.
Speaker 1:Timeline in turmoil this weekend. Paul Graham taking shots at Palantir saying you shouldn't work at Palantir. Gary Tan chimes in and says, is now an awkward time to mention I helped come up with the very first save the site the save the Shire t shirt at Palantir? Very, very funny. That's But, you know, we love we we love Palantir.
Speaker 1:We love PG's writing. And he is a foundational member of the the tech elite. But he gets he gets spicy with the political takes. He has strong political opinions and he brings them to the timeline. And,
Speaker 2:Well, like that
Speaker 1:It's Duke Duke so
Speaker 2:Gary and PG can have a little bit of fun.
Speaker 1:Yeah. Exactly. Love to see it. Web dev Mason always with some great takes. There's, there's some people, The Blue Origin story has really grown since we first covered it.
Speaker 1:Now people are very upset that Katy Perry went, said it was an affront to real astronauts. They didn't go all the way to space. They only went to the Karman line.
Speaker 2:Well, I saw people saying that, you know, how could you go to space when there's problems on Earth?
Speaker 1:Yes.
Speaker 2:And then you could also kind of extend that out to how could you do anything
Speaker 1:Exactly.
Speaker 2:There's problems on Earth?
Speaker 1:I think that's so funny because like, obviously, why are you wasting money on space when there's people that are hungry? But we literally talked to a farmer who was like, Starlink is increasing farming yields. So it's like, no, actually, like going to space and spending on like the crazy thing actually helped Yeah. People eat, which is great. But web dev Mason says, this is so sad.
Speaker 1:Dead culture stuff. Eject me into the timeline where she yanks the microphones in and shouts, I flew over our home world and saw us, the pale blue dot, the blessed sprouting seed of the Virgo super cluster. And I must report to every living soul that it is dope. So she wants she because the story is that Katy Perry now regrets going and says that there's been too much backlash. She says that she shouldn't have gone.
Speaker 1:But Mason says, no. Own it. Go and celebrate it because it is fantastic. Question about watches. We already talked about bezel.
Speaker 1:But is it appropriate to wear a Rolex GMT as an analyst? I love this answer. It says, it's it depends. Imagine your first all nighter. There you are burning the midnight oil when you decide to take off your Rolex GMT and place it on your desk to allow your wrist better control over the almighty Excel shortcuts you are about to employ.
Speaker 1:You take a look around, and what do you see? Every other analyst has placed their Patek Philippe Calatrava travel time in front of them for the exact same reason. Now if you, sir, are capable of bearing the overwhelming feeling of shame that will inevitably conquer you, then by all means, consider it absolutely appropriate. Hilarious. What a great post.
Speaker 1:Hilarious. Hilarious. Anyway, we should cover the VCs. The the what what's going on in higher ed at some point, but there was a good post by Connor. He says, VCs are attacking higher education.
Speaker 1:Trump squeezes higher ed funding. Universities sell PE holdings to fund their operations. VC funding dries up. I don't think this is actually gonna happen. What the the the news is that Yale is, like, selling off a portion of their venture capital portfolio, but I doubt that that really hasn't
Speaker 2:affected the
Speaker 1:VC funding landscape. And I don't think I don't think the university endowments are a major, major source. I think, like, pension funds are even bigger now and and and, like, sovereign wealth funds are even bigger.
Speaker 2:Yeah. And also very likely. Again, I doubt they're reacting to short term pressure. It's probably, you know, Yale selling $6,000,000,000 of secondaries probably is part of a larger strategy to generate liquidity on long duration Yep. Investments.
Speaker 2:Right?
Speaker 1:So here are some posts that I wanna follow-up on. We'll highlight them today, but we'll either have these folks on the show or do deep dives on these topics. Person of swag, Adam, says vibe sheeting. Is this anything? He's built Cursor for Microsoft Excel, going into the lion's den, competing directly with Microsoft co Copilot.
Speaker 1:But we just heard it that some of the Microsoft Copilot products are falling behind a little bit. And so I thought it was fun that he was, building a, like, plug in just into, Excel, and I could imagine this becoming a great company. So excited to talk to him about that and dive in deeper. Also, there's a new planet. Delian mentioned this.
Speaker 1:K two eighteen b. I did a whole, deep research report on k two eighteen b. Very, very fascinating. Interesting. I had Science gone.
Speaker 1:I had Chatuchipiti tell me an entire speculative science fiction story about how we might get to k two eighteen b. Spoiler alert, it's gonna be like five hundred years to get there, even at like point one c or something like that, bec which is the speed of light because it's so far away. But a multi generational
Speaker 2:shift could how many episodes we could do in 500 We
Speaker 1:do a lot.
Speaker 2:Quite a lot.
Speaker 1:Interestingly, I had ChatGPT. I was like, tell me a sci fi story and like, why don't you just make me the character in it? And it was very weird. And it was like, now you're in cryo sleep for a hundred years. It was like, now you're an old man.
Speaker 1:But because of life extension technologies, you're a 50 years old and, like, like, all like, your kids are now older than you because of this weird time thing. It was very fun. Very weird.
Speaker 2:Alright. A perfect show.
Speaker 1:Anyway, good luck. Last one is notable cap. This is a leak from Arthur Rock, Arthur Rock, series b to browser base. Right? Paul Klein, who's been on the show.
Speaker 1:So I
Speaker 2:assume you One last one last one from Nir. I like this one very Reminder of how far AGI goalposts have moved. It's from an old book
Speaker 1:Yep.
Speaker 2:Or something. It says, an AGI could beat you at chess, tell you a story, bake you a cake, describe a sheep and name three things larger than a lobster. It's also solidly the stuff of science fiction and most experts agree that AGI is many decades away from becoming reality, if it will become reality at all. So Wow. The last three models I use could describe a sheep.
Speaker 1:Couldn't bake you a cake though. Couldn't you Couldn't bake you a cake. But it can tell you how to bake a cake. It really can do all of those things and more. So, yeah, AGI's here.
Speaker 1:It's just get on with your life.
Speaker 2:Unevenly distributed.
Speaker 1:Yeah. Does that make
Speaker 2:sense? I was at the beach over the weekend and I was thinking to myself, I was looking around, I was like, none of these people are AGI pills. And then everybody went back to enjoying the beach.
Speaker 1:Yep. That's the nature of
Speaker 2:it. Anyways Anyways.
Speaker 1:Thank you for watching today. Yeah. We will see you tomorrow. We got great
Speaker 2:show for lined up.
Speaker 1:Bunch of news breaking, and we'll talk to you then. Bye.
Speaker 2:Looking forward to it. Cheers.