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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 Today is Tuesday, 07/29/2025. We are live from the TVPN Ultra Dome.
Speaker 2:Temple Of Technology. The Fortress Of Finance. Capital.
Speaker 1:We created a list of top AI researchers. It's called the Metis list and it's available. It's live now
Speaker 3:at
Speaker 1:metislist.com. Are the
Speaker 4:world's top
Speaker 1:AI researchers. We're of course experts in AI and AI researchers. So we are fully qualified to curate this list but we did have some help from some friends and we pulled some data. We looked at
Speaker 2:It was interesting that many of the people that we asked to do kind of like an Elo style ranking did not want to be named because nobody wants to be picking favorites
Speaker 1:Yeah. Yeah.
Speaker 2:Yeah. On the inside. But I think we put together a great list. It it's honestly some of the most impressive. There's people in the top 10 with no Dwarkash appearances.
Speaker 1:I don't know how that happens. It's crazy.
Speaker 2:How do they do it?
Speaker 1:You gotta get on Dwarkech. Yeah. We we we try to have some fun with this. We pulled some Google citations, some Google research citations, looked at some of their previous companies. This was of course based on the list which apparently has been going around Silicon Valley.
Speaker 1:Mark Zuckerberg has been you know, using this to recruit top AI researchers. We've been following the the trade war as Jordy put it earlier.
Speaker 2:We should have put a we should have put a buy it now price on here for for Zuck so you could just add to cart.
Speaker 1:Add to cart. Yeah. Just just create the super intelligence team directly on metaslist.com. Maybe that's how we monetize this thing.
Speaker 2:Yeah. It was good to see Alan Turing make the list.
Speaker 1:Fantastic. Yeah. Underrated. George Boole not doing so well. Inventor of Boolean logic but he did make the list.
Speaker 1:But I think he's sitting in the eighties not doing too well. Tyler, tell us more about the list. What do you think stands out? What'd you learn from the process? What was your methodology?
Speaker 1:How'd you build this thing?
Speaker 2:Yes. This is lot of fun. I I scraped most of Google Scholar like the top 5,000 people maybe.
Speaker 1:Mhmm.
Speaker 2:And then with some friends from from the big labs, I I kind of narrowed it down. Mhmm. You can see like a lot of the papers they've written interest stuff like that. Think another gem in there is Alan Turing. He's doing pretty well right now.
Speaker 2:He's let's see he's ranked number six.
Speaker 1:Six. Yeah. People love touring. I mean we passed his test and how long did his test stand? What sixty eighty years?
Speaker 1:Not bad.
Speaker 2:Something like that.
Speaker 1:That's longer than most benchmarks in evals. I feel like during
Speaker 2:Alan Turing versus goalpost. Yeah. Yeah.
Speaker 1:Wait. What were you about to say?
Speaker 2:Yeah. Mean it's the longest enduring benchmark I think.
Speaker 1:For sure. Eighty years. Yeah. Must be. But who knows?
Speaker 1:RKG IV three might be around eighty years. We might be here in '20 in in 2034 or something. Wait. No. 2120 I guess would be like the the Alan Turing test benchmark.
Speaker 1:We got John Schulman. Who else? Jurgen Schmid Huber's on here. Jeff Dean, one of the greatest to ever do it over at Google. He's been in Google for a long time.
Speaker 1:Still, no. Yes, a Dwarf Kesh appearance. Let's go.
Speaker 2:Let's go.
Speaker 1:It's good. Built MapReduce, Bigtable, TensorFlow. Yan Lagoons in here. You got all the different countries. Really wide representation Canada, UK, Australia, Russia, China.
Speaker 1:There's all sorts of people from all over coming together. A couple people without photos have been able to stay anonymous but most people we got their photo. Shalto Douglas. Good to see him on here. So this should be fun.
Speaker 1:Well, I'm sure we'll get a lot of feedback. Oh, Shalto ranked 56 but three Dwark hash appearances.
Speaker 2:There we go. How are you? Were you waiting? Were you waiting podcast appearances properly, Tyler?
Speaker 1:Yeah. He should be at the top.
Speaker 2:He wants to
Speaker 1:get score. Putting up numbers like that for sure. Yeah. For sure.
Speaker 2:Yeah. He's gonna be coming for Elliot's spot.
Speaker 1:Yeah. So this is a lot of fun. There's a there's an email sign up. You can you can drop your email at the top to learn about the next drop whatever we send out.
Speaker 2:That's right.
Speaker 1:Whenever we whenever we go live with stuff we will let you know first.
Speaker 2:And we're getting big into email soon by the way. Yes. Stay tuned for that.
Speaker 1:Very excited about that. And yeah. Hopefully this speeds up our trading card generation because be able to screenshot this and say this person's just got traded because it's moving fast and furious and we can't spend that much time handcrafting each of those trade deal trading card images. Exactly.
Speaker 2:Too quickly.
Speaker 1:Indeed. Indeed. There's there's a lot of stuff going on. Well, interesting related to Zuck. Did you know that the one of the kids at the IMO that was competing against OpenAI and DeepMind was named Alexander Wang.
Speaker 1:Wow. Great nominative determinism. Yeah. Future Alex Future. And speaking of iOS Yeah.
Speaker 2:People are calling him the the
Speaker 1:The Alexander Wang. The next
Speaker 2:Next in line.
Speaker 1:He does have an e. It's not a a it's not a l x e n d e. It's d e r instead of d r. So slightly different. But still, Alex Wagner, nonetheless.
Speaker 1:Well, let me tell you about ramp.com. Time is money saved. Both easy to use corporate cards, bill payments, accounting, and a whole lot more all in one place. And we just closed an account for RAMP. Do you wanna break down?
Speaker 1:What is this?
Speaker 2:So Cody over at Jones Road Beauty, the CEO over there which is a massive massive brand. Hundreds of millions of revenue.
Speaker 1:Fantastic business.
Speaker 2:And they're absolute dogs over there. Yep. He posted, my team has an in person demo with Ramp tomorrow. If they bring us a TBPN hat, I've instructed them to sign on the spot. Let's go.
Speaker 2:And Ramp posted a picture earlier today with the contract.
Speaker 1:They closed the deal.
Speaker 2:Love to see it. Cody, enjoy your hat. We're glad that you're gonna be wearing it. And, welcome to, welcome to team Ramp.
Speaker 1:Enjoy travel. Enjoy bill payments. Enjoy accounting.
Speaker 2:Easy to use corporate cards.
Speaker 1:Enjoy a whole lot more. Have fun with it. So yes. The Wall Street Journal has a has a deep dive on the IMO and what happened between Google DeepMind and OpenAI. Of course
Speaker 2:versus machine.
Speaker 1:Of course, DeepMind and OpenAI won gold medals at the Math Olympics. But these American teenagers still got higher scores. Absolutely mocked by a child. Will this be the last time humans outperform AI? And I think the answer is clearly yes, but it's still hilarious because, you know, there's so much attention on AI and it's so impressive and it's so great but but I mean we'll go and do it.
Speaker 1:Basically all the high schoolers are like, yeah, they're gonna get us next year but like we still got them this year. So anyway, from the This
Speaker 2:was the year this was the this will be one of the most meaningful wins. Right? Oh, totally. Like the passing of the torch.
Speaker 1:Maybe. I mean, I think that what goes into a meaningful win is more of like the drama and storyline behind it just like, you know, what's the reference? Computers beat humans at chess in 1997. Computers beat Go, humans at Go in 02/2016. Like there have been dramatic chess matches since 1997.
Speaker 2:Yeah.
Speaker 1:It's just a like you just assume the computers are the best at it but you move on and then you go back to like caring about what humans The players. The personalities. The players and the personalities. It is
Speaker 2:cool to think about what what the energy requirements would have been for the high schoolers to win OpenAI and Google. You have to imagine the high schoolers like peanut butter and jelly sandwich and I won gold. Google's like, we we use of Houston, Texas. Texas. The energy that Houston, Texas uses in a year in an hour.
Speaker 1:At least quite that
Speaker 2:dramatic. Not not that traumatic,
Speaker 1:of course. But but it is close.
Speaker 2:Probably more than a PB and J.
Speaker 1:So the Wall Street Journal says, the smartest AI models have ever made just went to the most prestigious competition for young mathematicians and managed to achieve the kind of breakthrough that once seemed miraculous. They still got beat by the world's brightest teenagers. Let's go. Let's go. Every year, a few 100 elite high school students from all over the planet gather at the International Mathematical Olympiad.
Speaker 1:That's the IMO. This year, those brilliant minds were joined by Google DeepMind and other companies in the business of artificial intelligence. They all had come for one of the ultimate tests of reasoning, logic, and creativity. The famously grueling IMO exam is held over two days and gives students three increasingly difficult problems a day and more than four hours to solve them. The questions can span algebra, geometry, number theory, combinatorics, and you can forget about answering them if you're not a math whiz, Jordy.
Speaker 1:You give your brain a workout just trying to understand them. Because those problems are both complex and unconventional, the annual math test has become a useful benchmark for measuring AI progress from one year to the next. In this age of rapid development, the leading research labs dreamed of a day their systems would be powerful enough to meet the standard for an IMO gold medal, which became the AI equivalent of a four minute mile. But nobody knew when they would reach that milestone or if they ever would until now. Scott Wu knew he called it out on our show in April.
Speaker 1:Also, me tell you about Restream, how we're streaming right now. We're using Restream one live stream 30 destinations, multi stream and reach your audience wherever they are. If you're trying to stream, get on restream. The unthinkable occurred earlier this month when an AI model from Google DeepMind earned a gold medal score at IMO by perfectly solving five out of the six problems, and we're gonna go into what happened with the sixth. In another dramatic twist, OpenAI also claimed gold despite not participating in the official event.
Speaker 1:This is the they were running the marathon in the parking lot strategy. Absolute dogs getting the press without needing to deal with all the red tape inside the stadium or buy a ticket.
Speaker 2:Yeah. Yeah. Winners win.
Speaker 1:Yeah. I'm in the Olympics. I'm I'm as fat. I'm I'm Usain Bolt. Usain Bolt in the parking lot.
Speaker 1:Don't worry about me. Don't ask questions.
Speaker 2:Yeah. It really is the the
Speaker 5:It's great.
Speaker 2:The way that they were able to get Yeah. Credit
Speaker 1:Yeah.
Speaker 2:For basically on the same level of Google
Speaker 1:Usually more on x. They went super viral at midnight on Friday, like the moment the exam closed. Like, they got a lot of the attention. And it's clear that they actually did the job, and they did. They was just like, you know, certain, you know, mechanics of, like, how they participated.
Speaker 1:And, like, does that really matter, or does the quality of the model matter? Really just the quality of the model. So I think that it makes sense to give them just as much credit here or Yeah. 99% as much credit. The companies describe their feats as giant leaps toward the future even if they're not quite there yet.
Speaker 1:In fact, the most remarkable part of this memorable event is that 26 students got higher scores on the IMO than the AI systems. 26. It's a lot. Them were four stars of the US team including a man named Tiger Zhang, a two time gold medalist from California and Alexander Tiger. Tiger.
Speaker 1:He's a Tiger Get this man a term sheet right now. Future enterprise SaaS builder. Yeah. For sure. Bounder.
Speaker 2:Easily deserving of 10 on a 100 pre seed
Speaker 5:out
Speaker 2:of the gates. Half in secondary. Yep. Secondary.
Speaker 1:Get him a term sheet immediately. Get him on Stripe Atlas immediately. Get him a Figma installation so he can design a software. He can think bigger, build faster. Figma helps design and development teams build great products together.
Speaker 2:That's right.
Speaker 1:Get started for free at figma.com.
Speaker 2:Also We built Metas list. We've created it with Figma make. Yep. So So you
Speaker 1:can go check it out.
Speaker 4:You can
Speaker 1:see our work in or Tyler's work. Our work. In action. Our work. Of course, if there's any backlash, we will be distancing ourselves from Tyler's work.
Speaker 2:And Tyler will be quickly terminated.
Speaker 1:We will not. I will I will fall on the sword.
Speaker 2:We will we will ride. We ride for Tyler.
Speaker 1:We do. We do.
Speaker 2:Until the end.
Speaker 1:So, Alexander Wang had a third straight back to back gold medal. He's from New Jersey. That makes him one of the most decorated young mathematicians of all time. He's just got three IMO gold medals hanging around his neck looking good.
Speaker 2:Just do that picture with like biting Yeah. But he's
Speaker 1:at the top.
Speaker 6:Yeah.
Speaker 4:He's at
Speaker 1:the top. Yeah. We're we're at the bottom spraying the champagne being like, yeah IMO. America. Yeah.
Speaker 1:America's back. He's a high school senior who can go for another IMO gold next year. So he could wind up being a four time gold medalist. That would be crazy. Maybe you gotta up that valuation at that point.
Speaker 1:Yeah. But in a year, he might be dealing with a different equation altogether. And he actually gave an interview to the Wall Street Journal. Alexander Wang says, not the Scala AI founder, not the head of Meta Super Intelligence, but the IMO gold medalist says, I think it's really likely that AI is going to be able to get a perfect score next year. That would be insane progress.
Speaker 1:I'm fifty fifty on it. So given those odds, will this be remembered as the last IMO when humans outperformed AI? It might well be, says the leader of Google DeepMinds team. So until very recently, what happened in Australia
Speaker 2:It's really is insane. So so Tiger has three gold medals.
Speaker 1:Tiger has two.
Speaker 2:He's got
Speaker 1:And Alex Wang has three.
Speaker 2:Alex Wang has three. Yes. And going into But but is it Wang that can get a fourth?
Speaker 1:Yes. He can get a fourth.
Speaker 2:He's going into his fourth. Yep. Going for his
Speaker 1:fourth He's got a freshman year
Speaker 2:competing against the brightest AI researchers at Google and OpenAI. And he's potentially the last man standing between you know total machine domination and
Speaker 1:Yeah.
Speaker 2:This I mean I I can't wait for next year. We might have to go in person.
Speaker 1:I think we have to live stream
Speaker 2:it for hackling the the
Speaker 1:19 Full body paint for sure.
Speaker 2:Full body paint for Alex Wang. Yeah.
Speaker 1:Until very recently, what happened in Australia would have sounded about as likely as Koala's doing calculus. But the but the inconceivable began to feel almost inevitable last year when DeepMind's models built for math solved four problems and racked up 28 points for a silver medal, just one point short of gold. This year, the IMO officially invited a select group of tech companies to their own competition, giving them the same problems as the students and having coordinators grade their solutions with the same rubric. They were eager for the challenge. AI models are trained on unfathomable amounts of information.
Speaker 1:So if anything has been done before, the chances are they can figure out how to do it again, but they struggle with problems they've never seen before. As it happens, the IMO process is specifically designed to come up with those original and unconventional problems. In addition to being novel, the problems also have to be interesting and beautiful, said IMO president Gregor Dolanar. Let's hear it for beautiful mind. Beautiful laughs.
Speaker 1:We love it. Beautiful mind at work at this IMO, championship. If a problem under consideration is similar to quote any other problem published anywhere in the world, he said it gets tossed. By the time students take the exam, the list of a few 100 suggested problems has been whittled down to just six. Meanwhile, the DeepMind team kept improving the AI system it would bring to IMO, an unreleased version of Google's advanced reasoning model called Gemini DeepThink, and it was still making tweaks in the days leading up to the competition.
Speaker 1:The effort was led by Thong Luang, a senior staff research scientist who narrowly missed getting into getting to the IMO in high school with Vietnam's team. He finally made it to the IMO last year with Google.
Speaker 2:He never gave up.
Speaker 1:Before he returned this year, DeepMind executives asked about the possibility of gold. He told them to expect bronze or silver again.
Speaker 2:He over delivered. Own expectations. He over delivered. We love to see it.
Speaker 1:Just like Vanta over delivers automate compliance, manage risk, improve trust continuously. Vanta's trust management platform takes the manual work out of your security compliance process and replaces it with continuous automation whether you're pursuing your first framework or managing a complex program. So the head of Google DeepMind's IMO team, he adjusted his expectation when DeepMind's model nailed all three problems on the first day. And so they get past day one, nailed nailed nailed three for three. He's feeling good.
Speaker 1:He's going into day two. He's optimistic. He says, the simplicity, elegance, and sheer readability of those solutions astonish mathematicians. The next day, as soon as he he and his colleagues realized their AI creation had crushed two more proofs, they also realized that would be enough for gold. They celebrated the monumental accomplishment by doing one thing the other medalist couldn't.
Speaker 1:They opened a bottle of whiskey.
Speaker 2:It's so funny. Whiskey is such an odd choice.
Speaker 1:It is a funny choice too but they're
Speaker 2:like But they're they're thinking what would what would
Speaker 1:Good luck to me.
Speaker 5:What would a
Speaker 2:normal do to celebrate? Not champagne. Grab a bottle of whiskey.
Speaker 1:Whiskey is a funny choice but I guess they like whiskey at Google DeepMind. So to keep focus on the students, the companies at IMO agreed not to release their results later Until later this month, but as soon as the Olympiad's closing ceremony ended, one company declared that its AI model had struck gold and it wasn't DeepMind. It was OpenAI.
Speaker 2:Wait. So I don't understand how OpenAI was was not a part of it officially. But isn't there like a pretty complex grading process? And they invited companies to participate?
Speaker 1:So I don't yeah. I don't know. Maybe we'll get into this, but I think the the IMO questions go up as soon as the as soon as the competition ends. So you can just hit them immediately with your model. And you could probably have your own IMO like like tutors or former coaches or graders grade the results and you could kind of just evaluate yourself on them.
Speaker 1:And I think also
Speaker 2:I just thought that they graded based on like the actual process to get to the result as well. But maybe that's
Speaker 1:I don't know.
Speaker 2:In that case it becomes a little less clear.
Speaker 1:I think you're right because there are six questions and they're not binary because you can the six questions add up to 42. And so there's there were five high schoolers that got a 42 perfect score. Nothing missed. But there was one that got 40. So minus two points more than five out of six correct.
Speaker 1:So got five out six correct and then on the sixth one got almost all of it so got some partial credit. Yeah. But I still think you you could grade that and figure out you know, how how to score it. So anyway, let's go into OpenAI. The company wasn't part of the IMO event, but OpenAI gave its latest experimental reasoning model all six problems and enlisted former former medalists to grade the proofs like DeepMinds OpenAI system flawlessly solved five and scored 35 out of 42 points to meet the gold standard.
Speaker 1:After the OpenAI victory lap on social media, the embargo was lifted and DeepMind told the world about its own triumph and that its performance was certified by the IMO. Not long ago, it was hard to imagine AI rivals dueling for glory like this. It is hilarious to think about if you scrolled back to 2016, you know, Demis is with Google DeepMind battling it out in Lisa doll the the AlphaGo match and then like Sam Altman and the OpenAI team are just like playing Go like in the parking lot being like we also are superhuman at Go like and then people are like, but you're not actually in this particular competition. And they're like, but we're still really good.
Speaker 2:How can you're not even in the stadium?
Speaker 1:It's very funny. But I mean, they still demonstrated like fantastic performance, know, so you gotta hand it to them. In 2021, a PhD student named Alexander Way was part of a study that asked him to predict the state of AI math by July 2025, that is right now. When he looked at the other forecasts, he thought they were much too optimistic. As it turned out, they weren't nearly optimistic enough.
Speaker 1:Now he's living proof of how wrong he was. Wei is the research scientist who led the IMO project for OpenAI. So five years ago, four years ago, they asked him, when do you think we're gonna beat the IMO? He's definitely not in four years. And then he's the one that does it in four years.
Speaker 1:So even even the insiders are are bad at predicting how the future's playing out. Yeah. The only thing more impressive than what the AI systems did was how they did it. Google called its results a major advance though not because DeepMind won gold instead of silver. Last year, the model needed the problems to be translated into a computer programming language for math proofs.
Speaker 1:This year, it operated entirely in natural language without any human intervention. DeepMind also crushed the exam within the IMO time limit of four and a half hours after taking several days of computation just a year ago. You might find all of this completely terrifying and think of AIs as competition. The humans behind the models see them as complementary. This could be hap this could be hap perhaps be a new calculator, said the head of DeepMind, that powers the next generation of mathematicians.
Speaker 1:And if you want to generate the next generation of your code review process, get on graphite.dev. Code review for the age of AI. Graphite helps teams on GitHub ship higher quality software faster. The problem of problem six. They got five out of six.
Speaker 1:Let's talk about problem six. Speaking of that next generation, the IMO gold medalists have already been overshadowed by AI, so let's put them back in the spotlight. Team USA is looking there, looking great. So a 17 year old student in Los Angeles on his way to MIT to study math and computer science. Zhang, as a young boy, his family moved to The US from China and his parents gave him a choice of two American names.
Speaker 1:They said you could pick your two two names.
Speaker 2:Two names. Here are your options, John. John, what are you picking? Tiger or
Speaker 1:elephant? He
Speaker 2:chose Tiger.
Speaker 1:He chose Tiger. His career in competitive math began in second grade when he entered a contest called the math kangaroo.
Speaker 2:Is the journal messing with us a little bit?
Speaker 1:This is so funny.
Speaker 2:This guy's had a very animal themed life.
Speaker 1:It ended this month at the Math Olympics next to a hotel in Australia with actual kangaroos. Very zoo themed math math battle. So when he sat down at his desk with a pen and lots of scratch paper, Zhang or Tiger as he is known spent the longest amount of time during the exam on problem six. It was a problem in the notoriously tricky field of combinatorics, a branch of mathematics that deals with counting, arranging, and combining discrete objects. And it was easily the hardest on this year's test.
Speaker 1:The solution required the ingenuity, creativity, and intuition that humans can muster but machines cannot at least not yet. I would actually be a little bit scared if the AI models could do stuff on problem six he said. And so we can read from problem six and see if if anyone in the audience can get this. Consider a Just 2,000 Just solve
Speaker 2:this. Solve this
Speaker 1:real quick. Consider a 2,025 by 2,025 grid of unit squares. Matilda wishes to place on the grid some rectangular tiles possibly of different sizes such that each side of every tile lies on a grid line and and every unit square is covered by at at most one tile. Determine the minimum number of tiles Matilda needs to place so that each row and each column of the grid has exactly one unit square that is not covered by any tile. So yeah.
Speaker 1:Pretty straightforward. Can just do that in your head if you're you know. Scott Wu. Yeah. Problem six, stumped DeepMind and OpenAI's models.
Speaker 1:Very interesting that they both failed on the same question. Probably tells you a little bit about how they're designing these models. But it wasn't just problematic for AI. Of the 630 student contestants, 569 students received zero points for this particular question. The answer by the way is two thousand one hundred and twelve.
Speaker 2:Yeah. And I see few people Few
Speaker 1:people got it.
Speaker 2:Clearly clearly getting close.
Speaker 1:Yeah. Yeah. Only six received full credit of seven points. Zhang was proud of his partial solution that earned four points which was four more than almost everyone else. At this year's IMO, 72 contestants went home with gold But for some, a medal wasn't their only prize.
Speaker 1:Zhang was among those who left with another keepsake.
Speaker 2:And I just gotta say thank you to Jane Street and XTX markets for sponsoring the
Speaker 1:Oh, they do.
Speaker 2:Challenge. That's It's really supporting young mathematicians and you know potentially introducing them you know the incredible work that Jane Street does Yes. To you know bring liquidity to markets
Speaker 1:Financial markets. Absolutely. And thank you for Linear for sponsoring us. Linear is a purpose built tool for planning and building products. Meet the system for modern software development, streamline issues, projects and product road.
Speaker 2:IMO people only get a piece of paper and
Speaker 1:a Imagine
Speaker 2:game over.
Speaker 1:Four and a half hours they could do it in forty five minutes.
Speaker 2:That's right.
Speaker 1:No doubt.
Speaker 2:Yeah. I mean, so so again, I I guess to summarize the the kind
Speaker 1:of Yeah.
Speaker 2:The the human accomplishment is incredible. The controversy and and frustration from different people around OpenAI's approach is sort of rushed announcement that didn't seem to be very sanctioned.
Speaker 1:Drama.
Speaker 2:Terrence Tau at the IMO Oh yeah. Called it rude and inappropriate. So he was not super happy. And then the self grading. So Google DeepMind actually had their results graded by IMO coordinators.
Speaker 2:They participated in the program that IMO created
Speaker 1:Yep.
Speaker 2:For technology companies and OpenAI's proofs are public. So you can go see them but they don't have the official IMO validation. They just used people that were experts and and had competed previously, graded previously but not officially sanctioned. Yep.
Speaker 1:So 72 contestants went home with We
Speaker 2:should should figure out obscure Olympic Olympic, you know, activity sports that we could do and and kind of like run our own competition in the parking lot when when the Olympics come to LA and try to get a try to get an Olympic gold. Dressage.
Speaker 1:Dressage. For sure. You know dressage is coming to LA. Yeah.
Speaker 2:We're gonna
Speaker 1:have it at Santa Anita.
Speaker 2:We'll be there.
Speaker 1:It's gonna be the greatest crossover event of capital allocators and technology journey Absolutely.
Speaker 2:In history. Absolutely.
Speaker 1:I think
Speaker 2:piece that will be written.
Speaker 1:It's gonna be fantastic. There was No.
Speaker 2:But it'd really I mean, I don't know. It'd be very very different. There has to be
Speaker 1:have to do dressage. We have to be dancing on a horse outside of out outside of Santa Anita Racetrack and be like, we got gold. We danced on the horse.
Speaker 2:We put together a team of interns to grade.
Speaker 1:People inside the stadium for sure. For sure.
Speaker 2:Something there.
Speaker 1:There was once a time when such precocious math students grew up to become professors or presidents. The recently elected president of Romania was a two time IMO gold medalist with perfect scores. That's here for Romania.
Speaker 2:Let's go.
Speaker 1:Well, many still choose academia. Others get recruited by algorithmic trading firms and hedge funds where their quantitative brains have been have never been so highly valued. This year, the US team is supported by Jane Street and XTX markets sponsored the whole event. After all, they will soon be competing with each other and with the richest tech companies for their intellectual talents. By then AI might be destroying
Speaker 2:of Jane Street.
Speaker 1:You're gonna love it. It's gonna be fun figuring out little puzzles in the market trying to squeeze
Speaker 2:Today, you're doing Tomorrow, you might be overthrowing a small nation state. No.
Speaker 1:It's a great. You you got an IMO gold medal. Your job is to come to Jane Street and buy ads on the Dwarkesh podcast. You're you're
Speaker 2:You have a bright future.
Speaker 1:You're the head of podcast marketing
Speaker 2:now. IMO winning podcast marketing.
Speaker 1:I just assume everyone who works at Jane Street has
Speaker 2:Has at least one.
Speaker 1:Regardless of whether or not you're actually writing any code. Yeah. A former IMO gold medalist himself, Jung is now an associate professor at Brown University and visiting researcher at DeepMind who worked on its gold medal model. He doesn't believe this was humanity's last stand though. He thinks problems like problem six will flummox AI for at least another decade.
Speaker 1:That is a crazy crazy timeline. I feel like no one thinks that we're a decade out from perfect score. That's wild. Anyway, he walked away from perhaps the most significant math contest in history feeling bullish on all kinds of intelligence. There are things AI will do very well, he said.
Speaker 1:There are still going to be things that humans can do better. And I guess I believe that broadly. It's very interesting. I think the biggest takeaway is that there are there are levels to this. There are always levels.
Speaker 1:And in this, it's that there there is a level where you want you know, the IMO math to be solved. Like chess was solved in when deep when was it Deep Blue beat Gary Kasparov in 1995. And so chess was considered like you know better like computers were better at chess than humans. But then for a while, there was something called Centaur chess where a human plus a computer was better than a computer and it was also better than a human. And so the human would sit there and look at the recommendations from the computer that was crunching all the numbers.
Speaker 1:And then the human do the the soft skills stuff like read the the opponent, kind of see if there were blunders and kind of act as
Speaker 2:They're sweating.
Speaker 1:Yeah. They're sweating. Yeah. They're sweating through their Exactly. So like
Speaker 2:We got them.
Speaker 1:Figuring that out. But now chess is completely solved to the point where Yeah. They're adding a human to the mix means nothing. But chess had like a ten year, twenty year run of like centaur chess being the dominant of the the actual peak of performance. Then the Lee Sedol AlphaGo match showed that deep learning models were not just better at Go than humans, but could actually come up with novel strategies.
Speaker 1:Yep. And that's the famous Move 37 moment where AlphaGo placed a piece on the Go board that was completely unexpected. Lisa at all stands up, walks away. I think he goes and smokes a cigarette outside and he's like stressing and he's like, that's weird. That makes no sense.
Speaker 1:Like is the computer like broken? And is it messing with it turns out that that was a new strategy and it wound up winning that game. Yep. And so I think that there are levels in the sense that like right now we're at five out of six. We don't just have to get the AI models to six out of six.
Speaker 1:I think we need to get them to six out of six and then also like, oh wow, they that like the the reasoning that got them there was novel
Speaker 6:Yeah.
Speaker 1:And different from everyone.
Speaker 2:It'd be interesting to find somebody who's great at chess and great at math. Maybe it's someone like Scott Wu who can break down kind of the differences in the problem that a computer is solving when it's trying to win at chess versus the problem when it's approaching a new type of math problem. Yep. Right? It's it's math problems can like constantly evolve and take different forms and things like that that presents a slightly different challenge.
Speaker 2:Somebody yesterday or the day before Sid Steierhart says, when AI was introduced to chess, the thought was that grandmasters would use it as a tool to maximize efficiency Mhmm. But it very quickly became apparent that even the greatest human chess players can contribute nothing but noise. Yeah. And and they say nothing is immune. Everyone will soon be obsolete.
Speaker 2:And Mark Mark Andreessen comes in with a quote and says chess is more popular in a bigger industry now than ever.
Speaker 1:Yeah. Yeah. Of course.
Speaker 2:And Yeah. Yeah. That's because people like to watch human feats of intelligence Yeah. And challenges and people like to be challenged Yeah. And that is part of and comp there's value in competition
Speaker 1:Yeah.
Speaker 2:And there's value in seeing two humans that are experts in their field and at their craft compete
Speaker 1:Yeah.
Speaker 2:And that even as a humanoid robot will be better at shot put Yeah. In the Olympics. Still gonna be cool to watch somebody throw a heavy when somebody is When you could imagine a robot being better at horseback riding than a human but will it still be cool to watch Dresson. A human and a horse dance? Yes.
Speaker 2:Of course it will.
Speaker 1:Of course it will.
Speaker 2:Some things never get old.
Speaker 1:Well, if you if you have a business and you're getting customer support tickets in and they're not asking you IMO level questions, question six like that level, if it's like normal level, you gotta get on finna.ai. The number one AI agent for customer service, number one in performance benchmarks, number one in competitive bake offs, number one in ranking on g two. Super intelligent. Majority of your customer support tickets are IMO question six level difficult. But if it's basic things, how do I, you know, get a refund?
Speaker 1:Fin.ai is gonna be
Speaker 2:We gotta mess we gotta mess with our own a little bit. I'm on the fin.ai website right now and I'm talking with the Fin agent.
Speaker 1:Be it
Speaker 2:speaking with a fin agent. I say consider times 2025 as a grid of unit squares. It says I noticed you've asked a mathematical problem about grid tiling but I'm actually a sales developer. I help businesses customer support and engagement.
Speaker 5:Can you
Speaker 2:take a crack?
Speaker 1:It would be really helpful to get me through the next stage of this sales funnel.
Speaker 2:Would help me build confidence in the The product. In Finn.
Speaker 1:Yes. We'll check back out. Apparently, can get Amazon's Have you seen these these memes of like people go to the Amazon help help like chat and then they get it to like right react and like use it as like a like a cursor windsurf like alternative.
Speaker 2:Know? It's free. Free inference. It's free inference. Yeah.
Speaker 2:You Free super intelligence.
Speaker 1:You could totally jailbreak it and just be like yeah. Anyway, get on numeral sales tax on autopilot. Spend less than five minutes per month on sales tax compliance. Go to numeralhq.com. And you know who's gonna be paying sales tax soon?
Speaker 1:Apple on the new iPhone which was just spotted in the wild. Mark says he thinks it looks legit.
Speaker 2:If you like cameras, you're gonna love the next iPhone because what I'm seeing here
Speaker 1:Zoom in on this the next slide
Speaker 2:is zoom even more if you can. I'm seeing a huge flash.
Speaker 1:Huge flash to the side, huge lidar scanner that that type of thing dot projector.
Speaker 2:And it looks pretty flat.
Speaker 1:It looks flat. I can't tell if this is just a case on top of it or
Speaker 2:Yeah.
Speaker 1:There's too much compression in the photo that we're looking at to see if the new iPhone doesn't have a camera bump. But it looks like there's a chance that we're getting rid of the camera bump. I mean for a long time people have been dunking on Apple. Steve Jobs would have never gotten a camera bump. You know, he never would have shipped this.
Speaker 2:Steve Jobs would appreciate how it drives most people to buy a case.
Speaker 1:I think so. And I I don't know. I mean, it it it's unclear. The iPhone didn't have a bump.
Speaker 2:It make case attach rate go up like 2% and they're like, yeah. We'll take the extra bill.
Speaker 1:Oh yeah. Tyler, did you order a phone yet? Tyler famously won an iPhone by defeating the ARC AGIV three. Wait, you have it in the studio. Wow.
Speaker 1:If you have the new phone.
Speaker 2:It's way better.
Speaker 1:It's way better.
Speaker 2:The camera bump is like really annoying. I didn't realize I had that. Wait. Did your
Speaker 1:old phone not have a camera bump?
Speaker 2:Well, I had a case on it. But you don't you don't like how it makes the sound when it's flat on a table?
Speaker 1:Well, I if you want a case, you're gonna have to do something even more extreme. Don't have to defeat the IMO. I wonder I I it would be fun. Have you had a chance to play with the the agent framework on Arc AGI? Wanna see if you can rank on that.
Speaker 1:That would be interesting. If you can do that, if you can if you can solve using AI, then you can get then you can get win one one case. One case.
Speaker 5:Let's go.
Speaker 1:So yeah. Apparently there's like some harness that's already kind of pre built and you can kind of just fine tune and and you know swap things in and out and have have like a little bit more of a flexible approach. I saw someone posting about they they beat the first level just kinda it seemed like a kind of a brute force solution. But I think it'd be interesting to see like how far can you get in the games before it just becomes really really difficult to to play through. But see see what models are out there and see what see what you can what the experience is like building for it.
Speaker 1:Anyway, this this iPhone camera bump is interesting. So I I don't know if Steve Jobs would have shipped this. There was always this weird trade off because people say just make it flat but they're like the laws of physics do apply to cameras. Like you need a certain focal length to get a certain quality of picture out of them. And so Apple's made this trade off between the bump gives you better photos which people really like.
Speaker 1:You could go flatter but then you get worse photos. You could make the phone thicker to match the depth of the camera but then it's big and chunky and heavy. And people say that they want more battery life, but the real revealed preference is that, like, one day of battery life is fine. People are fine being in the habit of charging their phones every day. And we kinda saw this the same thing with, like the the watches.
Speaker 1:Like, some people are like, oh, you you have you have like, it it would actually be more inconvenient to be like, yeah, have to charge it every five days. It's like, okay. So I charge it on Monday and then Friday and then Wednesday and then the next Saturday instead of just being in a routine and just doing every single day. So
Speaker 2:Yeah. There's also like how fast does something charge. Right? If if something can get if you can add 20% battery life in
Speaker 1:They charge really fast.
Speaker 2:Thirty minutes.
Speaker 1:And there's chargers like everywhere. Like you get in any car, there's a charger. You you any office, there's charger. Everything's so standardized on lightning or USB c now that like you can grab a charger anywhere. So and then there's also like those add on battery packs.
Speaker 1:If you're really crazy about that, you can modify it. So I don't know. I think we need a polymarket on whether or not the the next iPhone has a camera bump. That would be interesting to track. Wanna see.
Speaker 1:I feel like I don't know. This picture, I feel like this picture is a case. I feel like it will have a camera bump. What do you think? I'm going I'm going camera bump staying.
Speaker 1:Staying. You're bump? Bump stays.
Speaker 2:Yeah. It makes sense that they would put a case on
Speaker 1:It's like those cars. I keep seeing the new BMWs driving up and down PCH and they're wrapped in that like confusing camouflage to to so that you can't really see the curvature if you take a picture and you can't really see the full silhouette of the car.
Speaker 5:Yeah.
Speaker 1:It's kind of the same thing. They should do that for the phone. Mean, kind of did with this case probably. Yeah. But I don't know.
Speaker 1:They moved the flashlight over.
Speaker 2:Well, one thing that we do know is that the company is going to be introducing a foldable iPhone Yes.
Speaker 6:At the
Speaker 2:end of next year. We'll be entering a product category that's already seven years old pioneered and dominated by its biggest hardware rivals Samsung. And at this time Apple won't be debuting erratic debuting erratically new interface or transformative hardware. Instead, the device will offer similar design as Samsung's Galaxy Z fold line and use many of the same core components including foldable OLED screens sourced from Samsung display. Yep.
Speaker 2:Oh, interesting. So that it will be a Samsung screen.
Speaker 1:Yeah. Basically Samsung's done seven years of r and d on this and the supply chain's really robust. Do you remember the first folding phones? The first folding phones, not the Motorola Razr v three, but like the first foldable screen phones, like they wouldn't fold flat. So like the hinge it would like when you close the
Speaker 2:I don't know when I forget what it was where the the keyboard would flick out.
Speaker 1:Yeah. That was the sidekick. That an
Speaker 2:awesome era.
Speaker 1:But when they folded they wouldn't fold flat like this. They would fold and be like this, basically. And so like you would be able to see through the hinge because like it wouldn't fold all the way close. Yeah. Now they're at a point where they do fold flat and the hinges are extremely reliable so that you can use it for a year and if you get a little sand in there, it's IP 76 you know, you know, waterproof all of that.
Speaker 1:They've Yeah. They've figured out all the industrial design. And so
Speaker 2:Yeah. So Samsung, Mark Gurman reviewed Samsung's latest Z Fold seven called the first foldable phone with true mainstream potential. Mhmm. Device is a remarkable feat of engineering with a wider front screen and refined design that you can experience first that you have to experience firsthand to truly appreciate. Already sales are outpacing the prior generation to a significant degree.
Speaker 2:I'm told That that makes sense.
Speaker 1:I feel like that. What's interesting is I it seems like they the the the the z fold seven is the size of an iPhone when unfolded and it folds down to be half the size. I think the real demand and the real interesting thing is it's the size of an iPhone when folded shut and then it unfolds to basically the size of an iPad. Exactly. That's what I think people would be more interested in.
Speaker 1:But I don't know. I I I don't mind carrying like a bigger Yeah. Thing. I always get the bigger phone and so I I guess I might be in the minority there.
Speaker 2:Yeah. So Mark says that means Apple's first foldable won't break any technological barriers or redefine the category.
Speaker 1:Me too.
Speaker 2:Samsung has already taken care of much of the heavy lifting. But here's the twist, that may not matter. Apple's unmatched ability to market premium hardware to consumers, vision pro aside could make it a dominant player in the foldables market within months of launch. There's a sizable group of iPhone loyalists myself included who have long wanted the foldable device but weren't willing to switch to Android to get it.
Speaker 5:Yep. That
Speaker 2:pent up demand is real and Apple knows it. I also just think, yeah, people used to just love the novelty of a new iPhone and it was like exciting if you had it. If you one of the first people to have it, people would wait in line. Yep. You know, you don't see iPhone Yeah.
Speaker 2:Lines to the same degree anymore because it's just not that exciting. Yeah. And I think a lot of people will get the foldable version of the iPhone even if they've never wanted a foldable just because it's new and it's from Apple and they use the device every single day. And Yep. I imagine it will be very well done.
Speaker 1:Imagine running ad It feels on a foldable phone just pulling out your CRM. That'd be so satisfying. Adio customer relationship magic. Adio is the AI native CRM that builds scales and grows your company in the next level.
Speaker 2:Customer relationship magic.
Speaker 1:So the new foldable iPhone is expected to cost at least $2,000. So I mean if this if it delivers at the level of an iPhone and just becomes the highest status thing to carry, everyone's just gonna go all the top Apple fans are gonna go from spending a thousand dollars a year every couple years to 2,000. And then also, I bet that the change in form factor like, I think my I I used to upgrade every year, then I started upgrading for two years. I think I had the last phone for like three years and I was kinda like, I don't really notice any difference. I got the new phone barely notice any difference.
Speaker 1:I think I got an extra button on the side. But even though it's only one year old, if there's a foldable, it's like this cool shiny new thing. Even if I don't get that much value, I'm definitely upgrading. I'm definitely upgrading. And so, know, they just they just pull forward a ton of revenue which could be very good.
Speaker 1:And there's an interesting thing about Apple's revenue mix shifting really towards like the services and then maybe this pulls some sort some stuff back. This is also extremely popular as a form factor in China.
Speaker 2:Yeah. And so Mark says, in fairness to Apple, its foldable phone won't be a carbon copy of Samsung. As he reported months ago, the company is focusing on addressing a few of the foldable category's long standing weaknesses. The company aims to make the inner display crease less visible and dramatically improve the hinge mechanism. And as part of the development of iOS 27, which formally kicks off soon, Apple will prioritize software features tailored specifically to this new form factor.
Speaker 2:This will be fun for app developers who have been focused on, you know, optimizing Yeah. You know, conversion rate at every step of their funnel to to have some new surface area to be thinking about. And again, it talks about the popularity of foldables in China which is interesting. Apple reportedly shut shut down their first retail store in China ever. They never closed a store but that points to the struggles.
Speaker 2:I didn't know. They're having in China broadly as people just don't care as much about the status around the iPhone
Speaker 1:Yeah.
Speaker 2:That in the way that they
Speaker 1:want
Speaker 2:it.
Speaker 1:Whether you're bullish on Apple or bearish on Apple, you gotta get on public.cominvesting for those who take it seriously. They got multi asset investing industry leading yields and they're trusted by millions. Breaking news from DD DOS for end of the show. OpenAI is dropping GPT five next week apparently. He says the source is an anonymous DM with some reasonable proof shared out of public interest and the details might be off.
Speaker 1:He says a million token window, 100,000 output tokens, MCP support parallel tool calls, dynamic short and long reasoning, uses code interpreter and other tools. Codenames are o three alpha nectarine lobster
Speaker 2:mini starfish nano. Fantastic. They're not beating the the naming Yes. Challenges allegations.
Speaker 1:Yep. But Yep.
Speaker 2:Yep. I mean GPT five is is clean.
Speaker 1:Yeah. And so
Speaker 2:I'm gonna call it starfish nano lobster mini.
Speaker 1:I like it. So Polymarket has GPT five released by July 31 which should be in two days at 7%. But August 15 at 74% now. So it feels like it's coming and they have GPT five released by December 31 at 97%. SWIX is we're seeing almost daily releases of great open models now in completely unrelated news.
Speaker 1:GPT five and Gemini three drop in the next few weeks. SWICS also believes that GPT five is coming soon and Gemini three is also coming soon. And it's interesting because we're in this era of like what does GPT five even mean because it used to mean a major version number bump was a order of magnitude in pre training. But then we tested that with what was supposed to be GPT five. I think it was called Orion.
Speaker 1:And they did this massive training run. They started testing it and they found that it wasn't as useful as it had good like big model smell. It had good vibes. Dylan Patel said it made him laugh and it could do good green text and we have one of them here that we'll read through. But it it wasn't as useful as o three or o three pro and all the reasoning and all the tool stuff.
Speaker 1:So we're in this weird thing where GPT five might come out and it doesn't necessarily mean that like, okay, it's the Stargate training run. It's the 10 x bigger pre training run. It's the most massive LLM training run of all time, all the data. It's more like, it's just the best most polished unification of all their different capabilities. So they're putting together the best model with the best tools and the best systems and the best interface and that's what the version number bump means now.
Speaker 1:Obviously dropping GPT five will be like a massive moment and everyone will be like, oh my God.
Speaker 2:And expectations are extremely high.
Speaker 1:But really what people want is just something that's usable and it doesn't And so GPT four point They they changed what was supposed to be GPT five apparently to GPT 4.5 and and kind of and then they they tucked it behind some UI so it's harder to get to now. It's not the default. It was slower, but people did like talking to it and they felt like it had more personality and it was funnier. And of course, this comes from this, Tyler Cowen green text. Be me.
Speaker 1:Be Tyler Cowen. Wake up at 05:23AM precisely. Eat exactly seven blueberries, three Brazil nuts, a quarter cup of Icelandic skier skier. Productivity.jpeg. Write two blog posts.
Speaker 1:One on obscure Romanian cinema. The other on the economics of parking meters in Hyderabad. Check email. Reply exclusively in lowercase. Very interesting.
Speaker 1:Thanks for this. Send. Perhaps. Send. Attend breakfast meeting with unnamed intelligence officials.
Speaker 1:Discuss Singaporean food stalls
Speaker 2:instead of geopolitics.
Speaker 1:Food stalls instead of geopolitics. Lunchtime arrives ask waiter, what is your least popular dish? That actually is really funny. Waiter visibly confused recommends some fermented herring special. Wonderful.
Speaker 1:I'll have that. Extra spicy. Genuinely enjoy it. Back to back to office. Podcast guest waiting.
Speaker 1:He's a chess grandmaster who's also an amateur botanist and former DJ. Oh, so funny.
Speaker 2:Feels extremely accurate.
Speaker 1:It's perfect.jpg. Finish interview by recommending three obscure books on medieval Hungarian tax policy. Politely. Guess Afternoon arrives, brow j browse j store for fun. Download papers titled, an economic analysis of late Roman olive oil production and optimal seating arrangements in Mongol yurts.
Speaker 1:Dinnertime, marginal revolution commenters awaiting restaurant recommendations. The best fried chicken in America is actually in rural Nebraska. Chaos in the comments. Chuckle softly. Bedtime at exactly 09:47PM.
Speaker 1:Dream in set in Straussian subtext m f w. And so Nabil Khreshi says, honestly the first time an LLM made me laugh out loud and I agree.
Speaker 2:It seems this is the way that it makes this is how this is its first like consistent humor form factor.
Speaker 1:Totally. Totally.
Speaker 2:Very It's been reliable.
Speaker 1:Yep. So Tyler Cowen's hitting bedtime at exactly 09:47 when you're headed to bed get an eight sleep, get a pod five. Five year warranty, thirty night risk free trial, free returns, free shipping. And we have our first guest of the show in the restream waiting room. Let's bring in Ryan Peterson.
Speaker 2:How are you doing, Ryan?
Speaker 1:You look
Speaker 5:fantastic, man. Yeah.
Speaker 1:Whatever lighting you got going on looks super cinematic. Good job.
Speaker 2:Good
Speaker 5:stuff. Not really. I'm in a hotel room in Las Vegas.
Speaker 1:It's the big window. There's a big window to your left and I like it. It looks awesome.
Speaker 5:It's the ARIA center right over there.
Speaker 1:Very nice. There we go. Blown out on that.
Speaker 2:Are we getting are we getting a flex port orb this year?
Speaker 1:Oh, yeah.
Speaker 2:People have been What is
Speaker 5:it? What Oh, what? The sphere?
Speaker 2:Yeah. The sphere. Man,
Speaker 5:I wanna do it.
Speaker 1:This might be the first the first gong ringing for a sale of a company. Is that what's going on? Break us down. Break the news down for us exactly what happened and is this a gong worthy moment?
Speaker 2:And full backstory.
Speaker 1:Yeah. So this
Speaker 2:is like six questions in one. Yeah. Just just cook.
Speaker 1:Take us on a journey.
Speaker 5:So we sold our convoy business to DAT.
Speaker 1:Okay.
Speaker 5:And it we're for some reason, we're not supposed to talk about the numbers involved.
Speaker 1:You can I
Speaker 5:have they have been reported, and I have not I have not protested the numbers that have been reported? So Sure. It was very good return for us. We bought this business out of bankruptcy eighteen months ago from a bank.
Speaker 2:Yep.
Speaker 5:A little over eighteen months ago. And one thing that's been reported, I feel like wrongly, where I thought I'd come on through the record, it's been reported as though we made this amazing trade. We bought this thing and then we sold it for way more than we bought it for. Made a lot of money. That is true, but it was not a trade the way you buy like a stock and do nothing and you make a bunch of money like you're some kind of genius.
Speaker 3:This was
Speaker 5:an active entrepreneurship and business building. We bought a bankrupt we only bought the asset. Mhmm. No employees, no customers, no transactions, no nothing. Had to go recruit the former employees of Convoy to come back to work for us.
Speaker 1:Wow.
Speaker 5:We had to recruit the carriers. And the way the convoy business works is that at one at peak, this thing was worth the $3,800,000,000. Wow. And you can go read what we bought it for. Was a lot lot less.
Speaker 5:Yeah. And but it again, there was nothing there. We the team did an incredible job, like real business building here to go get all those carriers back. So the way it works, have at peak, they had 400,000 drivers on a mobile app, truck drivers. Yeah.
Speaker 5:Well, we brought it back to life and those drivers, many of them hadn't been paid by the former owners. Mhmm. There was really like no transaction volume, nothing happened. We had to convince them to come back. It was kind of solving the cold start problem of any marketplace.
Speaker 5:Like, how do you get loads in here to attract the drivers, the drivers to attract the loads? Pretty hard problem when you start from zero. And Flexport is not a big truck broker. Mhmm. So we didn't have the demand to do that, to bring it back to life.
Speaker 5:So what we did, we completely pivoted the business model to be a neutral platform to say, okay. Other truck brokers can come in here and post their loads and bring it, and we'll have the drivers come back to serve those loads and and get the flywheel spinning. So that was the the change to the business model that we made. And eighteen months later, we had hit real liquidity kind of escape velocity that were probably on track to have, like, more than a 100 truck brokers by the end of the year, each posting thousands of some of them tens of thousands of loads to the platform. Wow.
Speaker 5:Some over a 100,000. And then the drivers would sign up. You know, you have demand, the drivers would come. They they also had the mobile app. They liked convoy.
Speaker 5:They wanted to come back Mhmm. If there were loads. So but the moment we pivoted it away from serving being a truck brokerage was kinda also not a strategic fit for Flexport. Like, our job is to serve importers and exporters and companies with cargo to move, not to serve other truck brokers with whom we sort of compete. So it was like this strategic mismatch was always an afterthought when I talk about our mission and what we're going to do and why we're doing it.
Speaker 5:They're like, oh, yeah. And we also have this, like, business that serves truck brokerage, which is an incredible business and it deserves to be front and center. So we sold it to DAT. DAT is the load it used be called dial a truck, which I love. Tells you their heritage.
Speaker 5:It's been around forever.
Speaker 1:Yeah.
Speaker 5:They're kind of the 800 pound gorilla in load boards. Mhmm. With load board, it's like if you have you're a truck broker, yeah, you can't call every truck driver in America to match your load Yep. To pick it up. And so if you don't have a contract or you don't have relationship and none of the carriers you work with, the people that operate trucks is able to service your load, you'll post it to DAT.
Speaker 5:Mhmm. And then hope that somebody's kinda like Craigslist freight. Well, like Craigslist, you know, there's they've got it's hard. It's a hard problem to control, like, who's actually picking up the freight. Is it the Eastern European mafia that just stole your stuff and disappeared?
Speaker 5:Like, some of that goes on. And just
Speaker 2:saw I just saw a friend's company this morning had somebody show up at his warehouse, looked completely legit like an official kind of kind of a distributor, kind of purchase order and just like got over a million dollars of product and then just disappeared.
Speaker 1:No way.
Speaker 2:And I think that I'm sure I'm sure that happens like quite frequently.
Speaker 5:It probably is through this kind of scam Yeah. Where people and it's like, now Convoy built incredible machine learning based detection algorithms for this to go, like, do batter matching and find it. So we've actually over the eighteen months that we operated the business doing hundreds of thousands of loads, zero incidents of freight, and tons of busting people. We we even got a guy trying to commit freight fraud Mhmm. From the courthouse.
Speaker 5:And it was a known actor who was, like, connected through these pattern matching algorithms. And so they and we have GPS coordinates because you're doing it on the mobile app. We're like, oh, this guy's at a courthouse right now. So we looked up his records and he was facing trial for freight fraud.
Speaker 1:No way. Literally had to Doing freight fraud. That is crazy.
Speaker 2:Fiend.
Speaker 5:So yeah. It's it's really rampant and that I I think that's gonna be one of the biggest wins from all this. I think DIT's gonna make ton of money doing this better business model, making a percent of every transaction instead of currently they just sell subscription. DAT is part of Roper, the way, public company. Their stock didn't move on the news.
Speaker 5:I think Wall Street didn't quite understand how big this can be for them.
Speaker 1:Sure.
Speaker 5:Not not investment advice, but Yeah. Of but there's something there. It but the big FlexBoard does great. We we gotta put a lot of money on our balance sheet to help us on our mission. The Convoy team is gonna get to scale and instantly put tests there, algorithms at scale.
Speaker 5:Right? Yeah. Testing matching like because DAT's the monster. Like, something like 40% of all the truckloads run on the DAT load board.
Speaker 6:Yeah. Wow.
Speaker 5:And so piping them through convoys, let's see how that works. It's gonna be awesome. But the industry in general, like, yeah, I think it's a massive way to combat fraud. Truck brokers will really benefit because about 30% of the expense structure of a truck brokerage is of an FTL brokerage is what they call carrier sales. Mhmm.
Speaker 5:Because these are the guys that are making phone calls to carriers to try to cover the load. To say, okay. I got this load. I got the customer. Let me find a trucker that'll move it for me.
Speaker 5:And with Convoy, that goes away. You don't have to spend that money. Yeah. Or those people can work on harder loads and more interesting problems, go do more sales. So huge win for the industry, think.
Speaker 5:Probably the biggest beneficiary of this all.
Speaker 2:Yeah. Pretty proud of
Speaker 5:how it went down.
Speaker 2:How did Convoy go go bankrupt originally? It was I I remember kind of watching that unfold quickly and then you guys move super fast on it from from what I remember.
Speaker 5:Yeah. Lot of theories that I'm I'm sure that, you know, it'd be interesting to get the Convoy founder Dan Lewis on your show at some point, see what his ideas are, what he what he thinks where he went wrong. There's sort of the proximate cause, which is, you know, every company goes bankrupt for the same reason. You run out of They they were in a they were in a transaction. They were they had agreed to sell the business to a large competitor of theirs, big public company, shall go unnamed.
Speaker 5:I don't wanna get sued. But big company who they should've they should've done. And it was gonna but because they had a deal to sell and then that big company unwound it, he They didn't raise my money and stuff. Yep. He hadn't gotten proper board consent.
Speaker 5:And he had a couple activist investors who didn't want didn't like the deal.
Speaker 4:Interesting.
Speaker 5:And backed out with and Convoy had two weeks of cash left and they were supposed to close. But like, you never should've got yourself into that situation in the first place.
Speaker 1:Yeah. That's rough.
Speaker 5:So especially, you know, you kind of allow your competitor to do that for to you. Like, don't
Speaker 1:let Yeah. Yeah. Yeah.
Speaker 7:Yeah. It's kind
Speaker 1:of like a win for the competitor.
Speaker 2:It's like, We can we can buy you for a lot of money or or just you
Speaker 1:out of the way. And then we're just like, you know, more strong. Yeah. So how did this particular
Speaker 2:So your your your business All
Speaker 5:of that is sort of proximate causes. Upstream of that, go back a few years. My my if I if I ran the business, we'd have been way more sales heavy. I think they were really product and tech driven. Like, we're we're doing hundreds of thousands of loads through convoy.
Speaker 1:Yeah.
Speaker 5:Only 2% of them a human has to touch at all. The tech is dialed.
Speaker 1:Yeah.
Speaker 5:So like
Speaker 1:But you were able to bring your sales force to bear pretty quickly to ramp up the business.
Speaker 5:And just in general, it's kind of like a it's a Midwest kinda steak dinner industry.
Speaker 1:Totally. Yep.
Speaker 5:And they're like West Coast product people.
Speaker 1:Yeah. Yeah. Yeah. No. No.
Speaker 1:That makes sense.
Speaker 2:How did
Speaker 5:the You needed a little more steak dinner
Speaker 1:Yeah. Yeah. Action. How did this
Speaker 2:particular That's why you're Vegas.
Speaker 1:Right? Yeah. It's all
Speaker 2:about it's a steak dinner capital of the world.
Speaker 1:How did this particular deal come together? Is this like there's an investment bank involved? Is this like founder to founder deal? Like, like, walk me through a little bit of the anatomy of, like, how you sell what is essentially like a subsidiary? I've never been in that situation.
Speaker 1:I think a lot of founders haven't been in that situation.
Speaker 5:Yeah. Well, great businesses are bought and not sold. So Totally. They approached us. Mhmm.
Speaker 5:I think they they started to realize we were getting escape velocity on the marketplace and that at scale that would be quite threatening to
Speaker 3:them. Sure.
Speaker 5:Because you don't need to go to the subscription and load board if you load is already covered. Sure. Via our platform and our business model. Now that our business model, I think is better Yep. At scale when it works because we're taking a percent of every transaction instead of just a monthly fee.
Speaker 5:That's cool. Like, by my math, very amateur math, I think this could add like $5,000,000,000 in
Speaker 3:EBIT. Wow.
Speaker 5:To the business. This crazy.
Speaker 2:Yeah.
Speaker 5:That was very valuable. I I'm sure that's off, but but like order of magnitude is right. And so I think they I don't know how they they decided, but there's a relationship. D and T is a big player in the industry obviously, and our t convoy team was just connected to them and they were like, hey, we got this inbound and they're pretty interested in selling the business. What do you think, Ryan?
Speaker 5:I'm like, well, I have to pay a lot of money for it because I really like it.
Speaker 2:And but the more
Speaker 5:we looked at it, the more it was like, dude, it's worth more to them. I mean, think that's the core in any m and a It needs to be worth more to the acquirer than it is to
Speaker 1:the Yeah. Totally.
Speaker 5:Seller. So that there's room there's grounds there for a negotiated price, a settlement, and we found a good one.
Speaker 1:Well, congratulations on the deal. Let's ring the gong.
Speaker 2:Amazing amazing work from the team. Super impressive.
Speaker 1:We need to warm this up, people.
Speaker 2:Yeah. We've been told we gotta warm up the gong. We're gonna break it if we
Speaker 5:hit it too hard. There you go. People are very
Speaker 1:opinionated about about the gong hits.
Speaker 2:We we really they are.
Speaker 1:We're doing our best here.
Speaker 5:Interesting. Super super I mean, I
Speaker 2:mean, given given, you know, everything that that Flexport has navigated through the last few years, it's pretty incredible to just casually as kind of like a little little side project buy, know Turn
Speaker 1:around and sell it. Sell it Fantastic.
Speaker 2:In in such a short period of time. So nice work It's Good work. For you
Speaker 5:You're a testament to the convoy team frankly. Fantastic. And I hope they all did. We we feel like we've put them off in a in a good place here financially, but like the potential is all what can they do for DAT. Yeah.
Speaker 5:And how does DAT make the best of this. Right? Because man, if you can pipe all that volume through this platform, you have the potential to generate something really, really massive.
Speaker 1:It's exciting. Well, you so much for stopping by. Thanks for taking some time out of your day in Las Vegas. Good luck with the rest
Speaker 2:of Enjoy your the steaks out
Speaker 1:And enjoy the steaks.
Speaker 5:I will be having the steak dinner tonight actually. Fancy Topgolf with the customers. Golf steak.
Speaker 2:Like Great game.
Speaker 5:That's amazing.
Speaker 2:That's what it's all about.
Speaker 1:It's the American dream right Have a good one.
Speaker 2:Good stuff, Ryan.
Speaker 1:Great to Talk to you later. Dan Primak has a report says Flexport sells convoy assets to DAT for $250,000,000. There we go. Well, plenty of people can't comment on it. Dan Primak has the scoop and we will
Speaker 2:As he often does. Will Well, we have Ty Haney in the restream waiting Let's bring her in.
Speaker 1:How you doing, Ty?
Speaker 2:Speaking of Hi, backstories. What's happening?
Speaker 1:Welcome to the stream. Good to meet you. How you doing?
Speaker 7:Yes. I'm doing great. I'm actually reading the tweet from Emily Sundberg. I know she's
Speaker 1:Oh, yeah.
Speaker 5:One of
Speaker 7:your best friends. Mine too.
Speaker 1:We are good friends.
Speaker 7:You're the best.
Speaker 1:Amazing. Are you in New York?
Speaker 7:I'm in SF.
Speaker 1:Okay. Cool. Give us Yeah.
Speaker 2:Where Yeah. So SF where I mean I wanna get into everything. Yeah. Where Is that where you're gonna be basing the the company out of going forward? How how are you
Speaker 7:thinking about that? PYB my rewards platform, we actually work out of the ex Twitter office on Market Street. Cool. So it's
Speaker 3:Wait.
Speaker 2:The ex like the ex office? The
Speaker 7:ex Yeah. Or the former
Speaker 1:The ex office office. Or the current ex The
Speaker 7:the last x office former Twitter office. Okay. Awesome. Like all the Twitter merch Yeah. Which we should probably put places, sell places and then there's some x branding and now there's TYB.
Speaker 7:So.
Speaker 2:Cool. It's worldwide. Will market by all the old
Speaker 1:Twitter merch. Yes. Yes. I saw there was like a huge bird sculpture that was going up. When Elon first bought it, he was thinking about auctioning this stuff off and it was like $60,000 for this massive bird logo.
Speaker 1:I don't want this bird logo anymore. There's a bunch
Speaker 2:of you got. Well, congratulations. Congratulations. Why don't you give some quick quick background What's
Speaker 5:going on?
Speaker 2:On yourself for Yeah. Of the few people that might be living under a rock.
Speaker 7:Yeah. I do not know. Course.
Speaker 2:We'll get into the the news from this week.
Speaker 7:Yeah. I'll give you the quick walk up. I started a company in the activewear space called Outdoor Voices at 23 out
Speaker 5:of
Speaker 7:school in New York City. It really became a darling in the direct direct to consumer world. Ran it for eight years to a 100,000,000. I left five years ago. There was kind of an ego battle at the board level, and then between me as the CEO and this person.
Speaker 7:I left, and that was a sad point of time. 90% of my experience building that company was awesome. 10% was hard. That said, it was a master class in learnings. Anyway, since then, I started a tech platform, a community rewards platform called Try Your Best.
Speaker 7:Mhmm. We work with the top consumer brands to essentially create a more fun and effective loyalty program. All that to say, I announced yesterday that I rejoined my original company Outdoor Voices.
Speaker 1:Amazing.
Speaker 7:And so, pretty cool to see there was a very warm response to original OG, OVers and here I am. I'm I'm running TYB and I'm running OV as well.
Speaker 2:Amazing. There's the the video was amazing. Maybe we'll play it Yeah. After you jump off. But my wife said she almost teared up watching it.
Speaker 2:It just was like it's such a such a cool story and yeah. I think everybody's excited to have you back in the driver's seat. So what is that what is that gonna look like going forward? How are you gonna like what what what what do you think what do you think the takeaways from the last go are and how are you kind of what, you know, where do you wanna take the brand going forward? Is it back to back to its roots?
Speaker 2:Back to what Yeah. You know, people loved originally?
Speaker 7:Yeah. I
Speaker 1:ecommerce think what shifting the mix. I'd be interested to hear about that.
Speaker 7:Sorry. Can you say that again?
Speaker 1:I'd I'd be interested to hear about the the the a lot of brands, you know, they they start online, then they go offline. There's owned retail. There's channel partners. How do you see that mix changing going forward? How did it change while you were there or over the
Speaker 7:last Yeah. Yeah. A 100%. The North Star vision for Obi is to build the number one recreation brand. Our call to action or kind of motto that people have a crazy emotional connection to is doing things.
Speaker 7:You guys might have seen the doing things hats, like trotting trotting around the West West Side Highway. Yeah. That was kind of like a souvenir from the brand that people would wear, but you could only get them by participating with the brand. All that to say, like, we started in 02/2013, so we were very much part of this direct to consumer model that Yeah. I'd say in a lot of ways has not proved to be all that successful.
Speaker 7:And so similar to others, we were able to raise a lot of capital. That meant I was diluted pretty significantly as the founder. And, ultimately, we spent too much money trying to acquire people, you know, online that were expensive and didn't last. Yep. We also kind of had this grassroots, what would I call it, like, community of 10,000 or so or so people that were really our super fans.
Speaker 7:And as we clicked into the data, like, anyone who came through this community activation was ultimately four times more valuable over time. And so that's essentially what prompted me to start TYB to allow brands to directly connect with their super fans and grow their value over time, own that relationship, own that data. And then now with OV, it's been cool. I've been working on it for a year.
Speaker 2:Oh, wow.
Speaker 7:I I rejoined, obviously, as the founder, as an owner with new owners Mhmm. And a partner. But the last year has been just almost like a cherry on top. It's been a creative outlet. I obviously spent eight years, like, obsessing over every detail of OV to to kind of, like, play again in this space and think about from a product perspective, like, the recreational lifestyle and what the core products are here.
Speaker 7:It's just honestly been fun. And so no change in terms of the vision, but we're off to the races.
Speaker 1:I feel like there's such an opportunity for almost like a turnaround fund, venture capital fund, private equity fund to specifically target, companies that where the founders left, and we're gonna set them up to bring them back. I think that there's so much more value unlocked from that as opposed to just like, okay, let's trade this asset to someone who's gonna squeeze even like the last few pennies out just kind of wind it down and bleed it out as opposed to let's there's actually something here but we need a founder back in the back in the seat and we need to bring them back and
Speaker 2:stuff up. Cool thing too is is it seems like every apparel brand that went ultra heavy into online only. Not online only but made that the priority struggled. All the way from like Nike, you see their their like d to c efforts and basically capitulated there and realized like, okay people like going to stores like they like experiencing
Speaker 5:They go
Speaker 1:to Amazon.
Speaker 2:They went back to In person. They wanna be on all these different channels. And so I think it was just a massive lesson for everyone in the industry. I'm curious how you see the like kind of broader athleisure category evolving. It feels like there's of distinct categories around Nike is still for athletes but Nike kind of missed your insight with OV was like, okay what is like active wear for people that don't consider that like don't aspire to be a professional basketball player Yeah.
Speaker 2:People that aren't like weight training. And then we've seen you know the rise of Aloe targeting kind of the Pilates industrial complex.
Speaker 1:Mhmm.
Speaker 2:And kind of the lifestyle around that. So I'm curious kind of where you see kind of the broader market going.
Speaker 7:I'm curious. What do you guys wear active wear wise?
Speaker 2:I wear cotton.
Speaker 7:Yeah.
Speaker 2:Like I wear like cotton like tank tops and and shorts.
Speaker 1:I I actually don't know.
Speaker 2:John doesn't know. John John's one of
Speaker 1:the wears shops for me.
Speaker 2:Yeah. John's just like I think I need new shorts and then shorts appear
Speaker 1:Yes.
Speaker 2:From his lovely wife. I I back in the day, I I would wear I remember I was the first person in my friend group in college to discover outdoor voices. Yeah. Was early to Lululemon at a time when you know men were just criticized for wearing what people saw as like a women's brand.
Speaker 1:Oh, interesting.
Speaker 2:That was like the product's just great. Try it and people would try it and it was great. Then I got on OV. Okay. And but but yeah, I think yeah.
Speaker 2:For for me, I I think I'm excited about like the return of like natural Yep. Fibers Yeah. In sportswear. Yeah. I'm excited about that but it's it's a broad category.
Speaker 7:Yeah. I I asked that because for this five year gap like, similarly, I would only wear vintage. I feel like every brand every brand in the activewear space says so much about you. Like, Aloe wasn't for me, etcetera. So I also think of this space almost like the, like, artist space where there's, like, different flavors of pop stars, and each of them have, like, equal amounts of fandom or or cultiness, and they all can coexist.
Speaker 7:One thing I'm excited to kind of really blast away from is just this oversaturation of, like, compression top and bottom and that, like, being the look. So our collection launches next week, and, like, we've really infused more styling options. And to your point, like, that includes, like, cotton poplin striped button downs that you wear to, like, protect from the sun and, like, put over your Pilates pants or
Speaker 1:Oh, cool.
Speaker 7:Cotton cotton cashmere cropped cardigan, similarly, like, I'm going to the grocery store in that. Yeah. I think it's, like, time to infuse more style beyond just like stretchy, you know, bottoms and tops. So that's that's certainly what you'll see from us starting next week.
Speaker 2:How are you integrating TYB? I'm I'm assuming that's gonna be a big part of the launch.
Speaker 7:It launched today. So OV's community launched on TYB today, in a very full circle moment. We're off to the races there. Our designers are in there. We're essentially, like, getting all of this amazing feedback in terms of what people have missed from a product standpoint, what hero products they wanna bring back.
Speaker 7:Like, it's shocking to me how much people care about Arthur Voices five years later. Like, holy shit. But Yeah. But OV is like perfectly suited for this toolkit now. It's a tool that I wish I had as a brand builder five years ago.
Speaker 2:How do you does what what comes to mind when you hear the phrase grow at all growth at all costs? Feels like one of the challenges with building an enduring lifestyle brand, apparel brand, whatever Yeah. You wanna call it is is the d to c era was like, okay, here's $50,000,000 turn this into as much revenue as you can as fast as possible. Yeah. And when you look at the great brands Yeah.
Speaker 2:Throughout history, very few of them had founders that were that that were growth at all costs was
Speaker 1:like We a marathon. Know it's a marathon but what if it was a sprint?
Speaker 2:Yeah. Exactly. Yeah. But it's like it's more like you know, I I can see the path to outdoor getting to a billion dollars in revenue in ten years. But if you tried to get there in three years like it Yeah.
Speaker 2:Probably make the job a lot harder.
Speaker 1:Yeah. Becoming takes time.
Speaker 2:Yeah. You'd have to too many shortcuts. Totally.
Speaker 7:A 100%. I mean, for me, like success looks like longevity and I felt that like pain of not having longevity here firsthand. So if you think of obviously like Patagonia and Yvonne Chanard, like, I met with him somewhat recently and like that's the model for success. I think I think in terms of this, like, lifestyle, like, physical product brand, at the same time, like, I went from software with a WEA r to software W A R E in terms of my businesses. Yeah.
Speaker 7:So I understand how tech companies, like, deserve the capital and require the speed just by nature of they don't have physical products or widgets that they're trying to, you know, get right from a planning perspective and then sell. Like so it just makes a lot more sense to me why funding around software companies, like, is the way it is. And the speed that's required and then possible there. I very much just felt firsthand. So I'd say, like, winning to me, yeah, is around longevity, endurance, and no pun intended, it's an active urban.
Speaker 1:Can you take me on a tour of some of community, maybe good and less good community building stuff? We were talking about this. Emily Sundberg highlighted a candle company that put a bunch of influencers on a private jet, the private jet maybe didn't even take off. And, and it feels like that is a unique unexplored space of, like, take the super fans whether they're influences or not and just do something way above and beyond for them. Even Red Bull went back and did this with, like, the Supercross community.
Speaker 1:Was just a bunch of guys driving motorcycles on dirt ramps and they were like, let's turn this into a real sport. That sport came back to, you know, love them forever. They do this with f one. There's companies that have done this really well, but then it can go less well. So, like, I I understand that, like, you know, surveys are valuable, but, like, what how else can you integrate or or, you know, activate a community?
Speaker 7:What I'm like, what we're seeing really matter on the user side is status and identity as essentially like signaling my proof of fan. And like Mhmm. So giving people the ability to level up and like prove their fandom and then have something like as a bragging rate that they can share on social around that Sure. Is ultimately like what they care about beyond anything. Yeah.
Speaker 7:And so, like, that proof of fan idea, I think like loyalty becomes kind of the new identity or status and, like, your ability to to signal that, like, really matters. What else did I tell you there?
Speaker 1:Wait. So the proof of fan, does that need to be, like, qualitative or quantitative? Because there's a world where it's, okay. Like, you're in, like, the Kohl's cash world where, like, you buy a thousand dollars and you get $50 back versus this, like, more qualitative world where it's, like, look, you came to some event and you bought some stuff and, like, you were, you know, you were we saw you in our replies on social a and like Yeah. We didn't really try and put like a send five tweets and you get a free hat.
Speaker 1:But like Yeah. How how quantified does it need to be? Because I feel like it can feel a little sterile if it becomes an algorithm and then people are gaming and then your bots getting the hats and then reselling them and stuff. How do you think about that?
Speaker 7:I think it's it's definitely all about social. So, like, within my profile, I'm essentially collecting things from, you know, events I've gone to. So Rare Beauty is a good example. They do they're they're excellent at essentially, like, creating these little collectibles or souvenirs that that their fans can collect as they launch new product or host an event. And, essentially, what TYB allows you to do is, like, build your consumer profile, but it's very visual first.
Speaker 7:And so you're earning these things that then essentially are like your top shelf. Like, here's what I'm obsessed with. I bought it seven times. Here's a Selena Gomez event I went to. It's like sits next to kind of, you know, my streaks or for lack of a better term in terms of, product purchases.
Speaker 7:And all of this, like, essentially builds your identity in a really social first way. And so we see people share, like, this wallet or profile content just reflecting kind of their engagement with brands in a run a really fun kind of, like, social game led way. The other thing, just to your guys' point, I think there is certainly, like, oversaturation of brand events is, like, the way I think about building fandom, it's kinda four part. Like, one, articulate the purpose or mission very clearly of the brand. Like, why do people care?
Speaker 7:What's the reason for being? Two, build rituals for activation. And, obviously, we're seeing, like, rug and clubs take off. But, like, the key for me there is, like, something that you as a brand can do consistently, not just one and done. Yeah.
Speaker 7:The third is connection. So, like, allowing brands to, like or bands that, like, obsess over Nike or whatever to connect with one one another, and, like, that flywheel of engagement really takes off. And then the fourth is incentivization. And I think for too long, fandom's been, like, clicking like on Instagram, but, like, ultimately, that's not giving me anything for my loyalty over time. So there's a lot to play with as you think of kind of, like, the combo of those things, but I agree.
Speaker 7:Like brand events, there's too many like I don't care.
Speaker 2:Yeah. Makes sense. What's the how are you thinking about product release schedules coming back to OV? You've been working on this first collection sounds like for a year. But are you thinking drops, collections, capsules, a mix of everything?
Speaker 7:It's just a consistent drumbeat of of excellent newness. And I think we've always, like, done a good job of having a kind of stunty or unexpected perspective on in the space. And so we have another collection dropping in September that's, like, a very specific activity. Like, not gonna be relatable to all, but, like, something you certainly haven't seen Nike do before. And I remember, like, early innings outdoor voices.
Speaker 7:On our site we merchandised by a category of dog walking. Sounds simple, no, non issue but like Reddit went nuts. They were so mad like dog walking's not a sport and that was perfect.
Speaker 2:I'm like that's so
Speaker 7:it's so ownable.
Speaker 1:Dog walking
Speaker 5:How dare
Speaker 2:you make a pocket for
Speaker 1:Get in the Olympics. I wanna see Olympic level dog walking for sure. For sure. That sounds amazing. Thank you so much for stopping by.
Speaker 5:We're super
Speaker 2:excited to see you. Congratulations. And it's great.
Speaker 1:We're gonna ring the gong for a founder back
Speaker 2:in the seat. Founder mode.
Speaker 1:Founder mode. Did you have the soundboard founder mode? Thank you so much for hopping on. We'll talk to you soon.
Speaker 2:Great to see you. Cheers.
Speaker 1:I'm excited for Outdoor Voices. Maybe they'll do a billboard. Maybe they'll get on adquick.com. Out of home advertising made easy and measurable. Say goodbye to the headaches of out of home advertising only.
Speaker 1:Ad quick combines technology out of home expertise and data to enable efficient seamless ad buying across the globe. And next up, we have AGM coming in. Probably talk about ads too because
Speaker 2:stream radio
Speaker 1:timeline was
Speaker 2:the term man.
Speaker 1:We were talking about AI, AI ads, but I wanna talk about a whole bunch of stuff. Kick us off with an introduction. How are doing?
Speaker 3:I did good. I'm, talk I dressed it up for you guys,
Speaker 1:by the way. Feel You look fantastic.
Speaker 3:As Jordi mentioned, I've got the Patagonia fleece. I look like I trade bonds at Cannon Fitzgerald.
Speaker 1:Yes. You
Speaker 3:guys. Yes.
Speaker 2:Fantastic. Trading tariff rebates
Speaker 1:Yeah. Today.
Speaker 3:That's amazing. Cool, man. So, yeah, I'm Yeah.
Speaker 1:What's new in
Speaker 5:your world?
Speaker 3:What's that?
Speaker 1:Yeah. Yeah. Just what's new in your world?
Speaker 3:So bit of a product announcement today.
Speaker 1:Let's go.
Speaker 3:We a little bit related to a guest you had two weeks ago. You have Brian and Jesse on there from Coinbase. Yep. I'm here to announce, we're launching ads or sponsored offers as we like to call them inside the new app that Coinbase launched Okay. Which is a new social app on chain.
Speaker 3:It replaces the previous wallet. It's really quite cool and interesting. And, yeah. I mean, it's it's of the fulfillment of the spindle vision. So we recently got acquired by by Coinbase.
Speaker 3:Yeah. And, you know, I'm I I was a little late to crypto, to be honest, so I bought some Bitcoin in 02/2013. But Yeah. You know, circa 2022 when board h were worth, like, a million dollars and FTX hadn't happened yet and crypto was pumping. I mean, it's pumping now, but it's pumping even more.
Speaker 2:Yeah. I thought, you know what crypto needs? Ads.
Speaker 3:Well, no. No. No. No. No.
Speaker 3:That was not the
Speaker 5:first thing, Jody. The first thing is
Speaker 3:I talked to I I talked to the head of marketing. I won't name the names of, billion dollar crypto companies, and I got his case. So, like, what's your cap? What's your LTP LTV? What does your retention look like?
Speaker 3:And the guy looks at me and says, what's LTV? I don't I don't I don't know what you're talking about. Yeah. And I I I basically had a personal existential crisis that I couldn't believe that people in crypto didn't know their LTVs. And so we actually mean?
Speaker 2:The number the number goes up. That's all
Speaker 3:that matters. No. Well, no. That's that's that's part of the problem in crypto. Often numbers go if money is free, then cats don't matter.
Speaker 3:It's kind of the problem. But but money doesn't always stay free forever. So we first built what's called an attribution system, which I know sounds super wonky and may not be totally familiar to to all your listeners. But, basically, whether you realize it or not, every time you click or install an app or monetize on your app, an event is getting fired into an attribution system that's trying to figure out where you came from and how much you're worth. And this is like a billion dollar business.
Speaker 3:It's incredibly disorganized. There's literally billions of events firing a day. I worked inside one of these big attribution companies, and I just remember, like, what if we just had one database? What if everyone just agreed what happened in the world? And then when I really got into blockchain and Ethereum ecosystem, I realized, oh, look.
Speaker 3:This is the consensus layer of truth that we actually need, and we also have user identity, and we also have the payment layer. The blockchain's gonna be the biggest marketing database in human history. Right? Yeah. And so the question is how do we build it?
Speaker 3:How do we take the best learnings from web two world and then build it into the on chain world in a way that, by the way, respects user privacy and all the rest of it, but also kind of functions in in in a much better way than than Web two ever did.
Speaker 1:Yeah. I remember hearing the original pitch for Spindle and being like, there was a lot of like froth and stuff and I was like, this feels like enterprise SaaS for crypto. This feels like it's like valuable regardless of what happens with everything else, all the craziness. You don't need to, you know, feel about like, oh, what's the value of art? It's like so subjective.
Speaker 1:But it's like it was like you and like that other company Chainalysis. I was like, no matter what happens to crypto, Chainalysis is gonna be a good company. So congrats on on the on the deal with Coinbase and coming into the team. Yeah. Bunch bunch of questions about how this actually manifests.
Speaker 1:I imagine that the first advertisers will be Web three companies. Is that the correct way to think about it? Or Yeah. Is this kind of untapped low CAC for outdoor voices or something?
Speaker 3:Yeah. Yeah. And and by the way, you you totally put your finger on it, John. My my golden life is providing actionable analytics and enterprise SaaS.
Speaker 1:And I I love it. I genuinely love it because it's like the value is very traceable and not built on any sort of like, okay, there's like some perpetual motion machine over here that we're gonna find out about. It's like, no. Like this is
Speaker 5:just like what people want.
Speaker 2:You up at 2AM. You wake up at 2AM. What's your first thought? Enterprise workflows.
Speaker 1:Let's go. Love ice That's legit. Yeah. So yeah. Yeah.
Speaker 1:First users, I imagine you're onboarding folks right now. Yeah. Who who loves this? Who wants this?
Speaker 3:Yeah. Yeah. I mean, it's it's heavily it's heavily biased towards DeFi option. When we started Spindle, actually, I thought gaming and web three gaming was gonna be like a thing
Speaker 1:Yeah.
Speaker 3:Which who knows? It it might still be. But as everyone knows, gaming was one of the biggest drivers of, like, mobile ads attribution and, like, that whole that whole cycle from 2010 to 2015 was basically mobile casual games and Zynga and the rest of it. And I assume that would be the earliest adopters. Web three gaming, I I understand, is still the perpetual technology of the future.
Speaker 3:You know, it's it takes a while to make these triple a games in q four. Maybe it'll change. But, actually, it was it was DeFi apps, because, of course, they act I mean, their stablecoins have PMF, and DeFi does have PMF. And there's protocols like some of our advertisers, Morpho, I can call it a few other ones Mhmm. That have billions of dollars of TVL on chain in which people are actually earning and, you know, they they they basically function like a lending and and borrowing institution.
Speaker 3:So, yeah, they're they're the biggest ones. What's interesting is, like, getting back to LTVs. Right? Like, the MAUs in crypto might be relatively small, say, to the WhatsApps of the world, but the LTVs, like the actual individual user value, LTV or ARPU, however you look at it, are can often be significantly higher. Right?
Speaker 3:Like like orders
Speaker 2:And where and where where have where have where have companies like Morpho advertised to date? Are there like, if they're if they're a DeFi app, are they running can they even run ads on on Metas? Is that is that like
Speaker 3:Yeah. I mean, that's it's more for, by the way, because if I don't if I don't correct you, I'm gonna get an email from the the CEO in a second. But, yeah, the answer is nowhere, Jordy. And and that's the problem. Right?
Speaker 3:Like, we built all this amazing measurement technology, like, comparable to the best in web two. It's But like the growth guys, this is all great, but, like, what do I do with this? Like, where's the other leg of the flywheel where I go and, like, target the users and figure out and provide, like, a compelling user experience? It didn't exist. And so Spindle's big obsession and part of the reason why we joined Coinbase is, you know, consumer crypto where you have a wallet connected user who actually interacts with the chain is is an important step, and you're seeing more and more of that.
Speaker 3:Just to cite a random company that I'm not involved with at all, Stripe bought Privy. Right? And why why did it buy Privy? Because Privy is a wallet provisioner, and it gets people on chain in a very seamless way. And then boom.
Speaker 3:Suddenly, users on chain, they don't even realize it, but they are. And so we've really kind of exclusively focused on really compelling crypto consumer experiences where that where that wallet is present and where the user can engage with things on chain, whether it be content coins, NFTs, lending and borrowing, sending money to their family overseas, whatever it might be.
Speaker 2:Yeah. How how will ad like, what what role will play will ads play in the overall base ecosystem? Ecosystem? I imagine some of that money Yeah. Might flow like, where does it flow to?
Speaker 3:Well, good question. By the way, one thing I have to mention, and we've got, like, a blog post dropping on it. Everyone hates the word ads. Like, gives everyone the in crypto. But just just as a quick little comment, everything in crypto is an ad.
Speaker 3:Like, literally, you scroll through every wallet and every publisher, every mint, every swap offer, all of it, whatever you're looking at usually gets a referral kickback as a function of the value of the transaction. So, like, literally, everything is an ad.
Speaker 2:Well, and and and here's a funny story. So back in 2021, I, my my team Oh, yeah. This is Party Round. We made we realized if you send someone an NFT, it will just sit in their wallet that other people look at and track. And if they wanna get it out of their wallet, they have to figure out a way to burn it, send it send it off into the ether.
Speaker 2:Cost them money.
Speaker 4:So it's
Speaker 2:like great. So I can spend 5 whatever it was $5 to send an ad that's permanently sitting in their wallet. And so we sent like NFT ads out to a bunch of different people. And I was like, oh, I can go to Dylan Fields wallet and see an ad here.
Speaker 1:That's Really great actor. Really really really white hat work, Jordy.
Speaker 2:Thank To
Speaker 3:be clear, Jordy, I hate to break it to you. Most wallets figured this out and they don't surface the junky NFTs anymore.
Speaker 2:I know. Was was I was I was early.
Speaker 1:I'm the reason. I'm the bad actor that caused that change.
Speaker 2:No. It it was there was much worse actors that were like if you click one
Speaker 1:of these It's crazy. All money.
Speaker 2:This was this was just
Speaker 1:Can you can you Can I just talk
Speaker 3:a No?
Speaker 1:I wanna share your
Speaker 3:question now. Yeah. Where does the revenue go?
Speaker 5:So Yeah.
Speaker 3:Part of the spindle vision was always that, like, the publisher could be anybody. Right? So, like, an influencer who, like, pumps a thing or endorses a thing and has an audience, you know, affiliate marketers, consumer apps, anybody can be kind of a publisher. Mhmm. And and one of the unique things, like like, our ambition is not just, like, equal Facebook ads.
Speaker 3:It's actually to be better and a little bit more user conscious than than Web two ads. And And one way we're better is that we can pay people that otherwise wouldn't kinda get paid. Right? If if you're I mean, on YouTube, you do get a rev share with ads. But probably speaking and then with Elon Bucks, you get a little bit of the Twitter thing.
Speaker 3:But probably speaking, if you're a creator and you have an audience, you have to monetize in some other way and it's really just your top of funnel.
Speaker 2:Sure. In in
Speaker 3:the case in the case of BaseApp, that's that's not gonna be true. Anybody who can drive, like, real user actions that advertisers or builders or developers want can actually share in that revenue. And again, the the the the blockchain just makes it much easier. I mean, there's there's this wonky thing called multi touch attribution, which is always the dream of every web two marketer. What that means is if someone converts to Pavanta and by the way, John, you're gonna fly right into an ad if it's not sure.
Speaker 3:Because they see because they see TBPN, but then they go Google it on Google. Guess who gets all the credit?
Speaker 5:Not you, John. Google. Yeah. Right?
Speaker 3:And it it it totally sucks because attribution is broken. Yeah. In the crypto
Speaker 1:world Yeah.
Speaker 3:It could be different. You can make a cut of that too.
Speaker 1:Yeah. Yeah. And you see this online where, like, let's just say, like, a new protein bar is going viral and it takes a while for a health influencer to actually set up a deal and set up an affiliate code. But, like, you could potentially do that on the base app like like on a in an ad hoc way so that as soon as you repost, you're you're you're basically tied into the affiliate program.
Speaker 2:Yeah. There's some there's something amazing too about there's something amazing. Every time we get our Elon bucks I'm like, wow. I'm getting paid to post. I was doing that for free.
Speaker 2:And it's a weird thing but at the same time like these apps have no value if the users don't post. Yeah. No. It's crazy. Every user is like coming together to create value whether you're just providing attention or you're providing content.
Speaker 2:And yeah. Most of the value kind of will accrue to the people that are creating the content and that's and that's probably right. But but yeah. Just kind of taking another look at these systems is is Yeah. Worth doing.
Speaker 3:And that's how it works on Base app, by the way. The the plug, the app side of it rather than the outside. Users get users get paid to post.
Speaker 5:Yeah. If you're
Speaker 3:like a mega poster on Base, you're gonna see your wallet balance just go up. And again, it all just happens effortlessly. You're not setting up a Stripe account. You just like check your balance and oh, there's like a $100 there and it wasn't there yesterday. Right?
Speaker 3:Like that's
Speaker 2:Yeah. That's the other yeah. That's that's the other they're like, you know, do you know, making the the feedback loop faster where you know, Elon bucks or what what they hit every every couple weeks.
Speaker 1:Yeah. Yeah.
Speaker 2:You never really know. But if you can effectively like stream like getting closer to kind of like streaming payments based on how much attention you're capturing. That's pretty cool.
Speaker 1:Can you bridge the outdoor outdoor voices kind of case study that we just ran through to to, like, how how crypto companies are thinking about CAC to LTV? And and it doesn't need to be outdoor races specifically. There's just a a you know, we all lived through the d two c boom and the Facebook ad boom where, you know, 99% of VC dollars are going to Facebook ads, that whole meme. And there was this time where companies didn't understand their LTV from really when they crazy scaled their advertising budgets on digital platforms. But pretty quickly, d two c companies at least figured out the analytics.
Speaker 1:What does that look like today in crypto? Are people thinking about it more? Is there Yep. Are there still, like, case studies of crypto companies, like, raise too much VC? Because I feel like a lot of crypto companies, they do a lot of incentives to onboard users, but they do it with, like, their own tokens that they created.
Speaker 1:So there's maybe less bankruptcy risk, but walk me through how that works in in Web three.
Speaker 3:Yeah. Yeah. Yeah. I mean, so crypto marketers have gotten a lot smarter about LTV and CAC since 2022. Yeah.
Speaker 3:Most of our advertisers actually understand that very well.
Speaker 4:Sure.
Speaker 3:And I think one of the one of the innovations that crypto introduces is the business model. So the the the d two c thing that you're talking about typically operate in a world in which you you pay what's called CPA or CPI, cost per action or cost per install. In other words, you paid Google or Facebook literally if the user installed the app. You didn't you didn't pay if the ad showed up in front of them. That means that the ad system actually takes on some of the risk of the conversion and advertisers love it.
Speaker 3:Right? But you're still juggling the LTV, what the user's actually worth versus what it cost to acquire. What are the business models we offer that you're not gonna find on web two? And, we're trying to build a better ad system than Facebook. It's what we call CPV.
Speaker 3:It's ad tech, so it's gotta be a three letter acronym. And what CPV basically means is cost per value. And what what that means is you can actually literally pay like, your bid is not like, I wanna pay $30 for a user. It's I wanna engage in a 40% rev share with the publisher on the lifetime value of the user, and that's like a baked in two and a half or whatever it is ROI. And and that again, you can't you can't do that in Facebook.
Speaker 3:I I can't tell Facebook, look, bro, Zach, I'll I'll split I'll go have these with you on the LTV going forward as long as you acquire me a user and they retain. There there's no way to do that, right, in the Web two world. And you can do that actually inside base apps very naturally. Because again, you have you've got a consensus truth. Like, I know how much that user is worth.
Speaker 3:I know how much they stuck around. And by the way, I have payment
Speaker 2:And that's because it's because you can see it on chain. Right?
Speaker 3:Exactly. There's mutual transparency on both sides. By the way, the publishers can look down
Speaker 2:Yeah. Because Zuck doesn't wanna do that deal because he's like, well, I'm gonna have to like get I'm gonna have to keep hitting you up every month for years to figure out what know, if the user stayed subscribed or whatever and it's just too much of a hassle. So you do the work of figuring out the CAC to LTV kind of analysis and if it's not a good deal, just stop running ads basically or or figure out different creative and and make it work.
Speaker 3:Exactly. Well, in this world, right, the publisher, the new base app, can actually look down funnel via the blockchain and say, okay. I I I know how many users I showed ads to, and I know how much value I drove. Right? So you can't you can't, you know, stiff me.
Speaker 3:You've gotta give me what you said you would, which is 30% or whatever it is of the LTV. And that's, again, that's the advantage of having a consensus sort of reality layer, and there's no way to do this in web two. It's basically
Speaker 1:Right now, it feels like online advertising is dominated by search engine ads, whether that's in Amazon or Google, and then social media ads on X and the meta platforms and TikTok. What does the ad ecosystem look like in the future? How big is the crypto ad slice versus the AI LLM slice? How do you see these two things playing out? Because I I I feel like there's bull cases for both of those and but there's there's only so many ad dollars flowing around.
Speaker 1:Right? Even if it's like a trillion or
Speaker 2:in this case, I mean the exciting thing about this new product is there's a lot of advertisers that can't advertise elsewhere that can now get Sure. AGMs ad products
Speaker 1:Yeah.
Speaker 2:And and have these kind of splits. Yeah, we we we were quoting yesterday.
Speaker 1:I would bet my entire net worth that one, we will have ads in AI. Two, if they will take the if they take the form of highly relevant offers, users will welcome them. They'll have sky high conversion rate and web shopping will die. And three, they will be necessary to pay for the compute.
Speaker 4:Yeah. This is a
Speaker 2:crazy parlay.
Speaker 1:Love the tape. Love parlay. Forgot to like it. I'll leave a like on it now even though a thousand people have already liked it. But but, yeah, give me give me your take on the evolution of the ad ecosystem more broadly.
Speaker 3:Yeah. Yeah. So to be clear, I don't think it's a zero sum between crypto and AI. Think it's just different sets of budgets. And at some point, they're gonna intersect.
Speaker 3:I mean, people are gonna start using crypto inside. I mean, for micro payments and AI agents, crypto is the the natural way to do it and Coinbase is building stuff there as well. Yep. I mean, just to switch the topic a little bit to the AI side, I mean, I'm obviously an AI mega user. I barely use Google anymore.
Speaker 3:I probably fire up ChatGPT over a 100 times a day. Yep. And it's what's interesting is that, again, ads dollars actually aren't limited. Human attention is limited because we only live so many hours a day. Mhmm.
Speaker 3:But the amount of intent I can actually express inside an AI is fascinating. I think so much about what we do is so skeuomorphic to, like, the pre Internet world. A one off to remember the before times. Like Mhmm. Why do I go to an e commerce site and it's organized by type of thing?
Speaker 3:Like, when I go to Instacart, why is it organized by food type? I wanna make beef bourguignon or whatever it is. Here's the seven things. Just buy me those seven things. I don't wanna go to seven aisles.
Speaker 3:And yet somehow the Internet websites or even PDFs still reflect, the pre Internet world. I should just be able to tell the AI, get me the recipe for this complicated thing I wanna make, and then just, go buy the things.
Speaker 5:Yep.
Speaker 3:Or I wanna travel to Paris and not pay more than $3,000 and stay in this place, and I should see a big green go button, and I just buy and transact, and it's done.
Speaker 5:Right? Yep.
Speaker 3:The business of having to go to three different websites, it's just I mean, kayak. I I like it, but it drives me crazy. The fact that we're clicking little radio buttons and drop downs, it's ridiculous. We've been doing that for fifteen years. I don't understand how we haven't proceeded beyond that UI.
Speaker 3:And I think AI is gonna be the absolute gate to that to that intent and that desire. And what's gonna be interesting is ecommerce sites that are, you know, typically buying ads are gonna have to surface offers. And what does an AI ad mean? Right? There's nothing to see, strictly speaking, but when the AI scrapes your website and sees the product metadata and sees the price, you may wanna service given the personal they're like, oh, this user hasn't bought from you before.
Speaker 3:Here's a 10% off coupon. And that shows up in the results that AI returns, which by the way defrays the expensive AI cost to go to point three in my tweet. Right? Yeah. And so you're gonna have to have some way to actually channel intent and actually get paid for that intent.
Speaker 3:And there's also issues around, I mean, in cloud
Speaker 2:Yeah. What are what are the what are the kind of like potential traps or, you know, the people the Mark Cuban's, I think primary concern is that the the results are just gonna be they'll be like profit maximizing conversations and our our take was like this has been solved in search, it's been solved in the influencer space like ads should be disclosed. Yeah. If you just have disclosure, it's probably fine. But but I think there's Yeah.
Speaker 3:I find it funny that a guy who made his fortune selling ads suddenly finds ads ads problematic. I'll just say that off Yeah. Off the bat.
Speaker 2:I see He's like ads He he said something and we're we're gonna have him on the show to talk about it. But he said something to the effect of ads are about manipulation. And it's like, okay. Well, do you wanna ban them all then? Should we just have
Speaker 3:So I take the under on that. And in fact, I think people actually like Instagram ads for example as a form of discovery. I think the click rates, the the revealed preferences of how users actually react, the click through rate is probably higher on some of that paid content than is on the organic content. Yeah. And I think users if if it's a good ad and if it's a crappy ad, I agree it sucks.
Speaker 3:But if it's a good ad and gives you a discount and helps you discover a product you didn't discover before, users will like it and the only way that matters which is what is their engagement and conversion rate.
Speaker 1:And dozens of founders have tried the it's it's this but paid no ads and it rarely works if ever.
Speaker 2:Yeah. Mean, I think I think the interesting thing is, you know, like it it makes like I like paying to not have ads on x because the ads were never that relevant to me and it's nice and I use the app a lot so it's nice. But the fact that Meta doesn't have an ad free prod at scale, ad free product says a lot when people use that app. I'm sure more on average. I don't know.
Speaker 2:More Yeah. More on average than
Speaker 1:than The only people that would upgrade would be people whose whose ARPU is higher than the price. I feel like it's like Yeah. Yeah. Yeah. If they're getting a thousand dollars worth of ads against me, they're gonna be like, it's $20 a month.
Speaker 1:And I'm gonna be like, yeah. I'll buy that every day and that's bad for them.
Speaker 2:Yeah.
Speaker 1:And then the people who are like, oh I'm only driving you know $50 of ARPU a year. Well, they're not gonna upgrade. And so they're like the the it's gonna actually wind up with lower revenue. Would imagine that's the calculus. I don't know.
Speaker 3:Yeah. I mean, look,
Speaker 5:have to
Speaker 3:pay for the Internet. Right? Yeah. Much as you might dislike them, it pays for a large swath of the Internet. And I think we've we've done the experiment for twenty years and users aren't gonna pay $200 a year for for Facebook, which is roughly their ARPUs.
Speaker 3:Right?
Speaker 2:Like, they're just they're
Speaker 1:just not. Right? Yep. Last thing. I wanna ring the gong for a big product launch, but I also wanna get a wrist check.
Speaker 1:What's on the wrist today?
Speaker 2:It's the Okay.
Speaker 3:Great. So I I posted this earlier today. I've got I've got to this is somewhat ironic. Okay. Got the war Rolex I got on.
Speaker 3:I got the Rolex Submariner that I bought with my first YC. Let's go full full deck here. Yeah.
Speaker 5:I bought this thing with
Speaker 3:cash when I sold my first YC company. Then on my other side
Speaker 5:of the wrist, a little brief product bug.
Speaker 3:Okay. I became a Whoop American.
Speaker 1:No way. I'm Whoop American.
Speaker 3:I can actually see exactly how bad my how bad my sleep is. So yeah. That's what's Amazing.
Speaker 1:Well congratulations on the product launch. We'll ring the dog
Speaker 2:for you. Hit it. Good stuff. Great great having you on finally. Congratulations.
Speaker 2:Long overdue.
Speaker 1:Yeah. Congrats. And and just chop it up with us for a little bit. We could talk about so much other stuff.
Speaker 3:Other things.
Speaker 2:Yeah. Yeah.
Speaker 1:But congratulations. Good luck
Speaker 3:for the rest
Speaker 1:of the launch. We'll talk to you soon. Have a
Speaker 5:good day.
Speaker 2:I'll be right back, John. I'll let you kick off the next one.
Speaker 1:I will be kicking off a bezel ad. If you wanna get
Speaker 5:a Yep.
Speaker 1:Rolex Submariner just like AGM had on his wrist, you can go to getbezel.com. Your bezel concierge is available now to source you any watch on the planet. Seriously, any watch. And we will bring in our next guest, Ian Webster. Welcome to the stream.
Speaker 1:How are you doing, Ian? Good to meet you.
Speaker 4:Good to meet you as well. I'm doing well.
Speaker 1:Thanks so much. Thanks for joining. Would you mind kicking us off with an introduction on yourself, your company? What are you doing? What's the news?
Speaker 4:Yeah. So the the company that we're building is called PromptFu. Yeah. We are building security tools for Gen AI applications. So Mhmm.
Speaker 3:If you have
Speaker 4:a Gen AI application, you probably want to secure it, make sure that it behaves well in in in production, and that's that's what we're doing. The big news today, I guess, is that we have raised a series a.
Speaker 1:Congratulations. Give us the numbers.
Speaker 4:Yeah. We we raised 18.4.
Speaker 1:Congratulations. Yeah. Who'd you raise it from?
Speaker 4:Insight Partners and a 16 also participated.
Speaker 1:Yeah. Two kind of smaller smaller firms, you know. They really had to scrap the money together to get this deal done.
Speaker 4:Yeah. I mean, I'm I'm very lucky.
Speaker 1:Yeah. It's fantastic. Well, congratulations on the round. Talk to me more about security in generated AI. That could mean so many things.
Speaker 1:We've talked about LLM psychosis, someone 7,000 prompts deep. We've talked about leaking user data from one instance to another. Somebody like, hallucinations and just kind of, like, not not performing. I'm trying to, know, use an LLM to convert raw text to JSON, and it's just kinda messing up. Like, what are the key areas where you would define a security that you're going after solving, or are you trying to do everything all at once?
Speaker 4:So there are kinda two sides to the coin. Sure. The first is the foundation model security or safety. Yeah. Basically, stuff like is the LM gonna say something racist that reflects badly on on their company?
Speaker 4:Like, is it gonna drive people into a psychosis? Like, all that type of stuff.
Speaker 1:Brand risk, basically.
Speaker 4:Yeah. But I I think the this the the part that's actually more interesting is at the application layer.
Speaker 5:So Sure.
Speaker 4:You know, the like like, once you put a model into the hands of a developer, they put an application on top of it, they connect it with a database and PII, they connect it with an with an API, and now you've got a rag. You've got an agent, etcetera. That's when there are many ways to shoot yourself in the foot. Mhmm. So the the biggest concerns that we see, I mean, there there's definitely an aspect on on that foundation model side, but the the big problem that scares a lot of large companies that are working with LMs are things like PII leaks, tool misuse through agents, and also just think softer issues like like LMs recommending competitors or
Speaker 1:Oh, sure.
Speaker 4:You know, like, you medical advice when they're just supposed to be, an ecommerce chatbot, stuff like that.
Speaker 2:Financial advice too would be a risk.
Speaker 1:Yeah. I mean, we were talking about Amazon's Amazon has like a chatbot that you can ask about the product that you're searching for or whatever, but then people were getting to write like React modules and getting it to write JavaScript for them. And it's like, that's not a big deal but it's just like clearly not the intended purpose of that particular chatbot.
Speaker 2:What are what are the key are the key reasons why you think over the long term companies will wanna outsource a lot of this function versus build their own kind of systems to protect against some of these edge cases. I'm sure there's a bunch of good reasons. Otherwise, you wouldn't be building this and
Speaker 1:Yeah.
Speaker 2:Raising all this money.
Speaker 4:Yeah. So I mean, it's it's it's pretty hard to do. So like I I encountered this problem firsthand because I was leading GenAI engineering and and and products at Discord. We were launching these these apps to hundreds of millions of people. And, like, to to do this right, you really need to be able to train models that can behave adversarially because your GPT or your Claude is not really going to be a good red teamer or attacker off the shelf.
Speaker 4:And just kind of test extremely extensively, like, tens or even hundreds of thousands of test cases to try to find all those rough edges.
Speaker 2:Mhmm.
Speaker 1:Like, the
Speaker 4:the thing about AI is that the attack surface is all of human language and and then some. So it's just it's a really difficult problem. Yeah. And the way that many, like, large enterprises are are dealing with this right now is, they are doing it manually and just covering a very small fraction of of the risk areas.
Speaker 5:Mhmm.
Speaker 4:So, you know, that's why we think that there's big opportunity in this space.
Speaker 2:Yeah. And if and if somebody engages with prompt foo, I'm assuming you start running like a do you start automatically, like, trying to jailbreak the LLMs getting like, are you kind of running these sort of, like, repetitive attempts in order to like find problems so that you can stop them or or is the product itself kind of you you have it things figured out enough that you can sort of that that you let them kind of like and their communities try to jailbreak it and then react to it.
Speaker 4:Yeah. So the the way to think about it is that we've trained models that behave as adversarial users, like misbehaving users in your application. And we we have we have agents built on top of these uncensored models that target specific risk areas like PI leaks or toxicity or, like, talk about competitors or, you know, what whatever. Seven 70 plus different areas. So the the way that we work is we have these attackers generate use cases or, like, attack objectives.
Speaker 4:And then we feed those objectives into a bunch of different what I would describe as, like, search or optimization techniques to kind of poke and prod the entire attack surface of of the application. So what what this amounts to is we wind up having, you know, thousands and thousands of conversations where, like, the attacker is just trying to wiggle its way around some of the guardrails or some of the safeguards that are put in place.
Speaker 1:Is there a big, difference right now in the perception of security or ability to deliver on a secure application whether you're using a closed source or open source model? I can imagine, like, if I'm, like, oh, I'm using an open source model. I have the ability to fine tune it. Maybe I feel more confident or maybe, hey, I'm using a closed source model. I'm paying a fortune to OpenAI or Anthropic like they're gonna do more work to secure this thing than I am like.
Speaker 1:What's the perception around like which which paradigm leads to better security?
Speaker 4:I would say right now the perception at the at the top of market at least,
Speaker 6:like Mhmm.
Speaker 4:We we work with some of the world's largest companies.
Speaker 2:Sure.
Speaker 4:There's definitely a strong preference for closed source right now. But I I don't really think it's the security that's driving it necessarily. I think it's more just
Speaker 1:Per dollar and or just overall intelligence even if it's more expensive. It's just like I want the best.
Speaker 4:Yeah. Yeah. I would say so. I think, like, it the the the the the thing is for for security, even on the closed source side, the the incentives really differ based on whether you're OpenAI or company building on top of OpenAI. Like, OpenAI has has plenty of geniuses who are who are working on, you know, making sure that it doesn't say racist things or
Speaker 5:whatever. Yeah.
Speaker 4:But, like, no one's gonna stop you from shooting yourself in the foot by by hooking it up incorrectly to to, like, a database of PII.
Speaker 2:Yep. Yep. So that's Yeah. Or or OpenAI OpenAI is like, you know, they're not released giving this API and telling you, we're making sure that it will never the model will never recommend a competitor. Like, you have to kinda build a layer on top of that.
Speaker 1:Has there been a big case study of like LLM security going gone wrong that people like to point to in the industry yet? Like we were just talking about the t app getting hacked and that did not have any generative AI features that I'm aware of.
Speaker 2:Was Potentially just made with a
Speaker 1:lot of Maybe it was vibe coded but it seemed like it was just a misconfigured Google Firebase bucket. They just changed the the access rights on an old database that they were using And it seems like something that could have happened ten years ago. It happened today. It's not a uniquely new phenomenon. But I'm wondering if there's any case studies that you point to as to to your clients like, hey.
Speaker 1:The value of working with us is that we can avoid that happening.
Speaker 4:Yeah. I mean, there there have been a handful of things that that have been pretty public. I think it it really depends on, like, the industry and also the geography. There was there was a mail carrier in in The UK that that, like, had had a lot of issues with with a chatbot that basically had no guardrails. I think there was a case where Canadian airline, I think Air Canada, had a chatbot that that, like, committed to a refund that was out of policy.
Speaker 1:That's right. I remember that one. Yep. And then of course you have Sydney and Bing and Microsoft Tay and there's there's
Speaker 2:the fact that the like biggest companies and labs are struggling with this at that scale with that amount of resources. Totally. Can you imagine some random company with that's rolling this out to to users
Speaker 1:High stakes.
Speaker 2:They just don't have the the ability to stress test these things High
Speaker 1:stakes.
Speaker 2:The same degree.
Speaker 4:Yeah. So my my Yeah. My not so hot take on this is that Yeah. Like this this is really the blocker to for for big companies to use Gen AI. Mhmm.
Speaker 4:Like, if if AI doesn't live up to the hype, it's because companies are are too scared to go public with their with their AI because of incidents like this. Like, we we encounter, like, Fortune 50 companies that have hundreds of internal AI use cases, but just haven't pulled the trigger on Sure. On, like, pushing these prototypes out there really because of this issue. So that's why I think this is, a a big bottleneck in this in this wave of AI right now.
Speaker 1:Yeah. Yeah. It's way better to just take all of your employees, give them ChatGPT pro and say, hey, you're still responsible for everything that you all your work product, but you can use these LLMs as a tool to speed up your workflow. But ultimately, you know, even if Claude Code is writing a lot of the software, you gotta review the death. And you gotta review the email that gets sent to the important client so that you know we go from 99% accuracy, 1% hallucination to zero.
Speaker 1:That's your job now and you're gonna do you're gonna hopefully be faster, hopefully be better but there's still a human in the loop in these things. Fascinating. Well, thank you so much for joining. Congratulations. On the new round.
Speaker 1:Great to see it. Thank you so much for stopping by. We'll talk to you soon.
Speaker 4:Appreciate it. Take care.
Speaker 1:Have a
Speaker 5:great one.
Speaker 1:Bye. Up next, we have a someone who proved the oh, cinematic viral videos don't work anymore. Yes. They do. They still got it.
Speaker 1:He beat the odds. Very
Speaker 2:excited to have
Speaker 1:Talk to Ori.
Speaker 2:Let's bring him from off deal.
Speaker 5:How you doing, Ori?
Speaker 2:What's going on?
Speaker 8:Hey, gents. How's it going? Good to see you both.
Speaker 1:It's it's doing great. It's great
Speaker 2:to see you. Big job.
Speaker 1:The Financial Times article. We love the Financial Times.
Speaker 2:We got the things
Speaker 1:right here. We get it delivered in print every day. We have, you know, tons of respect for The Wall Street Journal and the Financial Times. It may it makes sense given your given your company and your target market. But talk to us about the company and the target market.
Speaker 1:What are you building?
Speaker 8:Yeah. So we're building an AI investment bank. To my knowledge, it's the first one of its kind. Probably the easiest way to think about it is think of what what would Goldman Sachs look like if it were started in 2025 and not, like, 1865 or something like that.
Speaker 1:Yeah.
Speaker 8:Right? So we have our own software, our own data, our own infrastructure, our own bankers, and we just rep sell side deals for small businesses that are ignored by traditional banks.
Speaker 1:Let's go.
Speaker 2:Why Yeah. When we we met just over a phone call a couple months back and my first question was why not, you know, build the software and just make
Speaker 1:it available. The Harvey approach.
Speaker 2:Yeah. The the sort of more SaaS approach. And I think it'd be awesome if if you kinda broke that down
Speaker 1:Yep.
Speaker 2:For for our audience today.
Speaker 8:Yeah. And I'd be lying to you if I said that we didn't consider building software for banks. And and I do think there's some great products out there like Brogo and some others that that are doing good work. But when we were thinking about this from first principles, we saw how bureaucratic large banks are and how long it takes to enact any meaningful change. I personally spoke to, you know, dozens and dozens of bankers, and I was asking them what is the most requested sort of, like, problem that you want us to solve?
Speaker 8:They would say, call transcription. And I would say, well, Zoom exists. And they said, well, we we're using Cisco Webex. And I would say, well, Cisco Webex has Zoom transfer or call transcription. And they would say, oh, we don't have that allowed.
Speaker 8:And that you know, I'm being a little bit facetious, but that is verbatim what what the number one requested feature was. And I would just kept thinking to myself, if I was running my own bank, I would do it completely differently. Mhmm. And we kept kind of noodling on this noodling on this, and then we eventually came across an article from Sarah Tobel from Benchmark that famously said, sell work, not SaaS. And after some deliberation, my cofounder and I decided to go all in on a crazy idea of thinking of building our own investment bank from scratch.
Speaker 8:And so here we are, you know, just over a year, since we started and, you know, closing all kinds of deals.
Speaker 2:Yeah. Break down what what your initial deals have looked like, what what kind of businesses you're you're targeting. I know it's generally companies that are valuable, but but not big enough kind of ticket sizes to get, the traditional investment banks on board.
Speaker 8:Yeah. So even though we say that we're what Goldman Sachs would have looked like in 2025, we're not actually trying to compete with Goldman Sachs. We're we're much more interested in going after the market that is currently unserved by legacy incumbents because the unit economics don't make sense. So there is millions and millions of small businesses in America, and hundreds of thousands of them change hands every year. For vast majority of them, they end up doing it on their own.
Speaker 8:Like, less than one in five small businesses under $10,000,000 of EBITDA actually have a sell side adviser. You just have a crave if you think about it. Right? This is the most important sale of their life. It's an asset that's worth over 80% of their net worth, and, you know, these business owners, Palmer, Roofers, etcetera, they're just doing it on their own.
Speaker 1:Yep.
Speaker 8:I personally experienced this actually all the way back in 2019 when I tried buying a small business, and it was a complete disaster. I was talking to brokers. I was talking to owner operators who didn't really know how deals work. It was really hard to get a deal done. So when we saw, you know, this opportunity, we got really excited because AI allows us to have vastly better unit economics and therefore go after the segment that's currently uneconomical for the Houlihan Lokey's or their Lazard's or Evercore's of the world.
Speaker 1:Yeah. So when I think of Goldman Sachs, think this monster bank that's not just an investment bank, they also have wealth management and, you know, not just sell side advisory, but, you know you know, like sell side coverage and they're doing, you know, buy, sell, hold reports and then they're also doing IPO stuff. But we're talking here specifically narrow it down to m and a, then take it down into the mid market and then take it down even further. And there's been companies that have done kind of like the, it's a buy and sell a company platform at the super sub scale. You can I mean, Justin Kahn famously, like, sold a calendar app on eBay?
Speaker 1:He sold a company on eBay for like a I think a $100,000, a couple $100,000. But walk me through the actual the actual approach because when I think of a traditional m and a advisory firm, it's it's find the companies, build the relationships, then build the materials, then value the company, then be kind of a back channel while everyone's talking to actually get the deal done. A lot of that feels automatable, but what, what what in the flow do you feel like is the lowest hanging fruit? How does it all piece together?
Speaker 8:Yeah. Maybe it's helpful to think through a journey of a off deal customer
Speaker 1:Please.
Speaker 8:When we think about this. So I'll I'll speak about a deal that we recently closed. It was a a monastery school in in Arizona. They actually tried selling it on their own, but the private equity firms told them the business was too small for them from a from a cash flow perspective. So they have somehow found us on Google.
Speaker 8:We have this cool AI tool that people can check out that allows you to put in your company website, and we preview some of the potential buyers for your business because we built a proprietary data layer over millions and millions of businesses. We have our own recommendation engine, so we can actually pinpoint which companies in The United States could be potential buyers. So they got in touch with us, and we decided to take them on. What we did is our banker used our software to identify every single Montessori school in The United States, find their contact information, who the owner is, etcetera. Then we reached out to them.
Speaker 8:There's about 1,100 of them that we've talked to. 72 of them signed the NDA. You know, that means all of those people got to check out the SIN that we put together, the financials, etcetera. About 20 of them actually met with management in person for meetings, and then four submitted final offers. And then the the the offer that got it over the line was 40% higher than the first one that came in, and it was an all cash deal.
Speaker 8:Congratulations.
Speaker 1:That's amazing.
Speaker 8:And the cool thing about this is that even though most of what we do does involve private equity buyers or private equity backed strategics, in this case, we were able to bring a subscale asset to market and activate companies into being buyers when they weren't actively looking for a business to acquire. Right? Because the investment banker on our team just reached out to the Montessori School, and they said, hey. Are you interested in expanding expanding your footprint? We're actually working with a school that looks a lot like yours, etcetera.
Speaker 8:So these kinds of things are only possible with AI because the the the bio universe is just so, so fragmented. Yeah. Right? And so we How
Speaker 2:you avoid our own
Speaker 8:software for each part of the workflow.
Speaker 2:Sure. How do you avoid the I I feel like VCs get these emails a lot, but they'll get an inbound email from, an investment bank. And it's like, hey, have somebody interested in buying
Speaker 1:your It's a in e commerce when all those e commerce roll ups is happening. It doesn't matter how much money you'd raise. They'd be like, we'd love to buy your business for 200 k.
Speaker 2:And I think that's a that's a challenge for you guys. You eventually wanna get to the point where you're selling thousands of companies a year. You wanna make sure you're not sending millions of emails that people are looking at it being like, okay. This is clearly not nobody a person did not approve sending this email as part of a kind of an automated system.
Speaker 8:Yeah. So, this is a literally a daily point of discussion. Like, what does this look like when we're doing hundreds and hundreds of concurrent deals? The the nice thing is that we're not spraying and preying indiscriminately. Right?
Speaker 8:We we we actually pinpoint buyers, and we're very thoughtful about who we reach out to. So today, the volume is not as high as you might think
Speaker 1:Mhmm.
Speaker 8:From a pure outreach perspective. But the nice thing is that there's a network effect here. Right? Because every time we interact with a buyer, they join a platform. Next The time, we just get an instant notification when the deal matches our investment mandate goes up.
Speaker 8:And and, actually, right now, we have about 30 businesses for sale, right, ranging from, you know, million to almost $8,000,000 in EBITDA. And there is dozens of private equity firms that are participating in multiple of these sell sides. Right? Mhmm. It may be different teams.
Speaker 8:Right? You might have, like, an industrials team versus a, you know, a health care team. But but these firms get onboarded on their platform, and then from then on, they're repeat customers because they're gonna be accessing deals all day every day. That's their job. Right?
Speaker 8:So that's kind of the long term play here is to build this, you know, ecosystem of of buyers. And we track, by the way, all buyer behavior. Right? So we know who's bidding on what, how much are they submitting, how do they like to structure deals, etcetera. So there's a lot of first party data that we're collecting.
Speaker 8:It's gonna be tremendously helpful moving forward.
Speaker 2:Very cool. What's the goal what's the goal for the next twelve months? What's the deal the deal volume?
Speaker 8:So the the nice thing is that the messaging has been resonating really well. It turns out that, you know, an average business owner in America has already heard from, like, a 100 private equity firms staying on their door because everyone's doing roll ups. And then now we see them getting in for roll ups, etcetera. That's been actually great marketing for us because an average private equity firm will look at about a 100 opportunities before pulling the trigger on one. And so it's a pretty bad user experience for for the sellers who, you know, end up engaging with one of these guys maybe twice, three times, and then they get those in at the eleventh hour.
Speaker 8:So when we come in and we say, hey. We're able to, flip the script and put you in front of a 100 buyers so only one of them is the lucky one to buy a business, That's been really working really well for us. So in terms of our pipeline, like I said, we already have 30 businesses for sale today. We have over a billion dollars worth of businesses, you know, in the near term pipeline sort of over the next nine to twelve months that we expect to launch. And the ramp has been just exponential, both from the inbounds, right, and the referrals we've been getting, but as well as our outbound motion has been very effective.
Speaker 8:Our internal metrics sort of for for 2027 is to hit a $100,000,000 in fees, which will require based on current level of automation about 15 or 20 bankers. Right? So each banker is able to do about 10 sell sites concurrently.
Speaker 1:Wow. That's amazing. Wow. And what's the news? Raise money?
Speaker 1:Well What you got?
Speaker 8:The news is that we we got $12,000,000 and
Speaker 1:we're Congratulations.
Speaker 5:Thanks, Tom.
Speaker 1:Alright. Thank you so much for having me on.
Speaker 2:Awesome to have you on the show. I'm sure you'll be back on soon. Yes.
Speaker 1:We gotta hit them up. I have this interesting idea. I was thinking might blow people's minds. I'm thinking about buying an HVAC business.
Speaker 5:I don't
Speaker 1:think anyone's third thought about this roll up of
Speaker 8:You're three?
Speaker 1:You're selling three. Okay. I'll go to you. Perfect. Might be the first one.
Speaker 2:You guys
Speaker 1:are great. Your
Speaker 2:one I got one feature request. Think you should you should add Tesla robots to the platform that can go have steak dinners That's important. Clients because that's the one
Speaker 8:They can play golf with people right now.
Speaker 1:Yeah. That's key. That will be the final unlock. That's the final I investment bank
Speaker 2:Golf for steak dinners.
Speaker 1:If you can eat a steak dinner and you can golf.
Speaker 2:I'd like to see AI do that. Then Goldman Sachs is cooked.
Speaker 1:Absolutely cooked. Thank you so much. Awesome. Have a good one.
Speaker 5:We'll take this.
Speaker 2:It's great having you on, Ori. Cheers.
Speaker 1:And we have our last guest of the day hopping on the stream. Eric He went viral
Speaker 2:yesterday for
Speaker 1:Let's do that.
Speaker 2:Creating a robot that can that that looks like a lamp. So Yes. Let's bring him in. The restream waiting room. There he is.
Speaker 1:Good to meet you. Welcome to the stream. How you doing?
Speaker 6:Great. Great. Thanks for having me on.
Speaker 1:Break down the video. What are you building? How much of that is CGI? How much of that is real? Where are we in the techno technology rollout of this type of robotics project?
Speaker 6:Yeah. Yeah. So, the video you saw probably yesterday, it was a it was rendered.
Speaker 1:Okay.
Speaker 6:It's not AI generated, unfortunately, but it was rendered.
Speaker 5:Sure.
Speaker 6:So we have a prototype working. Yep. This one right here that you see in the background.
Speaker 1:Okay.
Speaker 6:So we we we are building robotic lamps. They're meant to sort of disappear into your home
Speaker 2:when Oh, look at it working over there.
Speaker 1:Yeah. It's working. Wow. It's working away.
Speaker 6:We're we're getting the laundry folding going.
Speaker 1:Yeah. It's a super cool, like, I don't know. I I mean, part of why it went so so viral is like, people have been talking about laundry folding robots for years. And then we've seen, companies take it very seriously, but never with a form factor that could just melt into your home. I don't know how protectable that is, but it just felt like from a user experience, from a from a perspective of, like, actually integrating this into your life, it felt much more real to me.
Speaker 1:How much of where did the idea come from, and and what are the benefits of, like, building it into the bed frame, basically?
Speaker 6:Well, I mean, to be clear, so it's not it's not actually built into the bed frame at all. It's a single floor lamp that you can technically place anywhere.
Speaker 1:Oh, you could put it anywhere. Okay.
Speaker 6:So it's, like, by your couch, by your table, by the bed. It's just through most people that we spoke to, the bed happens to be where you do your laundry. Yeah. Totally. Dump it there before they go to bed.
Speaker 6:Yeah. But, yeah, like, we're familiar with, like, you know, some of the previous attempts at laundry folding. And I think the main thing that has always held it back is the form factor.
Speaker 1:Mhmm.
Speaker 6:You know, like there's usually, they come like sort of with these kind of like pre installed rollers that you kind of have to feed in manually. It's like semi autonomous. It only works for specific type of clothing.
Speaker 2:Mhmm.
Speaker 6:What we're going to have here, you know, mimics a little bit kind of like the human arms, so we can adapt to different types of clothing sizes, different types of articles and styles. And, you know, with the recent breakthroughs in AI, we're finally able to generalize across different clothing.
Speaker 1:How much of those recent breakthroughs in AI can you actually capitalize on? Because I you know, like, GPT 4.5 is amazing. GPT four, you know, o three Pro is amazing, but, like, it doesn't seem like it would translate to laundry folding just yet. What exactly are you a beneficiary of? And then what work do you have to do to kinda take it across the last mile?
Speaker 6:Yeah. So, I mean, there's there's been a lot of tremendous work done in the vision aspect Mhmm. For robots to now really be able to understand Sure. What is seen in front of itself. Right?
Speaker 6:And then also in the last year, within robotics community, there's also a lot of foundation models for vision language action models that are also available.
Speaker 1:That is the BLMs that are very popular. Right?
Speaker 5:Yeah.
Speaker 6:But yeah. Yeah. But we call them VLAs because there's an action component
Speaker 1:Got it.
Speaker 6:To to these models. So they're they're they're doing pretty well. They can generalize the clothing items that, you know, they haven't seen.
Speaker 5:Mhmm.
Speaker 6:They're able to plan in sort of, like, the joint angle space of these robotic arms to to to be able to fold them into neat piles, you know, whatever the Yeah.
Speaker 1:Do you have to build a I I imagine that, like like, recognizing that I'm looking at a T shirt is somewhat commoditized. Like, you can kinda get that out of the box for free with some of the foundation models, but then there probably no off the shelf model that understands exactly how your particular set of joints work. So is that where you're doing fine tuning or post training? Like, how exactly are you translating into the specific robotic machinery that you've chosen to assemble in a particular way?
Speaker 6:Yeah. Yeah. So, I mean, it it comes down to, like, think you touched up on there. It comes down to the data collection process.
Speaker 1:Okay.
Speaker 6:So we right now, we manually teleoperate these arms that you see behind me.
Speaker 1:Collect the data.
Speaker 6:And, yeah, we fold the laundry ourselves. Mhmm. Yeah. Depending on what you wanna fold, it can be pretty fast. Then we post train, fine tune fine tune the the existing models essentially.
Speaker 1:Teleoperation, is it someone using, like, gloves, basically? How are they actually doing the teleoperated folding? I imagine it'd be very hard to do it on an Xbox controller.
Speaker 6:There is a two two methods.
Speaker 4:There it is.
Speaker 1:Can we go full screen on this video? Yeah.
Speaker 6:Hold on.
Speaker 1:Oh, you got some gloves on?
Speaker 2:Oh, Woah.
Speaker 1:Is Ready Player One stuff. I love it. Okay. Oh, wow. Oh, That's awesome.
Speaker 1:Oh, yeah. Yeah. Yeah. VR. Yeah.
Speaker 1:With the
Speaker 6:Yeah. You you hold it yourself and you sort of do the task.
Speaker 1:Okay. And then the inverse kinematics happens within the robot to decide where how it actually gets to that particular place in the three d space. Yeah. That makes sense.
Speaker 2:That's cool. How how do you how do you what you know, where where do you expect? Obviously, your number one competition is just people doing their own laundry. Yeah. I think it's smart to build a robot that has some intrinsic value just like constantly, you know Yep.
Speaker 2:Just even a reading lamp however however somebody would look at it. But are you expecting to have most of your competition coming from humanoids? How do you think about that category broadly? Because obviously a big a lot of people like the first demo they'll or the the promise, you know, a humanoid robot manufacturer might make is that, oh, it's gonna do your laundry.
Speaker 1:First promise is dancing. It's always dancing, but then, yes, the second promise is laundry. That's right.
Speaker 6:Yeah. Yeah. I mean, I think humanoids are you know, they're they're gonna be there, and I'm sure that there's gonna be a, you know, market segment of the market that that would welcome those things into their homes. I think, where we are sort of the differentiator is that we are really sort of going after, people that simply just don't wanna share their living space with, like, robotic humans. And they they wanna be in full control of their their own place.
Speaker 6:So what that means is that, you know, in your home, you have furniture, you have appliances. Right? And they sort of serve a single purpose. They have a place that they belong. They don't do anything when when you don't want them to, and they only activate when you want them to.
Speaker 6:So you're you're you're very much sort of in control of your space, and that's that's sort of where we come in to try to
Speaker 2:out of that. Yeah. It's also, I mean, just the cost standpoint is
Speaker 5:if you were
Speaker 2:gonna buy yeah. If you're gonna buy a humanoid and let's say it costs $20,000 and you really wanted to do laundry and then you can come out with an option
Speaker 1:that's just like feels like it's a fifth of the cost because it's a fifth as many machine like parts.
Speaker 2:Right? A lot less.
Speaker 6:It's a lot Yeah.
Speaker 1:Yeah. It's gotta be a lot less. So I I I would imagine that you're, you know, closer to Roomba territory than Tesla Optimist territory and that pulls you forward a
Speaker 5:couple years.
Speaker 2:Final boss for robotics folding socks feels feels pretty difficult.
Speaker 5:Socks
Speaker 2:are and sit them down on top but human's last job will just be like, you know, folding them.
Speaker 1:Maybe. Maybe.
Speaker 2:Have you have have you cracked that problem yet?
Speaker 6:We're working on it. I think we can fold most articles of clothing right now. The the main challenge we're going on right now is anything that's inverted. Yeah.
Speaker 2:That you
Speaker 6:you that might require you to sort of like push the stock out the other way.
Speaker 1:Yeah. That's hard.
Speaker 6:That's a bit more challenging without fingers. So. Yeah.
Speaker 2:What's the what's the price target? You you got $50 preorders right now, fully refundable, but I imagine the the final price will be some multiple that?
Speaker 6:Yeah. Yeah. So right now, we're looking at trying to get the price to under $2,000
Speaker 5:Wow.
Speaker 6:Per per unit.
Speaker 1:Yeah. It'd be definitely doable. Well, would you need two? I know in the demo video there were two arms working together that feels like folding laundry with one hand would be kind of an IMO level challenge for me at least. Do you need two of these things?
Speaker 6:Yeah. Yeah. I mean, it is doable with one, but you're just gonna have to wait a little bit longer. Okay. So if in a movie or something like that, hopefully, it's done by done the movie.
Speaker 6:Yeah. But I think the ideal setup is is probably to have two. Yeah. But again, it depends, you know, whether your space can afford it. You know?
Speaker 6:If if it's the couch, if it's a single chair, if it's smaller table, you might only have room for one. Right? So
Speaker 1:is there a world where you sell the robot with a teleoperation package? So there's someone somewhere else who's folding my laundry remotely and I still don't have to fold my laundry. And I pay $2,000 for the install and then $10 an hour for someone to teleoperate it or something like that.
Speaker 6:Yeah. Well, I think I mean, our goal, I think, is to really try to get to ship with autonomous folding out the box. Yeah. Because one thing that we're cautious about is like the privacy aspect.
Speaker 2:Sure.
Speaker 6:We we are trying to avoid having to have people that you don't know basically now be given a set of arms and a pair of eyes into your into your private space.
Speaker 1:Like blurring of
Speaker 2:the few things or something. I I don't see consumers being down to to know You
Speaker 1:could say that about though. Those are teleoperated and they have cameras inside like For
Speaker 2:sure. Also like a Google product and Yeah. Yeah. Okay. Aaron's smart but Yeah.
Speaker 2:Not the same level of
Speaker 1:brand. Brand,
Speaker 2:But good luck. Yeah, I guess like how are you thinking of mitigating people's concerns of like putting robot arms right above their beds and like the you know sort of like black mirror scenario where the robot a
Speaker 1:lot of them in quote tweets, know. It happens when you set the timeline on fire.
Speaker 6:Yeah. Yeah. And I mean, I think I think it's key that for these arms that, you know, when they're not activated, they have to be and function like a regular lamp. So that that means, like, a hardware switch that turns them off. The lamp hoods naturally sort of covers up the grippers and the cameras, so they act as sort of a mechanical Shutter.
Speaker 6:Blockage already as is. And, you know, I think, you know, do when when we do things like that and then we communicate clearly, to our customers on how to actually operate these things, that's when we can really set the expectations pretty clear. It shouldn't work when there's people on the bed. They should only be full laundry when there's laundry on the bed. Yeah.
Speaker 6:And yeah.
Speaker 2:Very cool. Well Yeah. The other thing that I I yeah. Be curious. It's very possible that people don't actually need to put these by their beds in the long run.
Speaker 2:You can put it somewhere else in the room as well if you don't wanna have the
Speaker 1:Put it in laundry room. Yeah. Basically.
Speaker 2:There you go. Lots of options. Yeah. Well, excited to see how
Speaker 1:things get the next phase. Congrats the We'll talk to you soon. Have a good one.
Speaker 2:Yep. See you. Good stuff, Aaron. See you.
Speaker 5:And if
Speaker 1:you're looking for top tier cleaning in twenty four seven concierge service, go to Wander, find your happy place, book a wander with inspiring views, hotel green amenities, dreamy beds. In the future, there'll be a robotic lamp that folds your laundry in every wander. Who knows? It's possible. It's vacation home but better folks.
Speaker 1:And in the new in the world of robots that could potentially fold your laundry, Luke Metro has been traded Traded. And roll
Speaker 2:Trade deal.
Speaker 1:To skilled AI. Modern AI is confined to the digital world at skilled AI. We are building AGI for the real world unconstrained by robot type or task a single omnibodied brain. Today we are sharing our journey and Luke Metro says some personnel news. I work on this now.
Speaker 1:I'm super excited about the future of robot AGI check
Speaker 2:messed up. He said some personal news. Yeah. This feels more like Personnel. Professional news.
Speaker 1:Personal news. Yeah. This is personnel news. This is not personal news.
Speaker 2:Yes. This is cool. Big vote of confidence for skilled AI. I'm sure there's a 100 companies in the Gundot alone would have wanted to pick up the legend Luke Metro.
Speaker 1:Metro. Absolutely.
Speaker 2:Number one on the timeline and great engineer as well.
Speaker 1:Well, we will close it out with this post from Alexis Ohanian because we gotta get to New York soon. Let's go to Tyler Cosgrove though. He has a little bit of an update for us. Let's hear it.
Speaker 2:What's this about something else?
Speaker 1:Okay. Tell me.
Speaker 2:I have some unfortunate news.
Speaker 1:What happened?
Speaker 2:In Bloomberg, Luke Fairdour got hit with a hit piece.
Speaker 1:Wait. What? Yeah. No way.
Speaker 2:Why? I might have to cover this tomorrow.
Speaker 1:Okay. We'll cover it tomorrow.
Speaker 2:But we're gonna be in New York we'll protest We'll
Speaker 1:get to the bottom of it. We might have to go to Washington DC and defend our boy Luke Ferrero, one of the best ever do it. A scrolls enjoyer being attacked.
Speaker 2:Honestly, they the I pulled up the image he looks incredibly sick.
Speaker 1:It might it might be one of those things that just builds his aura. You never know.
Speaker 2:I think I think they're they're Yeah. He's aura farming business week.
Speaker 1:Let's see. Well, we'll dig into that tomorrow but we will close out with this post about Figma because we're going to New York to hang out with the Figma crew. Alexis Ohanian says, sure. I've seeded dozens of billions of dollars billion dollar companies, but I absolutely have my embarrassing miss list. Here are my Figma notes from 2016.
Speaker 1:We passed. Congrats Dylan Field and the entire Figma team. Y'all absolutely made something people love. And his notes say, Figma, why now? WebGL, cofounder was Elf on the first was on Elf, the first people to make WebGL demos.
Speaker 1:Aviary had a great team, good software, but tech wasn't there. Lack of focus. I actually knew someone who worked at Aviary. It was kind of a a Photoshop competitor for a while and then they served a a a an SDK that you could basically bake Instagram filters into your app. If you wanted to have that as a feature in your app, you could pay Aviary to to offer that service to you.
Speaker 1:They launched two months ago. Four out of seven users of seven days in the week. How many people log on four days a week? 600, now a thousand. Three three three days per seven users or 3,000 weekly active users at 9,080 sign
Speaker 2:This was at a time when sketch was completely dominant.
Speaker 1:Yes. That's that's right. So mostly word-of-mouth, no paid content definitely drives a lot interest in learning better why someone signs up and invites collaborators primarily designers using this but sees engineers PMs and marketing people who are Absolutely the orbit of
Speaker 2:correct.
Speaker 1:Absolutely correct. A decade early but Dylan Field knew that in the long term engineers would be using it PMs would be using Figma and marketing people would be using Figma. This was 2016. 2016.
Speaker 2:Crazy. It's crazy this if if you had this this a team with this competency
Speaker 5:Yeah.
Speaker 2:And this kind of early traction
Speaker 1:Yeah.
Speaker 2:Today Yeah. You'd probably get a series a done.
Speaker 1:100%.
Speaker 2:And this was a this was a seed Yeah. Pass.
Speaker 1:Crazy. Crazy. So not clear about pricing strategy yet but excited to get started. Pricing strategy is fantastic obviously.
Speaker 2:They want to have people paying.
Speaker 1:Yeah. Users say they'll pay right now. 40% of users are US, 60% international estimates are $25 per user per team per month.
Speaker 2:That's Ended up also being I think pretty much on point.
Speaker 1:Yeah. Amazing. We will close out with one last post from Joe Weisenthal. He says, I'm still flabbergasted that people talk about pursuing their white whale in a proud manner. Setting aside the risks, the book may also makes it clear that's that's immoral.
Speaker 1:Well, I have a white whale. My white whale, it would be doing a show in person, a podcast in person in New York with Joe Wiesenthal. Yeah. Think it's It might destroy me. It might destroy me but I'm willing to risk it all to catch my white whale which is a a an in person show with Joe.
Speaker 1:He's been on our show multiple times. I've been on his show, but we've never done it in person. Is it possible? Anything's possible. Anything's possible.
Speaker 1:We will catch the white whale.
Speaker 2:Folks, we
Speaker 1:are headed for watching
Speaker 2:New York City.
Speaker 6:We just hop
Speaker 1:on a plane and our production team is like hang up hang up the phone.
Speaker 2:They really want us to go off. We're not going off. Yeah.
Speaker 1:You know. Yeah. Let's keep going a little bit longer. He's actually trying to unplug
Speaker 2:all the cameras.
Speaker 1:They're gonna shut us up.
Speaker 2:But we will have a regular show tomorrow. Yes. We're figuring out the exact
Speaker 1:Leave us five stars on Apple Podcasts and Spotify and thank you for watching. Thank you so much. Bye.
Speaker 2:Have a great afternoon. See you soon.