BUILD RAG

“When it comes to uh competency, there's always a trade-off between intelligence and knowledge. If you have more knowledge, if you have better training, uh you need less intelligence to be competent. And that's exactly uh what happened with the the rise of coding agents, right? The models don't have higher fluid intelligence per se. They don't have like a higher uh IQ, so to speak. It's just that they're way better trained.”

“The main arguments would still stand for humanoids. One is that our world is sort of designed for humans. So one hypothesis is that if you design policies for like, they single out mobile managers, then once you solve a lot of tasks in that environment, then you see that it's limiting because many tasks in our world are like opening a bottle, or like opening a fridge and then taking something from it. So you have to keep the door open. Or even, I think some people say, well, you don't need wheels, but then what if you solve a lot of tasks on a wheeled platform and then there's a little curb on your floor or by a street side and then the robot is like stopped there. So I do think that ultimately, if you want to do a lot of tasks and be useful in environments where humans operate, you need to go to a human or as close to a human embodiment as possible.”

“Silicon Valley's consensus culture produces consensus founders.”

“But there's this weird dynamic on chain, which is I can just issue a utility token to fund my project. And so like what role does debt actually play? And I guess my view would be it largely has been supply and demand for leverage. And so credit cycles on chain, they don't necessarily follow sort of credit cycles in the TradFi world.”

“Our developer creator earned about a billion and a half on the platform, and it goes pretty deep. Like top thousand devs are averaging 1.3 million, like real people making a living. So it goes way beyond the walls of this building. When we launched Robux and the ability for creators to make a living, we knew within six or eight hours that this was going to take off.”

“My timeline to AGR, you know, if you if you just try to to extrapolate from the the current rate of progress and the amount of investment that's going into not just the LLM stack, but also like uh side ideas, side bets that might work out like you know, NDI for instance, I think we're probably looking at AGI 2030, early 2030s uh most likely. So around the time uh that you are going to be releasing like maybe AR 6 or AR 7 uh that's probably going to be a GI.”

“I would say any skill you want to preserve in your head, you should probably not use AI for. So I use AI for editing right now. You very quickly end up on a slippery slope. There are already scientists and researchers looking at the negative cognitive impacts of depending on AI, much like your ability to navigate is probably deteriorated since using Google Maps. In some respects, each individual is more enhanced, augmented using these tools. But if you do want to keep certain muscles strong and able, that's where I would hesitate. But if you lose it, it's a hell of a lot harder to reclaim it.”

“My experience is the better we are at doing our job of, like, helping you generate the emails, the more they are exactly like the emails that you had before, right? If we're doing a great job, the email that you write should be no different, whether we help you write it or not. We simply help you do it faster and we help you make fewer mistakes.”

“If you're doing a startup, you want to ride, you know, whatever the trend is that's happening. I think the right time to launch a feature or launch a product is right before it seems possible. So in the case of AI Assistant, I think, you know, no one else had released something like what we do in email. I think a lot of people were like, we're not quite there yet. And that's what you want to get it out.”

“I think courage is learned. You have to practice it. And if you're not afraid, it's not courage, right? If someone's fearless, they're by definition not using courage. You have to be afraid of something. So you can edge yourself and you can edge kids into that. I don't think courage is a decision. I don't think courage is something you get from reading a book. I think you have to prove to yourself that you have it. And the only way your subconscious will believe it is if you are actually doing things that are uncomfortable. It is through action and progressive resistance that you develop courage.”

“There was never really, like, exogenous quality sustainable yield. And I think the first the first glimpse of that was Athena, last year or two years ago when we had, like, exogenous yield that was not due to, you know, like, leverage against Bitcoin. It was, to some extent, leverage because it was, still driven by the funding fees, but it was somewhat upon exogenous yield. And what we observe with Prime is when you have something that is sustainable, and can sustain sustainable and at scale, it takes a bit of time, but people start trusting it.”

“I think for me, the understanding was like people used to think that all the robots are so different. All of their data is like so different. And every lab has or like they invest in like a couple of embodiments. It was just I think, post RTX, the idea was that people moved in the direction of thinking that all robotics, all robots are kind of similar. It's like, it's only as different as like English and Chinese or something. And the concepts are similar. It's just the manner of expression that's different.”

“I was talking to everyone at BrainPoint that this is going to be really good and big in Solana. Because we always wanted this and we finally have it. And I think although we live in this permissionless 24-7 world, it's still fine and some people still lose money and things break.”

“Everyone was doing powders and pills, but the compliance on those is terrible. People buy them and they sit in the cupboard. Gummies change the habit because they actually taste good. We took the most nutrient-dense profile we could find and put it into a format that people actually look forward to eating every single morning.”

“I think my one-sentence explanation is that with the era of internet scale foundation models, things that used to work maybe 20, 30 percent of the time are now working 60 to 70 percent of the time. And in robotics, right, as a very complicated, dynamic, engineered system with many pieces, in the past, if every small component of your entire system only worked 30 percent of the time, it would take many, many iterations to get a whole performance system working at scale. But now when every single part of the entire stack just works that much better, from the research iteration process to the engineering scaling process to the data collection engines, I think you can really just see the pace increase when you just have many more successes and a much higher hit rate when you're going about and scaling up your research.”

“We want to reconnect fragmented rollups and unify liquidity through the EEZ.”

“You want to do it well, you want to inform people about the token, what does it do, what are the risks, what is the yield coming from, be as transparent as possible, try to curate as much as possible. Because that's how you build a user base that appreciates those things, that invites other people, trusts you, etc.”

“Another way is the economics don't make sense. And if you have confidence in the trends in the economics, you can afford to make that investment, and you can, you know, cover the gap with central capital. And then over time, it'll make sense. And the best example I have of this is YouTube. So YouTube was losing money like crazy because at the time, serving that amount of video infrastructure was really expensive for bandwidth and for storage and for, you know, re-encoding the videos and stuff. And that obviously worked out real well.”

“I think what's going to happen here is, yeah, to some extent, the AI is going to help you triage them and things like that, but I think also the social network is going to start to bear a lot more, right? So, like, personally, I filter partly based on the content of emails, but a big part of my filter is, like, where I met that person. I think that sort of thing is going to become even more important of, like, who's connected. So, I see, like, higher importance for relationships in the social network and less importance on the actual content of the email because that's much more easy to engineer over time.”

“It's not that the models are smarter. It's that they're suddenly more useful. It is possible to be more useful in particular domains without being smarter. Yeah, clearly because that's means good things for me. I'm not getting any smarter right now like at you know age 45. But you know I can learn how to do things and that's sort of what's happening with the models as of like late.”

“So my definition is uh AGI is basically going to be a system that can approach any new problem any new task any new domain and make sense of it like model it become competent at it uh with the same degree of efficiency as a human could. So meaning it's going to need basically the same amount of training data uh and training computes as as a human would which is which is very little like humans are really really uh data efficient. So general intelligence is human level skill acquisition efficiency on the on the same scope of tasks that uh humans could potentially uh round to do.”

“Toyota is one of our most significant investors. And we chose Toyota early on, one, because the Toyota family has dreamt about building aircraft for daily transportation, dating all the way back to the 1930s. Two, Toyota is known around the world for the quality and the reliability with which they build.”

“We've agreed with the FAA on every detail of the design, not just testing. The FAA designated engineering representatives have signed off on each of those drawings before we start making them. Then the full aircraft comes together and we now begin flying it. First step is Joby pilots fly that aircraft... [Commercial rides begin] as soon as the end of this year.”

“Figur's been at, sort of the RWA, intersection of of TradFi and credit origination since 2018. You know, we set out to really rebuild capital markets, but doing so, on chain. And so, you know, we're vertically integrated across the whole stack from credit origination, mostly known for tokenizing HELOCs, on chain. Done about 22,000,000,000, of those to date. We structure the cash flows, and then we also distribute, across TradFi and DeFi.”

“I 100% agree that we are a few breakthroughs away from general purpose robotics, you know, that it's the dream that we are working so hard for. I think, again, if you want something commercially viable, something that will maybe make money or help some people in the world, I think a lot of those ingredients are already ready to have a larger impact than maybe even just a few short months or years ago. But for the true full vision of embodied, you know, AGI, I do think there is still fundamentally a few open research challenges left.”

“We didn't reinvent the wheel with the ingredients. We just remixed the format. It's the same thing as taking a successful software product and moving it to mobile, or taking a successful supplement and making it a gummy. You take a proven value proposition and deliver it in a way that fits better into a person's daily routine.”

“Attention is the most valuable currency.”

“Think we kind of all looked at the past few years, and we thought low risk DeFi is a thing. And, everyone's happy to earning a two and a half percent or 3% forever, and I just simply don't believe it. Or maybe Solana is more higher risk appetite in general and is more keen to get, you know, 12% yield. We found that people are extremely interested in getting this this extra yield as long as they understand the asset.”

“A thin layer reconnects the ecosystem to provide a unified economic zone.”

“Camino was born about three years ago, kind of out of a of a need to serve some of the stable coins, in Solana. It's you initially, it was, an LP, protocol to to tokenize LPs, and then it once we realized that, actually, the bottle end was not well served or did fit all the needs, we decided to build our own bottle end as well. The reason why it was all created was to serve DeFi and Solana because we thought the blockchain will, create a lot of economic activity, which is what is happening now.”

“I think it's really important to talk about what a game changer AI is. You take one of the greatest aerodynamic minds on the planet and you enable him with something that makes him 10x as productive. The benefits compound in a crazy way. This is the most profound technology, I think, in the history of humanity.”

“Specific to clinicians or practitioners, ask them what types of adverse events they've seen. What are the most concerning adverse events that they've seen? A simpler way to put that is, how do you handle freak outs? What do you do when somebody really loses their shit? And if their answer is, people don't lose their shit, there aren't any adverse events, they're either lying, delusional, or very inexperienced. Maybe all three. Those are not mutually exclusive. So I find that to be a pretty quick, necessary but not sufficient way to use a particular line of questioning to separate seasoned practitioners who are honest from those who are neither of those things.”

“You have to be willing to fail on ninety percent of your ads. We were pumping out fifty to a hundred different creative variations a week just to find the one or two winners that would actually scale. If you're not testing at that volume, you're basically just guessing with your marketing budget and hoping for a miracle.”

“One thing we uh we did a bit at Google in fact you know Google made it kind kind of difficult and and I was sad about that is uh hire your power users like hire your fans. This this is a really really good idea like find find the the most enthusiastic users from your community and and and just hire them on your team.”

“Alphabet is an interesting position to, in some respects, kind of own the full stack. Engineers aren't going to like that I'm using that term, but they have distribution. They have hardware in terms of TPUs. They have incredible unparalleled access to information. They've got Demis Hasimus and DeepMind internally. They've got the ability to spin things out like Waymo. There's just so much going on within Alphabet that I find it very fun and terrifying to take a close look at. And I say that also because it is completely unclear how exactly Google compensates for or plans for shifting to some type of ad revenue from AI generated responses.”

“I literally try more and more to treat being CEO as a craft. It’s a craft that requires fitness and mental health and a whole structure around it. We work on metabolic health and research around how diet affects all kinds of things like bipolar, schizophrenia, and how clearly we think. I have a phlebotomist come to my house once a month to watch metabolic markers.”

“There's serially five calls, and the feature extract is actually like five different things in parallel. So every time you ask a question to that assistant, we're doing like 10 LLM calls. And I want to note that before we did that, we embedded all your emails, right? So there was a whole bunch of your processing done beforehand, and we had to pay on your millions, honestly, to set up the data to do that.”

“If you look at why everything is is starting to work so well with squinging agents, it's really because uh code provides you with a verifiable reward signal. And I think right now we're in this situation where any problem where the solutions you propose can be uh uh formally verified and you can actually trust the reward signal. It's not just some guess made by a model. Any domain like this uh can be fully automated with current technology with with the LM based stack and uh code is sort of like the first domain to fall but there will be many others in the future. I think mathematics is also is also primed to see a revolution in next few years for the same reasons.”

“I built a business called Gruns. We make gummy vitamins. We started it about three years ago and just recently crossed that billion-dollar valuation mark in the exit. It was a fast ride, but we found a hole in the market where people wanted the benefits of greens powders without the terrible taste and the mess of a shaker bottle.”

“This new age for builders allows for a more stable network architecture.”

“The external goal is 10 percent of global gaming. Global gaming is about 200 billion dollar market. We did 6.8 billion in bookings last year, 10 percent would be like 20 billion. That'd be a reasonable first step at where we would like to go. But really, I would say the global gaming market is emblematic of really a new way of people to communicate.”

“I was like, you know, at the time in back in 2016, 2017, I was like, okay, we're going to need a a benchmark to capture the ideas. Uh we're going to need a program synthesis benchmark. And uh my my mental model for that was ImageNet. I was like, oh, I'm going to make the imageet of reasoning. So, I started brainstorming a few ideas around like 2017. I explored many different things. Uh and eventually I settled on the uh RGI format uh around like early 2018. You know I was doing this on the side. It was a side project like my main project was uh developing kas at Google. Uh so summer 2018 uh I wrote the ARC task editor and then I started just making lots of tasks by hand and about one year later I had made 10,000 tasks.”

“Science is fundamentally a a symbolic compression process where you're looking at a big mess of observations like you know the the position of planets in the sky or something like that and you're compressing that down to uh a very simple symbolic rule. You're saying like yeah like all these you know thousands of observations actually just all uh this one simple equation that's symbolic compression. Science is not about curve fitting. Science is about finding the equation, finding the most compressive symbolic model of your pile of observation.”

“I built a business called Gruns. We make gummy vitamins. We started it about three years ago and just recently crossed that billion-dollar valuation mark in the exit. It was a fast ride, but we found a hole in the market where people wanted the benefits of greens powders without the terrible taste and the mess of a shaker bottle.”

“The Ethereum Economic Zone reconnects fragmented rollups to recreate one economic zone.”

“Well, one of the aspects is, as you mentioned, rules are sort of subject to interpretation. And even if you have the same language, there are multiple ways to interpret it. So here's an example. So we said, well, don't do things that or don't interact with anything that's harmful. And I think there was something in the data set which like it's it's all a cigarette. And then it was like, well, I'm not going to pick up a cigarette because it's going to be harmful. Currently, I think our robots are more the problems don't come from the fact that they are too smart to work around the rules. It's just that I think they are too incapable of doing zero-sharp things in the real world.”

“Somebody walks into my house. This is a shoes-free house. Let's say somebody comes in tracking mud all over the place. That person's going to get dragged by their hair out and then they're never coming back in. Zero tolerance policy for broken windows. When these minor infractions are permitted, the Overton window, the broadness of what is now allowable behavior shifts. If you allow minor infractions, you're going to get moderate infractions. You allow those, you're going to get major infractions. From the very first days of the blog, the comments section has guidelines. If you're an asshole, we're going to boot you.”

“Everyone was doing powders and pills, but the compliance on those is terrible. People buy them and they sit in the cupboard. Gummies change the habit because they actually taste good. We took the most nutrient-dense profile we could find and put it into a format that people actually look forward to eating every single morning.”

“Real-time proving gives specialized chains seamless access to Ethereum’s settlement and security.”

“At the core, this is an electric aircraft that can take off and land like a helicopter, but it has a wing. And so it can transition and fly on that wing that makes it more efficient and it makes it quieter. The acoustics are critical to what we're trying to build. We want a vertical takeoff and landing aircraft that you can land as close to the communities that you're looking to serve.”

“At a certain level of business, the actual product is almost secondary to the access you have. Being able to get into the right distribution channels or get on the phone with the right retail buyers is what separates the billion-dollar brands from the ones that stay stuck in Shopify land forever. Access is the ultimate unfair advantage.”

“What we observed with Prime is when you have something that is sustainable and that scale, it takes a bit of time, but people start trusting it and then they realize they can do useful things. People with that want to earn yield, they can rely on it. So this was always the promise of defy composable money, but there were no pieces to compose with.”

“In a world full of tool systems and AI, what human abilities or habits are becoming more valuable, not less? I would say the relational, the tactile, anything IRL in real life that can be extended also to, for instance, in my case, informational advantage, offline informational advantage. A lot of the LLMs are slicing and dicing the internet. One might argue all of them are doing that. And whether you are looking at longevity in professional terms, if you're looking at longevity in creative terms, I think putting on the lens of looking at what you can do in IRL that currently... allows me to have an informational advantage because none of that is online.”

“If you have uh a big idea and it has very low chance of success, but uh if it works, it's going to be big and no one else is going to be working on it, right? It's it's not something popular. It's not something if you don't do it, no one else will do it. And this is basically our situation. If you're in this situation, then then you should you should should try a chance, you know, should should go and work on it.”

“We think of that as a functional thing, or like in the real world, we're used to things that we can interact with. From the very first day we started building Roblox, for some reason we were really into having all of the objects in the world be functional. When the car would fall, like a wheel would fall off the car, it would do what you would expect it to do.”

“And then Google killed off Google Inbox, which to me was their next-gen email product. And I thought to myself, hey, if Google with its infinite resources, with the largest email user base in the world, that they're not willing to invest to try to figure out what the future of email is. Maybe I need to do something about this. And I have a long history with email. Actually, my dad and I ran an ISP in our basement in the 90s. So I call up a bunch of my Firebase buddies and I said, hey, you guys want to start another company? I'm thinking we should build an email app.”

“I do believe that you know when we create a GI retrospectively it will turn out that it's a code base that's less than 10,000 lines of code and that if you had if you had known about it back in the in the 1980s you could have done AGI back then using the comput resources available back then. Wow that's a crazy prediction. That's I I think retrospectively this will turn out to be to be true.”

“Roblox has primarily grown virally. Viral means word of mouth, sharing links. I was just at GDC last night and I was talking to some representatives from one of the big four short form video platforms. They said a third of the gaming content on their platform is Roblox content. By having users and influencers share interesting things, that does create a lot of viral pull on the platform.”

“We chose Pinecone primarily for performance considerations. It has a feature that none of the other top-tier vector databases has, which is name-stacing, where we can, without a performance penalty, have a huge number of users on there together. So I think if you're in the process right now of picking your vector database, you should think, how many namespaces do I need? Is it one per user? Is it one per company? Is it one global one?”

“There's a cloud aspect to it. We run on our own cloud. It's super efficient, super cost effective. We have 40 plus data centers all around the world. We have hundreds of thousands of servers, you know, at peak times when Roblox is hitting 20 or 30 or even more million people. That's a lot of compute complexity.”

“We didn't reinvent the wheel with the ingredients. We just remixed the format. It's the same thing as taking a successful software product and moving it to mobile, or taking a successful supplement and making it a gummy. You take a proven value proposition and deliver it in a way that fits better into a person's daily routine.”

“And I would even emphasize that to expect such a result where the generalist outperforms specialists on the very niche domains that, you know, the specialists have kind of been overfit to, this was actually quite shocking to me. You know, like, I think there's been so many examples over the past years where people have tried to scale single task methods to multitask methods. And you definitely get a lot, you know, maybe you learn faster, you learn a more robust policy that's less brittle to small perturbations. But oftentimes, you have to give up raw performance, right? Generally, in a lot of cases, the only way to max out your performance on this one narrow regime that you care about is to train a specialist and overfit to that domain. And so it was really exciting here to kind of see positive transfer, where the generalist outperforms even this presumably very tuned baseline from the individual labs on their setups themselves.”

“Perhaps recently, you know, you know, for example, with this work, Pivot, maybe the answer is that actually there is some very good amount of physical intelligence already contained in these like internet trained models by themselves without any robot data pre-training or fine tuning. Again, I don't, I also don't think that like internet data alone, just watching, you know, Reddit threads and Wikipedia is enough to solve contact rich robotics. But I do think that we've so far just been like seeing the tip of the iceberg for the knowledge that is already contained in these, you know, large VLMs.”

“Attention is the most valuable currency.”

“I look at it with LLMs and with the automation we would like to build if it was like auto triage and stuff, being more of a knowledge base. It is a corpus of information about everything that is going on at your business and everything you've ever sent and everyone you've ever talked to and all of your SaaS notifications, all of your meeting invites, everything. We can now mine that to do useful things for you. I think it's going to be a reframing from a tool to send and receive messages to a knowledge base that knows all about you that can help you get your job done.”

“I think we always wanted to get here to have something like quality assets that people can simply hold on chain, self-custody, or, you know, borrow land loop, which is like kind of like a simple way of tranching it, you know, getting the senior trash or the junior trash by lending or by looping it.”

“Like literally and maybe to kind of just put this a bit more concretely, you know, if you have your robot in some given initial condition and, you know, you try something with RT1, RT2, it doesn't work. Well, you're kind of out of luck. You can try the same thing over and over again. You can slightly maybe rewrite the language instruction, like instead of, you know, pick up the cocaine, you can write like maybe like lift the cocaine, but you don't really have the granularity you need to be like, actually, you are two centimeters, you know, too low. You missed the table because it's at a new height. It's kind of obscured by shadows. So you want to like be more gentle and approach more from the left. There's no really way to do that right now with the interfaces, the language interfaces that we train RT1 and RT2 on. But with RT trajectory, the idea is maybe if you have this kind of like line sketch of a course trajectory of how the robot should do the task, you could, under the same initial conditions, just change the prompt a little bit, do some prompt engineering and actually see qualitatively different behavior from the robot.”

“So uh what we're doing at India is uh we're doing program synthesis research. And when I talk about program synthesis, often people ask me, oh, so are you doing like codegen? are you building an alternative to coding agents and that's actually not at all what we are doing. We are working at a much much more uh much lower level than that. Uh what we're actually doing is that we are trying to build a new branch of machine learning an alternative to deep learning itself uh rather than like coding agents. Coding agents are like this very very high level last layer piece of the stack and we're actually trying to rebuild the whole stack on top of different foundations.”

“I don't want to spend my time on a small business anymore. If I'm going to put in the same amount of effort and stress, I want to make sure the ceiling is ten billion dollars, not ten million. You have to look at categories that are already massive but haven't been disrupted by a modern brand or a better user experience in decades.”

“We did the thing where you take an email, you remove a section, and then you train it on the correct answer being the actual email you set in the first case. Your data set is emails with sections removed and then the correct output is the section completed. We did this in a bunch of cases. This taught it the formatting and generally how emails should work. That combined with the RAG approach that I talked about and some prompting was enough to get the voice right as well.”

“I don't want to spend my time on a small business anymore. If I'm going to put in the same amount of effort and stress, I want to make sure the ceiling is ten billion dollars, not ten million. You have to look at categories that are already massive but haven't been disrupted by a modern brand or a better user experience in decades.”

“There's a massive opportunity in building an ACH distribution layer. Right now, moving money is still slower and more expensive than it should be for most businesses. If you can create a seamless way for companies to handle those high-volume transactions without the typical banking friction, you're sitting on a gold mine that every enterprise will want.”

“You have to be willing to fail on ninety percent of your ads. We were pumping out fifty to a hundred different creative variations a week just to find the one or two winners that would actually scale. If you're not testing at that volume, you're basically just guessing with your marketing budget and hoping for a miracle.”

“His answer is, just put more interesting stuff in front of the camera. Make what's in front of the camera more interesting. And the equivalent of that, at least for me as a non-fiction writer, is doing interesting things. Go out in the world, do interesting things, or observe interesting things in real life and write about those things. Do experiments, et cetera. Anything that is analysis-based is relegated to the machines at this point. They're so good. AI, broadly speaking, LLMs being one manifestation of that are just too good. They're so good. So do interesting things and write about them.”

“There's a massive opportunity in building an ACH distribution layer. Right now, moving money is still slower and more expensive than it should be for most businesses. If you can create a seamless way for companies to handle those high-volume transactions without the typical banking friction, you're sitting on a gold mine that every enterprise will want.”

“I think it's one of the most exciting takeaways for me, at least, was the fact that the line, the boundary between what are perception problems, what are open world object recognition, and what is robot control. This line starts to blur, right? We do not have a pipeline system where you first take care of perception and you solve that and then you solve control after. We're literally just treating both of these problems as a single VQA kind of instantiation.”

“At a certain level of business, the actual product is almost secondary to the access you have. Being able to get into the right distribution channels or get on the phone with the right retail buyers is what separates the billion-dollar brands from the ones that stay stuck in Shopify land forever. Access is the ultimate unfair advantage.”

“One of the core insights that we had early on when building this was that we couldn't get planning to work for the quality of models that we were working at the time. I think that's probably still true, where if you try to break it down into a series of steps where each step sort of feeds into the next step and each step does some piece of work, that there's going to be errors made by the models at each step that propagate through. So we changed it a little bit and we said, okay, what if the goal here was to end up with one prompt that had all of the information you need in context.”

“Silicon Valley's consensus culture produces consensus founders.”

“Agentic loops running overnight, iteration and all the stories we hear about... we see that same thing is going to happen to the much more complex thing of building a video game. Building a game is super complicated because it's got art, it's got what is interesting for people, what is fun, and it’s hard to define. It’s a big mix of 3D assets and code and 3D experiences.”

“It's very intuitive. So if you like, try to learn new, new sports, like do you go surfing or skiing? I feel like during the day, like when you started, it's really hard. But I found that like once you, once you like, if you go surfing for like two days or skiing for two days, like initially it's like really hard. And then you go, you sleep overnight and then you come back. And then you're immediately much better. And I like that in some way, the learning to learn faster paper has sort of mapped it into like, as Ted said, the day cycles and the night cycles, where the day cycle is sort of like in context learning, where you collect more examples, but then it's in context. And then the night cycle is like where you go retrain or find you change the weights of the model.”

“The most underrated aspect of Roblox is how much deep tech and theories around economics and theories around systems sit underneath it. Behind that very spontaneous 'let's just go play something together' there's a lot of deep tech. There's a lot of also systems theory, like we've had to design an economy. We've had to design thoughtful search and discovery. We've had to design thoughtful systems.”

“I think we always wanted to get here to have something like quality assets that people can simply hold on chain, self custody, or, you know, borrow land loop, which is, like, kind of, like, a a similar way of tranching it, you know, getting the senior trash or the junior trash by lending or by looping it. We always wanted to have this, but the the assets were never there. So we always had native, crypto, so ETH and Bitcoin, and stable coins.”

“As you want to scale from hundreds in a community to thousands and then tens of thousands, you really want to do that with autonomy. I think this is another area where the administration and the FAA, the DOT are really leaning in to look at how do we make our airspace safer and how do we increase the capacity of it.”