The Ledger, every show

“There's no, like, I don't think, like, unless we have, like, great breakthroughs, like, George's vision is achievable, like, or, like, he should be thinking about a narrower problem, such as, I'm only gonna make this for, like, work for self-driving car con ne…”

“If they end up expanding onto the server side, and they'll probably build something like PyTorch as well, right? Like, eventually, that'll where it will land. And I think there, they will kind of fail on the, like, lack of differentiation. Like, it wouldn't be…”

“I think, like, Together and Fireworks and all these people are trying to build some faster CUDA kernels and faster, like, you know, hardware kernels in general. But those modes only last for a month or two. Like, these ideas quickly propagate.”

“You can write a very simple framework but then you also should be willing to eat the long compile times of, like, searching for that optimal performance at runtime.”

“The mode that Nvidia has right now, I feel like, is that they're, they have the interconnect that no one else has. Like, AMD GPUs are pretty good. I'm sure there's very silicon that is not bad at all, but, like, the interconnect like, NVLink is uniquely awesom…”

“My view of the LLM inference market in general is that it's like the laundromat model. Like you, the margins are going to drive down towards the bare minimum, like It's gonna be all kinds of arbitrage between how much you can get the hardware for, and then how…”

“Outside of this, like, where we don't have good symbolic models, like, synthetic data obviously, like, doesn't make any sense. So synthetic data is not a magic wand where it'll work in all cases, in every case, you know, whatever. It's just where we as humans …”

“And this might be a little controversial, but like, I find a lot of arguments, ah, based on whether, like, closed source models are safer, or open source models are safer, very much related to whether, what kind of cultural, ah, culture they grew up in, what k…”

“Maybe open source models are being as used as GPT is at this point in, like, all kinds of, in a very fragmented way. Like, in aggregate, all the open source models together are probably being used as much as GPT is. Maybe, you know, close to that.”

“If that central sinkhole is there, who's gonna go coordinate all of this integration across all of these, like, open source frontends? But I think if we do that, if that actually happens, I think that probably has a real chance of the open source models having…”

“Probably doesn't have a chance against Google, because, you know, Google has Android, and Chrome, and Gmail, and Google Docs, and everything, you know. So people just use that a lot.”

“The whole process of, like, how we think we got to AGI will be continuous and not, like, not discontinuous”

“The open source thing will be very much in line with getting to AGI, because open source has that, like natural selection effect. Like, if a better open source model comes, Really no one says, huh, I don't want to use it because there are ecosystem effects, I'…”

“The LLSS leaderboard is the best thing we have right now to understand whether a model is better or not versus another model, but it's also biased and only having a sliver of view into how people actually use these models. Like, the people who actually end up …”

“Home robotics being, like, five to seven years away into commercialization. I think, like, It's not, like, next year or two years from now, but, like, five to seven years from now, I think, like, a lot more robotics companies might pop out.”

“My view is actually hardware is still the bottleneck, and AI is also a little bit of bottleneck, but, like, I don't think there's any, like, obvious breakthroughs we need. I think it's just work.”

“Mojo as a fundamental frontend would be replacing PyTorch, not, like, augmenting PyTorch. So, in that sense, I don't see a synergy in more deeply, like, integrating Mojo.”

“Each large company has a sufficient enough set of verticalized workloads that have a pattern to them that, say, a more generic accelerator like an NVIDIA or an AMD GPU does not exploit. So there is some level of power efficiency that you're leaving on the tabl…”

“And for, then, like, the thesis was very simple. It was, like, AI is currently rate-limiting Meta's ability to do things. Our ability to build various product integrations, moderation, various other factors. Like, AI was the limiting factor, and we just wanted…”

“But the amount of feedback that is driving back into the open source ecosystem is, like, negligible. Maybe less than one percent of, like, the usage.”

“That is by the end of this year, and 600 K H-One hundred equivalents. With 250 K H-one hundreds and including all of the other GPU or accelerator stuff, it would be 600 and something K aggregate capacity.”

“So, I think the, it's all a matter of time. I think time is the biggest bottleneck. It's like, when do you stop training the previous one, and when do you start training the next one? And how do you make those decisions? The data, do you have net new data, bet…”

“If you don't have enough compute, you figure out how to make do with smaller models, but like, no one as of today, I think, would feel like they have enough compute. I don't think, like, I've heard any company within the AI space be like, oh yeah, like, we fee…”

“When we think about audio, or images, or video, they're, like, so advanced that we have the concept of color spaces, we have the concept of, like, frequency spectrums, like, you know, we figured out how ears process, like frequencies in mouse spectrum, or what…”

“50 years from now, it would be pretty obvious to, like, kids of the generation to just, like, you know, I guess I was saying, I was gonna say roll a reel on their phone, maybe phones will be, they're just like, you know, on their glasses, they're watching some…”

“It's used in Mars rover simulations, to drug discovery, to Tesla cars, and there's a huge diversity of, like, applications in which it is used in.”

“I think the scariest was when I went to visit CERN at some point, and they said they were using it, PyTorch, and they were using GANs at the same time for, like, particle physics research, and I was scared more about the fact that they were using GANs than the…”

“A couple of months ago we deployed Our home robotics stuff into, like, several tens of New York City homes, and like, try to make it do a bunch of tasks”

“PyTorch is like a 190,000 lines of code or something at this point.”