00:52:40 · Vincent Weisser, Jordi Hays, Rodrigo Liang
It's, like, going where, like, the big labs almost can't go necessarily, taking big, like, bold bets that also might not pay pay off all of them. Right? Or, like, if you have 100 shots on goal, like, some of them will probably pay off and result in interesting outcomes. So I think this is, like, really also, I think, what we are empowering, right, is is kind of, like, helping these new nail labs and and big AI natives and enterprises to move much faster and not have to basically all build the same stack each by themselves in house. Because obviously, a of them are like tiny teams of like tens of people instead of like thousands. So we're able to like help them move much faster basically, But I'm adopting our sec. [00:53:20] S0: When you hear of a, you know, major American tech company, let's say, someone [00:53:29] S4: in [00:53:29] S0: the mag seven that has extra capacity, do you reach out to them? Do you get do you do you do you ping them? Are you at the scale yet that that a deal would be interesting to them? Or are they really searching for these, you know, $10,000,000,000 plus opportunities?
00:53:29 · Jordi Hays, Vincent Weisser, John Coogan
[00:53:29] S0: the mag seven that has extra capacity, do you reach out to them? Do you get do you do you do you ping them? Are you at the scale yet that that a deal would be interesting to them? Or are they really searching for these, you know, $10,000,000,000 plus opportunities? [00:53:47] S3: For sure, like, we already are, like, sourcing, like like, pretty large clusters, so it's, like, sometimes, like, up to, like, five to 10,000 GPUs. So it's, like, we we basically, like, looking at every source and pocket of supply that we can find. Like, we've literally turned every stone to find, like, the last tribute available on earth. And, like like, we we've we've been quite good at at that. So it's like in in some ways, like, I think we're, like that that has been, like, one of the core tenants almost, like, since the beginning is that, like, we we really didn't want it to, like, orchestrate, like, the global compute supply efficiently. So we did a lot of, like, optimization fault tolerance and this retraining even in the early days to, like, train across, like, distributed compute. So it's, like, definitely I I think to this question, it's, like, like, I think it's something that we're definitely, like, considering. Like, if there's any anyone with some spare GBUs here, you can always set us up. [00:54:40] S1: That's great. Alright. Back on on China, do you agree with my perception that if there is some sort of lockdown on Chinese open source export controls, that would not affect
00:54:40 · John Coogan, Jordi Hays
[00:54:40] S1: That's great. Alright. Back on on China, do you agree with my perception that if there is some sort of lockdown on Chinese open source export controls, that would not affect [00:54:56] S0: Yeah. Are they mad that American companies are distilling on or or post training their open source models? [00:55:03] S1: It was by design. That was goal of the project. But I what what I'm what I'm interested about is is would they try and claw back access to Kimi or GLM, any of those models that are already been deployed? Because there's an element of, like, once the the weights have been downloaded, it's sort of just out there. Of course, you could go and try and, like, sue every company, but that's very hard if you're in an American jurisdiction and you're a Chinese company. But how would you see that playing out? Would it just be going forward, no more open source, and that's the CCP telling Chinese companies or some other shape of of of, like, restriction?
00:55:03 · John Coogan, Vincent Weisser, Byron Boots
[00:55:03] S1: It was by design. That was goal of the project. But I what what I'm what I'm interested about is is would they try and claw back access to Kimi or GLM, any of those models that are already been deployed? Because there's an element of, like, once the the weights have been downloaded, it's sort of just out there. Of course, you could go and try and, like, sue every company, but that's very hard if you're in an American jurisdiction and you're a Chinese company. But how would you see that playing out? Would it just be going forward, no more open source, and that's the CCP telling Chinese companies or some other shape of of of, like, restriction? [00:55:43] S3: Yeah. I think it's really hard to know. I think, like, a good example was, like, in some extent, like, the most popular Chinese malts already have been closed for Nommo, is coin. Right? Like, in some ways, like, they've actually, like changed their licensings Mhmm. And stopped almost closing. So I think there will be both, like, companies changing their policies, right, but then also I think like, probably like state intervention, right, it's like in different shapes or form. Mhmm. So I think basically, one can't rely on the steady stream of frontier open, like, releases out of China in many ways, but it's, like, brought from different perspectives. And I think, similarly, a lot of other sovereigns, like, obviously, including The US also doesn't want to build on on necessarily Chinese op mods. It's like Mhmm. [00:56:23] S2: I think
00:56:23 · Byron Boots, Vincent Weisser, Rodrigo Liang
[00:56:23] S2: I think [00:56:23] S3: a lot of American enterprises, obviously, also, like, sovereign use cases, like, need American op mod, but I think similar for for other continents. Right? It's like, I think there there's been a lot of work, obviously, and and we're, like, collaborating with people also across Europe, across India, across other geos. So it's like, I think we'll we'll see a much more, like, multipolar, I think, open, like, ecosystem of, like, open frontend models. So I think that's, like, a healthy, like, balancing away from just relying on Chinese open models, even though they've obviously, like, been a great accelerant of, like, open source progress. I think it's also unhealthy to rely just on that ecosystem. [00:57:01] S4: Yeah. [00:57:02] S3: And, yeah, like, I think we'll be like, there will be, I think, a bunch of, like, quite unpredictable changes similar to all. Like, the last few months have been quite unpredictable Mhmm. I think, to everyone involved. So I think this will continue to be the case in the sense that it will be, like, quite a dicey policy like, AI policy landscape for the next few years. Mhmm.
00:57:02 · Vincent Weisser, John Coogan
[00:57:02] S3: And, yeah, like, I think we'll be like, there will be, I think, a bunch of, like, quite unpredictable changes similar to all. Like, the last few months have been quite unpredictable Mhmm. I think, to everyone involved. So I think this will continue to be the case in the sense that it will be, like, quite a dicey policy like, AI policy landscape for the next few years. Mhmm. [00:57:21] S1: Last question. Data centers are data center construction, new data center construction, deeply unpopular in America domestically. Simultaneously, the workloads that are being done in AI data centers are basically latency is basically irrelevant. For training, certainly, for most inference tasks, if you're waiting a couple minutes for a result, an extra five hundred milliseconds to get across the world isn't gonna This feels like a recipe for global competition, for aggressive data center expansion in a country that does see it favorably, that does see an economic boom from it, or does have a lot of energy. What is the state of the non domestic, non US data center build out?