Unsupervised Learning with Jacob Effron
00:37:27 · Danila Shtan, Jacob Effron
[00:37:27] S0: No. The workload's a workload. Like... Exactly like you said. It is slightly different, But in a sense, you need a high enough baseline to not be constrained by that. And then the rest is just your optimization problem. The way you pack things. The way you split things. Right? Like you don't need whole nodes for some of the workloads. So you need to collocate workloads. You need to have the right primitives. You need to expose those through the platform, etcetera, etcetera, etcetera. But in a sense, like differentiated workloads almost never like impose any changes on on on how you build on the lowest level. Yes, of course, like nowadays with like these new architectures, like what is it called? NVIDIA LPX, like the outcome of the grog deal. Right? This like adds to it. But in a sense, if you have experience running other generations, this is just another like 0.5 generation. Right? Yes, this will be a little bit novel and it's connected in a in a weird... Like, compared to the previous one's way. And it kinda is... Like, there are some restrictions when you can run and not run on that. But efficiency gains. And this is like just a, like a niche local addition to the platform to what to what you offer to the broader market. But in general, no. There is like way less custom, like custom solutions that you would expect from that. The workload is a workload. [00:39:17] S1: Why didn't the hyperscalers, like, move into this market faster or win this market, you know, more convincingly early on in in in this first chapter, at least?
00:39:26 · Danila Shtan
[00:39:26] S0: First of all, sometimes there is a notion that they didn't even try. There is a solid amount of business that hyperscalers get from out of this market. Like huge deals, they are very competitive. Sometimes people say, Oh, have you seen AWS prices? Well, these are public prices. I assure you. Like for proper deals, they are doing proper prices and they're very competitive. And like they're very aware of the market. I think in a sense, like there are two two angles to that. First, like what I've mentioned before, a lot of these companies need to juggle like their internal consumption and what they can put for, like, for for the broad market. And there is... Like, we are in chip shortage world. Right? So, like, if NVIDIA could have bought... Like, could have produced, like, 10 x the chips, probably this this this whole market would have been shaped differently. Because they... Like, Microsofts and Googles of the world would both buy capacity for themselves and for the broader market to operate. This was partly... Like, simply not enough capacity for their scale. Right? Because there is not enough capacity for their scale, this is a relatively small business for them. AWS revenue is what? Like, billion or something? I mean, like, a business for, like, $2.03, 4,000,000,000. It's not insignificant paying margin. But they compared to what they... Their conservative, large scale established businesses, it's not that easy either.
00:41:08 · Jacob Effron
[00:41:08] S1: Yeah. But your point is basically like they're, you know, they get a chip allocation that is like, you know, not as large as they'd want. They have to use some of that, you know, a large amount of that for training themselves. There's only so big that that inference business or that that the cloud business can be given all that. And Yeah. Yeah. It's interesting to figure out how to prioritize. Do you go after like the few folks with large contracts or do you try and get this like mid market enterprise up and coming segment? But I guess you're you're kind of doomed either way if if you only have a certain number of chips to Yes.
00:41:39 · Danila Shtan
[00:41:39] S0: Exactly. And then... And and and then at the same time, this becomes a relatively small, like, part of your revenue portfolio. And you're like, do I even need to allocate resources to that? And that is especially a pressing question because like, for the hyperscalers, it's not just a matter of like sales. It's also a matter of changing the infrastructure that was built at scale for other kinds of workloads. The networking, the throughput performance, the storage performance, by the way, right, that I've mentioned earlier. So this, like, this requires... If you want to have it universally, like, implemented on... Through the whole stack, this is a massive investment on their part that needs to be justified by the size of a potential business. And it's not that there yet. I think if we start getting out of this, like, chip shortage in, like, I don't know, two, three, five years, maybe, we will definitely see this shift. And they will pay more attention because this will become, like, increasing a large chunk of business. And they will start investing. They will, like, reorganize and redesign their, like, internals to be more accommodating to these demands, etcetera, etcetera, etcetera. And then with their whole sales power, they'll go and try to win this market. And the question is whether the novel players, like like us, for example, will be fast enough to grow and represent, like, significant competition when they get there. Yeah. And, like, I'm 100% that... Sure that they will pay more attention in the future. Yeah. Our bet is that we'll be fast enough to be in the league with them and fight as equals rather than a small player trying to run-in their trails.
00:43:39 · Jacob Effron
[00:43:39] S1: Makes sense. I what do you think happens to... Like, you mentioned there's like these, like, you know, 300 to 500, like, you know, Neo Clouds, everyone trying to get into this market. Like, as you've kind of... You know, you mentioned that you're kinda thinking the chip shortage comes to an end at some point. Like, as you zoom five years, ten years in the future, like, how many of these businesses are still around? Or like, what is the end state of this market?
00:43:58 · Danila Shtan
[00:43:58] S0: Listen, I think the whole, like, AI consumption is gonna grow. And it will be like universally used everywhere. Like AI is everywhere. Like right now, like web services are everywhere. AI services will be everywhere. So in a sense, like you have AWS, right? But you also have Hetzner. You also have DigitalOcean. You also have Linode. You also have like tons and tons and tons of local hosting providers that are giving you virtual machines, sometimes bare metal, etcetera, etcetera, etcetera. So this market is gonna be vast. Will all of the current three to 500 companies survive the next five years? I'm not sure. But I am pretty sure that there will be a place for the very long tail of providers down the line. Like, some of this, the current players will consolidate, some of them will die off, new new players will be launched, etcetera, etcetera, etcetera. It's a... Like, it's not a bad market right now. It's not a bad business to be in. So they will constantly attract capital and attention and investments, etcetera, etcetera, etcetera. And I trust that, like, in five years' time, there's still gonna be, like, hundreds of players in this market who found the investment related to and several $100,000,000, and they can offer something to someone in the market. Same as it is with, like, with the the small scale clouds like DigitalOcean these days. Right? Like, DigitalOcean did not die because AWS is growing.