Unsupervised Learning with Jacob Effron
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.
00:45:42 · Jacob Effron
[00:45:42] S1: You're obviously doing a lot of things in house like sandboxes and, you know, web search and, you know, helping people with their their models over time. And, you know, I I think one question a lot of people are asking is, you know, what parts of the AI infrastructure end up just being subsumed into these future AI hyperscalers and, like, live, you know, in just one combined offering? And then what are, like, the standalone pieces of AI infrastructure that will persist as companies?
00:46:06 · Danila Shtan
[00:46:06] S0: In a sense, I think it will, like, it will kind of mimic what's happened with like the legacy generation of clouds, previous generation of clouds. Right? When your growth kind of dictates that you need to start addressing new and like new sectors, new markets, etcetera. Because otherwise your growth is like bounded and you can't like can't show your projections, can justify your valuation, etcetera, etcetera, etcetera. So there will be a natural push for the larger companies to start like increasing their portfolio, like trying to get into new products, into new services, etcetera, etcetera, etcetera. It doesn't mean that there will be a one size fits all solution. Because in a sense, if you're concerned by that, you will... Like, we just need to stop doing whatever we are doing and just wait for like OpenAI to rule the world, Anthropic to rule the world. Because these companies will eventually... Like, you do realize that OpenAI has models, runs inference. They have their own search that they... Like, they don't exactly expose it. But if you're building the agent on their platform, it has access to search. They have all kinds of like sandboxing, local agents, cloud agents, etcetera, etcetera, etcetera. They both... OpenAI and Anthropic are now investing in forward deployed organizations and are gonna go and do the work that was traditionally like, I don't know, Deloitte's or like Accenture's piece of pie. Right? So they will be everywhere. And I think this is a natural motion for the large company to start getting into a broader markets. But it doesn't mean this is... They are gonna be the only ones. So even nowadays, there is a place for independent object storage players all of a sudden. Right? Or independent compute players or independent small scale inference players for that matter. Independent database players. Like like, on one... Like, you've seen, like, Google has, like, big BigQuery and whatever, all kinds of data stuff. But then Snowflake kinda, like, appears from out of nowhere. AWS has, like, all kinds of, like, managed databases, large scale databases, like Aurora, Redshift, etcetera, etcetera, etcetera. But then MongoDB appears. And it's pretty successful. I can't say it's, like, super large scale and probably by nowadays standards will never be. Because nowadays standards for a large company is like trillion plus. Right?
00:48:55 · Danila Shtan, Jacob Effron
But like two years ago it was a very solid and very successful company. Or someone like Clickhouse appears with their cloud offering. Right? Also a massive managed database, an independent company that finds its niche and works it real well. So I think, like, larger company, larger clouds will grow. They will have, like products in every sector and will be pretty successful at selling them. Those because of bundling, because of their sales power, etcetera, etcetera, etcetera. But there will always be a place for niche players. And because the market is huge, niche doesn't mean small. Niche doesn't mean small scale or low revenue or low valuation. This can be solid companies. [00:49:43] S1: Yeah. I mean, as you mentioned, you know, OpenAI and Anthropic having this kind of broad suite of offerings too. I mean, in many ways, they're obviously building their own AI clouds. And I thought one thing that was interesting recently was, you know, obviously, limitation of those AI clouds versus others is is the the, you know, having just one model family, right, to be able to call from. But I thought it was really interesting that OpenAI announced that partnership with Baseten. I'm curious what your take on... Was was on that. I mean, is that them just trying to get into this general, you know, hyperscaler game across models?