Erik Bernhardsson: evaluation

Transcript context

…Yeah. Another big thing in the infra 2.0 wishlist was truly serverless infrastructure. The other on your landing page, you called them native cloud functions, something like that. I think the issue I've seen with serverless has always been people really wanted it to be stateful, even though stateless was much easier to do. And I think now with AI, most model inference is like stateless, you know, outside of the context. So that's kind of made it a lot easier to just put a model, like an AI model on model to run. How do you think about how that changes how people think about infrastructure too? Yeah. I mean, I think model is definitely going in the direction of like doing more stateful things and working with data and like high IO use cases. I do think one like massive serendipitous thing that happened like halfway, you know, a year and a half into like the, you know, building model was like Gen AI started exploding and the IO pattern of Gen AI is like fits the serverless model like so well, because it's like, you know, you send this tiny piece of information, like a prompt, right, or something like that. And then like you have this GPU that does like trillions of flops, and then it sends back like a tiny piece of information, right. And that turns out to be something like, you know, if you can get serverless working with GPU, that just like works really well, right. So I think from that point of view, like serverless always to me felt like a little bit of like a solution looking for a problem. I don't actually like don't think like backend is like the problem that needs to serve it or like not as much. But I look at data and in particular, like things like Gen AI, like model inference, like it's like clearly a good fit. So I think that is, you know, to a large extent explains like why we saw, you know, the initial sort of like killer app for model being model inference, which actually wasn't like necessarily what we're focused on. But that's where we've seen like by far the most usage. Yeah. And this was before you started offering like fine tuning of language models, it was mostly stable diffusion. Yeah.…

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