Shawn Wang: belief

Transcript context

…The model just saw something out of domain immediately and was like, I have no idea what to do. And you need it to be able to overlap that positional embedding on top of each other. One follow up, right? Before we close out. I think being on Twitter and looking at all these new headlines is really helpful, but then it only gets you a very surface level understanding. Then you still need a process to decide which one to invest in. I'm trying to dig for what is your formula for deciding what to go deep on and what to kind of skip. From a practical standpoint, as a company, I already know there are three to five things that will be valuable and useful to us. And then there's other stuff that's out of scope for different reasons. Some stuff is out of scope from, hey, this is not going to impact or help us. And then other things are out of scope because we can't do it. A really good instance for that is specific algorithms for improving extremely large scale distributed training. We're not going to have the opportunity to get 2000 H100s. If we do, it'd be really cool. But I'm just saying, as for now, you got to reach for the things that would be useful. Things that would be useful for us, for everybody actually, to be honest, is evaluations, different post-training techniques, and then synthetic data construction. I'm always on the look for that. And then how do I figure out which new piece of news is actually novel? Well, that's sort of my mental cache to a certain extent. I've built up this state of, hey, I already know all the things that have already been written for the state of the art for certain topic areas. And then I know what's being recycled as an empirical study versus something that actually is very insightful. Underrated specific instance would be the DeepSeek paper where I'd never seen it before, but the multi-head latent attention. That was really unexpected to me because I thought I'd seen every way that people wanted to cut mixture of experts into interesting ways. And I never thought something would catch my eye to be like, oh, this is totally new. And it really does have a lot of value. That's mainly how I try to do it. And you talk to your network too. I just talk to the people and then know and make sure that I have certain subject matter experts on speed dial that I also like to share information with and understand, hey, does this catch your eye too? Do you think this is valuable or real? Because it's a noisy space we're in right now, which is cool because it's really interesting and people are excited about it. But at the same time, there is actually a 10X or more explosion of information coming in that all sounds really, really unique and new. And you could spend hours down a rabbit hole that isn't as useful. Awesome, Mark.…

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