Ryan Kidd: belief

Transcript context

…Yeah, so I mean, we do some of the standard stuff that you would see at other tech companies, right? Like we have CV review, we have some code signal tests, so brush up on your coding skills and so on. And they do detect AI use. We are, of course, considering ways to allow for tests that include AI use, but these are obviously harder, right? They're harder to design, they're harder to check and so on. But yeah, that's part of our general application. Now that's for some streams. I'll say this, mentor selection, sorry, scholar selection, like we're trying very hard to provide something like a service to mentors. So if a mentor says to us, I don't want to do CV review, I don't want to do code signal, I just have this selection problem that I want fellows to, applicants to work on, and then like, I want you guys to help me evaluate this. Build me like a team of contractors or some automated evaluation process to do first pass screening, and then we'll go from there. That's our favorite kind of evaluation in some way, because we know that it's as close as possible to the actual job, the actual research as we can get. Of course, this is typically, in Nanda's case, it's like, go away and do a 10-hour mechinterp pseudo-work test and then present your results to me. You can use AI, do whatever, just find something interesting. And this is great, because then we get great results. Some other streams, it's harder to do this. It's harder to administrate. And so we do rely on some proxies that are perhaps less specific than ideal, but I think are no worse than anyone else in the industry is doing. And of course, I think the way you stand out, obviously it's going to depend on the specific mentor, because MATS is very heterogeneous in that respect, right? The best thing to apply to Neil Nandastream is going to be vastly different than applying to Ethan Perez and the Anthropic Megastream. But in general, you want to really understand your basics. about AI safety, so do a blue dog course, right? Because there may be some critical knowledge or a paper that if you haven't read, you don't understand, if you don't understand what deceptive alignment is, that might be really bad for Ethan Perez or Buck Schlegeris' kind of control research, and even applying, getting to the streams. If you don't understand that for InterpStream, probably doesn't matter as much, unless, of course, you're dealing with deception and you're interpreting. So make sure you understand your basics. Make sure that if you're applying to a stream that is empirical heavy, that you can do code signal tests, you can code, including without AI assistance, at least for the time being. It doesn't hurt to apply to other programs as well. Mass is far from the only program out there now. This is not like early days. Like there are so many great research programs out there. Pivotal, ERA, PIBS, Laser Labs, SPAR, ARENA for technical. I think ASTRA is now running again. ram out there now. This is not like early days. Like there are so many great research programs out there. Pivotal, ERA, PIBS, Laser Labs, SPAR, ARENA for technical. I think ASTRA is now running again. Yeah, there's tons of great programs out there. And that can really booster your CV. If you have experience in the kind of research that you want to do at Mass already, then so much the better. Consider it like a postdoc opportunity or something, or a post-research opportunity. Build your own independent projects. Yeah, sorry if that's like too much advice to be actionable. Yeah, I think it boils down to tangible product is, is like king, right? I mean, and I, I say that always in the AI engineering world as well, if any, you know, and I'm far from the world's leading expert on how to break into that space. But what I always tell people if they ask me is a working demo is kind of the coin of the realm. You know, like it's all. People might be interested in what you have to say, but they really want to see that you can make something work. They want to see it online. It could be a replet or it could even be a collab notebook or something, but you've got to make something that can work. And it sounds like this is a pretty similar worldview. You've got to show that you can get in there, make something happen, as you put it with Neil's track in particular, find something interesting. If you can do that, we might have something to talk about. One thing that jumps out is like maybe not as emphasized as I would have thought is being in command of current research. That's something I think at this point, like really nobody can keep up with all the current research because, you know, that exponential has gotten away from all feeble human minds, I would say, maybe with a few hyperlexics that can still keep up. But I have found like Keeping up with research is a pretty-- feels important to me. It feels like an important part of how I stay conversant with people across a lot of different areas. But obviously, what I'm doing in trying to be conversant with people across a lot of different areas is not the same thing as research. How much emphasis do you think mentors in general put on being on top of the literature, so to speak?…

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