No Priors Ep. 41 | With Imbue Co-Founders Kanjun Qiu and Josh Albrecht

Imbue is a company developing AI agents that can reason and code. Today, Elade and I sit down with Kanjun Qiu and Josh Albrecht, co-founders of Imbue, to discuss training large foundation models for high-level reasoning, why agents require architectures different from large language models or language token prediction models, and how current computers are getting in the way of their users. Kanjun, Josh, welcome to No Priors.

Thank you.

Thanks.

So perhaps you can start by just telling us the story of how you guys know each other and where the idea for Imbue came from.

Josh and I met at a conference and then started a big house together, uh, it was a big house, 20% house, and also started this first company around the same time. I've always been really interested in agency, uh, and kind of like how do we enable humans to have more agency, and Josh has always been really interested in AI, uh, and so it kind of made sense. Uh, we, at that time, talked about like, "Oh, you know, someday we're gonna be able to have AI systems that give humans a lot more agency." Fast-forward to 2018 or so, uh, we were running an AI recruiting company called Sourceress, and that was actually kind of the first AI agent that we built. Um, it was, you know, not transformer models, uh, like, more old-school MLP, uh, but it was a system that recruiters used and kind of automatically got candidates in their inbox, and we learned a lot about, "Oh, if you have an autonomous system like this, like what do you actually need to make it work?" And around that time, some of our housemates were building GPT-3, and, uh, we were seeing, like, "Oh, scaling works. You know, if we just keep scaling, actually, you're gonna get pretty far with a lot of these language models." So our question at that time was, you know, "How far can we get with language models? Does this kind of self-supervised learning, which is working so well on language, work in other modalities as well?" So in early 2020, that's when we first started seeing self-supervised learning working across video and images and language, and we were like, "Huh, there's something really interesting here where maybe machines are learning the same kinds of representations or similar representations of what humans are learning, and maybe they can get to a point where they can actually do the types of things that humans are able to do." And that's when we first started Imbue, or start- started talking about Imbue.

You clearly know a bunch of people working at sort of large, uh, language model research labs well. When you looked at what they were doing, how did the focus come to be on agents in particular, and how is that different from a general language model?

Yeah, I- I think we've always been interested in agents, in not just, you know, recommender systems or classifiers or things like that, but in systems that are gonna go do real work for us, right? That are gonna actually be useful in the real world. Right now, you can ask some kind of chatbot something, and it'll give you back a response, but the burden is sort of on you to go do something with that to verify whether it's correct or not. I think the real promise of AI is if we can get systems that can actually act on our behalf and can accomplish goals and kind of do these larger things and sort of free us up to, uh, to focus on the things we're interested in.