Andreas Stuhlmüller, CEO of AI research platform Elicit, discusses why he chose to start a nonprofit research lab rather than pursue an academic professorship after his Stanford postdoc.
Insight
Stuhlmüller: AI requires deeper world models to make novel scientific discoveries
“Having deeper models of how, let's see, what are the underlying structures of different domains, how they're related or not related, I think will be an important ingredient for models actually being able to make novel contributions.”
Prediction Not checkable as stated
Stuhlmüller: Generalist AI research platforms will be a winner-take-all market
“So I think there will be, at least within research, I think there will be, like, one best platform, more or less for this type of generalist research. I think there may still be, like, some particular tools, like, for genomics, like, particular types of module…”
Opinion
Stuhlmüller: Trading inference compute for answer accuracy is undervalued in AI
“Being able to invest more or less compute into getting more or less accurate answers is, I think, one of the core things we care about, and that I think is currently undervalued in the AI space.”
Insight
Stuhlmüller: Pure long-context LLMs are significantly harder to debug than RAG
“In one sense, I think you're right that the throw everything into the context window thing is easier to maintain because you just can swap out a model. In another sense, it's, if things go wrong, it's harder to debug, where, like, if you know, here's the proce…”
Disclosure
Stuhlmüller: Elicit builds scaffolding rather than training foundation models
“The way we are building Elicit is not let's train a foundation model to do more stuff. It's like let's build a scaffolding such that we can deploy powerful models to good ends.”
Disclosure
Stuhlmüller: Seed VCs urged Elicit to build legal AI over research
“We did encounter, I guess talking to VCs for our seed round. A lot of VCs were like, you know, researchers, they don't have any money. Why don't you build a legal assistant?”