Episode Details

Livestreams for the AI Engineer World’s Fair (Multimodality ft. the new GPT-4o demo, GPUs and Inference (ft. Cognition/Devin), CodeGen, Open Models tracks) are now live! Subscribe to @aidotEngineer to get notifications of the other workshops and tracks!

It’s easy to get de-sensitized to new models topping leaderboards every other week — however, the top of the LMsys leaderboard has typically been the exclusive domain of very large, very very well funded model labs like OpenAI, Anthropic, Google, and Meta. OpenAI had about 600 people at the time of GPT-4, and Google Gemini had 950 co-authors. This is why Reka Core made waves in May - not only debuting at #7 on the leaderboard, but doing so with all-new GPU infrastructure and 20 employees with <5 people on pre-training and a relatively puny $60m in funding.

Shortly after the release of GPT3, Sam Altman speculated on the qualities of “10,000x researchers”:

* “They spend a lot of time reflecting on some version of the Hamming question—"what are the most important problems in your field, and why aren’t you working on them?” In general, no one reflects on this question enough, but the best people do it the most, and have the best ‘problem taste’, which is some combination of learning to think independently, reason about the future, and identify attack vectors.” — sama

* Taste is something both John Schulman and Yi Tay emphasize greatly

* “They have a laser focus on the next step in front of them combined with long-term vision.” — sama

* “They are extremely persistent and willing to work hard… They have a bias towards action and trying things, and they’re clear-eyed and honest about what is working and what isn’t” — sama

“There's a certain level of sacrifice to be an AI researcher, especially if you're training at LLMs, because you cannot really be detached… your jobs could die on a Saturday at 4am, and there are people who will just leave it dead until Monday morning, or there will be people who will crawl out of bed at 4am to restart the job, or check the TensorBoard” – Yi Tay (at 28 mins)

“I think the productivity hack that I have is, I didn't have a boundary between my life and my work for a long time. So I think I just cared a lot about working most of the time. Actually, durin