Geoffrey Hinton in conversation with Fei-Fei Li — Responsible AI development on HackerTube: recommended by 2 Hacker News commenters across 2 separate months, 2024.
interview · dated
A 2023 University of Toronto conversation between Geoffrey Hinton and Fei-Fei Li on responsible AI development. They look back at the history of deep learning and ImageNet and discuss the ethics and risks of AI.
HN recommends it for Hinton's research history and the two pioneers reflecting on a decade of progress.
“Goes over Hinton's history and why he went the direction he did with his research”
3 Hacker News comments link this video. Each one links back to its thread.
See "Geoffrey Hinton in conversation with Fei-Fei Li" where the two got together and looked back at the developments over the last ~10 years, including why and how they did their part: * ▶ this video
in “A stubborn computer scientist accidentally launched the deep learning boom” · View on HN
This 'conversation' with Geoffrey Hinton and Fei-Fei Li goes over a lot of the history of things (1h50m): * ▶ this video * [link] ('mirror') Goes over Hinton's history and why he went the direction he did with his research, as well as Li's efforts with ImageNet.
in “The Google employees who created transformers” · View on HN
François Chollet says LLMs do not learn in-context. But Geoff Hinton says LLMs' few-shot learning compares quite favorably with people! ▶ this video The truth is in the middle, I think. They learn in-context, but not as well as humans. The approach in the article hides the unreliability of current LLMs by generating thousands of programs, and still the results aren't human-level. (This is impressive work though -- I'm not criticizing it.)
in “Getting 50% (SoTA) on Arc-AGI with GPT-4o” · View on HN