80,000 Hours Podcast With Rob Wiblin

Big machine learning models can identify plant species better than any human, write passable essays, beat you at a game of Starcraft 2, figure out how a photo of Tobey Maguire and the word 'spider' are related, solve the 60-year-old 'protein folding problem', diagnose some diseases, play romantic matchmaker, write solid computer code, and offer questionable legal advice. Humanity made these amazing and ever-improving tools. So how do our creations work? In short: we don't know. Today's guest, Chris Olah, finds this both absurd and unacceptable. Over the last ten years he has been a leader in the effort to unravel what's really going on inside these black boxes. As part of that effort he helped create the famous DeepDream visualisations at Google Brain, reverse engineered the CLIP image classifier at OpenAI, and is now continuing his work at Anthropic, a new $100 million research company that tries to "co-develop the latest safety techniques alongside scaling of large ML models". Links to learn more, sum