Neel Nanda joins the podcast to talk about mechanistic interpretability and how it can make AI safer. Neel is an independent AI safety researcher. You can find his blog here: https://www.neelnanda.io Timestamps: 00:00 Introduction 00:46 How early is the field mechanistic interpretability? 03:12 Why should we care about mechanistic interpretability? 06:38 What are some successes in mechanistic interpretability? 16:29 How promising is mechanistic interpretability? 31:13 Is machine learning analogous to evolution? 32:58 How does mechanistic interpretability make AI safer? 36:54 36:54 Does mechanistic interpretability help us control AI? 39:57 Will AI models resist interpretation? 43:43 Is mechanistic interpretability fast enough? 54:10 Does mechanistic interpretability give us a general understanding? 57:44 How can you help with mechanistic interpretability? Social Media Links: ➡️ WEBSITE: https://futureoflife.org ➡️ TWITTER: https://twitter.com/FLIxrisk ➡️ INSTAGRAM: https://www.instagram.com/futureoflifeinstitute/ ➡️ META: https://www.facebook.com/futureoflifeinstitute ➡️ LINKEDIN: https://www.linkedin.com/company/future-of-life-institute/

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“What did the council decide on item 42?” — answered with the speaker and the moment.