Mechanistic Interpretability in Deep Learning - Multiple Results

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/