Understanding the inner thoughts of AI

Neel and his team are trying to do something phenomenally difficult: understand an intelligence that didn't come with a manual. Together, they explore the cutting-edge "neuroscience" of artificial intelligence—revealing the surprising, elegant structures being discovered inside these networks (like spare autoencoders), the inherent limits of looking under the hood, and why interpretability is absolutely essential if we are to build safe, aligned and trustworthy AI as we move towards AGI. Learn more about this area of research via https://deepmind.google/

Timecodes

• 00:00 Introduction
• 02:41 Motivation for interpretability research
• 04:01 Mechanistic interpretability
• 08:14 Chain of thought monitoring
• 18:14 Interpretability techniques
• 35:00 Auditing models for safety
• 48:53 What comes next for interpretability

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