ABOUT THIS EPISODE
A new essay from former OpenAI researcher Nick Cammarata is being hailed as a potentially historic AI breakthrough. His argument: neural networks may already be far more understandable than researchers believed, and years of apparent complexity may reflect flaws in how we’ve been looking at them. NLW breaks down the surprisingly simple connection between cat faces and car fronts, why bigger models could be easier to interpret, and what this could mean for detecting AI deception—with a look at what the evidence shows and what remains unproven.
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