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This premiere episode provides a comprehensive history of artificial intelligence development from the 1950s through the present day, tracing the cycles of excitement and disappointment ("summers and winters") that led to today's breakthrough moment with large language models. The hosts e…

What if We Succeed?

This episode explores why AI systems might develop harmful or deceptive behaviors even without malicious intent, examining concepts like convergent instrumental goals, alignment faking, and mesa optimization to explain how models pursuing benign objectives can still take problematic actions. The ho…
This episode explores how sparse autoencoders can decode the phenomenon of superposition in neural networks, demonstrating that the seemingly impenetrable compression of features into neurons can be partially reversed to extract interpretable, causal features. The discussion centers on an Anthropic…
This episode explores how Anthropic researchers successfully scaled sparse autoencoders from toy models to Claude 3 Sonnet's 8 billion neurons, extracting 34 million interpretable features including ones for deception, sycophancy, and the famous Golden Gate Bridge example. The discussion emphasizes…
Ansvarsfraskrivelse: Podkasten og kunstværket, det finnes indlejret på denne siden, er fra John Jezl and Jon Rocha, som tilhører dens eier og ikke er tilknyttet eller godkjent av Listen Notes, Inc.