Ep. 203: Melanie Mitchell on Can Artificial Intelligence Beat Human Thinking

Melanie Mitchell is one of the leading AI researchers in the world. She is Professor at the Santa Fe Institute. Her current research focuses on conceptual abstraction and analogy-making in artificial intelligence systems. Melanie is the author or editor of six books and numerous scholarly papers in the fields of artificial intelligence, cognitive science, and complex systems. Her most recent book is entitled ‘Artificial Intelligence: A Guide for Thinking Humans’. This episode’s podcast covers:

Evolution of AI from cybernetics to neural networks and deep learning
How big (labelled) data helped AI
What is intelligence?
The problem of extremes
Neuro-symbolic approaches
AI’s weakness: abstraction and analogy
What can LLMs really do?
What benchmarks to use
What AI lacks compared to humans
Books mentioned: Godel, Escher, Bach: An Eternal Golden Braid (Hofstadter), The Mind’s I (Dennett, Hofstadter), Broad Band: The Untold Story of the Women Who Made the Internet (Evans)

You can follow Melanie on X and Substack.

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