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How "Thinking Out Loud" Makes AI Smarter
In this episode, we break down a fascinating new approach that helps AI models think more like humans. Researchers Zhiyuan Li, Hong Liu, Denny Zhou, and Tengyu Ma have discovered that by guiding AI to think step-by-step — a process they call "Chain-of-Thought" (CoT) — it can tackle much tougher tasks like solving puzzles, doing math, and making complex decisions. We’ll explain how this method works and why it could be a game-changer for AI. If you’re curious about how AI can learn to think better, this episode is for you!
Original Paper:
"Chain of Thought Empowers Transformers to Solve Inherently Serial Problems" by Zhiyuan Li, Hong Liu, Denny Zhou, and Tengyu Ma.
Link: https://arxiv.org/abs/2402.12875v3
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By Anlie Arnaudy, Daniel Herbera and Guillaume FournierIn this episode, we break down a fascinating new approach that helps AI models think more like humans. Researchers Zhiyuan Li, Hong Liu, Denny Zhou, and Tengyu Ma have discovered that by guiding AI to think step-by-step — a process they call "Chain-of-Thought" (CoT) — it can tackle much tougher tasks like solving puzzles, doing math, and making complex decisions. We’ll explain how this method works and why it could be a game-changer for AI. If you’re curious about how AI can learn to think better, this episode is for you!
Original Paper:
"Chain of Thought Empowers Transformers to Solve Inherently Serial Problems" by Zhiyuan Li, Hong Liu, Denny Zhou, and Tengyu Ma.
Link: https://arxiv.org/abs/2402.12875v3