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EP 35 | CME295: LLM Reasoning episode artwork

Apr 10, 2026 20 min

EP 35 | CME295: LLM Reasoning

from AI Bites: The Academic Series Hosted by Jack Lakkapragada

Can a language model actually think, or is it just a sophisticated autocomplete? In this episode, we dive into the fascinating—and highly debated—topic of LLM reasoning. We explore how to unlock complex problem-solving capabilities without changing the underlying model. Key Topics: In-Context Learning: How models can learn to do new tasks on the fly just from the examples provided in your prompt. Chain-of-Thought (CoT): Why forcing a model to "show its work" step-by-step drastically improves its ability to solve math and logic puzzles. The Illusion of Understanding: The boundaries of current AI reasoning, tackling why models hallucinate facts and where their logic ultimately breaks down. Note: This is an AI-generated study resource created via NotebookLM based on the Stanford CME295 curriculum and personal study notes.

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EP 35 | CME295: LLM Reasoning

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