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Subbarao Kambhampati - Do o1 models search?

Machine Learning Street Talk (MLST)

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Advancements in Large Language Models and Reasoning

This chapter explores the evolution of large language models (LLMs), focusing on their reasoning capabilities and the limitations of autoregressive models. It discusses innovative approaches like prompt augmentation and inference time scaling, while also addressing the challenges and costs associated with these methodologies. The conversation highlights recent advancements from major tech companies and draws parallels to teaching strategies, emphasizing the importance of improving problem-solving within AI.

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