Episode 40: DeepSeek facts vs hype, model distillation, and open source competition
Mixture of Experts
Advancements in Model Distillation and Reasoning
This chapter explores the importance of long chain reasoning in machine learning, particularly for mathematical problems, and introduces model distillation as a means of optimizing resource usage by transferring knowledge from larger models to smaller ones. It discusses the implications of open-source models in fostering innovation, while also addressing concerns over the competitive landscape of AI providers. The chapter concludes with insights on the evolving role of large models as educational tools, suggesting a future where efficient AI solutions will become more accessible.
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