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DeepSeek R1, a new large language model from China, is described, highlighting three key techniques: Chain of Thought prompting to improve reasoning and self-evaluation; reinforcement learning, specifically Group Relative Policy Optimization, enabling the model to learn independently and optimize its performance without needing labeled data; and model distillation, creating smaller, more accessible versions of the model while maintaining high accuracy. These techniques allow DeepSeek R1 to achieve performance comparable to, and eventually surpassing, OpenAI's models in tasks like math, coding, and scientific reasoning. The model's innovative training methods are explained, emphasizing its efficiency and potential to democratize access to advanced AI.
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DeepSeek R1, a new large language model from China, is described, highlighting three key techniques: Chain of Thought prompting to improve reasoning and self-evaluation; reinforcement learning, specifically Group Relative Policy Optimization, enabling the model to learn independently and optimize its performance without needing labeled data; and model distillation, creating smaller, more accessible versions of the model while maintaining high accuracy. These techniques allow DeepSeek R1 to achieve performance comparable to, and eventually surpassing, OpenAI's models in tasks like math, coding, and scientific reasoning. The model's innovative training methods are explained, emphasizing its efficiency and potential to democratize access to advanced AI.
Send us a text
Support the show
Podcast:
https://kabir.buzzsprout.com
YouTube:
https://www.youtube.com/@kabirtechdives
Please subscribe and share.
5,420 Listeners