[Podcast] DeepSeek R1: AI Reasoning (Revised 4 Jan 2026 - v2)
Автор: Vinh Nguyen
Загружено: 2026-01-07
Просмотров: 25
Описание:
https://arxiv.org/pdf/2501.12948v2
Disclaimer: This video is generated with Google's NotebookLM.
The provided document details the development and evaluation of DeepSeek-R1, a model designed to master complex logical reasoning through advanced reinforcement learning. The researchers introduced DeepSeek-R1-Zero, which autonomously developed problem-solving strategies like self-reflection and "aha moments" without any initial human-guided training. To improve user experience and readability, the team then created the main DeepSeek-R1 pipeline by combining a small amount of cold-start data with multi-stage training. This approach allowed the model to excel in mathematics, coding, and STEM tasks, rivaling top-tier closed-source models. Additionally, the authors successfully distilled these reasoning capabilities into smaller, more efficient models to promote broader accessibility. The report also emphasizes a robust safety framework and a language consistency reward to ensure the model remains helpful and reliable across various languages.
#ai #deepseek #research #largelanguagemodels #stateoftheart
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