BEIJING (Reuters) -Chinese AI developer DeepSeek said it spent $294,000 on training its R1 model, much lower than figures reported for U.S. rivals, in a paper that is likely to reignite debate over Beijing's place in the race to develop artificial intelligence.
DeepSeek 只花费29.4万美元训练了R1 model，真的假的？OPEN AI 咋办？
版主： 牛河梁
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LiSheQiang
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#7 Re: DeepSeek 只花费29.4万美元训练了R1 model，真的假的？OPEN AI 咋办？
DEEPSEEK R1 昨天刚发的nature
楼上老逼觉得他们比nature的审稿人更懂AI
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#8 Re: DeepSeek 只花费29.4万美元训练了R1 model，真的假的？OPEN AI 咋办？
https://www.nature.com/articles/s41586-025-09422-z
DeepSeek-R1 incentivizes reasoning in LLMs through reinforcement learning
Abstract
General reasoning represents a long-standing and formidable challenge in artificial intelligence (AI). Recent breakthroughs, exemplified by large language models (LLMs)1,2 and chain-of-thought (CoT) prompting3, have achieved considerable success on foundational reasoning tasks. However, this success is heavily contingent on extensive human-annotated demonstrations and the capabilities of models are still insufficient for more complex problems. Here we show that the reasoning abilities of LLMs can be incentivized through pure reinforcement learning (RL), obviating the need for human-labelled reasoning trajectories. The proposed RL framework facilitates the emergent development of advanced reasoning patterns, such as self-reflection, verification and dynamic strategy adaptation. Consequently, the trained model achieves superior performance on verifiable tasks such as mathematics, coding competitions and STEM fields, surpassing its counterparts trained through conventional supervised learning on human demonstrations. Moreover, the emergent reasoning patterns exhibited by these large-scale models can be systematically used to guide and enhance the reasoning capabilities of smaller models.
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Mountainlion
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#13 Re: DeepSeek 只花费29.4万美元训练了R1 model，真的假的？OPEN AI 咋办？
这种文章主要从cience角度看。
至于花了多少，除了ds，没人知道，没人在意
共产党是赤裸裸的黑手党，没有法律，没有道德，没有人性. 它做的都是见不得阳光的事
