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09-18

加了又怎样，OpenAI训练数据就干净吗

DeepSeek首次回应“蒸馏OpenAI”质疑

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class=\"h-time\">2025-09-18 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padding: 0 0 0 9px; float: left;}\n.head .h-name {font-size: 13px; color: #eee; margin: 0;}\n.head .h-time {font-size: 11px; color: #7E829C; margin: 0;line-height: 11px;}\n.small {font-size: 12.5px; display: inline-block; transform: scale(0.9); -webkit-transform: scale(0.9); transform-origin: left; -webkit-transform-origin: left;}\n.smaller {font-size: 12.5px; display: inline-block; transform: scale(0.8); -webkit-transform: scale(0.8); transform-origin: left; -webkit-transform-origin: left;}\n.bt-text {font-size: 12px;margin: 1.5em 0 0 0}\n.bt-text p {margin: 0}\n</style>\n</head>\n<body>\n<div class=\"wrapper\">\n<header>\n<h2 class=\"title\">\nDeepSeek首次回应“蒸馏OpenAI”质疑\n</h2>\n\n<h4 class=\"meta\">\n\n\n<a class=\"head\" href=\"https://laohu8.com/wemedia/102\">\n\n\n<div class=\"h-thumb\" style=\"background-image:url(https://static.tigerbbs.com/8274c5b9d4c2852bfb1c4d6ce16c68ba);background-size:cover;\"></div>\n\n<div class=\"h-content\">\n<p class=\"h-name\">老虎资讯综合 </p>\n<p class=\"h-time\">2025-09-18 12:47</p>\n</div>\n\n</a>\n\n\n</h4>\n\n</header>\n<article>\n<html><head></head><body><p>9月18日，DeepSeek再次引发轰动。由DeepSeek团队共同完成、梁文锋担任通讯作者的DeepSeek-R1研究论文，登上了国际权威期刊《Nature》的封面。今年1月，DeepSeek曾在arxiv公布了初版预印本论文，相较而言，此次发布在《Nature》的版本补充了更多模型细节，减少了描述中的拟人化说明。在补充材料中，DeepSeek提到了R1模型的训练成本仅29.4万美元，以及回应了模型发布之初关于蒸馏OpenAI的质疑。</p><p>今年1月，有报道提到，OpenAI研究人员认为，DeepSeek可能使用了OpenAI模型的输出来训练R1，这种方法可以在使用较少资源的情况下加速模型能力提升。在论文的补充资料部分，<strong>DeepSeek回应了关于DeepSeek-V3-Base训练数据来源的问题。“DeepSeek-V3-Base的训练数据仅来自普通网页和电子书，不包含任何合成数据。在预训练冷却阶段，我们没有故意加入OpenAI生成的合成数据，此阶段使用的所有数据都是通过网页抓取的。”DeepSeek表示。</strong>（一财）</p></body></html>\n\n</article>\n</div>\n</body>\n</html>\n","type":0,"thumbnail":"https://static.tigerbbs.com/d631d84cdad1cc99ed6c3f3ffc1934ce","relate_stocks":{},"source_url":"","is_english":false,"share_image_url":"https://static.laohu8.com/e9f99090a1c2ed51c021029395664489","article_id":"1190615103","content_text":"9月18日，DeepSeek再次引发轰动。由DeepSeek团队共同完成、梁文锋担任通讯作者的DeepSeek-R1研究论文，登上了国际权威期刊《Nature》的封面。今年1月，DeepSeek曾在arxiv公布了初版预印本论文，相较而言，此次发布在《Nature》的版本补充了更多模型细节，减少了描述中的拟人化说明。在补充材料中，DeepSeek提到了R1模型的训练成本仅29.4万美元，以及回应了模型发布之初关于蒸馏OpenAI的质疑。今年1月，有报道提到，OpenAI研究人员认为，DeepSeek可能使用了OpenAI模型的输出来训练R1，这种方法可以在使用较少资源的情况下加速模型能力提升。在论文的补充资料部分，DeepSeek回应了关于DeepSeek-V3-Base训练数据来源的问题。“DeepSeek-V3-Base的训练数据仅来自普通网页和电子书，不包含任何合成数据。在预训练冷却阶段，我们没有故意加入OpenAI生成的合成数据，此阶段使用的所有数据都是通过网页抓取的。”DeepSeek表示。（一财）","news_type":1,"symbols_score_info":{}},"isVote":1,"tweetType":1,"viewCount":16,"authorTweetTopStatus":1,"verified":2,"comments":[],"imageCount":0,"langContent":"CN","totalScore":0}],"lives":[]}