一水 发自 凹非寺 量子位 | 公众号 QbitAI 我并不认为Scaling Law已经完全结束了 。 正当学生Ilya为Scaling Law"泼下冷水"时，他的老师、AI教父Geoffrey Hinton却毅然发表了上述截然相反的观点。 这一场面一出，我们不禁回想起了两件有趣的事。 一是Ilya几乎从学生时代起就坚信Scaling Law，不仅一抓住机会就向身边人安利，而且还把这套理念带进了OpenAI。 可以说，Ilya算是Scaling Law最初的拥趸者。 二是Hinton后来在回顾和Ilya的相处时，曾大肆夸赞Ilya"具有惊人的直觉"，包括在Scaling Law这件事上，Hinton曾坦言： 当时的我错了，而Ilya基本上是对的。 比如Transformer确实是一种创新想法，但实际上起作用的还是规模，数据的规模和计算的规模。 但是现在，这对师徒的态度却来了个惊天大反转。 所以，这中间到底发生了什么？ Scaling Law不死派：Hinton、哈萨比斯 其中，最大的挑战无疑是数据缺失问题。 大部分高价值数据都锁在公司内部，免费互联网数据已基本耗尽。 而这个问题将由AI自行解决，即模型通过推 ...

Core Viewpoint - The article discusses the key figures supporting OpenAI's research, particularly Mark Chen and Jakub Pachocki, who are pivotal in the company's core research efforts as it approaches the release of GPT-5 [1][5]. Group 1: Key Figures - Mark Chen, the Chief Research Officer, has played a significant role in developing DALL-E and contributing to GPT-3 and GPT-4, including adding image recognition capabilities to GPT-4 [12][19]. - Jakub Pachocki, the new Chief Scientist, succeeded Ilya and has been recognized as one of the most outstanding minds of his generation, overseeing projects like GPT-4 [4][22]. - Both Chen and Pachocki are in their 30s, have competitive programming backgrounds, and have been integral to OpenAI's major projects, including the GPT series [9][29]. Group 2: Research Dynamics - Chen is responsible for building and managing the research team, while Pachocki sets the research roadmap and long-term technical vision, indicating a collaborative and flexible working relationship [5][30]. - Their shared experience in competitive programming influences OpenAI's strategy to engage in international coding competitions, which they believe is crucial for advancing their models [30][34]. - OpenAI recently achieved notable success in global programming competitions, highlighting their commitment to pushing the boundaries of AI capabilities [32]. Group 3: Strategic Focus - OpenAI is transitioning from a pure research lab to a company that balances research with product development, focusing on practical applications of AGI [39][42]. - The dissolution of the Super Alignment team after Ilya's departure reflects a shift in focus towards aligning existing models with expected outcomes rather than hypothetical superintelligence [41]. - Chen and Pachocki emphasize the importance of addressing current model limitations and enhancing their practical utility, contrasting with Ilya's vision of AGI as a transformative milestone [39][41].