Makalah DeepSeek-R1 muncul di sampul Nature, mendorong proses transparansi AI

【DeepSeek-R1 Paper Featured on Nature Cover, Promoting AI Transparency】Paper DeepSeek-R1 has been featured as a cover article in Nature, with Liang Wenfeng, founder and CEO of DeepSeek, as the corresponding author. The research team demonstrated through experiments that the reasoning ability of large language models can be improved through pure reinforcement learning, reducing human input workload, and performing better than models trained by traditional methods in tasks such as mathematics and programming. DeepSeek-R1 has reached 91.1k stars on GitHub, receiving praise from developers worldwide. An assistant professor at Carnegie Mellon University and others have commented on its evolution from a powerful but opaque solution seeker to a system capable of human-like dialogue. Nature has recognized it in an Editorial article as the first mainstream LLM published after peer review, marking a significant step towards transparency. Peer review helps clarify how LLMs work, assess their effectiveness, and enhance model safety.