Image created with gemini-2.5-flash-image with claude-sonnet-4-5-20250929. Image prompt: A cinematic photograph of a scholar in a grand stone library with Gothic arched windows, examining illuminated manuscripts that dissolve into floating neural network diagrams and mathematical equations, warm candlelight mixing with cool blue algorithmic light, Renaissance painting aesthetic meets modern AI visualization, deep shadows suggesting both historical gravitas and technical depth.
🚨 Major milestone for open-source AI: DeepSeek-R1, with Wenfeng Liang as corresponding author, has landed on the cover of Nature! 🔥 It’s the first fully peer-reviewed LLM published in a top academic journal, sparking huge debate in China’s tech community Zhihu. Zhihu mind https://x.com/ZhihuFrontier/status/1968573286696239247
Finetune DeepSeek 🐳 with two Mac Studios + MLX 🚀 We use pipeline parallelism to split the full 671GB model across two devices connected by a single TB5 cable. LoRA reduces the number of parameters to train from 671 billion down to 37 million, reducing the memory overhead from https://x.com/MattBeton/status/1968739407260742069
Congrats to @deepseek_ai ! DeepSeek-R1 was published in Nature yesterday as the cover article, and vLLM is proud to have supported its RL training and inference🥰 https://x.com/vllm_project/status/1968506474709270844
DeepSeek-R1 incentivizes reasoning in LLMs through reinforcement learning | Nature https://www.nature.com/articles/s41586-025-09422-z
Nature Portfolio also addressed this on Zhihu: Publishing this paper is itself a significant milestone👏 🤔 DeepSeek-R1 learns step-by-step reasoning with minimal human help: • Reinforcement learning: correct answers get rewards, mistakes penalized • Learns to self-verify & https://x.com/ZhihuFrontier/status/1968603082167828494
