DeepNewz, mobile.
People-sourced. AI-powered. Unbiased News.
DeepSeek's R1-Zero model represents a notable advancement in reinforcement learning (RL) for natural language processing. Unlike traditional large language models (LLMs) that often incorporate human feedback in their training processes, R1-Zero operates solely on reinforcement learning principles, without the use of human-labeled data. This approach is reminiscent of Tesla's method with its Full Self-Driving (FSD) technology, although Tesla primarily utilizes imitation learning. Early results indicate that R1-Zero demonstrates human-like reasoning skills and has achieved comparable performance to the R1 model in the ARC (AI Research Challenge) scores, despite its lack of supervised fine-tuning. The evolution of DeepSeek's models illustrates a shift towards more autonomous learning systems in AI development.
DeepSeek-R1-Zero almost matches R1 in ARC scores but solely relies on RL, no human labelled data was used! https://t.co/lGCuakQdg7
DeepSeek-R1-Zero (no supervised fine-tuning) showing human-like reasoning skills in natural language just by virtue of reinforcement learning (RL). https://t.co/P0wCC3wVtN
On DeepSeek's R1 model: "LLMs to date...have relied on reinforcement learning with human feedback [RL-HF]; humans are in the loop to help guide the model, navigate difficult choices where rewards aren’t obvious, etc...R1-Zero..drops the HF part—it’s just reinforcement learning" https://t.co/1DC0oJWptT
