How DeepSeek-R1 Was Built; For dummies
DeepSeek just made a breakthrough: you can train a model to match OpenAI o1-level reasoning using pure reinforcement learning (RL) without using labeled data (DeepSeek-R1-Zero). But RL alone isn’t perfect — it can lead to challenges like poor readability. A mix of methods in a multi-stage training fixes these (DeepSeek-R1).
The launch of GPT-4 forever changed the AI industry. But today, it feels like an iPhone 4 compared to the next wave of reasoning models (e.g. OpenAI o1).
These "reasoning models" introduce a chain-of-thought (CoT) thinking phase before generating an answer at inference time, which in turn improves their reasoning performance.
While OpenAI kept their methods under wraps, DeepSeek is taking the opposite approach — sharing their progress openly and earning praise for staying true to the open-source mission. Or as Marc said it best:
Deepseek R1 is one of the most amazing and impressive breakthroughs I’ve ever seen — and as open source, a profound gift to the world. 🤖🫡
