DeepSeek kicked off 2026 with a new AI training method for scaling
4 months ago
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- China's DeepSeek introduces a new AI training method called 'Manifold-Constrained Hyper-Connections' (mHC) to scale models more efficiently.
- The method allows models to share richer internal communication while maintaining stability and computational efficiency.
- Analysts describe the approach as a 'striking breakthrough' that could significantly impact the AI industry.
- DeepSeek's research signals its capability for rapid experimentation and unconventional research ideas.
- The company is reportedly working on its next flagship model, R2, following a delay due to performance issues and chip shortages.
- DeepSeek's previous model, R1, matched top competitors like ChatGPT's o1 at a lower cost but struggled with broad industry traction.
- The openness of DeepSeek's research reflects a newfound confidence in the Chinese AI industry.