DeepSeek kicks off 26 with paper signalling push to train bigger models for less
4 months ago
- #AI
- #Deep Learning
- #Research
- DeepSeek starts 2026 with a new technical paper proposing a rethink of its deep learning architecture.
- The paper introduces Manifold-Constrained Hyper-Connections (mHC) to make AI model training more cost-effective.
- DeepSeek aims to compete with better-funded US rivals by improving efficiency.
- Chinese AI firms are increasingly open, sharing more research publicly.
- DeepSeek's papers often signal upcoming engineering choices for future model releases.
- mHC was tested on models with 3B, 9B, and 27B parameters, showing scalability without major computational overhead.