Скачать или смотреть 🧐👉 DeepSeek's mHC: Training Massive AI Models Without Extra Cost

🚀 DeepSeek has unleashed its Manifold-Constrained Hyper-Connections (mHC) architecture, shaking up the AI scene by making massive model training way cheaper and more efficient.

The mHC method was tested on models with 3B, 9B, and 27B parameters, showing stable performance with zero extra computational cost. This breakthrough builds on ByteDance’s hyper-connection foundation, adding a manifold constraint to cut memory overhead and keep things scalable.

With CEO Liang Wenfeng leading the charge, DeepSeek’s latest paper signals a new wave of AI innovation from China, especially as the industry faces Nvidia chip restrictions. Analysts expect mHC to be the backbone of DeepSeek’s upcoming models, likely launching before Spring Festival 2026.

This move not only boosts DeepSeek’s competitive edge but also highlights the growing open, collaborative culture among Chinese AI companies.

💡 Stay tuned—AI training just got a whole lot smarter and cheaper!

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