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Machine Learning Algorithms & Natural Language Processing
Machine Learning Algorithms & Natural Language Processing
Apr 25, 2026 · Artificial Intelligence

Why DeepSeek‑V4 Took Twice as Long: Inside the Training‑Stability Challenges and Engineering Hacks

The DeepSeek‑V4 technical report reveals that the model’s doubled training time stems from massive token and parameter scaling, severe training‑stability issues in MoE layers, and a suite of engineering solutions—including Anticipatory Routing, SwiGLU Clamping, specialist expert training, and a custom sandbox cluster—while also exposing high hallucination rates despite impressive benchmark performance.

DeepSeek V4Generative Reward ModelLLM
0 likes · 12 min read
Why DeepSeek‑V4 Took Twice as Long: Inside the Training‑Stability Challenges and Engineering Hacks
Baobao Algorithm Notes
Baobao Algorithm Notes
Apr 14, 2026 · Industry Insights

Why Mastering AI Agents Is the Most Critical Skill Right Now

The article argues that leveraging AI agents like Claude Code is now the top priority for developers, explaining how agents boost productivity, the importance of their operating environment, and why embracing them is essential for future success in the AI-driven workplace.

Claude CodeLLMagent training
0 likes · 10 min read
Why Mastering AI Agents Is the Most Critical Skill Right Now
Meituan Technology Team
Meituan Technology Team
Jan 29, 2026 · Artificial Intelligence

How LongCat‑Flash‑Thinking‑2601 Achieves Real‑World Generalization for Agents

LongCat‑Flash‑Thinking‑2601, a 560‑billion‑parameter MoE model, combines environment expansion, multi‑environment RL, systematic noise training, a heavy‑thinking reasoning mode, and Zigzag sparse attention to deliver strong benchmark performance and robust real‑world agent capabilities.

Environment ExpansionLarge Language ModelNoise Robustness
0 likes · 14 min read
How LongCat‑Flash‑Thinking‑2601 Achieves Real‑World Generalization for Agents