How DeepMind’s AI Uncovered New Unstable Singularities in Fluid Dynamics

DeepMind, together with researchers from NYU, Stanford and Brown, used physics‑informed neural networks, a Gauss‑Newton optimizer and multi‑stage training to systematically discover previously unknown unstable singularities in three fluid‑dynamics equations, revealing a concise asymptotic formula linking blow‑up rates to instability order.

DeepMindGauss-Newton optimizerPhysics‑Informed Neural Networks

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How DeepMind’s AI Uncovered New Unstable Singularities in Fluid Dynamics

Baobao Algorithm Notes

Jul 16, 2025 · Artificial Intelligence

What Small Labs Reveal About RL Training: Multi‑Stage, Entropy, and Resource Strategies

The article analyzes Skywork OR1's technical report, detailing how small‑scale teams use GRPO‑based reinforcement learning with multi‑stage training, advantage‑mask variants, high‑temperature sampling, adaptive entropy loss, and resource‑allocation tricks to improve large language model performance while avoiding premature entropy collapse.

AI researchentropy controlmulti-stage training

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What Small Labs Reveal About RL Training: Multi‑Stage, Entropy, and Resource Strategies

Architect

Feb 8, 2025 · Artificial Intelligence

DeepSeek‑R1: From Zero to Full‑Featured AI Model via Cold‑Start Data and Multi‑Stage Training

The article explains how DeepSeek‑R1 improves upon the Zero version by introducing expert‑crafted cold‑start data and a four‑phase multi‑stage training pipeline, resulting in markedly better reasoning, coding, and general knowledge performance across benchmark tests.

AI inferenceDeepSeekReinforcement Learning

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DeepSeek‑R1: From Zero to Full‑Featured AI Model via Cold‑Start Data and Multi‑Stage Training

Meituan Technology Team

Jul 6, 2022 · Artificial Intelligence

Improving Search Relevance in PointCheck

The article details Meituan‑Dianping's search relevance pipeline, describing how multi‑similarity matrix structures, multi‑stage domain‑adaptive training, POI field summarization, and online inference optimizations together improve a BERT‑based relevance model's offline metrics and reduce the BadCase rate in production.

BERTMeituanmulti-similarity matrix

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