This #AI mines the numbers buried in scientific papers and turns them into usable data fast
by Jülich Research Centre @TechXplore_com Learn more: https://
bit.ly/3QA7Ymm #ArtificialIntelligence #MachineLearning #ML
MACHINE LEARNING
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AI mines numbers from scientific papers into usable data
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NES: AI Framework Predicts Your Next Code Edit
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What if your IDE could predict your next code edit before you even type it? Researchers at Ant Group present NES, a new AI framework that learns from past editing patterns. It uses two models: one to guess where you'll edit next, and another to suggest what to change—all
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Organizational Design for AI Agents: The Next Critical Frontier
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Organizational design for agents is hard, benchmarking agents working in concert is hard. Together, this is the next critical frontier for making AI matter in economically valuable tasks, and we really don’t know very much about it.
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AI Knows More, Humans Learn Faster: Key Differences
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Any AI knows more than any individual human But any individual human learns faster than any AI
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Another Problem Solved by Artificial Intelligence
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Sir another one of your problems has fallen to AI.
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Long-Context Reasoning Limits Discovered in Automated Bug Fixing
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Congrats to the team on “The Limits of Long-Context Reasoning in Automated Bug Fixing” being accepted to ICLR 2026 The team put long-context reasoning to the test for automated bug fixing and found something surprising. Performance actually drops as context grows. Check out
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DeepSeek V4 Launch with SGLang Optimizations and RL Pipeline
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DeepSeek V4 by @deepseek_ai just dropped! SGLang is ready on Day 0 with a full stack of optimizations from architectures to low-level kernels. We also deliver a verified RL training pipeline in Miles (by @radixark) for V4 at launch: Native "ShadowRadix" Design: DeepSeek V4's
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Hugging Face Models Directory Should Support Quantization Filtering
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Ideal fix would be for the HF models directory to grow a direct understanding of the structure of those kinds of repos and treat them as individual models that can be listed separately, including filter by quantization type
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Open Source Code Execution Chat ML Innovation
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Will play around! Open source execution over chat is what ML work has been waiting on.
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Token Importance in On-Policy Distillation with Selective Training
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"TIP: Token Importance in On-Policy Distillation" This paper introduces selective token training for on-policy distillation, relying on student entropy to find high-signal tokens. A key point is that entropy misses confident mistakes, so they add teacher-student divergence to