Franchement oui… mais pas que. Réfléchir avant d’agir c’est la base.
Mais avec un LLM, t’es plus juste en train d’exécuter ou réfléchir solo. En vrai tu réfléchis avec lui, Et c’est là que ça change tout. Si t’as une idée floue il sort un truc moyen
Si t’es clair il t’emmène
LLMS
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How an LLM changes the way you think with it
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Gemini Document Creation Falls Short of Frontier Standards
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Gemini now can create documents, and it is a nice start, but not up to the frontier yet, as you can see from my "LBO of Hogwarts" test. PowerPoints are substantially worse than NotebookLM, spreadsheets are primitive, still no thinking trace, it doesn't think hard enough, either.
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Tau3-Bench Timing Concerns Against Competing Models
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Not sure if this is a good look since most of the competing models were released BEFORE Tau3-Bench
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AI-Native Founders Rise: Insights from Replit Leaders
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— Replit ⠕ (@Replit) 29 avril 2026
At @Replit they’re empowering a new wave of million-dollar founders. Cofounders @amasad and @HayaOdeh joined us at @southpkcommons to discuss: – The rise of AI-native founders – New AI models and their capabilities – And why most founders quit too early Full Minus One
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ChatGPT Integrates Model Switcher Into Prompt Field
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ChatGPT's model switcher is now built directly into the Prompt field
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NVIDIA Leads AI Benchmarks with Open Models Across Domains
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📈 NVIDIA tops AI leaderboards and benchmarks with open models driven by extreme co-design across compute, networking, memory, storage, and software.
— NVIDIA (@nvidia) 29 avril 2026
This includes models for biology, AI physics, agentic AI, physical AI, robotics, and autonomous vehicles.
By being vertically… pic.twitter.com/ybjuWm637CNVIDIA tops AI leaderboards and benchmarks with open models driven by extreme co-design across compute, networking, memory, storage, and software. This includes models for biology, AI physics, agentic AI, physical AI, robotics, and autonomous vehicles. By being vertically
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LangChain Now Hiring Positions Available
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We can confirm #11 is hiring. https://
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Introspection Adapters Enable Language Models Self-Report Misalignment
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In new Anthropic Fellows research, we discuss “introspection adapters": a tool that allows language models to self-report behaviors they've learned during training—including potential misalignment.
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DeepSeek v4 Demonstrates SOTA Long Context Efficiency Without Benchmarking
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IMO DeepSeek v4 demonstrated utter confidence and competence by not benchmaxxing, not focusing on some BS final run cost, not even spending inference-optimal compute. just showed up, demonstrated SOTA long context efficiency techniques (CSA, HCA, mHC, flash at 8% cost of pro,
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Two models with 1M context, near equal, model just 20% of result
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And this is the part nobody is talking about:
Both models ship with 1M-token context. Both are within a few points of each other on most tasks. The gap between them is smaller than the gap between a good prompt and a bad one. The model is maybe 20% of your result. Your