Mistral released Mistral OCR 3, which outperforms existing enterprise document processing solutions as well as AI-native OCR systems.
LLMS
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Impressive non-thinking mode performance in AI models
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There's a thinking mode for it, but the difference isn't huge, the fact that the non thinking mode works so well is very impressive
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Potential upgrade for Gemma open-source model
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Something open source is planned. Let's see if we will get a Gemma upgrade.
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Latest LLM Advances: Opus 4.5, GPT-5.2-xHigh, Gemini 3 Flash
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Positive about where LLMs are going based on the last few weeks: – Amazing non-thinking model (Opus 4.5) – Impressive super long thinking model (GPT-5.2-xHigh) – Genuinely good smaller model (Gemini 3 Flash) Progress on all fronts!
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Technical Preview of Claude Task Mode Agent Workflow
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BREAKING 🚨: Early look at Claude Task Mode agent workflow. What do we know so far?
— 🚨 AI News | TestingCatalog (@testingcatalog) 18 décembre 2025
– Claude Tasks will operate various Skills and MCPs to achieve the goal.
– Claude will ask clarifying questions before the execution or skip it after a timeout.
– Claude will generate an action… pic.twitter.com/JvKN9G8H2TBREAKING : Early look at Claude Task Mode agent workflow. What do we know so far? – Claude Tasks will operate various Skills and MCPs to achieve the goal.
– Claude will ask clarifying questions before the execution or skip it after a timeout. – Claude will generate an action -
Scaling Laws and Symmetry in Neural Networks Research
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Scaling Laws and Symmetry The common belief is that scaling outperforms inductive biases. Give the model enough data and compute, and it will learn the structure on its own. But this new research finds the opposite. Researchers conducted comprehensive scaling experiments on
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Optimizing ChatGPT Custom Instructions for Maximum Usefulness
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I want my ChatGPT to be very useful for me, so over time, this is how I optimized the custom instructions: Be extremely accurate. Be brutally honest and call out misconceptions. No sycophancy. Tell me when I'm wrong. Think from first principles. Be encouraging. Take a
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Prompt Engineering Over Model Scale in AI Performance
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I've seen this turn mediocre responses into genuinely excellent analysis. The first pass might score 60% accuracy. After two rounds of adversarial revision? 85%+. The entire AI industry is about to realize that better prompting beats bigger models. This is just the beginning.
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Understanding Probabilistic Response Generation in LLMs
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The real breakthrough isn't the technique itself it's understanding why it works.
— God of Prompt (@godofprompt) 18 décembre 2025
LLMs generate responses probabilistically. The first answer is just the highest-probability path through their training data. But "most probable" doesn't mean "most correct."
When you introduce… pic.twitter.com/6aANnq7UHNThe real breakthrough isn't the technique itself it's understanding why it works. LLMs generate responses probabilistically. The first answer is just the highest-probability path through their training data. But "most probable" doesn't mean "most correct." When you introduce
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Improving AI Model Reasoning Through Adversarial Prompting Techniques
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But here's where it gets insane. The technique doesn't just improve accuracy on the current problem. It actually teaches the model better reasoning patterns for future questions.
When you force devil's advocate mode repeatedly, the model starts internalizing that adversarial