This is how Reinforcement Learning works, visualized https://t.co/RZAcQZ2vbc
— God of Prompt (@godofprompt) 22 novembre 2025
This is how Reinforcement Learning works, visualized
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This is how Reinforcement Learning works, visualized https://t.co/RZAcQZ2vbc
— God of Prompt (@godofprompt) 22 novembre 2025
This is how Reinforcement Learning works, visualized

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Windsurf got a new mode where Claude Sonnet 4.5 would do all the planning and faster SWE-1.5 model will be applying changes to the code. AI pair programming
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Really recommend their paper, it's a great intro to tabular foundation models:

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Anyone heard of TabPFN-v2?
Soon the end for XGBoost and Random Forest
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7. Ambiguity Resolution Under Pressure
— God of Prompt (@godofprompt) 22 novembre 2025
Prompt:
Interpret the vague instruction “Prepare the model for tomorrow’s run” in 10 completely different ways across these domains: machine learning, finance, biotech, aerospace, logistics, cybersecurity, robotics, meteorology, energy… pic.twitter.com/6WWQeMShK4
7. Ambiguity Resolution Under Pressure Prompt: Interpret the vague instruction “Prepare the model for tomorrow’s run” in 10 completely different ways across these domains: machine learning, finance, biotech, aerospace, logistics, cybersecurity, robotics, meteorology, energy
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4. Mathematical Generalization Stress Test
— God of Prompt (@godofprompt) 22 novembre 2025
Prompt:
Generalize the formula for expected error in a Monte Carlo model when sampling distribution skewness increases non-linearly. Create three versions: a practical heuristic for engineers, a fully rigorous derivation for… pic.twitter.com/RbcqMdnoam
4. Mathematical Generalization Stress Test Prompt: Generalize the formula for expected error in a Monte Carlo model when sampling distribution skewness increases non-linearly. Create three versions: a practical heuristic for engineers, a fully rigorous derivation for
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what are you building with @huggingface this weekend? leave them below

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gemini 3 pro beat all models on SWE-bench verified we were waiting for this, but we already *knew* it.
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You deserve to be proud Tony. Your intuition about robot learning, your design and implementation of ALOHA and Memo, and the initial results from @Sundayrobotics are significantly pushing this field forward.
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I hate to break it to you, @sama
, but there’s not enough compute in the universe to brute-force AI.