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@hamdambekovna: 😶
𝐇𝐚𝐦𝐝𝐚𝐦𝐛𝐞𝐤𝐨𝐯𝐧𝐚🩷
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Wednesday 24 June 2026 15:53:44 GMT
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ХОЖИАКБАР КАРИМОВ :
🌹🌹🌹🌹🌹🌹
2026-06-24 17:10:58
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Why do Large Language Models get stuck in endless, non-sensical loops? 🌀 Standard neural networks update their hidden states using arbitrary matrix multiplications. Geometrically, this creates an unconstrained vector field. The AI's "train of thought" has absolutely no mathematical gravity—meaning it can easily wander into chaos or loop forever. But what if we changed the physics of the latent space? By forcing the network to output a single scalar value (an "Energy Landscape"), the AI's thought process simply rolls downhill along the negative gradient. Infinite loops become mathematically impossible. 🧠 **The Quick-Win Mental Model:** To instantly grasp this, think of **Wind vs. Gravity**. • *Standard NN:* A paper airplane blown by shifting winds (arbitrary vectors). It can loop endlessly. • *Energy NN:* A ball rolling down a sculpted valley (conservative vector field). It *must* eventually settle at the lowest point. Standard models learn the *path*; Energy models learn the *terrain*. 🔗 **Want the rigorous proof?** If you want to see the actual PyTorch implementation, the Lyapunov stability proof, and how this unlocks Neuro-Symbolic logic, hit the link in our bio to read the full Substack Deep-Dive! 👇 **Question for you:** Have you ever caught an AI like ChatGPT or Claude in a bizarre logical loop? What was the prompt? Let's discuss in the comments! #MachineLearning #DeepLearning #NeuralNetworks #Physics #Mathematics
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