Energy-Based Models Explained: The Idea Yann LeCun Thinks Comes After LLMs

Most AI models are built to predict an answer directly, down to every pixel. Energy-based models do something different: they score how well a question and an answer fit together, with one number called energy. Low energy means they fit, high energy means they clash. Inside: why predicting every pixel of the future is hopeless, how a ball rolling downhill finds the best answer, the Boltzmann formula and its impossible sum, the collapse problem and its two fixes (contrastive and regularized), and John Hopfield's 1982 memories as energy valleys (Nobel Prize in Physics, 2024). This is the idea Yann LeCun argues will take AI beyond today's language models. Next: JEPA. Made by Vizuara. #Shorts #AI #MachineLearning #DeepLearning #EnergyBasedModels #YannLeCun