I’ve always been fascinated by Yann LeCun’s vision of world models and autonomous agents, so I decided to build a minimal, lightweight implementation of a Joint Embedding Predictive Architecture (JEPA) from scratch, which I call Micro-JEPA. In this project, the agent learns a representation of the environment, predicts future states in the latent space using a learned world model, and utilizes a cost/energy function to plan its steps toward a target while actively avoiding dynamic or static obstacles. There is a video of it working in the README GitHub Repo: https://github.com/Jacopos311/Micro/_JEPA submitted by /u/No_Firefighter8428
Originally posted by u/No_Firefighter8428 on r/ArtificialInteligence
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