AMI Labs' technical thesis rests on the Joint Embedding Predictive Architecture, or JEPA, a framework LeCun first proposed in a 2022 position paper, “A Path Towards Autonomous Machine Intelligence.” Its central design choice is to predict the future in an abstract latent representation space rather than by reconstructing raw pixels or generating tokens. LeCun's argument is that most of what happens in a video — the precise flutter of leaves, the exact texture of noise, unpredictable microscopic detail — is inherently unpredictable, and that forcing a model to reproduce that detail wastes capacity and degrades the quality of what it learns. A representation-space predictor, by contrast, is trained to discard the unpredictable and retain only what matters for understanding cause and effect.