Part 7/11:
The JEPA architecture, which Lakhani and his team are developing, represents a shift towards a more sophisticated AI capable of understanding and predicting physical interactions more naturally. This framework, unlike traditional LLMs, is designed to learn from observing videos, allowing it to form an understanding akin to human learning—which is inherently less reliant on vast textual data repositories.
Lakhani's JEPA system aims to efficiently learn concepts and tasks using a few examples, mirroring the human learning process. By predicting masked portions of videos in an abstract representation space, JEPA can process and predict outcomes without being bogged down by irrelevant details, leading to more effective training outcomes.