  Current automated systems have crucial limitations that need to be addressed
before artificial intelligence can reach human-like levels and bring new
technological revolutions. Among others, our societies still lack Level 5
self-driving cars, domestic robots, and virtual assistants that learn reliable
world models, reason, and plan complex action sequences. In these notes, we
summarize the main ideas behind the architecture of autonomous intelligence of
the future proposed by Yann LeCun. In particular, we introduce energy-based and
latent variable models and combine their advantages in the building block of
LeCun's proposal, that is, in the hierarchical joint embedding predictive
architecture (H-JEPA).
