Robotic Marvels: Conquering San Francisco’s Streets Through Next Token Prediction

A research team from University of California, Berkeley presents a causal transformer model trained via autoregressive prediction of sensorimotor trajectories, culminating in the remarkable feat of enabling a full-sized humanoid to navigate the streets of San Francisco in a zero-shot manner.

ai artificial intelligence berkeley california causal deep-neural-networks enabling humanoid machine learning machine learning & data science ml next prediction research research team robotic san francisco team technology the streets of san francisco through token transformer transformer model university via zero-shot