Robotic Marvels: Conquering San Francisco’s Streets Through Next Token Prediction | Synced
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...
Source: Synced | AI Technology & Industry Review
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.