TARS unveils AWE 3.5, an embodied-native model with 'Born as One' architecture
rohanpaul_ai · x · 2026-08-22
TARS has introduced the AI World Engine (AWE) 3.5, an embodied-native foundation model designed to address the issue of current embodied AI often feeling like bolted-on modules.
Its core "Born as One" architecture integrates action, perception, geometry, and touch into a single model from the start, rather than stitching them together later. This model-driven system aims to generalize across different tasks, objects, environments, and robot bodies. The training methodology implements a full closed-loop process: pre-training gives the model a base understanding of action patterns, spatial structure, and physical laws via two priors, while post-training uses the AI World Engine to roll out possible future states for validation.
More from Embodied
- WEDGE paper generates training environments conditioned on navigation agent failures — _akhaliq · 2026-10-16
- Viral meme nails AI's irony: it can write symphonies but can't do the dishes — briannekimmel · 2026-10-16
- Knödel Watch: animated vocabulary cards on ESP32-S3, open-sourced 4 days after unboxing — alexcovo_eth · 2026-10-16
- NVIDIA RTX Spark PC launches tomorrow with global events and strong early reviews — NVIDIA Blog · 2026-10-16
- SlipSense fuses pressure and vibration for 23ms zero-shot robotic slip detection — micoolcho · 2026-10-16
- Stanford's Fei-Fei Li team open-sources OpenWAM, a unified world-action model framework for robots — jiqizhixin · 2026-10-16