Deva-3 -

For the last decade, the holy grail of robotics and autonomous driving has been a simple question: How do we teach machines to predict the future?

We have tried rule-based systems (they break in the real world), end-to-end deep learning (they hallucinate), and large language models (they lack physics). But a new architecture is emerging from the labs that might finally crack the code. deva-3

It is called .

If you work in autonomy, robotics, or simulation, stop fine-tuning LLMs. Start looking at world models. For the last decade, the holy grail of

Current AVs rely on "predictive models" that assume other drivers are rational. DEVA-3 simulates irrational behavior. It can predict the "jerk" who cuts across three lanes without a blinker because it has seen that episode 10,000 times in training data. Wayve and Ghost Autonomy are rumored to be testing DEVA-3 variants on public roads in London right now. It is called

The model hallucinated cars sliding, pedestrians walking cautiously, and brake lights flashing. It had never seen snow, but it had learned friction and low-traction behavior from dry roads. It generalized the concept of slipperiness.