Virtual Worlds for Physical AI Systems

In this episode I'm joined by Apurva Shah, co-founder and CEO of Duality AI, a company building virtual worlds — or "world models" for robots and physical AI systems.

Apurva's path here is an unusual one. He spent most of his career in animation, first at Pacific Data Images (which later became DreamWorks) and then over a decade at Pixar. His co-founder, Mike Taylor, comes from the other end of the spectrum entirely: a controls engineer who led field robotics at Caterpillar, deploying house-sized haul trucks at Australian mines. As Apurva puts it, if he's the pixels, Mike is the atoms.

We talk about why real-world data, as valuable as it is, is never enough on its own — and how synthetic data can be used to deliberately fill the gaps and biases that creep into any collected dataset.

Some of the things we get into:

• The difference between digital twins and 3D assets and why Duality treats twins as modular building blocks you compose into scenarios, rather than as one monolithic environment
• How they build environments from the ground up using DEM data, satellite imagery, photogrammetry and biome catalogues and why building them this way means everything is annotated from the start
• Calibrating virtual sensors against real ones, including synthetic aperture radar, and why sensor noise characteristics matter as much as physics
• Predicting how a material will behave across the spectrum (infrared, SAR) just from its visual response — and when that prediction breaks down
• Why "clutter" only becomes clutter once you know what you're looking for, and why it doesn't need to be perfect
• Modelling star fields for localisation in space, where there are no roads or buildings to navigate by
• Explicit versus generative world models, and why you need both
• A project with AWS simulating emergency ambulance routing through a city, complete with autonomous vehicles, traffic control and teleoperated human agents
• Where Duality is not the right tool molecular scale, virtual patients, drug discovery
• And yes, a story about robotics companies renting Airbnbs, trashing them, and leaving

Towards the end we get into the bigger questions: whether AI takes our jobs or makes us better at them, where the line sits between "good enough" and slop, and why Apurva — a self-described humanist — thinks virtual environments are the one place where human and machine intelligence can genuinely learn from each other.

Find out more at duality.ai, or dig into their technical writing at duality.ai/blogs