Designing for Physical AI: From Innovation Lab to Factory Floor

Robots and machines operating in the real world still have to be programmed from scratch for every task, or trained on massive volumes of video and simulation data, only to fail the moment reality shifts.

Inait, founded by neuroscientist Prof. Henry Markram, takes a fundamentally different approach. Its fast-learning AI gives machines a digital brain that learns the way real-world experience teaches us - through cause and effect - adapting on the fly, without retraining, without server farms, and without trillions of data points.

This has moved beyond the lab: early versions of these models are already deployed with industrial partners, handling a wide range of manufacturing tasks. That changes the economics of Physical AI: faster deployment, radically lower energy and data costs, on-site learning, and systems that keep working when the environment changes.

After a keynote by Prof. Henry Markram he’ll be joined onstage by a panel of Physical AI leaders with experience from Microsoft, Capgemini, and FedEx - unpacking what’s next for AI that operates, learns, and adapts in the physical world.

Register at weblink