Tracks 2026

The physical AI field has the architectures, but lacks the data infrastructure to train them.

The shift from programmed to trained robots is the most consequential architectural change in the history of the field, and it is happening right now. Yet unlike language models that learned from the internet, physical AI systems depend on embodied interaction data that is scarce, expensive to collect, and largely locked behind proprietary pipelines. This track brings together Europe's researchers, engineers, and model builders to solve the foundational infrastructure challenge of the physical AI decade.

The economics of robotics have never been stronger. The bottleneck is no longer the technology, but everything around it.

Robotic systems have already proven their potential across warehouses, production lines, surgical suites, and construction sites. The question now defining the industry is what it takes to turn successful pilots into sustained, measurable ROI in real operational environments. The gap is not primarily technical. It is a workflow gap, a certification gap, a change management gap, and a procurement gap. This track brings robot builders and operators into the same room to close the distance between what robots can do and what they are actually doing at scale.

Europe produces researchers who define the global frontier of physical AI, but loses too many before they can build here.

Europe's engineering universities produce some of the world's most accomplished robotics researchers. Yet too many commercialise their work elsewhere, backed by capital structures and ecosystem density that do not yet exist at sufficient scale on this continent. The structural gaps are real and well documented. Europe faces a venture funding shortfall, a hardware investment culture that is still maturing, and an ecosystem fragmentation that prevents the density of talent, capital, and institutional knowledge found in the world's leading robotics clusters. This track brings together researchers, founders, investors, and policy stakeholders to move from diagnosis to action.

Proving a robot works is one problem. Scaling it is an entirely different one.

A robotics company that proves its system works faces a second challenge: building the supply chain, manufacturing process, and operational infrastructure to ship it, support it in the field, and improve it at a cost structure that sustains a business. Europe's answer to this challenge is not yet written. The decisions being made now, from domestic component manufacturing to supply chain resilience and mixed human-robot operations, will shape the continent's position in physical AI for the decade ahead. This track brings together hardware engineers, manufacturing executives, supply chain specialists, and industrial policy voices to write that answer.