Autonomous AI agents are becoming the new economic actors, shifting value away from platforms toward underlying coordination networks. Users are no longer participants in digital systems — they are the origin points of agents that act, transact and accumulate value independently.
AI is pushing compute from a shared resource into a strategic asset. As demand outpaces supply, companies are no longer optimizing for access—they’re building for control, collapsing the tech stack into tightly integrated, self-owned systems.
As AI systems scale, the real constraint is no longer compute but connectivity. At OFC 2026, photonics—and specifically chip packaging—emerges as the critical layer enabling performance, efficiency and scalability, positioning the Netherlands as a strategic player in global AI infrastructure.
As Greg Abel succeeds Warren Buffett, Berkshire Hathaway is quietly repositioning for the AI age. Not by chasing software hype, but by embedding itself in energy, infrastructure and operational efficiency — where intelligence meets thermodynamics and capital becomes strategic power.
As AI collides with the physical limits of energy, land and capital, Wall Street is revaluing the technology not as software but as infrastructure. From BlackRock’s power bets to Berkshire’s pivot, the next phase of AI will be built on megawatts, not models.
For more than two decades, innovation in consumer technology followed a familiar rhythm. Smaller chips. Faster processors. Thinner devices. Each generation promised more power without asking anything in return.
Photonics is not a buzzword. It is the technology that carries the internet across oceans, enables chips to be etched at atomic scale and forms the foundation of future quantum systems. From fibre-optic communications to advanced manufacturing, photonics has become a critical enabler of modern societies. By 2030, the global photonics market is expected to exceed one trillion dollars. Yet at the heart of this rapidly expanding field lies a strategic chokepoint: extreme ultraviolet (EUV) lithography.
Germany’s AI ambitions are shaped as much by infrastructure as by research, industry or policy. Datacenters, energy supply and high-performance computing form the essential backbone for AI deployment, yet they also introduce constraints that influence where, how and how quickly AI capabilities can scale. Ambition alone cannot overcome the realities of electricity grids, cooling requirements and permitting processes.
For years, Germany has been described as Europe’s “industrial engine”, a country where engineering discipline meets long-term economic planning. As artificial intelligence accelerates globally, Germany finds itself at a crossroads: well-equipped with research depth, industrial muscle and public investment—but also challenged by the speed, capital intensity and platform dynamics that define the AI race. What emerges today is a nation trying to translate a century of industrial expertise into leadership within a technology wave dominated elsewhere by hyperscale software ecosystems.
