Based on past experience, I believe Edge AI will not scale evenly. It will scale first where a physical system becomes too time sensitive, too distributed, and too operationally critical to rely on distant inference alone. Energy is now moving into that category. For years, edge computing has been discussed
Whilst currently behind the US in terms of investment and scaling, Europe’s edge opportunity is real. But the first durable demand will appear in a handful of workloads where latency, sovereignty, resilience and regulation make local inference essential. For years, edge computing has been discussed as though adoption would
The next phase of AI scaling will be won by the companies that can secure land, energy, and electrical infrastructure fast enough to bring capacity online!! For the last few years, the AI conversation has been dominated by chips, models, and compute. All focused on bigger clusters, faster training, more
Every few months, the same question returns: is AI a bubble? I think that fundamentally wrong; markets can overshoot, weak companies can fail, hype can run ahead of reality. But none of that really determines whether the underlying technology is foundational. The question I care about is whether AI is
The AI race is still often described as a race for chips, but that framing is rapidly becoming outdated. The tighter constraint is increasingly electricity: generation, transmission, substations, transformers, cooling, and the long construction timeline needed to turn ordered hardware into working capacity. The International Energy Agency (IEA) estimates data