Between the US and UK, there is wide gap between AI infrastructure consisting of chips, data centers and software models that power the AI tools. Almost 75 per cent of the supercomputers used in AI space are owned by the US, as against 15 per cent by China and the rest 10 per cent distributed elsewhere. In computer capacity, the UK holds 3 per cent of the world’s compute capacity. It comes to 1.8 gigawatts. The UK is expected to reach six gigawatts by 2030. A single Facebook project in Louisiana matches this capacity. It is necessary for the UK to operate with its own facilities in the midst of market disruption.
There is a global race to build the most powerful AI models, and the issue is settled in favour of OpenAI, Google, DeepSeek and Anthropic. At this frontier, it is not possible for any other country except the US and China to be competitive. There could be some thinking whether funds should be spent on the training front. The UK has earmarked 1 billion pounds for training capacity. The funds could be spent elsewhere.
It is wiser for the UK to build on server facilities that run on AI services. This space is called inference in AI field. Google is funding a data center 20 miles north of central London. The UK startups — Synthesia, Poly.ai, Wexler — cater to the needs of legal firms or training and marketing services. The well-heated finance industry in the UK and Europe should finance the local startups. There is no need to fight entrenched US tech firms. The UK and European nations should leverage the infrastructure to create new firms, and stimulate innovations for the longer term.
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