Snapshot · The Rest Is Politics
US Frontier AI Labs are likely to spend over $740 billion over the next 2–3 years, a scale that makes sovereign European AI infrastructure extremely costly to replicate.
Where this was said
At 11:56 · chapter starts 10:20
Alastair Campbell presses on the practical implications — NHS data projects stuck on older, less capable models while America races ahead, and the cyber-defence nightmare of having only offensive AI and no defensive equivalent. Stewart sets out the stark arithmetic: US Frontier labs will spend $740 billion over the next 2–3 years [1] — Rory Stewart "Frontier AI labs $740B spend: US Frontier AI Labs are likely to spend over $740 billion over the next 2–3 years, a scale that makes soverei…" 11:56 ; Europe is 'massively far behind'; and catching up would require hundreds of billions in data centres, talent, and chips. He deploys the Eurofighter analogy — yes, it's never quite as good as the American F-35, but at least it exists when you need it. The counterargument, which Stewart fairly presents, is that America needs European markets and data too, that open-source Chinese models provide an alternative, and that the real value is in building the application layer anyway. But Stewart's conclusion is uncompromising: we have to make the impossible bet, because the alternative is being switched off entirely [2] — Rory Stewart "The counterargument says America won't cut Europe off — they need our markets and our data. But Rory Stewart says betting on that goodwill …" 11:00 .
The counterargument says America won't cut Europe off — they need our markets and our data. But Rory Stewart says betting on that goodwill is like Shaka Zulu assuming the Industrial Revolution won't reach him. The Eurofighter was never as good as the F-35, but at least it existed when you needed it.
Building sovereign AI infrastructure for Europe and the UK would require hundreds of billions of pounds of investment in data centres, chips and talent — a genuine moonshot.
Pete Hegseth cheerfully declared Anthropic a bad company and celebrated blocking its export. Anthropic responded by asking the administration to explain the specific grounds so it could understand what differentiated its model from competitors. The Trump administration's inability to separate genuine security concern from corporate grudge is the central problem.
Bhanu and his team built approximately 50 free tools to attract search traffic, each linked back to SiteGPT.
With AI coding tools like Cursor, Bhanu can now create a new free marketing tool in less than 5 minutes by referencing existing tools.
Bhanu filters Ahrefs keyword results to show only those with a keyword difficulty below 10, making them realistic ranking targets for any decent website.
Bhanu sets a minimum search volume of 1,000 monthly searches when selecting keywords to target with free tools.
PropGPT averaged 20 downloads per day right after launching on the App Store through influencer marketing.
Eyal and Yali shut down all marketing and spent 4 months completely rebuilding PropGPT from scratch.
PropGPT has accumulated over 40,000 total downloads since launch.
PropGPT's large language model (AI) operating costs are just $20 per month, and the cost is continually falling.
Ad-based monetization works well for game apps where users spend extended time in-session, as seen with Grid and Wordle.
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