Slow Takes Ep. 7: Who Pays for All of This?

Every story this week came back to the same question. Not whether AI is getting more powerful, but who is paying for it. Anthropic locked away its most capable model and gave it to defence contractors. OpenAI proposed robot taxes to cushion the disruption its own products are causing. Meta committed $135 billion in a single year. Anthropic signed a deal measured in gigawatts without once mentioning the word consumption. And OpenAI walked away from the UK because the electricity was too expensive.Five stories. One thread. The bill is arriving. The question is who picks it up.Every Monday at 12:45 BST, Leor Gayr from Exploring ChatGPT and I go through the week’s AI news without hype. Here is what we covered.Slow Takes is also available on the YouTube channel: Exploring ChatGPT.1. Claude Mythos: the model you cannot useAnthropic revealed Claude Mythos Preview, its most powerful model to date, on 7 April. It will not be publicly released. Access is restricted to a handful of partners including Amazon, Apple, Microsoft, and CrowdStrike under Project Glasswing, a defensive cybersecurity initiative. During internal testing, the model found zero-day vulnerabilities in every major operating system and every major web browser. One was a 17-year-old remote code execution flaw in FreeBSD that Mythos discovered and exploited entirely autonomously.What we said on the live:Leor has a source who has used Mythos and confirms the capabilities are real. The model is extraordinarily powerful. But there is a cost problem nobody is talking about: token spend on Mythos runs 5 to 20 times higher than Opus 4.6. Even if Anthropic wanted to release it publicly, the economics do not work. Someone on the $200/month plan burning through Mythos tokens on emails and pizza questions would cost the company a fortune. This feeds directly into Anthropic’s enterprise model: over a thousand businesses paying more than a million dollars a year. They do not need a consumer release. They need trusted partners with deep pockets.What did not come up:The framing. Anthropic positioned this as a security story: we found the vulnerabilities so the bad actors cannot. That is true. It is also a story about governance by corporate discretion. The company that builds the most capable AI system in the world is the company that decides who gets access to it. The people affected by the technology it secures have no say. The model is extraordinary. The question is who gets to use extraordinary things and who decides.2. OpenAI proposes robot taxes for the disruption it createsOpenAI published a 13-page policy paper titled ‘Industrial Policy for the Intelligence Age’. The proposals include a public wealth fund seeded by AI companies and modelled on Alaska’s oil dividend, robot taxes to shift the burden from labour to capital, government-backed trials of a four-day work week at full pay, and automatic safety nets that activate when AI job displacement crosses defined thresholds.What we said on the live:Leor pushed back on the assumption that all jobs will disappear. The farming analogy is instructive: 80-90% of the workforce used to be farmers, machines replaced most of those roles, and people found other work. Jobs disappeared but work did not. The more interesting point is the timing. This paper arrived weeks before a reported IPO, at exactly the moment OpenAI was attracting heat for Pentagon contracts and political alignment. Sam Altman, who said OpenAI would always be a non-profit and would never run ads, is now proposing a policy framework that reads like a socialist manifesto. The ideas themselves are not new. Bill Gates proposed robot taxes years ago. The question is why this company is proposing them now.What did not come up:The automatic safety nets require measurements of job displacement that do not yet exist. Who measures? Who decides when the threshold is crossed? The company causing the displacement? If the answer is yes, that is a company writing the rules for its own disruption before anyone else does. The proposals sound progressive. The timing, weeks before a reported IPO, sounds strategic.3. Meta is spending $135 billion on AI this yearMeta announced AI capital expenditure of $115-135 billion for 2026. That is roughly double last year and treble 2024. Most of the spending goes to Meta Superintelligence Labs, led by Alexandr Wang, hired for $14.3 billion when Meta acquired Scale AI. Meta also launched Muse Spark, its first model under the new division. It is competitive but still behind Google, Anthropic, and OpenAI on key benchmarks.What we said on the live:Leor made a fair point: Meta is funding this from advertising revenue, not from layoffs. Their core business saw a 24% revenue increase. Hats off for spending the money they are making rather than firing people to raise it. The bigger question is why Meta needs its own model at all. Apple decided to partner with Google rather than build a competing AI. Meta could do the same. The answer, as one listener put it, is control. If you do not build your own moat, you end up dependent on companies that will eventually outpace you. And credit to Zuckerberg for pivoting from the metaverse without falling into a sunken cost fallacy. Revenues are up 24%. The strategy changed. That takes discipline.What did not come up:For context, the entire UK higher education sector earns roughly £45 billion per year. One company is outspending every university in the country combined on AI infrastructure. And nobody in that budget line is studying whether any of it works. The spending is treated as self-evidently worthwhile. The assumption is that more compute equals more capability equals more value. That assumption has never been tested at this scale.4. Anthropic’s gigawatt deal: capacity, never depletionAnthropic signed a compute deal with Google and Broadcom for 3.5 gigawatts of TPU capacity starting in 2027, on top of the 1 gigawatt already in use. Revenue has tripled to a $30 billion run rate. Over 1,000 businesses now spend more than $1 million per year on Claude. A gigawatt powers roughly 750,000 homes. The IEA says a single chatbot request uses ten times more electricity than a Google search.What we said on the live:The press release mentions infrastructure, investment, American jobs, exponential growth. It does not mention energy consumption. Not once. It does not mention environmental impact. Not once. The framing is always capacity, never depletion. At some point we have to ask what it means when the solution to every problem created by scale is further scale. We also talked about two shifts that could change the economics entirely: quantum computing, which is realistically five to ten years away from commercial deployment, and the move toward local open-source models. Most people do not need a frontier model for their daily work. A model running on an old laptop can handle research, writing review, and data crunching. As prices rise and people realise this, the demand for massive data centres may not materialise the way these deals assume.What did not come up:In the US, electricity bills are rising faster than inflation. Residential prices increased 11.5% in 2025. In Virginia, bills have risen up to 267% over five years as a direct result of data centre construction. The people footing the bill for AI infrastructure are not the companies building it. They are the families living near the data centres whose electricity costs have tripled. The language of investment hides a transfer of cost from corporations to communities.5. OpenAI shelves UK StargateOpenAI paused its Stargate UK data centre project, announced last September with NVIDIA and Nscale. The plan was for up to 31,000 GPUs across sites in the North East AI Growth Zone, near Newcastle and Blyth. OpenAI cited energy costs and regulatory uncertainty, specifically the UK government’s shifting position on copyright exemptions for AI training after a backlash led by Elton John and Dua Lipa.What we said on the live:The UK government committed £2 billion to accelerating AI adoption. OpenAI committed to building infrastructure in the North East, an area with deep historical ties to industrial labour and persistent unemployment since the decline of shipbuilding and steel. One of those commitments lasted. The other lasted until the energy bill arrived. Investment follows convenience, not policy. When the conditions change, the capital moves. The jobs stay promised. On regulation: as someone in the weeds of UK AI policy, the claim that the regulatory environment is too strict is simply not true. There is almost no AI regulation in the UK. The government has invested £2 billion elsewhere saying build, build, build with no critical literacy, no thinking about when to stop.What did not come up:These data centres take a decade to build. By the time they are operational, the technology they were designed for may not exist in its current form. Quantum computing and local models could reduce demand for centralised compute. OpenAI is not just walking away from a building project. It is walking away from a bet on a future that may not arrive. And the communities that reorganised their economic planning around that bet are left holding the cost.The threadEvery story this week was about cost. Anthropic’s Mythos costs too much to give to the public, so only defence contractors get access. OpenAI’s policy paper proposes redistributing costs it has not yet incurred. Meta is spending more on AI than an entire country spends on higher education. Anthropic’s energy deal uses the language of capacity to hide the language of consumption. And OpenAI walked away from the UK when the cost of electricity outweighed the cost of breaking a promise.The question none of these companies will answer is the one that matters most. Not how powerful the AI is. Not how much it costs to build. But who pays when it arrives, and who pays when it leaves.Go Slow.Paid subscribers get the Slow AI Curriculum: 12 months of structured critical AI literacy, with monthly webinars, critical prompts, and the full archive of frameworks and tools covered in every post. Not productivity tips. The judgement to know when AI is useful and when to leave it alone. CPD-accredited. Get full access to Slow AI at theslowai.substack.com/subscribe