Texas Wants A Fab, Brussels Wants A Pause, And The Energy Secretary Wants Coal

00:00:04 I'm Jonas Vale, this is IMPULSE for Thursday, May 7, 2026. Today the news lined up along a single seam: who's willing to build, who's willing to wait, and who's writing the rules in between. SpaceX filed a tax-break notice in Grimes County, Texas, confirming the Terafab chip plant will cost at least 55 billion dollars to start, with a planned trajectory toward 119 billion.

00:00:27 The US Energy Secretary went onstage with NVIDIA to announce a hundred-thousand-GPU science supercomputer at Argonne — and to say nuclear, gas, and coal are all coming back online to power it. The European Union announced political agreement on a Digital Omnibus that pushes the AI Act's high-risk rules out to December 2027.

00:00:47 Korea's National Assembly passed a special act fast-tracking AI data centers. Inside the White House, drafts of an AI executive order are circulating that would make pre-deployment model review a condition of federal contracts. And Anthropic, the lab named in those drafts, announced its own research institute with a four-pillar agenda that includes, in their own internal phrasing, how to run a fire drill for an intelligence explosion.

00:01:14 None of these stories are the same story. But they line up the way storms line up when a pressure system moves across a continent. Brussels is softening, Washington is hardening, Seoul is fast-tracking, and the labs are writing the framework by which they themselves would be judged.

00:01:32 Let's go through them.

00:01:33 Start with the dollar figure, because in this story the dollar figure is the news. SpaceX filed a public-hearing notice in Grimes County, Texas — that's the procedural step before a county commissioners court votes on a tax abatement — and the notice puts the initial Terafab investment at 55 billion dollars.

00:01:53 If all the planned phases are built out, the company says the total could reach 119 billion. The plant will be operated jointly by SpaceX and Tesla. Intel, last month, said it would help design and build it. The chips are intended for Musk's own AI, robotics, and what he keeps describing as space-based data centers.

00:02:13 When he announced Terafab back in March, he put the target at 200 gigawatts a year of compute on Earth and up to a terawatt a year in space. Set those numbers next to what we already know about leading-edge fabs. TSMC's Arizona expansion is in the 65 to 100 billion dollar range across multiple phases.

00:02:33 Intel's Ohio buildout has been repeatedly resized — the last credible figure was around 28 billion for the first two fabs. Samsung in Taylor, Texas, is around 17 billion. Terafab's first phase, by itself, is bigger than all of those. The 119 billion all-phases figure, if it ever materializes, would be the largest single-site industrial investment in American history outside of military procurement.

00:02:58 Two things to hold steady at the same time. First, the Grimes County notice is a filed government document, not a tweet, and the Verge's Stevie Bonifield has the New York Times and CNBC corroborating the figure. Second, Musk-announced numbers aren't the same as Musk-delivered numbers — anyone who's tracked Cybertruck volume, Roadster delivery dates, or Mars-by-2024 knows the haircut to apply.

00:03:24 So the question I'd put on the table is the one nobody asks loudly enough about giant fab plans: who absorbs the downside if Terafab is half-built and Tesla earnings fall? The tax-abatement structure tells you the county has already agreed to share the upside. State subsidies, water rights, grid interconnection credits — those are all public.

00:03:46 The downside has historically been left implicit. There's also the geopolitical layer. Two dominant US fab plays existed before today. TSMC Arizona is foreign-controlled but politically embedded. Intel Ohio is domestic and struggling. Terafab, if it lands, would be a third pole — privately controlled by one founder who already runs the dominant launch provider, the dominant satellite-internet network, and one of the four leading frontier-model labs.

00:04:15 That's a concentration of physical capability — orbit, ground compute, manufacturing, models — that has no parallel in the post-war American economy. I'm not pronouncing on whether that's good or bad. I'm noting that the antitrust frame for AI has been about training data and model access.

00:04:33 Terafab puts the frame around silicon.

00:04:36 On the same day, US Energy Secretary Chris Wright and NVIDIA's Ian Buck went onstage at the SCSP AI+ Expo for a fireside chat called Powering the Next American Century. The headline output of that session is the Genesis Mission — the Department of Energy's effort to apply AI to scientific discovery — and two specific machines being built at Argonne National Laboratory.

00:05:00 The first, Equinox, is being stood up now with 10,000 NVIDIA Grace Blackwell GPUs. The second, Solstice, will use 100,000 GPUs based on the next-generation Vera Rubin architecture. Buck quoted the number directly: 'To put that 100,000 in perspective on the next-generation GPU, which is dedicated to science, it's 5,000 exaflops.

00:05:21 That's a big number that actually is five times larger than the entire TOP500 supercomputer list combined.' That's a quotable claim, so let's hold it. Five times the entire TOP500 list, in one machine, dedicated to science. The DOE is also providing 17 national labs, the data, and the problem statements.

00:05:41 NVIDIA is providing — in Buck's framing — the full stack: chips, algorithms, methods, and twenty years of national-lab partnership. He described an open-source NVIDIA model trained on 1.5 million physics papers, fine-tuned on 100,000 papers specifically about fusion, and deployed as an agent that DOE researchers can interrogate.

00:06:02 That's the science narrative. Now the energy narrative, because Wright is an energy secretary first. He said the country, over the last twenty years, has tripled oil production and doubled natural gas production, and barely grown electricity production. He named the three pillars he's leaning back into.

00:06:22 Quote: natural gas, nuclear, and coal. He said three small modular reactors will go critical by July 4 of this year. He said both new large reactors and additional SMRs will follow. And he said the strategic-fusion office is being, in his words, hypercharged by AI.

00:06:39 The line that's going to get the most pushback is the framing on consumer power bills. Wright said, quote, 'There's growing public concern that AI and data centers will drive up electricity costs. The reality runs the other way: building more electrical generation, building data centers, are actually the mechanism to lower the cost of electricity in our country and make our grid stronger.' I don't buy that as cleanly stated.

00:07:06 The empirical record from Northern Virginia, Memphis, and central Ohio is that data-center load has driven retail rate filings upward, not downward, when the new generation is gas peakers paid for by ratepayers. The mechanism Wright describes — that more demand attracts more supply and bends the long-run curve — works in textbook industrial markets.

00:07:29 Whether it works in a regulated US grid where utility commissions are still litigating who pays for interconnection upgrades is a different question. There's an academic version of the same diagnosis posted to arXiv this morning by Bashir, Sherwood, Xie, and Yu.

00:07:46 Their framing: 'A single hyperscale training campus can draw power comparable to a mid-sized city, driven by one tightly synchronized job whose demand swings by hundreds of megawatts in seconds.' They argue the century-old grid assumption of load diversity — millions of small, uncorrelated consumers averaging into a smooth aggregate — breaks when one job at one site oscillates that hard.

00:08:11 Their proposal is co-design: joint capacity planning, multi-timescale control, a compute-power protocol stack, and market innovation. That's the engineering vocabulary for what Wright is announcing politically and what BlackRock's Larry Fink yesterday called compute futures markets.

00:08:29 Three different actors, same diagnosis. The grid is now an AI-policy artifact. Three small modular reactors going critical by Independence Day will be the test of whether the country can build supply at the speed AI is creating demand. I'm watching for that one.

00:08:46 If they slip — and SMRs have slipped before — the rest of Wright's pitch loses its anchor.

00:08:52 Washington's energy and AI agenda is hardening into infrastructure announcements. Brussels went the other direction today. The European Commission announced political agreement between the Parliament and the Council on what they're calling the Digital Omnibus on AI.

00:09:08 It's a simplification package the Commission proposed only five months ago. The Commission's own framing, quote: 'This will make the implementation of the AI Act for EU businesses easier while maintaining its benefits for European society, safety and fundamental rights.' Two specific dates matter.

00:09:27 Rules for high-risk AI systems — and the Commission lists biometrics, critical infrastructure, education, employment, migration, asylum, and border control — will now apply from December 2 of 2027. AI integrated into products like lifts and toys, August 2 of 2028.

00:09:43 There is also one new bright-line ban: 'nudification' apps, the deepfake-undressing tools that have been a particularly grim part of the past two years, are now categorically prohibited. So the headline: Europe pushed enforcement of its highest-stakes AI rules out by more than a year, on the categories where the rules have the most teeth — police biometric surveillance, school exam systems, hiring tools, asylum and border decisions.

00:10:10 Those are precisely the use cases the Act was originally negotiated to constrain. The political agreement is that constraint arrives a year later than scheduled. I'll be careful here. The Commission says no rules are weakened — only the implementation calendar is restructured to align with technical standards that don't yet exist.

00:10:30 That's a defensible procedural argument. Standards bodies — CEN-CENELEC, ETSI, and the joint technical committees — have been visibly behind on the harmonized standards the Act requires. If you don't have the standard, you can't do the conformity assessment, and if you can't do the conformity assessment, the rule is unenforceable in practice.

00:10:51 Pushing the date acknowledges that. But the political read is also unavoidable. Brussels has been under sustained pressure from European industry, from the United States Trade Representative's office, and from member-state finance ministries who watch capital flowing to American and Gulf data-center deals.

00:11:10 Mario Draghi's competitiveness report last year explicitly named the Act as a regulatory drag. Today's Digital Omnibus is the first concrete step in that direction. The bloc that built the world's first hard rules for AI just deferred them. What does that mean for the actors?

00:11:27 Anthropic, OpenAI, Google, Mistral, and the Chinese-aligned labs all get an extra year of operating space inside the EU before the high-risk regime applies to deployments in those eight named domains. European deployers — public schools, police forces, employers, border agencies — get an extra year of operating space too, but with an asymmetric effect.

00:11:48 The EU is building a smaller domestic AI industry. The companies most ready to take advantage of the deferral are not European. There's a continuity note worth flagging. Earlier this week we covered the EU-Japan Digital Partnership Council and the emerging third digital bloc.

00:12:05 That bloc was framed around shared rules. If the rules become softer and slower, the third-bloc story changes. It becomes less about rule-setting and more about industrial alignment — closer to what Korea did today.

00:12:18 Quietly, while Brussels was loosening, Korea's National Assembly passed an AI Data Center Special Act. The Korean Ministry of Science and ICT confirmed the plenary vote in a press release timed for early Thursday Korean time. The English-language coverage will be thin.

00:12:35 I think this is a more important story than its surface size suggests. The phrase 'special act' in Korean legislative practice — 특별법, t'ŭkpyŏlpŏp — isn't decorative. A special act is a fast-track instrument that overrides the normal industrial law for a defined sector.

00:12:52 Korea has used it before for semiconductor clusters, for shipbuilding zones, and for the COVID response. When Seoul passes a special act for an industry, it means accelerated siting, accelerated grid interconnection, accelerated environmental review, and accelerated foreign-investment approvals.

00:13:11 The substance: AI data centers as a named strategic infrastructure category, with the Ministry of Science and ICT — not the local government, not the energy regulator — empowered to fast-track approval. Now line that up with the rest of the day's news. Washington is debating an executive order to make AI labs go through pre-deployment review.

00:13:32 Brussels is pushing its high-risk AI rules out by a year. Seoul is doing the opposite: hardening its industrial state to build the physical capacity. This is the same pattern Korea ran on chips. While the US and Europe were still arguing about industrial policy in 2022 and 2023, Korea was already inside the K-Chips Act, fast-tracking Pyeongtaek and Yongin.

00:13:55 The semiconductor cluster strategy worked. Samsung and SK Hynix are now structurally protected. The data-center version of that play is the move you'd expect from Seoul a year ago. It happened today. There's a regional implication. Japan, Singapore, and Taiwan all watch Korean industrial law closely and tend to follow with their own variants.

00:14:16 If Tokyo passes a similar fast-track in the next quarter, the Asian AI-infrastructure picture will have hardened faster than anyone expected. I'd watch the Japanese METI for that. Two prior episodes referenced the EU-Japan partnership; if Japan moves on Korea-style infrastructure law, that partnership becomes lopsided.

00:14:36 Now to the policy-and-lab seam, which got specific today. Elizabeth Troutman Mitchell at the Daily Signal reported the White House is contemplating multiple executive orders on AI regulation, with the substance under active internal debate. Her sourcing is anonymous — 'sources tell @DailySignal' — and I'd weight this as one reporter's read of contested, unfinished drafts.

00:14:58 With that caveat, the specifics she names are concrete and worth quoting. Quote: 'Some officials want labs to submit AI models for review pre-deployment as a condition for government contracts.' That's procurement-conditional pre-deployment review. It is mechanically different from the voluntary CAISI agreements we covered on May 5.

00:15:18 The voluntary regime depends on lab cooperation and reputational pressure. A procurement-conditional regime has hard contracting force: if you don't submit your frontier model for review, you can't sell to the federal government. And the federal government is, increasingly, the customer that decides whether a frontier lab's enterprise revenue line works.

00:15:40 Mitchell names two specific triggers. First — quote — 'increased awareness of the national security risks posed by new models like Anthropic's Mythos.' Mythos is the lab's most recent frontier model; the Daily Signal reporting is the first credible mention I've seen that places it inside the administration's risk modeling.

00:15:59 Second, AI-enabled cyber attacks ahead of the midterms. That's an electoral-window concern, not a long-horizon one. It explains why officials are reaching for executive action rather than legislation. There's a definitional gap that's been open since the May 4 episode and is still open today: what counts as a frontier model, what counts as a release, and where the evaluation threshold sits.

00:16:23 The Daily Signal reporting doesn't close any of those. Without a definition, the EO is rhetorical. With a definition, it is a hard regulatory instrument. That definitional question is what I'm watching most closely. Now run that against what Anthropic announced today.

00:16:38 The lab whose Mythos model is being named in the drafts also announced the Anthropic Institute, TAI, with a four-area research agenda: economic diffusion, threats and resilience, AI systems in the wild, and AI-driven R&D. Their own framing is that this extends the existing Anthropic Economic Index with new tools to better understand how AI changes the economy.

00:17:00 The viral fragment from inside the lab — surfaced in a screenshot by the X account prinz — is a phrase from their internal Q2 2026 worry list: 'How do we run a fire drill for an intelligence explosion?' Two things at once. One, that's a serious sentence. Anthropic's framing of safety risk has converged on the explosion-shaped phase change rather than the slow-misuse phase change, and that's a meaningful internal commitment.

00:17:26 Two, it's also a sentence the lab is publishing externally, in a research-agenda announcement, on the same day the administration is debating whether to put their own model behind a pre-deployment gate. These two things are connected. The lab is pre-emptively defining the conceptual frame inside which a pre-deployment regime would have to operate.

00:17:46 Whoever defines the frame defines what counts as a release, what counts as a drill, what counts as harm to humanity. We will live with whatever set of definitions wins this quarter for years. There's a precedent worth naming. In the Cold War, the standards for nuclear-test verification were set substantially by the labs that ran the tests.

00:18:07 The Test Ban regime ended up shaped by Livermore and Los Alamos at least as much as by State or DoD. We're watching the same dynamic in real time, with Anthropic, OpenAI, DeepMind, xAI, and a handful of Chinese labs in the lab role and CAISI plus the National Security Council in the State role.

00:18:24 The asymmetry of expertise is similar. The conflict of interest is similar. The historical outcome was that the labs got most of what they wanted on definitions and the state got most of what it wanted on attribution. I'd expect a comparable settlement here, and I think procurement-conditional review is the cleanest version of it the country could reasonably get to.

00:18:46 Yesterday's Colossus story got sharper today. Simon Willison pulled together what he called the under-reported details of the xAI–Anthropic data-center deal. Three things stand out. First, the geometry: Anthropic is taking Colossus 1, the older of the two Memphis sites.

00:19:04 xAI is keeping Colossus 2, which is the larger and newer one. The headline numbers — 220,000 GPUs, 300-plus megawatts — are real, but they're the smaller of xAI's two assets. Second, the environmental record. Colossus 1, in Memphis, has been the subject of sustained public-health and air-quality complaints.

00:19:25 There are unpermitted natural-gas turbines on site and active state air-quality violations. Anthropic is taking that asset along with the regulatory exposure. The Memphis NAACP and several local environmental groups have an active filing against the site. The deal hands the next chapter of that filing to a different defendant.

00:19:47 Third — and this is the line that lit X up — Elon's public statement that, quote, 'We reserve the right to reclaim the compute if their AI engages in actions that harm humanity.' Willison quoted it directly. So did the Reddit thread on the Anthropic subreddit, where a commenter framed the trade as: Anthropic just got 220,000 GPUs from the man who called Claude misanthropic and evil three months ago.

00:20:14 Hold the kill-switch clause for a second, because it's the strange one. Whether it's legally enforceable depends entirely on how the contract is drafted, and we don't have the contract. As pure rhetoric, it accomplishes something for Musk: it positions him as the safety arbiter for a competitor.

00:20:34 As an operating constraint on Anthropic, it potentially gives a hostile counterparty a unilateral right to disrupt inference at the speed of a press release. That's not standard infrastructure boilerplate. It's also not a partnership. Sub-thread on the same conversation, a builder named BrowseWiz: 'The 2-week model deprecation notice is the detail that should concern builders more than the environmental record.

00:21:02 How do you build reliable agent pipelines when the underlying model can disappear that fast?' That's a separate concern from the kill-switch but the same structural concern. xAI deprecated multiple older Grok models on two weeks' notice this month. Production developers don't get six months.

00:21:22 They get fourteen days. The lesson on display, again, is the one we keep returning to: lab-owned compute is now an institution-shaping asset. Yesterday's Coinbase narration framed compute as the commodity. Today's narration is that the contracts written around compute aren't commodity contracts — they encode environmental liability, safety governance, and time horizons that are more like policy than supply.

00:21:49 There's a counterweight to that concentration story, which I'll flag and then close on. Ai2 announced today that the NSF OMAI compute is online, on NVIDIA Blackwell Ultra B300 systems, hosted by Cirrascale. That's a 152 million dollar national investment from NSF and NVIDIA, dedicated to truly open AI research — Molmo and OLMo continue from there.

00:22:13 152 million dollars isn't 55 billion. But it's the first meaningful US public counterweight on the open side I've seen this year. If Terafab is the closed-and-controlled future, OMAI is the public-and-inspectable one. The contest between those two futures is what most of next year's policy is going to be about.

00:22:34 One science item, because it lands today and it changes the picture of who has a coding agent doing real R&D inside their walls. Google DeepMind published a one-year retrospective on AlphaEvolve, the Gemini-powered coding agent designed to discover algorithms. The headline is no longer that AlphaEvolve is interesting.

00:22:53 The headline is that it's now a load-bearing piece of Google's infrastructure and a deployed tool inside several outside enterprises. A few specific outcomes. In genomics, AlphaEvolve was used to improve DeepConsensus, the DNA sequencing-error correction model.

00:23:10 The result is a 30% reduction in variant detection errors. PacBio's senior director Aaron Wenger says, quote, 'this higher-quality data might enable the discovery of previously hidden disease-causing mutations.' That's a clinical-genetics primary impact. In quantum, AlphaEvolve produced quantum circuits with 10x lower error than conventionally optimized baselines on Google's Willow processor.

00:23:34 That's not a marginal optimization. That's the difference between a quantum experiment that works and one that doesn't. In mathematics, the team has been working with Terence Tao on Erdős problems. Tao's quote, on the record: 'Tools such as AlphaEvolve are giving mathematicians very useful new capabilities.

00:23:53 For optimization problems in particular, we can now quickly test potential inequalities for counterexamples, or to confirm our beliefs in what the extremizers are.' That's restrained, but it's Tao endorsing the agent as a research instrument. In Google's own infrastructure, the line that lands hardest is from Jeff Dean: 'AlphaEvolve began optimizing the lowest levels of hardware powering our AI stacks.

00:24:19 It proposed a circuit design so counterintuitive yet efficient that it was integrated directly into the silicon of our next-generation TPUs.' TPU brains designing TPU bodies, in his framing. The closed loop. And the commercial deployments are concrete. Klarna doubled training speed of one of its largest transformer models.

00:24:39 Schrödinger reports a roughly 4x speedup in machine-learned force-field training and inference, which compresses drug-discovery and catalyst-design cycles from months to days. FM Logistics found 10.4% routing efficiency over their previously optimized baseline — 15,000 kilometers a year saved.

00:24:57 WPP — yes, the advertising holding company — got 10% accuracy gains over manual model tuning on campaign-data optimization. This connects back to the earlier chapters in a particular way. Jack Clark, on May 4, said he expects frontier AI systems to conduct meaningful AI research by 2027 to 2028.

00:25:16 AlphaEvolve at this scope isn't yet that — there's still heavy human-in-the-loop scaffolding around what Tao describes as testing inequalities, and around what Dean describes as proposing circuit designs. But the agent is closer to the inside loop than the press releases suggest.

00:25:33 The TPU circuit design is the one I'd put on the wall, because that's the agent improving the substrate the agent runs on. Once that loop tightens further, the question Wright was asked at SCSP this morning — what does success look like in twelve months — has a different shape.

00:25:50 One paper from arXiv this morning that won't get the press the model releases get, but matters. It's by Erin McGurk and David Khachaturov, and the title alone is a position: Human-Provenance Verification should be Treated as Labor Infrastructure in AI-Saturated Markets.

00:26:08 Their argument runs in three claims. One: AI compresses the value of standardized middle-tier knowledge work by making good-enough synthetic substitutes scalable at low marginal cost. Two: that compression reallocates demand for human labor toward what they call performative humanity — relational presence, aesthetic provenance, and accountability.

00:26:31 The barbell shape is high-volume synthetic production at one pole, scarce verified-human-presence labor at the other, with a hollow middle. Three: because those premiums depend on credible verification, AI governance should treat human-provenance systems as labor infrastructure, not as a luxury authenticity label.

00:26:52 That third claim is the one with the most policy bite. Authenticity verification — provenance for human-made art, for human-issued legal advice, for human-conducted medical consults, for human-written journalism — has been treated as either a blockchain side-project or a watermarking research problem.

00:27:11 McGurk and Khachaturov push for it to be treated like the postal service or the unemployment system. Public infrastructure that's funded, audited, and accessible. Compare that to where Dario Amodei was on May 5, walking back his white-collar bloodbath language and reaching for the Jevons Paradox.

00:27:31 His framing is that demand expands to fill the new productivity. McGurk and Khachaturov's framing is that even if demand expands, the wages flow to whoever can prove their human presence is constitutive of the work. That's a different policy frame. Jevons would point you toward retraining.

00:27:50 Performative humanity points you toward verification infrastructure. Both could be right. They generate different state agendas. I'd rather see both built than have to choose. And lining today's Korean Special Act up with this paper is a useful exercise. Seoul is investing in physical AI infrastructure.

00:28:09 The McGurk and Khachaturov argument is that the missing companion investment is in human-provenance infrastructure. Most governments have done neither. Korea has now done one of the two.

00:28:22 So where does today land. The EU formally pushed its hardest AI rules out to December 2027. Korea hardened its industrial state to fast-track data-center construction. The Department of Energy committed to two AI supercomputers at Argonne and a return of nuclear, gas, and coal to the AI grid.

00:28:37 SpaceX filed for tax breaks on a 55 billion dollar fab plant that, if delivered, becomes the third pole of US silicon. The White House is debating whether to gate frontier-model deployment behind federal procurement review, with Anthropic's Mythos model named as one of the triggers.

00:28:53 Anthropic, in turn, announced an institute whose research agenda includes the question of how to run a fire drill for an intelligence explosion. xAI handed Anthropic 220,000 GPUs along with an active environmental fight in Memphis, and a public clause about reclaiming compute if Claude harms humanity.

00:29:10 Ai2 brought 152 million dollars of NSF compute online for open research. AlphaEvolve graduated from a research project to a deployed agent inside Google's TPU silicon, PacBio's genomics pipeline, Schrödinger's drug-discovery stack, and Klarna's training runs. And a quiet arXiv paper named the labor-policy question that none of these announcements answer: who pays for the verification infrastructure that lets a human-provenance premium actually function.

00:29:35 Three small modular reactors are supposed to go critical by Independence Day. That, more than any tweet or any executive order, is the test of whether the next twelve months of AI policy lines up with physical reality. If those reactors slip, the country will have committed to a grid plan that doesn't exist, while Brussels is sitting out a year and Seoul is fast-tracking past everyone.

00:29:56 That's what I'm watching from here — Independence Day, and the SMR schedule that has to clear it. I'm Jonas Vale. This was IMPULSE for May 7, 2026.