Cassidy: For weeks, the infrastructure story has only gone one way — bigger.
Cassidy: Today, New York finally said stop.
Cassidy: This is AI Daily Briefing.
Cassidy: A statewide pause a billion-dollar compute deal with a European supplier not enough people are asking about
Cassidy: and a math conjecture that supposedly fell to ChatGPT.
Cassidy: Bill, where do we start?
Cassidy: Here's Bruce Gil at Gizmodo:
Quote: Gov.
Quote: Kathy Hochul signed an executive order on Tuesday establishing a temporary moratorium on certain new data centers that consume 50 megawatts
Quote: or more of power. The move makes New York the first state in the country to impose a statewide moratorium on large data center projects.
Bill: Hochul signed it Tuesday — a hard pause on anything pulling 50 megawatts or more, new builds and expansions.
Bill: We've spent three days talking megawatts and campus price tags, and here's the first story where a government actually says stop.
Cassidy: And it's a pause, not a permitting slowdown.
Cassidy: Every other state has been dragging its feet on approvals — New York put a wall up and told the Department of Public Service to spend a year
Cassidy: studying it. So instead of just asking whether this hurts the build-out, ask who benefits on the map.
Cassidy: When New York closes the door on a 50-megawatt project, that project doesn't evaporate — it moves to a state that wants it.
Bill: Which makes site selection a regulatory-arbitrage problem now.
Bill: If you're deciding where to drop a billion in construction
Bill: permit chaos and timeline risk just became line items — and New York just made itself the risky bet.
Cassidy: DataCenter Dynamics, with Georgia Butler:
Quote: Meta is planning to more than double its data center campus in Richland Parish, Louisiana, to 5GW of capacity.
Quote: The campus is set to be Meta's Hyperion data center project, previously a 2GW development.
Quote: Meta announced plans to build a 4 million sq ft (372,000 sqm) campus known as Hyperion in Richland Parish in late 2024.
Bill: So the New York moratorium we just hit?
Bill: Same week, Meta doubles down on Hyperion — 5 gigawatts, fifty billion dollars in Richland Parish.
Bill: One state slams the door, another rolls out the red carpet.
Cassidy: And this started as a 2-gigawatt project.
Cassidy: Now it's more than double that, plus a billion in local infrastructure.
Cassidy: The clue was the land: they quietly bought 1,400 more acres at the end of last year to make room.
Bill: Right, so the land grab came before the announcement.
Bill: Which means the site-selection math was already done before anyone in Albany started drafting a pause.
Cassidy: There's the geographic arbitrage nobody wants to say out loud.
Cassidy: Same day New York took itself off the board, the winning pitch in Louisiana was pretty simple: yes, you can build here.
Bill: Nine buildings phasing in through 2030.
Bill: You don't plan a decade-long buildout somewhere you think the regulators might change their minds.
Cassidy: Rebecca Bellan, writing in TechCrunch:
Quote: Reflection AI, a U.S.
Quote: startup vying to develop open models, has signed a $1 billion compute deal with European AI infrastructure company Nebius.
Quote: Nebius, formerly the international arm of Russian tech giant Yandex, will provide Reflection access to Nvidia’s latest chips.
Bill: So Reflection just put a billion dollars of compute through Nebius — which, if you didn't know, is the former international arm of Yandex.
Bill: A U.S. open-model startup, training on infrastructure with Russian lineage.
Cassidy: And that's the part the open-versus-closed shouting match never gets to.
Cassidy: Everyone's arguing about whether the weights are public.
Cassidy: Nobody's asking whose data center the training actually runs in.
Bill: Right — it's Nvidia's latest chips, but sitting inside a European provider with that history.
Bill: The 'open' story and the 'where does the compute physically live' story are pulling in opposite directions here.
Cassidy: And we're seeing this beyond Reflection.
Cassidy: We flagged Anthropic spreading bets across a Kentucky build and a European chip stack a few days back — now Reflection's doing the same
Cassidy: vendor-and-geography diversification.
Cassidy: That looks like an industry move.
Bill: It's the second compute deal in weeks, too — they'd just locked in SpaceX resources.
Bill: An $8 billion company scrambling to nail down capacity from anyone who'll sell it.
Bill: That tells you how tight supply actually is.
Cassidy: And notice the timing against the New York piece we just ran — one state slams the door
Cassidy: and the compute race routes straight through a European provider.
Cassidy: The map is doing the arbitrage for them.
Cassidy: From Joseph Howlett at Scientific American:
Quote: OpenAI just used its new large language model GPT-5.6 Sol to solve a math problem that humans have struggled with for more than a
Quote: half-century. And all it took was telling the artificial intelligence not to give up.
Bill: So Scientific American's headline is ChatGPT proved a 50-year-old conjecture, and the prompting secret was — tell it to believe in itself.
Bill: I want to be annoyed, but here's what makes this different from everything else we hit today: a proof is checkable.
Bill: Domain experts either verify it or they don't.
Bill: There's no 'beats strong baselines on our internal eval' fog.
Cassidy: Right, and that's the tension.
Cassidy: The output category is genuinely verifiable — but the article?
Cassidy: Three-minute read, byline, no preprint, no visible methodology.
Cassidy: When a claim this big lands with no paper attached, I treat the write-up as marketing until the math community weighs in.
Bill: Yeah — the proof might be real and the coverage still be thin.
Bill: Those are two separate things, and Scientific American blurred them.
Cassidy: And notice how far this is from the megawatt stories we've been in all episode.
Cassidy: Nobody needs a moratorium to run a math proof.
Cassidy: The interesting frontier isn't always the one drawing 5 gigawatts.
Cassidy: Nature Communications writes:
Quote: Many systems resist analytical modeling, making data-driven inference of dynamics important.
Quote: Yet data-driven methods can fail to converge or generalize
Quote: leaving open a central question: When can system behavior be learned reliably from data
Quote: and when is such learning impossible?
Quote: We answer this question using adversarial dynamical systems to identify the boundary between accessible and inaccessible regimes.
Bill: Okay, this one's a palate cleanser after all the megawatt talk.
Bill: Nature Communications has a proof about when you can even learn a system's dynamics from data
Bill: and when it's provably impossible no matter how clean your data is.
Bill: That impossibility half is the part I care about.
Bill: They construct adversarial systems where no single-sequence procedure can guarantee learning — which is the mathematical version of the
Bill: failure mode I hit in production all the time.
Bill: Sometimes your pipeline is fine, and the system still can't be learned.
Cassidy: And it's Koopman operator learning — they say they resolve a longstanding open problem in spectral analysis.
Cassidy: That's a real claim with the proof attached, which after this week is refreshing.
Bill: Right, and look at the validation targets — oscillators, chaotic fluid flow, and Arctic sea ice forecasting.
Bill: They pulled out hidden modes of sea ice decline.
Bill: That's the signal it survives something real, not just a whiteboard.
Cassidy: Compare that with the ChatGPT-proved-a-conjecture headline we hit earlier.
Cassidy: One of these comes with convergence guarantees and certification.
Cassidy: The other came with a press cycle.
Cassidy: Got thoughts on today’s briefing, an AI story we should be watching, or a correction?
Cassidy: Send it to aidailybriefing at lantern podcasts dot com.
Cassidy: We read every note, and your input helps sharpen the show.
Cassidy: Next we're watching New York’s Department of Public Service review of data-center environmental impacts
Cassidy: which is expected to take about a year.
Cassidy: You’ll find links to every story we covered today in the show notes, so if one caught your attention, you can head there to read more.
Cassidy: That’s AI Daily Briefing for today.
Cassidy: This is a Lantern Podcast.