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In Today’s Issue:
🛠️ Bezos’s Prometheus and the race to build a physical-world AI
🪖 A Google security director resigns over its Pentagon AI deal
⚛️ China’s nuclear build-out becomes an AI-power story
🏗️ Anthropic moves to lease and control its own data centers
🛰️ Iran puts Musk’s Starlink on its target list
✨ And more AI goodness…
⚡ The Signal
The AI race just moved out of the chatbox and into the physical world.
Jeff Bezos came out of stealth with Prometheus, a $41 billion startup that wants AI to design and build real machines, not just text. Around that headline, the day’s stories point at the same shift: China is racing to pour nuclear power into the grid AI now strains, Anthropic is signing leases to control its own data centers, and Iran is treating Elon Musk’s orbital internet as a military target. The frontier is no longer only which model is smartest. It is who controls the engineering, energy, compute, and satellites that intelligence runs on. Software was the easy part.
All the best,
Kim Isenberg
Google (Storyboard18)
🪖 A Google security boss quits over its Pentagon AI deal
René Mayrhofer, Google’s director of Android platform security, is resigning over the company’s new deal to put its AI models to work for the Pentagon. In a farewell note he called the decision “unavoidable,” writing, “I am a pacifist, and have long ago decided that I will not personally work for militaries engaging in offensive warfare.” His exit follows Google quietly dropping its pledge not to build AI for weapons and surveillance, and a petition from more than 580 employees, including DeepMind researchers, urging Sundar Pichai to refuse classified military work.
👉 tl;dr: A senior Google security leader is walking out over the Pentagon AI contract, a sign the Project Maven-era ethics fight is back.
⚛️ China’s nuclear sprint becomes an AI-power story
China has nearly doubled its nuclear power capacity since 2016 and now accounts for almost half of all reactors being built worldwide, new U.S. Energy Information Administration data shows. Capacity jumped about 76% (roughly 24 gigawatts) through 2024 and is still climbing, reaching 60 operating reactors, with 36 more under construction, more than 49% of all nuclear building on the planet. The timing is the point: as AI data centers push electricity demand to records, cheap and steady power is becoming the real limit on who can scale AI, and China is building that supply side fastest.
👉 tl;dr: The AI race increasingly runs on electricity, and China’s reactor boom is a quiet bid for the energy edge.
🏗️ Anthropic moves to control its own data centers
Anthropic is moving to control its own compute, signing its first deals to operate dedicated data centers instead of only renting servers, The Information reports. It has reportedly signed more than a dozen letters of intent for over 1 gigawatt of capacity, and is in talks for Google to financially guarantee the lease payments, since Anthropic alone lacks the balance sheet that lenders want. The move echoes OpenAI’s Nvidia-backed Ohio mega-campus and shows how chipmakers like Google, Nvidia, and Broadcom are quietly becoming the financiers of the AI build-out.
👉 tl;dr: Anthropic wants to own its compute destiny, with Google as co-signer, as the data-center land grab speeds up.
Map where AI can actually touch the physical world in your job.
Why it helps: Most AI tools still live in text and code. Bezos’s bet on an “artificial general engineer” is a reminder that the next wave is about designing and making real things, and the teams that spot where that applies will move first.
Try this: Paste today’s Featured Story into your AI and ask: “For my industry, list five physical or engineering tasks (design, testing, manufacturing, logistics, maintenance) where an ‘artificial general engineer’ could cut time or cost within two years. For each, give one concrete pilot I could start this quarter and one reason it might fail.”
🎬 Watch This
Demis Hassabis on what comes after the chatbot.
In this wide-ranging conversation, the Google DeepMind CEO and Nobel laureate maps where he thinks AI heads next, from accelerating scientific discovery and robotics to a future that could look radically different from today. Worth watching because Hassabis is one of the few people building frontier models who reasons in decades of science rather than quarters of product, and he is candid about both the promise and the risks.
“We heard you wanted to use Codex rate-limit resets on your own time. Starting today, you can save your resets and use them later.”
– OpenAI, announcing saved rate-limit resets for its Codex coding tool. The move reads as a pointed bit of customer goodwill in the intensifying price-and-limits war with Anthropic.
A developer says they ‘vibe-coded’ a working World of Warcraft-style MMO almost entirely with Claude Fable 5. Posting to r/ClaudeAI, the builder claims Fable 5 generated the game end to end and even produced its own art instead of pulling in existing asset files. The public repo, “World of Claudecraft,” lends the story some weight: it is a real, playable TypeScript and Three.js game with three zones, around 60 quests, five-player dungeons, and all nine classic classes, and its README notes every spell and item icon is “drawn on canvas at runtime, no asset files.” Caveat: We could not independently verify how much of the code Fable 5 actually wrote, so treat the “fully AI-built” claim as the developer’s for now.
Jeff Bezos Bets $12 Billion on an ‘Artificial General Engineer’
The Takeaway
👉 Jeff Bezos has come out of stealth with Project Prometheus, an industrial-AI startup now valued at $41 billion after a $12 billion raise.
👉 Bezos is co-CEO alongside Vik Bajaj, a former Verily and Google X scientist; the roughly 150-person team includes researchers hired from Meta, OpenAI, and DeepMind.
👉 The goal is an “artificial general engineer”: AI that designs and manufactures real physical systems, from jet engines to new drugs, learning from real-world trial and error.
👉 Backers include JPMorgan, Goldman Sachs, and BlackRock, and most of the new cash is earmarked for compute.
Jeff Bezos is back in an operating role, and he is aiming at the physical world. On June 11, Project Prometheus emerged from stealth with a $12 billion raise at a $41 billion valuation. Bezos, who stepped down as Amazon’s CEO in 2021, is co-CEO alongside Vik Bajaj, a chemist and physicist who helped found Alphabet’s life-sciences arm Verily. The company launched quietly in November 2025 with $6.2 billion and has already hired roughly 150 people, including researchers from Meta, OpenAI, and DeepMind, across offices in San Francisco, London, and Zurich.
Jeff Bezos (Emma McIntyre / WireImage via TechCrunch)
Prometheus is chasing what it calls an “artificial general engineer”: AI that can design, test, and manufacture complex physical things, the kind of work that today takes large teams many years. “Something that today was going to take 100 engineers 10 years to build, if you can change that to taking 10 engineers one year to build, you’re just going to get way more things built,” Bezos said. The targets named so far run from jet engines to drug compounds. The hard part is data: unlike chatbots trained on the open web, a physical-world model has to learn from real-world trial and error. “We create that data for the most part ourselves,” Bajaj said.
Project Prometheus emerges from stealth (Semafor)
It places Bezos among the other AI titans, but on a different axis. Where OpenAI, Anthropic, and Google fight over chatbots and coding agents, Prometheus is betting the bigger prize is physical AI, the world of atoms rather than tokens. Bezos sounds unbothered by the field: “What we’re doing is so difficult, the last thing I’m worried about is moats.”
Why it matters: If physical AI works even partially, it pushes the technology out of writing and code and into the economy’s slowest, hardest sectors, manufacturing, materials, and medicine, and hands an early edge to whoever can fund the compute to get there. That is a contest measured in years and billions, which is the kind Bezos has played before.
Sources:
🔗 https://www.nytimes.com/2026/06/11/technology/bezos-prometheus-ai-engineer.html
🔗 https://www.axios.com/2026/06/11/prometheus-bezos-industrial-ai
🔗 https://techcrunch.com/2026/06/11/jeff-bezoss-prometheus-raises-12b-to-build-an-artificial-general-engineer-for-the-physical-world/
The IT strategy every team needs for 2026
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The chart: Epoch AI tracks the computing power of the single largest AI data center, in H100-equivalent GPUs on a log scale. The record has doubled roughly every 7 months (about 3.3x per year), climbing along the teal “frontier” line from around 100,000 H100-equivalents in early 2025 past 1 million by 2026, and is projected to approach 10 million by 2028, far above the cloud of non-frontier facilities below.
The lesson: This is the supply side of the rest of today’s issue. Compute is being concentrated into ever-larger single sites faster than the chips themselves improve, which is exactly why Anthropic is racing to control its own data centers and why power, not model design, is becoming the binding constraint on AI.
The caveat: Most of the curve is a projection. Epoch says it captures most record-holding facilities from 2024 to 2028 but that individual capacities and start dates are uncertain, and “H100-equivalents” is a normalization, not a literal GPU count. Packing this much compute into one site also concentrates power-grid and reliability risk.
🛰️ Iran Turns Musk’s Starlink Into a War Target
⚡ Bottom line: Iranian state media has placed Elon Musk’s Middle East assets, including Starlink, on a list of “military targets” as the US-Iran conflict escalates.
💡 Why it matters: Starlink and the AI-driven systems riding on it are now real-world infrastructure, and infrastructure gets targeted in war.
🔎 What it means: The politics of AI is reaching orbit, where one company’s satellites are both a lifeline and a liability.
The war over AI is no longer only about code; it is also about the hardware in orbit. Iran’s state-run Fars news agency reported that Elon Musk’s commercial interests across the region, “including Arab countries and Israel,” have been added to an initial list of potential targets, with Starlink, SpaceX’s satellite-internet network, singled out. Tehran’s grievance is that Starlink terminals have let activists stay online during state-ordered internet blackouts, and that Musk-linked systems have aided US military operations.
SpaceX (Getty Images via TechCrunch)
The threat lands at a pointed moment. SpaceX is reportedly moving toward a public listing, Musk’s xAI is weaving its Grok models deeper into his companies, and Starlink is increasingly the connective tissue for drones, sensors, and AI-driven systems on the modern battlefield. That dual-use reality, consumer internet by day and military backbone by night, is exactly what turns a private constellation into a target. For an AI ecosystem that runs on always-on connectivity, the lesson is uncomfortable: the more these networks matter, the more they look like strategic assets to an adversary.
Elon Musk (The Sun)
None of this is an attack, yet. It is rhetoric from a state outlet during an escalating confrontation, and Iran’s ability to reach satellites or distant ground stations is limited. But it marks a shift in how AI politics is fought: the contest is moving from who builds the smartest model to who controls, and who can credibly threaten, the physical rails that intelligence travels on.
What happens when you throw out the GTM playbook
That investor was wrong. Gamma is now worth $2B, with 50M users and more than half their growth driven by word of mouth.
They're one of 6 AI-native startups in HubSpot for Startups' free Bold Bets Playbook. Replit grew revenue 50x after half the team pushed back on the strategy. Ramp generated 100M+ views from a single stunt. Clay's co-founder wouldn't hang up a sales call until the prospect DMed him in Slack.
Each one took a GTM risk most founders would never greenlight. Each one paid off.