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Jeff Bezos just came out of retirement. His first CEO role since leaving Amazon. And he's building something nobody expected. 🤯 It's called Prometheus. $12 billion raised. $41 billion valuation. Backed by JPMorgan, BlackRock, Goldman Sachs, and Bezos himself. 150 employees. $273 million per person. That's how much investors are betting on this. But here's what makes it different from every other AI company. Prometheus isn't building another chatbot. It's not generating text or images. It's building what Bezos calls an "artificial general engineer" AI that designs jet engines, optimizes manufacturing, and prototypes physical products. LLMs learned from the internet's text. Prometheus is learning from the physical world physics, simulations, engineering data, manufacturing processes. In Bezos' own words: "Something that takes 100 engineers 10 years to build we want to make that 10 engineers, one year." His co-CEO is Vik Bajaj, former Google X executive who worked with Sergey Brin on what became Waymo. No ties to Amazon. No ties to Blue Origin. Bezos said "it deserves a dedicated team obsessed with this one thing." While everyone is racing to build the best AI for words, Bezos is quietly building AI for the physical world. That might be the bigger bet.

Ten thousand wild horses racing across the grasslands like thunder shaking the earth itself. 🐎✨ Some scenes are too powerful to put into words. #Horses# #Grassland# #Nature# #Epic# #Cinematic# #Chinalife# #Xinjiang#

The Dragon Boat Festival is approaching! Have you ever wondered what happens when a Cantonese dragon boat meets the South Pacific waves? It turns out that communities there are just as passionate about water racing!Though thousands of miles apart, the spirit of Guangdong's dragon boat and New Zealand's Waka beats to the same cultural rhythm.

Elon Musk just identified the real bottleneck to artificial intelligence on Dwarkesh Patel’s podcast. He didn’t use political science. He used physics. Impedance matching. In electrical engineering, impedance matching means a component adjusts its own resistance to mirror whatever system it’s plugged into. It becomes the thing it’s connected to. Musk: “They impedance match to the government, to the Public Utility Commission. Literally and figuratively.” The companies responsible for powering every data center, every GPU cluster, every training run on Earth didn’t just slow down. They absorbed the exact operational frequency of the federal bureaucracy. They became it. Musk: “They have to do a study for a year. A year later, they’ll come back to you with their interconnect study.” Twelve months. Not to build anything. Not to deliver a single watt. To study whether you’re allowed to plug into the grid. In technology, one year is an evolutionary epoch. NVIDIA ships a new architecture. OpenAI leaps an entire generation. DeepMind publishes frontier breakthroughs quarterly. Inside government, one year is a single administrative pulse. And the friction isn’t accidental. It’s structural. The utility matches the regulator. The regulator matches the legislature. The legislature matches the election cycle. Each one calibrated to the metabolic rate of the next. A feedback loop of institutional inertia with no exit ramp. Every AI lab. Every hyperscaler. Every nation racing toward superintelligence. Same invisible ceiling. A permitting desk. The ultimate bottleneck is not compute. Not data. Not talent. It is the regulatory capture of electricity itself. And nobody with the authority to fix it has any incentive to move faster. The system wasn’t designed to produce outcomes. It was designed to produce process. A year-long interconnect study isn’t a safety measure. It’s a tax on momentum. The race to AGI will not be decided by who builds the best model. It will be decided by who builds the best grid. You cannot impedance match the future to the past. Eventually, the circuit burns out.

5 Short Prayers for Anxiety & Fear: 1. Lord, calm my racing thoughts with Your peace. 2. Jesus, I give You this fear, I trust You. 3. Father, replace my worry with faith. 4. Holy Spirit, remind me I’m never alone. 5. God, thank You for carrying my burdens.

Tom Mueller was SpaceX’s first employee and built the rocket engines that helped make Elon Musk’s space empire possible. Now, the billionaire engineer has a new bet: Impulse Space, a startup racing to build the fast lane for satellites, cargo and eventually people after launch. My latest feature story in @Forbes takes a look under the hood of Mueller's grand ambitions in the emerging space economy.

スーパー耐久 富士24時間 お疲れ様でした🍀 Hitotsuyama Racingは、トラブルがありながらも24時間を無事完走っ😖✨⭐️ 横断幕と一緒に写真撮ったり 写真タイムでピットウォークで出来ない カッコイイポージングで撮ってくれたり ありがとうございました‼️🙏🏻

Jensen Huang just revealed the mathematics of manufacturing a mind. We are no longer writing software. We are pouring concrete. The world is racing to construct AI factories. Not data centers. Planetary-scale nervous systems. The largest infrastructure buildout in human history. Huang: “Each one of these, at 1 gigawatt level, started at 30, 20, 30 billion dollars. It is at 50, 60 billion dollars, and soon it will be 80, 100 billion dollars per gigawatt.” One hundred billion dollars. That is not a corporate budget. That is the GDP of a sovereign nation. Poured into a single physical structure designed to convert raw electricity into cognition. Biology had millions of years to iterate. To mutate. To fail and adapt. These factories get one attempt. Huang: “100 billion dollars into an AI factory. It must work the first time and it must work right away.” Evolution had the luxury of time. A hundred billion dollars does not. So Nvidia built a digital universe to stress-test the physical one. Using the DSX Sim Omniverse blueprint, partners design and validate an entire Vera Rubin AI factory inside a digital twin before a single rack ships. Every layer. Chips. Network. Cooling. Power grid. Designed end to end. We are simulating reality inside a machine to ensure we can build the machine in reality. Because compute is revenue. And the bottleneck was never silicon. It is thermodynamics. Current AI factories overprovision power by up to 40%. DSX Max LPS eliminates that. More GPUs inside the same power envelope. Billions in recaptured annual revenue. And Nvidia is deploying AI agents inside the factory itself. Balancing cooling and power in real time. Steering stranded watts rack to rack. Routing energy wherever compute demand lives. The intelligence is regulating its own physiology. Hunting for stranded energy. Balancing its own thermals. The machine is learning to keep itself alive. Huang: “Because Nvidia ultimately is not just building a GPU, not just building a system, we’re helping customers build these AI factories, these AI infrastructure that is so immensely complex.” Nvidia’s moat is not silicon. It is that no other entity on Earth has built the complete architecture for constructing and operating intelligence at industrial scale. TSMC fabricates the chips. Nvidia fabricates the factory that turns those chips into cognition. For ten thousand years humanity built monuments to outlast our bodies. Pyramids. Cathedrals. Skyscrapers. We are now pouring hundreds of billions into structures designed to outthink our minds. They must work the first time. Because there is no second draft when the thing you are building might one day write its own.