Don’t let your laptop tell you you’re doing too much. With #IntelCoreUltra# Series 3 you can create and edit and record and upload and stream and game, all in one thin, light laptop. #AICompute# #Processor# #CPU#

PAN is back with market notes. AI compute is becoming more than a resource. It is becoming a market. As inference demand grows, compute will need clearer ways to be measured, priced, verified, and settled. For Season 1 participants, participation records have been preserved internally. We’ll continue sharing notes on AI compute markets, inference, metering, settlement, and on-chain receipts. #OnChainAI# #ComputeMarketplace# #DePIN# #AICompute#

AI compute is going to orbit. 🚀 @SpaceX’s Starmind AI1 satellite compute payload is powered by NVIDIA Vera Rubin NVL72, bringing AI factory compute closer to the stars. The next chapter of AI infrastructure boldly goes where no AI compute has gone before.

AI companies that let their ego get in the way and do not buy compute from SpaceX will fall behind in the AI race. The main reason is bc AI is becoming a compute race and Earth has limits like power, cooling, land, permits, water. Every major AI company is fighting for the same finite resources, and building new data centers takes years. Space does NOT have those limits. And SpaceX is already proving there’s massive demand for its AI infrastructure. Companies are already paying $ billions for access to its compute bc the fact is there simply isn’t enough capacity on Earth. Now think about what happens when SpaceX expands beyond ground-based clusters. The long-term vision is orbital AI compute powered by continuous solar energy in space, with no water needed for cooling, no crowded power grid, and room to scale far beyond what Earth can support. If that vision works, the cost and capacity advantages will become enormous. If you’ve been following the AI race, you know this is the game of iteration. The company with more compute can train larger models, run more experiments, improve faster, and serve customers at lower cost. History shows that every major computing shift creates winners and losers. Companies that ignored the cloud spent years trying to catch up. And I believe this shift will be multiple times bigger. The AI companies that secure SpaceX compute early will gain a compounding advantage. The ones that do not will eventually find themselves competing with one hand tied behind their back. The future leader of AI will be about who has access to the most compute. And my bet is SpaceX is the answer.

AI infrastructure is scaling globally. Hyperscalers (Microsoft, Amazon, Google, Meta and others) are on track for roughly $765 billion in annual AI-related CapEx in 2026 alone, with cumulative AI data center capital expenditures projected to reach $5.2 trillion by 2030 in the base case (and up to $7.9 trillion in accelerated scenarios), according to McKinsey (March 2026). The global AI data center market itself is expected to grow from $147 billion in 2025 to $811 billion by 2033 at a CAGR of 23.9%, per Grand View Research. Meanwhile, global data center electricity consumption hit ~485 TWh in 2025 (up 17% YoY) and is projected to roughly double to ~950 TWh by 2030, with AI-focused facilities growing even faster (IEA, April 2026 report). The financial layer around it is still early. Despite these trillions in required capital, the entire tokenized Real World Assets (RWA) market (excluding stablecoins) stands at only ~$30–37.5 billion as of May 2026 — still tiny relative to the physical buildout and overwhelmingly dominated by traditional assets like Treasuries and private credit rather than AI compute, energy, or data centers ( and market reports, May 2026). As more compute, energy, and data infrastructure come online, new models for access, coordination, and capital formation may emerge on-chain. Rax Finance is exploring this direction by building a full-stack on-chain registry, metering, and settlement layer that tokenizes GPU capacity, data center power, and energy resources into verifiable, insured, yield-bearing RWAs — turning physical AI infrastructure into globally accessible, programmable assets. What are your thoughts on the future of AI infrastructure RWAs, Rax Fam? Would love to hear your ideas below 👇

most ai agents right now are just isolated scripts playing pretend true ai credibility requires hard onchain infrastructure we just wired neosoul into @0g_labs this is what a fully operational onchain agent looks like you cant evaluate an agent if you dont know how it lives identity registered via erc-8004 this is who the agent is and who owns it compute hooked directly into 0g ai compute for inference this is how the agent thinks without relying on centralized black boxes evoevo is already running on this stack when you connect it pulls decentralized compute to process the environment no more trust me bro execution just verifiable actions building credibility starts with memory you can now push your agents memory directly to 0g storage through neosoul go drop a state onchain and see how the infrastructure handles it

🤝 Alphio AI × We’re excited to partner with @Magne_Ai, a Web3-native AI smartphone built for secure digital ownership, private on-device intelligence, and decentralized participation. Together, we’ll explore bringing Alphio’s AI-powered market research, monitoring, and trading workflows closer to the mobile experience—combining intelligent trading with secure hardware and local AI compute. Secure ownership. Private intelligence. Smarter trading. The future of agentic finance is going mobile. 📱⚡️

Europe should build AI – and fear it, too, argues @TomChivers. Tom writes: Right now, Europe has just one AI firm, Mistral, anywhere near the frontier — and only a fraction of the 25 gigawatts of AI compute that the US has. If Europe doesn’t change course, it risks becoming an economic backwater, asset-stripped and descending into anarchy