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 being tokenized today on Arbitrum to unlock the credit markets needed to finance one of the world’s fastest-growing productive assets For @0xZergs, the programmable economy creates an opportunity to build entirely new financial infrastructure for AI Through @USDai_Official, the team is turning GPUs into collateral, giving AI infrastructure companies a new path to access flexible capital This is what the future of finance holds

AI at the edge isn’t necessarily a threat to centralized data centers — it’s a shift toward hybrid computing. Routine, low-latency and privacy-sensitive workloads can move to phones, PCs, vehicles and enterprise devices, reducing some cloud inference and bandwidth demand. But frontier-model training, complex reasoning, agentic workloads, massive context and advanced inference still require centralized compute. The bigger picture: AI compute is being distributed, not eliminated. Edge AI can actually act as a pressure valve for power- and grid-constrained data centers, allowing scarce centralized capacity to focus on increasingly demanding workloads. Cloud + Edge > Cloud vs. Edge. I don’t view edge AI as an immediate existential threat to hyperscale data-center demand. I view it as an evolution of the architecture. The cloud will increasingly handle the workloads that require enormous amounts of compute. The edge will handle workloads where latency, privacy, bandwidth and cost make local processing more efficient. And the boundary between the two will continue to move. The long-term AI infrastructure story therefore may not be about cloud versus edge. It may be about cloud + edge + increasingly intelligent distribution of compute. The winners may ultimately be the companies enabling that entire transition — from silicon and memory to networking, data centers, power and the intelligent devices sitting at the edge

AI scales with energy.....and Tesla is building the battery infrastructure to support that scale Megapacks are becoming the foundation for energy abundance Tesla is now building them at Megafactories in California, Texas and Shanghai, while deployments have expanded across 65+ countries worldwide The scale is already massive: • 77+ GWh of Megapack storage operating globally • 99.3% fleet uptime • Lathrop Megafactory: ~40 GWh/year capacity • Texas Megafactory: designed for ~50 GWh/year of Megapack 3 • Tesla deployed another 13.5 GWh of energy storage in Q2 alone As AI compute, data centers and electrification keep scaling, generating energy is only half the problem You also need to store enormous amounts of it and deliver it exactly when the grid needs it That is where Megapack becomes critical The future is electric

AI compute, but make it decentralized. Add liquidity and earn on incentivized DGAI-USDT pools with @dgrid_ai, the network routing AI requests across a distributed grid of independent nodes and AI models. → @BNBCHAIN: → @arbitrum:

AI compute is not a winner-takes-all market. There will be several winners. You can pick the company you like most or buy $NCLD ETF. Top 10 holdings: $NBIS 33.27% $CRWV 27.20% $IREN 7.43% $HUT 4.94% $APLD 4.29% $WULF 4.06% $GLXY 3.98% $CIFR 3.44% $RIOT 3.24% $CORZ 3.06%

AI compute might be turning into a whole new asset class! @CernBasher makes an interesting point: the AI buildout is getting way too expensive for tech companies to fund everything themselves. That’s where Wall Street comes in. Pension funds, insurers and big investment firms could finance the AI factories, while companies pay to use the compute they produce. Basically, finance AI infrastructure like we already finance airports, power plants and real estate. If that model takes off, it could change how Tesla, SpaceX and the rest of the AI industry fund the next massive wave of compute. $TSLA $SPCX

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.