OpenAI's latest fundraising from SoftBank and MGX may be bad news
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In the meantime, revenue per worker continues to climb. Source: BofA, Lance Roberts @LanceRoberts
Source: The Long View @HayekAndKeynes
A forecast attributed to JPMorgan puts global AI compute demand at roughly 530 GW by 2031. Projected supply? 250 GW. That leaves a 280 GW shortfall—even as supply potentially quadruples between 2025 and 2031. The projected gap would grow from around 50 GW today to nearly 280 GW. The investment implications extend across the infrastructure stack: → Neoclouds: Nebius ($NBIS) and CoreWeave ($CRWV) could benefit from sustained demand for scarce GPU capacity. → Chips: NVIDIA ($NVDA) and AMD ($AMD) supply the accelerators. → Memory: Micron ($MU) helps address growing memory requirements. → Physical infrastructure: Networking, storage, electricity and cooling determine how much capacity actually comes online. Persistent shortages could support pricing, utilisation and longer contracts. Execution, financing costs and hardware depreciation will still determine investor returns. Much of the debate centres on whether AI companies are spending too much. These projections raise another question: Can the industry build fast enough to meet demand? Chips must be manufactured. Power secured. Data centres connected. If this scenario plays out, some of AI’s biggest winners could be the companies removing those bottlenecks. Source: JPM, Milk Road AI

