The AI Cold War That Will Redefine Everything (www.wsj.com)

The WSJ piece frames a looming "AI Cold War" — a bifurcation of the global AI ecosystem driven by geopolitical rivalry, export controls, and national security concerns. Governments are moving from a shared research commons toward competing stacks: restricted access to high-end chips, curated datasets, and cloud services will force countries and companies to build redundant supply chains, bespoke accelerators, and localized AI platforms. The article argues this split will reshape where and how models are trained, who can scale them, and which safety, privacy, and IP norms win out. For the AI/ML community, the consequences are both technical and institutional. Expect heavier emphasis on hardware-software co-design (domain-specific accelerators), edge and federated learning to sidestep cloud and data-transfer limits, and diverging model ecosystems with different toolchains, benchmarks, and governance rules. Researchers may face curbs on collaboration, access to top-tier compute, and dataset sharing, driving uneven innovation and higher costs. The shift also accelerates government investment in sovereign compute, talent retention policies, and standards setting — meaning technical choices will increasingly reflect strategic, not just scientific, priorities.