IBM’s Quantum Leap & Military AI Testing Cuts
▼ Summary
– IBM plans to build an error-corrected quantum computer, Starling, by 2028, aiming for cloud availability by 2029.
– Starling will consist of modular chips housed in a new Poughkeepsie data center, designed for large-scale quantum computing.
– IBM claims Starling could solve quantum computing’s biggest technical hurdle by being the first large-scale machine with error correction.
– The Pentagon is cutting the Office of the Director of Operational Test and Evaluation’s staff by half, reducing it from 94 to 45 employees.
– The downsizing marks a significant overhaul of a department critical for testing AI and weapons systems, potentially benefiting defense tech companies.
IBM has unveiled ambitious plans to develop a groundbreaking quantum computer called Starling, targeting operational readiness by 2029. The company aims to overcome one of quantum computing’s biggest challenges, error correction, by creating a modular system housed in a dedicated New York data center. This project represents a potential turning point for the industry, promising computational power far beyond today’s quantum machines.
Starling’s architecture will consist of interconnected modules, each containing multiple chips designed to work in unison. IBM believes this approach will enable the first large-scale implementation of error correction, a critical milestone for practical quantum computing. If successful, the system could unlock new possibilities in fields like materials science, drug discovery, and cryptography.
Meanwhile, the Pentagon is dramatically scaling back its AI and weapons testing capabilities, raising concerns about oversight and safety. Defense Secretary Pete Hegseth has slashed staffing at the Office of the Director of Operational Test and Evaluation by more than 50%, reducing the team from 94 to 45 personnel. The office, created in the 1980s to ensure military systems meet safety and performance standards, has never faced cuts of this magnitude.
Critics argue the downsizing could weaken accountability, potentially benefiting defense contractors at the expense of rigorous evaluation. The move follows broader trends of streamlining military spending, though its long-term implications for AI and weapons development remain uncertain.
(Source: Technology Review)
