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Chronicles

The story behind the story

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An interview with IBM VP of Quantum Computing Jay Gambetta on the company's plan to build a 100,000-qubit computer within 10 years, finding scientists, and more

The company wants to make large-scale quantum computers a reality within just 10 years.  —  Late last year, IBM took the record …

MIT Technology Review Michael Brooks

Context & Ripple Effects

The interview lands mid-arc for IBM's quantum program. The company laid out its first public quantum roadmap in 2020, promising a 1,000+ qubit processor by 2023, then shipped the 433-qubit Osprey in 2022 on the way to a 4,000-qubit target. Gambetta's 100,000-qubit, 10-year goal extends that same cadence from processor milestones to a machine at industrial scale.

What has followed since gives the plan a budget and an endpoint: IBM committed to IBM Quantum Starling, a fault-tolerant machine in New York state by 2029, and later pledged more than $10B over five years toward a large-scale, error-free computer. The interview is the moment IBM frames the talent problem — finding the scientists — as the binding constraint alongside the qubit count.

First-order effects

  • IBM must staff a decade-long build: the stated plan to recruit scientists makes hiring, not hardware, the immediate bottleneck for the 100,000-qubit program.
  • The 100,000-qubit target resets expectations for IBM's roadmap cadence, which had been measured in hundreds of qubits per processor generation (127 Eagle, 433 Osprey).

Second-order effects

  • Google, which alongside IBM sees an industrial-scale quantum computer potentially by 2030, faces pressure to match IBM's explicit timeline and funding, turning qubit roadmaps into a public race.
  • IBM's later acquisition of HRL Laboratories to integrate electron spin quantum circuits shows the plan forcing hardware bets — new qubit modalities folded in to close the scaling gap the FT coverage flags as the core challenge.

Third-order effects

  • If the pattern holds, quantum computing consolidates around a handful of well-funded industrial players able to sustain billion-dollar, multi-year commitments, with fault tolerance by 2029 as the dividing line between research programs and products.
  • The shift from qubit-count records to error-free, large-scale machines moves the industry's competitive metric from raw qubits to logical-qubit economics, rewarding whoever solves error correction first.

The trend: Quantum computing is moving from processor-count milestones toward funded, deadline-bound races to fault-tolerant industrial machines, with IBM's 100,000-qubit plan and Google's parallel ambition as its leading data points.