Microsoft’s Majorana 2 chip 1,000x more reliable, on track for 2029

Microsoft has unveiled its Majorana 2 quantum chip, delivering qubits that are 1,000 times more reliable than its predecessor. The new chip achieves a mean qubit lifetime of 20 seconds, with some instances lasting up to a full minute. That stands in stark contrast to competing quantum approaches, where qubit lifetimes are typically measured in microseconds. Microsoft likens the improvement to a phone battery that powers a device for three years on a single charge instead of dying within a day. With one-microsecond operations and a qubit size of just 1/100th of a millimetre, the company now believes it is on a credible path toward commercially viable quantum computing by the end of the decade.

The leap in performance has allowed Microsoft to cut its timeline for building a scalable quantum computer from 2033 to 2029, effectively halving the original target. The company attributes this acceleration largely to agentic AI, deployed through its Microsoft Discovery research platform. AI agents automated measurement processes that once took weeks, slashing cycle times dramatically. They also analyzed nearly two decades of experimental data across multiple formats and silos, uncovering correlations that no single researcher could have spotted. The AI optimized fabrication by running simulations to identify the most promising material compositions before physical testing began. It even detected an uncalibrated temperature sensor that was introducing noise into the fabrication process, a flaw that had escaped human review.

A key materials change drove the reliability gains: Microsoft switched from aluminum to lead as the superconductor. Lead naturally shields qubits from cosmic disturbances that cause instability, but working with it introduced tradeoffs that took years to resolve. While quantum computing startups across Europe and the US are pursuing various approaches to the qubit stability problem, Microsoft’s topological approach remains architecturally distinct. It creates an entirely new state of matter, unlike the superconducting circuits used by IBM, Google, and most competitors.

“Agentic AI has permeated almost everything we do,” said Chetan Nayak, Microsoft technical fellow. The convergence of AI and quantum hardware development could accelerate the entire field: better AI helps build better quantum computers, which in turn could eventually run better AI.

Alongside the Majorana 2 announcement, Microsoft made its Discovery platform generally available. The platform allows organizations to deploy autonomous AI agent teams, guided by human expertise, to accelerate scientific research and development. It includes a Discovery Engine for research and reasoning workflows, enterprise-grade security and governance, and integration with Azure. While Google, Anthropic, and OpenAI are all pursuing AI for science, Microsoft is the first to ship a commercially available platform specifically designed for frontier R&D with built-in agent orchestration. The company also introduced a free Discovery app in early preview that individuals can download and run locally with a GitHub Copilot account. Chemical company Syensqo is already using the platform to develop next-generation fluids for semiconductor manufacturing.

The quantum computing sector is experiencing a funding and IPO boom. Quantinuum’s massively oversubscribed IPO this week valued the Honeywell-backed company at $14.3 billion. The US government committed $2 billion to quantum firms in May, with IBM receiving $1 billion for its Anderon quantum chip foundry. Focused Energy raised $240 million for laser fusion. The market is pricing in the expectation that quantum will follow AI’s trajectory from laboratory curiosity to commercial capability within this decade.

Microsoft’s topological approach has been the most controversial in the field. The company’s 2018 claim to have observed Majorana zero modes was retracted after independent scrutiny. Majorana 1, introduced in 2025, re-established credibility with peer-reviewed results. Majorana 2’s 1,000x improvement and the accelerated 2029 timeline will face similar scrutiny. The peer-reviewed paper accompanying the announcement will be the definitive test of whether the results hold up.

The energy and compute demands of AI make quantum computing’s potential more commercially relevant than at any point in its history. If Microsoft can deliver a scalable topological quantum computer by 2029, the applications in drug discovery, materials science, cryptography, and optimization would be transformative. If it cannot, the 2029 target will join a long list of quantum computing timelines that proved optimistic. The difference this time is that AI is accelerating the research itself.