TL;DR
Microsoft unveiled Majorana 2, a quantum chip with qubits 1,000x more reliable than its predecessor, achieving a mean 20-second lifetime versus microseconds for competitors. Agentic AI via Microsoft Discovery accelerated the development, and Microsoft now targets a scalable quantum computer by 2029, halving its original timeline.
Microsoft has unveiled Majorana 2, a next-generation topological quantum chip whose qubits are 1,000 times more reliable than those in the first Majorana chip introduced last year. The improvement is so significant that Microsoft has cut its timeline for achieving a scalable quantum computer from 2033 to 2029, halving the original target. The company credits agentic AI, deployed through its Microsoft Discovery research platform, with accelerating the materials science, fabrication optimisation, and measurement automation that made the leap possible.
The numbers are striking. Majorana 2’s qubits maintain their quantum state for a mean lifetime of 20 seconds, with some instances lasting as long as one minute. Most competing quantum approaches measure qubit lifetimes in microseconds. Microsoft’s analogy: it is roughly comparable to a phone battery that lasts three years on a single charge instead of dying in a day. Combined with one-microsecond operations and a qubit size of 1/100th of a millimetre, the chip puts Microsoft on what it describes as a path to commercially valuable quantum computing by the end of the decade.
How agentic AI built a better chip
The key materials change was switching from aluminium 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 overcome. Quantum computing startups across Europe and the US are pursuing different approaches to the qubit stability problem, but Microsoft’s topological approach, which creates an entirely new state of matter, is architecturally distinct from the superconducting circuits used by IBM, Google, and most competitors.
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Microsoft Discovery’s AI agents were deployed across the quantum team’s workflow in several ways. Agents automated the measurement process that previously took weeks when done manually, cutting cycle time by orders of magnitude. They analysed nearly two decades of experimental data across multiple formats and silos, finding correlations that no individual researcher could see across that volume. They optimised fabrication processes by running simulations to identify the most promising material compositions before physical experimentation. And they detected an uncalibrated temperature sensor that was introducing noise into the fabrication process, a flaw that had gone unnoticed by human review.
“Agentic AI has permeated almost everything we do,” said Chetan Nayak, Microsoft technical fellow. The application of AI to quantum hardware development represents a convergence that could accelerate the entire field: better AI helps build better quantum computers, which in turn could eventually run better AI.
Microsoft Discovery goes public
Alongside the Majorana 2 announcement, Microsoft made its Discovery platform generally available. The platform lets organisations deploy autonomous AI agent teams, guided by human expertise, to speed scientific research and development. It includes a Discovery Engine for research and reasoning workflows, enterprise-grade security and governance, and integration with Azure. Google, Anthropic, and OpenAI are all pursuing AI for science, but Microsoft is the first to ship a commercially available platform specifically designed for frontier R&D with built-in agent orchestration.
Microsoft also introduced a free Discovery app in early preview that individuals can download and run locally with a GitHub Copilot account. Customers including chemical company Syensqo are already using the platform to develop next-generation fluids for semiconductor manufacturing.
The competitive context
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, and 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 optimisation 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.
Stephan is the sports journalist for the Maple Grove Report.
