Microsoft unveils Majorana 2 and advances quantum computing roadmap

Microsoft has introduced Majorana 2, its next-generation topological quantum chip, alongside the general availability of Microsoft Discovery, an AI-powered research platform designed to accelerate scientific discovery.

The company says the new chip delivers a 1,000-fold improvement in qubit reliability compared with the previous generation, representing a step towards more scalable quantum computing.

Majorana 2 incorporates a new materials stack based on lead superconductors, enabling a mean qubit lifetime of 20 seconds, with some qubits remaining stable for up to 1 minute. Microsoft says the improvement has allowed it to shorten its projected timeline for a scalable quantum computer, aiming for 2029.

A key element of the announcement is the role of Microsoft Discovery, the company’s agentic AI platform for scientific research and development. Microsoft said its quantum team used specialised AI agents to automate measurements, optimise fabrication processes, analyse large datasets, identify previously unnoticed flaws, and generate new research hypotheses.

According to Microsoft, agentic AI has become a regular part of its quantum research workflow, supporting scientists and engineers as they manage complex materials, fabrication, software, and measurement challenges.

The company also announced that Microsoft Discovery is now generally available for organisations conducting research in sectors such as life sciences, materials science, chemicals, energy, manufacturing, and consumer goods. A free local application is also being released in preview, allowing individual researchers to access core AI-driven research capabilities through a GitHub Copilot account.

Why does it matter?

Quantum computing still faces major barriers around qubit stability, reliability, error correction, and scalability. Microsoft’s announcement is significant because it links progress in quantum hardware with the use of agentic AI in scientific workflows. If the company’s roadmap holds, AI-assisted research could help accelerate progress towards practical quantum systems, with potential long-term implications for materials science, energy, health, chemistry, and other fields that depend on complex simulation.

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