Celebrating 10 years of IBM Quantum on the cloud

2026-05-08 · Source: IBM Research · Field: Technology & Digital — Artificial Intelligence & Machine Learning, Emerging Technologies & Innovation · Depth: Intermediate, quick

Summary

IBM initiated its quantum computing cloud service on May 4, 2016, with a five-qubit system, followed by the release of Qiskit, the first quantum SDK, in 2017. In 2020, IBM published a five-year technical roadmap for its quantum development. Key milestones include the Eagle processor surpassing 100 qubits in 2021, quantum computing outperforming classical systems in 2023, and a new error correction path emerging in 2024, alongside fleet upgrades to 100+ qubit systems. By 2025, Qiskit functions are expected to expand, fostering algorithm evolution and ecosystem growth. The company anticipates quantum computing will transition from cloud-based access to widespread scientific discovery by 2026, emphasizing early sharing and rapid development.

Key takeaway

For AI Scientists and Research Scientists exploring advanced computational paradigms, IBM's commitment to open quantum access and rapid iteration suggests a viable path for integrating quantum resources. You should consider leveraging Qiskit and IBM's cloud platform for experimental work, as the ecosystem is designed for collaborative development and accelerated discovery, potentially leading to breakthroughs in areas like materials science and drug discovery.

Key insights

Early sharing and open development accelerate quantum computing's progress and real-world application.

Principles

• Share early, share often
• Open access drives innovation
• Collaboration scales impact

Method

IBM's approach involves releasing quantum hardware and software (Qiskit) to the cloud, publishing roadmaps, and continuously upgrading systems while fostering an open ecosystem.

In practice

• Utilize Qiskit for quantum development
• Access IBM's quantum cloud
• Monitor IBM's quantum roadmap

Topics

• IBM Quantum Cloud
• Qiskit SDK
• Quantum Processors
• Quantum Error Correction
• Scientific Discovery

Best for: AI Scientist, Research Scientist, Director of AI/ML

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Editorial summary, takeaway, and curation by AIssential. Original article published by IBM Research.