Nvidia has announced what it believes to be the world’s first family of open source quantum AI models, Nvidia Ising, designed to help researchers and enterprises build quantum processors capable of running useful applications.
To achieve useful quantum applications at scale, significant breakthroughs are needed in quantum processor calibration and quantum error correction. AI is key for turning today’s quantum processors into large-scale, reliable computers.
Open models empower developers to build high-performance AI while maintaining total control over their data and infrastructure.
Named after a landmark mathematical model that dramatically simplified the understanding of complex physical systems, the Nvidia Ising family provides high-performance, scalable AI tools for quantum error correction and calibration — two of the most critical challenges in building hybrid-quantum classical systems.
Ising models run the world’s best quantum processor calibration and enable researchers to tackle much larger, more complex problems with quantum computers by delivering up to 2,5x faster performance and 3x higher accuracy for the decoding process needed for quantum error correction.
“AI is essential to making quantum computing practical,” says Jensen Huang, founder and CEO of Nvidia. “With Ising, AI becomes the control plane — the operating system of quantum machines — transforming fragile qubits to scalable and reliable quantum-GPU systems.”
The quantum computing market is expected to surpass $11-billion in 2030, according to analyst firm Resonance. This growth trajectory is highly dependent on continued progress in addressing critical engineering challenges, such as quantum error correction and scalability.
Nvidia Ising includes customisable models, tools and data that accelerate quantum processors:
- Ising Calibration: A vision language model that can rapidly interpret and react to measurements from quantum processors. This enables AI agents to automate continuous calibration, reducing the time needed from days to hours.
- Ising Decoding: Two variants of a 3D convolutional neural network model — optimised for either speed or accuracy — to perform real-time decoding for quantum error correction. Ising Decoding models are up to 2,5x faster and 3x more accurate than pyMatching, the current open source industry standard.