NVIDIA today unveiled the NVIDIA Ising family, the world's first open-source quantum AI models designed to accelerate quantum computing development. The models address two critical bottlenecks in quantum computing: processor calibration and error correction. Named after the mathematical model that simplified complex physical systems, Ising provides scalable AI tools that can deliver up to 2.5x faster performance and 3x higher accuracy for quantum error correction decoding.

The quantum computing market is projected to exceed $11 billion by 2030, according to analyst firm Resonance, but this growth depends on solving fundamental engineering challenges. NVIDIA Ising includes two main components: Ising Calibration, a vision language model that automates quantum processor calibration from days to hours, and Ising Decoding, a 3D convolutional neural network with variants optimized for speed or accuracy. The models are already being adopted by major players including Atom Computing, Cornell University, IonQ, and Sandia National Laboratories.

NVIDIA is providing a cookbook of quantum computing workflows, training data, and NIM microservices to help developers fine-tune models for specific hardware architectures. The models can run locally to protect proprietary data and integrate with NVIDIA's CUDA-Q software platform and NVQLink hardware interconnect. By making these tools open source, NVIDIA aims to establish AI as the control plane for quantum machines, transforming fragile qubits into scalable quantum-GPU systems.