Quantum isn’t ready for the big leagues yet, but Nvidia thinks it can help.

On Tuesday, the chip giant debuted Ising, a family of open models that aim to speed up the development of useful, scalable quantum computers. In a press release, Nvidia claims that Ising offers “the world's best AI-based quantum processor calibration capabilities" with error correction decoding 2.5 times faster and three times more accurate than conventional methods.

In a statement, Nvidia CEO Jensen Huang said that AI is “essential” to making quantum computing practical. “With Ising, AI becomes the control plane—the operating system of quantum machines—transforming fragile qubits to scalable and reliable quantum-GPU systems.”

The Ising family includes new models, tools and data to accelerate quantum development:

• The Ising Calibration model is a vision language model that can interpret and react to measurements from quantum processors, with agents continuously calibrating quantum computers without downtime.
• The Ising Decoding model, meanwhile, offers two variants of a 3D neural network that perform error correction in real time more than twice as fast as current industry standards.

The Ising models are already being put to use in research labs and institutions, including Harvard University’s school of engineering, Infleqtion, IQM Quantum Computers, Lawrence Berkeley National Lab and the UK National Physical Laboratory.

Nvidia’s addition to the quantum landscape marks a growing interest in the once-theoretical technology. Quantum, for instance, was a major focus of CES in January, with several sources telling The Deep View that quantum and AI will have a symbiotic relationship.

“I can foresee a world where a quantum processing unit, a QPU, would coexist alongside the GPU and the CPU,” Dr. Pouya Dianat, chief revenue officer of Quantum Computing Inc., told The Deep View at the time.

Our Deeper View

Quantum computing is still a finicky technology with a ton of roadblocks. However, Nvidia is putting its weight behind quantum and feeding the ecosystem the same way it feeds open models. By developing foundational systems that make this tech work better, Nvidia is embedding itself into the foundation of quantum computing long before the tech reaches maturity. And given the current compute shortage and quantum's potential to ease AI's energy burden, it might not be long before the industry at large starts to take the tech more seriously.