India, June 25 -- Quantum computers are inherently unstable systems, requiring frequent calibration to maintain optimal performance. Traditionally, this process relies on manual intervention, as traditional algorithmic approaches struggle to interpret complex data and balance competing figures of merit in this nascent technology.

As systems scale-up, these manual processes can limit uptime, incur substantial engineering time and cost, and become a critical bottleneck. Addressing this challenge is essential to enable practical, large-scale quantum computing.

The NVIDIA Ising family of open-source AI models are specifically developed for key quantum computing workloads, addressing challenges in both calibration of systems and decoding for...