A year and a half after announcing their partnership, Nvidia and Quantum Machines have made a significant breakthrough in quantum computing. The two companies have successfully used an off-the-shelf reinforcement learning model running on Nvidia's DGX platform to better control the qubits in a Rigetti quantum chip, keeping the system calibrated.

This achievement brings the industry one step closer to achieving error-corrected quantum computing, a holy grail in the field. According to Yonatan Cohen, co-founder and CTO of Quantum Machines, the goal is to run quantum error correction, but this collaboration focused on calibration, specifically calibrating the "π pulses" that control the rotation of a qubit inside a quantum processor.

The partnership's success is attributed to the powerful computing capabilities of Nvidia's DGX platform, which enabled the teams to perform the compute-intensive task of constantly adjusting the pulses in near real-time. The collaboration is expected to continue, with plans to make the tools available to more researchers and utilize Nvidia's upcoming Blackwell chips for even more powerful computing.