Nvidia opens new quantum research centre in Boston
The future of quantum computing may depend on AI, and Nvidia is building the tools to make that future real, starting in Boston.

Nvidia has unveiled plans to open the Nvidia Accelerated Quantum Research Center (NVAQC) in Boston, a facility set to bridge quantum computing and AI supercomputing.
Expected to begin operations later this year, the centre aims to accelerate the shift from experimental to practical quantum computing.
Rather than treating quantum hardware as a standalone endeavour, Nvidia intends to integrate it with existing AI-driven systems, believing this combination could unlock solutions to problems unsolvable by today’s machines.
Quantum computing—much like AI in its early stages—fits naturally with Nvidia’s core strength: parallel processing. Instead of continuing to rely on traditional serial computing, the company has long embraced parallelism through its GPU technology and CUDA software platform.
Nvidia’s success in transforming GPUs from graphics engines into tools for scientific and commercial applications began with its bold decision to make CUDA available across all its products, even at the cost of short-term profit margins.
Nvidia now sees quantum error correction as the next major challenge. Current quantum computers, operating with between fifty and one hundred qubits, face a high error rate due to environmental ‘noise.’
Achieving truly useful systems will require a million qubits or more, most of which will be used for error correction. Instead of depending solely on traditional methods, Nvidia plans to use AI to develop scalable solutions capable of correcting errors in real time.
The Boston-based NVAQC will serve as a testing ground for these innovations. Harvard, MIT, and quantum startups like Quantinuum and QuEra will collaborate with Nvidia’s quantum team to train AI models for error correction and test them using Nvidia’s top-tier supercomputers.
By doing so, Nvidia hopes to make quantum computing not just viable, but powerful and practical at scale.
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