D-Wave Quantum recently released a collection of offerings to help developers explore and advance quantum artificial intelligence (“AI”) and machine learning (“ML”) innovation, including an open-source quantum AI toolkit and a demo. Available now for download, the quantum AI toolkit enables developers to seamlessly integrate quantum computers into modern ML architectures. The demo shows how developers can use the toolkit to experiment with using D-Wave(TM) quantum processors to generate simple images, reflecting what D-Wave believes is a pivotal step in the development of quantum AI capabilities. By releasing this new set of tools, D-Wave aims to help organizations accelerate the use of annealing quantum computers in a growing set of AI applications. The quantum AI toolkit, part of D-Wave’s Ocean(TM) software suite, provides direct integration between D-Wave’s quantum computers and PyTorch, an ML framework widely used to train and create deep learning models. The toolkit includes a PyTorch neural network module for using a quantum computer to build and train ML models known as a restricted Boltzmann machine (“RBM”). Used to learn patterns and connections from complex data sets, RBMs are employed for generative AI tasks such as image recognition and drug discovery. Training RBMs with large datasets can be a computationally complex and time-consuming task that could be well-suited for a quantum computer. By integrating with PyTorch, D-Wave’s new toolkit aims to make it easy for developers to experiment with quantum computing to address computational challenges in training AI models. “With this new toolkit and demo, D-Wave is enabling developers to build architectures that integrate our annealing quantum processors into a growing set of ML models,” said Dr. Trevor Lanting, chief development officer at D-Wave.