D-Wave Launches Quantum AI Developer Toolkit for ML Integration

PALO ALTO, Calif. – August 4, 2025 – D-Wave Quantum Inc. (NYSE: QBTS) has announced the release of a new open-source Quantum AI Developer Toolkit and a corresponding demo, aimed at fostering innovation in quantum artificial intelligence and machine learning.

Available for download now, the toolkit is designed to enable developers to integrate D-Wave’s annealing quantum computers into machine learning architectures. The accompanying demo illustrates how developers can leverage this toolkit to experiment with D-Wave quantum processors for tasks such as generating simple images, showcasing early potential for quantum AI capabilities.

D-Wave’s objective with these new tools is to accelerate the application of annealing quantum computers across a growing range of AI applications. The Quantum AI Toolkit, which is part of D-Wave’s Ocean software suite, provides direct integration between D-Wave’s quantum computers and PyTorch, a widely used, production-grade machine learning framework for building and training deep learning models. Specifically, the toolkit includes a PyTorch neural network module that allows for the use of a quantum computer to build and train a type of neural network known as a Restricted Boltzmann Machine (RBM).

Restricted Boltzmann Machines are employed for generative AI tasks, including image recognition and drug discovery, by learning patterns and connections from complex datasets. Training RBMs with large datasets can be computationally intensive and time-consuming, making it a potentially suitable task for quantum computing. By integrating with PyTorch, D-Wave’s new toolkit seeks to simplify the process for developers experimenting with quantum computing to address these computational challenges in AI model training.

Dr. Trevor Lanting, Chief Development Officer at D-Wave, commented on the release, stating, “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. Customers are increasingly asking us for ways to facilitate the exploration of quantum and AI, recognizing the collaborative potential of these two complementary technologies.”

D-Wave continues to advance its quantum AI product roadmap, delivering new solutions and expanding development efforts through collaborations. The company is currently engaged in exploratory quantum AI projects with several organizations:

• Japan Tobacco Inc. (JT): D-Wave completed a joint proof-of-concept project with JT’s pharmaceutical division, which applied D-Wave’s quantum computing technology and AI to the drug discovery process. This quantum proof-of-concept demonstrated superior performance compared to classical methods for AI model training in drug discovery.

• Jülich Supercomputing Centre at Forschungszentrum Jülich: Researchers utilized D-Wave’s quantum technology to develop a machine learning tool that predicts protein-DNA binding with greater accuracy than traditional classical computer methods. The team achieved improved results across various metrics by integrating quantum computing with support vector machines, significantly enhancing classification performance.

• TRIUMF: Canada’s particle accelerator center, along with its partner institutions, recently published research in npj Quantum Information. The paper highlights significant speedups achieved using D-Wave’s quantum computers over classical approaches for simulating high-energy particle-calorimeter interactions. This work holds potential for creating major efficiencies in scenarios where AI models are used to generate synthetic data.

Organizations interested in exploring the integration of quantum computing into their AI workloads can apply to the Leap Quantum LaunchPad program.

Kevin Chern, Senior Benchmarking Researcher at D-Wave, is scheduled to showcase the toolkit and demo during his presentation titled “An Introduction to Quantum Annealers in Optimization and Machine Learning” at The AI Research Summit at Ai4 2025. The presentation will take place on August 13, 2025, from 11:05 a.m. to 11:25 a.m. PT.