Open-source toolkit seamlessly integrates quantum systems into AI model training
\nNew open-source ML demo represents a milestone in quantum AI development<\/p>\n
PALO ALTO, Calif. \u2013 August 4, 2025\u00a0\u2013 D-Wave Quantum Inc. (NYSE: QBTS) (\u201cD-Wave\u201d), a leader in quantum computing systems, software, and services, announced today that it has 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<\/a>and a demo<\/a>. Available now for download, the quantum AI toolkit enables developers to seamlessly integrate quantum computers into modern ML architectures. The demo illustrates how developers can leverage this toolkit to experiment with using D-Wave\u2122 quantum processors to generate simple images, reflecting what D-Wave believes is a pivotal step in the development of quantum AI<\/a> capabilities.<\/p>\n 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\u2019s Ocean\u2122<\/a> software suite, provides direct integration between D-Wave\u2019s quantum computers and PyTorch<\/a>, a production-grade ML framework widely used to build and train 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).<\/p>\n 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\u2019s new toolkit aims to make it easy for developers to experiment with quantum computing to address computational challenges in training AI models.<\/p>\n \u201cWith 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,\u201d said Dr. Trevor Lanting, chief development officer at D-Wave. \u201cCustomers are increasingly asking us for ways to facilitate the exploration of quantum and AI, recognizing the collaborative potential of these two complementary technologies.\u201d<\/p>\n Turning Quantum AI Potential into Real-World Value<\/p>\n D-Wave continues to advance its quantum AI product roadmap, delivering new solutions to customers while expanding development efforts. The company is working with a growing number of customers on exploratory quantum AI projects including:<\/p>\n Japan Tobacco Inc.: D-Wave has completed a joint proof-of-concept project with the pharmaceutical division of Japan Tobacco Inc. (JT)<\/a> that used D-Wave\u2019s quantum computing technology and AI in the drug discovery process. The quantum proof-of-concept outperformed classical methods for AI model training in drug discovery. Organizations looking to explore the integration of quantum computing into AI workloads can apply to the Leap Quantum LaunchPad\u2122<\/a> program.<\/p>\n Kevin Chern, Senior Benchmarking Researcher at D-Wave, will showcase the toolkit and demo during his presentation titled \u201cAn Introduction to Quantum Annealers in Optimization and Machine Learning,\u201d at The AI Research Summit at Ai4 2025<\/a>, on August 13, 2025 from 11:05 a.m. to 11:25 a.m. PT.<\/p>\n About D-Wave Quantum Inc.<\/p>\n D-Wave is a leader in the development and delivery of quantum computing systems, software, and services. We are the world\u2019s first commercial supplier of quantum computers, and the only company building both annealing and gate-model quantum computers. Our mission is to help customers realize the value of quantum, today.\u00a0Our quantum computers \u2014 the world\u2019s largest \u2014 feature QPUs with sub-second response times and can be deployed on-premises or accessed through our quantum cloud service, which offers 99.9% availability and uptime.\u00a0More than 100 organizations trust D-Wave with their toughest computational challenges. With over 200 million problems submitted to our quantum systems to date, our customers apply our technology to address use cases spanning optimization, artificial intelligence, research and more. Learn more about realizing the value of quantum computing today and how we\u2019re shaping the quantum-driven industrial and societal advancements of tomorrow:\u00a0www.dwavequantum.com<\/a>.<\/p>\n Forward-Looking Statements<\/p>\n Certain statements in this press release are forward-looking, as defined in the Private Securities Litigation Reform Act of 1995. These statements involve risks, uncertainties, and other factors that may cause actual results to differ materially from the information expressed or implied by these forward-looking statements and may not be indicative of future results. These forward-looking statements are subject to a number of risks and uncertainties, including, among others, various factors beyond management\u2019s control, including the risks set forth under the heading \u201cRisk Factors\u201d discussed under the caption \u201cItem 1A. Risk Factors\u201d in Part I of our most recent Annual Report on Form 10-K or any updates discussed under the caption \u201cItem 1A. Risk Factors\u201d in Part II of our Quarterly Reports on Form 10-Q and in our other filings with the SEC. Undue reliance should not be placed on the forward-looking statements in this press release in making an investment decision, which are based on information available to us on the date hereof. We undertake no duty to update this information unless required by law.\u00a0<\/p>\n Media Contacts:<\/p>\n D-Wave<\/p>\n Alex Daigle<\/p>\n
\nJ\u00fclich Supercomputing Centre at Forschungszentrum J\u00fclich: Researchers<\/a> used D-Wave\u2019s quantum technology to develop a ML tool that predicts protein-DNA binding with greater accuracy than traditional methods using classical computers. The team integrated quantum computing with support vector machines to achieve improved results in various metrics, significantly enhancing classification performance.
\nTRIUMF: Canada\u2019s particle accelerator center and its partner institutions recently published a paper in npj Quantum Information<\/a> showing significant speedups using D-Wave\u2019s quantum computers over classical approaches for simulating high-energy particle-calorimeter interactions\u2014potentially leading to major efficiencies where the AI model is used to create synthetic data.<\/p>\n