• Expanded product roadmap to enhance D-Wave’s Leap(TM) quantum cloud service and bring new Quantum AI solutions to market
• Initiative targets three key development areas: quantum distributions for generative AI, Restricted Boltzmann Machine (“RBM”) architectures, and GPU integration
• CEO Dr. Alan Baratz emphasizes the potential of annealing quantum computing to transform AI/ML by offering more efficient model training, reduced energy consumption, and faster time-to-solution 

D-Wave Quantum (NYSE: QBTS), a leader in quantum computing systems, software and services, and the first commercial provider of quantum computers, has announced a significant expansion of its Leap quantum cloud service, targeting advancements in artificial intelligence (“AI”) and machine learning (“ML”). The newly revealed roadmap outlines strategic initiatives aimed at integrating quantum computing with AI/ML technologies to offer more efficient and powerful computational capabilities (https://ibn.fm/oZpfR).

The product roadmap is designed to support customers in addressing various AI/ML workloads, from pre-training optimization to more accurate model training and new AI business use cases that integrate artificial intelligence and business optimization. The roadmap focuses on three pivotal development areas:

• Quantum distributions for generative AI: The focus in this area is on designing novel, modern generative AI architectures that directly use quantum processing unit (“QPU”) samples from quantum distributions that cannot be generated by classical computers. 
• Restricted Boltzmann Machine (“RBM”) architectures: RBM architectures that directly leverage D-Wave’s QPU for various applications are increasingly being used by customers, potentially leading to reduced energy consumption in training and running AI models. 
• GPU integration with Leap Quantum Cloud Service: D-Wave is incorporating additional graphics processing unit resources in the Leap quantum cloud service for the training and support of AI models, while also working to reduce latency between QPUs and classical computing resources, a critical step in enabling hybrid-quantum technology for AI/ML.

The initiative comes at a time when the AI industry is facing an energy crunch, given the high energy usage and associated costs necessary to satisfy a growing set of use cases. Current AI models, especially large language models (“LLMs”), require extensive amounts of power to train and run. At current rates of growth, AI is expected to account for up to 3.5% of global electricity demand by 2030 (https://ibn.fm/lUbDP).

D-Wave’s Quantum AI solutions have the potential to change that given annealing quantum computing’s unique capability to solve optimization issues and help customers leverage better, faster and more energy efficient AI and ML workloads.

Dr. Alan Baratz, CEO of D-Wave, highlighted the transformative potential of this roadmap, underlining that the company is already seeing early evidence that annealing quantum computing could play a key role in helping AI/ML with more efficient model training, reduced energy consumption and faster time-to-solution.

“With results demonstrating our annealing quantum computer’s ability to outperform classical techniques, coupled with rapidly increasing demand from our customers for Quantum AI solutions that integrate with their business optimization requirements, we believe the impact of D-Wave’s Quantum AI solutions could be transformative, bringing a powerful new set of new computing tools for generative AI,” Dr. Baratz said.

For more information, visit the company’s website at www.DWaveQuantum.com.

NOTE TO INVESTORS: The latest news and updates relating to QBTS are available in the company’s newsroom at https://ibn.fm/QBTS

Forward-Looking Statements

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’s control, including the risks set forth under the heading “Risk Factors” discussed under the caption “Item 1A. Risk Factors” in Part I of the company’s most recent Annual Report on Form 10-K or any updates discussed under the caption “Item 1A. Risk Factors” in Part II of the company’s Quarterly Reports on Form 10-Q and in the company’s 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 the company on the date hereof. The company undertakes no duty to update this information unless required by law.

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