- D-Wave’s hybrid solver plug-in enables developers to more easily incorporate quantum into feature selection and machine learning workflows
- D-Wave’s quantum applications cover problems as diverse as logistics, artificial intelligence, materials sciences, drug discovery, scheduling, fault detection, and financial modeling
- According to International Data Corporation (“IDC”), 78% of organizations believe that AI-driven projects significantly, or very significantly, impact business outcomes(1)
D-Wave Quantum (NYSE: QBTS), a leader in quantum computing systems, software, and services, and the world’s first commercial supplier of quantum computers, recently announced a new hybrid solver plug-in for feature selection as a part of its focus on helping companies leverage quantum technology to streamline the development of machine learning applications (https://ibn.fm/IEM2a).
The new hybrid solver plug-in for D-Wave’s Ocean(TM) SDK enables developers to more easily incorporate quantum into feature selection and machine learning workflows, seamlessly integrating with scikit-learn, an industry-standard state-of-the-art machine learning library for Python, which is immediately available for download and use.
D-Wave’s focus is to help customers apply the unique capabilities of quantum computing to practical business applications that solve computationally complex problems.
The value delivered by D-Wave comes from its practical quantum applications for problems as diverse as logistics, artificial intelligence, materials sciences, drug discovery, scheduling, fault detection, and financial modeling. D-Wave’s technology is being used by some of the world’s most advanced organizations, including Volkswagen, Mastercard, Deloitte, Davidson Technologies, ArcelorMittal, Siemens Healthineers, Unisys, NEC Corporation, Pattison Food Group Ltd., DENSO, Lockheed Martin, Forschungszentrum Jülich, University of Southern California, and Los Alamos National Laboratory.
The launch of D-Wave’s new hybrid solver plug-in comes at a time when companies are turning to AI and machine learning technologies to navigate increased complexity in the enterprise. According to IDC, 78% of organizations believe that AI-driven projects significantly or very significantly impact business outcomes (https://ibn.fm/tHObs). (2)
“We’re hearing from customers that the combination of quantum hybrid solutions with feature selection in AI/ML model training is important for accelerating business impact,” said Murray Thom, vice president of quantum business innovation at D-Wave. “This plug-in represents yet another example of how D-Wave is facilitating quantum ML workstreams and making it easy to incorporate optimization in feature selection efforts.”
D-Wave’s new Ocean plug-in makes it easier to use D-Wave’s hybrid solvers for feature selection in workflows. Feature selection is a key building block of machine learning. It is a problem of determining a small set of the most representative characteristics to improve model training and performance in machine learning. With the new plug-in, developers do not have to be experts in optimization or hybrid solving to get the business or technical benefits of both. The developers who are creating feature selection applications can build a pipeline with scikit-learn and then embed D-Wave’s hybrid solvers into the workflow more easily and efficiently.
Developers can easily get started by signing up for the Leap quantum cloud service for free, installing the plug-in, and viewing demos and examples created by the company. For a more collaborative approach, developers can reach out to D-Wave directly and explore the feature selection offering in AWS Marketplace.
For more information, visit the company’s website at www.DWaveQuantum.com.
(1) IDC, Emerging AI/ML Feature Store Technology Bolsters Enterprise Intelligence Initiatives, Doc. #US50007823, Feb. 28, 2023
(2) IDC, Emerging AI/ML Feature Store Technology Bolsters Enterprise Intelligence Initiatives, Doc. #US50007823, Feb. 28, 2023
NOTE TO INVESTORS: The latest news and updates relating to QBTS are available in the company’s newsroom at https://ibn.fm/QBTS
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