(PRNewswire) QC Ware, a leader in enterprise software and services for quantum computing, has announced a significant breakthrough in quantum machine learning (QML) that increases QML accuracy and speeds up the industry timeline for practical QML applications on near-term quantum computers.
QC Ware’s algorithms researchers have discovered how classical data can be loaded onto quantum hardware efficiently and how distance estimations can be performed quantumly. These new capabilities enabled by Data Loaders are now available in the latest release of QC Ware’s Forge™ cloud services platform, an integrated environment to build, edit, and implement quantum algorithms on quantum hardware and simulators.
“QC Ware estimates that with Forge Data Loaders, the industry’s 10-to-15-year timeline for practical applications of QML will be reduced significantly,” said Yianni Gamvros, Head of Product and Business Development at QC Ware. “What our algorithms team has achieved for the quantum computing industry is equivalent to a quantum hardware manufacturer introducing a chip that is 10 to 100 times faster than their previous offering. This exciting development will require business analysts to update their quad charts and innovation scouts to adjust their technology timelines.”
Apart from the Forge Data Loaders, the latest release of Forge includes tools for GPU acceleration, which allows algorithms testing to be completed in seconds versus hours, and turnkey algorithms implementations on a choice of simulators and quantum hardware. Simulations are executed on CPUs and Nvidia GPUs on AWS. Quantum hardware integrations include D-Wave Systems, and IonQ and Rigetti architectures through Amazon Braket.
QC Ware Announces Breakthrough in Quantum Machine Learning Algorithms
