As organizations continue to struggle to maximize storage utilization and optimize analyzing massive amounts of data, Microsoft is upping its focus on the “high promise of quantum technology,” Daniel Stocker, program manager, Azure Quantum technology, told VentureBeat.
With those data sizes growing and complexity increasing, Azure Quantum built a QIO solution for Azure Storage that’s designed to keep the load on storage clusters uniform while reducing the amount of data that needs to move.
Azure Quantum has been supporting the Azure storage team this year with a quantum-inspired optimization solution. Stocker said, “quantum-inspired” refers to running quantum algorithms on classical systems while developers prepare to be ready for when “hardware is available at scale. We’re not there yet,” he said.
Moving data intelligently
The quantum solution has helped Azure storage team increase capacity, efficiency, and predictability, which helps customers get high-quality service from Azure Storage. “We optimize every move we make, and we make them intelligently,” Stocker said.
Stocker said Azure offerings are available for both quantum-inspired and quantum hardware systems on a pay-as-you-go model. Developers can use Python or Microsoft Q#, Microsoft’s open-source language for developing quantum algorithms. Python is the language of choice for developing quantum algorithms, while Q#, Stocker, said “will future proof Azure Storage long-term. “
Microsoft points to three customers that it says has seen significant results from Azure Quantum.
- Trimble uses Azure Quantum to find the most efficient routes for a fleet of vehicles, ensuring fewer trucks run empty and maximizing their operating load for each trip.
- OTI Lumionics is accelerating materials design with quantum-inspired optimization solutions that simulate organic materials used in OLED displays for the design of next generation consumer electronics.
- Ford partnered with Azure Quantum to build a QIO-based traffic optimization solution that significantly reduced both traffic congestionand driver travel time by delivering globally optimized routing to thousands of drivers simultaneously. Preliminary studies show more than a 70 percent decrease in congestion, as well as an 8 percent reduction of average travel time.
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