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Quantum Computing Inc. makes NeuraWave deployment-ready for edge AI

15th article in the last 90 days, one of 109 articles referencing Quantum Computing. Previous coverage: Wellcome Leap’s Q4Bio Challenge Names Phase III Winners (Apr 2026).

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Quantum Computing Inc. (QCi) said its NeuraWave photonic reservoir computing platform reached deployment-ready status after first debuting at SC25. The company tied the change to demand for real-time AI inference and advanced signal processing at the edge.

QCi said NeuraWave uses hybrid photonic-digital computing, positioning it as an alternative to power-hungry digital processor approaches. The company also said the platform targets low latency and reduced power use while supporting applications for time-series prediction, anomaly detection, and edge intelligence.

In describing its design, QCi said NeuraWave delivers real-time AI inference with ultra-low latency and reduced power. It said the architecture was made for scalable, hardware-accelerated inference aimed at edge and embedded deployment.

QCi said NeuraWave uses the form factor of a standard server PCIe plug-in card and that units were manufactured and now available for customer orders. Dr. Yong Meng Sua, chief technology officer of QCi, said, “This marks an important step forward for photonic computing, bringing it out of the laboratory and into the hands of users that require real-time and energy-efficient AI inference.” Prajnesh Kumar, Quantum Technology Lead at QCi, added, “With the form factor of a standard server PCIe plug-in card, NeuraWave brings photonic computing to AI at the edge. By processing data with light instead of electrons, we're creating a fundamentally different approach to real-time analysis, one that has the potential to unlock capabilities beyond what traditional electronic chips can achieve.”

QCi also said the announcement reinforced its broader strategy and referenced its previously announced 2025 technology roadmap, with forward-looking statements including risks around NeuraWave’s ability to support a wide range of applications and achieve performance and processing speed expectations compared with electronic systems.

Press release, provided by Cision on behalf of Quantum Computing. Read the original.

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