Infleqtion, a global leader in quantum information technologies, has unveiled its groundbreaking Contextual Machine Learning (CML) platform at GTC 2025. This innovative AI approach enables machine learning models to process information over extended time periods and from multiple sources simultaneously, enhancing pattern recognition, predictive accuracy, and real-time decision-making across defense, autonomous systems, and next-generation computing.
By implementing CML on NVIDIA A100 GPUs using the NVIDIA CUDA-Q platform, Infleqtion has significantly advanced AI’s ability to interpret and act on complex data streams. This enhancement improves situational awareness and decision-making in critical applications while providing a bridge between today’s AI capabilities and future quantum-powered machine learning systems.
“There is a symbiotic relationship between AI supercomputing and quantum computing,” said Sam Stanwyck, Group Product Manager for Quantum Computing at NVIDIA. “Infleqtion’s work demonstrates how NVIDIA’s CUDA-Q platform is bringing accelerated computing to quantum workflows, and how these workflows are finding application reaching beyond quantum computing.”
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The introduction of CML builds on Infleqtion’s previous successes at the intersection of GPU and QPU hardware, including its recent breakthrough in quantum materials design using CUDA-Q to accelerate next-generation material discovery. Now, the company is applying these advancements to AI, bringing quantum-inspired machine learning to practical applications in sectors such as defense, energy, and autonomous technology.
Traditional AI models, including transformers, often struggle to track patterns over time, making it difficult to analyze streaming data, anticipate future events, or synthesize insights from diverse data sources. Infleqtion’s CML approach, inspired by the quantum mechanical principle of contextuality, enhances AI’s ability to process information over extended timeframes and across different data types, leading to improved adaptability, efficiency, and accuracy.
“AI is processing more data in real-time than ever before, from tracking multiple data sources to making split-second decisions in dynamic environments,” said Pranav Gokhale, General Manager of Computing at Infleqtion. “CML helps AI analyze larger sets of information over longer-context timeframes, improving its ability to detect patterns and adapt to changing conditions. By optimizing this approach using accelerated computing, we’re building the foundation for future AI solutions powered by quantum computing.”
The real-world potential of CML is already being tested through key defense initiatives. Infleqtion recently secured a contract with the U.S. Navy for the QuIRC project, which applies CML-powered AI to enhance real-time RF signal processing. This technology aims to improve situational awareness, security, and operational efficiency in both conventional RF systems and next-generation Quantum RF sensors. Additionally, Infleqtion won first place among 133 competitors in the U.S. Army’s xTechScalable AI competition for its SAPIENT platform, a multi-sensor fusion system designed to enhance navigation and intelligence capabilities. By leveraging CML, SAPIENT can process large sensor data streams with compact models, enabling scalable deployment to edge GPUs powered by NVIDIA Jetson™.
With these advancements, Infleqtion is positioning itself at the forefront of AI and quantum computing convergence, driving the next era of intelligent, high-performance computing solutions.