Kipu Quantum has released an off-line Digitized Quantum Feature Extraction (DQFE) pipeline that allows quantum-enhanced machine learning models to execute inference operations entirely on classical hardware. The architecture separates the quantum and classical processing loops, restricting quantum processor utilization to an initial, specialized training stage. By eliminating real-time Quantum Processing Unit (QPU) dependencies during active [...] The post Kipu Quantum Launches Hybrid Framework to Enable Offline Inference for Quantum Machine Learning appeared first on Quantum Computing Report
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