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The patent highlights a groundbreaking approach to enhance the scalability and performance of quantum machine learning (QML) on near-term quantum computing platforms, including quantum simulators. This solution transforms high-dimensional classical input data into an enhanced feature space in quantum format. The feature space transformation ensures efficient mapping and preparation for quantum state loading, paving the way for improved quantum data processing and analysis. The optimal representation method for classical data on quantum systems minimizes the need for additional qubits for higher-dimensional data, handles large feature sets and high volumes of data, and ensures efficient convergence during quantum machine learning (QML) model training. QML leverages its ability to process high-dimensional, complex data, delivering solutions beyond the reach of classical high performance computing hardware. Srikumar Ramanathan, chief solutions officer, Mphasis, said, 'Quantum Machine Learning (QML) is emerging as a transformative paradigm, enabling academia and industry to solve real-world AI challenges with unprecedented efficiency. This technology and the associated patent stand as a testament to our commitment to innovation and the advancement of next-generation technologies.' Mphasis is a leading Information Technology (IT) solutions provider specialising in cloud and cognitive services. The company's consolidated net profit jumped 1.06% to Rs 427.81 crore in Q3 FY25 as compared with Rs 423.33 crore in Q2 FY25. Net sales marginally increased to Rs 3,561.34 crore in Q3 FY25, up 0.71%, as compared with to Rs 3,536.15 crore in Q2 FY25 The counter declined 2.25% to Rs 2,120.65 on the BSE. Powered by Capital Market - Live News |