Orquestra®: Quantum-Ready Workflows for ML and Optimization
Workflows in Orquestra are particularly well-suited for running and managing complex quantum machine learning (QML) tasks due to their modular and extensible nature. We will demo the process of solving real-world problems with novel hybrid quantum-classical machine learning approaches. We will walk you through our steps, from initial ideation to a final workflow that can run on a quantum computer. This will culminate in real, new results returned from experiments on a quantum computer that significantly pushes state-of-the-art QML with near-term quantum devices. The libraries and algorithms introduced here to tackle real-world ML and optimization problems will be at the core of Orquestra’s quantum AI capabilities in the near future.
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