Will Quantum Computing Define The Future Of AI?

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Google, this week, has launched a new version of their TensorFlow framework — TensorFlow Quantum (TFQ), which is an open-source library for prototyping quantum machine learning models.  Quantum computers aren’t mainstream yet; however, when they do arrive, they will need algorithms. So, TFQ will bridge that gap and will make it possible for developers/users to create hybrid AI algorithms combining both traditional and quantum computing techniques. TFQ, a smart amalgamation of TensorFlow and Cinq, will allow users to build deep learning models to run on a future quantum computer with minimal lines of Python. According to the Google AI blog post, TFQ has been designed to provide the necessary tools to bring in the techniques of quantum computing and machine learning research communities together in order to build and control natural and artificial quantum systems. e.g. Noisy Intermediate Scale Quantum (NISQ) processors with ~50 – 100 qubits. The purpose of quantum com
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Picture of Sejuti Das
Sejuti Das
Sejuti currently works as Associate Editor at Analytics India Magazine (AIM). Reach out at sejuti.das@analyticsindiamag.com
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