Baidu has released the toolkit for its quantum machine learning platform, Paddle Quantum, which it says will enable developers to build and train quantum neural network models. Built on the Chinese tech giant’s deep learning platform PaddlePaddle, the toolkit also includes quantum computing applications.
Paddle Quantum, currently available on GitHub, comprises a set of quantum machine learning toolkits including a quantum chemistry library and optimisation tools, as well as three quantum applications: quantum machine learning, quantum chemical simulation, and quantum combinatorial optimisation.
Several underlying functions of PaddlePaddle, including matrix multiplications, also enable Paddle Quantum to support quantum circuit models and general quantum computing research, Baidu said in a statement Wednesday.
Touting the platform’s added flexibility, the Chinese tech vendor said Paddle Quantum could run a new implementation of the Quantum Approximate Optimisation Algorithm (QAOA) at half the number of layers in its quantum neural network.
Director of Baidu’s Institute for Quantum Computing, Duan Runyao, said: “Researchers in the quantum field can use the Paddle Quantum to develop quantum artificial intelligence (AI) and deep-learning enthusiasts have a shortcut to learning quantum computing.”
Baidu also introduced seven new tools, offering 27 enhanced features, for PaddlePaddle. These included Paddle.js, a deep learning JapaScript library that would enable developers to use AI within the browser or smart mini programmes in apps such as Wechat. The updates also included Parakeet, a text-to-speech toolkit with various models such as WaveFlow and ClariNet, as well as Paddle X, an integration development tool for data processing.
According to Baidu, PaddlePaddle has been adopted by more than 1.9 million developers, with more than 84,000 businesses using the deep learning platform to create more than 230,000 models. The company said it also worked with several global hardware manufacturers including Intel, Huawei, MediaTek, and Inspur, on the PaddlePaddle ecosystem.
Baidu CTO Wang Haifeng said: “Now is an unprecedented opportunity for the development of PaddlePaddle given the rise of industrial intelligence and the acceleration of AI-powered infrastructure. We will continue to embrace the open-source spirit, drive technological innovation, and partner with developers to advance deep learning and AI technologies and speed up the process of industrial intelligence.”
Alibaba last November also published the core codes of its machine learning platform Alink on GitHub, uploading a rang of algorithm libraries that it said supported batch and stream processing. These were essential to support machine learning tasks such as online product recommendations and smart customer services.
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