We implement a quantum AI pipeline under Node-red front end control. Quantum AI features a parallel calculation capability which can expedite the AI training process for many industrial applications. However, its setup process is inherent complicated. Generally, It not only requires conversion to/from traditional data to quantum data, but also the design of complex quantum circuit. We wrap the whole procesures into a kubeflow pipeline, and show the control flow can be run on a Node-red GUI front end. The test case runs a mnist data set CNN classification application and the accuracy can reach a %96 high with short one half training time compared to traditional AI. We are seting up the PR and will have a local repository for all the code and readme file illustrating the complete processes.
We implement a quantum AI pipeline under Node-red front end control. Quantum AI features a parallel calculation capability which can expedite the AI training process for many industrial applications. However, its setup process is inherent complicated. Generally, It not only requires conversion to/from traditional data to quantum data, but also the design of complex quantum circuit. We wrap the whole procesures into a kubeflow pipeline, and show the control flow can be run on a Node-red GUI front end. The test case runs a mnist data set CNN classification application and the accuracy can reach a %96 high with short one half training time compared to traditional AI. We are seting up the PR and will have a local repository for all the code and readme file illustrating the complete processes.