AI Navigator: IDE for AI Applications

infoAdditional Details

Features

Navigating through the simple development of AI applications

AI Navigator provides navigation through the development of AI applications via a GUI and supports the implementation of AI applications to run on Renesas devices through the shortest steps.

This tool also provides guidance on downloading and installing toolchains for use in the development of AI applications. Accordingly, you can easily construct a development environment for AI applications by installing this plugin into e² studio.

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Providing a variety of AI applications and AI models

You can import a variety of AI applications from AI Application Zoo provided by Renesas.

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Shortening the periods for developing applications

The AI application also contain converted AI models which are executable on the target devices, so you can easily try AI applications on an evaluation board.

The executable AI models have been released as open source. Accordingly, you can use them with your own applications and thus shorten the periods for the development of AI models. 

Providing a transfer learning feature for the AI models

In combination with the transfer learning tool, AI Navigator provides a transfer learning feature for AI models in the AI applications with the use of desired datasets.

RZ/V AI transfer learning tool (TLT): https://renesas-rz.github.io/rzv_ai_sdk/latest/howto_retrain.html (GitHub)

Shortening the design processes and learning times for AI models

You can tune the AI models in the AI applications which have already been designed and learned to suit your purposes, thus shortening the design processes and learning times for AI models.

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Converting the AI models into executable files that are optimized for Renesas devices

In combination with the AI model conversion tools provided by Renesas, a desired AI model can be converted into an executable format that takes advantage of the hardware accelerator on the target device.

The AI models converted into executable files that are optimized for Renesas devices achieve more lightweight model sizes and faster performance on inference.