The e-AI is solution to enable the Artificial Intelligence(hereafter AI) technology to embedded systems.
AI consists of “Training” and “Inference”.
Renesas‘ e-AI solution enables the use of AI by running only “inference” on MCUs and MPUs.
Also refer the “What is Renesas’ e-AI Solution?

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learning vs interference

Advantage of e-AI

The biggest advantage of e-AI is “real-time processing”
e-AI can judge or response without delay of network, therefore it can get the result of inference faster than cloud case.
e-AI can be used where continuous input data is judged one after another with AI by using this real-time performance.

Renesas will contribute to the realization of an environmentally friendly smart society that supports safer and healthier lifestyles through innovations from endpoint intelligence.

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Cloud Endpoint

Correspondence between AI application examples and MCUs/MPUs

There are many AI application examples, and the requirements of memory size / performance are different. Refer to following figure for choosing which MCU/MPU is good for your AI application.

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Correspondence between AI application examples and MCUs/MPUs

Refer to the actual application example by videos or partner solutions.

e-AI development environment

Renesas provides the e-AI development environment to realize AI implementation easier for MCU or AI accelerator.
When user inputs the trained AI model into this tool, then the tool converts to a program that runs on the MCU or AI accelerator without any additional operations.

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e-AI Tools

Downloads of e-AI development environment

Download e-AI development environment from these pages.

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e-AI tool for Microcomputer

e-AI development environment for microcomputer

This tool supports many kinds of Renesas’ microcomputers. The tool can convert from trained model of “PyTorch”, “Keras”, “Tensorflow”, or 8-bit quantized model of “TensorFlow Lite” and import it easily to e2 studio that is Renesas' integrated development environment. These kind of Renesas products are suitable to be used for relatively small-scale AI for endpoints.

[New]
Released e-AI Translator V2.2.0. (Mar. 2022.)
Addition of new function “CMSIS_INT8” for high-speed inference operation of ”TensorFlow Lite” 8-bit quantized model. (Support RA, RX families)
Released CMSIS for RX library V1.0.0, additionally. (Mar. 2022.)
This library is required to use the new function “CMSIS_INT8” for RX family

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e-AI tool for AI acceelerator (RZ/V, DRP-AI)

e-AI development environment for AI accelerator

This tool supports RZ/V series equipped with the AI accelerator "DRP-AI".
This tool can convert from ONNX format that trained by framework such as “PyTorch” to DRP-AI object code.
These Renesas products are suitable to be used for relatively mid-scale AI for endpoints or edge.

e-AI supported products

Each development environments are supported following products

Supported Products by e-AI Translator

Supported Products by e-AI Translator
RA Family ecosystem partner
RZ/A Series ecosystem partner
RE Family ecosystem partner
RL78 Family ecosystem partner
RX Family ecosystem partner
Renesas Synergy™ Platform ecosystem partner

Supported Products by DRP-AI Translator

Supported Products by DRP-AI Translator
RZ/V series ecosystem partner

Our experiment by Renesas Naka Fab

A demonstration experiment on equipment abnormality detection and predictive maintenance by e-AI was conducted (2015) at the semiconductor front-end factory -"Renesas Naka factory (Renesas Semiconductor Manufacturing Co., Ltd.)"- in Hitachinaka City, Ibaraki Prefecture. New added value, such as abnormality detection and predictive maintenance, can be realized without making major remodeling to existing facilities, while utilizing the existing facilities. In addition, e-AI has greatly improved detection precision with regard to facility abnormalities that previously could only be properly judged by a skilled technician or operator. We have received inquiries from more than 40 customers from Japan and overseas, and started discussions with more than 10 AI-related partners for concretization of business. This example convinced customers that e-AI could contribute to their business and could solve social problems. At the Naka factory, preparations are now under-way for practical use of e-AI for abnormality detection and predictive maintenance.

Plug-ins for e² studio for connecting AI and embedded systems are available.

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Renesas NAKA Fab e-AI PoC

Documentation

Title Type Date
Flyer
PDF642 KB日本語
White Paper

Videos

RE Solution: Digits Recognition

Character recognition by AI requires not only large-capacity ROM/RAM but also high-speed computing performance. In addition, low power consumption is also required for digits recognition of water, electricity, and gas meters. Satisfying these needs, the RE01 1500KB is ideal for AI-based digits recognition, which is expected in smart meters and factory automation. In this demo, a camera captures digits that imitate a rotary analog meter and recognizes these digits, including intermediate states.

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