Renesas Blog

Introduction to RZ/V AI applications that can be easily implemented without AI training

Introduces Renesas' efforts to optimize performance, circuit size and power consumption of accelerators for deep neural networks used in AI processing in SoCs for AD and ADAS in the early design stage.

Among several types of DNN simulators we provide for R-Car SoC, we will focus on Accurate Simulator, which reproduces operations equivalent to those on actual devices, and explain how to apply it to network analysis and accuracy improvement.

The e-AI Translator v3.0.0 has been released. This release supports the 3D shape function and RNN function used in signal processing and regression models.

We are introducing the history and future of the software suite for the 32-bit MCU RX to enable development with low-code/no-code. The 9th blog introduces the latest provisioning method for IoT devices.

An overview of key use cases for RA4T1 and RA6T3 motor control MCUs that enable both high-efficiency and miniaturization of motor applications.

Using the RL78/G23 microcontroller and the RL78 Fast Prototyping Board, we will create a mole-catching game to showcase how smoothly the development process can go.

MPU Guide app allows you to find out the best matching product from our RZ microprocessors product family and access our RZ MPU community from your smartphone.

For the first time in the entry-level microcontrollers of the RX family, a CAN controller has been integrated. This enables the reduction of power consumption and cost in CAN bus applications

The advanced features of the ZSSC3241 SSC enable using the bridge sensor as a thermometer for temperature compensation.