Texas Instruments demonstrates range of micro-controller (MCU) and microprocessors (MPU) at embedded world. These devices cater to various applications in Industrial, Consumer Electronics, Robotics and Vision Analytics based product segments. By design the processors draw very less power, I will cover the steps to measure the power and to evaluate the performance parameters in my upcoming blog post.
Being hands on with one of the recently launched TI's AM62A processor, I can bet this device is something industry would be looking forward to integrating in many of their analytics and edge AI based products. The device comes with hardware accelerators for deep learning and Image processing to integrate RGB raw sensors. This is first device in industry to also support IR sensors like OV2312 - RGB and IR frames are time division multiplexed.
The Yocto build environment based Linux SDK for edge AI provides
- Upstream RT-Linux LTS Kernel 5.10 (will get migrated to version 6.1 shortly) with peripheral drivers, U-Boot bootloader.
- Pre-integrated firmware for hardware accelerated deep learning and camera ISP
- GStreamer plugins and edge AI application stack
The SDK documentation provides simple steps to build, develop and run high performance deep learning applications using a live camera and display. More details on software can be found here
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