Based on the Texas Instruments AM5729, developers have access to the powerful SoC with the ease of BeagleBone-- Black header and mechanical compatibility. BeagleBone-- AI makes it easy to explore how artificial intelligence (AI) can be used in everyday life via the TI C66x digital-signal-processor (DSP) cores and embedded-vision-engine (EVE) cores supported through an optimized TIDL machine learning OpenCL API with pre-installed tools.

Foundation today announces general availability of the newest, fastest, most powerful BeagleBoard.org Built on our proven open source Linux approach, BeagleBone AI fills the gap between small single board computers (SBCs) and more powerful industrial computers. Leveraging the Texas Instruments Sitara AM5729 processor, developers have access to powerful machine learning capabilities with the ease of the BeagleBone Black header and mechanical compatibility. BeagleBone AI makes it easy to explore how artificial intelligence (AI) and machine learning can be used in everyday life. Through BeagleBone AI, developers can take advantage of the TI C66x digital-signal-processor (DSP) cores and embedded-vision-engine (EVE) cores on the Sitara AM5729 processor.

The newly revealed BeagleBone AI is a board aimed at developers interested in experimenting with machine-learning and computer vision. Unveiled this week, the computer houses four dedicated chips originally designed to help self-driving cars "see" the world around them. The board's Texas Instruments (TI) Embedded Vision Engine (EVE) chips offer up to 8x the performance per watt when running calculations for computer-vision models compared to running on an Arm Cortex A15-based CPU. This optimized hardware is accessible to developers via the TI Deep Learning OpenCL (Open Computing Language) API. Foundation say the BeagleBone AI board will be able to automate tasks in industrial, commercial and home settings.

A newly released BeagleBone AI board will help developers who are interested in getting more out of machine learning and computer vision. The computer has four dedicated chips designed to help self-driving cars. BeagleBoard has Texas Instruments (TI) Embedded Vision Engine (EVE) chips that offer up to 8x performance per watt while running calculations for computer vision models. The performance is better as compared to running on an Arm Cortex A15-based CPU. The hardware is accessible to developers using TI Deep learning OpenCL (Open Computer Language) API.