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  • Author Author: cstanton
  • Date Created: 10 Sep 2019 3:27 PM Date Created
  • Last Updated Last Updated: 28 Jul 2020 3:29 PM
  • Views 2958 views
  • Likes 7 likes
  • Comments 26 comments
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BeagleBone®︎ AI - Technical Specifications

NEW! BeagleBoneRegistered AI

Technical Specifications | Frequently Asked Questions | Comparison Chart | BeagleBoneRegistered Accessories | Getting Started | BeagleBoneRegistered Quiz

 

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What is the BeagleBoneRegistered AI?

BeagleBoneRegistered AI, a new addition to the BeagleBoard.orgRegistered BeagleBoneRegistered family, is a high-end Single Board Computer aimed at developers interested in implementing machine-learning and computer vision with simplicity. BeagleBoneRegistered AI simplify the use of artificial intelligence (AI) in daily application via the TI C66x digital-signal-processor (DSP) cores, two dual-core ARM Cortex-M4 co-processors for real-time control, two dual-core Programmable Real-Time Unit (PRU) subsystems and four Embedded Vision Engines(EVEs) supported through an optimized TIDL machine learning OpenCL API with pre-installed tools. The BeagleBoneRegistered AI also has an additional dual-core PowerVR SGX544 3D GPU and a Vivante GC320 2D graphics accelerator. Focused on everyday automation in industrial, commercial and home applications.

BeagleBoneRegistered AI comes in a similar form-fact as BeagleBoneRegistered Black and compatible with many BeagleBoneRegistered Cape add-on boards make it easy to extend the functionality.

 

 

Processors and RAM

  • Dual 1.5GHz ARMRegistered CortexRegistered-A15 with out-of-order speculative issue 3-way superscalar execution pipeline for the fastest execution of existing 32-bit code
  • 2 C66x Floating-Point VLIW DSP supported by OpenCL
  • 4 Embedded Vision Engines (EVEs) supported by TIDL machine learning library
  • 2x Dual-Core Programmable Real-Time Unit (PRU) subsystems (4 PRUs total) for ultra low-latency control and software generated peripherals
  • Memory: 1GB RAM and 16GB on-board eMMC Flash

 

Connectivity

  • Gigabit Ethernet
  • 802.11ac 2.4/5GHz WiFi via the AzureWave AW-CM256SM
  • Bluetooth 4.2 and Bluetooth Low Energy via the AzureWave AW-CM256SM
  • USB Type-C for power and superspeed dual-role controller
  • USB type-A host

 

Audio and Video

  • IVA-HD subsystem with support for 4K @ 15fps H.264 encode/decode and other codecs @ 1080p60
  • VivanteRegistered GC320 2D graphics accelerator
  • Dual-Core PowerVRRegistered SGX544Tm 3D GPU

 

Additional Features and Connectivity

  • 2x46 expansion headers compatible with many BeagleBoneRegistered cape add-on boards
    • 16-bit LCD interfaces
    • 4+ UARTs
    • 2x I2C ports
    • 2x SPI ports
    • Lots of PRU I/O pins
  • Zero-download out of box software environment
  • Self-hosted web IDE with local compilers, libraries and examples
  • Debian distribution (initially version 9.9, 10.0 available)
  • Linux kernel support (initially 4.14, with 4.19 and 5.2 available)
  • Connectivity via USB gadget (network/serial), WiFi access point and station, Ethernet, and serial debug header

 

Click through to our online stores to Buy NowBuy Now

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Top Comments

  • jomoenginer
    jomoenginer over 2 years ago +2

    I had seen this from the BeagleBoard email and really wanted to be excited about it, but after looking deeper I could only muster a half-hearted Yawn.  The use of a TI AM5729 Dual Core ARMCortex-A15 processor…

  • clem57
    clem57 over 2 years ago in reply to coolkedar +2

    They have the normal capes that should work. Of course you can design your own or just breadboard what you wish.

    Yes coolkedar you can...

  • jomoenginer
    jomoenginer over 2 years ago in reply to coolkedar +2

    Like the other BBs, just ensure not to connect the sensor directly to a GPIO pin and be mindful that the GPIOs are 3.3v rather than 5v.  Derek Molloy in his books suggests to use a transistor or something…

Parents
  • coolkedar
    coolkedar over 2 years ago

    Can I attach various sensors like accelerometer , temperature sensors to it?

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  • jomoenginer
    jomoenginer over 2 years ago in reply to coolkedar

    Like the other BBs, just ensure not to connect the sensor directly to a GPIO pin and be mindful that the GPIOs are 3.3v rather than 5v.  Derek Molloy in his books suggests to use a transistor or something similar on the GPIO to driver external circuits.

     

     

    Here's a note from the BB AI reference doc.

    https://github.com/beagleboard/beaglebone-ai/wiki/System-Reference-Manual

     

    See section 7.1

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  • jomoenginer
    jomoenginer over 2 years ago in reply to coolkedar

    Like the other BBs, just ensure not to connect the sensor directly to a GPIO pin and be mindful that the GPIOs are 3.3v rather than 5v.  Derek Molloy in his books suggests to use a transistor or something similar on the GPIO to driver external circuits.

     

     

    Here's a note from the BB AI reference doc.

    https://github.com/beagleboard/beaglebone-ai/wiki/System-Reference-Manual

     

    See section 7.1

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