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The element14 ESSENTIALS of artificial intelligence (AI) covers an overview of AI today, spanning a brief history, fundamental concepts, algorithms, the Bayes Theorem, and applications. To extend the knowledge covered in the main module, this supplementary guide discusses the types of related components or development boards used for prototyping or product development.
Components
The Ultra96-V2 updates and refreshes the Ultra96 product that was released in 2018. Like Ultra96, the Ultra96-V2 is an Arm-based, Xilinx Zynq UltraScale+ 
MPSoC development board based on the Linaro 96Boards Consumer Edition (CE) specification. Ultra96-V2 will be available in more countries around the world as it has been designed with a certified radio module from Microchip. Additionally, all components are updated to allow industrial temperature grade options. Additional power control and monitoring will be possible with the included Infineon Pmics.
Like Ultra96, the Ultra96-V2 boots from the provided Delkin 16 GB microSD card. Engineers have options of connecting to Ultra96-V2 through a Webserver using integrated wireless access point capability or to use the provided PetaLinux desktop environment which can be viewed on the integrated Mini DisplayPort video output. Multiple application examples and on-board development options are provided as examples. Ultra96-V2 provides four user controllable LEDs. Engineers may also interact with the board through the 96Boards-compatible low-speed and high-speed expansion connectors by adding peripheral accessories such as those included in the MikroE Click Mezzanine for 96Boards (available as an accessory).
Micron LPDDR4 memory provides 2 GB of RAM in a 512M x 32 configuration. Wireless options include 802.11b/g/n Wi-Fi and Bluetooth 5 Low Energy. The radio module is Agency Certified in over 75 countries. UARTs are accessible on a header as well as through the expansion connector. JTAG is available through a header. The convenient JTAG/UART Pod (available as an accessory) provides both JTAG and UART connections via USB. I2C is available through the expansion connector.
Two Microchip USB3320 USB 2.0 ULPI Transceivers and one Microchip USB5744 4-Port SS/HS USB Controller Hub enable multiple USB connections. Ultra96-V2 provides one upstream (device) and two downstream (host) USB 3.0 connections. A USB 2.0 downstream (host) interface is provided via the high-speed expansion. The integrated power supply generates all on-board voltages from an external 12V supply (available as an accessory).
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Raspberry Pi 4 Model B is the latest product in the popular Raspberry Pi range of computers. It offers ground-breaking increases in processor speed, multimedia performance, memory, and connectivity compared to the prior-generation Raspberry Pi 3 Model B+, while retaining backwards compatibility and similar power consumption. For the end user, Raspberry Pi 4 Model B provides desktop performance comparable to entry-level x86 PC systems. This product's key features include a high-performance 64-bit quad-core processor, dual-display support at resolutions up to 4K via a pair of micro-HDMI ports, hardware video decode at up to 4Kp60, 2GB of RAM, dual-band 2.4/5.0GHz wireless LAN, Bluetooth 5.0, Gigabit Ethernet, USB 3.0, and PoE capability (via a separate PoE HAT add-on). The dual-band wireless LAN and Bluetooth have modular compliance certification, allowing the board to be designed into end products with significantly reduced compliance testing, improving both cost and time to market.
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The BeagleBone
AI is a high-end Single Board Computer aimed at developers interested in implementing machine-learning and computer vision with simplicity. BeagleBone AI includes a dual-core ARM Cortex-A15 running at 1.5 GHz, 16GB on-board eMMC flash, a SuperSpeed USB Type-C interface, Gigabit Ethernet and dual band wireless connectivity. BeagleBone AI simplify the use of artificial intelligence (AI) in daily industrial, commercial and home applications 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 BeagleBone AI also has an additional dual-core PowerVR SGX544 3D GPU and a Vivante GC320 2D graphics accelerator. Packaged similarly to BeagleBone Black and compatible with many BeagleBone Cape add-on boards.
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