XMOS software development kit for AIoT

The kit equips developers with standardised tools and resources that they need to create devices that absorb contextual data from their environment, infer meaning from that data, and translate the results into action. It includes:

• AIoT tools: scripts, tools and libraries to convert TensorFlowLite for Microcontroller models into a format that targets accelerated operations on the xcore.ai platform
• FreeRTOS: libraries to support FreeRTOS operation on xcore.ai, providing a familiar, standard industry programming environment to work in
• Examples: examples showing a variety of operations based on bare-metal and FreeRTOS operation, including smart microphone sensing
• Documentation: getting started guides, example builds and execution walkthroughs, as well as access to XMOS’ open-source libraries of interfaces & signal processing algorithms

These tools will enable developers to rapidly deploy custom or off-the-shelf AI models using a standard framework alongside all of the control, communications, signal and I/O processing required to create a complete and secure application solution.

“Our AIoT SDK enables developers to create intelligent endpoint-AI solutions for a huge variety of applications,” said Mark Lippett, CEO of XMOS. “The flexibility of the xcore.ai architecture enables our customers to create truly differentiated solutions using standard embedded software techniques like TensorFlowLite for MCU in a fraction of the time required using traditional hardware approaches.”

"It's great to see XMOS's latest contributions to low-energy embedded machine learning and I'm pleased that TensorFlow Micro has been able to integrate,” commented Pete Warden, Technical Lead for the TensorFlow Mobile team at Google. “This combination will enable a lot of exciting applications in the future."

Early access to the XMOS AIoT SDK will be available on the GitHub open source platform, designed to be used in conjunction with the xcore.ai Explorer Kit, which is available on limited release via xmos.ai.

Future releases will include other xcore.ai hardware platforms, targeting specific use case applications. This includes a smart home platform – a small form-factor reference design with additional WiFi capability, designed to demonstrate the capabilities of voice at the edge of networks and due to be released in early 2021.