Two MCU Families and Software Ecosystem Enable Edge AI Everywhere
The Overview: MCUs Enable Edge AI in Any Device
In a pair of new microcontroller (MCU) families, Texas Instruments (TI) sets out on its mission to usher in edge AI across its full embedded processing portfolio. The MSPM0G5187 and AM13Ex MCUs integrate TI’s TinyEngine neural processing unit (NPU), a dedicated hardware accelerator for MCUs that optimizes deep-learning inference operations to reduce latency and improve energy efficiency when processing at the edge.
Who Needs It & Why: Imparting Smarts to Cost-Effective Applications
Consumers want their everyday electronic devices to be smarter. That goes for everything from fitness wearables to home appliances and electrical systems. However, many engineers believe they can’t afford AI capabilities in their applications that demand cost-effectiveness, low power, and/or customized coding.
With TI’s new MSPM0G5187 Arm Cortex-M0+ MSPM0 MCU, embedded designers can bring edge AI to a wide range of simpler, smaller, and more cost-effective applications.
Under the Hood: An NPU that Works in Parallel with the CPU
Through local computation, the TinyEngine NPU executes computations required by neural networks in parallel to the primary CPU running application code. Compared to similar MCUs without an accelerator, this hardware acceleration accomplishes multiple goals, minimizing the flash-memory footprint. And, for each AI inference, it lowers latency by up to 90X and slashes energy usage by more than 120X.
Thanks to its high efficiency, the MSPM0G5187 MCU helps resource-constrained devices, including portable, battery-powered products, to process AI workloads. The device reduces system and operating costs by offering an affordable alternative to other MCU or processor architectures.
Both MCU families are supported by TI’s CCStudio Edge AI Studio, a free development environment that simplifies model selection, training, and deployment across TI’s embedded processing portfolio. This edge AI toolchain gives engineers full flexibility to run AI models on TI MCUs through either hardware or software implementations.
More than 60 models and application examples are available in the tool to help developers start deploying edge AI in any device, with additional tasks and models planned in the future.
Production quantities of the MSPM0G5187 MCU are available for purchase now; the AM13E23019 MCU is available in preproduction quantities. Additional package and memory variants will be released by the end of 2026.
Learn more about edge computing
About the Author
David Maliniak
Executive Editor, Microwaves & RF
I am Executive Editor of Microwaves & RF, an all-digital publication that broadly covers all aspects of wireless communications. More particularly, we're keeping a close eye on technologies in the consumer-oriented 5G, 6G, IoT, M2M, and V2X markets, in which much of the wireless market's growth will occur in this decade and beyond. I work with a great team of editors to provide engineers, developers, and technical managers with interesting and useful articles and videos on a regular basis. Check out our free newsletters to see the latest content.
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About me:
In his long career in the B2B electronics-industry media, David Maliniak has held editorial roles as both generalist and specialist. As Components Editor and, later, as Editor in Chief of EE Product News, David gained breadth of experience in covering the industry at large. In serving as EDA/Test and Measurement Technology Editor at Electronic Design, he developed deep insight into those complex areas of technology. Most recently, David worked in technical marketing communications at Teledyne LeCroy, leaving to rejoin the EOEM B2B publishing world in January 2020. David earned a B.A. in journalism at New York University.