TI expands microcontroller portfolio and software ecosystem to enable edge AI in every device
New MCUs with the TinyEngine™ NPU join TI's comprehensive portfolio of AI-enabled hardware, software and tools, allowing engineers to deploy intelligence anywhere
News highlights:
- TI's integrated TinyEngine NPU can run AI models with up to 90 times lower latency and more than 120 times lower energy utilization per inference than similar MCUs without an accelerator.
- New general-purpose and real-time MCUs from TI include the TinyEngine NPU to enable more efficient edge AI in any application, from simple to complex systems.
- With integrated generative AI in TI's CCStudio™ IDE and more than 60 models and application examples in
CCStudio Edge AI Studio , developers can quickly and easily add edge AI to any device.
For more information, see ti.com/edgeAI, ti.com/MSPM0G5187 and ti.com/AM13E23019.
TI's embedded processing portfolio is supported by a comprehensive development ecosystem, including the CCStudio integrated development environment (IDE). Its generative AI features allow engineers to use simple language to accelerate code development, system configuration and debugging through industry-standard agents and models paired with TI data. Altogether, TI is accelerating the adoption of edge AI in any electronic device, from real-time monitoring in wearable health monitors and home circuit breakers to physical AI in humanoid robots. These end-to-end innovations are featured in TI's booth at embedded world 2026,
"TI invented the digital signal processor almost 50 years ago, laying the groundwork for today's edge AI processing," said
"While much of the world has been focused on AI acceleration and NPUs in bigger SoCs, it turns out some of the more interesting and far-reaching applications of AI can be enabled inside smaller chips like microcontrollers," said
Advanced intelligence at your fingertips
Consumers are always looking for everyday technology to be more intelligent, from fitness wearables to home appliances and electrical systems. However, many engineers believe that AI capabilities are exclusive to higher-end applications given high costs, power demands and coding requirements. TI's new MSPM0G5187
With 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:
- Minimizes the flash memory footprint.
- Lowers latency by up to 90 times per AI inference.
- Reduces energy utilization by more than 120 times per AI inference.
Such levels of efficiency allow resource-constrained devices – including portable, battery-powered products – to process AI workloads. At under
To learn more, read the technical article, "How edge AI-accelerated
Real-time control plus AI acceleration for multimotor systems
Motor control applications in appliances, robotics and industrial systems increasingly call for intelligent features such as adaptive control and predictive maintenance, but implementing these capabilities has historically required complex, multi-chip designs. Building on over two decades of motor control leadership through the C2000™ real-time MCU portfolio, TI's new AM13Ex MCUs are the industry's first to integrate a high-performance
This degree of integration enables designers to implement sophisticated motor control and AI features simultaneously without external components, lowering bill-of-materials costs by up to 30%. Key enhancements include:
- The ability to maintain precise real-time control loops for up to four motors while the TinyEngine NPU runs adaptive control algorithms for load sensing and energy optimization.
- An integrated trigonometric math accelerator that performs calculations 10 times faster than coordinate rotation digital computer (CORDIC) implementations, delivering more precise, responsive motor-control performance.
To learn more, read the application brief, "Achieving edge AI-enabled motor control in industrial automation and home appliance designs."
Easily train, optimize and deploy AI models
Both MCU families are supported by TI's
TI at embedded world 2026
At embedded world 2026, in Hall 3A, Booth No. 131, TI will demonstrate how its technologies help engineers develop faster with AI; enhance performance with edge AI; and deploy AI at the edge across factories, buildings and vehicles. Also featured is TI's partner ecosystem, which provides the complete foundation to bring innovative embedded solutions to market faster. See ti.com/ew for more information.
Package, availability and pricing
- Production quantities of the MSPM0G5187 MCU are available for purchase now on TI.com, with the AM13E23019 MCU available in preproduction quantities. Additional package and memory variants will be released by the end of 2026.
- Multiple payment and shipping options are available.
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