Texas Instruments introduced two new microcontroller families, the MSPM0G5187 and the AM13Ex, each integrating its TinyEngine neural processing unit. The TinyEngine NPU delivers deep‑learning inference with up to 90‑fold lower latency and more than 120‑fold lower energy consumption compared with conventional processors, enabling real‑time AI on the edge.
The MSPM0G5187 is built on an Arm Cortex‑M0+ core and targets low‑cost, low‑power applications such as wearables, home appliances, and other consumer devices. It is priced at under $1 for 1,000‑unit orders, positioning it as a cost‑effective entry point for AI‑enabled products. The AM13Ex pairs an Arm Cortex‑M33 core with the TinyEngine NPU and a sophisticated real‑time control architecture, making it suitable for motor‑control, robotics, and industrial automation where both AI inference and deterministic timing are required.
Production of the MSPM0G5187 is already underway, while the AM13Ex is in pre‑production with additional variants slated for release by the end of 2026. TI’s software ecosystem, including CCStudio and CCStudio Edge AI Studio, supports rapid development and deployment of AI models on both families, reducing time‑to‑market for customers.
The launch expands TI’s embedded‑processing portfolio and reinforces its leadership in analog and embedded solutions that serve long product lifecycles. By embedding AI directly into its microcontrollers, TI addresses a growing demand for on‑device intelligence in robotics, industrial automation, and consumer electronics, where latency, power, and privacy are critical.
"TI invented the digital signal processor almost 50 years ago, laying the groundwork for today’s edge AI processing," said Amichai Ron, senior vice president of embedded processing and DLP products. "By enabling AI across our software, tools, devices and ecosystem, we are making edge AI accessible and easy to use for every customer and every application.",
The new microcontrollers come at a time when TI is pursuing a broader AI strategy that includes collaborations with NVIDIA for robotics and automotive applications, the acquisition of Silicon Labs for $7.5 billion to strengthen its embedded wireless portfolio, and a $60 billion investment in domestic manufacturing in Texas and Utah. These moves position TI to capture a larger share of the rapidly expanding edge‑AI market while maintaining its reputation for reliability and long‑term product support.
The introduction of the TinyEngine‑powered MCUs signals TI’s continued focus on delivering cost‑effective, reliable solutions that can be integrated into a wide range of devices, potentially driving new sales and reinforcing its leadership in the analog and embedded‑processing space.
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