According to a report by Electronic Enthusiasts Network (Author: Li Wanwan), in the wave of global digital transformation, edge AI has become the core driving force for the intelligent upgrade of various industries. According to market research data, the global edge AI market size reached $20.78 billion in 2024, and is expected to further grow to $25 billion in 2025. From industrial manufacturing to smart homes, from autonomous driving to energy management, edge AI is reshaping the operational logic of traditional industries with advantages such as low latency, high privacy, and high efficiency. However, challenges such as technological fragmentation, scene adaptation difficulties, and the balance between power consumption and performance are also restricting the large-scale implementation of edge AI. How to break through bottlenecks through chip technology innovation has become a focus of industry attention. In this context, Electronic Enthusiasts Network recently interviewed Texas Instruments (TI), a global semiconductor giant, to conduct an in-depth dialogue on its technological breakthroughs in edge AI chips, industry implementation practices, and ecological layout. As a leader in the field of analog and embedded processing, TI is redefining the boundaries of edge intelligence with its strategy of “hardware-software synergy + deep scene cultivation”.
Core Technologies Lead Innovation, Product Highlights Abound
TI stated that the company always stands at the forefront of technology, closely monitoring the development trends of edge intelligence technology, and continuously innovating and optimizing products to accurately meet the diverse market demands for performance, power consumption, and security. TI’s embedded product portfolio widely covers microcontrollers, microprocessors, wireless connectivity, and millimeter-wave radar-based devices, fully supporting the development of applications based on neural networks, endowing systems with intelligent functions. In 2024, TI launched the C2000™ MCU TMS320F28P55X series, marking another milestone in its edge AI field. This series integrates an edge artificial intelligence (AI) neural processing unit (NPU) for the first time in the C2000™ series, providing 24 high-precision PWM channels and up to 39 ADC channels, specifically designed to meet the growing intelligent demands in real-time control systems in industrial and automotive fields. TI introduced that the introduction of the integrated AI hardware accelerator offloads the execution of neural network models from the main CPU, achieving a significant reduction in latency time by 5 to 10 times compared to software. This innovation has been successfully applied in arc detection for solar and energy storage systems, achieving additional fault detection functionality while maintaining the original functions of a single chip, effectively reducing system costs and shrinking system size; in the field of motor drive fault detection, its fault detection accuracy reaches 99%, demonstrating excellent performance. TI’s AM62x and AM6xA series processors adopt a system-on-chip (SoC) architecture, integrating hardware accelerators and low-power Arm® Cortex® microprocessors, providing a perfect balance of performance, speed, and energy efficiency for edge AI applications. This series offers diverse performance and power consumption options for different industrial and automotive application scenarios. For example, in autonomous vehicles, the AM6xA processor integrates an image signal processor (ISP), an AI accelerator with up to 32 TOPS (trillion operations per second), a quad-core 64-bit Arm® Cortex® A53 microprocessor, a single-core Arm® Cortex®-R5F, and video encoding/decoding capabilities, enabling real-time processing and control of images captured by cameras, fully meeting the high standards of data transmission and communication required by automotive systems. TI not only continues to innovate in product development but also builds a complete edge AI application toolchain, including the free software development tool Edge AI Studio, aimed at accelerating the entire process of edge AI development for TI processors and microcontrollers, from data collection, model training to compilation and deployment, significantly lowering development barriers. In addition, TI provides a wealth of hardware development board resources to help customers quickly validate designs. In terms of after-sales support, TI has established a comprehensive after-sales service system to provide timely and professional technical support and services to ensure product stability and reliability.
Wide Application Directions, Deepening Ecological Cooperation
TI stated that the company is committed to integrating edge AI into everyday applications to enhance product usability, safety, and efficiency. Through close collaboration with customers and third parties, TI deeply understands market trends and design needs, exploring the impact of edge AI technology on system performance. TI continues to invest in an expandable product portfolio, including microcontrollers, microprocessors, wireless connectivity, and radar-based devices integrated with edge AI functions, helping designers create smarter, more efficient, and more competitive products. In the perception field, TI supports products with visual AI capabilities that can interpret and respond to sensor data, achieving functions such as object detection, depth and motion estimation, and gesture detection. For example, in defect detection scenarios, AI perception technology can quickly identify and track defective components and materials, significantly improving product quality and production efficiency. The C2000™ MCU products based on edge AI also perform excellently in real-time monitoring and control fields, capable of conducting arc and motor bearing fault detection, recognizing patterns, and detecting anomalies to achieve predictive maintenance. For instance, in solar-powered systems, edge AI technology is used for real-time arc detection to prevent fires or downtime, and the application of the TMS320F28P55x MCU has improved the accuracy and timeliness of arc detection, reducing false positives and missed detections, enhancing system safety and reliability. In the audio field, TI’s audio-based edge AI technology can recognize speech in real-time, identify music, detect anomalies, and improve audio quality. For example, keyword wake-up and command detection functions have been widely applied in electronic locks, appliances, and even automotive fields, providing users with a more convenient and intelligent interaction experience. TI also shared specific cases of solving customers’ “urgent pain points.” In photovoltaic inverters, designers need fast and predictable system fault detection. TI’s C2000™ MCU TMS320F28P55x series chips, with their integrated neural processing unit (NPU) and highly optimized algorithms, achieve the fastest detection of arc signals in 0.5 seconds, with a fault detection accuracy rate of over 99%. This innovative solution not only extends the lifespan of equipment and reduces maintenance costs but also plays an important role in ensuring electrical safety. For example, the Huashengchang AFD-80 arc signal detector and several SOLAX products with optional arc protection all use this series of TI chips to achieve rapid response and high accuracy in arc detection.
In Conclusion
Texas Instruments (TI), as a leading company in the global semiconductor industry, has achieved significant results in edge AI chip technology innovation and industry implementation practices, thanks to its deep technical accumulation, extensive product portfolio, and comprehensive ecological support. In the future, TI will continue to strengthen its R&D investment in embedded processors, sensors, and low-power designs, launching more innovative edge intelligence products to contribute to the global intelligent transformation.
Disclaimer：This article is original from Electronic Enthusiasts Network, please indicate the source above when reprinting. For group communication, please add WeChat elecfans999, for submission and interview requests, please send an email to [email protected].
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