Multimodal AI For IoT Devices Requires A New Class Of MCU


The rise of AI-driven IoT devices is pushing the limits of today’s microcontroller unit (MCU) landscape. While AI-powered perception applications—such as voice, facial recognition, object detection, and gesture control—are becoming essential in everything from smart home devices to industrial automation, the hardware available to support them is not keeping pace. The challenge? The broad ... » read more

AI Native: What Does It Mean For Embedded Processing?


Artificial intelligence (AI) continues transforming how users interact with technology. AI-powered chatbots like ChatGPT, along with advancements in data analytics and mobile technology, have contributed to high expectations among tech users. Consumers want and expect faster, more personalized, and smarter experiences — whether they're controlling a smart home device or speaking to a chatbot ... » read more

AI For The Edge: Why Open-Weight Models Matter


The rapid advancements in AI have brought powerful large language models (LLMs) to the forefront. However, most high-performing models are massive, compute-heavy, and require cloud-based inference, making them impractical for edge computing. The recent release of DeepSeek-R1 is an early, but unlikely to be the only, example of how open-weight AI models, combined with efficient distillation t... » read more

Advancing AI At The IoT Edge


In a highly connected world, there is a need for more intelligent and secure computation locally and preferably on the very devices that capture data, whether it be raw or compressed video, images, or voice. End markets continue to expect compute costs to trend down, at a time when computation demands are increasing, as is evident from recently popularized AI paradigms such as large language mo... » read more