The Rise Of Scalable AI SoCs For The IoT Device Edge


The landscape of computing is undergoing a profound transformation, with Artificial Intelligence (AI) at its forefront. This shift is particularly evident at the device edge, where traditional System-on-Chip (SoCs) implementations are being reimagined to effectively support demanding AI and machine learning (ML) workloads. This evolution necessitates the development of a new class of AI-capa... » read more

How Grinn And Synaptics Are Accelerating Edge AI Adoption And Innovation


From smart cities to industrial automation, organizations are rethinking how and where data is processed. The answer, increasingly, is at the Edge—where devices can analyze information in real time without sending it to the cloud. This approach improves responsiveness, enhances security, and reduces reliance on network connectivity. Recognizing this shift, Grinn Global and Synaptics have p... » read more

Artificial Intelligence Of Things (AIoT) Guide


For organizations exploring connected technologies, the conversation around the Internet of Things (IoT) has shifted. They are looking to make devices smarter, responsive and capable of operating with greater insight. The Artificial Intelligence of Things (AIoT) combines the sensor-driven, networked structure of IoT with the decision-making power of artificial intelligence (AI) at the edge t... » read more

Edge AI: Enabling Smart IoT Applications


As industries race to unlock the next wave of innovation, edge AI is emerging as a game-changer—bringing intelligent, real-time data processing directly to the device level across industries. ‘Edge AI: Enabling Smart IoT Applications’ is your in-depth guide to the transformative potential of artificial intelligence at the edge. This insightful eBook explores 15 powerful use cases that ... » read more

RRAM: Transforming Memory Solutions For AI-driven IoT Devices And Embedded Systems


Artificial Intelligence (AI) and Machine Learning (ML) applications are driving increased demand for high-performance, low-power memory solutions across consumer, medical, and industrial markets. These applications require efficient, Non-Volatile Memory (NVM) to process, store, and retain large volumes of data, as well as support frequent Firmware Over-The-Air (FOTA) updates. In the consumer... » read more

Report: The AI Efficiency Boom


Artificial Intelligence (AI) is undergoing a fundamental transformation. While early AI models were large, compute-heavy, and dependent on cloud processing, a new wave of efficiency-driven innovations is moving AI inference—the generation of model results—to the edge. Smaller models, improved memory and compute performance, and the need for privacy, low latency, and energy efficiency are dr... » read more

The Complete Guide To Intelligent Edge Technology


The rise of edge technology is transforming how data is processed and decisions are made, right where data is generated. Unlike traditional cloud computing, intelligent edge computing pushes processing closer to the source, enabling faster responses and improved efficiency. The global edge AI market reflects this shift, which was valued at $20.78 billion in 2024. By 2030, it's projected to gro... » read more

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

Next Level Inductive Sensing For New Metallic, Waterproof And Robust HMI Touch Designs


The need for advanced and improved human machine interfaces (HMIs) is increasing due to increasing digitalization trends including Industry 4.0, the Internet of Things (IoT), the Artificial Intelligence of Things (AIoT), and more. At the same time, product designers use various HMI touch technologies to improve and differentiate their designs from competitors. Liquid tolerance and sleek metalli... » read more

Energy-Aware DL: The Interplay Between NN Efficiency And Hardware Constraints (Imperial College London, Cambridge)


A new technical paper titled "Energy-Aware Deep Learning on Resource-Constrained Hardware" was published by researchers at Imperial College London and University of Cambridge. Abstract "The use of deep learning (DL) on Internet of Things (IoT) and mobile devices offers numerous advantages over cloud-based processing. However, such devices face substantial energy constraints to prolong batte... » read more

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