Events & News

System-on-Modules (SoMs) are compact embedded computing platforms that integrate the processor, memory, storage, and I/O into a single ready-to-use module. They reduce design complexity, accelerate time-to-market, and save development costs in industrial and embedded applications. However, selecting the right SoM is more than a hardware choice—it directly affects your product’s development, functionality, manufacturability, and long-term

Artificial Intelligence (AI) models are computational tools designed to simulate aspects of human intelligence. Once trained on large volumes of data, these algorithms evolve into models capable of recognizing patterns, making decisions, and generating insights. The more data they learn from, the more accurate they become. From machine learning and deep learning to generative AI

The Internet of Things (IoT) represents a groundbreaking shift in technology, where everyday objects are interconnected to collect, share, and analyze data, transforming the way we live and work. Edge AI, a subset of artificial intelligence, processes data locally on devices rather than relying solely on centralized cloud servers. This combination of IoT and Edge

The tech world is abuzz with the rise of ARM processors. Known for their energy efficiency and powerful performance, ARM processors are transforming everything from smartphones to servers. In this guide, we’ll explore the benefits and applications of ARM processors and take a closer look at Geniatech, a leader in ARM technology innovation. Get ready

Imagine a world where your devices do more than perform tasks—they make smart decisions instantly. This is the reality of Edge AI, enabled by the convergence of IoT devices, the advancement of edge computing, and recent leaps in AI technology. This blog will introduce you to the concept of Edge AI, explaining how it works

The AI hardware market in 2025 encompasses a diverse range of hardware solutions tailored for different performance needs and deployment environments. From massive cloud-based training to compact embedded inference, AI hardware plays a pivotal role in enabling intelligent applications across industries. This article explores the three main categories of AI hardware —GPUs, FPGAs, and ASICs—highlighting

As embedded processors targeting different market segments, the Synaptics VS680 and Qualcomm Snapdragon 888 represent distinct approaches to modern computing. This analysis evaluates their architectures, benchmarks, and real-world performance across key metrics. Key Specifications Comparison Feature Synaptics VS680 Snapdragon 888 Process Node 12nm FinFET 5nm Samsung (5LPE) CPU Quad Cortex-A73 + Quad Cortex-A53 1x Cortex-X1