Ai-Hardware

Edge AI: Intelligence at the Edge Edge AI brings intelligence closer to the data source. Instead of sending every image, signal, or sensor reading to a distant data center, the device itself can run the AI model. This on-device processing helps in areas with spotty connectivity or strict privacy needs. Users see faster responses, and organizations can keep sensitive data on-site. The result is a more capable, reliable system that works even when the network isn’t perfect. ...

Hardware Accelerators: GPUs, TPUs, and Beyond Hardware accelerators unlock speed for AI, graphics, and data tasks. They come in several forms, from general GPUs to purpose-built chips. This guide explains how GPUs, TPUs, and other accelerators fit into modern systems, and how to choose the right one for your workload. GPUs are designed for parallel work. They hold thousands of small cores and offer high memory bandwidth. They shine in training large neural networks, running complex simulations, and accelerating data pipelines. In many setups, a CPU handles control while one or more GPUs do the heavy lifting. Software libraries and drivers help map tasks to the hardware, making it easier to use parallel compute without manual tuning. ...