Hardware for artificial intelligence

Hardware specially designed and optimized for artificial intelligence Specialized computer hardware is often used to execute artificial intelligence (AI) programs faster, and with less energy, such as Lisp machines, neuromorphic engineering, event cameras, and physical neural networks. Since 2017, several consumer grade central processing units (CPUs) and systems on a chip (SoCs) have on-die neural processing units (NPUs). As of 2023, the market for AI hardware is dominated by graphics processing units (GPUs), such as those by Nvidia and AMD, newer domain-specific accelerators such as Google's Tensor Processing Units (TPUs), and various NPUs found in consumer hardware. Scope For the purposes of this article, AI hardware refers to computing components and systems specifically designed or optimized to accelerate artificial-intelligence workloads such as machine-learning training or inference. This includes general-purpose accelerators used for AI (for example, GPUs) and domain-specific accelerators (for example, TPUs, NPUs, and other AI application-specific integrated circuits (ASICs)). Event-based cameras are sometimes discussed in the context of neuromorphic computing, but they are