AI and Hardware Integration
AI and hardware are deeply intertwined, with hardware providing the essential computational power and infrastructure for AI algorithms to function effectively, and AI, in turn, influencing hardware design for greater efficiency. 1 Here's a breakdown of how they are integrated: 1. Specialized Hardware for AI Workloads: GPUs (Graphics Processing Units): Originally designed for rendering graphics, GPUs are excellent at parallel processing – performing many calculations simultaneously. 2 This makes them highly efficient for the massive matrix multiplications and computations required in training and running deep learning models (a subset of AI). 3 NVIDIA is a prominent manufacturer of GPUs specifically optimized for AI. 4 TPUs (Tensor Processing Units): Developed by Google, TPUs are Application-Specific Integrated Circuits (ASICs) designed specifically for machine learning workloads, particularly those involving TensorFlow. 5 They are optimized for high-throughput, low-precis...