AI Chip (Detailed)
Specialized semiconductor hardware designed to accelerate AI workloads including training and inference.
Overview
AI chips are specialized processors optimized for the matrix multiplications and parallel computations that dominate neural network workloads. They achieve 10-1000x better performance-per-watt than general-purpose CPUs for AI tasks through dedicated compute units and memory architectures.
Landscape
GPUs: NVIDIA (H100, B200), AMD (MI300X) — dominant for training. Custom ASICs: Google TPU, AWS Trainium/Inferentia — optimized for specific frameworks. Edge AI: Apple Neural Engine, Qualcomm AI Engine — on-device inference. Novel architectures: Cerebras (wafer-scale), Groq (deterministic LPU), SambaNova (dataflow). The AI chip market is projected to exceed $200B by 2028.