AI Hardware & Chips

The silicon wars powering the AI revolution.

Industry Overview

AI hardware represents the physical infrastructure making modern AI possible. From NVIDIA's datacenter GPUs to custom ASICs from Google and startups like Cerebras, this category covers the silicon wars determining who controls the AI stack.

Key Players

  • GPU Giants: NVIDIA (H100/H200, Blackwell, GB300 Grace Blackwell Ultra), AMD (MI300X), Intel (Gaudi 3, Arc Pro B70)
  • Cloud Custom Silicon: Google (TPU v6), AWS (Trainium 2), Microsoft (Maia)
  • Startups: Cerebras (wafer-scale CS-3), Groq (LPU, NVIDIA acquired for $20B), SambaNova
  • Foundries: TSMC (2nm mass production), Samsung, Intel Foundry Services
  • Edge Silicon: Apple (M5 Pro/Max Fusion Architecture), Qualcomm (Dragonwing IQ-10)

Current Trends (2026)

  • Custom ASIC Boom: 44.6% shipment growth projected vs 16.1% for GPUs
  • Training vs Inference Split: Specialized inference chips (Groq, Cerebras) gaining ground
  • Memory Bottleneck: HBM4 supply shortage threatening chip production
  • Deskside AI Supercomputers: NVIDIA DGX Station GB300 puts 748 GB coherent memory and 20 petaFLOPS on a desktop
  • Edge AI Renaissance: Apple's M5 Max delivers 614 GB/s bandwidth for on-device LLM inference

Why It Matters

AI is compute-constrained. The companies controlling chip production, supply chains, and architectures control the pace of AI advancement. NVIDIA's near-monopoly makes them one of the world's most valuable companies — while Apple's Fusion Architecture pushes serious AI inference to the edge, and the GB300 DGX Station now makes trillion-parameter models viable at deskside scale.

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