Mar 2, 2025
Chipping Away: AI x Hardware
Introduction
Software has been the favored child for Silicon Valley for decades; Hardware relegated to a niche. But AI is rewriting the playbook. Compute demand is soaring, and AI infrastructure spending is set to cross $500 billion in the next five years. Hardware is back in the spotlight
Market Map
GPUs are fueling AI’s rise, but supply constraints and high costs are becoming bottlenecks. Training a large model like GPT-3 can cost $1.4 million per session, making efficiency the next frontier. The race is now on to build AI hardware that doesn’t break the bank, as models scale.
Investment
Investment is pouring in. Tech giants Intel and AMD are pushing new architectures like the MI300 series, while top VCs like Sequoia Capital are backing startups like Cerebras and SambaNova. The market is shifting beyond general-purpose GPUs to specialized chips built for AI. Cerebras’s wafer-scale engines handle high-performance computing (HPC) for health and finance, while Groq’s LPUs process 500 tokens per second for smaller models.
Startups
Startups are creating AI accelerators, photonic systems, and neuromorphic chips. Innovation is fast, but whether they can truly deliver higher performance at lower costs is the question.
Shifting
The market is shifting beyond general-purpose GPUs to specialized chips built for AI. Cerebras’s wafer-scale engines handle high-performance computing (HPC) for health and finance, while Groq’s LPUs process 500 tokens per second for smaller models.
Summary
Hardware relegated to a niche. But AI is rewriting the playbook. Compute demand is soaring, and AI infrastructure spending is set to cross $500 billion in the next five years. Hardware is back in the spotlight