The artificial intelligence revolution rides on the backs of silicon chips. Training complex AI models requires vast amounts of computational power best delivered by graphics processing units (GPUs) and customized tensor processing units (TPUs).

Established Suppliers: NVIDIA and AMD

GPU pioneers NVIDIA and AMD enable most AI workloads today. Both companies are investing heavily in data center chips purpose-built for AI with advanced architectures. Their GPU sales now rely heavily on demand from AI research labs as well as hyperscale cloud providers renting out processing.

Cloud Platforms Rush to Enable AI

Speaking of clouds, Amazon, Microsoft and Google operate profitable cloud divisions focused on machine learning. Companies large and small can tap into on-demand AI computing resources without the overhead of owning hardware. Cloud unit growth has accelerated thanks to surging AI workloads.

Hungry Startups Seek Funding

Dozens of promising hardware startups also chase the AI boom, designing innovative chips optimized for speed, efficiency and cost. Many pursue funding or acquisition from tech titans to scale up production. Those reaching sufficient mass production may one day go public.

Growth Forecasts Look Sunny

Total AI chip sales are expected to balloon in the years ahead. Market research firm Omdia projects global revenue ballooning from $7.7 billion in 2022 to over $70 billion by 2027 based on insatiable AI demand. Cloud, data center, automotive and mobile applications should all contribute.

Could Progress Slow?

Of course, expert AI predictions often miss the mark. Technical bottlenecks may arise slowing progress in deep learning and related compute needs. New algorithms could also reduce hardware requirements. And if an "AI winter" cooldown hits, chipmakers relying on red-hot growth could find Wall Street turning its back.

For now though, the investment outlook appears bright for established and emerging companies proving critical tools in AI's upward ascent.