tech
How the Currency of the AI Economy Actually Works
The AI companies racing for dominance are hitting a major bottleneck.
TL;DR
- AI companies are experiencing a shortage of "compute," hindering their rapid growth.
- Compute capacity involves hardware processing power, networking, and storage, primarily using GPUs.
- AI production is costly, requiring not only chips but also high-speed networking, storage, and power infrastructure.
- Taiwan Semiconductor Manufacturing Co. (TSMC) holds a near-monopoly on semiconductor production, creating a bottleneck.
- Data centers are crucial for training and hosting AI models, with companies often buying reserved GPU capacity and bandwidth.
- Large tech firms like Meta, Microsoft, Google, and Amazon pre-order chips years in advance.
- Compute capacity is becoming as strategically important as the AI models themselves in the current race.