"Valuations further differentiate the periods: dotcom tech stocks often traded at 150 to 180 times trailing earnings, while current AI frontrunners average around 40 times. Some AI hardware purchasers have reported improved return on ivested capital (ROIC), but results vary across the industry. This solid groundwork distinguishes AI from historical bubbles and primes leading companies like Nvidia for substantial expansion."
"The absence of idle GPUs underscores a fundamental shift in how infrastructure is built and used. In the telecom bubble, companies like WorldCom boasted about laying thousands of miles of fiber, but without optics, switches, or actual traffic, it sat dormant. Today, AI data centers absorb every chip produced. Technical papers highlight GPUs "melting" under load, a sign of intense, productive activity."
AI GPUs are being consumed immediately upon shipment, with each unit reserved, deployed, and generating revenue instead of remaining idle. Training workloads create extreme thermal stress, sometimes causing overheating during intensive model runs. Valuations for leading AI companies are notably lower than dotcom-era multiples, and some hardware purchasers report improved ROIC while outcomes vary across firms. Hyperscalers such as Microsoft and Amazon are scaling models for search, advertising, and cloud services, sustaining practical demand. Nvidia holds over 80% market share in AI accelerators and benefits from a zero-inventory dynamic and sustained orders.
Read at 24/7 Wall St.
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