Amazon Deepens AI Push as Crypto Miners Pivot to AI Infrastructure
Amazon is ramping up its AI ambitions with the launch of Trainium 3, a new chip aimed at challenging Nvidia’s GPU dominance. Available through Amazon Web Services (AWS), the chip promises up to four times the training speed of its predecessor while maintaining the same energy footprint.
The Trainium 3 chips are at the heart of Amazon’s new “UltraServers,” each capable of running 144 chips simultaneously. This positions Amazon to compete directly with Nvidia and Google in large-scale AI workloads, including language model training and other compute-intensive tasks.
Google’s strong lead in AI model development—reportedly giving it an 87% chance of producing the top model by year-end—has prompted a “code red” at OpenAI, highlighting the intensifying competition.
Scaling AI infrastructure, however, presents challenges. The massive energy and space requirements are difficult for most tech companies to meet alone. That’s where crypto miners are stepping in. With existing large-scale data centers, firms like Core Scientific, CleanSpark, and Bitfarms are repurposing their operations to support AI workloads, effectively becoming utility providers for hyperscale computing.
IREN, a former bitcoin mining company turned neocloud provider, saw its stock soar after securing a $9.7 billion AI cloud deal with Microsoft. Similarly, TeraWulf partnered with Fluidstack on a $9.5 billion AI infrastructure venture backed by Google. These firms already control gigawatts of power capacity and the cooling and grid infrastructure required for AI clusters.
Market performance highlights the risks. Bitcoin has dropped more than 17% over the past 30 days, the CoinDesk 20 index fell 19.3%, and the NASDAQ 100 is down about 1.5% after recovering from a larger drawdown. Analysts warn that the AI infrastructure boom could resemble past tech bubbles. OpenAI, for instance, has committed trillions to infrastructure, much of which depends on continued high demand. Bain & Co. estimates that a slowdown could create an $800 billion funding gap, requiring $2 trillion in combined annual revenue by 2030 to sustain projected AI compute needs.
A slowdown in AI demand could trigger liquidity strains similar to the 2022 crypto crash, with ripple effects across broader risk assets.
For now, crypto miners-turned-AI providers are betting on a new digital gold rush—this time powered by GPUs rather than ASICs.
