Amazon Enters AI Arms Race Aiming to Rival Nvidia as Crypto and Risk Asset Fears Mount

Amazon is stepping deeper into the AI arms race with the release of Trainium 3, a chip designed to rival Nvidia’s dominant GPU hardware.

The new chips, available through Amazon Web Services (AWS), promise a fourfold increase in training speed over the previous version, while maintaining the same energy footprint. The move will put the tech giant in competition with Google and Nvidia as the scramble for infrastructure heats up.

Each cluster of Amazon’s new “UltraServers” can run up to 144 Trainium 3 chips, positioning them to handle large-scale language model training and other compute-heavy tasks. The launch is part of Amazon’s broader push to expand its AI infrastructure and reduce dependence on others.

Amazon’s push, coupled with Google’s dominance in the AI model race, where it now has an 87% chance of securing the best one by the end of the year, has reportedly seen OpenAI’s Sam Altman declare a “code red.”

AI and crypto

However, building more AI servers creates a problem that few tech giants can solve on their own: finding enough power and space. That’s where crypto miners, which already have large data centers operational, are stepping in, using some of their hardware to enter the AI arms race and profit off of it.

Amid the arms race and following the 2024 Bitcoin halving, which cut block rewards in half, several large mining firms began repurposing their energy-intensive operations into AI-ready facilities. Companies like Core Scientific, CleanSpark, and Bitfarms are now being viewed less as bitcoin bets and more as utility providers for hyperscalers.

Bitcoin miner-turned-neocloud firm IREN (IREN) has, last month, soared after inking a $9.7 billion AI cloud deal with Microsoft (MSFT). Similarly, TeraWulf (WULF) inked a $9.5 billion AI infrastructure joint venture with Fluidstack, backed by Google.

These firms control gigawatts of power capacity, with existing infrastructure ready for AI clusters that require advanced cooling and stable grid connections.

Bubble risk?

Still, the pivot comes with risks.

Miners are borrowing heavily to retrofit sites for AI workloads, and as investors grow wary of the sheer pace and scale of costs behind the “AI trade,” correlated risk assets (such as tech stocks and crypto) are under pressure.

Bitcoin BTC$92,147.34 is down more than 17% in the past 30 days, while the broader CoinDesk 20 (CD20) index lost 19.3% of its value over the same period. The tech-heavy NASDAQ 100 index is down around 1.5% over the past month, having recently recovered from a more than 7% drawdown in the period.

Analysts have warned that the AI infrastructure boom bears resemblance to past bubbles. OpenAI, for example, has committed to trillions on infrastructure spending, funds for which it still needs to raise.

Much of the capital being committed to the AI arms race is being recycled through the same players, selling AI chips or cloud services. If demand for AI slows, Bain & Co. has predicted a shortfall of up to $800 billion for these companies, which would need $2 trillion in combined annual revenue by 2030 to fund the computing power needed for projected demand.

If demand for AI compute slows, these hybrid operations could face the same liquidity crunch that plagued the crypto sector in 2022. Such a hit would likely affect the wider market, pushing risk assets down heavily.

For now, though, the miners are betting the future of their business on a new kind of gold rush powered by GPUs, not ASICs.