Amazon’s latest $11 billion AI data center in Indiana signals a profound shift in the foundational infrastructure powering the artificial intelligence revolution, an investment of unprecedented scale that underscores the intense competition for AI compute. In less than a year, Amazon transformed vast Indiana cornfields into its largest AI data center yet, an astonishing feat of rapid deployment and engineering. This colossal facility is not merely a testament to Amazon’s logistical prowess but a strategic declaration in the high-stakes race for AI dominance, particularly through its commitment to homegrown chips and key partnerships. 


CNBC’s MacKenzie Sigalos provided an exclusive inside look at this monumental project, interviewing key figures like Matt Garman, CEO of Amazon Web Services (AWS), and Mike Krieger, Chief Product Officer at Anthropic. Their discussions, featured on ‘Squawk Box’, illuminated Amazon’s aggressive strategy to build out the physical backbone for advanced AI models, highlighting both the technological ambition and the burgeoning societal challenges that accompany such immense undertakings. 

 

At the heart of Amazon’s strategy is a bold bet on proprietary AI chips, a move designed to reduce reliance on third-party silicon and optimize performance for specific AI workloads. This Indiana compound, once fully completed, will host 30 buildings, seven of which are already operational. Crucially, it was built exclusively for Anthropic, a prominent rival to OpenAI, which is now running its Claude models on half a million of Amazon’s in-house AI chips, dubbed Trainium 2. This direct integration and co-development signify Amazon’s “build-it-and-they-will-come” approach, creating tailored infrastructure that attracts leading AI developers and locks them into the AWS ecosystem. 

The speed of execution is remarkable. Matt Garman emphasized this velocity, stating, “This is not some future project… this is running and training their models today.” This immediate operational capability provides Amazon with a significant competitive edge, allowing it to translate capital expenditure directly into active, revenue-generating AI workloads. The relentless pace of expansion is also evident in Garman’s candid admission: “We’re rapidly adding new capacity all over the place, and so I don’t know that we’ll be done ever. We’re going to continue to build as our customers need more capacity.” 


This massive complex will draw more than two gigawatts of electricity, enough to power over 1.6 million homes. 


The ability to rapidly deploy such complex infrastructure is a critical differentiator in the AI arms race. Mike Krieger from Anthropic lauded Amazon’s execution, noting, “These deals all sound great on paper, but they only materialize when they’re actually racked and loaded and usable by the customer, and Amazon is incredible at that.” This sentiment underscores the practical challenges of scaling AI compute and Amazon’s unique capability to deliver tangible resources at speed, leveraging decades of experience in building large-scale physical infrastructure like warehouses. 

 
Amazon’s decision to power this facility with its own Trainium 2 chips is a direct challenge to the current dominance of Nvidia in the AI hardware market. Sigalos highlighted this, noting it is “the largest cluster of non-Nvidia chips anywhere in the world.” This strategic move aims to diversify the AI chip supply chain and potentially offer more cost-effective and specialized solutions to AWS customers, fostering an environment where innovation isn’t bottlenecked by a single hardware provider. It signals a new infrastructure race where hyperscalers are not just competing on cloud services but on the underlying, custom-designed hardware that powers the next generation of AI. 

However, the rapid expansion of these energy-intensive data centers is not without its challenges. Local communities, like New Carlisle in Indiana, are beginning to voice concerns over the environmental impact and potential strains on local resources. As Becky Quick pointed out, there’s a growing “not in my backyard” sentiment, with residents worried about rising prices and the sheer scale of these industrial installations. The local power utility, for instance, anticipates peak demand to double once the full campus is online, raising questions about energy supply and sustainability. Despite these concerns, as Sigalos noted, for many communities, the arrival of these tech giants feels like an “inevitable reality” they must adapt to, driven by a mix of local incentives and robust grid power, including nuclear and gas options. 

Amazon’s $11 billion investment in Indiana is more than just a data center; it’s a blueprint for the future of AI infrastructure. By combining proprietary chip development, strategic partnerships with leading AI model developers, and an unparalleled capacity for rapid, large-scale construction, Amazon is solidifying its position as a foundational layer in the evolving AI landscape. This aggressive build-out reflects a long-term commitment to meeting the insatiable demand for AI compute, a demand that, as AWS CEO Matt Garman suggests, shows no signs of abating. 

 