TLDR

Amazon’s new AI chief Peter DeSantis is betting on a low-cost strategy to compete in the AI race.
Amazon plans to use its in-house Trainium and Inferentia chips to build AI models cheaper than rivals.
Its Nova model has lagged competitors in benchmarks, but Nova 2 is said to be more competitive.
Amazon’s stock has dropped around 8% since January over investor concerns about $200 billion in capital spending.
The head of Amazon’s AGI Lab, David Luan, announced his departure on Tuesday.

Amazon has a new plan for AI: beat the competition on price, not just performance.

Amazon.com, Inc., AMZN

Peter DeSantis, Amazon’s newly appointed AI chief, is pushing a strategy built around cost. His core argument is simple — AI is too expensive, and Amazon can change that.

“AI has a cost problem,” DeSantis said. “If we ultimately want AI to transform everything, the costs have to be different.”

DeSantis took over AI responsibilities in December after former chief AI scientist Rohit Prasad departed. He’s a 28-year Amazon veteran who helped build AWS and its chip operations.

Amazon’s stock is down roughly 8% since January. Investors are uneasy about the company’s plan to spend $200 billion on capital expenditures this year — mostly on AI infrastructure — while analysts project Amazon will burn around $9 billion in cash in Q1 alone.

The pressure on DeSantis is real.

Amazon’s Chip Strategy

The plan centers on Amazon’s homegrown chips: Trainium for training models and Inferentia for running them. Amazon claims these chips are up to 50% cheaper than comparable offerings from rivals.

“If we can build our models on our chips, we can build them at a fraction of the cost of a pure-play AI model provider,” DeSantis said.

That cost advantage is already attracting some customers. Boston-based drug discovery firm Nimbus Therapeutics found Amazon’s Nova model returned results as accurate as Anthropic’s Claude at one-tenth the price.

Amazon also offers Nova Forge, which lets enterprise customers build customized AI models rather than paying for premium products like ChatGPT or Gemini.

Amazon’s flagship Nova model has lagged behind rivals in independent benchmarks. The company says Nova 2 performs better, though it hasn’t released third-party benchmark data to back that up.

Amazon was also slow off the mark on generative AI. When ChatGPT launched in late 2022, Amazon scrambled to respond, holding emergency meetings to form a strategy.

“Amazon was slower to realize the importance of generative AI,” said Lloyd Walmsley, senior analyst at Mizuho.

Talent and Competition

Amazon faces a talent challenge too. Its base pay for software engineers and research scientists trails Meta, OpenAI, Apple, and Anthropic, according to Levels.fyi. The company also recently cut around 30,000 white-collar workers across two rounds of layoffs.

On Tuesday, David Luan, head of Amazon’s AGI Lab, announced he was leaving. The lab will continue operating under DeSantis.

DeSantis says he’s not chasing splashy model releases like OpenAI and Anthropic. He called frequent launches “kind of how you stay in the news” but said they don’t necessarily move the needle for customers.

Amazon says more than 70% of Alexa queries are now handled by variants of its Nova model. Over 300 million people used its Rufus shopping chatbot in 2025.

DeSantis acknowledged investor concerns about spending but pushed back, drawing parallels to skepticism Amazon faced when it first invested in physical retail and then AWS data centers.

Amazon’s AGI Lab, which focuses on AI agents, continues to report to DeSantis following Luan’s exit.

The post Amazon (AMZN) Stock: New AI Chief Plans to Use In-House Chips to Cut Costs appeared first on CoinCentral.

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Filed under: News - @ February 27, 2026 1:22 pm