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Amazon is ramping up efforts to develop its own artificial intelligence (AI) chips in a bid to reduce its dependence on market leader Nvidia. Through its chip design unit, Annapurna Labs, Amazon aims to create more cost-efficient AI infrastructure for its cloud computing division, Amazon Web Services (AWS), while providing customers with an alternative to Nvidia’s dominance.
Annapurna Labs, which Amazon acquired in 2015 for $350 million, has been at the forefront of this initiative. Next month, Amazon is set to unveil “Trainium 2,” an advanced AI chip designed for training large-scale machine learning models. Already in use by companies such as Anthropic, Databricks, and Deutsche Telekom, Trainium 2 is expected to increase performance significantly over its predecessor.
AWS executives see the push for in-house chips as critical to optimizing data center efficiency and lowering costs for both Amazon and its cloud customers. According to Dave Brown, AWS’s Vice President of Compute and Networking Services, AWS remains committed to supporting Nvidia hardware but believes offering a competitive alternative fosters a healthier market. Amazon’s Inferentia chip, another product from Annapurna Labs, is already helping customers save up to 40% on AI processing costs.
Amazon’s AI spending continues to grow, with over $75 billion projected in 2024—largely for technology infrastructure. This expansion aligns with similar initiatives by cloud giants like Microsoft and Google, who are also investing heavily in custom AI chips to meet growing demand for machine learning capabilities.
Industry analysts note that Amazon’s vertical integration strategy reflects a broader trend among tech companies aiming to gain more control over hardware and reduce dependency on suppliers. While AWS chips currently account for a small portion of the market, they provide important competition to Nvidia’s near-monopoly in AI processing hardware.
Although Amazon has yet to match Nvidia in market share or benchmark its chips against Nvidia’s, experts believe the company’s AI chip innovation and cost benefits could drive broader adoption among cloud customers, challenging Nvidia’s lead in the future.
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