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Amazon has been developing its own AI chips to cut costs, which has also helped increase Amazon Web Services (AWS) profitability. However, the e-commerce giant is struggling to develop AI chips that can rival Nvidia’s standard chips. Project migration issues, compatibility gaps, and low usage are some of the concerns slowing the adoption of Amazon’s AI chips. The situation has also put heavy revenues at stake that Amazon generates from its cloud business. The challenges Amazon faces were identified through confidential documents and sources familiar with the matter, as reported by Business Insider. Amazon’s In-House AI Chips Encounter Stifled Adoption Trainium and Inferentia are the top-of-the-line Amazon-designed chips that debuted near the end of last year. The publication reported that last year, Trainium’s adoption rate among AWS’s customers was merely 0.5% compared to that of Nvidia’s graphic processing units. Also read: Amazon Profit Exceeds Wall Street Expectations as AWS’s Generative AI Works Wonders Amazon made the assessment to measure the usage percentage of different AI chips through its AWS services in April 2024, according to the report. At the same time, the adoption rate for Inferentia was slightly higher, with 2.7%. Inferentia is a special chip designed for inference, an AI task that usually refers to the computing process for AI model usage by end consumers. The report mentioned an internal document saying that; “Early attempts from customers have exposed friction points and stifled adoption.” The above statement refers to the challenges that large cloud customers have faced when transitioning to Amazon’s custom chips. Nvidia’s CUDA platform is considered more appealing to customers, and the report identifies it as a key reason. Amazon’s Custom AI Chip Development Under Internal Review AWS, the world’s largest cloud service provider, is now developing its home-brewed computer chips to facilitate operations. Amazon, at times,…

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Filed under: News - @ May 28, 2024 6:24 pm