How Amazon Is Making Custom Chips To Catch Up In Generative A.I. Race

()

Introduction (00:00:00)

Amazon has a chip lab in Austin, Texas designing custom microchips for data centers and AI applications.
The custom chips are aimed at competing with Intel and Nvidia and allow Amazon to save costs and enhance performance.
Amazon's CEO Adam Selipsky recognizes the demand for chips in generative AI and believes Amazon is well-positioned to supply the capacity needed by customers.
Amazon Web Services (AWS) is the world’s largest cloud computing provider, with significant profits funding its custom silicon projects and developer tools.
AWS's profit and growth rates have declined, and Amazon hopes to leverage custom chips and AI to regain momentum and compete with Microsoft and Google.

Amazon's subsidiary Annapurna Labs, acquired in 2015, assists in custom chip design with facilities in Austin, Texas, Silicon Valley, Canada, and Israel.
AWS started producing custom silicon in 2013, with the Nitro hardware, and released ARM-based server chips (Graviton) in 2018.
AWS has developed AI-focused chips: Trainium for training machine learning models and Inferentia for low-latency machine learning inference.
Nvidia currently leads in AI model training hardware, while companies like Apple and Google have also invested in custom silicon.
Microsoft, compared to Amazon and Google, is behind in the custom chip market, reportedly developing an AI chip named Athena with AMD.

AWS invested in AI infrastructure and services long before the recent generative AI surge, with innovations like recommendation engines and Amazon Alexa.
Amazon's new large language models (LLMs) include Titan and a cloud service called Bedrock to streamline generative AI applications.
Competitors Microsoft and Google rapidly gained attention with AI initiatives, prompting Amazon to focus on accelerating conversations and deployments in generative AI.
AWS emphasizes providing various state-of-the-art models from multiple providers intending to cater to different customer needs.

AWS's AI products, like AWS HealthScribe and CodeWhisperer, are used by many customers and provide significant advantages in efficiency and task completion.
Amazon has a multi-faceted AI strategy through their machine learning hub, SageMaker, which supports customers’ AI endeavors across different domains.
AWS has announced a $100 million generative AI innovation center to assist customers in understanding and applying generative AI in their business contexts.
Customers considering Amazon, Google, and Microsoft must choose the best fit for their generative AI requirements, with Amazon offering a comprehensive approach.