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AMZN Jun 2024 230.000 put

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  • Yahoo Finance Video

    Why Amazon's AWS is so focused on chips

    Amazon's AWS (AMZN) made a series of AI-related announcements at its annual re:Invent conference, including a new AI chatbot called Q and an expansion of their relationship with Nvidia (NVDA). The company also announced a series of new chips, including the AWS Graviton4 and AWS Trainium2. As AWS CEO Adam Selipsky tells Yahoo Finance's Allie Garfinkle in the video above, the chips are a part of the company's push to improve price performance, especially given that customer needs are growing. "These workloads, thees things that customers want to do aren't going to be economically feasible unless we keep on dramatically improving price performance," Selipsky says. For more expert insight and the latest market action, click here to watch this full episode of Yahoo Finance Live.

  • Business Wire

    AWS Announces More Model Choice and Powerful New Capabilities in Amazon Bedrock to Securely Build and Scale Generative AI Applications

    LAS VEGAS, November 29, 2023--At AWS re:Invent, Amazon Web Services, Inc. (AWS), an Amazon.com, Inc. company (NASDAQ: AMZN), today announced Amazon Bedrock innovations that expand model choice and deliver powerful capabilities, making it easier for customers to build and scale generative artificial intelligence (AI) applications customized to their businesses. Amazon Bedrock is a fully managed service that offers easy access to a choice of industry-leading large language models and other foundat

  • Business Wire

    AWS Announces Five New Amazon SageMaker Capabilities for Scaling with Models

    LAS VEGAS, November 29, 2023--At AWS re:Invent, Amazon Web Services, Inc. (AWS), an Amazon.com, Inc. company (NASDAQ: AMZN), today announced five new capabilities within Amazon SageMaker to help accelerate building, training, and deployment of large language models and other foundation models. As models continue to transform customer experiences across industries, SageMaker is making it easier and faster for organizations to build, train, and deploy machine learning (ML) models that power a vari