Favorite We spoke with Dr. Swami Sivasubramanian, Vice President of Data and AI, shortly after AWS re:Invent 2024 to hear his impressions—and to get insights on how the latest AWS innovations help meet the real-world needs of customers as they build and scale transformative generative AI applications. Q: What made

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Shared by AWS Machine Learning December 17, 2024

Favorite Today, we are excited to announce that the Llama 3.3 70B from Meta is available in Amazon SageMaker JumpStart. Llama 3.3 70B marks an exciting advancement in large language model (LLM) development, offering comparable performance to larger Llama versions with fewer computational resources. In this post, we explore how

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Shared by AWS Machine Learning December 17, 2024

Favorite According to the National Cancer Institute, a cancer biomarker is a “biological molecule found in blood, other body fluids, or tissues that is a sign of a normal or abnormal process, or of a condition or disease such as cancer.” Biomarkers typically differentiate an affected patient from a person without the

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Shared by AWS Machine Learning December 14, 2024

Favorite Twitch, the world’s leading live-streaming platform, has over 105 million average monthly visitors. As part of Amazon, Twitch advertising is handled by the ad sales organization at Amazon. New ad products across diverse markets involve a complex web of announcements, training, and documentation, making it difficult for sales teams

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Shared by AWS Machine Learning December 14, 2024

Favorite This post was written with Darrel Cherry, Dan Siddall, and Rany ElHousieny of Clearwater Analytics. As global trading volumes rise rapidly each year, capital markets firms are facing the need to manage large and diverse datasets to stay ahead. These datasets aren’t just expansive in volume; they’re critical in

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Shared by AWS Machine Learning December 14, 2024

Favorite Amazon SageMaker HyperPod is designed to support large-scale machine learning (ML) operations, providing a robust environment for training foundation models (FMs) over extended periods. Multiple users — such as ML researchers, software engineers, data scientists, and cluster administrators — can work concurrently on the same cluster, each managing their

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Shared by AWS Machine Learning December 14, 2024

Favorite Amazon SageMaker Pipelines includes features that allow you to streamline and automate machine learning (ML) workflows. This allows scientists and model developers to focus on model development and rapid experimentation rather than infrastructure management Pipelines offers the ability to orchestrate complex ML workflows with a simple Python SDK with

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Shared by AWS Machine Learning December 14, 2024

Favorite Amazon Q Business is a generative AI-powered assistant that can answer questions, provide summaries, generate content, and securely complete tasks based on data and information in your enterprise systems. A large portion of that information is found in text narratives stored in various document formats such as PDFs, Word

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Shared by AWS Machine Learning December 13, 2024

Favorite We are excited to announce new features that allow creation of more powerful apps, while giving more governance control using Amazon Q Apps, a capability within Amazon Q Business that allows you to create generative AI-powered apps based on your organization’s data. These features enhance app customization options that

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Shared by AWS Machine Learning December 13, 2024

Favorite Amazon SageMaker has redesigned its Python SDK to provide a unified object-oriented interface that makes it straightforward to interact with SageMaker services. The new SDK is designed with a tiered user experience in mind, where the new lower-level SDK (SageMaker Core) provides access to full breadth of SageMaker features

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Shared by AWS Machine Learning December 13, 2024