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 this re:Invent different? Swami Sivasubramanian: The …
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Organizations are continuously seeking ways to use their proprietary knowledge and domain expertise to gain a competitive edge. With the advent of foundation models (FMs) and their remarkable natural language processing capabilities, a new opportunity has emerged to unlock the value of their data assets. As organizations strive to deliver personalized experiences to customers using …
Multi-tenant RAG with Amazon Bedrock Knowledge Bases Read More »
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 the ability to visualize those workflows …
How Amazon trains sequential ensemble models at scale with Amazon SageMaker Pipelines Read More »
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 own jobs and files without interfering …
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 driving strategy development, enhancing execution, and …
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 to find precise information quickly. In …
How Twitch used agentic workflow with RAG on Amazon Bedrock to supercharge ad sales Read More »
In Part 1 of this series, we introduced the newly launched ModelTrainer class on the Amazon SageMaker Python SDK and its benefits, and showed you how to fine-tune a Meta Llama 3.1 8B model on a custom dataset. In this post, we look at the enhancements to the ModelBuilder class, which lets you seamlessly deploy …
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 and configurations, allowing for greater flexibility …
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 let business users tailor solutions to …
Amazon Q Apps supports customization and governance of generative AI-powered apps Read More »
