Gen AI News Talk
Simplify multimodal generative AI with Amazon Bedrock Data Automation
Developers face significant challenges when using foundation models (FMs) to extract data from unstructured assets. This data extraction process requires carefully identifying models that...
How TUI uses Amazon Bedrock to scale content creation and enhance hotel descriptions in...
TUI Group is one of the world’s leading global tourism services, providing 21 million customers with an unmatched holiday experience in 180 regions. TUI...
Llama 3.3 70B now available in Amazon SageMaker JumpStart
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...
AWS re:Invent 2024 Highlights: Top takeaways from Swami Sivasubramanian to help customers manage generative...
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...
Multi-tenant RAG with Amazon Bedrock Knowledge Bases
Organizations are continuously seeking ways to use their proprietary knowledge and domain expertise to gain a competitive edge. With the advent of foundation models...
Accelerate analysis and discovery of cancer biomarkers with Amazon Bedrock Agents
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...
How Twitch used agentic workflow with RAG on Amazon Bedrock to supercharge ad sales
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...
How Clearwater Analytics is revolutionizing investment management with generative AI and Amazon SageMaker JumpStart
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...
Implementing login node load balancing in SageMaker HyperPod for enhanced multi-user experience
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....
How Amazon trains sequential ensemble models at scale with Amazon SageMaker Pipelines
Amazon SageMaker Pipelines includes features that allow you to streamline and automate machine learning (ML) workflows. This allows scientists and model developers to...
