Favorite 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

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Shared by AWS Machine Learning December 13, 2024

Favorite EBSCOlearning offers corporate learning and educational and career development products and services for businesses, educational institutions, and workforce development organizations. As a division of EBSCO Information Services, EBSCOlearning is committed to enhancing professional development and educational skills. In this post, we illustrate how EBSCOlearning partnered with AWS Generative AI

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Shared by AWS Machine Learning December 12, 2024

Favorite This post was co-written with Varun Kumar from Tealium Retrieval Augmented Generation (RAG) pipelines are popular for generating domain-specific outputs based on external data that’s fed in as part of the context. However, there are challenges with evaluating and improving such systems. Two open-source libraries, Ragas (a library for

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Shared by AWS Machine Learning December 12, 2024

Favorite Amazon Aurora PostgreSQL-Compatible Edition is a fully managed, PostgreSQL-compatible, ACID-aligned relational database engine that combines the speed, reliability, and manageability of Amazon Aurora with the simplicity and cost-effectiveness of open source databases. Aurora PostgreSQL-Compatible is a drop-in replacement for PostgreSQL and makes it simple and cost-effective to set up,

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Shared by AWS Machine Learning December 12, 2024

Favorite Earlier this year, we published the first in a series of posts about how AWS is transforming our seller and customer journeys using generative AI. In addition to planning considerations when building an AI application from the ground up, it focused on our Account Summaries use case, which allows

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Shared by AWS Machine Learning December 12, 2024

Favorite Amazon Q Business is a generative AI-powered assistant that enhances employee productivity by solving problems, generating content, and providing insights across enterprise data sources. Beyond searching indexed third-party services, employees need access to dynamic, near real-time data such as stock prices, vacation balances, and location tracking, which is made

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Shared by AWS Machine Learning December 11, 2024

Favorite In this series, we share two approaches to gain insights on multimodal data like text, images, and charts. In Part 1, we presented an “embed first, infer later” solution that uses the Amazon Titan Multimodal Embeddings foundation model (FM) to convert individual slides from a slide deck into embeddings.

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Shared by AWS Machine Learning December 11, 2024

Favorite Today, we are excited to announce that Pixtral 12B (pixtral-12b-2409), a state-of-the-art vision language model (VLM) from Mistral AI that excels in both text-only and multimodal tasks, is available for customers through Amazon SageMaker JumpStart. You can try this model with SageMaker JumpStart, a machine learning (ML) hub that

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Shared by AWS Machine Learning December 11, 2024

Favorite With access to a wide range of generative AI foundation models (FM) and the ability to build and train their own machine learning (ML) models in Amazon SageMaker, users want a seamless and secure way to experiment with and select the models that deliver the most value for their business. In

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Shared by AWS Machine Learning December 10, 2024

Favorite Today, we are excited to announce that Mistral-NeMo-Base-2407 and Mistral-NeMo-Instruct-2407—twelve billion parameter large language models from Mistral AI that excel at text generation—are available for customers through Amazon SageMaker JumpStart. You can try these models with SageMaker JumpStart, a machine learning (ML) hub that provides access to algorithms and models that can

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Shared by AWS Machine Learning December 7, 2024