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Amazon Bedrock Marketplace now includes NVIDIA models: Introducing NVIDIA Nemotron-4 NIM microservices

AWS Machine Learning - AI

At AWS re:Invent 2024, we are excited to introduce Amazon Bedrock Marketplace. This a revolutionary new capability within Amazon Bedrock that serves as a centralized hub for discovering, testing, and implementing foundation models (FMs). Saurabh Trikande is a Senior Product Manager for Amazon Bedrock and SageMaker Inference.

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Supercharge your auto scaling for generative AI inference – Introducing Container Caching in SageMaker Inference

AWS Machine Learning - AI

Today at AWS re:Invent 2024, we are excited to announce the new Container Caching capability in Amazon SageMaker, which significantly reduces the time required to scale generative AI models for inference. It supports a wide range of popular open source LLMs, making it a popular choice for diverse AI applications.

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Amazon Bedrock Prompt Optimization Drives LLM Applications Innovation for Yuewen Group

AWS Machine Learning - AI

In this blog post, we discuss how Prompt Optimization improves the performance of large language models (LLMs) for intelligent text processing task in Yuewen Group. Evolution from Traditional NLP to LLM in Intelligent Text Processing Yuewen Group leverages AI for intelligent analysis of extensive web novel texts.

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How AWS sales uses Amazon Q Business for customer engagement

AWS Machine Learning - AI

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. Field Advisor serves four primary use cases: AWS-specific knowledge search With Amazon Q Business, weve made internal data sources as well as public AWS content available in Field Advisors index.

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EBSCOlearning scales assessment generation for their online learning content with generative AI

AWS Machine Learning - AI

In this post, we illustrate how EBSCOlearning partnered with AWS Generative AI Innovation Center (GenAIIC) to use the power of generative AI in revolutionizing their learning assessment process. The evaluation process includes three phases: LLM-based guideline evaluation, rule-based checks, and a final evaluation.

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Generate financial industry-specific insights using generative AI and in-context fine-tuning

AWS Machine Learning - AI

In this blog post, we demonstrate prompt engineering techniques to generate accurate and relevant analysis of tabular data using industry-specific language. This is done by providing large language models (LLMs) in-context sample data with features and labels in the prompt.

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Enable Amazon Bedrock cross-Region inference in multi-account environments

AWS Machine Learning - AI

Amazon Bedrock cross-Region inference capability that provides organizations with flexibility to access foundation models (FMs) across AWS Regions while maintaining optimal performance and availability. We provide practical examples for both SCP modifications and AWS Control Tower implementations.