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Amazon Bedrock Knowledge Bases now supports Amazon OpenSearch Service Managed Cluster as vector store

AWS Machine Learning Blog

Amazon Bedrock Knowledge Bases has extended its vector store options by enabling support for Amazon OpenSearch Service managed clusters, further strengthening its capabilities as a fully managed Retrieval Augmented Generation (RAG) solution. Why use OpenSearch Service Managed Cluster as a vector store?

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Build conversational interfaces for structured data using Amazon Bedrock Knowledge Bases

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Large language models (LLMs) have transformed natural language processing (NLP), yet converting conversational queries into structured data analysis remains complex. Amazon Bedrock Knowledge Bases enables direct natural language interactions with structured data sources.

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Syngenta develops a generative AI assistant to support sales representatives using Amazon Bedrock Agents

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Syngenta and AWS collaborated to develop Cropwise AI , an innovative solution powered by Amazon Bedrock Agents , to accelerate their sales reps’ ability to place Syngenta seed products with growers across North America. The collaboration between Syngenta and AWS showcases the transformative power of LLMs and AI agents.

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Deploy Meta Llama 3.1 models cost-effectively in Amazon SageMaker JumpStart with AWS Inferentia and AWS Trainium

AWS Machine Learning Blog

8B and 70B inference support on AWS Trainium and AWS Inferentia instances in Amazon SageMaker JumpStart. multilingual large language models (LLMs) are a collection of pre-trained and instruction tuned generative models. An AWS Identity and Access Management (IAM) role to access SageMaker. Meta Llama 3.1 by up to 50%.

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Large Language Models: A Self-Study Roadmap

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Step 1: Cover the Fundamentals You can skip this step if you already know the basics of programming, machine learning, and natural language processing. The key here is to focus on concepts like supervised vs. unsupervised learning, regression, classification, clustering, and model evaluation. So, lets get started.

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Accelerating Mixtral MoE fine-tuning on Amazon SageMaker with QLoRA

AWS Machine Learning Blog

Although QLoRA helps optimize memory during fine-tuning, we will use Amazon SageMaker Training to spin up a resilient training cluster, manage orchestration, and monitor the cluster for failures. To take complete advantage of this multi-GPU cluster, we use the recent support of QLoRA and PyTorch FSDP. 24xlarge compute instance.

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Transforming financial analysis with CreditAI on Amazon Bedrock: Octus’s journey with AWS

AWS Machine Learning Blog

We walk through the journey Octus took from managing multiple cloud providers and costly GPU instances to implementing a streamlined, cost-effective solution using AWS services including Amazon Bedrock, AWS Fargate , and Amazon OpenSearch Service. Along the way, it also simplified operations as Octus is an AWS shop more generally.

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