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Build generative AI applications quickly with Amazon Bedrock IDE in Amazon SageMaker Unified Studio

AWS Machine Learning Blog

Building generative AI applications presents significant challenges for organizations: they require specialized ML expertise, complex infrastructure management, and careful orchestration of multiple services. The following diagram illustrates the conceptual architecture of an AI assistant with Amazon Bedrock IDE.

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Enterprise-grade natural language to SQL generation using LLMs: Balancing accuracy, latency, and scale

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Recent advances in generative AI have led to the rapid evolution of natural language to SQL (NL2SQL) technology, which uses pre-trained large language models (LLMs) and natural language to generate database queries in the moment. AWS solution architecture In this section, we illustrate how you might implement the architecture on AWS.

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Agents as escalators: Real-time AI video monitoring with Amazon Bedrock Agents and video streams

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Amazon Bedrock is a fully managed service that provides access to high-performing foundation models (FMs) from leading AI companies through a single API. Using Amazon Bedrock, you can build secure, responsible generative AI applications. The solution uses the AWS Cloud Development Kit (AWS CDK) to deploy the solution components.

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Llama 4 family of models from Meta are now available in SageMaker JumpStart

AWS Machine Learning Blog

Virginia) AWS Region. These models are designed for industry-leading performance in image and text understanding with support for 12 languages, enabling the creation of AI applications that bridge language barriers. With SageMaker AI, you can streamline the entire model deployment process.

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Benchmarking Amazon Nova and GPT-4o models with FloTorch

AWS Machine Learning Blog

The growing need for cost-effective AI models The landscape of generative AI is rapidly evolving. OpenAI launched GPT-4o in May 2024, and Amazon introduced Amazon Nova models at AWS re:Invent in December 2024. simple_w_condition Movie In 2016, which movie was distinguished for its visual effects at the oscars?

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Adobe enhances developer productivity using Amazon Bedrock Knowledge Bases

AWS Machine Learning Blog

For instance, a developer setting up a continuous integration and delivery (CI/CD) pipeline in a new AWS Region or running a pipeline on a dev branch can quickly access Adobe-specific guidelines and best practices through this centralized system. About the Authors Kamran Razi is a Data Scientist at the Amazon Generative AI Innovation Center.

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LLM continuous self-instruct fine-tuning framework powered by a compound AI system on Amazon SageMaker

AWS Machine Learning Blog

This framework is designed as a compound AI system to drive the fine-tuning workflow for performance improvement, versatility, and reusability. Likewise, to address the challenges of lack of human feedback data, we use LLMs to generate AI grades and feedback that scale up the dataset for reinforcement learning from AI feedback ( RLAIF ).

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