Accelerating data science innovation: How Bayer Crop Science used AWS AI/ML services to build their next-generation MLOps service

Favorite The world’s population is expanding at a rapid rate. The growing global population requires innovative solutions to produce food, fiber, and fuel, while restoring natural resources like soil and water and addressing climate change. Bayer Crop Science estimates farmers need to increase crop production by 50% by 2050 to

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Shared by AWS Machine Learning July 8, 2025

Advancing AI agent governance with Boomi and AWS: A unified approach to observability and compliance

Favorite Just as APIs became the standard for integration, AI agents are transforming workflow automation through intelligent task coordination. AI agents are already enhancing decision-making and streamlining operations across enterprises. But as adoption accelerates, organizations face growing complexity in managing them at scale. Organizations struggle with observability and lifecycle management,

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Shared by AWS Machine Learning July 3, 2025

Optimize RAG in production environments using Amazon SageMaker JumpStart and Amazon OpenSearch Service

Favorite Generative AI has revolutionized customer interactions across industries by offering personalized, intuitive experiences powered by unprecedented access to information. This transformation is further enhanced by Retrieval Augmented Generation (RAG), a technique that allows large language models (LLMs) to reference external knowledge sources beyond their training data. RAG has gained

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Shared by AWS Machine Learning July 3, 2025

End-to-End model training and deployment with Amazon SageMaker Unified Studio

Favorite Although rapid generative AI advancements are revolutionizing organizational natural language processing tasks, developers and data scientists face significant challenges customizing these large models. These hurdles include managing complex workflows, efficiently preparing large datasets for fine-tuning, implementing sophisticated fine-tuning techniques while optimizing computational resources, consistently tracking model performance, and achieving

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Shared by AWS Machine Learning July 3, 2025

Transforming network operations with AI: How Swisscom built a network assistant using Amazon Bedrock

Favorite In the telecommunications industry, managing complex network infrastructures requires processing vast amounts of data from multiple sources. Network engineers often spend considerable time manually gathering and analyzing this data, taking away valuable hours that could be spent on strategic initiatives. This challenge led Swisscom, Switzerland’s leading telecommunications provider, to

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Shared by AWS Machine Learning July 3, 2025

Use Amazon SageMaker Unified Studio to build complex AI workflows using Amazon Bedrock Flows

Favorite Organizations face the challenge to manage data, multiple artificial intelligence and machine learning (AI/ML) tools, and workflows across different environments, impacting productivity and governance. A unified development environment consolidates data processing, model development, and AI application deployment into a single system. This integration streamlines workflows, enhances collaboration, and accelerates

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Shared by AWS Machine Learning July 2, 2025

Build and deploy AI inference workflows with new enhancements to the Amazon SageMaker Python SDK

Favorite Amazon SageMaker Inference has been a popular tool for deploying advanced machine learning (ML) and generative AI models at scale. As AI applications become increasingly complex, customers want to deploy multiple models in a coordinated group that collectively process inference requests for an application. In addition, with the evolution

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Shared by AWS Machine Learning July 1, 2025

Revolutionizing drug data analysis using Amazon Bedrock multimodal RAG capabilities

Favorite In the pharmaceutical industry, biotechnology and healthcare companies face an unprecedented challenge for efficiently managing and analyzing vast amounts of drug-related data from diverse sources. Traditional data analysis methods prove inadequate for processing complex medical documentation that includes a mix of text, images, graphs, and tables. Amazon Bedrock offers

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Shared by AWS Machine Learning July 1, 2025

Choosing the right approach for generative AI-powered structured data retrieval

Favorite Organizations want direct answers to their business questions without the complexity of writing SQL queries or navigating through business intelligence (BI) dashboards to extract data from structured data stores. Examples of structured data include tables, databases, and data warehouses that conform to a predefined schema. Large language model (LLM)-powered

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Shared by AWS Machine Learning July 1, 2025