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Tag: Amazon RDS

Explore data with ease: Use SQL and Text-to-SQL in Amazon SageMaker Studio JupyterLab notebooks | Amazon Web Services

Amazon SageMaker Studio provides a fully managed solution for data scientists to interactively build, train, and deploy machine learning (ML) models. In the process...

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Architect defense-in-depth security for generative AI applications using the OWASP Top 10 for LLMs | Amazon Web Services

Generative artificial intelligence (AI) applications built around large language models (LLMs) have demonstrated the potential to create and accelerate economic value for businesses. Examples...

Generating value from enterprise data: Best practices for Text2SQL and generative AI | Amazon Web Services

Generative AI has opened up a lot of potential in the field of AI. We are seeing numerous uses, including text generation, code generation,...

Improve your Stable Diffusion prompts with Retrieval Augmented Generation | Amazon Web Services

Text-to-image generation is a rapidly growing field of artificial intelligence with applications in a variety of areas, such as media and entertainment, gaming, ecommerce...

Use AWS PrivateLink to set up private access to Amazon Bedrock | Amazon Web Services

Amazon Bedrock is a fully managed service provided by AWS that offers developers access to foundation models (FMs) and the tools to customize them...

Intelligent document processing with Amazon Textract, Amazon Bedrock, and LangChain | Amazon Web Services

In today’s information age, the vast volumes of data housed in countless documents present both a challenge and an opportunity for businesses. Traditional document...

Intelligent video and audio Q&A with multilingual support using LLMs on Amazon SageMaker | Amazon Web Services

Digital assets are vital visual representations of products, services, culture, and brand identity for businesses in an increasingly digital world. Digital assets, together with...

Reinventing the data experience: Use generative AI and modern data architecture to unlock insights | Amazon Web Services

Implementing a modern data architecture provides a scalable method to integrate data from disparate sources. By organizing data by business domains instead of infrastructure,...

Accelerate machine learning time to value with Amazon SageMaker JumpStart and PwC’s MLOps accelerator | Amazon Web Services

This is a guest blog post co-written with Vik Pant and Kyle Bassett from PwC. With organizations increasingly investing in machine learning (ML), ML...

Announcing the updated Microsoft SharePoint connector (V2.0) for Amazon Kendra | Amazon Web Services

Amazon Kendra is a highly accurate and simple-to-use intelligent search service powered by machine learning (ML). Amazon Kendra offers a suite of data source...

Implement backup and recovery using an event-driven serverless architecture with Amazon SageMaker Studio

Amazon SageMaker Studio is the first fully integrated development environment (IDE) for ML. It provides a single, web-based visual interface where you can perform...

Improved ML model deployment using Amazon SageMaker Inference Recommender

Each machine learning (ML) system has a unique service level agreement (SLA) requirement with respect to latency, throughput, and cost metrics. With advancements in...

How the UNDP Independent Evaluation Office is using AWS AI/ML services to enhance the use of evaluation to support progress toward the Sustainable Development...

The United Nations (UN) was founded in 1945 by 51 original Member States committed to maintaining international peace and security, developing friendly relations among...

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