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How Nippon India Mutual Fund improved the accuracy of AI assistant responses using advanced RAG methods on Amazon Bedrock

Favorite This post is co-written with Abhinav Pandey from Nippon Life India Asset Management Ltd. Accurate information retrieval through generative AI-powered assistants is a popular use case for enterprises. To reduce hallucination and improve overall accuracy, Retrieval Augmented Generation (RAG) remains the most commonly used method to retrieve reliable and

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Shared by AWS Machine Learning July 29, 2025

Fine-tune and deploy Meta Llama 3.2 Vision for generative AI-powered web automation using AWS DLCs, Amazon EKS, and Amazon Bedrock

Favorite Fine-tuning of large language models (LLMs) has emerged as a crucial technique for organizations seeking to adapt powerful foundation models (FMs) to their specific needs. Rather than training models from scratch—a process that can cost millions of dollars and require extensive computational resources—companies can customize existing models with domain-specific

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Shared by AWS Machine Learning July 29, 2025

The inside story of building NotebookLM

Favorite Hear how Googlers developed and tested NotebookLM, your virtual research assistant — straight from the source. View Original Source (blog.google/technology/ai/) Here.

Build modern serverless solutions following best practices using Amazon Q Developer CLI and MCP

Favorite Building modern serverless applications on AWS requires navigating best practices to manage the integration between multiple services, such as AWS Lambda, Amazon API Gateway, Amazon DynamoDB, and Amazon EventBridge. Security considerations, performance optimization, and implementing a comprehensive monitoring systems adds further requirements to build a serverless architecture while adhering to AWS best practices.

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Shared by AWS Machine Learning July 28, 2025

Optimizing enterprise AI assistants: How Crypto.com uses LLM reasoning and feedback for enhanced efficiency

Favorite This post is co-written with Jessie Jiao from Crypto.com. Crypto.com is a crypto exchange and comprehensive trading service serving 140 million users in 90 countries. To improve the service quality of Crypto.com, the firm implemented generative AI-powered assistant services on AWS. Modern AI assistants—artificial intelligence systems designed to interact

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Shared by AWS Machine Learning July 28, 2025