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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. Amazon Q Developer CLI with Model Context Protocol …

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

Legal teams spend bulk of their time manually reviewing documents during eDiscovery. This process involves analyzing electronically stored information across emails, contracts, financial records, and collaboration systems for legal proceedings. This manual approach creates significant bottlenecks: attorneys must identify privileged communications, assess legal risks, extract contractual obligations, and maintain regulatory compliance across thousands of documents …

Build an intelligent eDiscovery solution using Amazon Bedrock Agents Read More »

This post is co-written with Bogdan Arsenie and Nick Mattei from PerformLine. PerformLine operates within the marketing compliance industry, a specialized subset of the broader compliance software market, which includes various compliance solutions like anti-money laundering (AML), know your customer (KYC), and others. Specifically, marketing compliance refers to adhering to regulations and guidelines set by …

How PerformLine uses prompt engineering on Amazon Bedrock to detect compliance violations  Read More »

Cold start in recommendation systems goes beyond just new user or new item problems—it’s the complete absence of personalized signals at launch. When someone first arrives, or when fresh content appears, there’s no behavioral history to tell the engine what they care about, so everyone ends up in broad generic segments. That not only dampens …

Boost cold-start recommendations with vLLM on AWS Trainium Read More »

Large language models (LLMs) have rapidly evolved, becoming integral to applications ranging from conversational AI to complex reasoning tasks. However, as models grow in size and capability, effectively evaluating their performance has become increasingly challenging. Traditional benchmarking metrics like perplexity and BLEU scores often fail to capture the nuances of real-world interactions, making human-aligned evaluation …

Benchmarking Amazon Nova: A comprehensive analysis through MT-Bench and Arena-Hard-Auto Read More »

Learn more about new AI tools available from Google Shopping, like our launch of our try on feature and price alert updates. ​ 

We’re launching Web Guide, a Search Labs experiment that uses AI to intelligently organize the search results page, making it easier to find information and web pages. ​ 

At the AWS Summit in New York City, we introduced a comprehensive suite of model customization capabilities for Amazon Nova foundation models. Available as ready-to-use recipes on Amazon SageMaker AI, you can use them to adapt Nova Micro, Nova Lite, and Nova Pro across the model training lifecycle, including pre-training, supervised fine-tuning, and alignment. In this …

Customize Amazon Nova in Amazon SageMaker AI using Direct Preference Optimization Read More »

What does it take to enable billions of people to truly ask anything in Search?In the latest episode of the Google AI: Release Notes podcast, host Logan Kilpatrick sits … ​ 

In recent years, the emergence of large language models (LLMs) has accelerated AI adoption across various industries. However, to further augment LLMs’ capabilities and effectively use up-to-date information and domain-specific knowledge, integration with external data sources is essential. Retrieval Augmented Generation (RAG) has gained attention as an effective approach to address this challenge. RAG is …

Multi-tenant RAG implementation with Amazon Bedrock and Amazon OpenSearch Service for SaaS using JWT Read More »