This post details implementing object detection with Amazon Nova 2 Lite. Readers will learn how to deploy an object detection application using Amazon Bedrock, AWS Lambda, and Amazon API Gateway, as well as how to craft effective prompts and visualize results.
This post presents a solution for building highly scalable, serverless multi-agent generative AI systems on AWS. It integrates LangGraph Agents as orchestrators with Amazon Bedrock AgentCore Memory and Observability.
The article explores the significant risks of connecting AI agents like GitHub Copilot to AWS MCP Server for natural language cloud management. It illustrates with an example where an agent's command led to the termination of critical EC2 instances, resulting in a large unexpected AWS bill.
This post demonstrates AgentWatch, a solution for proactive AWS infrastructure monitoring. It performs checks every 15 minutes, summarizing CloudWatch metrics, logs, and alarms across multiple AWS accounts, delivering reports to Slack and responding to natural language queries.
This post demonstrates how Amazon FinTech teams are using Amazon Bedrock and other AWS services to build a scalable AI application. The goal is to transform how regulatory inquiries are handled, allowing each team to maintain its own dedicated knowledge base.
This post explains how to secure reserved short-term GPU capacity for ML workloads using Amazon EC2 Capacity Blocks for ML and SageMaker training plans. These solutions help address GPU availability challenges for tasks like load testing, model validation, and time-bound workshops.
This content discusses the critical need for a centralized observability solution for enterprise AI platforms with numerous users, focusing on tracking user activity, satisfaction, and engagement drivers. It addresses the challenge of disparate data sources across multiple AWS services when such a solution is absent.
This post details how Baz improved its AI Agent Code Review accuracy using Amazon Bedrock and Amazon Bedrock AgentCore. It covers the architectural decisions, implementation details, and business outcomes achieved by automating their code review process.
This post illustrates three methods for implementing Programmatic Tool Calling (PTC) on Amazon Bedrock. These include a self-hosted Docker sandbox on ECS, a managed solution using Amazon Bedrock AgentCore Code Interpreter, and an Anthropic SDK-compatible path.
This podcast episode explores how Agentic AI is transforming the travel industry, discussing its applications and future implications. The discussion delves into AI's impact on travel experiences and services.
This article describes a sample implementation for monetizing AI Agents using the x402 micropayment protocol, integrated with AWS CloudFront and Lambda@Edge. It details an architecture where AI Agents can autonomously pay in USDC, supporting networks like Base Sepolia and Solana Devnet.
This executive dialogue explores how Tuya is revolutionizing smart living, progressing from AIoT to Physical AI. Their collaboration with AWS is pivotal in this transformation, driving innovations in smart home and building solutions.
This article outlines a serverless AWS design for processing user-generated media, extracting intelligence using AI services. It leverages Rekognition, Transcribe, and Bedrock, persisting data into DynamoDB without traditional EC2 instances.
OpenAI's frontier models and Codex are now generally available on AWS, offering enterprises a new way to integrate OpenAI technology within their existing AWS infrastructure. This availability allows customers to accelerate their AI development from evaluation to production using familiar AWS environments.
This post details how to secure AI agents' access to external services using Amazon Bedrock AgentCore Identity. It specifically implements the Authorization Code Grant (3-legged OAuth) on Amazon ECS with secure session binding and scoped tokens.
This content from Amazon Web Services explores the application of AI in investment management, emphasizing accuracy and reliability. It highlights how AI can enhance decision-making without compromising precision in financial operations.
This AWS "Humans In The Loop" podcast explores the future of Agentic AI with Rory Richardson. The discussion delves into the implications and potential of autonomous AI and its interaction with human oversight.
This content from the AWS Humans In The Loop Podcast explores the latest advancements with Kiro, detailing its new powers and enhanced agent skills. It provides an update on the evolving capabilities of this AI system within the Amazon Web Services ecosystem.
AWS has generally available the Spring AI AgentCore SDK, simplifying the development of production-ready Java AI agents. This SDK collapses weeks of infrastructure work for agentic AI into a single annotation, handling aspects like scaling, reliability, and memory repositories.
The AWS AI Practitioner certification is foundational and suitable for non-technical professionals as it focuses on AI concepts and their application, not coding. Its scenario-based questions align with business problem-solving skills, favoring practical, managed service solutions.