The article presents Greg's recipe for success with Agentic AI. It details how Greg's approach led to success, leveraging Amazon Web Services technology.
BMW Group and AWS are collaborating to advance data-driven engineering, aiming to innovate future automotive development. This partnership focuses on leveraging cloud technologies to enhance engineering processes and decision-making.
HelloFresh implemented AI solutions to significantly reduce engineer response time, from hours to seconds. This process optimization was achieved in partnership with Amazon Web Services.
This content explains how Amazon Web Services (AWS) can be used to accelerate the integration of Artificial Intelligence (AI) into the Software Development Life Cycle (SDLC).
Amazon Web Services (AWS) introduces "Formula 1® Circuit Classes" and "F1 Insights," leveraging AWS technology to deliver new analytics and fan experiences for Formula 1. These innovations aim to deepen understanding of races through advanced data and insights.
This content explores how Amazon Web Services (AWS) is utilized to generate insights for Formula 1, specifically focusing on street circuits. It likely details the technologies and data analysis techniques employed to enhance understanding and performance in these unique racing environments.
This article connects previous pieces to explain multimodal RAG. It details how Amazon Bedrock Knowledge Bases now supports multimodal content, including images, audio, and video, to build end-to-end RAG workflows on AWS.
This article presents a real AWS benchmark comparing the raw AWS CLI against the official awslabs.aws-api-mcp-server for AI agents, concluding that a well-designed CLI tool outperforms MCP. It reframes the question of which to use as a trade-off between engineering time and input tokens per run.
This week, AWS added Claude Opus 4.7 to Amazon Bedrock, coinciding with Amazon's additional $25 billion investment in Anthropic, totaling $33 billion. This represents the largest corporate AI infrastructure bet in history, with immediate implications for engineers building on AWS using Claude in production agentic systems.
Anthropic has committed over $100 billion to AWS in a decade-long agreement for AI training and inference capacity, utilizing Trainium chips. This comes as Anthropic's annualized revenue has surged past $30 billion, reflecting unprecedented consumer growth in the AI sector.
OpenAI has made its frontier models, including GPT-4, and its Codex models available through Amazon Web Services (AWS). This integration streamlines access to powerful AI tools for AWS customers, allowing direct incorporation of these advanced models into their existing workflows.
This document outlines methods to resolve private marketplace eligibility errors encountered when trying to access Amazon Bedrock models. It provides a step-by-step guide to overcome impediments and ensure proper access to the models.
This post details how to build a custom portal embedding SageMaker AI MLflow Apps UI. It covers the React front end and Flask reverse proxy architecture, AWS CDK deployment, SigV4 authentication, and security aspects.
Amazon Web Services' Bedrock Agentcore is revolutionizing the travel industry. It introduces new capabilities to transform customer experiences in this sector.
This guide explores the shift towards efficiency in putting Large Language Models (LLMs) into production, introducing AWS Labs’ LLMeter. The tool is a Python-based benchmarking library, detailing its importance, usage, and crucial metrics like Time to First Token and Tokens Per Second.
This post explains how to integrate Amazon Quick with AWS services using Amazon Bedrock AgentCore Runtime's Model Context Protocol (MCP) support. It demonstrates creating a conversational AI assistant that translates natural language into AWS CLI commands, streamlining operations.
This post demonstrates how to implement custom code-based evaluators in Amazon Bedrock AgentCore. It teaches how to register Lambda-based evaluators for a financial market-intelligence agent and combine them with built-in evaluators for fact-checking and PII detection.
This article details how to build scalable Claude AI agents on AWS Lambda, addressing the challenge of Lambda's stateless nature with persistent WebSocket connections. It proposes using the Model Context Protocol (MCP) with Upstash Redis for session state management, enabling stateful interactions, high concurrency, and cost efficiency.
This content explores how Amazon Web Services' Bedrock AgentCore is enabling Agentic AI. It details the functionalities and impact of this technology on the development of autonomous AI systems.
GoKwik streamlines the checkout process and effectively combats fraud by leveraging artificial intelligence on the AWS platform. This implementation demonstrates how AI can optimize customer experience and enhance security in online transactions.
