Technical concepts explained in plain language
Burrowed in the alleys of Hongik-dong, a hushed residential neighborhood in eastern Seoul, is a faded stone-tiled building stamped “Korea Baduk Association,” the governing body for professional Go. The game is an ancient one, with sacred stature in South Korea. But inside the building, rooms once filled with the soft clatter of hands dipping into…
OpenAI and Pacific Northwest National Laboratory introduce DraftNEPABench, a new benchmark evaluating how AI coding agents can accelerate federal permitting—showing potential to reduce NEPA drafting time by up to 15% and modernize infrastructure reviews.
In this post, we explain how we implemented multi-LoRA inference for Mixture of Experts (MoE) models in vLLM, describe the kernel-level optimizations we performed, and show you how you can benefit from this work. We use GPT-OSS 20B as our primary example throughout this post.
In this post, we show you how to build a comprehensive photo search system using the AWS Cloud Development Kit (AWS CDK) that integrates Amazon Rekognition for face and object detection, Amazon Neptune for relationship mapping, and Amazon Bedrock for AI-powered captioning.
A viral essay from Citrini about how AI bullishness could be bearish was impactful enough for Bloomberg to give it partial responsibility for a decline in the stock market, and all the cool economics types are talking about it.
In this post, we examine how Bedrock Robotics tackles this challenge. By joining the AWS Physical AI Fellowship, the startup partnered with the AWS Generative AI Innovation Center to apply vision-language models that analyze construction video footage, extract operational details, and generate labeled training datasets at scale, to improve data preparation for autonomous construction equipment.
In this post, we explore how Sonrai, a life sciences AI company, partnered with AWS to build a robust MLOps framework using Amazon SageMaker AI that addresses these challenges while maintaining the traceability and reproducibility required in regulated environments.
In 2025, Amazon SageMaker AI saw dramatic improvements to core infrastructure offerings along four dimensions: capacity, price performance, observability, and usability. In this series of posts, we discuss these various improvements and their benefits. In Part 1, we discuss capacity improvements with the launch of Flexible Training Plans. We also describe improvements to price performance for inference workloads. In Part 2, we discuss enhancements made to observability, model customization, and model hosting.
In this post, you’ll use a six-step checklist to build a new MCP server or validate and adjust an existing MCP server for Amazon Quick integration. The Amazon Quick User Guide describes the MCP client behavior and constraints. This is a “How to” guide for detailed implementation required by 3P partners to integrate with Amazon Quick with MCP.
The NVIDIA Blackwell platform has been widely adopted by leading inference providers such as Baseten, DeepInfra, Fireworks AI and Together AI to reduce cost per token by up to 10x. Now, the NVIDIA Blackwell Ultra platform is taking this momentum further for agentic AI. AI agents and coding assistants are driving explosive growth in software-programming-related Read Article
The NVIDIA Blackwell platform has been widely adopted by leading inference providers such as Baseten, DeepInfra, Fireworks AI and Together AI to reduce cost per token by up to 10x. Now, the NVIDIA Blackwell Ultra platform is taking this momentum further for agentic AI. AI agents and coding assistants are driving explosive growth in software-programming-related Read Article
In this post, we show how to create an AI-powered recruitment system using Amazon Bedrock, Amazon Bedrock Knowledge Bases, AWS Lambda, and other AWS services to enhance job description creation, candidate communication, and interview preparation while maintaining human oversight.
This post shows you how to implement robust error handling strategies that can help improve application reliability and user experience when using Amazon Bedrock. We'll dive deep into strategies for optimizing performances for the application with these errors. Whether this is for a fairly new application or matured AI application, in this post you will be able to find the practical guidelines to operate with on these errors.
LinqAlpha is a Boston-based multi-agent AI system built specifically for institutional investors. The system supports and streamlines agentic workflows across company screening, primer generation, stock price catalyst mapping, and now, pressure-testing investment ideas through a new AI agent called Devil’s Advocate. In this post, we share how LinqAlpha uses Amazon Bedrock to build and scale Devil’s Advocate.
In this post, we discuss how Amazon Nova in Amazon Bedrock can be used to implement an AI-powered image recognition solution that automates the detection and validation of module components, significantly reducing manual verification efforts and improving accuracy.
Amazon Nova Sonic delivers real-time, human-like voice conversations through the bidirectional streaming interface. In this post, you learn how Amazon Nova Sonic can solve some of the challenges faced by cascaded approaches, simplify building voice AI agents, and provide natural conversational capabilities. We also provide guidance on when to choose each approach to help you make informed decisions for your voice AI projects.
This story originally appeared in The Algorithm, our weekly newsletter on AI. To get stories like this in your inbox first, sign up here. Lots of influential people in tech last week were describing Moltbook, an online hangout populated by AI agents interacting with one another, as a glimpse into the future. It appeared to show…
This post walks through how agent-to-agent collaboration on Amazon Bedrock works in practice, using Amazon Nova 2 Lite for planning and Amazon Nova Act for browser interaction, to turn a fragile single-agent setup into a predictable multi-agent system.
For years, our newsroom has explored AI’s limitations and potential dangers, as well as its growing energy needs. And our reporters have looked closely at how generative tools are being used for tasks such as coding and running scientific experiments. But how is AI actually being used in fields like health care, climate tech, education,…
In this post, we demonstrate how to use the CLI and the SDK to create and manage SageMaker HyperPod clusters in your AWS account. We walk through a practical example and dive deeper into the user workflow and parameter choices.