AI

Organizations need seamless access to their structured data repositories to power intelligent AI agents. However, when these resources span multiple AWS accounts integration challenges can arise. This post explores a practical solution for connecting Amazon Bedrock agents to knowledge bases in Amazon Redshift clusters residing in different AWS accounts. The challenge Organizations that build AI […]

This post is cowritten by Laura Skylaki, Vaibhav Goswami, Ramdev Wudali and Sahar El Khoury from Thomson Reuters. Thomson Reuters (TR) is a leading AI and technology company dedicated to delivering trusted content and workflow automation solutions. With over 150 years of expertise, TR provides essential solutions across legal, tax, accounting, risk, trade, and media

With global power demand from data centers expected to more than double by 2030, the MIT Energy Initiative (MITEI) in September launched an effort that brings together MIT researchers and industry experts to explore innovative solutions for powering the data-driven future. At its annual research conference, MITEI announced the Data Center Power Forum, a targeted research effort for

With Amazon Bedrock Custom Model Import, you can deploy and scale fine-tuned or proprietary foundation models in a fully managed, serverless environment. You can bring your own models into Amazon Bedrock, scale them securely without managing infrastructure, and integrate them with other Amazon Bedrock capabilities. Today, we are excited to announce the addition of structured

Adoption of new tools and technologies occurs when users largely perceive them as reliable, accessible, and an improvement over the available methods and workflows for the cost. Five PhD students from the inaugural class of the MIT-IBM Watson AI Lab Summer Program are utilizing state-of-the-art resources, alleviating AI pain points, and creating new features and

As AI agents are adopted at scale, developer teams can create dozens to hundreds of specialized Model Context Protocol (MCP) servers, tailored for specific agent use case and domain, organization functions or teams. Organizations also need to integrate their own existing MCP servers or open source MCP servers for their AI workflows. There is a

Coding with large language models (LLMs) holds huge promise, but it also exposes some long-standing flaws in software: code that’s messy, hard to change safely, and often opaque about what’s really happening under the hood. Researchers at MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) are charting a more “modular” path ahead.  Their new approach

Microsoft, Alphabet, Meta, and Amazon are investing tens of billions in data centers. AI infrastructure is now a key driver of US economic growth.

AgiBot is using AI-powered robots to do new manufacturing tasks. Smarter machines may transform physical labor in China.

In this post, we show you how Amazon Search optimized GPU instance utilization by leveraging AWS Batch for SageMaker Training jobs. This managed solution enabled us to orchestrate machine learning (ML) training workloads on GPU-accelerated instance families like P5, P4, and others. We will also provide a step-by-step walkthrough of the use case implementation. Machine