AI

Amazon Aurora PostgreSQL-Compatible Edition is a fully managed, PostgreSQL-compatible, ACID-aligned relational database engine that combines the speed, reliability, and manageability of Amazon Aurora with the simplicity and cost-effectiveness of open source databases. Aurora PostgreSQL-Compatible is a drop-in replacement for PostgreSQL and makes it simple and cost-effective to set up, operate, and scale your new and […]

This post was co-written with Varun Kumar from Tealium Retrieval Augmented Generation (RAG) pipelines are popular for generating domain-specific outputs based on external data that’s fed in as part of the context. However, there are challenges with evaluating and improving such systems. Two open-source libraries, Ragas (a library for RAG evaluation) and Auto-Instruct, used Amazon

AI is replacing the humans who pretend to be OnlyFans stars in online amorous messages.

EBSCOlearning offers corporate learning and educational and career development products and services for businesses, educational institutions, and workforce development organizations. As a division of EBSCO Information Services, EBSCOlearning is committed to enhancing professional development and educational skills. In this post, we illustrate how EBSCOlearning partnered with AWS Generative AI Innovation Center (GenAIIC) to use the

A new version of Google’s flagship AI model shows how the company sees AI transforming personal computing, web search, and perhaps the way people interact with the physical world.

The project’s leader says that allowing everyone to access the collection of public-domain books will help “level the playing field” in the AI industry.

In this installment of WIRED’s AI advice column, “The Prompt,” we answer questions about giving AI tools proper attribution and teaching future generations how to interact with chatbots.

In 2025, blockchain alternatives will offer more choice, open source innovation, and community-controlled options. They will carry the torch of the open internet.

Machine-learning models can fail when they try to make predictions for individuals who were underrepresented in the datasets they were trained on. For instance, a model that predicts the best treatment option for someone with a chronic disease may be trained using a dataset that contains mostly male patients. That model might make incorrect predictions

Large language models (LLMs) that drive generative artificial intelligence apps, such as ChatGPT, have been proliferating at lightning speed and have improved to the point that it is often impossible to distinguish between something written through generative AI and human-composed text. However, these models can also sometimes generate false statements or display a political bias.