AI

Quality assurance (QA) testing has long been the backbone of software development, but traditional QA approaches haven’t kept pace with modern development cycles and complex UIs. Most organizations still rely on a hybrid approach combining manual testing with script-based automation frameworks like Selenium, Cypress, and Playwright—yet teams spend significant amount of their time maintaining existing

The rise of powerful large language models (LLMs) that can be consumed via API calls has made it remarkably straightforward to integrate artificial intelligence (AI) capabilities into applications. Yet despite this convenience, a significant number of enterprises are choosing to self-host their own models—accepting the complexity of infrastructure management, the cost of GPUs in the

Big AI companies courted controversy by scraping wide swaths of the public internet. With the rise of AI agents, the next data grab is far more private.

A surge of AI-generated content is frustrating Pinterest users and left some questioning whether the platform still works at all.

WIRED spoke with DeepMind’s Pushmeet Kohli about the recent past—and promising future—of the Nobel Prize-winning research project that changed biology and chemistry forever.

At Amazon, our culture, built on honest and transparent discussion of our growth opportunities, enables us to focus on investing and innovating to continually raise the standard on our ability to deliver value for our customers. Earlier this month, we had the opportunity to share an example of this process at work in Mantle, our

Building intelligent agents to handle complex, real-world tasks can be daunting. Additionally, rather than relying solely on large, pre-trained foundation models, organizations often need to fine-tune and customize smaller, more specialized models to outperform them for their specific use cases. The AWS AI League provides an innovative program to help enterprises overcome the challenges of building

This post is co-written by Thomas Capelle and Ray Strickland from Weights & Biases (W&B). Generative artificial intelligence (AI) adoption is accelerating across enterprises, evolving from simple foundation model interactions to sophisticated agentic workflows. As organizations transition from proof-of-concepts to production deployments, they require robust tools for development, evaluation, and monitoring of AI applications at

dLocal, Uruguay’s first unicorn, has established itself as a pioneer in cross-border payments since its founding in 2016. Today, the company operates in over 40 emerging countries, connecting more than two billion consumers with global technology leaders. Operating at this scale requires strict and consistent compliance processes. Each month, thousands of merchant ecommerce websites are