AI

Imagine a future where artificial intelligence quietly shoulders the drudgery of software development: refactoring tangled code, migrating legacy systems, and hunting down race conditions, so that human engineers can devote themselves to architecture, design, and the genuinely novel problems still beyond a machine’s reach. Recent advances appear to have nudged that future tantalizingly close, but […]

This post is co-written with Mark Berkeland, Oscar Rodriguez and Marina Gerzon from Vonage. Voice-based technologies are transforming the way businesses engage with customers across customer support, virtual assistants, and intelligent agents. However, creating real-time, expressive, and highly responsive voice interfaces still requires navigating a complex stack of communication protocols, AI models, and media infrastructure.

At a Pittsburgh summit, the Trump administration, energy executives, and tech barons joined as one to promote AI as the future of fossil fuels.

AI agents will change how we all work and live. Our AWS CEO, Matt Garman, shared a vision of a technological shift as transformative as the advent of the internet. I’m energized by this vision because I’ve witnessed firsthand how these intelligent agent systems are already beginning to solve complex problems, automate workflows, and create

The mission? Teaching models to better understand how to build code will lead to superintelligent AI.

MIT researchers have developed a new theoretical framework for studying the mechanisms of treatment interactions. Their approach allows scientists to efficiently estimate how combinations of treatments will affect a group of units, such as cells, enabling a researcher to perform fewer costly experiments while gathering more accurate data. As an example, to study how interconnected

Jason Wei, who worked on OpenAI’s o3 and deep research models, will be joining Meta’s superintelligence lab. His colleague Hyung Won Chung is also joining Meta, a source tells WIRED.

xAI’s new $300 monthly subscription comes with two AI companions powered by its most capable model to date. I tried them. It got weird.

Amazon Bedrock Knowledge Bases has extended its vector store options by enabling support for Amazon OpenSearch Service managed clusters, further strengthening its capabilities as a fully managed Retrieval Augmented Generation (RAG) solution. This enhancement builds on the core functionality of Amazon Bedrock Knowledge Bases , which is designed to seamlessly connect foundation models (FMs) with

This post was co-written with Mohammad Jama, Yun Kim, and Barry Eom from Datadog. The emergence of generative AI agents in recent years has transformed the AI landscape, driven by advances in large language models (LLMs) and natural language processing (NLP). The focus is shifting from simple AI assistants to Agentic AI systems that can