AI

Large language models (LLMs) excel at using textual reasoning to understand the context of a document and provide a logical answer about its contents. But these same LLMs often struggle to correctly answer even the simplest math problems. Textual reasoning is usually a less-than-ideal way to deliberate over computational or algorithmic tasks. While some LLMs

This post was written with Ilan Geller, Kamal Mannar, Debasmita Ghosh, and Nakul Aggarwal of Accenture. Video highlights offer a powerful way to boost audience engagement and extend content value for content publishers. These short, high-impact clips capture key moments that drive viewer retention, amplify reach across social media, reinforce brand identity, and open new

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.