Use dynamic arrays and tables for fast, scalable cascading drop-down lists in modern Excel.

According to Anthropic, Opus 4.6 “brings more focus to the most challenging parts of a task without being told to, moves quickly through the more straightforward parts, handles ambiguous problems with ...

Discover how to build a homemade rubber band-powered paper airplane in this easy and engaging tutorial. We’ll guide you step-by-step as you craft the frame with skewers, add aerodynamic paper wings, ...

As people rang in the new year, TikTok turned into a time machine, christening “2026 as the new 2016” in a constant scroll of Snapchat dog filters, Mannequin Challenge throwbacks and choker and crop ...

On Monday, Anthropic announced Opus 4.5, the latest version of its flagship model. It’s the last of Anthropic’s 4.5 series of models to be released, following the launch of Sonnet 4.5 in September and ...

An illustration Anthropic commissioned to mark the release of Opus 4.5. (Anthropic) Hot on the heels of Google's Gemini 3 Pro release, Anthropic has announced an update for its flagship Opus model.

Anthropic is making its most aggressive push yet into the trillion-dollar financial services industry, unveiling a suite of tools that embed its Claude AI assistant directly into Microsoft Excel and ...

What if you could build a fully functional financial model in minutes, without spending hours wrestling with formulas, cleaning messy data, or manually updating projections? With the introduction of ...

Some cars invite you in with chrome and comfort. The Model T invites you into a time machine, hands you three pedals that mean the wrong things, and politely asks you to learn 1910s. Then it coughs, ...

The software development world has been transformed by AI-powered coding assistants such as Cursor and Claude Code, which have changed how engineers write and debug code. Processing Content These ...

A new kind of large language model, developed by researchers at the Allen Institute for AI (Ai2), makes it possible to control how training data is used even after a model has been built.

When AI models fail to meet expectations, the first instinct may be to blame the algorithm. But the real culprit is often the data—specifically, how it’s labeled. Better data annotation—more accurate, ...