We invite you to join our industry specialists for a virtual session on how to use Bloomberg functionality in Excel. This ...

ABSTRACT: This paper proposes a structured data prediction method based on Large Language Models with In-Context Learning (LLM-ICL). The method designs sample selection strategies to choose samples ...

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, ...

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 ...

New York – October 7, 2025 – AI market intelligence platform AlphaSense announced the acquisition of Carousel, an AI-powered Excel modeling company. This acquisition adds Carousel’s modeling ...

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, ...