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Wolfram is the company where computation meets knowledge. A leader in scientific and technical innovation, Wolfram continues to build toward a future where sophisticated computation and knowledge-based programming are universally accessible. Combined, the new Wolfram Language, Wolfram Engine and Wolfram Cloud will make possible a computable model of the world—in essence, a global brain. Wolfram is the creator of Mathematica, the world’s foremost technical computing program; Wolfram|Alpha, the widely used computable knowledge engine; and Wolfram Notebooks, the ultimate environment for technical workflows combining literate programming and interactive publishing on desktop, web and mobile in one unified system. Computation. Knowledge. Content. Interaction. Infrastructure.

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In the Media

Wolfram’s AI Products: Which Tool is Right for You?

Published Mar 11, 2026

Wolfram has developed several features for integrating our technology with LLMs. The major products are chat notebooks, Notebook Assistant, LLM functions, remote MCP server, the MCPServer paclet and AgentOne. With all these offerings, it is confusing to know which one to use. This notebook should help you figure it out. … »

Investigating Validity of AI-Derived Stripped Gluon Amplitudes with Symbolic Computation

Published Mar 6, 2026

A new paper arrived on the ArXiv last week which has generated a lot of attention across social media: “Single-minus gluon tree amplitudes are nonzero.” Within the paper, the authors present various single-minus tree-level n-gluon stripped amplitudes before generalizing the result to arbitrary n > 2. In particular, the authors … »

Understanding Smoke Point in Cooking with Wolfram

Published Mar 3, 2026

When making pancakes, the first one is always tricky. Is the oil in the pan hot enough? Or too hot? If you start too soon, that first pancake is pale and greasy instead of golden brown and toasty. Wait too long and the temperature may reach the oil’s smoke point, … »

Making Wolfram Tech Available as a Foundation Tool for LLM Systems

Published Feb 23, 2026

LLMs don’t—and can’t—do everything. What they do is very impressive—and useful. It’s broad. And in many ways it’s human-like. But it’s not precise. And in the end it’s not about deep computation. So how can we supplement LLM foundation models? We need a foundation tool: a tool that’s broad and general … »

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