March 4, 2015 — Stephen Wolfram

Where should data from the Internet of Things go? We’ve got great technology in the Wolfram Language for interpreting, visualizing, analyzing, querying and otherwise doing interesting things with it. But the question is, how should the data from all those connected devices and everything else actually get to where good things can be done with it? Today we’re launching what I think is a great solution: the Wolfram Data Drop.

Wolfram Data Drop

When I first started thinking about the Data Drop, I viewed it mainly as a convenience—a means to get data from here to there. But now that we’ve built the Data Drop, I’ve realized it’s much more than that. And in fact, it’s a major step in our continuing efforts to integrate computation and the real world.

So what is the Wolfram Data Drop? At a functional level, it’s a universal accumulator of data, set up to get—and organize—data coming from sensors, devices, programs, or for that matter, humans or anything else. And to store this data in the cloud in a way that makes it completely seamless to compute with.

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February 27, 2015 — Vitaliy Kaurov, Technical Communication & Strategy

Martin Handford can spend weeks creating a single Where’s Waldo puzzle hiding a tiny red and white striped character wearing Lennon glasses and a bobble hat among an ocean of cartoon figures that are immersed in amusing activities. Finding Waldo is the puzzle’s objective, so hiding him well, perhaps, is even more challenging. Martin once said, “As I work my way through a picture, I add Wally when I come to what I feel is a good place to hide him.” Aware of this, Ben Blatt from Slate magazine wondered if it’s possible “to master Where’s Waldo by mapping Handford’s patterns?” Ben devised a simple trick to speed up a Waldo search. In a sense, it’s the same observation that allowed Jon McLoone to write an algorithm that can beat a human in a Rock-Paper-Scissors game. As Jon puts it, “we can rely on the fact that humans are not very good at being random.”

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August 1, 2014 — Arnoud Buzing, Director of Quality and Release Management

Earlier this month we released Mathematica 10, a major update to Wolfram’s flagship desktop product. It contains over 700 new functions and improvements to just about every part of the system.

Mathematica + Raspberry Pi

Today I’m happy to announce an update for Mathematica and the Wolfram Language for the Raspberry Pi that brings those new features to the Raspberry Pi. To get the new version of the Wolfram Language, simply run this command in a terminal on your Raspberry Pi:

sudo apt-get update && sudo apt-get install wolfram-engine

This new version will also be pre-installed in the next release of NOOBS, the easy setup system for the Raspberry Pi.

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July 30, 2014 — Wolfram Blog Team

Kenzo Nakamura uses Mathematica to create Escher-inspired mathematical art. His trademark piece, Three-Circle Mandala, depicts a large circle covered by three smaller, repeating circles that form a Sierpinksi gasket.

When Nakamura began using Mathematica, he didn’t originally intend to use it for his artistic endeavors. He found the program by chance at a seminar while looking for the right tool to help him write his master’s thesis.

Now, in addition to using Mathematica for technical and operations research, Nakamura uses it to create Mathematica-derived visual illusions. Although his works are static drawings, their infinite properties create the illusion of movement.

Watch Nakamura discuss using Mathematica to create his drawings, and see a few of his creations.


(YouTube in Japanese)

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July 22, 2014 — Wolfram Blog Team

Conrad Wolfram at TEDxHOP
Photography by Tracy Howl and Paul Clarke

Has our newfound massive availability of data improved decisions and lead to better democracy around the world? Most would say, “It’s highly questionable.”

Conrad Wolfram’s TEDx UK Parliament talk poses this question and explains how computation can be key to the answer, bridging the divide between availability and practical accessibility of data, individualized answers, and the democratization of new knowledge generation. This transformation will be critical not only to government efficiency and business effectiveness—but will fundamentally affect education, society, and democracy as a whole.

Wolfram|Alpha and Mathematica 10 demos feature throughout—including a live Wolfram Language generated tweet.

More about Wolfram’s solutions for your organization’s data »


May 30, 2014 — Wolfram Blog Team

Donald Barnhart is a self-proclaimed mad optical scientist and independent business owner. He’s been developing optical design and analysis software in Mathematica since 1991, he’s the creator of the popular Optica software package, and he’s the developer of the first successful high-resolution holographic instrument that measures three-dimensional velocity fields in fluids.

Now Barnhart has another invention to add to his list of accomplishments: a totally new kind of photo album called the SlideOScope.

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July 20, 2012 — Michael Trott, Chief Scientist

(This is the first post in a three-part series about electrostatic and magnetostatic problems involving sharp edges.)

Mathematica can do a lot of different computations. Easy and complicated ones, numeric and symbolic ones, applied and theoretical ones, small and large ones. All by carrying out a Mathematica program.

Wolfram|Alpha too carries out a lot of computations (actually, tens of millions every day), all specified through free-form inputs, not Mathematica programs. Wolfram|Alpha is heavily based on Mathematica, and many of the mathematical calculations that Wolfram|Alpha carries out rely on the mathematical power of Mathematica. And while Wolfram|Alpha can carry out a vast amount of calculations, it cannot carry out all possible calculations, either because it does not (yet) know how to do a calculation or because the (underlying Mathematica) calculation would take a longer time than available through Wolfram|Alpha. So for a detailed investigation of a more complicated engineering, physics, or chemistry problem, having a copy of Mathematica handy is mandatory.

But there is also the reverse relation between Mathematica and Wolfram|Alpha: Wolfram|Alpha’s knowledge, especially its data knowledge, allows it to carry out investigations and calculations that can substantially increase the power of pure Mathematica. And all of this is because Wolfram|Alpha’s knowledge is accessible through the WolframAlpha[] function within Mathematica.

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August 26, 2011 — Maryka Baraka, Marketing Content Manager

Now that the Computable Document Format (CDF) is officially released, the real fun has begun. At least for me. Whether or not you plan to start using CDF in your own work anytime soon, you’ve got to admit, it’s pretty cool. From publishing textbooks and making complex information easy to understand to recreational games and everyday blogging, CDF truly makes it possible to communicate ideas in a more participatory way—as adopters of the format have already proven.

It has been exciting to see the tremendous interest in CDF following last month’s launch. Although CDF is a new advancement, it’s clear that the possibilities it presents resonate with authors and readers alike, and hence with publishers as well.

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May 17, 2011 — Wolfram Blog Team

Ever wondered how to grill the perfect steak? Or how well dunking food into an ice bath stops the cooking process? Nathan Myhrvold used Mathematica to answer these questions, and many others.

Myhrvold, the first chief technology officer at Microsoft, has had a longtime interest in cooking and has a background in science and technology. When he started using new techniques like sous vide, in which food is slowly cooked in vacuum-sealed bags in water at low temperature, he discovered that many chefs don’t know much about the science behind cooking. He decided to change that with a massive cookbook that was released in March. In 2,438 pages, Modernist Cuisine covers a wide range of cooking techniques and their scientific backgrounds, including heat transfer and the growth of pathogens. (It has recipes, too.)

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March 17, 2011 — Jon McLoone, International Business & Strategic Development

There is an old word game where you try to get from one word to another through connections with other words. For example, you might get from “cold” to “stationary” via the word “frozen”, since “cold” and “frozen” are synonyms and “frozen” and “stationary” are synonyms, albeit for different meanings of the word “frozen”.

I thought of this game when I started to learn the new graph theory functions in Mathematica 8. We can think of the words in the English language as the vertices of one large graph and the synonym connections between them as the graph edges. If you do that, it looks like this:

Synonym connections as graph edges

So let’s see if we can generally solve this synonym chain problem.

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