November 20, 2017 — Jon McLoone, Director, Technical Communication & Strategy

The classic board game Risk involves conquering the world by winning battles that are played out using dice. There are lots of places on the web where you can find out the odds of winning a battle given the number of armies that each player has. However, all the ones that I have seen do this by Monte Carlo simulation, and so are innately approximate. The Wolfram Language makes it so easy to work out the exact values that I couldn’t resist calculating them once and for all.

Risk battle odds flow chart

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November 14, 2017 — Stephen Wolfram

A Powerful Way to Express Ideas

People are used to producing prose—and sometimes pictures—to express themselves. But in the modern age of computation, something new has become possible that I’d like to call the computational essay.

I’ve been working on building the technology to support computational essays for several decades, but it’s only very recently that I’ve realized just how central computational essays can be to both the way people learn, and the way they communicate facts and ideas. Professionals of the future will routinely deliver results and reports as computational essays. Educators will routinely explain concepts using computational essays. Students will routinely produce computational essays as homework for their classes.

Here’s a very simple example of a computational essay:

Simple computational essay example

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October 10, 2017 — Etienne Bernard, Lead Architect, Advanced Research Group

Automated Data Science

Imagine a baker connecting a data science application to his database and asking it, “How many croissants are we going to sell next Sunday?” The application would simply answer, “According to your recorded data and other factors such as the predicted weather, there is a 90% chance that between 62 and 67 croissants will be sold.” The baker could then plan accordingly. This is an example of an automated data scientist, a system to which you could throw arbitrary data and get insights or predictions in return.

One key component in making this a reality is the ability to learn a predictive model without specifications from humans besides the data. In the Wolfram Language, this is the role of the functions Classify and Predict. For example, let’s train a classifier to recognize morels from hedgehog mushrooms:

c = Classify[{

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October 4, 2017 — John Fultz, Director of User Interface Technology

Ten months ago, I announced the beginning of our open beta program for Wolfram Player for iOS. The beta is over, and we are now shipping Wolfram Player in the App Store. Wolfram Player for iOS joins Wolfram CDF Player on Windows, Mac and Linux as a free platform for sharing your notebook content with the world.

Wolfram Player

Wolfram Player is the first native computational notebook experience ever on iOS. You can now take your notebooks with you and play them offline. Wolfram Player supports notebooks running interfaces backed by Version 11.1 of the Wolfram Language—an 11.2 release will come shortly. Wolfram Player includes the same kernel that you would find in any desktop or cloud release of the Wolfram Language.

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September 29, 2017
Shadi Ashnai, Manager, Image Processing
Markus van Almsick, Consultant, Algorithms R&D

Microscopes were invented almost four hundred years ago. But today, there’s a revolution in microscopy (as in so many other fields) associated with computation. We’ve been working hard to make the Wolfram Language a definitive platform for the emerging field of computational microscopy.

It all starts with getting an image of some kind—whether from a light or x-ray microscope, transmission electron microscope (TEM), confocal laser scanning microscope (CLSM), two-photon excitation or a scanning electron microscope (SEM), as well as many more. You can then proceed to enhance images, reconstruct objects and perform measurements, detection, recognition and classification. At last month’s Microscopy & Microanalysis conference, we showed various examples of this pipeline, starting with a Zeiss microscope and a ToupTek digital camera.

Microanalysis tools

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September 14, 2017 — Stephen Wolfram

Our Latest R&D Output

I’m excited today to announce the latest output from our R&D pipeline: Version 11.2 of the Wolfram Language and Mathematica—available immediately on desktop (Mac, Windows, Linux) and cloud.

It was only this spring that we released Version 11.1. But after the summer we’re now ready for another impressive release—with all kinds of additions and enhancements, including 100+ entirely new functions:

New functions word cloud

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August 14, 2017 — Jeffrey Bryant, Research Programmer, Wolfram|Alpha Scientific Content

Eclipse paths crossing

The upcoming August 21, 2017, total solar eclipse is a fascinating event in its own right. It’s also interesting to note that on April 8, 2024, there will be another total solar eclipse whose path will cut nearly perpendicular to the one this year.

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August 8, 2017 — Jeffrey Bryant, Research Programmer, Wolfram|Alpha Scientific Content

Eclipse illustrations with the Wolfram Language

On August 21, 2017, an event will happen across parts of the Western Hemisphere that has not been seen by most people in their lifetimes. A total eclipse of the Sun will sweep across the face of the United States and nearby oceans. Although eclipses of this type are not uncommon across the world, the chance of one happening near you is quite small and is often a once-in-a-lifetime event unless you happen to travel the world regularly. This year, the total eclipse will be within driving distance of most people in the lower 48 states.

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July 19, 2017 — Stephen Wolfram

The Philosophy of Chemicals

“We’ve just got to decide: is a chemical like a city or like a number?” I spent my day yesterday—as I have for much of the past 30 years—designing new features of the Wolfram Language. And yesterday afternoon one of my meetings was a fast-paced discussion about how to extend the chemistry capabilities of the language.

At some level the problem we were discussing was quintessentially practical. But as so often turns out to be the case for things we do, it ultimately involves some deep intellectual issues. And to actually get the right answer—and to successfully design language features that will stand the test of time—we needed to plumb those depths, and talk about things that usually wouldn’t be considered outside of some kind of philosophy seminar.

Thinker

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June 29, 2017 — Swede White, Media & Communications Specialist

Revolutionary social networks lead image

As the Fourth of July approaches, many in America will celebrate 241 years since the founders of the United States of America signed the Declaration of Independence, their very own disruptive, revolutionary startup. Prior to independence, colonists would celebrate the birth of the king. However, after the Revolutionary War broke out in April of 1775, some colonists began holding mock funerals of King George III. Additionally, bonfires, celebratory cannon and musket fire and parades were common, along with public readings of the Declaration of Independence. There was also rum.

Today, we often celebrate with BBQ, fireworks and a host of other festivities. As an aspiring data nerd and a sociologist, I thought I would use the Wolfram Language to explore the Declaration of Independence using some basic natural language processing.

Using metadata, I’ll also explore a political network of colonists with particular attention paid to Paul Revere, using built-in Wolfram Language functions and network science to uncover some hidden truths about colonial Boston and its key players leading up to the signing of the Declaration of Independence.

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