Brian Wood

Doing Data Science Better with Wolfram and the Multiparadigm Approach

May 23, 2019 — Brian Wood, Lead Technical Marketing Writer, Document and Media Systems

Just as Wolfram was doing AI before it was cool, so have we been doing data science since before it was mainstream. A prime example is the creation of Wolfram|Alpha—a massive project that involved engineering, modeling, analyzing, visualizing and interfacing with terabytes of data, developing a natural language interface, and deploying results in a sensible way. Wolfram|Alpha itself is a tool for doing data science, and its continued success is largely because of the underlying strategy we used to build it: a multiparadigm approach driven by natural curiosity, exploring all kinds of data, using advanced methods from a range of areas and automating as much as possible.

Any approach to data science can only be as effective as the computational tools driving it; luckily for us, we had the Wolfram Language at our disposal. Leveraging its universal symbolic representation, high-level automation and human readability—as well as its broad range of built-in computation, knowledge and interfaces—streamlined our process to help bring Wolfram|Alpha to fruition. In this post, I’ll discuss some key tenets of the multiparadigm approach, then demonstrate how they combine with the computational intelligence of the Wolfram Language to make the ideal workflow for not only discovering and presenting insights from your data, but also for creating scalable, reusable applications that optimize your data science processes.

Doing Data Science Better with Wolfram and the Multiparadigm Approach

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Stephen Wolfram

Launching Today: Free Wolfram Engine for Developers

May 21, 2019 — Stephen Wolfram

Why Aren’t You Using Our Technology?

It happens far too often. I’ll be talking to a software developer, and they’ll be saying how great they think our technology is, and how it helped them so much in school, or in doing R&D. But then I’ll ask them, “So, are you using Wolfram Language and its computational intelligence in your production software system?” Sometimes the answer is yes. But too often, there’s an awkward silence, and then they’ll say, “Well, no. Could I?”

Free Wolfram Engine for DevelopersI want to make sure the answer to this can always be: “Yes, it’s easy!” And to help achieve that, we’re releasing today the Free Wolfram Engine for Developers. It’s a full engine for the Wolfram Language, that can be deployed on any system—and called from programs, languages, web servers, or anything.

The Wolfram Engine is the heart of all our products. It’s what implements the Wolfram Language, with all its computational intelligence, algorithms, knowledgebase, and so on. It’s what powers our desktop products (including Mathematica), as well as our cloud platform. It’s what’s inside Wolfram|Alpha—as well as an increasing number of major production systems out in the world. And as of today, we’re making it available for anyone to download, for free, to use in their software development projects.

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Stephen Wolfram

Wolfram|Alpha at 10

May 18, 2019 — Stephen Wolfram

Wolfram|Alpha at 10

The Wolfram|Alpha Story

Today it’s 10 years since we launched Wolfram|Alpha. At some level, Wolfram|Alpha is a never-ending project. But it’s had a great first 10 years. It was a unique and surprising achievement when it first arrived, and over its first decade it’s become ever stronger and more unique. It’s found its way into more and more of the fabric of the computational world, both realizing some of the long-term aspirations of artificial intelligence, and defining new directions for what one can expect to be possible. Oh, and by now, a significant fraction of a billion people have used it. And we’ve been able to keep it private and independent, and its main website has stayed free and without external advertising.

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Posted in: History, Wolfram|Alpha

Dorian Birraux
Arnoud Buzing

Announcing the Wolfram Client Library for Python

May 16, 2019
Dorian Birraux, Engine Connectivity Engineering
Arnoud Buzing, Director of Quality and Release Management

Get Full Access to the Wolfram Language from Python

The Wolfram Language gives programmers a unique computational language with an enormous array of sophisticated algorithms and built-in real-world knowledge. For many years, people have asked us how to access all the power of our technology from other software environments and programming languages. And over the years, we have built many such connections, like Wolfram CloudConnector for Excel, WSTP (Wolfram Symbolic Transfer Protocol) for C/C++ programs and, of course, J/Link, which provides access to the Wolfram Language directly from Java.

So today we’re happy to formally announce a new and often-requested connection that allows you to call the Wolfram Language directly and efficiently from Python: the Wolfram Client Library for Python. And, even better, this client library is fully open source as the WolframClientForPython git repository under the MIT License, so you can clone it and use it any way you see fit.

Announcing the Wolfram Client Library for Python

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Stephen Wolfram

What We’ve Built Is a Computational Language (and That’s Very Important!)

May 9, 2019 — Stephen Wolfram

Wolfie

What Kind of a Thing Is the Wolfram Language?

I’ve sometimes found it a bit of a struggle to explain what the Wolfram Language really is. Yes, it’s a computer language—a programming language. And it does—in a uniquely productive way, I might add—what standard programming languages do. But that’s only a very small part of the story. And what I’ve finally come to realize is that one should actually think of the Wolfram Language as an entirely different—and new—kind of thing: what one can call a computational language.

So what is a computational language? It’s a language for expressing things in a computational way—and for capturing computational ways of thinking about things. It’s not just a language for telling computers what to do. It’s a language that both computers and humans can use to represent computational ways of thinking about things. It’s a language that puts into concrete form a computational view of everything. It’s a language that lets one use the computational paradigm as a framework for formulating and organizing one’s thoughts.

It’s only recently that I’ve begun to properly internalize just how broad the implications of having a computational language really are—even though, ironically, I’ve spent much of my life engaged precisely in the consuming task of building the world’s only large-scale computational language.

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Tuseeta Banerjee

Neural Networks: An Introduction

May 2, 2019 — Tuseeta Banerjee, Research Scientist, Machine Learning

If you haven’t used machine learning, deep learning and neural networks yourself, you’ve almost certainly heard of them. You may be familiar with their commercial use in self-driving cars, image recognition, automatic text completion, text translation and other complex data analysis, but you can also train your own neural nets to accomplish tasks like identifying objects in images, generating sequences of text or segmenting pixels of an image. With the Wolfram Language, you can get started with machine learning and neural nets faster than you think. Since deep learning and neural networks are everywhere, let’s go ahead and explore what exactly they are and how you can start using them.

Explaining neural networks

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Tim Shedelbower

The Art of Connecting the Dots with the Wolfram Language

April 26, 2019 — Tim Shedelbower, Visualization Developer, Algorithms R&D

Connect the dots. It was exciting to draw from number to number until the sudden discovery of a hidden cartoon. That was my inadvertent introduction to graph theory very early in school. Little did I know adults used the same concept to discover hidden patterns to solve problems, such as proving that a single crossing of seven Königsberg bridges to four land masses is not possible, but coloring a map distinctly with four colors is. These problems inspired the methods we know today as graph theory. And in honor of the work of late mathematician and connect-the-dot author Elwyn Berlekamp, we see how sophisticated this “child’s play” can be by examining the different styles and themes we can apply to graphs.

Connect the dots with Graph and PlotTheme

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Stephen Wolfram

Version 12 Launches Today! (And It’s a Big Jump for Wolfram Language and Mathematica)

April 16, 2019 — Stephen Wolfram

The Road to Version 12

Today we’re releasing Version 12 of Wolfram Language (and Mathematica) on desktop platforms, and in the Wolfram Cloud. We released Version 11.0 in August 2016, 11.1 in March 2017, 11.2 in September 2017 and 11.3 in March 2018. It’s a big jump from Version 11.3 to Version 12.0. Altogether there are 278 completely new functions, in perhaps 103 areas, together with thousands of different updates across the system:

Version 12 launches today

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Swede White

Fishackathon: Protecting Marine Life with AI and the Wolfram Language

April 11, 2019 — Swede White, Public Relations Manager

Fishackathon

Every year, the U.S. Department of State sponsors a worldwide competition called Fishackathon. Its goal is to protect life in our waters by creating technological solutions to help solve problems related to fishing.

The first global competition was held in 2014 and has been growing massively every year. In 2018 the winning entry came from a five-person team from Boston, after competing against 45,000 people in 65 other cities spread across 5 continents. The participants comprised programmers, web and graphic designers, oceanographers and biologists, mathematicians, engineers and students who all worked tirelessly over the course of two days.

To find out more about the winning entry for Fishackathon in 2018 and how the Wolfram Language has helped make the seas safer, we sat down with Michael Sollami to learn more about him and his team’s solution to that year’s challenge.

Wolfram Language at Fishackathon

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Alec Titterton

Wolfram and the Raspberry Pi Foundation Collaborate on Free Access to Educational Project Materials

April 9, 2019 — Alec Titterton, CBM Content Development Manager, European Sales

Wolfram Research is pleased to announce further collaboration with the Raspberry Pi Foundation as part of supporting makers across the world through education. A collection of 10 Wolfram Language projects has been launched on the foundation’s projects site. These projects range from creating weather dashboards to building machine learning classifiers to using AI for facial recognition. The goal is to put the power of computational intelligence into the hands of anyone who wants access—democratizing the skills that will increasingly be needed to innovate and discover what is possible with modern computation.

By providing easy-to-follow, step-by-step tutorials that result in a finished, functioning piece of software, Wolfram aims to lower the barrier of entry for those who wish to get immediately started programming, building and making. Projects can be completely built on the Raspberry Pi or within a web browser in the Wolfram Cloud.

Wolfram and Raspberry Pi join forces

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