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Analyzing and Translating an Alien Language: Arrival, Logograms and the Wolfram Language
If aliens actually visited Earth, world leaders would bring in a scientist to develop a process for understanding their language. So when director Denis Villeneuve began working on the science fiction movie Arrival, he and his team turned to real-life computer scientists Stephen and Christopher Wolfram to bring authentic science to the big screen. Christopher specifically was tasked with analyzing and writing code for a fictional nonlinear visual language. On January 31, he demonstrated the development process he went through in a livecoding event you can watch on YouTube.
Announcements & Events
Meet the Authors of Hands-on Start to Wolfram Mathematica, Second Edition
Jeremy Sykes: To celebrate the release of Hands-on Start to Wolfram Mathematica and Programming with the Wolfram Language (HOS2), now in its second edition, I sat down with the authors. Working with Cliff, Kelvin and Michael as the book's production manager has been an easy and engaging process. I'm thrilled to see the second edition in print, particularly now in its smaller, more conveniently sized format.
Announcements & Events
Our Readers’ Favorite Stories from 2016
It's been a busy year here at the Wolfram Blog. We've written about ways to avoid the UK's most unhygienic foods, exciting new developments in mathematics and even how you can become a better Pokémon GO player. Here are some of our most popular stories from the year.
Education & Academic
Gardening à la Gardner
When looking through the posts on Wolfram Community, the last thing I expected was to find exciting gardening ideas.
The general idea of Ed Pegg's tribute post honoring Martin Gardner, "Extreme Orchards for Gardner," is to find patterns for planting trees in configurations with constraints like "25 trees to get 18 lines, each having 5 trees." Most of the configurations look like ridiculous ideas of how to plant actual trees. For example:
Computation & Analysis
Protecting NHS Patients with the Wolfram Language
The UK's National Health Service (NHS) is in crisis. With a current budget of just over £100 billion, the NHS predicts a £30 billion funding gap by 2020 or 2021 unless there is radical action. A key part of this is addressing how the NHS can predict and prevent harm well in advance and deliver a "digital healthcare transformation" to their frontline services, utilizing vast quantities of data to make informed and insightful decisions.
This is where Wolfram comes in. Our UK-based Technical Services Team worked with the British NHS to help solve a specific problem facing the NHS---one many organizations will recognize: data sitting in siloed databases, with limited analysis algorithms on offer. They wanted to see if it was possible to pull together multiple data sources, combining off-the-shelf clinical databases with the hospital trusts' bespoke offerings and mine them for signals. We set out to help them answer questions like "Can the number of slips, trips and falls in hospitals be reduced?"
Education & Academic
Launching Wolfram|Alpha Open Code
Note added 09/29/2021: Some information regarding Wolfram Cloud products described in this post may be outdated. Please visit https://www.wolfram.com/cloud to learn more. Code for Everyone Computational thinking needs to be an integral part of modern education—and today I’m excited to be able to launch another contribution to this goal: Wolfram|Alpha Open Code. Every day, millions […]
Computation & Analysis
Edit Your NaNoWriMo Novel with the Wolfram Language
If you're like many of us at Wolfram, you probably know that November was National Novel Writing Month (NaNoWriMo). Maybe you even spent the past few weeks feverishly writing, pounding out that coming-of-age story about a lonely space dragon that you've been talking about for years.
Congratulations! Now what? Revisions, of course! And we, the kindly Wolfram Blog Team, are here to get you through your revisions with a little help from the Wolfram Language.
Computation & Analysis
New in the Wolfram Language: FeatureExtraction
Two years ago, we introduced the first high-level machine learning functions of the Wolfram Language, Classify and Predict. Since then, we have been creating a set of automatic machine learning functionalities (ClusterClassify, DimensionReduction, etc.). Today, I am happy to present a new function called FeatureExtraction that deals with another important machine learning task: extracting features from data. Unlike Classify and Predict, which follow the supervised learning paradigm, FeatureExtraction belongs to the unsupervised learning paradigm, meaning that the data to learn from is given as a set of unlabeled examples (i.e. without an input -> output relation). The main goal of FeatureExtraction is to transform these examples into numeric vectors (often called feature vectors). For example, let's apply FeatureExtraction to a simple dataset: