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Brain, Neurons, Cognition: Computational Neuroscience

As the next phase of Wolfram Research's endeavor to make biology computable, we are happy to announce the recent release of neuroscience-related content. The most central part of the human nervous system is the brain. It contains roughly 100 billion neurons that act together to process information, subdivided functionally and structurally into areas specialized for certain tasks. The brain's anatomy, the characteristics of neurons and cognitive maps are used to represent some key aspects of the functional organization and processing abilities of our nervous system. Our new neuroscience content will give you a sneak peek into the amazing world of neuroscience with some facts about brains, neurons and cognition.
Keiko Hirayama, Wolfram|Alpha Developer, Wolfram|Alpha Scientific Content
Education & Academic

New Books on Applications of the Wolfram Language

We're always excited to see new books that illustrate applications of Wolfram technology in a wide range of fields. Below is another set of recently published books using the Wolfram Language to explore computational thinking. From André Dauphiné's outstanding geographical studies of our planet to Romano and Caveliere's work on the geometric optics that help us study the stars, we find a variety of fields served by Wolfram technology.
Michael Gammon, Blog Administrator, Document & Media Systems
Computation & Analysis

How Many Animals and Arp-imals Can One Find in a Random 3D Image?

And How Many Animals, Animal Heads, Human Faces, Aliens and Ghosts in Their 2D Projections?

Introduction

In my recent Wolfram Community post, "How many animals can one find in a random image?," I looked into the pareidolia phenomenon from the viewpoints of pixel clusters in random (2D) black-and-white images. Here are some of the shapes I found, extracted, rotated, smoothed and colored from the connected black pixel clusters of a single 800x800 image of randomly chosen, uncorrelated black-and-white pixels.
Michael Trott, Chief Scientist, Wolfram|Alpha Scientific Content
Best of Blog

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.
Michael Gammon, Blog Administrator, Document & Media Systems
Best of Blog

Exploring a Boxing Legend’s Career with the Wolfram Language: Ali at 75

Muhammad Ali (born Cassius Marcellus Clay Jr.; January 17, 1942--June 3, 2016) is considered one of the greatest heavyweight boxers in history, with a record of 56 wins and 5 losses. He remains the only three-time lineal heavyweight champion, so there's no doubt why he is nicknamed "The Greatest." I used the Wolfram Language to create several visualizations to celebrate his work and gain some new insights into his life. Last June, I wrote a Wolfram Community post about Ali's career. On what would have been The Greatest's 75th birthday, I wanted to take a minute to explore the larger context of Ali's career, from late-career boxing stats to poetry. First, I created a PieChart showing Ali's record:
Jofre Espigulé-Pons, Machine Learning
Computation & Analysis

Automotive Reliability in the Wolfram Language

This post originally appeared on Wolfram Community, where the conversation about reliable cars continues. Be sure to check out that conversation and more---we can't wait to see what you come up with! For the past couple of years, I've been playing with, collecting and analyzing data from used car auctions in my free time with an automotive journalist named Steve Lang to try and get an idea of what the used car market looks like in terms of long-term vehicle reliability. I figured it was about time that I showed off some of the ways that the Wolfram Language has allowed us to parse through information on over one million vehicles (and counting).
Nick Lariviere, Kernel Developer, Algorithms R&D
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