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News, Views & Insights

Date Archive: 2018 December

Education & Academic

The Story of Spikey

Spikeys Everywhere We call it “Spikey”, and in my life today, it’s everywhere: It comes from a 3D object—a polyhedron that’s called a rhombic hexecontahedron: But what is its story, and how did we come to adopt it as our symbol?

Stephen Wolfram
Products

’Tis the Season: Reflective Ornaments, Singing Trees & More from Wolfram Community

Wolfram Community continues to grow with innovative projects from Wolfram technology aficionados—our total number of members having recently passed 20,000! Deck the halls with these shiny new examples of the content making our tech-oriented social network thrive, and be sure to post your own Wolfram technology–based projects as well.
Chapin Langenheim, Editor & Web Project Coordinator, Project Management
Education & Academic

The Computational Classroom: Easy Ways to Introduce Computational Thinking into Your Lessons

A version of this post was originally published on the Tech-Based Teaching blog as “Computational Lesson-Planning: Easy Ways to Introduce Computational Thinking into Your Lessons.” Tech-Based Teaching explores the intersections between computational thinking, edtech and learning. Sometimes a syllabus is set in stone. You’ve got to cover X, Y and Z, and no amount of reworking or shifting assignments around can change that. Other factors can play a role too: limited time, limited resources or even a bit of nervousness at trying something new. But what if you’d like to introduce some new ideas into your lessons—ideas like digital citizenship or computational thinking? Introducing computational thinking to fields that are not traditionally part of STEM can sometimes be a challenge, so feel free to share this journey with your children's teachers, friends and colleagues.
Jesika Brooks, Blog Editor - EduTech, Outreach & Communications
Computation & Analysis

Deep Learning and Computer Vision: Converting Models for the Wolfram Neural Net Repository

Julian Francis, a longtime user of the Wolfram Language, contacted us with a potential submission for the Wolfram Neural Net Repository. The Wolfram Neural Net Repository consists of models that researchers at Wolfram have either trained in house or converted from the original code source, curated, thoroughly tested and finally have rendered the output in a very rich computable knowledge format. Julian was our very first user to go through the process of converting and testing the nets.

We thought it would be interesting to interview him on the entire process of converting the models for the repository so that he could share his experiences and future plans to inspire others.
Tuseeta Banerjee, Research Scientist, Machine Learning