Almost as mysteriously as it disappeared 36 years ago, University of Waterloo’s Faculty of Mathematics’ giant 85-foot Pink Tie has made a return.
The unofficial symbol for the Faculty, the Pink Tie, first appeared outside the Mathematics and Computer Building, which was officially opened in 1968.
According to the Legend of the Pink Tie, it was the subject of sabotage and was eventually nicked in 1984 by an organization calling itself The Tie Liberation Organization.
“I wasn’t necessarily entrepreneurial in my time at Waterloo, but I was always very inventive,” remembered Jeff Shiner (BMath ’92), the CEO of a growing Toronto-based startup. “All I knew was that I wanted to create new computer programs.”
As Shiner came of age with the personal computer, he taught himself programming languages. “I remember getting my first Commodore 64 when I was 12 or 13 years old,” he says. “I geeked out at everything related to the computer. When it came time to decide on a university, Waterloo Math’s computer science program was the only one on my radar.”
The faculty is now the first Faculty of Mathematics to hold Sponsoring Institutional Membership of the Association for Women in Mathematics (AWM).
AWM encourages women and girls to study and to have active careers in the mathematical sciences, and to promote equal opportunity and the equal treatment of women and girls in the mathematical sciences.
Artificial neural networks have come to dominate the field of artificial intelligence. From self-driving cars to devices that recognize handwriting to interactive chatbots to astonishingly accurate online translators, artificial neural networks lie at the core of a staggering array recent AI developments.
Researchers have developed a new method to make machine learning more efficient.
The technique, called “less-than-one-shot learning,” can train an AI model to accurately identify more objects than the number it was trained on – a huge shift from the expensive, time-consuming process that currently requires thousands of examples of one object for an accurate identification.
