A second-year Waterloo Engineering student shared the top prize at a recent hackathon focused on the creation of technology to protect privacy.
Lena Nguyen of systems design engineering teamed up with Anne Chung, a second-year computer science student at the University of Waterloo, to develop software that puts browsers on kids mode by disabling web page fields asking for sensitive information such as addresses and credit card numbers.
This week, the denizens of Twitter began posting photos of themselves with an odd array of labels. Some, like “face,” were confusingly benign, while others appeared to verify harder truths: Your humble writer was declared a cipher, a nobody, “a person of no influence.” Fair enough. But many of the labels were more troubling. There were rape suspects and debtors. A person would be labeled not just black, but “negro” and “negroid.”
Cancer treatment could be dramatically improved by an invention at the University of Waterloo to precisely locate the edges of tumors during surgery to remove them.
The new imaging technology uses the way light from lasers interacts with cancerous and healthy tissues to distinguish between them in real-time and with no physical contact, an advancement with the potential to eliminate the need for secondary surgeries to get missed malignant tissue.
A Waterloo startup has partnered with a German automotive giant to demonstrate how its artificial intelligence technology can potentially accelerate the development of the electronic brain behind autonomous vehicles.
Artificial neural networks simulate the human brain's ability to make decisions, to learn and to adapt to the environment. A team of engineers at Audi saw a reduction of more than 90 per cent in the number of hours spent processing and refining data for those networks using technology developed by Waterloo-based DarwinAI.
Engineering researchers at the University of Waterloo have unearthed inherent gender and age biases buried in a popular image dataset used to train artificial intelligence (AI) systems around the world.
The discovery will help researchers find ways to rebalance the data so it better reflects demographic diversity, ultimately paving the way for more accurate AI models.