It is no secret that deep neural networks (DNNs) can achieve state-of-the-art performance in a wide range of complicated tasks. DNN models such as BigGAN, BERT, and GPT 2.0 have proved the high potential of deep learning. Deploying DNNs on mobile devices, consumer devices, drones and vehicles however remains a bottleneck for researchers. For such practical, on-device scenarios, DNNs must have a smaller footprint.
One of the hottest topics at this year’s World Economic Forum in Davos was the wave of automation expected from advances in artificial intelligence (AI), and the consequent displacement of workers. This anticipated realignment was depicted as good or bad news depending on who was speaking and who was listening.
Prof. Alexander Wong of the Systems Design Engineering department at the University of Waterloo is quoted in this article.
AI (Artificial Intelligence) has experienced several periods of severe funding cuts and lack of interest, such as during the 1970s and 1980s. They were called “AI winters,” a reference to the concept of nuclear winter where the sun is blocked from a layer of smoke and dust!
But of course, things are much different nowadays. AI is one of the hottest categories of tech and is a strategic priority for companies like Facebook, Google, Microsoft and many others.
Fakhri Karray, ECE Professor and co-Director of the Waterloo Artificial Intelligence Institute, will be inducted in Gatineau/Ottawa on 30 March 2019 as an Engineering Institute of Canada Fellow for his exceptional contribution to engineering in Canada.