CARTE Industry Speaker Seminar: Building the Next Generation Interactive Devices
April 9, 2021 12:00-1:00 PM
On April 9th, The Centre for Analytics and AI Engineering (CARTE) hosts Dr. Afsaneh Fazly, Research Director at the Samsung Toronto AI Centre.
Register through this link.
Abstract: Wouldn’t we all love to seamlessly communicate and interact with our cell phones, smart watches, and even our home appliances? This is indeed the holy grail of AI: to build machines and systems that can think, behave, and communicate in a way that is indistinguishable from human intelligent behaviour (the Turing test). The AI community has long realized that effectively and truly passing the Turing test is extremely difficult, if not close to impossible. As such, for the past few decades, AI researchers have focused on solving fundamental problems in separate sub-fields of AI, such as computer vision, computational linguistics, machine learning, planning, and reasoning (to name a few). With the recent advances in these areas, we are finally at a point where we can bring the puzzle pieces of AI together to build wholistic multi-faceted and multi-modal systems that actually work in practise, hence the recent surge in industry investment and interest in AI. In this talk, I will first give a high-level overview of how AI research is key to the success of an innovative company such as Samsung. I will then go over some of our efforts at the Samsung AI Centre in Toronto around building multi-modal communication and understanding systems that will pave the way for next generation human–machine interaction.
Speaker Bio: Afsaneh Fazly is currently a Research Director at the Samsung Toronto AI Centre, leading a team of outstanding scientists and engineers on a variety of projects at the intersection of vision and language. Afsaneh has extensive experience in both academia and the industry, publishing award-winning papers, and building strong teams solving real-world problems. Her research draws on many subfields of AI, including Computational Linguistics, Cognitive Science, Computational Vision, and Machine Learning. She strongly believes that solving many of today’s real-world problems requires an interdisciplinary approach that can bridge the gap between machine intelligence and human cognition. Prior to joining Samsung Research, Afsaneh worked at several Canadian companies where she helped build and lead teams of scientists and engineers solving a diverse set of AI problems. Prior to that, she was a Research Scientist and Course Instructor at the University of Toronto, where she received her PhD from.