AI & Fundamentals
Are we experiencing a technological singularity? - Pascal Poupart, Professor, University of Waterloo

Pascal Poupart image

DATE: Thu, October 22, 2020 - 2:00 pm

LOCATION: Please register to receive the Zoom link

DETAILS

 

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Abstract:

Ever since mathematician I.J. Good speculated about the conception of a first ultra intelligent machine in 1965, it has been hypothesized that a technological singularity will occur when the invention of artificial superintelligence will abruptly trigger runaway technological growth. Increasing computational resources and network connectivity coupled with the accumulation of large amounts of data and advances in machine learning are fueling beliefs that unbounded self-evolving systems will soon emerge. In this seminar, Pascal Poupart will discuss recent advances in machine learning that are enabling increasingly adaptive systems as well as important limitations that still need to be overcome.

 

Bio:

Pascal Poupart is a Professor in the David R. Cheriton School of Computer Science at the University of Waterloo and a Canada CIFAR AI Chair at the Vector Institute. He served as Research Director and Principal Research Scientist at the Waterloo Borealis AI Research Lab funded by the Royal Bank of Canada (2018-2020). He also served as scientific advisor for ProNavigator (2017-2019), ElementAI (2017-2018) and DialPad (2017-2018). He received the B.Sc. in Mathematics and Computer Science at McGill University in 1998, the M.Sc. in Computer Science at the University of British Columbia in 2000 and the Ph.D. in Computer Science at the University of Toronto in 2005. His research focuses on the development of algorithms for Machine Learning with application to Natural Language Processing, Health Informatics, Computational Finance, Telecommunication Networks and Sports Analytics. He is most well known for his contributions to the development of Reinforcement Learning algorithms. Notable projects that his research team are currently working on include probabilistic deep learning, robust machine learning, data efficient reinforcement learning, conversational agents, automated document editing, adaptive satisfiability, sports analytics and knowledge graphs.

Pascal Poupart received a Canada CIFAR AI Chair (2018), Cheriton Faculty Fellowship (2015-2018), a best student paper honourable mention (SAT-2017), a silver medal at the SAT-2017 competition, a top reviewer award (ICML-2016), a gold medal at the SAT-2016 competition, a best reviewer award (NIPS-2015), an Early Researcher Award from the Ontario Ministry of Research and Innovation (2008), two Google research awards (2007-2008), a best paper award runner up (UAI-2008) and the IAPR best paper award (ICVS-2007). He serves as member of the editorial board of the Journal of Machine Learning Research (JMLR) (2009 - present) and guest editor for the Machine Learning Journal (MLJ) (2012 - present). He routinely serves as area chair or senior program committee member for NIPS, ICML, AISTATS, IJCAI, AAAI and UAI.


 

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