From AlphaGO to ChatGPT Public Talk

Ryan McGuinness — Tue, 14 Mar 2023 20:17:46 +0000

From AlphaGO to ChatGPT Public Talk Ryan McGuinness Tue, 03/14/2023 - 16:17

Sponsored by the Faculty of Math Data Science Graduate Programs, please join University of ��ݮ��Ƶ expert in artificial intelligence, Professor Pascal Poupart, for a public talk in which he will describe the key technological advances in recent years which were behind, and ultimately facilitated, these breakthroughs.

In recent years, AlphaGo beat the best human players in the challenging game of Go, large language models such as ChatGPT and GPT-4 converse in a human way while displaying an unprecedented depth of knowledge, DALL-E 2 and Stable Diffusion create realistic images and art from natural language descriptions, the auto industry is rolling out AI-based autonomous driving systems, Alpha Fold 2 predicts the structure of over 200 million proteins to accelerate scientific research and other large foundational models can predict the physical and chemical properties of compounds to accelerate the design of new materials.

While the industry often highlights the increasing size of their models (e.g., billions to trillions of parameters), this gives a false impression that simply throwing a lot of data to large computer clusters in order to train ever larger models is the key. However, important algorithmic advances were necessary to achieve those breakthroughs. Professor Poupart will explain the role that residual optimization and stochastic optimization played to enable deep learning. He will also discuss important advances in reinforcement learning, self-supervised learning and few-shot learning that improved significantly the quality of foundational models.

The success of AI has also led to new challenges in terms of explainability. While most models in advanced AI systems are difficult to interpret, Professor Poupart will also discuss recent advances in probing and conversational agents that can provide some degree of explainability.

Coffee and tea will be provided.

Registration is short, sweet and not mandatory. However, it is strongly encouraged and appreciated so we can anticipate the number of participants and provide you with any updates and information closer to the date - thank you!

Pascal Poupart is a Professor in the David R. Cheriton School of Computer Science at the University of ��ݮ��Ƶ, ��ݮ��Ƶ (Canada). He is also a Canada CIFAR AI Chair at the Vector Institute and a member of the ��ݮ��Ƶ AI Institute. He serves on the advisory board of the AI Institute For Advances in Optimization (2022-present). He served as Research Director and Principal Research Scientist at the ��ݮ��Ƶ 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, Montreal (Canada) in 1998, the M.Sc. in Computer Science at the University of British Columbia, Vancouver (Canada) in 2000 and the Ph.D. in Computer Science at the University of Toronto, Toronto (Canada) in 2005. His research focuses on the development of algorithms for Machine Learning with application to Natural Language Processing and Material Design. 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 Bayesian federated learning, probabilistic deep learning, data efficient reinforcement learning, conversational agents, automated document editing, sport analytics, adaptive satisfiability and CO2 conversion & capture.

Pascal Poupart's Homepage

Innovations and Challenges at a time of Pandemic

Ryan McGuinness — Mon, 14 Sep 2020 15:22:53 +0000

Innovations and Challenges at a time of Pandemic Ryan McGuinness Mon, 09/14/2020 - 11:22

The Centre for Bioengineering and Biotechnology is pleased to present the innovative work of Professor Alexander Wong.

Even when the innovation translation and commercialization is successful, unforeseen events such as the recent COVID-19 pandemic can lead to new challenges as well as opportunities for innovation. In this talk, we will highlight innovations made by the Vision and Image Processing Research Group and DarwinAI, a spin-off from the research group, in an open collaborative initiative for accelerating AI for clinical assistance in a time of pandemic. This talk will feature the journey from taking research innovation from the lab and turning it into an industrial reality holds many challenges, particularly when doing it through the launch a new tech startup.

Alexander Wong is currently the Canada Research Chair in Artificial Intelligence and Medical Imaging, Member of the College of the Royal Society of Canada, co-director of the Vision and Image Processing Research Group, a valued member of the Centre for Bioengineering and Biotechnology, and an associate professor in the Department of Systems Design Engineering at the University of ��ݮ��Ƶ. He has published over 550 refereed journal and conference papers, as well as patents, and have received numerous awards and recognitions for his research and teaching contributions. He is also the co-founder of DarwinAI, an award-winning AI company focused on accelerating deep learning development through explainable AI.

This event will be presented via Webex.

REGISTRATION REQUIRED

The following is the link and password to attend this online event.

Topic: Innovation and Challenges with Alex Wong
Host: Carly Turnbull
Date: Tuesday, September 15, 2020
Time: 1:00 pm, Eastern Daylight Time (New York, GMT-04:00)

Session number: 172 847 5481
Session password: CREATE

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To join the training session
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1. Go to https://uwaterloo.webex.com/uwaterloo/k2/j.php?MTID=tb9810e379aa4cf2231798ac3602f7f14
2. Enter your name and email address.
3. Enter the session password: CREATE
4. Click "Join Now".
5. Follow the instructions that appear on your screen.
To view in other time zones or languages, please click the link
https://uwaterloo.webex.com/uwaterloo/k2/j.php?MTID=t9d02d5f3de47ef42450a100a8428eb27