Date & Time:
March 18, 2021 1:00 pm – 2:00 pm
Live Stream
03/18/2021 01:00 PM 03/18/2021 02:00 PM America/Chicago Mengye Ren (U. of Toronto) – Steps Towards Making Machine Learning More Natural Live Stream

Steps Towards Making Machine Learning More Natural

Watch via live stream

Over the past decades, we have seen machine learning making great strides in AI applications. Yet, most of its success relies on training models offline on a massive amount of data and evaluating them in a similar test environment. By contrast, humans can learn new concepts and skills with very few examples, and can easily generalize to novel tasks. In this talk, I will highlight three key steps towards making machines learning more human-like, and these steps will unlock the next generation of technologies. The first step is to make machines learn new concepts continually and incrementally using limited labeled data. The second step is to develop flexible representations that can generalize well to novel concepts under different contexts. Finally, I'll show how to make abstract and compositional reasoning given visual inputs. I'll then conclude with an outlook of future directions towards building a more general and flexible AI.

Host: Sanjay Krishnan

Mengye Ren

PhD Student, University of Toronto

Mengye Ren is a PhD student in the machine learning group of the Department of Computer Science at the University of Toronto. He was also a research scientist at Uber ATG working on self-driving cars from 2017 to 2021. His research focuses on making machines learn in more naturalistic environments with less labeled data. He has won a number of awards including two NVIDIA research pioneer awards and the Alexander Graham Bell Canada Graduate Fellowship.

Related News & Events


“Machine Learning Foundations Accelerate Innovation and Promote Trustworthiness” by Rebecca Willett

Jan 26, 2024

Nightshade: Data Poisoning to Fight Generative AI with Ben Zhao

Jan 23, 2024
In the News

In The News: U.N. Officials Urge Regulation of Artificial Intelligence

"Security Council members said they feared that a new technology might prove a major threat to world peace."
Jul 27, 2023
UChicago CS News

UChicago Computer Scientists Bring in Generative Neural Networks to Stop Real-Time Video From Lagging

Jun 29, 2023
UChicago CS News

Computer Science Displays Catch Attention at MSI’s Annual Robot Block Party

Apr 07, 2023
UChicago CS News

UChicago, Stanford Researchers Explore How Robots and Computers Can Help Strangers Have Meaningful In-Person Conversations

Mar 29, 2023
UChicago CS News

Postdoc Alum John Paparrizos Named ICDE Rising Star

Mar 15, 2023
UChicago CS News

New EAGER Grant to Asst. Prof. Eric Jonas Will Explore ML for Quantum Spectrometry

Mar 03, 2023
UChicago CS News

Assistant Professor Chenhao Tan Receives Sloan Research Fellowship

Feb 15, 2023
UChicago CS News

UChicago Scientists Develop New Tool to Protect Artists from AI Mimicry

Feb 13, 2023
In the News

Professors Rebecca Willett and Ben Zhao Discuss the Future of AI on Public Radio

Jan 26, 2023
UChicago CS News

UChicago Launches Transform Accelerator for Data Science & Emerging AI Startups

Jan 19, 2023
arrow-down-largearrow-left-largearrow-right-large-greyarrow-right-large-yellowarrow-right-largearrow-right-smallbutton-arrowclosedocumentfacebookfacet-arrow-down-whitefacet-arrow-downPage 1CheckedCheckedicon-apple-t5backgroundLayer 1icon-google-t5icon-office365-t5icon-outlook-t5backgroundLayer 1icon-outlookcom-t5backgroundLayer 1icon-yahoo-t5backgroundLayer 1internal-yellowinternalintranetlinkedinlinkoutpauseplaypresentationsearch-bluesearchshareslider-arrow-nextslider-arrow-prevtwittervideoyoutube