Autonomous Vehicles

A leading machine learning expert and CEO of a self-driving car startup, the University of Toronto’s Raquel Urtasun recently shared some of the secrets to her success in a Globe and Mail article highlighting five Canadian women who are breaking down gender barriers in the automotive industry.

“It’s a combination of very strategic problem solving, never ever giving up, and building an incredible team around me,” Urtasun, a professor of computer science in the Faculty of Arts & Science, told the Globe. “Because it’s not about me, it’s about what together we can do.”

Urtasun, whose startup Waabi has raised more than $100 million in initial financing, noted that women often have to do “ten times more” than male counterparts to be recognized. She also expressed her belief that diversity in hiring needs to focus on career pathways rather than merely placing people in jobs. “It’s not about how many leaders you have, it’s about, do you have a path for them to be reaching up?” she said.

She added that she hopes her efforts with Waabi will leave behind a positive legacy – both through the company’s self-driving technology as well as its own hiring practices. “When I retire one day, I want to look back and say that all this effort and all the things I did were for a reason and impacted the world in a positive manner. We provided change. We provided opportunities for people. We provided a better life for people.”

Read the article in the Globe and Mail

�鶹ֱ��app student-led team wins international self-driving car challenge for second year in a row

geoff.vendeville — Fri, 07 Jun 2019 18:41:34 +0000

�鶹ֱ��app student-led team wins international self-driving car challenge for second year in a row

geoff.vendeville Fri, 06/07/2019 - 14:41

Cutline

aUToronto's converted Chevy Bolt EV, Zeus, drives autonomously through MCity, a simulated town at the University of Michigan, as part of the international AutoDrive Challenge (photo courtesy of aUToronto)

Liz Do

Topic

Our Community

Artificial Intelligence

Autonomous Vehicles

Computer Science

Faculty of Applied Science & Engineering

Faculty of Arts & Science

Graduate Students

Undergraduate Students

UTIAS

The aUToronto team has done it again.

The University of Toronto's only student-led self-driving car team, composed of engineering and computer science students, edged out seven other universities during the second instalment of the AutoDrive Challenge in Michigan last week.

The three-year international competition challenges universities across North America to turn an Chevy Bolt EV into a self-driving car by 2020. The second year of the competition took place in Ann Arbor and pitted �鶹ֱ��app against Kettering University, Michigan State University, Michigan Tech University, North Carolina A & T State University, Texas A & M University, University of Waterloo and Virginia Tech.

"I am extremely proud of our team,” said faculty advisor Tim Barfoot, a professor at �鶹ֱ��app's Institute for Aerospace Studies (UTIAS). “It was fantastic to see all their hard work pay off. The car performed pretty much exactly as planned. The team really came together and did a brilliant job of supporting each other."

aUToronto is composed of �鶹ֱ��app engineering and computer science undergraduate and graduate students (photo courtesy of aUToronto)

This year’s competition “focused on urban environment driving scenarios in static and dynamic objects.” The teams had to complete four driving challenges that demonstrated the vehicles’ autonomous capabilities by obeying traffic signs, traffic lights at intersections, as well as navigating pedestrian crosswalks.

The final challenge took place at MCity, a simulated town built at the University of Michigan for self-driving vehicle testing.

“We performed perfectly on the traffic sign challenge, with a flawless parking job at the end,” says technical team lead Keenan Burnett, a �鶹ֱ��app engineering science graduate who's now pursuing a master's at UTIAS. “During the MCity challenge, we made it the farthest out of all the teams.”

Burnett says the key to their win was their many enhancements to �鶹ֱ��app's self-driving car, Zeus, over the past year. These included the use of lidar (light detection and ranging) localization to precisely determine the car’s position, and employing deep neural networks to correctly detect pedestrians and traffic lights. To do this, they collected a data set of more than 70,000 images.

The team placed first in all but one of the nine judging categories. They received top marks in social responsibility, the mapping challenge, pedestrian challenge, MCity challenge and more. They were runners-up in concept design.

“We are very proud of the work we've done so far and have our eyes on the future,” says Burnett. In preparation for the final competition next year, the team will begin improving Zeus’ object-detection capabilities and focus on developing a fully reliable and safe operating system.

“I think we have a good shot at year three,” adds Burnett. “We hope to test Zeus on public roads sometime in the next year.”

These �鶹ֱ��app experts in AI want to teach you how to program a self-driving car

noreen.rasbach — Wed, 30 Jan 2019 14:43:31 +0000

These �鶹ֱ��app experts in AI want to teach you how to program a self-driving car

noreen.rasbach Wed, 01/30/2019 - 09:43

Cutline

Jonathan Kelly and Steven Waslander are the instructors behind a new set of online courses on programming self-driving cars (image courtesy of Coursera)

Tyler Irving

Topic

Our Community

Autonomous Vehicles

Faculty of Applied Science & Engineering

Institute for Aerospace Studies

Two experts in autonomous vehicles from the University of Toronto’s Faculty of Applied Science & Engineering have partnered with Coursera to offer a four-course specialization in self-driving cars.

“The interest in autonomous driving is exploding,” says Steven Waslander, an associate professor at the University of Toronto Institute for Aerospace Studies (UTIAS).

“The investments have been phenomenal – every student I have trained in this area has had multiple job offers. There is a massive opportunity to contribute to this domain.”

Jonathan Kelly, an assistant professor at UTIAS, points out that self-driving cars have the potential to increase road safety, lead to more efficient use of roadways and vehicles, and even reduce pollution.

“We want to see this industry come to fruition,” says Kelly. “The Coursera platform enables us to reach as big an audience as possible.”

The specialization is aimed at learners who already have some engineering experience, including upper-year undergraduates, as well as graduates looking to upgrade their qualifications or enter a new field.

Through online video lectures, programming exercises and open-source simulation software, students will learn how to assemble the full software stack required to define the operations of an autonomous vehicle.

By the end of the first course, Waslander says students will have taught a virtual car to drive itself around a simulated racetrack. “We want to get people up and running quickly, giving them a broad sweep of every aspect of self-driving car development – how you process the data from sensors, estimate the car’s location, plan its next move and issue commands to drive the wheels,” he says.

That may sound straightforward, but both Waslander and Kelly caution that applying these principles in the uncontrolled environment of real-world driving is incredibly complex.

“I think you’d be hard-pressed to find a more challenging engineering problem than designing robust self-driving cars,” says Kelly. “But that challenge is very exciting. It forces you to think about new ways of doing things. And the more people we have doing it, the greater our chances of success.”

“Our courses are really meant as a starting point,” says Waslander. “They’ll get you into this world, but there are many ways that you can deepen your knowledge and experience from there.”

The first of the four courses, Introduction to Self-Driving Cars, is available now on the Coursera platform. Three others, to be launched in the coming weeks, include:

State Estimation and Localization for Self-Driving Cars
Visual Perception for Self-Driving
Motion Planning for Self-Driving

“Self-driving cars will reshape our cities and our lives, in the process creating tens of thousands of new jobs for those who have the right skills,” says Jeff Maggioncalda, CEO of Coursera. “We’re excited to partner with the University of Toronto, a top-ranked leader in autonomous vehicle research, to train the next generation of engineers who will bring safe, autonomous vehicles to public roads.”

To develop the courses, Waslander and Kelly drew on more than 30 years of combined experience in autonomous robotics research.

As a graduate student, Waslander worked on some of the first quadcopter aerial robots, programming them to navigate challenges without human intervention. Eventually, he moved on to ground-based vehicles such as the Autonomoose, an autonomous car that drove more than 100 kilometres on public roads in Ontario last summer.

Kelly has focused his research on autonomous robotic systems for a wide range of tasks, from space exploration to elder care. He and his team have also collaborated with a local industrial partner to develop a low-cost retrofit for electric wheelchairs that automates complex tasks, such as navigating doorways or docking behind a desk.

Kelly and Waslander are both excited by the chance to share their knowledge with a broader audience.

“In a couple of years, I would love to see a montage of the people who have completed this course talking about the impact they are having in their jobs,” says Kelly. “There are a lot of challenges to address, and we’re grateful for the opportunity to get more people involved in addressing them.”

�鶹ֱ��app's Angela Schoellig named to MIT's list of Innovators Under 35

ullahnor — Wed, 16 Aug 2017 14:38:09 +0000

�鶹ֱ��app's Angela Schoellig named to MIT's list of Innovators Under 35

ullahnor Wed, 08/16/2017 - 10:38

Cutline

Professor Angela Schoellig demonstrates a drone that can land on water to take environmental samples (photo by Tyler Irving)

Tyler Irving

Author legacy

Tyler Irving

Topic

Breaking Research

Faculty of Applied Science & Engineering

Subheadline

Engineering researcher recognized by MIT Technology Review

Assistant Professor Angela Schoellig of the University of Toronto Institute for Aerospace Studies (UTIAS) has been named one of the world’s top Innovators Under 35 by MIT Technology Review.

The Faculty of Applied Science & Engineering's Schoellig works on control theory and applying machine learning to drones, autonomous vehicles and other robots.

“It’s an honour,” says Schoellig of the publication's recognition. “To be named among this group of luminaries comes as a wonderful surprise. It’s also great for my students and postdoctoral researchers, because it’s really about their work as well.”

As a child, Schoellig was captivated by mathematics. During her master’s degree, she studied mathematical models that could describe everything from the chemical reactions in a living cell to the movements of birds. When she learned that mathematical algorithms could also be used to program robots, she was hooked.

“I really wanted to do something where you directly see the impact and the result,” she says.

As a PhD student at ETH Zurich, where she worked under the supervision of robotics pioneer and �鶹ֱ��app engineering alumnus Raffaello D’Andrea, Schoellig and her colleagues worked on software that could enable flying robots to execute a triple flip in the air, as well as other acrobatics. But she quickly discovered that the algorithms alone weren’t enough.

“The model that we had would not provide enough information for the robot to do the task,” she says. “You need to use the data from previous runs to improve the task execution, which gets you closer to how humans learn things.”

In other words, she needed to apply machine learning to robots.

Machine learning, a form of artificial intelligence, has become a common part of our lives – it’s what enables smartphones to recognize voice commands and computer programs to recognize faces in photos. But teaching a robot is a very different challenge from teaching a computer.

“If a computer doesn’t recognize a face, that’s not a big deal,” says Schoellig. “But if a robot makes a mistake, it could crash. While you can train a computer on millions of photos, getting that amount of data for a robot is very expensive and difficult.”

One of Schoellig’s biggest challenges is designing algorithms that are flexible enough to enable robots to experiment but rigid enough to ensure that they will be safe while they are learning the new task.

Another major challenge Schoellig works on is handling dynamic environments, where conditions change over time. One of her current projects aims to enable autonomous drones to make deliveries to remote locations, such as communities in Canada’s north. These drones would need to adapt to changing wind speeds and light conditions that make navigation difficult.

Schoellig also has projects in the mining and environmental monitoring sectors, such as developing a drone that can land on water and take samples to track pollution levels. She is even looking at the possibility of using drones to deliver automated external defibrillators (AEDs) to treat patients suffering cardiac arrest.

For Schoellig, smarter robots have the potential to make our lives better and easier.

“We hear a lot about how robots will replace humans, but that’s not how I see it,” she says. “Humans have always built tools to help them to advance, from a simple hammer to a computer. We couldn’t predict in the 1970s how computers would change our society. I think we are at a similar point with robotics, and I’m excited to see what creative ideas will emerge.”

Two �鶹ֱ��app scholars awarded Sloan Research Fellowships

ullahnor — Tue, 21 Feb 2017 15:37:01 +0000

Two �鶹ֱ��app scholars awarded Sloan Research Fellowships

ullahnor Tue, 02/21/2017 - 10:37

Cutline

Angela Schoellig, an assistant professor at the University of Toronto Institute for Aerospace Studies, is one of two �鶹ֱ��app researchers receiving a Sloan Research Fellowship

Jennifer Robinson

Author legacy

Jennifer Robinson

Topic

Breaking Research

Autonomous Vehicles

Computer Science

Faculty of Applied Science & Engineering

Faculty of Arts & Science

A robotics expert using machine learning to improve autonomous aerial vehicles and a mathematician specializing in computational complexity theory from the University of Toronto are among 126 researchers awarded Sloan Research Fellowships this year.

Angela Schoellig, an assistant professor at the University of Toronto Institute for Aerospace Studies (UTIAS), and Benjamin Rossman, an assistant professor of mathematics and computer science, will each receive USD $60,000 over a two-year period to stimulate their fundamental research.

“This is both an incredible honour and very humbling,” said Schoellig. “It really is recognition of the work of my entire research group and all of my collaborators – both current and past. This award will enable us to focus on new exciting directions in the development of machine learning algorithms for robotics.”

The Alfred P. Sloan Foundation said in a news release today that the early-career scholars chosen this year represent the most promising scientific researchers working today. The Sloan fellowships are made “in recognition of distinguished performance and a unique potential to make substantial contributions to their field.”

Assistant Professor Benjamin Rossman, one of two �鶹ֱ��app researchers who will receive this year's Sloan Research Fellowship, specializes in showing that certain computational problems are inherently difficult to solve

“�鶹ֱ��app congratulates our researchers on receiving this prestigious North America-wide award," said Vivek Goel, �鶹ֱ��app’s vice-president of research and innovation. "We’d also like to thank the Sloan Foundation for once again recognizing and supporting the excellence of �鶹ֱ��app scholars of outstanding promise.”

Schoellig, who heads the Faculty of Applied Science & Engineering's Dynamic Systems Lab and is associate director of the Centre for Aerial Robotics Research and Education (CARRE), conducts research combining robotics, controls and machine learning. Her goal is to enhance the performance and autonomy of robots by enabling them to learn from past experiments and from each other.

For example, researchers can’t program an autonomous vehicle, like a self-driving car, for every possible weather condition. “We can’t replicate them all in the lab,” she said. Instead, they can program the vehicle to react cautiously in an unknown situation and learn from each new experience accordingly. Safety is their number one priority.

She has been working with aerial vehicles for the past nine years and more recently has applied her motion planning, control and learning algorithms to outdoor ground vehicles. As expected, she says the algorithms that work for flight, transfer well to driving.

Interest in her field has exploded in the past six to seven years, she said, recalling that when she did her PhD, finding funding for robotics research and development was difficult. But, “now it’s a complete change” as automotive and tech companies race to lead this emerging field.

“It’s always a concern that the technology is being oversold,” she said, noting the excitement each advancement in autonomous vehicles receives by the media and corporations. “But as researchers, we know and understand the limitations of the technology.”

Rossman, who has a joint appointment in mathematics and computer science in the Faculty of Arts & Science, specializes in showing that certain computational problems are inherently “hard” to solve. An application of the importance of finding “hard” problems is in cryptography – we want our encrypted information to be beyond the ability of computers to easily crack.

This line of research involves reasoning about mathematical models of computation such as Boolean circuits. Rossman’s main tool is a blackboard, as he works on theorems and major unsolved problems like P = NP?

“The University of Toronto has a great tradition in computational complexity theory,” Rossman said. “�鶹ֱ��app University Professor Stephen Cook is one of the founders of the field and a major figure in the P = NP? question. Over the years, many wonderful people and ground-breaking results have come out of �鶹ֱ��app. I am honoured to be part of the great Theory Group here.”

Most recently, his research has focused on Boolean formulas, a tree-like model of computation that lacks “memory” to store intermediate results.

“Despite the apparent weakness of this model, we still don’t have strong lower bounds” Rossman said. “This challenge is the next frontier in complexity research.”

Since 1955, Sloan Research Fellows have gone on to win 43 Nobel Prizes, 16 Fields Medals, 69 National Medals of Science, 16 John Bates Clark Medals and numerous other distinguished awards.

NSERC recognizes �鶹ֱ��app research into self-driving cars and microbial ticking time bombs in our bodies

ullahnor — Tue, 07 Feb 2017 16:12:46 +0000

NSERC recognizes �鶹ֱ��app research into self-driving cars and microbial ticking time bombs in our bodies

ullahnor Tue, 02/07/2017 - 11:12

Cutline

�鶹ֱ��app researcher Madeleine Bonsma-Fisher is one of two �鶹ֱ��app scientists awarded an NSERC today (photo by Martin Lipman/NSERC)

Sean Bettam

Author legacy

Sean Bettam

Topic

Breaking Research

NSERC

Faculty of Arts & Science

Subheadline

Biophysicist Madeleine Bonsma-Fisher and computer scientist Raquel Urtasun among national award recipients

We go to the gym, count calories and take our vitamins – all in an effort to stay fit and avoid getting sick. But are we actually healthy?

Enter PhD candidate Madeleine Bonsma-Fisher in the Faculty of Arts & Science's department of physics, one of two �鶹ֱ��app scientists given a boost today by the Natural Sciences and Engineering Research Council of Canada (NSERC). A member of Professor Sidhartha Goyal’s research group, she studies our bodies' microscopic communities, called the “microbiome” to learn what it means to be healthy and was awarded an NSERC Gilles Brassard Doctoral Prize for Interdisciplinary Research.

The other �鶹ֱ��app scientist awarded an NSERC today has helped fuel the development of self-driving cars.

Raquel Urtasun of the Faculty of Arts & Science's department of computer science received an E.W.R. Steacie Fellowship to advance her work in the field of machine perception, particularly its use in the development of autonomous vehicles. Urtasun has developed a benchmark series of challenges for autonomous vehicles to test their performance.

Associate professor Raquel Urtasun is being recognized for her research on self-driving cars (photo by Martin Lipman/NSERC)

“My congratulations to our NSERC award winners,” said Vivek Goel, �鶹ֱ��app’s vice-president of research and innovation. “They are both conducting research that is pushing the boundaries of human knowledge in areas that have remarkable potential for societal impact. We are grateful to NSERC for this recognition of and investment in �鶹ֱ��app researchers.”

Bonsma-Fisher studies a recently discovered immunity mechanism found in about half of all bacteria. Our bodies are filled with bacteria and viruses that attack them, known as phages. Some of these tiny organisms float harmlessly along while others are ticking time bombs that could cause infections, diseases and even obesity.

The microbiome is unique to each person, and diversity and adaptation among bacteria and phages make it difficult to say for certain what a healthy microbiome looks like. The newly found immunity mechanism allows bacteria to keep a record of each attack it encounters with a phage. Bonsma-Fisher hopes to use this record, along with large amounts of publicly available human microbiome data, to understand the interactions between bacteria and phages. Locating common features across many individuals will help determine the characteristics of a healthy microbiome.

“At this early stage of my career, it’s valuable to meet and learn from other scientists, and this award is giving me that opportunity to an overwhelming extent,” said Bonsma-Fisher. “The connections it makes possible will – at the very least – leave me knowing more than I did, and at most they can lead to exciting new ideas and collaborations.

“I’m a physicist working at the interface of disciplines and am learning most of the biology as I go. There’s nothing better than learning it from others at the forefront of the field.”

Her research will provide a more detailed account of the foundations of human well-being and how microscopic organisms affect our bodies. It will also help other researchers develop new treatments for common conditions to keep us healthy from the inside out.

Urtasun, on the other hand, is a pioneer in the area of machine perception.

During an era in which robotics and artificial intelligence (AI) are beginning to play a very important – and very personal – role in our lives, Urtasun has developed algorithms that allow vehicles to perceive and understand the environment in three dimensions and in real time.

Her work is enabling autonomous vehicles to navigate the streets safely and swiftly while detecting other vehicles and obstacles on the road and accounting for factors such as motion, speed and traffic flow.

She developed the KITTI (Karlsruhe Institute of Technology and Toyota Technological Institute at Chicago) benchmark, a series of challenges for developers of autonomous vehicles that are used to test their creations and assess the performance of their systems. KITTI has helped to significantly push forward the field of self-driving cars and has been heavily used by more than 500 groups both in academia and industry, including Daimler, NVIDIA, Baidu, Samsung and Toyota.

“I am honoured and humbled to receive this award” said Urtasun, an associate professor of computer science and Canada Research Chair in Machine Learning and Computer Vision. “This award is recognizing the work of my research group of students, postdocs and collaborators who are not only tremendous researchers but also amazing individuals. Their hard work, perseverance and willingness to go outside of the box have been the key to our success.

“This award will enable us to focus on new exciting directions in the development of new AI algorithms and applications.”

A key goal of Urtasun’s work is doing more with less – using fewer cameras and sensors to capture greater amounts of information and detail about a dynamic environment. Her research is advancing the state of the art for industry and helping to make personal robotics more accessible and affordable for everyone. Her current goal is to adapt her technology to make cities smarter and better to live in.

Urtasun and Bonsma-Fisher will be honoured along with other recipients from across Canada at a ceremony in Ottawa this evening hosted by the Governor General.

GM Canada president: “The tree of artificial intelligence was planted in Toronto”

ullahnor — Wed, 16 Nov 2016 20:00:52 +0000

GM Canada president: “The tree of artificial intelligence was planted in Toronto”

ullahnor Wed, 11/16/2016 - 15:00

Cutline

Steve Carlisle, head of General Motors Canada, looks at autonomous robots built by �鶹ֱ��app's Institute for Aerospace Studies (photos by Roberta Baker)

Jennifer Robinson

Author legacy

Jennifer Robinson

Topic

Global Lens

Institute for Aerospace Studies

Faculty of Applied Science & Engineering

Artificial Intelligence

Subheadline

Steve Carlisle scouts �鶹ֱ��app talent, talks partnerships

The automotive industry is going through a period of profound disruption – the most since the car replaced the horse – but Canadian universities like the University of Toronto have what's needed to help automakers leapfrog ahead of the competition, says the head of GM Canada.

That’s what drew Steve Carlisle, president and managing director of General Motors Canada, and his team on Tuesday to �鶹ֱ��app's downtown Toronto campus where they met some of the University’s world-leading researchers involved in artificial intelligence, deep learning, robotics and systems control.

The frenzied race to build the autonomous vehicle has brought big new tech players into the automotive field like Google and Tesla and everyone is searching for the next big thing and the talent – like �鶹ֱ��app’s computer science and engineering students – to make it happen.

“I tell them in Detroit that the tree of artificial intelligence was planted in Toronto,” Carlisle said, referring to the pioneering work of �鶹ֱ��app's Geoffrey Hinton, an emeritus professor of computer science who holds the title of University Professor, the highest distinction �鶹ֱ��app bestows on its faculty. Hinton now splits his time between the University and Google.

“And boy, wouldn’t it be great to do some of that work here in Toronto,” he added.

�鶹ֱ��app President Meric Gertler (left) greets GM Canada head Steve Carlisle (right) during his visit to �鶹ֱ��app's downtown Toronto campus

Canada is well positioned to lead the world thanks to this research prowess and its manufacturing innovation but time is of the essence, Carlisle said. And competition is fierce with places like Silicon Valley and Israel.

No one – yet – has put together all the pieces of how autonomous vehicles will work best from consumer safety to affordable price points, he explained. That’s why companies like GM Canada are open to partnering with leading academic institutions like �鶹ֱ��app because “collaborations will help us get there faster,” Carlisle said.

That collaborative spirit is one that �鶹ֱ��app has already embraced with a number of strategic research agreements with industry, said Professor David Sinton, vice-dean of research at the Faculty of Applied Science & Engineering.

Along with being a global leader in a number of critical fields, �鶹ֱ��app is an important anchor that is leveraging its talent and research excellence with partners like GM to help grow the Ontario economy.

The university is “building a culture of entrepreneurship in our students” with nine campus-led accelerators that support startups to transform great ideas into products, said Vivek Goel, �鶹ֱ��app’s vice-president of research and innovation.

For example, the Rotman School of Management’s Creative Destruction Lab is home to 50 artificial intelligence companies – considered one of the greatest concentrations of AI companies in any program in the world.

As part of his visit here, Carlisle met with Professor Tim Barfoot of �鶹ֱ��app's Institute for Aerospace Studies (UTIAS) and Canada Research Chair in autonomous space robotics, who provided a demonstration of one of the institute’s autonomous robots on campus.

GM head Steve Carlisle (left) takes a closer look at an autonomous robot with Professor Tim Barfoot (right)

The yellow, golf cart-sized robot, developed with the support of industry partner Clearpath Robotics, is equipped with advanced sensory equipment. For the demonstration, the vehicle used only vision from a camera to determine its movements along the twists and turns of a pathway beside University College.

Carlisle also visited with the Blue Sky Solar Racing Team and met with Raquel Urtasun, associate professor in �鶹ֱ��app’s department of computer science and Canada Research Chair in machine learning and computer vision, who gave the GM team a sneak peek at the latest advancements in using deep-learning techniques to improve the ability of autonomous vehicles to interpret the landscape around them.

To demonstrate its commitment to embracing and leading this new future for the automotive industry, GM Canada has announced plans to expand its engineering base in Ontario to reach a total of approximately 1,000 positions over the next few years. The company is also opening the Automotive Software Development Centre in Markham and plans to develop an Urban Mobility Campus with a focus on electric vehicles in southeastern Toronto.

This "new" GM Canada is “not your parents’ auto industry anymore,” Carlisle told students at a recruitment talk. Today’s GM is heavily focused on the “development of new connected, autonomous and shared vehicles and mobility systems.”

“Our goal is to disrupt ourselves,” he said.

The new areas that the automotive industry of the 21st century needs to excel in are mobile connectivity, data analytics, artificial intelligence, advanced battery technology, sensors, software development and cyber security, Carlisle explained.

“After visiting many of our top Canadian universities – including right here at the University of Toronto – I can tell you we have the strengths right in our backyard,” he said.

“In fact, Ontario now produces more qualified science, technology, engineering and mathematics professionals (STEM) than California. Yet, ask yourself, who has the reputation for innovation? That just doesn’t seem quite right. That seems like something we should spend some time on squaring up.”