Why Uber Is Building an AI Team in Toronto

The transcript discusses Uber's strategic move to establish a presence in Toronto, leveraging the city's strong AI research community, particularly at the University of Toronto. It highlights the work of Raquel Urtasun in machine vision for autonomous vehicles and addresses the impact of legal challenges, such as the California injunction, on Uber's operations. The discussion also covers the structure and future growth of Urtasun's team and Toronto's emergence as a significant hub for AI and machine learning.

Why is Uber forming alliances with universities like the University of Toronto?

• To avoid legal challenges in California

• To access top AI talent

• To reduce operational costs

• To expand its ride-sharing services

What is the primary focus of Raquel Urtasun's team at Uber?

• Developing new ride-sharing algorithms

• Improving customer service

• Enhancing machine vision for autonomous vehicles

• Creating marketing strategies for Uber

How might the legal issues with Alphabet affect Uber's research?

• It could halt all of Uber's operations

• It might only affect Uber's marketing strategies

• It might limit research to non-Lidar technologies

• It could lead to a complete shutdown of Uber's AI projects

What is the Vector Institute's role in Toronto's AI landscape?

• It is a marketing agency for AI companies

• It is a research institute affiliated with the University of Toronto

• It is a government body regulating AI technologies

• It is a startup incubator for AI businesses

What is Uber's long-term plan for Raquel Urtasun's team?

• To merge the team with another department

• To keep the team small and focused

• To expand the team to dozens of researchers

• To relocate the team to California