AI safely moving your cars and trucks

Raquel Urtasun is redefining what it means to put "intelligence" in Artificial Intelligence (AI). As a professor of computer science at the University of Toronto and an innovator at heart, she is at the forefront of deploying AI in autonomous vehicle technology. Her work is not just groundbreaking; it’s scientifically mesmerizing.

Beyond her academic pursuits, she’s also the founder and CEO of Waabi , a company dedicated to revolutionizing self-driving technology.

While Canada missed out on tech giants like Facebook and Google, there’s an incredible opportunity here to champion homegrown innovations like Waabi. Raquel's venture could very well become the next big name in tech, shaping the future much like Meta did in the early 2000s.

Raquel Urtasun is not just pushing the boundaries of AI—she’s redrawing the map entirely. Canada has a golden opportunity to lead the next wave of technological innovation, and supporting visionaries like Raquel and companies like Waabi is crucial. Let's not miss this chance to be at the forefront of the AI revolution.

I recently had the privilege of attending one of her seminars, where she shared her applied work on making vehicles "smart" using AI. What sets Raquel apart from others who talk about AI is her hands-on experience. She isn't just speculating on what AI could do; she's actively deploying these technologies in real-world scenarios. Her approach brings Generative AI to a whole new level by integrating it into the physical world—think streets, cars, pedestrians, and the complex dance between them. This is where the future of AI lies: not just in simulations or theoretical applications but in the tangible, messy reality of our everyday lives.

Raquel has dubbed the current state of autonomous vehicle technology "AV 1.0," indicating that we are still in the early stages. However, her vision for "AV 2.0" is filled with promise—not just for creating more efficient transportation systems but, more importantly, for making our roads significantly safer. The leap from AV 1.0 to AV 2.0 and more could mean fewer accidents, better traffic management, and a more sustainable urban mobility future.

Waabi’s technology leverages advanced AI models to train self-driving cars in a simulated environment that is safer and more efficient than traditional methods. This innovation is crucial for the scalable development of autonomous vehicles. Unlike conventional approaches that rely heavily on real-world testing, Waabi’s approach minimizes risks and accelerates learning. This shift could pave the way for a faster, more robust deployment of autonomous vehicles on our roads.

Raquel’s work has implications beyond just the automotive sector. Her contributions to machine learning, computer vision, and robotics have set new benchmarks in AI research. She has authored hundreds of peer-reviewed papers and received several prestigious awards, such as the NVIDIA Pioneers of AI Award and the Google (also Amazon) Faculty Research Award, highlighting her influence in academic and industrial circles.

For those eager to dive deeper into her cutting-edge research and understand the full scope of her contributions, you can explore her publications and projects at the following link: Raquel Urtasun's Research.