Exceptional episode for you today with Prof. Jason Corso, in which he details how he's tackling the biggest problem in machine vision. Jason's super sharp and very well-spoken... don't miss this one!

Jason:

• Professor of Robotics, Electrical Engineering and Computer Science at the prestigious University of Michigan, with over 20 years of research spanning video understanding, robotics, and AI.

• Has published over 150 academic papers that, together, have been cited over 20,000 times.

• Co-founder and Chief Science Officer at Voxel51, a leading platform for visual AI development.

• His work bridges academic innovation and real-world impact, earning him more major honors than I have space to list!

Today’s episode skews a bit toward hands-on practitioners like data scientists and AI/ML engineers, particularly anyone tackling computer-vision problems. That said, Jason is a charismatic and exceptional communicator so perhaps any listener to this podcast will enjoy today’s episode.

In it, Jason details:

• How his research spinout, Voxel51, is solving the biggest bottleneck in computer vision.

• The surprising way autonomous vehicles learn to handle accidents they've never seen.

• Why the secret to better AI models isn't better algorithms — it's something else that’s hiding in plain sight.

The SuperDataScience podcast is available on all major podcasting platforms, YouTube, and at SuperDataScience.com.