Self Driving Car: Deep Learning Meets Robotics

We will hear from David Frenk* on:

Intro

• The AI revolution and how self-driving cars fit in: Deep Learning meets Robotics
• Early attempts at autonomous vehicles (including some pretty funny video footage)
• The current state of the art (people will be surprised by how many AVs are already on the roads)
• The biggest breakthrough yet: YOLO network (with awesome video of real-time object detection)

Deep Dive - Computer Vision for AVs

• What a computer sees: Image pre-processing: filtering, etc.
• How a computer reasons about what it sees: Convolutional Neural Networks overview (including some cool examples of computer generated art and neural style transfer)
• Live Demo: YOLO network in action (have some people come up on stage with props, take a photo, and run real-time object detection on the photo)

My Self-Parking Car project

• Robot design
• Project structure
• Data-collection process
• Live Demo: Have an audience member set up a "curb" and watch the robot parallel park.

*David Frenk is a Twin Cities software engineer currently working as a consultant for Target. He has previously worked on AI-driven fintech at Masters Capital Management and IoT applications at Trane. David has a Masters degree in Philosophy from Oxford and did 2 years of postgraduate work at NYU where he studied artificial intelligence and mathematical models of cognition. He has been developing a self-parking robotic car since mid-2017.