Do you know who Austin Russell is?
  • He's a college dropout
  • He never earned his degree
  • He had some wild and crazy ideas — and some people were literally betting on him to fail
He proved them wrong by becoming the youngest self-made billionaire on the planet at age 25. His current net worth is approximately $2.2B (yes, billion).

So, the world has another billionaire? Who cares? What makes Austin's story so special?

I'll tell you:

Austin studied optics, and more specifically, LiDAR. It was his passion.

After receiving a $100,000 grant from the Peter Thiel foundation, Austin dropped out of college to start a company, Luminar, which makes LiDAR sensors that allow self-driving vehicles to "see" their surroundings.

He built the company up and it eventually went public in December 2020.

Now, he's the youngest self-made billionaire, at only 25 years old.
 

You know what Austin's story reminds me of?

In many ways, Austin reminds me of Andrew Carnegie, the classic American "rags to riches" story.

In 1835 Carnegie lived in a small one-room home in Dunfermline, Scotland. He was born into a family of destitute laborers with no real future ahead of him.

He had very little schooling before he and his family emigrated to America in 1848.

...and then everything changed.

By working hard, relentlessly executing, and never giving up, Andrew Carnegie built an empire, The Carnegie Steel Company.

Along the way, he became one of the richest people in America, playing an absolutely vital role in the industrialization of the United States.

And while he certainly wasn't a perfect human being by any means (the 1889 Johnstown Flood being one of the most glaring examples), most historians agree that his contributions to the world outweigh the detriments.

Both Carnegie and Russel's story shows you what can be accomplished through hard work and relentless execution.
 

You can learn LiDAR and autonomous vehicles.

Self-driving cars are far from "solved". There is no winner in this field yet.

Companies like Tesla, Waymo, and Cruise are hiring self-driving car engineers as fast as the universities and online programs can churn them out — all of them are looking for a competitive edge.

The question is...will you be in on the self-driving car revolution?
 

Brand new course: Visual Sensor Fusion for Autonomous Cars

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Earlier this week we released a brand new course inside PyImageSearch University — Visual Sensor Fusion for Autonomous Cars.

By the end of this course you will be able to:
  • Explain the difference between standard cameras and LiDAR
  • Write code that can fuse camera and LiDAR together
  • Describe, employ, and use sensor fusion algorithms in your projects
  • Perform camera calibration, including intrinsic and extrinsic parameters
  • Create LiDAR point clouds from your own sensors and projects
  • Code projects that use cutting edge 3D perception
  • Explain the difference between early vs. late sensor fusion
  • Perform point pixel projection in your projects and work
  • Project a LiDAR point (3D) to an image (2D)
  • Explain, code, and use the "magic formula" that makes it all possible
  • Visualize the 2D and 3D data together making stunning visualizations like you see above
  • Apply sensor fusion to autonomous vehicles and your own work
Additionally, text articles, video tutorials, and Jupyter Notebooks are included. A Certificate of Completion is also offered to those who pass the final exam in the course.
 

25 courses for the price of one.

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PyImageSearch University includes 24 additional courses, including:
  • OpenCV 101 — OpenCV Basics
  • OpenCV 102 — Basic Image Processing Operations
  • OpenCV 104 — Histograms
  • Face Applications 101 — Face Detection
  • Face Applications 102 — Fundamentals of Facial Landmarks
  • Face Recognition 101 — Fundamentals of Facial Recognition
  • Augmented Reality 101 — Fiducials and Markers
  • Deep Learning 101 — Neural Networks and Parameterized Learning
  • Deep Learning 102 — Optimization Methods and Regularization
  • Deep Learning 103 — Neural Network Fundamentals
  • Deep Learning 104 — Convolutional Neural Networks (CNNs)
  • Deep Learning 105 — Hands-on Experience with CNNs
  • Deep Learning 120 — Regression with CNNs
  • Deep Learning 125 — Data Pipelines with tf.data
  • Deep Learning 130 — Hyperparameter Tuning
  • PyTorch 101 — Fundamentals of PyTorch
  • Autoencoders 101 — Intro to Autoencoders
  • Siamese Networks 101 — Intro to Siamese Networks
  • Image Adversaries 101 — Intro to Image Adversaries
  • Object Detection 101 — Easy Object Detection
  • Object Detection 201 — Fundamentals of Deep Learning Object Detection
  • Object Detection 202 — Bounding Box Regression
  • OCR 101 — Fundamentals of Optical Character Recognition
  • OCR 110 — Using Tesseract for Translation and Non-English Languages
We release brand new courses every month, so PyImageSearch University is a great way to stay on top of state-of-the-art trends in computer vision and deep learning.
 

25% OFF all memberships

We're currently offering 25% OFF all memberships to PyImageSearch University.

But hurry, this deal ends Monday at midnight EDT:



Opportunities like these don't come around often.

Don't miss out on it.

Adrian Rosebrock
Chief PyImageSearcher