Austin Russell, 26, is the youngest self-made billionaire.
No, he’s not into app-making, cryptos or social media.
He’s an innovator. Russell, CEO of Luminar Technologies (born on March 14, 1995), improved lidars, a critical technology for safer self-driving vehicles.
Lidar stands for “light detection and ranging”, a key component that could make autonomous vehicles as ubiquitous as donuts.
Critical component
Unlike competitors relying on standard parts, Luminar custom-built every component: lasers, sensors, scanners, and processors. Self-driving cars that uses laser pulses to create 3D maps of the environment.
Industry experts, including Tesla chief Elon Musk, have dismissed automotive lidars as "ridiculous", a "fool's errand", "expensive sensors that are unnecessary", like having a "whole bunch of expensive appendices".
"Anyone relying on lidar is doomed," Musk once declared.
But Russell identified opportunities others overlooked. His innovation is actually a low-cost iteration of lidars, which first came to market in 1962.
An increasing number of self-driving cars, however, now use laser pulses to create 3D maps of the environment.
- Lidar, used by drones to avoid collisions or form fancy images in the sky, calculates distances by emitting laser pulses and measuring the time it takes for the reflected light to return.
- It is used for precision parking of spacecraft on the International Space Station. Now, it's seen as a critical component for self-driving cars that uses laser pulses to create 3D maps of the environment.
What’s changed: 150x cost improvement
At present, lidars for cars are expensive, bulky contraptions. The global automotive lidar market size is relatively small, estimated at $448.00 million in 2023, as per IndustryARC.
Russell’s solution: miniaturise, improve, and hit economies of scale, thereby solving the one problem that automakers from BMW and BYD to Volvo and Zeekr couldn’t crack: self-driving.
Luminar's key motes: a high-resolution lidar, mass production and lower cost.
Compared to traditional camera or radar-based systems, the system offers greater accuracy, especially in low-light conditions, enhancing vehicle safety and navigation.
His method allows the scanner to create precise, three-dimensional maps of objects and environments by assessing how long the light travels.
Childhood
Born in Newport Beach, California, he showed extraordinary talent from the start. By elementary school, he had memorised the periodic table and was diving into advanced physics.
By 13, he filed his first patent - for a groundwater recycling system.
At 17, after taking $100,000 from Peter Thiel's Fellowship, which offered him to drop out and pursue his dreams, Russell founded Luminar Technologies, known for pioneering advancements in lidar technology for autonomous vehicles.
By his early 20s, he became one of the youngest self-made billionaires, thanks to the company's success.
Breakthrough
Russell is just getting started.
Compared to current lidars, Russell’s system has shrunk the $75,000 tag price of current lidars to just $500 apiece – a price crush by a factor of 150.
His breakthrough came from switching to 1,550nm wavelength, though requiring low power – a huge improvement from traditional lidar, which uses 905nm lasers, as per Wired.
This enabled stronger signals while staying completely eye-safe for people. And unlike the 60s-era lidars or its modern-day $75,000 versions currently used in Waymo and others, Luminar’s system could:
- Detect objects at 250 metres – an unprecedented range
- Work in complete darkness
- Identify low-reflectivity objects
- Process environmental data in real-time
Transformer
The result is transforming an industry like nothing has ever done before. Major automakers started lining up:
- Volvo
- Daimler Trucks
- Other automakers
Many cars are already fitted with lidar, including: Honda Legend (uses two frontal cameras and a Valeo data fusion controller, for level 3 automation), Mercedes-Benz S-Class (Level 3 automatation), Jaguar Waymo robotaxis, DEMO car, Hesai Technology, RoboSense, Zvision, and Innovusion, among others.
The $2.4-billion payoff
Luminar developed a powerful lidar designed for mass production. The company went public through a merger with Gores Metropoulos Inc., catapulting its valuation and influence.
Russell owns about 104.7 million shares, roughly one-third of the company. By the end of the first trading day, his net worth soared to $2.4 billion.
Tesla challenge
Lidar, or the lack of it, is the biggest problem EV leader Tesla faces with its so-called full-self driving (FSD) technology.
Reason: Tesla CEO Elon Musk has ditched lidars completely.
Musk favours vision-only self-driving tech — which does not work in snowy, rainy conditions or when the cameras are blinded by sunlight.
For years, this has led to a PR and technical disaster for Tesla. Even Musk’s most ardent supporters have assailed his vision-only orthodoxy.
Musk is a hard-core evangelist of a vision-based, 8-camera, chip-driven platform to tell the self-driving AI the difference between a deer, a fly on the windscreen and a human being – while the vehicle is moving.
Game-changing invention
Cameras are cheap. Lidars, though useful for safer navigation, are not. Russell enhanced the underlying lidar technology, and tweaked it enough to be produced at scale.
What sets Russell apart isn’t just enhancing existing technology — it’s rethinking how autonomous vehicles “see” their surroundings.
Instead of tweaking old designs, he introduced a breakthrough approach – changing the game for the entire industry.
Alongside vision, lidars could crack the Holy Grail of self-driving technology.
This method allows the scanner to create precise, three-dimensional maps of objects and environments by assessing how long the light travels.
Our take
Elon Musk's vision-only dogma for “full self-driving” (FSD) could be his own undoing. He once said: “the best part is no part” – i.e. the less number of components used in a product, the better for scaling production.
This, in effect, compromises safety in real-world use of self-driving systems – given the “edge cases” previously unseen by the self-driving AI with vision-only input and neural networks-based processing.
To be fair, Tesla’s FSD has improved dramatically over the years, using end-users as testers.
Musk began promising full self-driving cars in 2013, when he first publicly discussed the Tesla "Autopilot" system.
In Elon Musk’s universe, the future of autonomous driving is perpetually just around the corner. His vision of achieving full self-driving without lidar, relying solely on cameras and neural networks, has become a rallying cry for the Tesla faithful.
But in the real world of commercialised autonomy, his stance raises a burning question: Did Musk fundamentally misunderstand the path to making autonomous vehicles a reality?
Was Musk wrong about automotive lidars?
While Tesla grapples with delays and scrutiny over its FSD system, including lawsuits, competitors leveraging lidar and robust onboard computing are silently—and successfully—transforming the landscape.
Real-life robotaxi services, equipped with lidar and powerful processing, have leapfrogged into actual commercial deployments. Companies like Waymo and Cruise are offering rides in fully autonomous vehicles, proving that lidar's precision and reliability are essential for navigating complex urban environments.
Then there’s China. The nation is buzzing with lidar-powered robotaxis that rival their Western counterparts in sophistication and operational success. These futuristic fleets are achieving lower unit costs, streamlining operations, and scaling up at a pace that makes Musk’s dream feel like a mirage.
And then there's Russell's $500-apiece high-resolution lidar system, which could usher in the era of self-driving transport.
Russell's innovation goes beyond self-driving cars, with applications in agriculture and aviation to mining, forestry, energy and archaeology.
It could be the next frontier of big-power rivalry.
Instead of processing visual details like a traditional camera, it gathers depth data to determine the distance between the camera and the subject.
This helps the image signal processor (ISP) focus quickly and accurately, reducing blur and enhancing sharpness for both photos and videos.