Fireside Chat: It’s Time to Meet Lidar’s Biggest Rulebreaker

lidar - Fireside Chat: It’s Time to Meet Lidar’s Biggest Rulebreaker

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Editor’s Note: This interview has been edited and condensed for clarity. The answers by Keilaf represented here comprise a combination of direct quotes and paraphrasing. This article is part of Joanna Makris’ Fireside Chat series, where she provides retail investors with the scoop on the hottest technologies and trends from today’s business leaders, industry experts and money managers.

I had an opportunity to sit down and chat (via Zoom) with Omer David Keilaf, CEO and co-founder, Innoviz Technologies (NASDAQ:INVZ). Innoviz is on my buy list as an early leader in lidar (Light Detection and Ranging) technology. Prior to founding Innoviz, Keilaf was a senior officer in Unit 81, the elite technological unit of the Israel Defense Forces (IDF). In this role, he helped pioneer technologies to make the impossible possible.

After “MacGyver-ing” through several technological solutions for the IDF, he’s now solving yet another impossible technological challenge. Keilaf is working to make autonomous driving (AD) safe and affordable. By using lower-wavelength 905 nanometer technology, his company Innoviz is bending the laws of physics, while disrupting the cost-performance curve to help make AD mainstream.

Here’s what Keilaf had to say about the state of the industry, the hotly contested 1550 versus 905 nanometer debate, why Elon Musk is wrong about lidar and more.

How far away are we from seeing autonomous driving as a mainstream technology?

For autonomous driving technology to work, the car needs to make decisions as fast as possible and drive in a very relaxed way. If the car were to push the brakes too fast or maneuver too fast, people would not trust the system. So, the car needs to see very well, at long range, and in all conditions — direct sun, rain and darkness — while delivering a smooth driving experience. Today’s L2+ solutions won’t scale until we solve these serious safety issues. 

The lidar industry is divided into two different wavelength camps: 1550 and 905 nanometers. What’s the difference?

Each wavelength comes with tradeoffs, including the effects of water on the signal, power consumption and the availability of sensor components. It’s actually much more difficult to achieve higher performance with 905 nanometer technology — but 1550 nanometer is much more expensive. The gap in pricing between 1550 and 905 is significant — right now, it’s in the thousands of dollars. In the long term, it will still be in the hundreds of dollars. And, cost is king in the automotive industry. In talking to many car makers, their decision to deploy a L3 technology isn’t just based on technology — it’s mostly about price. If they can’t find the right price point, they’ll just wait. So, at Innoviz, we thought that if we could solve the 905 nanometer performance limitation, that is, develop the right chipset — it’s like the holy grail — the perfect combination of performance at lower cost.

What do you say to critics who claim it’s impossible to deliver a high performance lidar at 905 nanometers?

It’s a very noisy industry. The pushback on 905 nanometers is nothing new. At lower wavelengths, the transmitter and receiver are capped in the amount of laser power they can emit. The signal to noise ratio is lower, and you can’t get to long range. That was true five years ago. But it’s not the case anymore.

Current semiconductors are transparent to any wavelength above 1000 nanometers, which means we can use silicon and low cost standard processors for our lidar. We also use a single-photon detector, which doesn’t need a lot of light in order to see reflection. So, even with lower laser power, we can still get a reflection from 200 meters away. In contrast, 1550 nanometer systems need a more powerful laser. They also can’t use standard silicon in the detector, which also makes them more expensive. Our performance comes across very clearly, our solution is ten times smaller, and much cheaper than 1550 solutions. 

Innoviz won an OEM production contract with BMW for Level 3 lidar. What does that mean exactly? 

Innoviz was awarded a design win at BMW (OTCMKTS:BMWYY) for its self-driving car program for Level 3 capability, which is mostly for highway driving.

[See the following table for more context:]

Level 2 Hands off, eyes temporarily off Partly automated
Level 3 Hands off, eyes off Highly automated
Level 4 Hands off, mind off Fully automated
Level 5 Passenger autonomous Autonomous

Level 3 is like the “MVP” of autonomous driving. People are already spending a lot of time on the highway, and feeling very passive about driving, which makes this a good application for the technology. A lot of car manufacturers are talking about Level 3 capability — but there’s a big difference between doing Level 3 at 20km versus 130 km per hour. The requirements of the sensor and reaction time are very different. Innoviz is the only certified automotive-grade high-performance lidar.

The BMW program is expected to launch by the end of 2021. This was the result of hundreds of millions of dollars spent, hundreds of top engineers and tens of millions of kilometers driven for validation. Only selected OEMs are able to go through such a long and rigorous process.

Where are we right now on the cost curve?

For the next decade, the Level 2+ barrier is $500, but ultimately, lidars need to get down to $100 or less. The Level 3-4 price barrier is $1,000. We think we are the only LiDAR company that meets both performance and cost requirements. By using a solid state design, we can leverage a fully automated and scalable manufacturing process with shorter assembly and testing time. InnovizTwo, our next generation platform, offers a 70% cost reduction and can be used for Level 2-5 solutions. 

Elon Musk famously hates lidar, calling it a ‘crutch’ for autonomous vehicle makers. Thoughts?

In reality, what Tesla (NASDAQ:TSLA) is trying to do is considered impossible. Any automotive safety feature needs to have redundancy — there can be no single point of failure. Two cameras aren’t considered redundant to each other — they both suffer from the same limitations. So, Tesla’s technology has a glass ceiling. The safety level from a camera plus lidar is much higher than just a camera. That’s because a camera by itself suffers from vision and AI limitations.

For an autonomous car that mostly relies on cameras, like Tesla, low light conditions are a safety issue. A camera needs to detect that there’s an object in front of it, but it also needs context — it has to be able to classify that object to understand what it’s actually looking at. As a result, the AI required for a camera is very complex. It needs a lot more processing power. In contrast, it’s much easier for a lidar to give you a good understanding of the scene. The lidar is already collecting a lot of information, including the physical measurements of the object in front of it. The latency, or time to reaction, is faster and the processing power is more lean. It’s strange that someone with such vision would handicap a machine this way: Tesla is using a camera with a 2D sensor and trying to translate it into 3D. 

What do you think about cryptocurrency?

I will wait for Elon Musk’s next tweet.

Your comments and feedback are always welcome. Let’s continue the discussion. Email me at jmakris@investorplace.com.

On the date of publication, Joanna Makris did not have (either directly or indirectly) any positions in the securities mentioned in this article. The opinions expressed in this article are those of the writer, subject to the InvestorPlace.com Publishing Guidelines.

Joanna Makris is a Market Analyst at InvestorPlace.com. A strategic thinker and fundamental public equity investor, Joanna leverages over 20 years of experience on Wall Street covering various segments of the Technology, Media, and Telecom sectors at several global investment banks, including Mizuho Securities and Canaccord Genuity. 

Click here to track her top trades of the week, where she sheds light on market psychology and momentum, while leveraging her deep knowledge of fundamental analysis to deliver event-driven trading strategies.


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