Saswat Panigrahi (@saswat101) is the Chief Product Officer at Waymo (@Waymo), an autonomous driving technology creating a new way forward in mobility  
In this conversation, Saswat Panigrahi and Steph Smith go for a ride in Waymo’s autonomous vehicle and discuss the state of self-driving, Waymo’s advantages over the competition, the differences between LiDAR and video, the future of autonomous driving, societal unlock enabled by autonomy, and more 
Check out these Podcast Notes on Marc Andreessen talking about AI sentience 
Host: Steph Smith (@stephsmithio) 
Level 1 autonomy is like driver assistance 
Level 2 autonomy is lane sensing and automatic braking
Level 3 autonomy requires human intervention within a matter of seconds
Level 4 autonomy requires no human intervention 
Level 5 autonomy is “anywhere, anytime” 
Understanding the size of the opportunity on the other side of an innovation obstacle is the key to success 
Saswat and Waymo believe that a fully autonomous car will be safer than the human-driven alternative 
The hardest challenges were building the driver itself and measuring its performance 
Waymo built the full stack of hardware and software for its autonomous driving cars 
Waymo built the radars, cameras, lasers, hardware, and simulation infrastructure necessary to achieve autonomous driving 
Autonomous driving can be distilled down to:
  • Is the car aware of what’s happening around it? 
  • Can it anticipate what the things around it are going to do? 
  • Given its surroundings, can the vehicle reason on what it should do next?
Lasers help identify objects in the 360-degree surrounding area, and cameras are needed to distinguish between red lights and green lights, among other things 
Radars help the car see around corners even when the lasers, cameras, and human eyes cannot 
Autonomous vehicles require an “insane” amount of machine learning 
For example, machine learning makes predictions on what pedestrians will do next depending on their gate and hand motions 
The LiDAR vs video debate has become ideological, in a sense 
The best approach is taking a first principles approach 
LiDAR has strengths that a camera does not, and vice versa
LiDAR might perform better at night, but cameras better identify colors during the day 
Instead of debating LiDAR vs video, Saswat believes the more important question is whether or not the radars, lasers, cameras, and sensors position the vehicle better than the individual; he believes the answer to that question is resounding “yes” 
Waymo manufactures its LiDAR 
Waymo found that the best LiDAR and radio on the market were not optimized for the task of autonomous driving, so it decided to build those technologies itself 
Autonomous driving applies to all forms of transportation 
Waymo has driven +20M miles in testing and billions of miles of simulation as of this writing 
Waymo’s competitors have not driven anywhere near this amount of miles 
AI helps bring down costs for autonomous driving 
AI also helps improve the effectiveness of simulations for autonomous driving
There is AI at every level in the autonomous driving software stack  
Waymo took every fatal crash that ever occurred in Phoenix, re-simulated them, and showed that Waymo’s technology could have avoided the crash
Waymo is the first company to cross the one million miles of fully autonomous driving 
It did not record a single collision with injury in its one million miles of autonomous driving 
Waymo has recorded a total of 160 years of human driving time 
Waymo exists to make driving safer 
The company has a “deep fundamental alignment” with what the regulators are trying to achieve 
Within the vehicle, the software provides explanations for why it made certain decisions  
In the early days of Waymo, the company went to various cities that would challenge its driver in many different directions 
It went to 20 different cities to ensure that it was building a generalizable driver, and not one that just works in one location 
Various cities provide better testing elements than others; for example, Miami for heavy rain, Death Valley for extreme temperatures, and Tahoe for snow 
Our society is designed around driving; consider how much of our cities are designed around parking  
A parked car in a city takes up an underutilized, expensive asset (real estate) 
Think of the amount of space parking takes up in a city; parking does not contribute to the productivity of a city 
We dedicate more space in cities to sleeping cars than sleeping humans 
Consider the amount of air pollution idling cars cause in cities 
Consider the amount of real estate in cities is lost to idling or parked cars 
Any sufficiently advanced technology is indistinguishable from magic