Initially, I thought the lane-keeping problem for self-driving cars was too difficult to solve, but it turned out to be manageable with the right approach.

The challenge of self-driving includes solving perception problems, such as recognizing objects and predicting their movements, even when they are occluded.

I believe self-driving technology will eventually be fully solved as it is a bounded problem, unlike more complex scenarios.

To advance AI, we need to focus on building infrastructure that can handle edge cases, similar to the journey of self-driving cars, which have taken years to develop due to the complexities involved.

Innovations like self-driving cars require substantial long-term investment, often in the range of tens of billions of dollars over decades.

The final 20% of a project often takes 80% of the time, and we were committed to overcoming that challenge with Waymo, despite the technology gap compared to other self-driving companies.

The next challenge in software development will be ensuring the verification of code generated by AI, as simply improving code writing won't significantly speed up engineering processes.

To achieve full self-driving, we need to recreate how humans drive, which involves using optical sensors and neural networks to interpret the road environment.

Despite the advancements, society is cautious about adopting AI technologies, as seen with self-driving cars, which are statistically safer but face public skepticism.