If they had someone working on using the tech to ID mushrooms growing along the road then they’d probably come away with some new techniques to make the cars safer. Trying to make a self-driving car algorithm by only thinking about driving-related things seems like it will just lead to overfitting.

And in fact any car that doesn’t have enough cognitive surplus to identify mushrooms while driving in normal conditions may just not be safe to drive period.

I continue to be surprised he hasn't been taken to court yet for selling a $6K package that isn't anything but an empty promise.

Musk made a mistake, and he's spending billions to prove that he never made it.

snow makes HD maps somewhat less useful, as the terrain changes shape. But then, you need a map that evolves. Sadly for musky, the only company that can do that using purely visual data is Scape Technologies. Not even lyft can do that.

Good thing Teslas have radar...which penetrates falling snow.

>Musk made a mistake, and he's spending billions to prove that he never made it.

People drive fairly well with only visual sensors (eyes). That is proof of concept. Lidar seems like overkill.

Just like in cooking you can use meat cleaver and a paring knife or in a network you use switches and routers.

For example, an unprotected left turn during rush hour. The gap between cars that people drive into in that situation often does not leave any room for chance. For example, if another car speeds up or changes lanes, there can be an unavoidable accident. But the standard for human drivers is to take those chances during heavy traffic, and drivers that try to avoid that are not accepted.

The issue is that people are incorrectly going to hold Waymo's computer responsible for some unavoidable accidents in those types of scenarios, but at the same time expecting them to make those maneuvers even though the computer knows there isn't enough margin.

That's not a weakness of the AI. That's an inability of people to understand the nature of traffic and the relationship between AI and people.

The goal is not to achieve perfection, just demonstrably more safe than an average driver.

I'm curious how we will evaluate average driver. Clearly, including drunk driving accidents in the mix is not a helpful metric for safety-conscious drivers.

Sure it is. Even if you never drive drunk, there are still other drunk drivers on the road who are a danger to you.

But a self-driving AI, even an imperfect one, never drives drunk.

In practice, the target seems to be not just the average driver, but the best human driver (or at least the 99%th percentile.) Given the trajectory of improvement we often see with AI, surpassing the average human and surpassing all humans shouldn't be too far apart.

Who among us would admit, "yes, I am a bad driver, I need this more expensive thing to take control in the event of an accident"? Very few is my guess. In 2019, people use these for convenience, not because they think the system is a better driver. I bet that's true even for Waymo's taxis.

As for getting drunk drivers to use self-driving, that's as easy as asking them to either stop drinking or not drive. Then there is the cost. I wouldn't be surprised if the unemployed drink and drive more often.

Cost is definitely an issue, but reducing accidents and increasing convenience have a cash value which could pay for it if the research pans out.

What social factors do you have in mind?

It seems unlikely that people who buy/use early self-driving cars have the same percentage of drunk driving as the general population. Surely employment rates would be a factor, for example.

But even if it is true that those who drive cheaper, older cars are more likely to drive drunk? Today's new cars with high-tech self driving features are tomorrow's affordable used cars. You have to start somewhere.