I mean, I would assume that someone who doesn’t get a new enough car doesn’t have enough money to pay for commercial insurance. Also offering people rides on the street is a bad idea (because you can get robbed) and possibly illegal. This is just running an unlicensed taxi service. Gypsy cabs have been around for hundreds of years. It’s not a good idea.

That’s a terrible idea. His insurance won’t cover him in an accident. If a passenger is injured he may be on the hook for the medical care.

Plus, as soon as the cars can drive themselves people will stop needing Uber in many cases.

No parking? Just tell your car to go park on a street 10 blocks away.

Drunk? Car drives itself while you sleep.

Going to the airport? Car drops you off and returns home. Car also picks you up when you are back.

This is combined with the fact that people will do more disgusting things in an Uber without the driver there. If you have ever driven for Uber, you know that 10% of people are trying to eat or drink in the car. They are going to spill and it’s going to end up like the back of a bus.

It’s not just that. People fought duels over their honor in the past. We don’t have duels anymore, so we shouldn’t rely on a judge to recuse themselves.

It is a founding concept of European law that no one should be a judge in their own case:

https://en.wikipedia.org/wiki/Nemo_iudex_in_causa_sua

I think in one sense it can be good. Sometimes it is counterproductive to downvote someone from 1 to 0. I think this would prevent that, as the first downvote is probably the most important one.

But I agree that making any data public will allow everyone to be categorized easily. “This person dislikes this content and likes other content.”

Remember, you are giving this info to everyone. Mark Zuckerberg will be able to see what you like and dislike in all public votes.

Uh, that guy actually did steal literal IP. Uber was founded by an asshole who didn’t care about breaking the law.

six weeks before his resignation, Levandowski downloaded all these highly confidential files and proprietary design files

It happens all the time. Almost everyone who starts a new tech company has worked in a different one.

In California it’s totally fine. That’s why there’s so many tech startups there. It’s not taxes.

That’s not really how IP works. Just because you think of something while eating a sandwich that Google paid for, that doesn’t mean they own it. Your brain is not “company resources”. The sandwich was not necessary for the brainstorm.

It’s smarter to think up good ideas away from the office, but it’s completely legal to take knowledge and experience with you when you leave the company.

It saved him like several hundred per month.

If you live within biking distance of Google, you are spending a ton of money on rent. Work from home is way cheaper, especially since you can just live somewhere with sub-million houses.

Lol!

Yeah, just like how black people were bad and the “children of Ham” or whatever. After the Civil Rights Movement, Morman God mysteriously changed his mind and said “black people are ok now”.

It’s not. Investors literally only care about money.

Rich people don’t have “class consciousness” because they all want to be better and richer than other rich people. That’s what “keeping up with the Joneses” (or Kardashians) is. You don’t want the Joneses to improve, because that hurts you.

It’s a zero-sum game at the top. If your neighbor buys a Mercedes, you need to buy a Maserati. Like I said, neo-marxism fundamentally misunderstands rich people.

This is not about running the best company or running the best economy. It is about maintaining class power and privilege.

I understand your point, but neo-marxist perspectives like this fundamentally misunderstand what companies care about (for obvious reasons). No company cares about “class power” or “privilege” because shareholders only care about their own money.

Their “class” is not important when it comes to investing. If they could fire all the nepo babies and use AI instead, they would do it in 1 second.

The funny thing is that there are executives who know what they’re doing, but they may be outvoted by people who failed upward due to connections or a “good background” (ivy league, internship, etc.).

I always thought “what does a brand name education prove?” This isn’t the 1800s. Community college now is almost as good as Harvard was in the 1800s. Back then, just being able to read meant that you were educated.

Also, what does an internship prove? You know how to carry 8 coffees at once? You can wear a cheap suit? No, it’s all cover for connections. If businesses wanted the best people (say the top 10%) you could literally just set up a table outside a subway station and interview random commuters, getting probably 10 good prospects in a day.

Yes, it was. Tech led the downturn yesterday, but Nasdaq was only down like 2%. The “world” stocks (ex-US) are more volatile than the US. In my opinion (and Warren Buffett’s), they are not worth investing in as ETFs. Only particular companies. The markets are genuinely worse than in the US.

This isn’t software, it’s a car. It’s highly regulated. NHTSA doesn’t care if it’s a software issue.

It’s not just a predictive text program. That’s been around for decades. That’s a common misconception.

As I understand it, it uses statistics from the whole text to create new text. It would be very rare to output “cats have feathers” because that phrase doesn’t ever appear in the training data. Both words “have feathers” never follow “cats”.

Then these models are stupid. Humans don’t start as a blank slate. They have an inherent aptitude for language and communication. These models should start out with basics of language, so they don’t have to learn it from the ground up. That’s the next step. Right now they’re just well read idiots.

provenance requires some way to filter the internet into human-generated and AI-generated content, which hasn’t been cracked yet

It doesn’t need to be filtered into human / AI content. It needs to be filtered into good (true) / bad (false) content. Or a “truth score” for each.

We don’t teach children to read by just handing them random tweets. We give them books that are made specifically for children. Our filtering mechanism for good / bad content is very robust for humans. Why can’t AI just read every piece of “classic literature”, famous speeches, popular books, good TV and movie scripts, textbooks, etc?