WhiteMonkey

Tim Harford's Undercover Economist has examples of how to get people to self select:

https://www.goodreads.com/book/show/70420.The_Undercover_Eco...

You're right, Land Value Tax (LVT) would be much better, as other European cities use.

It's hard to off-shore property in a tax haven too.

It's one of those policies that is popular with virtually everyone right until the moment they get into power and meet the wealthy landowners/donors.

Most parts of the world look at McMansions and feel unsettled, particularly when they are marketed as "aspirational": sell your soul in order to get the biggest place you can get a mortgage for on your salary, so you can never leave your job.

The other benefit with having multiple projectors/lasers at different angles are that you can use different wavelengths: one that causes polymerisation, one that inhibits it.

> Suddenly, no one wants to invest in a company that requires significant capital

But this is the point: the reason Uber is successful isn't particularly because of their technical excellence or innovation, it's because they've used massive amounts of capital to very knowingly buy the market.

This is an example of one of the nefarious sides of capitalism -- a flaw -- not a celebration of how great it is at solving problems (which is genuinely is in a lot of circumstances).

If Uber didn't have as much capital, smaller distributed co-ops may well have prospered.

:(

> World's Largest Microgrid

Got to be up there (down there?) with World's Smallest Mountain

Fundamentally, if a human can drive a car with nothing but two relatively poor eyes with a pretty small field of vision set in a single location inside the vehicle, an AI can be trained to drive using the same inputs - any more sensors are a bonus.

The other thing people forget is the bar isn't that high: self driving vehicles don't have to be perfect, they just have to be better than humans are. All of the "whatabout" edge cases people proffer as examples of areas an AI would have trouble with, people have trouble with too. The difference is that once an AI learns to solve that edge case, it doesn't have to relearn going forward.

Would these layers be thin enough to be translucent?

As someone with a BSc. in AI from a university that's been handing them out since the 50s, I, er, disagree.

Just remember that the extra sensors are a "bonus": if a human being can successfully drive by just using their two eyes in the driving seat, with perhaps 200° range and a couple of mirrors, then an AI can be trained to do the same.

Human consciousness for one, I'd wager.