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The AI summaries are almost universally wrong or incomplete in an important way for everything I've search for lately. It's honestly devaluing the site in ways that might be hard to recover from.
With crazies it's not that bad. I remember the bus getting pulled over once by a car with people with pipes/bats who beat a grandpa for getting in an argument with one of the guys prior. That was the only actually violent occurance over thousands of rides, however I still have yet to feel as threatened with a personal vehicle. With a car I could have rammed the fuck out of them or ran them over, with a bike I could have been gone in a second, when the bus driver stops and opens the front door you're just stuck. Again, realistically it's mostly crazy homeless people who pose no threat but I prefer to have some control at least.
My issue with electric bicycles is:
If limited they don't fit with pedestrians or cars so you need to complicate infrastructure. Good for going to the post office but not as a daily since they're just not fast enough. Lovely for old people and to an extent kids.
If not limited they are less tested motorcycles with usually shitty tires and brakes, no ABS, TC, etc with pedals to fulful some potentially existing legal loophole since there's no way you're doing anything close to the motor output manually yet since you feel inclined to pedal gear becomes problematic.
I still have yet to try an electric motorcycle but I'd guess the little electric scooters would be great for commuting. I'm guessing an electric scooter that can do 100-140kmh would be the utility sweet spot. You'd be able to go everywhere and charge for pennies with minimal maintenance. You'd also get the scooter benefits of improved road muck/weather protection and actual underseat storage.
Can you share what these "hard problems" are that > 1% of developers are working on?
Lately most of the code I write has been through LLMs and I find them an enormous productivity booster overall, but despite the benchmarks they're not expert human level quite yet, and they need a LOT of coaxing to produce production quality code.
As far as things LLMs are bad at, I think it's mainly the long tail. I'm not sure there's one singular thing that >1% of programmers work on that LLMs suck at, but I think there are thousands of different weird sub-specialties that almost no one is working on and very little public code exists for, thus LLMs are not good at them yet.