My guess would be there's a healthy dollop of regulation pushing the German insurance market into that shape, otherwise you would probably see short-term insurers outcompeting long-term insurers since they wouldn't have to do old-age reserves and could therefore charge lower premiums. Consumers tend not to be nearly as good at rationally planning for long term expenditures as are actuaries.

Just seems very hard to believe a project as massive as a whole new airplane is the best solution to this problem.

The town in question (Salisbury, MA) is built on a narrow strip of land between a marsh and the ocean. Mostly between 2 and 5 houses wide. Doesn't seem like you need a geology PhD to determine you're going to have some erosion problems here.

As best I could determine, the beach replenishment in question was from access points 5 - 11, which covers 1.6 miles and about 150 homes. If I'm right on that, they put down enough sand to extend the beach 3-7 feet[0]. So the first thing to note is that this was a very small beach replenishment project. The senator is probably right that they should go bigger next time.

The cost per home for that would have come out to about $3333.33. Honestly, even if you triple it and do it every year, I don't find that to be an unreasonable expense to impose on owners of $1-5 million houses built on a sand dune. These guys need to quit whining and raise their _local_ taxes the relatively modest amount necessary to preserve their town. Something like $5k/year for beachfront and $1k/year for the rest would get the job done.

[0] This is assuming a constant slope to the beach. The low end is extending at 3 feet above sea level, the high end is extending at 6 feet above sea level.

"Factors that may also play a role in health, outside of daily duration of eating and cause of death, were not included in the analysis."

The health insurance situation is not great, but it's available through Obamacare. In my experience the actual cost is not much worse than employer provided, but the true cost is often subsidized, so employees don't always realize how much salary they are giving up for health insurance.

No eligibility for unemployment or workers comp though.

'enhance customer and crew experience' - Neither customers nor crew like it when the restaurant is busy enough that the line gets long. By making it more expensive to eat at peak times and less expensive to eat at off peak times, they think they can smooth out the demand schedule. Of course whether that's a net positive to any given consumer depends on their relative preferences on meal time, wait time, and meal cost. But the potential is there at least. On the crew side, a smoother demand schedule means they can either schedule fewer people on longer shifts, or if they keep schedules the same reduce the amount of "crunch time" during each shift.

From some of your other replies it looks to me like you're confusing that with an improved bound on the value of the solution itself.

It's a little unclear to me whether this is even a new solution algorithm, or just a better bound on the run time of an existing algorithm.

I will say I agree with you that I don't buy the reason given for the lack of practical impact. If there was a breakthrough in practical solver performance people would migrate to a new solver over time. There's either no practical impact of this work, or the follow on work to turn the mathematical insights here into a working solver just haven't been done yet.

There are two numerically painful parts of the problem: the advection term and the oscillation inducing terminal condition (because it has a discontiuous derivative). I like to deal with advection by transforming the equation to an advection free equation. I'm under NDA on the best solution to the oscillatory terminal condition so I can't give that one away unfortunately.

Comments URL: https://news.ycombinator.com/item?id=38106906

Points: 3

# Comments: 1

The comparison with Uber depends strongly on how similar the dispatch profiles are, and I would not be quick to assume that they are similar. If they are limiting the self-driving cars due to weather, or time of day, or any property of trip type it could easily have a substantial impact.

I believe that you are correct that scale is too low for analyzing injuries or deaths.

But the obvious way to prove this, to me anyway, is to run a randomized controlled trial. Put them in a dispatch system with human driven cars, randomize whether any given assignment goes to a human or a robot, and you've got the statistical gold standard.

Anybody understand why they're not doing this?

The numbers were confusing. Among them, for 2021-2022:

Ridership: 156,904

Revenue Mile: 315,409

Total expenses: $2,022,634

Fares collected: $3,255

The total fares and ridership from the budget do not seem consisten with the unit fares discussed in the article.

My best guess here is that the fares discussed in the article aren't showing up in the financial statements, and the ones in the statements are for another service entirely, maybe disabled transit.

Across their entire system, they're spending $12.89/ride. I'm lacking data for this assertion, but my gut is the non-microtransit stuff is fairly negligible here. Even if we knock it down to $10/ride we're still talking an 80% subsidy.

But 2019-2020, before the switch to microtransit they were at $28.03/ride. So they do seem to be picking up substantial operating efficiency, even if it's still heavily subsidized.

Covid's probably skewing that substatially...2018-2019 only $15.15 subsidy per ride. So still some improvements but not that amazing. And they were collecting $0.73/ride of revenue, so that subsidy rate was 95%.

The experience of one victim mentioned suggests it's economical to crack at least 50 bit entropy passwords for at most a $3.5 mil payout.

50 bits isn't great, but it's not terrible either.