2,703 karma · joined October 13, 2010
I won't try to defend the 3Gs ;)
The couple of times we've gone with guides who are serious birdwatchers, it is impressive to watch their abilities in this area of multimodal species identification (and male/female/adult/juvenile) in challenging visual and audio environments (and recall of species names in Latin, English, and Spanish).
Meanwhile I'm out there with my camera like "Hey, look at that beautiful red+blue bird!" ¯\_(ツ)_/¯
https://www.nbclosangeles.com/investigations/westwood-99-ran...
I don't say this to suggest excusing autonomous car companies from bearing liability, but just for context.
Perhaps we should not make the regulations too punitive on the AV companies as that would reduce the speed of replacing bad human drivers who currently cause 40,000 deaths a year in the US.
Pretty sure they are singlehandedly responsible for years of renewals...
Not confusing for me at all. But nice try.
If only!
And, importantly, they were physical in a time when it was hard to collect and collate the data in all of them. In 1990, there were about 5,000 distinct "white pages" phone books in the US. And OCR was pretty crappy.
Also, in all the places that I lived, mobile numbers didn't end up in the phone books, only residential landlines did. I don't know if that was universal.
How you can tell it's from 1997:
The master fell silent, but on his way out he pocketed a 20 Gigabyte corporate backup tape that was lying around.
It's clearly the case that people who are overweight, smoke, or consume alcohol heavily should pay more for health insurance based on massively increased risk of loss.
Fortunately, other forms of insurance (e.g., homeowners, automobile) are not regulated in this uneconomical fashion.
Given that the annual premium is like 0.27% of the value of the policy, a change in risk of a few percent because some big tree limbs were hanging over the house or because some brushes might have enabled a fire to spread to the house more easily could clearly swamp the value of the premium to them.
And, to be clear, I didn't want to spend $2,000 to fix the problems, I would have rather not had to deal with it, but that's part of the joy of being a homeowner.
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We live in a place (California) where the government has generally prevented homeowners insurance companies from effectively charging for risk (e.g., wildfires) and therefore many companies have stopped writing policies altogether. This doesn't seem like a good outcome. Note that this is the same state that won't let auto insurers charge based on "black boxes" either, so good drivers are subsidizing bad drivers (even more than in other places).
Yes, but this does not imply that customers with (potentially vastly) different risk profiles should pay the same rates.
The canonical example is that 18-year-old single males with previous speeding tickets pay more for auto insurance than married 40-year-old women with clean driving records.
While there are certainly some issues of concern in the article and the reviewed book, the above seems like exactly what insurance companies should be doing: pricing (or making available) coverage based upon risk.
This is not much different from an auto insurance company raising your rates (or cancelling coverage) because you've received a number of speeding tickets, which implies increased future risk of loss.
In fact, I received a letter from my homeowners insurance company a couple years ago stating that they would not renew our coverage due to conditions that they'd observed (clearly from aerial imagery) including overgrown bushes touching the walls of the house and some larger tree branches growing over the house.
I had a landscaping company come and fix the issues, sent my own drone up to take new pictures, sent the company the pictures, and they agreed to continue coverage. And now my house has less future risk of damage. This seems like a win-win for both of us.
Just as you can use that set of facts plan and optimize your budget, so should Ralph's be able to use that data to plan and optimize their business.
Unions are very much an in-group vs out-group phenomenon (and in many cases, the benefits are specifically to the more senior union members vis a vis the less senior ones.)
Amazon makes nearly a billion dollars in profit from search ads. Every week. Each week, they sell merchants and publishers enough search-distorting ads to capture a billion dollars in revenue.
Is it revenue or profit? They are not the same thing.
I would say that's not necessarily the case unless there are zero false positives. In fact, your university situation is exactly where a detection system that works 50-90% of the time would be a nightmare if a meaningful share of the 10-50% errors were false positives.
https://www.goodreads.com/book/show/6055.A_Voyage_for_Madmen