And the money is actually from the Insurance industry, whose goal is to drive down utilization while driving up fee-for-service. This way, they make a little money on non-insured procedures but make a shit load of money by keeping more of the insurance premium. It's messed up... (I work in the dental industry, and see practices getting bought by DSO's, PEs and VCs only to go from $1M / chair / year to 50k / chair / year. all the time).
They're starting to break the code on it, but there are concrete docks that Rome built 2000 years ago that still exist today - we have trouble building salt resistant concrete docks that last ~100 years.
Apparently it has to do with using a certain type of volcanic ash in the concrete...
Spent three years an eight months working in retail hell, and this was exactly what the company pushed employees to do - they were kind enough to sell shares to employees at a 10% discount but you had to be crazy, grossly miseducated or drank a bit too much of the kool-aid to believe that this organization was a good value store.
Total tangent, I used to have the Office 365 subscription but canceled it, yet I can still use word/excel - I've just lost access to the cloud features which I wasn't using to begin with - I would have thought they'd disable my version of word/excel but when I canceled it did not happen.
Blame the insurance companies - most major insurance companies use your SSN as a mechanism for identifying the patient. The member ID #'s can be used but it's quicker to just input the SSN.
The cold war was ended by the Strategic Defense Initiative - not because it worked but because we forced the USSR to pour resources into matching us and it bankrupted the country.
A million years? I think you over-estimate how insignificant we are to this planet.
I'm not advocating we destroy the environment, but we really can't do a whole darn lot to it. Can we set off every nuclear weapon at once? Sure, but even that will likely just ruin the surface for 50,000 - 100,000 years. Life will continue, just not humans and most likely nothing of any size.
If we manage to throw the planet into a run-away greenhouse cycle like Venus, yeah, life's done here but that seems like a tall order (though I am not well read or well versed on this subject matter so I could be wrong on this count.
Ok, off the soap-box, you were making the same point as me :)
I think the general point holds as $19.5B is a rounding error in the US's budget. There are issues with the lack of funding to EPA but with respect to this discussion it's a straw-man.
Of course peoples greed contributes to this problem. Each and every one of us have some suspect ancestors in our gene pool. It's how evolution works, so saying "But we're greedy and we need to fix that first" seems silly to me - you're fighting millions of years of evolution. That doesn't mean that I want to see unfettered capitalism, but these problems won't go away by sitting around a camp fire and singing Kum Bye Ya My Lord.
Our consumer consumption culture won't change until it has to, whether that means folks going into space and living in an incredibly demanding environment or it becomes untenable on this planet. Wish it were different, but that's just how this stuff works.
I would argue that actually it does - in order to bring the world commodity market crashing, as is suggested by the article, it requires iron coming down to earth and bringing mass down the gravity well, safely, requires either a great deal of energy or something like a space elevator.
Under the assumption that no space elevator exists, then this argument is spot on. The iron outside of earth's gravity well would be cheap for building in space, the iron on earth would be "cheap" for building on earth.
Commodity movement in either direction wouldn't make sense, so two distinct markets for iron would exist.
You do realize that we're still dealing with the world of models that need be trained. Models are only as good as the data that is given to them, and data is only as good as those who collect it. Neural Networks aren't even close to real AI, they're black-box models - believe them blindly and catastrophe will follow. An excellent example I recently read pertains to a hospital attempting to use a neural network in determining whether to send pnemonia patients home or have them stay in hospital for treatment. The model told them to send asthmatic patients home. Why you may ask? Well, asthmatic patients were always triaged to the ICU, thus the results told the hospital to send this group home. We don't even understand cognition in the human brain, how can we expect to stumble upon it with digital systems?
It's like every seminar and workshop about getting rich quick, write a book, run a seminar and get back to pay you for four hours a week about how to only work for four hours a week.
Now, his workout manual actually has lots of valuable data and insight and is excellent for applying the 80-20 rule as you can find workouts in there that take very little time and produce great results.
The entire tone of the article is rather off-putting. Through portions of the article there tended to be this sense of having pulled one over on corporate America, when that is hardly reality.
One data point: Nordstroms. They will take everything in returns. For them, customer lifetime value add of a hassle free customer experience outweighs edge cases like the author who take advantage of the system.
I'm sure there were many instances of the author taking advantage of the bureaucracy of large corporations, but that's no particular feat of genius- that's a byproduct of bureaucratic systems.
A writer whose name currently escapes me said something to the effect of, "Love your stories, but never believe them".
There's a lot of intuition and experience that is required to be a talented statistician; once the test has begun things are pretty much locked down (ie, if you know the math there is only one "right" answer from the data). The intuition and experience side of things comes with how the test itself is setup. Are things properly controlled, are you collecting the right data for what you're testing, is the data distributed properly for the test statistic you're using...the list goes on and on and on and on and on.
There are plenty of places that require intuition and these are the places that errors are often introduced. Statistics is an art.
Interesting post though I feel the author is somewhat missing the forest for the trees; the issue isn't about "real-time" the issue is that many people conducting A/B tests don't understand what the statistics are telling them nor do they understand when an adequate "sample" has been pulled.
Real-time data isn't needed for A/B testing but this falls into the PEBKAC category.