The harm most people are concerned about is mammals and birds. Pieces of plastic that are 'the size of a grain of rice' - don't pose any risk to mammals and birds. They also don't pose a risk to the majority of marine life.
The author claims the devices will 'break really quick' - devices engineered to be submerged in the ocean constantly have different design constraints than devices that are for capturing wind energy. There is no reason to believe that a properly designed structure will be prone to failure and breakage.
The author claims the devices will 'harm wildlife' - as long as it is a net harm reduction (which seems likely) who cares? Also she grossly exaggerates the risks of harm.
The author has a point that the captured plastic won't be desired by recyclers - not sure why that matters. Worse case scenario is burn it.
Her next two points have nothing to do with the device - beach clean up can occur independently of the booms.
Devices to reduce plastic waste flow to the oceans can still be done.
At 220 calories per day deficit over 6 months they would lose about 11 lbs of fat.
6*220*30/3500 = 11.3
At 220 calories deficit over 7 days, they would lose
So the 1.5 lbs doesn't make sense (in reality they probably just depleted their glucose storage a little bit which lost a 1+ of water weight).
They are not playing four handed.
It is four simultaneous games of headsup poker and it is mirrored hands (so we see where a human loses more of less than the bot with the same cards, and 'coolers' mostly get canceled out)
They played 20,000 hands each.
It was in mirrored play. So player A and B got one set of hands that they played against the computer; and C and D then got the computers hands and the computer got the same cards as A and B.
This greatly reduced the variance in outcome.
They were playing with 200 deep stacks (20,000$, with blinds of 50/100). So the humans were up by 31 buyins; or an average of about 8 buyins. Certainly not a huge margin of victory for that many hands.
If the fines purpose is to be a deterent, then the fine must be sufficient to result in a deterent effect.
If the fine is meant to compensate the public for the harm caused, then the fine should be adequate to cover the cost of the harm relative to frequency of individuals being caught.
If the fine is meant to cover the costs of enforcement, then the distribution of the fine makes sense to have it be on ability to pay.
The highest reasonable price would be that of a cheap community college. The price of an Ivy League is due to the value of the networking (both your peers, instructors and alumni).
You've confused statutory with effective rate.
The US has one of the lowest effective rates (how much the corporation actually pays after deductions, etc.), but one of the highest statutory rates (the worst theoretical possible rate that a corporation would pay if it had zero deductions and enormous profits).
My theory is that these are inducements to keep the 'double irish' and 'dutch sandwich' tax dodges available. It seems highly unlikely that Ireland and Netherlands, the two countries that have Allowed apple to avoid hundreds of billions in taxes, and which have suggested that they might change these tax practices, have suddenly become recipients of major investments.
Consumption taxes are relatively easy to evade.
Also the benefit from public tax expenditures isn't proportional to consumption, it is proportional to net worth.
Bill Gates benefits enormously from public education and public funding of universities. He benefits enormously from international trade negotiations and the military keeping international trade relations stable.
The creativity involved from my limited exposure seems close to nonexistant.
I don't really see any benefit from it, compared to any other game. Are parents just deluding themselves? Or is there some substantial creative benefit that I'm not seeing?
It doesn't cost anywhere close to that to bring a new drug to market try more like 43 million, but actually a lot less.
That is surprising that folks that claim C knowledge don't know that.
"There's a pretty big maturity difference between a grown-ass man and a 10 or 11 year old."
For many men, not as much as one might hope.
R has been around for a long time and has long been a standard.
Pythons sklearn is indeed an 'emerging star'.
Personally I use both.
Also have a look at some of the many stand alone tools vowpal wabbit (blazingly fast for regression learning, scales to ridiculous amounts of data) is superb, as is sofia-ml (for clustering, again scales quite well)
I tie them all together in python, since there are python bindings for R, and you can use pythons 'Subprocess' module to pipe commands and data for commandline tools that don't have python bindings.
There are other useful tools as well - I use Weka for some of my initial visualization and when I'm feeling lazy and want a quick result.