Fj_
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According to the links from the Scott's post, Rob Reich's position is that we should tax charitable donations at the exact same rates as all other spending, with an exception for under $1000/year donors getting 25% back. No more, no less.
I personally think that this is a blindingly stupid idea because it assumes that everyone who donates more than that will donate even more to compensate for the government taking a lion's share of their donations, because he sort of got himself into a frame of mind where he sees donations as more of a privilege to change the world according to one's wishes given to the donors, not as a lifeline for the recipients.
But nothing in the two articles about his position I read suggests anything more sinister than that misguided plan, which even makes sense on his own terms.
Keep in mind that a lot of user-submitted programs will try to do the same (because writing a step-by-step interpreter is hard), so they would keep evaluating each other spawning watchdog threads every time, so, um, your watchdog thread would be badly outnumbered.
The easy fix for you would be to run your watchdog in a separate process, but players wouldn't have this ability, which might make things either more interesting or boring (ruling out all strategies using eval). Maybe a specially designed restricted subset of Scheme with time-restricted eval would be a better choice?
By the way, after looking at your payout matrix to see what should I do if I see the... (read more)
I don't know what this was a reference to, but amusingly I just noticed that the video I wanted to link was a 2007 lecture at Google by him (if it's the same Geoffrey Hinton): https://www.youtube.com/watch?v=AyzOUbkUf3M
In it he explained a novel approach to handwriting recognition: stack a bunch of increasingly small layers on top of each other until you have just a few dozen neurons, then an inverted pyramid on top of this bottleneck, and train the network by feeding it a lot of handwritten characters using some sort of modified gradient descent to train it to reproduce the input image in the... (read more)