Help trade $1,000,000 for people to buy drugs for personal use: 2 years in prison.

Help trade $10,000,000,000 to help drug cartels launder money: er not sure. Remind me what happened to the HSBC execs again...

"Look! We built a telescope!" Yeah that's cool but I don't care, we already had telescopes.

The level of dumbassery in that statement is to high, you'd need a NASA rocket to get to the top of it.

Yes, a couple of old lenses and a cardboard tube is a telescope, as is Hubble, but to claim that they are somehow equivalent is just silly. It's like clutching your trusty Z80 and claiming the last 30 years of development are a complete waste because "we alread had computers".

"Hey, we have this permanent space station!" Who cares? Is that another world? No.

Good job that building and operating a space station in orbit tells one nothing about building and operatin one for going between two planets. It's a TOTAL waste of time to find out how things should be done rather than ploughing blindly ahead and hoping for the best.

Jesus christ, man, he's 11. Get him RPG Maker and let him figure out how to make a game with his own made-up story behind it.

Huh?

I don't think I'm exceptional by the standards of kids who learned to program. I started programming at age 11 because I wanted to write games. I managed to get a simple space invaders type game written myself from scratch in BASIC.

I the kid wants to learn to program games, 11 is an OK age to start.

I really fucking hate this about academia.

Nope, you mean "American undergraduate university teaching", not academia.

This is not an academic thing. This is something very peculiar to undergraduate teaching in the US.

I think partly it is the obsession with setting millions of questions for students to do. That way one can make it easy on the lecturer by declaring that the student just do a bunch from a textbook.

The system I went through doesn't even remotely work in that way. At the very beginning the lecturer in question (which eventually included me, at least for a while) made a list of recommended books. There were usually about 4 or 5 of unspecified edition, and there would be a bunch of some of them in the various libraries. Students were very much NOT expected to buy any of them unless they really wanted to. As the courses got more specialised, the list of textbooks would get longer (as no book covered everything), then disappeared completely when it became too cutting edge.

Some of the lecturers more advanced in years would occasionally give a glowing recommendation to a book that went out of print some time during the paleocene. I suspect it was a book they found useful as an undergrad and never checked to see if was still in print.

We then lectured. Every so often, a sheet of about 10-15 questions was handed out such that there were about 4 sheets in a 16 lecture course. The questions and lecture notes are generally handed to the next person when the course moves on to a new lecturer for them to use or ignore as they see fit.

It works well. The question sheet means that a specfic edition of a book or even a specific book at all is not required. Us writing the questions means that there's more incentive to have a small number of good questions rather than vast heaps of busy work.

I teach out of a thermodynamics text that gets churned every year or so.

Well, then don't. I went through university in the English system, up to and including being a lecturer for a while. The simple solution to this problem is simply to NOT teach out of a text book in this way. It is simply not in the unicersity culture here to to that.

Textbooks are helpful but the students do not need THAT specific textbook.

The first thing to do is write the questions yourself[*]. They're not nearly as hard to write as exam questions because frankly if you screw up a bit on one or two it matters much, much less, they also don't have to be a consistent length or difficulty. You also have a textbook full of questions for insipration. On the courses I was teaching, the lecturers would always hand materials to the next person, and the question sheets often had the year in which the questions were written. One nice undergraduate reminded my of my age by declaring that some of the questions were older than he was.

So, find a few good textbooks and recommend them to the students at the beginning of the course, as a genuine recommendation and not a recommend but I actually mean you have to buy this kind of thing. Then give your lectures and set your questions. The students can then work from the lectures, or any edition of any textbook.

[*] One problem is it seems the American system is based on setting vastly insane numers of questions, which may make this more difficult.

Really though, the last ethics class I took required an e-book with a 3 use license and six month expiration that cost $130. So, after six months, there is no access to the material at all, like a returned library book without even the value of a paper-bound book that could be burned for warmth.

Well, ironically that probably taught you a lot about ethics.

Why does jay-walking turn you into an evil anti-american, versus walking ten feet down the road to use the crosswalk?

Why indeed? Jay-walking is another of those insane laws. We get around fine without jaywalking laws in the UK. It's much more pedestrian friendly for a start.

The tobacco industry, big pharma... okay, I'm out.

Well, I was thinking of Hitler and the Nazis. They're always a good standby for extremism :)

You should really look into dropping Gamergate entirely, to divest yourself of its now relatively toxic branding, and creating several focused movements to replace it.

"relatively" toxic branding. I like precision. I can indeed think of things with more toxic branding, but not all that many mind you.

With the obsessive focus on quarterly profits, 2 years is a very long time. In reality, esprically with a company that size it is not. Large organisations are very slow to steer.

Yep, the BBC is a single homogeneous unit, so the higher ups protecting Saville during his active years 20 years ago or whatever are EXACTLY the same people as those doing the investigation. On that note we should arrest the geniuses at the local Apple store for human rights abuses because they are clearly the same people.

Not to mention their disgraceful one side coverage of the Scottish referendum on Independence this year have left many like myself really not giving much of a shit as to what they have to "report" these days.

Well, Salmond's ludicrous wishlist er, I mean plan for independence was fatally flawed in many ways. The thing is the case against was mostly "the case for is really flawed". Which was true. But yeah, journalists should give equal weight to each sides. Teach the controversy!

Just as gamergate is skeptical of conspiracies like 'patriarchy theory'.

I like how instead of responding to the GP and addressing his points, you jump on to a complete non-sequiteur and start beating that to death.

I called it cheating because they violated both one of the prime rules of AI: train on a data set that is more or less representative of the data set you will test with, and one of the prime rules of statistics

But they're not trying to do that. They're trying to debunk the claims of "near human" performance, which they do very nicely by showing that the algorithms make vast numbers of mistakes when the data in is not very, very close to the original data.

They also present a good way of finding amusing failure cases. I'd never thought of optimizing misclassifications to find how and where an algorithm fails.

Sounds like a plan.

Products are for suckers.

They should focus on social clouds for wearable augmented reality drones.

I think I understand... vaguely. To simplify, you're saying it's been trained on a specific dataset, and it chooses whichever image in the dataset the input is most like.

A bit.

It's easier to imagine in 2D. Imagine you have a bunch of height/weigt measurements and a lable telling you whether a person is overweight. Plot them on a graph, and you will see that in one corner people are generally overweight and in another corner, they are not.

If you have a new pair of measurements come along with no label, you could just find the closest height/weight pair and use that. That is in fact a nearest neighbour classifier. It works, except that you need to keep all the original data around.

If you imagine taking 1000 points along the two axes (1,000,000 in total) you could classify each of them according to who is nearest. If you do that you can see that there is more or less a line separating the two groups.

Machine learning is generally the process of finding that line, or an approximation to it somehow.

The DNNs don't find the nearest neighbour explicitly: they just tell you which side of the line a given input is on. They also have a bunch of domain specific knowledge buit in because we know something about the shape of the line, which helps find it. For example, image objects may be scaled up or down in size or distorted in a variety of ways.

Is that about the gist? I'm probably not going to understand things about higher dimensions without a lot of additional information.

The answer is in fact tied into dimensionality. In the 2D example, you can cover the whole space with 1,000,000 points. In 3D to do the same, you need 1,000,000,000. Beyond that the numbers rapidly become completely infeasible.