In the Financial industry, "Quants" or Quantitative Analysts use statistics and sophisticated heuristics to feed ideas and information to organizations that deal with trading in the various markets (stocks, options, futures, commodities, forex, etc.), such as hedge funds, statistical arbitrage operations, and private investors. It's a high paying, highly challenging position that deals with all kinds of mathematical functions and techniques, such as optimizing adaptive filters. It's one of the best places for a mathematician to earn a great salary, but your skill and experience needs to be very top level.

The page source shows me some beautifully nested divs indicating game components (like HUD). Is this all javascript?

Excellent film, even better quote!!

...someone makes this in Minecraft.

I am strongly in support of privatized/commercial space exploration, such as SpaceX and Virgin Galactic. For all the standard reasons of competitive innovation, and public accessibility, I believe this is one of the most promising endeavors that people can take on, despite the seemingly impossible barriers space imposes.

I got really excited for a very cool-looking game called Spore that came out a few years ago. But then I read about it's DRM policy, which only let you install it a limited number of times before the key became invalid.

So I didn't buy it. And I've never played it.

Correction: I confused PSpace with P. The above definition is for P and NOT PSpace. Haven't spent much time thinking about complexities ABOVE NP hard. PSpace actually considers the "memory" you need to solve the problem. This is relevant when you talk about Turing machines, where you have to use "tape" that you "write on" while solving the problem. The thing that's been proved is that you only need a polynomial amount of memory (relative to 'n') to solve problems that need NP Hard time.

To solve a problem that has 'n' parts in it:

PSpace hard means the problem is relatively simple, maybe check n things n times, which is only n*n things. For example, "For n cities, find the sum of all the distances between all the cities".

NP hard usually means you have to start at one part, then make a new decision each time you want to move on to the next part. The classic example is: "for n cities, start at a city and find the shortest possible distance to visit each city once". Since you have to make a new decision every time, you can solve this problem using permutations: you have n choices for the first city, then n-1 choices for the next city, then n-2 choices for the next city, and so on. To check ALL of the possible routes you can take and select the shortest, you need to check (n)*(n-1)*(n-2)* ... * (2) * (1) things. That's a factorial, and is denoted n!.

So for 12 cities:
12*12 = 144
12! = 479,001,600

For 20 cities:
20*20 = 400
20! = 2.432902008×10^18

The "search space" for problems that are NP Hard explodes to quickly to solve any reasonably sized problem. So basically, computers can solve problems that are PSpace hard, but they can't really solve any NP hard problems that are worth solving. E.g., to solve the NP Hard "traveling salesperson" problem I described above for all the cities in Italy, there's something like 12000 cities, which is (almost) impossible to solve with a computer. For fun:

12000*12000 = 144,000,000
12000! = 1.201858406×10^43741 (and that's just nuts)

The above is not the only way a problem can be NP Hard, but all these kinds of problems have "similar" classes of "time complexity". If you model this "time complexity" (that is, count the number of things you have to check) as a function, PSpace hard problems are polynomials at worst. NP Hard are worse than polynomials. The notation used here is called "Big Oh", and the above two problems are O(n^2) and O(n!), respectively.

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I've been told by a reliable source that at their new data center, Apple is building a large slingshot aimed at FaceBook and has been accumulating large quantities of caged birds.

Sorry, they had to ship the article before it passed QA. We have created a support ticket and are working on a patch to resolve the problem.

...a young man whose parents-in-law move in to his home.

Jack Eisenmann will never need more than 256 bytes of RAM.

This is why I love Australia. The people have their priorities straight.