A bot to do this for a more complicated games like FPSs would be interesting. To play well would involve solving a number of AI/computer vision problems. The bot would have to pick out enemies from the image it was seeing, it would have to figure out where it was on the map from visual cues and determine where to go, and so on. It would be a simplification of the problem of creating a robot that can intelligently navigate its environment, with the actual physical robot abstracted away to "push the stick forward to run."

What's the difference between "virtual" entertainment and "real" entertainment?

Why are all the links in this article to bit.ly shortened versions? I want to know what site I'm going to.

Mostly this is just a demonstration of how a computer can, from the initial scrambled state, immediately see clear through to a solution in a relatively short path, whereas humans can't visualize a whole solve instantly, and so they take it in steps, at a significant cost to solution length. Comparing the two videos you can see that the human is much faster than the robot at making sequences of turns, but must make many more moves than the robot.

No; all the major quests can be resolved in at least two different ways depending on how you decide to play, with effects right up to the ending. And of course there are several endings depending on player choices.

You mean, like the open source "investigation" of the leaked climate change research group emails? That turned out well...

Hmm. Looking at those sample images suggests to me that it's impossible to do something like this with satellite imagery. No one could write a program to distinguish ten red balloons from the tens of millions of red cars in the US.

I'd just like to put in that BattleMaster, the game cited in the summary, is awesome. I don't play it now, but I played it for four years or so and it's excellent. It's an amazing long-term game that mixes strategy, politics, and medieval roleplaying. You're always on a team (a realm of nobles), and you're usually at war. Wars are intricate affairs lasting months and punctuated by battles every few days. Realms can be created and destroyed, and the politics of a continent will slowly shift over the years as territory changes and hand and alliances are formed and broken. For those that are into it, there is real role-playing--that is, story-telling not directly related to game strategy, unlike pretty much all so-called massively multiplayer online "role-playing" games, where the world has a story but you wouldn't know it from the way players act and talk. In BattleMaster, people act like nobles, and one actually feels immersed in a real feudal society. As the summary suggests, it needn't consume much of your time (10 or 20 minutes a day will cover you), but if you get into it it can entertain you for much longer. I hope this mention on /. gets a few people into BM.

Engineer sounds, duh.

Do you tune out the whir of a car coming towards you while you're crossing the street? That's what this is about.

Some people might be interested in knowing where all this data comes from. There's a rule of thumb in astronomy that the angular resolution of your images is the wavelength of the radiation you're receive divided by the diameter of your telescope. Radio wavelengths are pretty long (up to tens of meters), so you need really big telescopes, which you get by scattering lots of little telescopes all over the place and then looking at the how the phase of the incoming radiation shifts based on location. So what you do is you sample the voltage of each antenna with 1 or 2 bits of resolution at the Nyquist frequency. So for 100Mhz radio waves you sample at 200MHz. That's 50MB/s for a single antenna. The SKA will likely have tens of thousands of little antennas scattered all over the place. So say 50MB/s times 20,000 antennas = 1TB/s = 100 petabytes/day, which is about what the summary says.

Now, it's not quite as bad as it looks. You don't have to pipe all this data to a central point to analyze it. You can take a small group of antennas and just look at the correlations between those, combine the data from that group and send the combined data to a second level of correlators, which takes data from a set of small groups, and so on, in a hierarchical fashion. You lose some information this way, but you get most of it, and the only wa to get all the information out of the data would be to bring it all to a central processing location so that data from all antennas could be compared to that of all other antennas, which is O(N^2) in the number of antennas and obviously infeasible for a telescope like the SKA. Even as it is, the system of hierarchical data collection is really pushing Moore's law, as the article shows.