Blog Ipsa Loquitur

Some friends of mine run the “All Your Law Are Belong to Us,” a law blog that covers video game happenings. They’re covering the lawsuit between the makers of World of Warcraft and the makers of Glider, a program that players use to cheat at World of Warcraft.

Glider plays World of Warcraft autonomously — a player installs the program and sets it to slay goblins and level up, and the player can then go outside and pretend to be a high-functioning adult who doesn’t pay robots to play video games for him.

(Seriously, if I paid $15 a month for the privilege of playing a video game, I’d be more than a little disinclined to pay more to avoid the chore of playing it.)

Anyway, AYLABTU has the best headline: Glider Crashes After Running Into Blizzard. Go read their post, because they deserve many eyeballs.

I don’t always use a tragedy to market my products, but when I do, I’m Microsoft.

Last week, VeriFone said and did some things calculated to hurt their competitor. VeriFone almost certainly lost the PR war, and I don’t really know what to make of the substance of their claims.

To be brief, VeriFone makes equipment that lets companies accept credit card payments, and they posted an incoherent open letter to consumers and “the industry” about a competitor’s hardware which is functionally identical to their own. VeriFone demands their competitor issue a recall, because such personal information as “name” and “credit card number” can be stolen by a person who runs the card through a card reader.

I wrote “a card reader” because both VeriFone and its competitor have a device that reads your name and credit card number from the magnetic strip on the back of the card. This information is the same stuff that is printed on the face of the card — it’s kind of ludicrous to think this is secret. Anyone who handles or even looks at a credit card has access to this information, not just those rogue users of the competitor’s device. These sorts of histrionics are extremely out of place, and smack of FUD when you consider the relative costs of Verifone to its competitors. (Hint: Verifone is not the cheaper choice.)

The one solid point that VeriFone has in its letter is the fact that the CVV1 codes are not printed on the face of the card, only the CVV2 code is. You can’t read that information with its competitor’s official software; you need third-party software to snag the CVV1 code, which VeriFone helpfully wrote and uploaded to its site (along with a tutorial video posted to YouTube) for all the world to see.

To their credit, VeriFone removed the links once it was (correctly) pointed out that they were acting like children.

I really like GeekDad. It’s a great blog that I’m sure I’ll use when I have geeklings of my own running around the house with lightsabers. But the story Why Watson’s Jeopardy! Win Is Mostly Meaningless is rife with bad thinking. I would assume a lesser site was trolling. That’s how bad this stuff is:

Programming a computer to parse Jeopardy! “answers” is of course the only real advance here, in terms of natural language processing, which is very cool. However, as it’s confined to the form of the show’s clues, which aren’t all or even most written in normal conversational English, all the Watson team has really demonstrated is that a genetic algorithm can be effectively applied to a highly restricted form of language processing, which isn’t really that impressive. I mean, there are many thousands of previous Jeopardy! clues and correct responses that can be used to hone the algorithm, since the way the show’s clues are crafted hasn’t changed much over the years.

What he means:

• This isn’t really parsing language; it’s parsing language that Jeopardy uses.
• Language that Jeopardy uses is not real language.
• I mean, there are thousands of examples of Jeopardy language Watson could have practiced on.

This is colossally stupid. Jeopardy language is a particular subset of language. So is the language I use when I order a pizza, or call tech support. Or use on a quiz show. Interactions in a singular context are, of necessity, reliant on a particular subset of language.

As to the second point, I thought Jeopardy’s clues were difficult to understand specifically because the language used is often couched in verse or obscure allusions. I don’t know how you can make the claim that Jeopardy’s clues are somehow easier to grasp than ordinary English with a straight face.

Except by resorting to the third point: there are so many examples of Jeopardy language that Watson could learn from, that an algorithm was as much an inevitability as an innovation. If that statement is true about this fabled, transparent “Jeopardy language,” than the statement is a thousand times more applicable to the English language. For every book of  Jeopardy-language clues Watson could have practiced on, there is a library of English language to practice on.

Reasonable minds can disagree, but to call this meaningless is at best intellectually dishonest, and at worst, simple trolling for hits. Either way, I expect better from Wired.

The internet should be a place for new business models, not new delivery methods retrofitted onto yesterday’s business models. Marco Arment:

First, it’s weird to me, as a long-time internet-only news reader, to pay money for a bunch of content I don’t care about. More than half of each issue is sports news, entertainment gossip, ads, and little newspaper games (crosswords, Sudoku, horoscopes), and I need to buy all of that to get the news, editorials, and app reviews that I care about.

Bundling a bunch of stuff I don’t care about with the few pieces I want to read is the old-world model, when custom-targeted or on-demand news for each reader was infeasible. But in this century, I can go to a handful of websites whenever I want news, view the handful of stories that interest me, then move on. Flipping through a bunch of uninteresting-to-us content and ads was an annoyance of the old world, like blow-ins, that we tolerated because we had to — but now, we don’t.

Read the rest at Marco.org.

I love the movie Groundhog Day — it popped up in several of my philosophy classes in college, and again in law school. The Library of Congress has a copy archived, because the movie is a significant cultural work. Phil spends years trapped in a time loop, but the movie never specifies how many. I just read the most definitive deconstruction of it:

The first stage is to work out how many separate days are shown on screen during the movie. So here’s a good old-fashioned list of them:

• Day 1: Groundhog Day
• Day 2: The first repetition
• Day 3: The fixed pencil
• Day 4: Punching Ned
• Day 5: Deceiving Nancy
• Day 6: Robbing the bank
• Day 7: Seeing Heidi 2 with a French Maid
• Days 8-12: Engineering the near-perfect date
• Day 13: The bad perfect date
• Days 14-21: One for every slap
• Day 22: “Phil you look terrible!”
• Day 23: Jeopardy
• Day 24: “This is pitiful!”
• Days 25-27: Breaking the alarm clock
• Day 28: Kidnapping Punxsutawney Phil
• Day 29-31: Phil’s suicides
• Day 32: I’m a God!
• Days 33- 35: First piano lessons
• Day 36: Sexually harassing Ned
• Day 37: Looking after the homeless man
• Day 38: The final Groundhog Day

Read the rest at Obsessed With Film.