Clearly this kid is the exception, in that he is looking for more work to do.

What were you doing with your time when you were 15 years old? Well, unless you were founding your very own startup, get ready to feel bad about yourself. Fast Company recently talked to Tanay Tandon, a kid who last year found the time to write the algorithm for Clipped, an app that ingests news articles and spits out a bulleted summary.

Why did he do it? Because he's a competitive high school debater, and he is tired of devoting all his time to research:

I’m a Lincoln-Douglas debater, and it involves lots of prep, reading evidence files and cases. It’s a long process for me, and I wanted to find something to condense an article into something more concise and readable.

This reporter, who spent a substantial chunk of her years in high school "cutting cards," or picking pieces of evidence out of U.S. News and New York Times articles, is in no way surprised that it would be a debater trying to disrupt the mind-numbing process of research. Do you know how many articles Lexis-Nexis turns up when you search for "President Obama"? Call your mom, because you aren't going to make it home for dinner.

In short, there's a fair chance that if this kid can actually make this thing work, he'll be a hero to grateful debaters everywhere.

However, if we might be forgiven a moment of back-in-my-day griping, learning to parse information on the fly is sort of the point of doing high school debate.

More like ActionHeroBot, right? (Photo: Georgia Tech)

They might be able to make burritos and rescue the drowning, but robots are still lacking in some basic functionality. Namely: The ability to do very much with tools. Those of you who've seen Planet of the Apes and/or ever attempted to jimmy the cap off a beer bottle will surely recognize that this is an important part of our special sauce as a species, and one that our mechanical brethren can't quite yet replicate. Hence, as per the MAKE blog, a team of researchers at Georgia Tech are working on that.

Specifically, they would like to build a robot MacGyver.

As this Georgia Tech announcement points out, we're increasingly deploying robots in dangerous situations and hard-to-get-to places (hello, Mars rover!), but they lack human abilities to interact with their environment. If they lose their keys, they can't root through their purse and find something to pick the lock: 

If today’s most sophisticated robot was trapped in a burning room by a jammed door, it would probably not know how to locate and use objects in the room to climb over any debris, pry open the door, and escape the building.

Those of us on self-appointed Skynet Watch might call that a feature, rather than a bug, but the research team headed up by professor Mike Stilman begs to differ. They've gotten a $900,000 grant from the Office of Naval Research to build a robot that can "use objects in their environments to accomplish high-level tasks."

In other words:

“Our goal is to develop a robot that behaves like MacGyver, the television character from the 1980s who solved complex problems and escaped dangerous situations by using everyday objects and materials he found at hand."

The solution will involve algorithms, naturally, which is exactly how we get Cylons, so thanks in advance, guys.

Best without bugs. (Photo: flickr.com/violetmonde)

Algorithms: They're not just for Amazon recommendations and online dating anymore. The latest application, as per the New Scientist: Battling oriental fruit flies, a species that inspires the cold sweats in anyone who makes his livelihood on a fruit orchard.

These pests are a far more serious threat than the nuisances spawned by slovenly kitchen habits. They infest at least 230 different kinds of crops. The result? Rotten, maggot-infested fruit and crop losses that can add up to billions of dollars.

Luckily, scientists in Taiwan--where the bugs are a persistent problem--are working on a solution:

In Taiwan, fruit fly populations are normally monitored using traps that are manually checked every 10 days. Cheng-Long Chuang and colleagues at the National Taiwan University in Taipei wanted to automate the counting process, so they placed infrared beams in the traps. Each trap records when the beam is broken, indicating that an oriental fruit fly has entered, attracted by a chemical designed to lure the insect. The results collected are sent via radio to a local station every 30 minutes, allowing real-time measurements of the population.

Cool, right? However, the next step sounds just a tiny bit like a Skynet for insects:

Part-funded by the Taiwanese government, the team have so far set up 240 traps on fruit farms around the country. Machine learning algorithms pool the continuous data arriving from each of these traps and predict when the local fruit fly population is about to explode.

When conditions go critical, government officials get a heads up via text message, allowing them to deploy insecticide.

We can't help but be a little concerned at the thought of an unfriendly artificial intelligence targeting creatures that a) spread rapidly and b) wreak havoc on the environment around them. Somebody better give the Singularitarians the bad news.

Mr. Hammond (LinkedIn.com)

Like any proud papa, Narrative Science cofounder and CTO Kristian Hammond has ambitions for his article-writing algorithm. In 15 years, he told Wired, 90 percent of news will be computer-generated. In 20 years, there'll be no topic his company doesn't cover. He even believes that a computer will win the Pulitzer Prize within five years. Well, it is Big Data Week, after all.

Narrative Science got its start covering the data-driven topics of sports and finance. Then came work from a fast-food company, turning sales figures into regular written reports for franchise-owners. Nowadays, they can even vary tone. Hammond wants to see the company breaking news, though that'll require investment in data mining and natural language processing. All that leads to a future that looks a little something like this, according to Wired:

Maybe at some point, humans and algorithms will collaborate, with each partner playing to its strength. Computers, with their flawless memories and ability to access data, might act as legmen to human writers. Or vice versa, human reporters might interview subjects and pick up stray details—and then send them to a computer that writes it all up. As the computers get more accomplished and have access to more and more data, their limitations as storytellers will fall away.

But can computers produce umpteen gazillion slightly varied versions of The Hunger Games, to capitalize on the latest money-making publishing fad? Asking for a friend.

Wait...they're using computer too?

One of the reason that Bernie Madoff was able to stay undetected for so long was that he could alternately charm and intimidate the young SEC staffers sent to investigate his firm. In the wake of that scandal, reports The Wall Street Journal, the SEC has developed a computer system that analyzes performance from thousands of hedge funds and looks for  unusually good performance year-over-year that, like Mr. Madoff, seems too good to be true. 

So far the data crunching effort has led to four indictments, a positive sign that has the SEC thinking about expanding the scope of their computerized scrutiny to include up to 20,000 mutual funds and private equity firms.

Wall Street's reaction has been to suggest that this kind of scrutiny will have a chilling effect on managers who perform well. "There are people out there who have been committing fraud, and we want to get them and get them out of the system," Robert Leonard, a partner at law firm Bingham McCutchen LLP who represents hedge funds told The Wall Street Journal. "I'm concerned there probably will be some chilling effect for managers who are knocking the cover off the ball."

Right. Money managers with nothing to hide are going to begin tanking their own returns, rather than risk a SEC investigation? The financial sector has been relying on the world's best mathematical minds and most powerful computers for decades to gain an edge. The fact that the SEC is just now beginning to use these methods to detect fraud is a shocking, if welcome sign that they realize they have a lot of catching up to do if they are going to keep pace with the bad actors in these markets. This will help them do a better job detecting those hard-to-identify bogus firms, the ones with zero name recognition and no website who list their address as a non-existent street in New Jersey.

They can teach you how to get a date

OkCupid has earned a reputation for its fun and insightful use of data, playing with the mountains of statistics it has on the science of love. But today it met its match in the mathematics blog Isomorphismes.

The main thrust of the argument here is that the mandatory questions users need to answer when creating a profile and finding a match really skew the system. They are often rather sensitive questions, for example Isomorphismes' mandatories include: Do you think homosexuality is a sin, would you try to control your mate with suicide, would the world be a better place if people with low IQs were not allowed to reproduce (yikes!).

Users who answer these questions differently have no chance of being matched. But users who do answer these questions the same way are ranked as very compatible, despite the fact that on a granular level, they may be wrong for one another. This bothers Isomorphismes, who pointed out that, 'Someone doesn’t become a great potential match simply because they’re not a bigot, a cheat, a eugenicist, or a depressive manipulative."

It also makes it fairly easy to appeal to a broad swathe. "The worst side effect of the current scoring system, is that a spammer could easily answer only the questions with obvious answers (basic facts and display of non-bigotry) and get a decently high match percentage with a lot of people. At which point, the spammer uploads a picture of an attractive guy/girl, writes some generic profile text, and scams away," writes Isomorphismes.

It seems the post touched a nerve. OkCupid employee Riley Goodside responded that while he couldn't address the whole post, the point about spammers was essentially correct. "The algorithm as described in the FAQ does suffer from this problem. However, we have enhancements that address the issue very effectively. The FAQ is slightly out of date, and shouldn't be taken as a complete, exhaustive description of how we make matches."

And for those who learn how to game the system, romance may be in the cards. "That is exactly what I did which led to my meeting my (now long-term) girlfriend. I was receiving about 5 profile views/week with 500 questions answered. I scrapped them all, answered 20 or 30 questions with non-offensive answers, and skyrocketed to 60-100 profile views/week," wrote one commenter on Hacker News. Love or spam, it's all in the eye of the algorithm.

Finally! The people will learn...some stuff.

Google rarely if ever discusses the secrets of the inner workings of the tech giant's search algorithms or the changes they're constantly making to it. Today, they did. What were they, and why'd they want to talk?

On their blog, Google's anti-spam lead, Matt Cutts, breaks the tweaks down. There are ten changes, but the serious tweaks to the way you'll be searching content are, inm short:

• They retired a "signal" in Google Image searches that "had references from multiple documents on the web."
• They've stripped or "de-duplicated" searches with doubled-up anchor text.
• They've enhanced the value of fresh, newer content over older content that will affect, according to their calculations, around 35% of all searches (though only "6-10%" of all searches will be affected to a "noticeable degree").
• They've refined the way searches turn up "official" content; in other words, a search for Foo Fighters is less likely to pick up their Wikipedia page than the page the band and/or record label owns.
• They've tweaked and improve searches by date-ranges; hopefully, this means that re-published content from long ago will finally fall further back and maybe even be filtered out of Last Week/Last Month searches.

There are other tweaks—like enhancing searches to pump up result value for cross-language web content—but Google was careful to warn SEO "experts" not to start picking up whatever Icelandic they can. No, really, because you know someone read that and immediately started looking to BitTorrent some Rosetta Stone tapes:

If you’re a site owner, before you go wild tuning your anchor text or thinking about your web presence for Icelandic users, please remember that this is only a sampling of the hundreds of changes we make to our search algorithms in a given year, and even these changes may not work precisely as you’d imagine.

So why the transparency? Well....

We’ve decided to publish these descriptions in part because these specific changes are less susceptible to gaming.

For the New York Times' Bits blog, Claire Cain Miller breaks down some of the context helpful to understanding the announcement:

There is also another reason that Google is shedding some light on the black box of its algorithm. It is under fire from government regulators who are investigating it for antitrust violations. One of their main concerns is how little Google reveals about how search works, even though changes in the algorithm can drastically affect Web businesses.

Not that this will have much if any kind of effect in deterring:

1. Government investigations into Google's antitrust violations. Because a company as big and as powerful as Google should probably be investigated for antitrust violations on principle.

2. SEO "experts" who think they know what's inside the black box of Google enough to sell their wisdom on otherwise helpless business owners who wouldn't know metadata from metaphysics (which, often, might as well be the same thing).

But, you know, on both fronts: Vaya con dios. In the mean time, hopefully this will push down any of my search results from, like, Mediaite or whoever. I've got another Flavors.Me page to build.

Image via NYT

Vitaly Borker made headlines back in December after he started attacking customers who complained about his business with abusive emails and threats of violence. It was also an interesting situation because Borker had managed to make his site the number one result on Google for a simple search on the term "eyeglasses". Borker told The New York Times David Segal that he had boosted his sites search rankings by garnering tons of reviews, even though many of them were negative.

Today Borker plead guilty to counts of threatening communications, mail fraud and wire fraud.

"I just wanted to let you guys know that the more replies you people post, the more business and the more hits and sales I get. My goal is NEGATIVE advertisement," he wrote on one review site, Get Satisfaction.

Google, never one to stand by while someone games their search engine, responded this afternoon with a fix,

"We were horrified to read about Ms. Rodriguez's dreadful experience. Even though our initial analysis pointed to this being an edge case and not a widespread problem in our search results, we immediately convened a team that looked carefully at the issue. That team developed an initial algorithmic solution, implemented it, and the solution is already live. I am here to tell you that being bad is, and hopefully will always be, bad for business in Google's search results."

Google did stop to point out that it wasn't the bad reviews driving Borker to the top of the search rankings, so much as news stories from major outlets like the New York Times and Bloomberg.

It was complicated enough to fit them all within a taxonomy of their location at the time of the attacks, but grew more complex with hundreds of requests for certain names to be placed adjacent to loved ones.

So the foundation turned to computer science, hoping an algorithm could help them sort the problem. According to a wonderful piece in the New Yorker by Nick Paumgarten, more than one of the initial experts contacted for the task declared that it was an impossible. "The reasons for these requests were varied. Sometimes the victims were cohorts, or best friends. In other cases, the families knew, from last phone calls, whom their loved ones had been with in the end—in an elevator, on a ledge—and wanted those people listed together."

Luckily Jake Barton, principle at Midtown design firm Local Projects, didn't know about the doubters when he accepted the challenge.

"They had decided on a structure before they had the capability of making those designs a reality," Barton told Betabeat by phone today. "They had imagined you could design an arrangment where all the names were spread evenly, but underneath this seemingly random set of names, would be this incredibly complex lattice work of meaning."

Barton and data artist Jer Thorpe used a classic algorithm designed to solve the "knapsack problem", a way of arranging irregular objects in the most efficient way possible. "A computer did all the heavy lifting and number crunching," says Barton. "But we made the tool adaptive enough so that the foundation could come in afterwards and make changes, and the system would respond dynamically. Efficiency is important, but you also need that human touch."