A Bit More Detail

Assorted Personal Notations, Essays, and Other Jottings

Posts Tagged ‘computers

[NEWS] Some Thursday links

leave a comment »

  • The Sacramento Bee reports that UC Davis spent hundreds of thousands of dollars on trying to salvage its reputation online, after famously being linked with security guards pepper-spraying student protesters.
  • Bloomberg notes China’s island-building spree in the South China Sea is causing environmental damage, notes Hungary may lose out on future investment because of labour shortages, and notes London property prices are sliding because of Brexit.
  • The Guardian suggests Russians do not care about Putin’s corruption.
  • The Independent reports on a Muslim anti-ISIS march not covered by mainstream media.
  • MacLean’s writes about the NDP, about the hard left turn, about James Laxer’s criticism of the Leap manifesto, and about the disinterest of Megan Leslie and other NDPers in going for the leadership.
  • The National Post notes the potential huge market for insects as human food and notes controversy over First Nations support for a controversial wind energy farm.
  • Quartz notes the culture gap between Koreans and Korean-Americans.
  • In the Toronto Star, Emma Teitel writes about how the pronoun “they” is easy to use.
  • Wired looks at a brain implant that gave a quadriplegic man control of his arm.

[BLOG] Some Wednesday links

leave a comment »

  • Antipope Charlie Stross speculates about really good sexbots.
  • blogTO notes the opening of Toronto’s first Uniqlo in October.
  • Centauri Dreams looks at the proposal for a laser-launched flyby probe to Alpha Centauri.
  • The Dragon’s Gaze notes evidence for the collision of planetesimals around HD 61005.
  • The Dragon’s Tales links to a study suggesting deer on the outer islands of Scotland were purposefully transplanted there in the Neolithic.
  • Joe. My. God. reports on Paul Ryan’s categorical exclusion of any interest in the Republican nomination.
  • Language Hat reports on the discovery of ancient Chinese manuscripts written in bamboo dating back 2500 years.
  • The Planetary Society Blog notes stunning comet photos taken by Rosetta.
  • Towleroad notes that the governor of Mississippi has a gay son who left the state after being gay-bashed.
  • Window on Eurasia looks at the background of leaders of frozen conflict situations like the Donbas.

[LINK] “Computer Algorithm Can Spot a Drunken Tweeter”

D-Brief’s Nathaniel Scharping blogs about a new computer algorithm that can detect drunken tweeters.

Drunk tweets, long considered an unfortunate, yet ubiquitous, byproduct of the social media age, have finally been put to good use.

With the help of a machine-learning algorithm, researchers from the University of Rochester cross-referenced tweets mentioning alcohol consumption with geo-tagging information to broadly analyze human drinking behavior. They were able to estimate where and when people imbibed, and, to a limited extent, how they behaved under the influence. The experiment is more than a social critique — the algorithm helps researchers spot drinking patterns that could inform public health decisions, and could be applied to a range of other human behaviors.

To begin with, the researchers sorted through a selection of tweets from both New York City and rural New York with the help of Amazon’s Mechanical Turk. Users identified tweets related to drinking and picked out keywords, such as “drunk,” “vodka” and “get wasted,” to train an algorithm.

They put each relevant tweet through a series of increasingly stringent questions to home in on tweets that not only referenced the author drinking, but indicated that they were doing so while sending the tweet. That way, they could determine whether a person was actually tweeting and drinking, or just sending tweets about drinking. Once they had built up a dependable database of keywords, they were able to fine-tune their algorithm so it could recognize words and locations that likely proved people were drinking.

To get tweeters’ locations, they used only tweets that had been geo-tagged with Twitter’s “check-in” feature. They then approximated users’ home locations by checking where they were when they sent tweets in the evenings, in addition to tweets containing words like “home” or “bed.” This let them know whether users’ preferred to drink at home or out at bars or restaurants.

Written by Randy McDonald

March 20, 2016 at 3:15 pm

[LINK] “A Computer With a Great Eye Is About to Transform Botany”

Wired‘s Margaret Rhodes reports how computers capable of detailed image analysis can transform botany.

My dad is a wildlife biologist, and during road trips we took when I was growing up he spent a lot of time talking about the grasses and trees along the highway. It was a game he played, trying to correctly identify the passing greenery from the driver’s seat of a moving car. As a carsick-prone kid wedged into the back seat of a Ford F150, I found this supremely lame. As an adult—specifically, one who just spoke with a paleobotanist—I now know something about my father’s roadtripping habit: Identifying leaves isn’t easy.

“I’ve looked at tens of thousands of living and fossil leaves,” says that paleobotanist, Peter Wilf of Penn State’s College of Earth and Mineral Sciences. “No one can remember what they all look like. It’s impossible—there’s tens of thousands of vein intersections.” There’s also patterns in vein spacing, different tooth shapes, and a whole host of other features that distinguish one leaf from the next. Unable to commit all these details to memory, botanists rely instead on a manual method of identification developed in the 1800s. That method—called leaf architecture—hasn’t changed much since. It relies on a fat reference book filled with “an unambiguous and standard set of terms for describing leaf form and venation,” and it’s a painstaking process; Wilf says correctly identifying a single leaf’s taxonomy can take two hours.

That’s why, for the past nine years, Wilf has worked with a computational neuroscientist from Brown University to program computer software to do what the human eye cannot: identify families of leaves, in mere milliseconds. The software, which Wilf and his colleagues describe in detail in a recent issue of Proceedings of the National Academy of Sciences, combines computer vision and machine learning algorithms to identify patterns in leaves, linking them to families of leaves they potentially evolved from with 72 percent accuracy. In doing so, Wilf has designed a user-friendly solution to a once-laborious aspect of paleobotany. The program, he says, “is going to really change how we understand plant evolution.”

Written by Randy McDonald

March 18, 2016 at 2:42 pm

Posted in Science

Tagged with , ,

[LINK] “The Sadness and Beauty of Watching Google’s AI Play Go”

Cade Metz’ Wired article reports from Seoul, where a Google-designed AI defeated a veteran player of Seoul in a beautiful if unorthodox manner. There are new ways of knowing the world about.

At first, Fan Hui thought the move was rather odd. But then he saw its beauty.

“It’s not a human move. I’ve never seen a human play this move,” he says. “So beautiful.” It’s a word he keeps repeating. Beautiful. Beautiful. Beautiful.

The move in question was the 37th in the second game of the historic Go match between Lee Sedol, one of the world’s top players, and AlphaGo, an artificially intelligent computing system built by researchers at Google. Inside the towering Four Seasons hotel in downtown Seoul, the game was approaching the end of its first hour when AlphaGo instructed its human assistant to place a black stone in a largely open area on the right-hand side of the 19-by-19 grid that defines this ancient game. And just about everyone was shocked.

“That’s a very strange move,” said one of the match’s English language commentators, who is himself a very talented Go player. Then the other chuckled and said: “I thought it was a mistake.” But perhaps no one was more surprised than Lee Sedol, who stood up and left the match room. “He had to go wash his face or something—just to recover,” said the first commentator.

Even after Lee Sedol returned to the table, he didn’t quite know what to do, spending nearly 15 minutes considering his next play. AlphaGo’s move didn’t seem to connect with what had come before. In essence, the machine was abandoning a group of stones on the lower half of the board to make a play in a different area. AlphaGo placed its black stone just beneath a single white stone played earlier by Lee Sedol, and though the move may have made sense in another situation, it was completely unexpected in that particular place at that particular time—a surprise all the more remarkable when you consider that people have been playing Go for more than 2,500 years. The commentators couldn’t even begin to evaluate the merits of the move.

Then, over the next three hours, AlphaGo went on to win the game, taking a two-games-to-none lead in this best-of-five contest. To date, machines have beaten the best humans at chess and checkers and Othello and Jeopardy!. But no machine has beaten the very best at Go, a game that is exponentially more complex than chess. Now, AlphaGo is one win away.

Written by Randy McDonald

March 12, 2016 at 1:34 pm

[BLOG] Some Monday links

  • City of Brass notes the lie that is Eurabia.
  • Crooked Timber considers Creative Commons licenses as a crude kind of anti-spam technology.
  • The Dragon’s Tales looks at Ontario’s interest in pioneering a guaranteed minimum income program.
  • Far Outliers looks at the history of Korean prisoners of war in the Second World War in Hawai’i.
  • Joe. My. God. notes the death of Nancy Reagan.
  • Language Hat starts a discussion about the cost of designing fonts.
  • Language Log notes the difficulties of some Westerners with learning Chinese compared to Western classical languages.
  • Marginal Revolution notes the complexity of the new European Union-Turkey deal on Syrian migrants.
  • Discover‘s Neuroskeptic notes that we are far from being able to upload content directly to our brains.
  • Strange Maps notes how, in Turkish, different cardinal directions are associated with a different colour.
  • Is Buffalo strongly anti-gay? Towleroad considers this finding, from a social media analysis.

[LINK] “Stanford researchers using Toronto-based Wattpad’s stories to inform artificial intelligence”

The Globe and Mail‘s Shane Dingman describes an unexpected for the Wattpad corpus.

If you are one of the 40 million people who enjoy reading or writing the mostly romantic werewolf, superhero or historical fiction stories found on Canadian startup Wattpad, you may also be contributing to the development of the next generation of artificial intelligence.

In a new paper called Augur: Mining Human Behaviors from Fiction to Power Interactive Systems, a group of Stanford University computer science researchers revealed that they used the Wattpad “corpus” – a collection of almost two billion words (or 600,000 chapters) written by regular people – to help a computer understand the world around it. The team intends to make the program they built, Augur, into an open-source tool that other researchers can build on.

“The basic idea is that it’s very difficult to program computers to understand the broad range of things that people do,” says fourth-year PhD student Ethan Fast, co-author of the paper (published as part of the upcoming Computer Human Interaction conference) and a member of Stanford’s Human-Computer Interaction Group. “Fiction has a lot of useful things to say about the world, and if you have enough of it, you can model it in much more depth than you could hope to manually.”

Until recently, Toronto-based Wattpad, founded in 2006, didn’t make its data available to researchers, and it may not have happened in this case if it weren’t for the intervention by co-founder Ivan Yuen, who knows members of the Stanford team. More than 200 million uploads (some stories, some just chapters) have been shared on Wattpad, the majority of its users are under 30 and they spend 13 billion minutes a month on the service. So far, the company, which has 112 employees, has raised more than $66-million (U.S.) in venture capital financing.

“When we started this in 2014, we knew there was value in the corpus, but we hadn’t really explored it too much,” Wattpad’s head of engineering, Jordan Christensen, says. “As we started working with the Stanford guys, it really opened our eyes a bit and now … through our own internal research and with partners, we are really starting to change the way we think about Wattpad.”

Written by Randy McDonald

March 7, 2016 at 6:06 pm

Follow

Get every new post delivered to your Inbox.

Join 526 other followers