The Best Part of Shaving The Winter Beard, originally uploaded by headtale.
…is getting to carve out all manner of redneck, yokel and classic facial hair styles as you whittle it down to “clean-shaven.”
(For the record, Regina is still fricken freezing – made worse by a thaw the other week that’s turned Regina into a city-sized curling rink – but we’re gearing up for Cuba in a couple weeks so the beard goes early this year!)
If you’re like me, you have contacts all over the place – on your home computer, on your work computer, on your smart phone, on a notepad by your phone, on little scraps of paper in your pocket. Soocial is a new site that attemps to easily automate the process of syncing contacts between all these different places (okay, maybe not the telephone notepad or the scraps of paper.)
I haven’t gone through and set it up yet so I can’t speak to how well it works. But it sounded useful so I thought I’d pass it along.
This is sort of an extension of an earlier post on “What is the One Defining Quality of Desirable Employees?” where I claimed that optimism trumped all.
I recently watched a YouTube clip (sorry, didn’t save the link) where the CEO of Zappo’s talked about some of the unique things they asked during interviews and one thing that clicked for me – you could probably have a really good idea of how good an employee will be by watching how much they smile during the interview.
That sounds fairly simplistic but I think there may be something to it. Part of it comes from Malcolm Gladwell’s hypothesis that you can make correct judgments about people and things within seconds. Part of it is because we’re in a customer-service focused business and if someone doesn’t smile much at an interview (when they’ll likely be nervous already), I doubt they’ll smile much at the circulation desk. And part of it is that I think you can draw a strong correlation between people who are happy (as evidenced by a lot of smiling) and people who have desirable qualities such as optimism, enthusiasm and openness to change.
No, that post title is not a joke. (Well, mostly not a joke.)
The reality is that I’m only slightly ashamed to admit that I find Justin Bieber and his recent rise to stardom fascinating.
There’s the fact that he’s from Woodstock, ON, just down the road from London. [Edit: I’m obviously not *that* fascinated because he’s from Stratford, not Woodstock. Worse, it was my mom who corrected me on this point!] Woodstock is a town that Shea and I passed through quite a few times during our year in London (I even have a fond memory of buying a mandolin with a crack in the casing at a garage sale for $5, keeping it in our apartment all year then bringing it back here and finally selling it at our own garage sale last fall for…$5.)
I like that he actually is a talented multi-instrumentalist while many manufactured pop stars can’t be trusted not to pee themselves while on stage!
And of course, the fact that he’s the first YouTube superstar is also of note to me given my personal interest in technology, online broadcasting and related subjects.
Apparently he’s the next person to get his picture on the cover of the Rolling Stone and in the accompanying interview, he made a couple comments – one on healthcare and one on abortion – which are getting a lot of attention/causing some measure of controversy.
(Okay, I admit I’ve used the “cute” tag on this post. The *real* reason I like Justin Bieber is revealed! ;-))
A generation ago, one of the biggest insurmountable challenges in computing was writing a chess program that could beat the world’s best human player. That eventually happened in 1997 when IBM’s Deep Blue beat the greatest Grandmaster of all-time Garry Kasparov (of course, computers had been beating inferior players for much longer – including ChessMaster 3000 regularly trouncing me in my college dorm room back in the early 1990’s!)
Today, the challenge has moved from the numerous mathematical but ultimately finite possibilities of chess to the much more difficult world of natural language processing. Once again, it’s IBM taking up the challenge. They’ve spent five years and tens of millions of dollars developing Watson, a super-computer specially designed to play Jeopardy with all of its uniquely worded, pun-filled trivia questions.
How does Watson actually work? It’s programmed with the rules and strategies of the game (if it’s further behind, it may make a bigger wager on a Daily Double question.) Beyond the framework of how to play Jeopardy, the IBM scientists have inputted a data set equivalent to the Library of Congress holdings into the massive super computer that is “behind the curtain” operating Watson (they only have a stand-in avatar on the Jeopardy stage.) Beyond that data set, the computer isn’t connected to the Net or any other external resources.
Watson is also “deaf and blind” as programming in speech and video recognition are yet another leap. (This was clear in the first game when Jennings gave a wrong answer then Watson immediately repeated it.) So instead of Watson “hearing” or “reading” the questions, they get put into its algorithm as a text file just as Alex Trebek reads them to the human contestants. Watson does word parsing and other analysis to come up with a near-instantaneous answer as well as calculations to determine how confident it is. Watson’s even been programmed to “push” a buzzer button when it wants to answer a question!
MetaFilter’s been following this since the project was first publicly announced in 2009 including a new thread now that the actual Jeopardy showdown, pitting Watson against two of Jeopardy’s all-time champions, has arrived.
Ken Jennings, who set a record by winning 74 straight games on Jeopardy, answers viewer questions about the experience after the first day.
The New York Times has created an interactive app which allows you simulate the experience of playing against Watson (though in a turn-based rather than buzzer-based format.)
It’s a three-day, total points tournament so you’ll have to tune in today and tomorrow to see who ultimately wins (and yes, the shows do feel like an infomercial for IBM!)
Finally, here’s an awesome documentary about the project (you’ll need a VPN or other digital trickery to view if you’re in Canada.) Here’s the YouTube preview:
With apologies to Leonard Cohen, this is easily the sweetest love song about the end of the world ever.
Or if that’s not your speed, how about a 200 love song YouTube playlist?
Happy Valentine’s Day!
Recipe for A Real-Life “Slapshot” Movie
Dating site, OKCupid, has a really interesting blog where they draw on their massive data pool from site members profiles and interactions to come up with some revealing information.
You would think this was planned, it’s so perfect…
