From an article reviewed by SNF and posted yesterday on Scientific American’s guest blog:
The cleverest card trick I’ve ever seen was performed not by a magician, but by a math professor.
A teaching assistant (let’s call him Nick), acting as magician’s assistant, recruited five student participants. Each student picked a card from a 52-card deck and handed it back to Nick, face up but invisible to Tom, the professor. Nick laid out four of these cards in front of Tom. To our astonishment, Tom immediately identified the missing fifth card.
The professor revealed the trick at the end of class. But when I came back to my dorm, bursting with excitement, my suitemate Benjamin refused to let me explain it; he had to figure this out on his own. He wandered off to his room muttering to himself, blissfully unaware that within twenty-four hours, this puzzle would prove disastrous to his dignity.
Read the whole article on the Scientific American website.
Earlier this July, my childhood dream finally came true. Over the series’ 20 year history, I’ve played more than 30 Pokemon video games, and with each new release I’ve wanted to become a gym leader and to catch ‘em all – a feat I accomplished, once, back in the first game. Now, as a 28-year old working on a Ph.D., I can finally achieve my dream with the help of Niantic’s latest augmented reality game, Pokemon GO.
I can find a Pidgey (the Pigeon Pokemon) on a city sidewalk thanks to GPS telling Pokemon GO where I am. Finding a Goldeen (the Goldfish Pokemon) on the same city street would not make sense.
In Pokemon GO, as I wander around my city, my phone periodically vibrates indicating that I’ve found a Pokemon. I quickly look at my phone and tap on the Pokemon to enter a battle with it. The game knows where I am thanks to GPS, the Global Positioning System, and uses that information to show me location-appropriate Pokemon, such as Water-type Pokemon close to rivers and Fire-type Pokemon in deserts.
In the summer of 2012, scientist and entrepreneur Russ George sailed purposefully past the coast of Vancouver to the archipelago of Haida Gwaii. There, he proceeded to dump 100 tons of iron sulfate into 10,000 square miles of ocean.
The Haida Indians had given him their blessing. George was the director of the Haida Salmon Restoration Corporation, and the Haida Indians were told that this iron would fertilize the plankton, a valuable feedstock for the native salmon. But George’s intentions went beyond fish farming: adding iron would allow swarms of plankton to blossom, which would draw down massive amounts of carbon dioxide. Russ George claimed to have found a solution for amending the starving salmon population and mitigating the rising concentration of greenhouse gases in one fell swoop.
Most experts, however, were infuriated.
Since then, George has become an infamous case of the dangerous line between ingenuity and recklessness. Supporters argue that such drastic measures may be needed in the future unless we somehow reduce our greenhouse gas emission. But most scientists and policymakers argue that his hasty deed had no scientific merit, and could cause irreversible damage to the ocean environment.
How could an experiment with such good intentions have gone so wrong?
Physics is full of outlandish scenarios where our basic intuitions break down. Quantum mechanics, relativity, nanoparticles…so many phenomena seem counter-intuitive, or even impossible, that it’s almost not surprising when we hear of another in some remote domain. But sometimes, physics surprises can be found right in our hands.
My favorite counter-intuitive motion can be demonstrated with an object that you likely have near you right now: a smartphone. To see it, hold your phone with the screen facing towards you and give it a light toss into the air, spinning it so the screen stays facing towards you. Make sure that if you drop it, it falls in your lap or somewhere soft.* Watch how the phone rotates in the air. Continue reading
In 2004, Albert Pujols was considered one of the best baseball hitters in the world, leading the Major Leagues the previous year with a .359 batting average. Jennie Finch was considered the world’s best softball pitcher, leading the U.S. to a Gold Medal in the Olympics by striking out more than one hitter per inning and giving up 0 runs. So when Finch challenged Pujols to a matchup, it was billed as a classic showdown of men vs. women. But that was just on the surface. Deep down, this matchup also provided the perfect experiment to test the limits of a human’s reaction time – and how our brains make it possible to surpass them.
“I do apologize for not being able to satisfy a lot of people’s expectations. I kind of felt powerless,” , said GO grandmaster Lee Sedol after a surprising 1-4 loss to the artificial intelligence AlphaGO recently.
Machines had conquered most of the games mankind has created, including chess, Scrabble, and even Jeopardy!. The ancient game GO, exponentially more complex than chess, was once considered to be one of the ultimate tests of machines’ capabilities. Yet with Lee’s loss, the game has been conquered. Given the rapid advances in artificial intelligence, one cannot help but wonder “Is there any limit to what a machine can do?”
While machines have become smart enough to defeat humans in sophisticated games, humans have cleverly devised a problem that machines definitely cannot solve. Impressively, the problem was constructed more than 80 years ago, even before the birth of digital computers. The star of humanity who came up with this construction was mathematician Kurt Godel. Later, Alan Turing, the father of computer science, used Godel’s techniques to prove an analogous theorem in the context of computer science. In its simplest form, this theorem states that there exist problems that a machine will never be able to conquer. Continue reading
Another SNF-workshopped article on Facts So Romantic, the blog of Nautilus magazine:
If I claimed that Americans have gotten more self-centered lately, you might just chalk me up as a curmudgeon, prone to good-ol’-days whining. But what if I said I could back that claim up by analyzing 150 billion words of text? A few decades ago, evidence on such a scale was a pipe dream. Today, though, 150 billion data points is practically passé. A feverish push for “big data” analysis has swept through biology, linguistics, finance, and every field in between.
But there’s a problem: It’s tempting to think that with such an incredible volume of data behind them, studies relying on big data couldn’t be wrong. But the bigness of the data can imbue the results with a false sense of certainty. Many of them are probably bogus—and the reasons why should give us pause about any research that blindly trusts big data.
Read the whole article on the Nautilus website.