Readings: Natalie Portman, China’s Museum, Madoff Tapes

A few reads from the last couple of days:

1) “From Lab to Red Carpet” [New York Times] – Natalie Portman won the Oscar for Best Actress in a Leading Role (for her performance as Nina, a ballerina in Black Swan) last night. But did you know that in her younger days, she was a brilliant student?

Among the lesser-known but nonetheless depressingly impressive details in Ms. Portman’s altogether too precociously storied career is that as a student at Syosset High School on Long Island back in the late 1990s, Ms. Portman made it all the way to the semifinal rounds of the Intel competition.

The piece also discusses the academic endeavors of other actors as well.

2) “China Debuts World’s Largest Museum” [Art Info] — the largest museum in the world is now in China. Located on the east side of Tiananmen Square, the National Museum of China measures 2.07 million square feet and thus surpassing the Metropolitan Museum of Art, which previously reigned as the largest museum at 2.05 million square feet. The third largest museum in the world is now The Hermitage in St. Petersburg (which I visited in 2007). (via)

3) “The Madoff Tapes” [New York Magazine] – an incredible piece by Steve Fishman. A different profile of the biggest Ponzi scheme in history, in which we hear from Madoff himself. Absolutely astounding that he called the people who trusted and invested with him as greedy.

“Everyone was greedy,” he [Madoff] continues. “I just went along. It’s not an excuse.” In his mind, the hedge funds and the banks were little more than marketers, skimming their 1 to 2 percent off the top, a fee for their supposed “due diligence,” though they exercised little oversight. “Look, there was complicity, in my view…”

Why Can Nothing Go Faster than the Speed of Light?

If you’re a high school or college student studying physics, certainly one of the topics you cover is speed of light. Your teacher/professor probably explained that nothing can go faster than c, that constant equivalent to 299,792,458 meters per second. However, if you still find yourself scratching your head, unable to answer the question “Why can nothing go faster than the speed of light?” I encourage you to read the explanation below, which I found on Reddit. I usually post snippets to quote, but I make exception here. The explanation below, excuse the pun, is positively enlightening.

###

There are a lot of simple, intuitive explanations of this to be had out there … but I kind of hate them all. You might google around a bit and find discussion of something called “relativistic mass,” and how it requires more force to accelerate an object that’s already moving at a high velocity, stuff like that. That’s a venerable way of interpreting the mathematics of special relativity, but I find it unnecessarily misleading, and confusing to the student who’s just dipping her first toe into the ocean of modern physics. It makes the universe sound like a much different, and much less wonderful, place than it really is, and for that I kind of resent it.

When I talk about this subject, I do it in terms of the geometric interpretation that’s consistent with generalrelativity. It’s less straightforward, but it doesn’t involve anything fundamentally more difficult than arrows on pieces of paper, and I think it offers a much better understanding of the universe we live in than hiding behind abstractions like “force” and outright falsehoods like “relativistic mass.” Maybe it’ll work for you, maybe it won’t, but here it is in any case.

First, let’s talk about directions, just to get ourselves oriented. “Downward” is a direction. It’s defined as the direction in which things fall when you drop them. “Upward” is also a direction; it’s the opposite of downward. If you have a compass handy, we can define additional directions: northward, southward, eastward and westward. These directions are all defined in terms of something — something that we in the business would call an “orthonormal basis” — but let’s forget that right now. Let’s pretend these six directions are absolute, because for what we’re about to do, they might as well be.

I’m going to ask you now to imagine two more directions: futureward and pastward. You can’t point in those directions, obviously, but it shouldn’t be too hard for you to understand them intuitively. Futureward is the direction in which tomorrow lies; pastward is the direction in which yesterday lies.

These eight directions together — upward, downward, northward, southward, eastward, westward, pastward, futureward — describe the fundamental geometry of the universe. Each pair of directions we can call a “dimension,” so the universe we live in is four-dimensional. Another term for this four-dimensional way of thinking about the universe is “spacetime.” I’ll try to avoid using that word whenever necessary, but if I slip up, just remember that in this context “spacetime” basically means “the universe.”

So that’s the stage. Now let’s consider the players.

You, sitting there right now, are in motion. It doesn’t feel like you’re moving. It feels like you’re at rest. But that’s only because everything around you is also in motion. No, I’m not talking about the fact that the Earth is spinning or that our sun is moving through the galaxy and dragging us along with it. Those things are true, but we’re ignoring that kind of stuff right now. The motion I’m referring to is motion in the futureward direction.

Imagine you’re in a train car, and the shades are pulled over the windows. You can’t see outside, and let’s further imagine (just for sake of argument) that the rails are so flawless and the wheels so perfect that you can’t feel it at all when the train is in motion. So just sitting there, you can’t tell whether you’re moving or not. If you looked out the window you could tell — you’d either see the landscape sitting still, or rolling past you. But with the shades drawn over the windows, that’s not an option, so you really just can’t tell whether or not you’re in motion.

But there is one way to know, conclusively, whether you’re moving. That’s just to sit there patiently and wait. If the train’s sitting at the station, nothing will happen. But if it’s moving, then sooner or later you’re going to arrive at the next station.

In this metaphor, the train car is everything that you can see around you in the universe — your house, your pet hedgehog Jeremy, the most distant stars in the sky, all of it. And the “next station” is tomorrow.

Just sitting there, it doesn’t feel like you’re moving. It feels like you’re sitting still. But if you sit there and do nothing, you will inevitably arrive at tomorrow.

That’s what it means to be in motion in the futureward direction. You, and everything around you, is currently moving in the futureward direction, toward tomorrow. You can’t feel it, but if you just sit and wait for a bit, you’ll know that it’s true.

So far, I think this has all been pretty easy to visualize. A little challenging maybe; it might not be intuitive to think of time as a direction and yourself as moving through it. But I don’t think any of this has been too difficult so far.

Well, that’s about to change. Because I’m going to have to ask you to exercise your imagination a bit from this point on.

Imagine you’re driving in your car when something terrible happens: the brakes fail. By a bizarre coincidence, at the exact same moment your throttle and gearshift lever both get stuck. You can neither speed up nor slow down. The only thing that works is the steering wheel. You can turn, changing your direction, but you can’t change your speed at all.

Of course, the first thing you do is turn toward the softest thing you can see in an effort to stop the car. But let’s ignore that right now. Let’s just focus on the peculiar characteristics of your malfunctioning car. You can change your direction, but you cannot change your speed.

That’s how it is to move through our universe. You’ve got a steering wheel, but no throttle. When you sit there at apparent rest, you’re really careening toward the future at top speed. But when you get up to put the kettle on, you change your direction of motion through spacetime, but not your speed of motion through spacetime. So as you move through space a bit more quickly, you find yourself moving through time a bit more slowly.

You can visualize this by imagining a pair of axes drawn on a sheet of paper. The axis that runs up and down is the time axis, and the upward direction points toward the future. The horizontal axis represents space. We’re only considering one dimension of space, because a piece of paper only has two dimensions total and we’re all out, but just bear in mind that the basic idea applies to all three dimensions of space.

Draw an arrow starting at the origin, where the axes cross, pointing upward along the vertical axis. It doesn’t matter how long the arrow is; just know that it can be only one length. This arrow, which right now points toward the future, represents a quantity physicists call four-velocity. It’s your velocity through spacetime. Right now, it shows you not moving in space at all, so it’s pointing straight in the futureward direction.

If you want to move through space — say, to the right along the horizontal axis — you need to change your four-velocity to include some horizontal component. That is, you need to rotate the arrow. But as you do, notice that the arrow now points less in the futureward direction — upward along the vertical axis — than it did before. You’re now moving through space, as evidenced by the fact that your four-velocity now has a space component, but you have to give up some of your motion toward the future, since the four-velocity arrow can only rotate and never stretch or shrink.

This is the origin of the famous “time dilation” effect everybody talks about when they discuss special relativity. If you’re moving through space, then you’re not moving through time as fast as you would be if you were sitting still. Your clock will tick slower than the clock of a person who isn’t moving.

This also explains why the phrase “faster than light” has no meaning in our universe. See, what happens if you want to move through space as fast as possible? Well, obviously you rotate the arrow — your four-velocity — until it points straight along the horizontal axis. But wait. The arrow cannot stretch, remember. It can only rotate. So you’ve increased your velocity through space as far as it can go. There’s no way to go faster through space. There’s no rotation you can apply to that arrow to make it point more in the horizontal direction. It’s pointing as horizontally as it can. It isn’t even really meaningful to think about something as being “more horizontal than horizontal.” Viewed in this light, the whole idea seems rather silly. Either the arrow points straight to the right or it doesn’t, and once it does, it can’t be made to point any straighter. It’s as straight as it can ever be.

That’s why nothing in our universe can go faster than light. Because the phrase “faster than light,” in our universe, is exactly equivalent to the phrase “straighter than straight,” or “more horizontal than horizontal.” It doesn’t mean anything.

Now, there are some mysteries here. Why can four-velocity vectors only rotate, and never stretch or shrink? There is an answer to that question, and it has to do with the invariance of the speed of light. But I’ve rambled on quite enough here, and so I think we’ll save that for another time. For right now, if you just believe that four-velocities can never stretch or shrink because that’s just the way it is, then you’ll only be slightly less informed on the subject than the most brilliant physicists who’ve ever lived.

###
Source: Reddit.

Side note: if you’re interested in learning more about space and the time continuum, I high recommend Brian Greene’s The Elegant Universe. I read it a few years ago, and it’s one of the best general (i.e., not a textbook) books on space and physics I’ve read.

Italo Calvino on Photography

I always find it fascinating when authors incorporate their academic thoughts into works of fiction.

I came across this this story by Italo Calvino titled “The Adventures of a Photographer,” found in his novel Difficult Loves. In it, we follow Antonino Paraggi, who is described as a non-photographer. Feeling isolated, he picks up the camera and begins to shoot. The story is short, and perhaps unrealistic (what of finding love through a model shoot?), but I wanted to highlight a couple of noteworthy passages.

Is it possible to use an extracurricular endeavor, such as photography, to discover ones faults, misgivings, and dissatisfactions in life? Calvino makes the case that it is so:

It must be said that his examination of photography to discover the causes of a private dissatisfaction—as of someone who feels excluded from something—was to a certain extent a trick Antonino played on himself, to avoid having to consider another, more evident, process that was separating him from his friends. What was happening was this: his acquaintances, of his age, were all getting married, one after another, and starting families, while Antonino remained a bachelor.

Have you encountered parents who become obsessed with photography because they think that if there’s a moment of their child’s life that they don’t capture, it will be lost forever?

Given the speed of growth, it becomes necessary to photograph the child often, because nothing is more fleeting and unmemorable than a six-month-old infant, soon deleted and replaced by one of eight months, and then one of a year; and all the perfection that, to the eyes of parents, a child of three may have reached cannot prevent its being destroyed by that of the four-year-old. The photograph album remains the only place where all these fleeting perfections are saved and juxtaposed, each aspiring to an incomparable absoluteness of its own.

Antonino’s argument here is interesting, but flawed:

For the person who wants to capture everything that passes before his eyes, the only coherent way to act is to snap at least one picture a minute, from the instant he opens his eyes in the morning to when he goes to sleep. This is the only way that the rolls of exposed film will represent a faithful diary of our days, with nothing left out. If I were to start taking pictures, I’d see this thing through, even if it meant losing my mind. But the rest of you still insist on making a choice. What sort of choice? A choice in the idyllic sense, apologetic, consolatory, at peace with nature, the fatherland, the family. Your choice isn’t only photographic; it is a choice of life, which leads you to exclude dramatic conflicts, the knots of contradiction, the great tensions of will, passion, aversion. So you think you are saving yourselves from madness, but you are falling into mediocrity, into hebetude.

I find it hard to believe that there is a person who wants to capture “everything” — that is impossible. Secondly, one would not use a still camera in this instance, but would shoot a film. On this topic, I highly suggest reading “While the Women Are Sleeping,” which I previously discussed here. The central obsession of shooting continuously in the two stories is very, perhaps eerily, similar.

And this is probably the best passage in the story. Can the photographed reality be better (i.e., more visually appealing, more engrossing, more ethereal, more subjective, etc.) than reality itself? I’ve previously noted, with my photography, that it’s often the case (because I sometimes envision a scene as I would like it to look, and complete my mental image in post-processing).

Photographed reality immediately takes on a nostalgic character, of joy fled on the wings of time, a commemorative quality, even if the picture was taken the day before yesterday. And the life that you live in order to photograph it is already, at the outset, a commemoration of itself. To believe that the snapshot is more true than the posed portrait is a prejudice…

###
Hat tip to @escapeintolife for posting a link to this story on Twitter.

Recap: IBM’s Watson Dominates at Jeopardy!

“I, for one, welcome our new computer overlords.”

So wrote Ken Jennings as part of his correct response to the Final Jeopardy! clue in tonight’s final game between Ken Jennings, Brad Rutter, and the newcomer, IBM’s Watson.

Though it didn’t do as well today as it did in match 1, Watson had another impressive showing in Game 2, earning $41,413 and combined with his $35,734 in game 1, won the two-day affair with combined winnings of $77,147. At the end of the Double Jeopardy! round, Ken Jennings computed that he wouldn’t be able to beat Watson even if Ken wagered it all, so he wagered conservatively in Final Jeopardy!. The category was 19th Century  Novelists and the clue was:

“William Wilkenson’s ‘An Account of the Principalities of Wallachia and Moldavia’ inspired this author’s most famous novel.”

All three contestants got the right answer: Bram Stoker, who wrote Dracula (I got it right at home, playing along). In the end, Ken Jennings wound up with $24,000. Brad Rutter came in third with $21,600 in winnings. Of course, IBM’s Watson was playing for charity, and the cool $1,000,000 prize will be split between World Vision and World Community Grid.

Overall, I was very impressed with Watson’s showing. And yes, I was wrong with my prediction that I made last week. The last three days on Jeopardy! have been a blast.

So what’s next for IBM? According to the New York Times:

For I.B.M., the future will happen very quickly, company executives said. On Thursday it plans to announce that it will collaborate with Columbia University and the University of Maryland to create a physician’s assistant service that will allow doctors to query a cybernetic assistant. The company also plans to work with Nuance Communications Inc. to add voice recognition to the physician’s assistant, possibly making the service available in as little as 18 months.

###
References:

1) Selected Nuances of Watson’s Strategies (How does Watson know what it know?)

2) Watson’s Wagering Strategies (excellent blog post from one of IBM’s researchers)

3)  All the questions and answers from Game 1 (part 1 and part 2) and from Game 2 in this Jeopardy! contest between Watson, Ken Jennings, and Brad Rutter.

 

Day 1 Recap: Ken Jennings vs. Brad Rutter vs. IBM’s Watson on Jeopardy

Well, a full day of competition between Ken Jennings and Brad Rutter vs. IBM Watson is now in the books. In the Jeopardy! round, Watson came out firing but also made a couple of mistakes. At the end of the first round of Jeopardy!, Brad Rutter and Watson were tied at $5,000 apiece while Jennings had $2,000.

Today was a different story. Watson was unstoppable in the beginning of the Double Jeopardy! round, chewing up clues all over the board. Watson found the two Daily Doubles and got them right. It was painful to watch how Rutter and Jennings were struggling to keep up with The Machine.

At the end of the first full game of Jeopardy!, Watson accumulated $35,734 in winnings compared to $10,400 for Brad Rutter and $4,800  for Ken Jennings. But the most interesting (!) part of the match was the Final Jeopardy round, in which the category was U.S. Cities. The answer was: “Its largest airport was named for a World War II hero; its second largest, for a World War II battle.” Both Ken Jennings and Brad Rutter  wrote “What is Chicago?” for its O’Hare and Midway, but Watson’s response was a ridiculous “What is Toronto???”

This is the kind of clue that, to me, is most indicative of how much the humans know vs. how much the computer has still ways to go. Final Jeopardy clues are traditionally more esoteric than any of the clues in the first two rounds. This clue was no exception. It wasn’t a factual clue (example: given the city’s airport, can you name the city? Easy as pie for Watson), but rather one that you’d have to parse: what major U.S. cities have two major airports? New York, Washington D.C., Los Angeles, and Chicago immediately come to mind. At the same time, there wasn’t a connecting dot in the clue, other than World War II (very broad indeed).  For me, this would have been a process-of-elimination question, so why did Watson have such a trouble with it (only 30% confidence in its answer)?

David Ferrucci, the manager of the Watson project at IBM Research, explained during a viewing of the show that several of things probably confused Watson:

First, the category names on Jeopardy! are tricky. The answers often do not exactly fit the category. Watson, in his training phase,  learned that categories only weakly suggest the kind of answer that is expected, and, therefore, the machine downgrades their significance.  The way the language was parsed provided an advantage for the humans and a disadvantage for Watson, as well. “What US city” wasn’t in the question. If it had been, Watson would have given US cities much more weight as it searched for the answer. Adding to the confusion for Watson, there are cities named Toronto in the United States and the Toronto in Canada has an American League baseball team. It probably picked up those facts from the written material it has digested. Also, the machine didn’t find much evidence to connect either city’s airport to World War II. (Chicago was a very close second on Watson’s list of possible answers.) So this is just one of those situations that’s a snap for a reasonably knowledgeable human but a true brain teaser for the machine.

Still, I was very impressed by Watson’s performance on day 1. It is certainly fast on that buzzer, as evidenced by many grimaces and sighs by Ken Jennings during the program (who is considered by many Jeopardy players and producers to be one of the best all-time players with his reaction time).

Ken Jennings and Brad Rutter vs. IBM’s Watson on Jeopardy!

Jeopardy! is one of my all-time favorite shows on Television. When I was in high school, I used to watch every show (it was a nightly ritual). These days, I watch Jeopardy! less than I used to in my younger days, but I’ll be certainly tuning in next week to see Ken Jennings (winner of 74 consecutive games on the show, with a total loot of over $3 million in prize money) and Brad Rutter (the biggest all-time money winner on the show) take on IBM’s artificial intelligence software, Watson.

Perhaps I am downplaying my enthusiasm. I’m really, really looking forward to this Jeopardy! contest, which will take place over three days on February 14, 15, and 16. Watson doesn’t just represent a machine force-fed a bunch of encyclopedias, dictionaries, and thesauri (although that’s certainly a major component of it); no, the machine is also facing the arduous task of deciphering the natural (English) language and everything it entails: nuances, hyperboles, puns, dialects, slang, metaphor, and so much more. In other words, Jeopardy! is a perfect test-drive for Watson: the questions on the show aren’t meant for a computer to answer. And this is why this Watson is such a huge deal:

Watson is a powerful machine. Its setup is called “Massively Parallel Probabilistic Evidence-Based Architecture,” and it runs on 2,800 Power7 processing cores. If all that computer and interpreting power presents an answer that satisfies Watson’s confidence interval, it “rings in” with the answer:

Concerning Watson, Richard Powers made a superb op-ed contribution to the New York Times. In “What is Artificial Intelligence?” (link via @openculture) he elaborates on Watson’s challenge:

Open-domain question answering has long been one of the great holy grails of artificial intelligence. It is considerably harder to formalize than chess. It goes well beyond what search engines like Google do when they comb data for keywords. Google can give you 300,000 page matches for a search of the terms “greyhound,” “origin” and “African country,” which you can then comb through at your leisure to find what you need.

Asked in what African country the greyhound originated, Watson can tell you in a couple of seconds that the authoritative consensus favors Egypt. But to stand a chance of defeating Mr. Jennings and Mr. Rutter, Watson will have to be able to beat them to the buzzer at least half the time and answer with something like 90 percent accuracy.

So the task is two-fold: first arrive at the correct answer and then “buzz in” before Ken Jennings or Brad Rutter. From my observation, Ken Jennings is one of the best players to have mastered the art of the buzz-in (I suspect that for many questions that his competitors knew that he knew as well, his ability to buzz-in before them contributed to at least 30% of his daily winnings on the show). However, I believe the IBM engineers designed Watson for maximum efficiency: as soon as the last syllable escapes Alex Trebek’s lips, Watson will ring in with the answer.

Actually, Watson already competed in a practice round against humans–and beat them, badly. The most interesting tidbit comes from this Discover Magazine piece:

The questions were fed in plain text to Watson, but it had to wait the same amount of time to ring in as the human players did. To make the game fair, it also had to trigger a mechanical signaling button. Watson spoke in a stilted computerized voice–and was almost never wrong.

So if that is the case, Watson isn’t truly “listening” to the questions posed by Trebek; rather, it is reading the plain text. This is important for a reason: if there’s a clue where Alex Trebek accentuates certain part of the answer or perhaps changes his intonation or even his accent, this will be a help for the human contestants. The discrepancy between how the humans are processing the answers vs. Watson cannot be overlooked. For those unfamiliar with Jeopardy!’s buzzer system, the way it is designed is to lock-out the buzzer until Alex Trebek has finished reading the question, and the lock-out period is determined by a human producer (who sits off-camera, and has a button of his/her own which enables the buzzers). If a contestant were to buzz in before the producer pushes that button, the contestant’s buzzer is automatically locked out for three seconds, and any attempt to buzz in before that “penalty” period expires locks the contestant’s buzzer for another three seconds. So this raises an important question: how does Watson know when it can buzz in (i.e., how does it receive notification that the lock-out period has passed?). Will the human players have the advantage here, or will Watson?

Another important question to ponder is this one raised by Richard Powers:

Answers, for Watson, are a statistical thing, a matter of frequency and likelihood. If, after a couple of seconds, the countless possibilities produced by the 100-some algorithms converge on a solution whose chances pass Watson’s threshold of confidence, it buzzes in.

This raises the question of whether Watson is really answering questions at all or is just noticing statistical correlations in vast amounts of data.

In a sense, Watson is like a machine trained in quantum mechanics: it can never be certain about any of the answers, but if it can break the confidence threshold (whatever that may be) for the answer (err, question), it will surely try to buzz in with the response.

I like Powers’s conclusion:

It does not matter who will win this $1 million Valentine’s Day contest. We all know who will be champion, eventually. The real showdown is between us and our own future. Information is growing many times faster than anyone’s ability to manage it, and Watson may prove crucial in helping to turn all that noise into knowledge.

I finish this post with a prediction: I believe Ken Jennings will be the champion of this Jeopardy! contest. I have high hopes for Watson, and I believe it will do quite well, but I am sticking with the all-time champion. Ken is just too good with the buzzer and an absolute whiz for me to bet against him.

What about you? Who do you think will win?

Readings: J.D. Salinger, Free Writing, Charles Darwin

Three things I’ve read today, all worth twenty minutes of your time:

1) “An Evening with J.D. Salinger” [Paris Review] – Blair Fuller recounts a very interesting evening with one of his favorite writers, J.D. Salinger. In attendance are Blair’s younger sister, Jill and her husband, Joe:

He [J.D. Salinger] asked us to call him Jerry, then asked some routine questions about what we were doing and why, but with a pleasing sympathetic intensity. He made several comments that put him on our side, the side of people starting out rather than the people settled in to lifelong careers. The conversation warmed, and we found that we could make each other laugh.

But as the evening progresses, things turn for the worse. The narrative in this piece is wonderful — you have to read the entire thing.

2) “No One is Forced to Write for Free” [Anna Tarkov's blog] — the day after the huge AOL purchase of Huffington Post, Anna Tarkov writes an excellent piece about why Huffington Post writers continue to write for free (and why it’s not as bad as some people make it out to be). Great argument:

No, the reality as we all know is that people chose to write on Huffington Post for free. They chose to do it because HuffPo gave them a platform where a lot of eyeballs would potentially see what they wrote. Most people can’t get that kind of visibility on their own blog. Maybe Dan Gillmor can, but I can’t. So if I decide to write on HuffPo for nothing more than attention, then I’m getting paid in a sense, just not in dollars. How is this different than a business buying a billboard on a busy expressway?

I’m curious whether people in other professions feel similarly about exposing their work for free: photographers, artists, etc.

3) “Charles Darwin’s Little Known Psychology Experiment” [Scientific American] – Darwin wasn’t just well-known for advancing his theory of evolution. This is a great read:

In 1872, Darwin published The Expression of the Emotions in Man and Animals, in which he argued that all humans, and even other animals, show emotion through remarkably similar behaviors. For Darwin, emotion had an evolutionary history that could be traced across cultures and species—an unpopular view at the time. Today, many psychologists agree that certain emotions are universal to all humans, regardless of culture: anger, fear, surprise, disgust, happiness and sadness.

(Hat tip: @matthiasrascher)