The New York Times did an article a few days ago on the magic shows at the Conference on Consciousness that was held in Vegas this year. Magicians discussed with the scientists that if you create an assumption of a behavior pattern, then your audience will assume something is fact when in truth it doesn't have to be. Today they have an article about how out-of-body experiences can be induced by creating a mismatch between the different sensory streams that our brain uses.
What this means is that even our brains-- though they are very complex and have learned from a lot of experiences as our lives go on-- sometimes still cannot detect scenarios that have the same sensory input as another more common scenario but are actually different. I like the example of the rubber hand. Subjects with their hand under the table and a rubber hand on the table had both hands stroked by a stick. Visually, you would see that the stick is stroking the rubber hand, and since you feel your own hand being stroked, you would assume the rubber hand is your own. The people even shrieked when the rubber hand was hit by a hammer!
(note: NYtimes links are only free for a couple days)
24 August 2007
23 August 2007
"the moon" incident
I just read about this in the Wittenberg Door.
During a science lecture by Bill Nye in Waco, a woman stormed out when the Science Guy informed his audience-- after quoting from Genesis that God made two lights in the sky along with the stars-- that the moon was not in fact a light but simply a reflector.
In this response, they express their opinion that the woman left upset because the Science Guy had purposefully brought up the bible and said that it was wrong, as if to attack the bible.
Maybe it's true-- maybe if our dear Bill had not brought up Genesis, everyone in Waco would have been happy to know that the moon is a reflector. sigh.
But anyway, how else do we scientists get christians to start considering figurative interpretations of the bible? Perhaps by donating to the unicorn museum billboard to be installed near the creation museum in Kentucky. Unicorn museum motto-- "Unicorns are real. The bible says so."
Also, the Waco Tribune *did* take down the story from their website. I can't judge whether that was out of embarrassment. They have at least 30 days of history on there, but no such original story from a few days ago.
During a science lecture by Bill Nye in Waco, a woman stormed out when the Science Guy informed his audience-- after quoting from Genesis that God made two lights in the sky along with the stars-- that the moon was not in fact a light but simply a reflector.
In this response, they express their opinion that the woman left upset because the Science Guy had purposefully brought up the bible and said that it was wrong, as if to attack the bible.
Maybe it's true-- maybe if our dear Bill had not brought up Genesis, everyone in Waco would have been happy to know that the moon is a reflector. sigh.
But anyway, how else do we scientists get christians to start considering figurative interpretations of the bible? Perhaps by donating to the unicorn museum billboard to be installed near the creation museum in Kentucky. Unicorn museum motto-- "Unicorns are real. The bible says so."
Also, the Waco Tribune *did* take down the story from their website. I can't judge whether that was out of embarrassment. They have at least 30 days of history on there, but no such original story from a few days ago.
21 August 2007
Anything you can do, I can do Meta
MIT Technology Review has a good article about Charles Simonyi in the Jan/Feb 2007 issue. Simonyi created microsoft word, and now he hopes to fix the way programmers do their job. He asks, "Why is it so hard to create good software?" here are some quotes.
"Everywhere you look, software is over budget, behind schedule, insecure, unreliable, and hard to use. Anytime an organization attempts to introduce a new system, or upgrade an old one, it takes a colossal risk."
"The US Government has found it nearly impossible to introduce or upgrade large-scale software systems: Decade long efforts at the FAA and FBI have collapsed in chaos. Businesses have fared no better. To give a single example, McDonald's executives dreamed of a (new software system)...By the time they gave up and canceled the project, they had to write off $170 million of its estimated $1 billion cost."
"But even as Moore's Law has made each year's new computers faster and cheaper, the flexibility and utility of our computer systems have been limited by the slower, uneven evolution of software. One formulation of this problem is known as Wirth's Law, after programming expert Niklaus Wirth: 'Software gets slower faster than hardware gets faster.'"
"...in Simonyi's quest to alleviate the chronic woes of the software field. 'It's not enough to be a great programmer,' Simonyi once told Hichael Hiltzik, author of a history of PARC. 'You have to find a great problem." [Simonyi's company] Intentional Software may not deliver on its grand promises. But no one can charge Simonyi with choosing too modest a problem."
One funny thing-- Simonyi doesn't know how to turn off Clippy. Ha.
Just to put in my two cents, I contend that it's so hard to create good software because programmers have typically been the type of person who wants to tinker and hack. A stereotypical coder enjoys tweaking things until they work, whether or not he knows exactly why it started working. (I used the male pronoun on purpose here! haha)
"Everywhere you look, software is over budget, behind schedule, insecure, unreliable, and hard to use. Anytime an organization attempts to introduce a new system, or upgrade an old one, it takes a colossal risk."
"The US Government has found it nearly impossible to introduce or upgrade large-scale software systems: Decade long efforts at the FAA and FBI have collapsed in chaos. Businesses have fared no better. To give a single example, McDonald's executives dreamed of a (new software system)...By the time they gave up and canceled the project, they had to write off $170 million of its estimated $1 billion cost."
"But even as Moore's Law has made each year's new computers faster and cheaper, the flexibility and utility of our computer systems have been limited by the slower, uneven evolution of software. One formulation of this problem is known as Wirth's Law, after programming expert Niklaus Wirth: 'Software gets slower faster than hardware gets faster.'"
"...in Simonyi's quest to alleviate the chronic woes of the software field. 'It's not enough to be a great programmer,' Simonyi once told Hichael Hiltzik, author of a history of PARC. 'You have to find a great problem." [Simonyi's company] Intentional Software may not deliver on its grand promises. But no one can charge Simonyi with choosing too modest a problem."
One funny thing-- Simonyi doesn't know how to turn off Clippy. Ha.
Just to put in my two cents, I contend that it's so hard to create good software because programmers have typically been the type of person who wants to tinker and hack. A stereotypical coder enjoys tweaking things until they work, whether or not he knows exactly why it started working. (I used the male pronoun on purpose here! haha)
give them more time
This new york times article talks about how highschool students who are far behind can finish-- if you just give them more time.
I believe strongly in eliminating expectations on time. Why should you get a HS diploma at 18, college diploma at 22, married at 23, promoted at 25....etc?
This precludes all interesting paths, like traveling the world for a year, earning money needed for family emergencies, spending time doing real community service, or playing in a rock band before you get your PhD in your late 30s (I know someone who did this).
Forget the timeline, people.
I believe strongly in eliminating expectations on time. Why should you get a HS diploma at 18, college diploma at 22, married at 23, promoted at 25....etc?
This precludes all interesting paths, like traveling the world for a year, earning money needed for family emergencies, spending time doing real community service, or playing in a rock band before you get your PhD in your late 30s (I know someone who did this).
Forget the timeline, people.
25 May 2007
ok go vids
I am a little old for all these new internet fads, but I just have to say that the Ok Go videos are the reason why YouTube should exist.
Junior year in college, one of my friends told me I would like Ok Go, and after that I used to listen to them. So when I saw this video on Mtv-U I was totally psyched, and of course I loved it.
a million ways to be cruel
And now that the treadmill video is out...can anyone ever beat it? Can they even make anything better themselves?? Note: as I post this right now, there have been over 17,600,000 views of this video on youtube.
here it goes again
When I saw them play at the This American Life tour a couple of months ago, one guy said it's his sister who choreographs the videos! She rocks.
Junior year in college, one of my friends told me I would like Ok Go, and after that I used to listen to them. So when I saw this video on Mtv-U I was totally psyched, and of course I loved it.
a million ways to be cruel
And now that the treadmill video is out...can anyone ever beat it? Can they even make anything better themselves?? Note: as I post this right now, there have been over 17,600,000 views of this video on youtube.
here it goes again
When I saw them play at the This American Life tour a couple of months ago, one guy said it's his sister who choreographs the videos! She rocks.
20 May 2007
artificial intelligence
Tons of technologies around us use some form of artificial intelligence. Science fiction media usually gives us the impression that AI is just a robot that can walk and talk like a human, but really AI is the practice of getting a machine to do something humans currently do, like make decisions or classify objects and rank their relevance. Mathematics, computer science, statistics and signal processing all play roles in the field of artificial intelligence-- we give it many names like statistical learning, machine learning, estimation, classification....etc.
Let me give you some examples... Spam filters try to classify email as spam. Netflix or Amazon (and others) try to suggest new products based on what you and others like. Alarm systems decide when a home has been broken into and notify the police. GPS boxes for your car give you directions and then adjust to your own choices or mistakes and give you a new route to follow. Google tries to find the best website match for your search terms. Translators try to find the best match from a set of words in one language to a set of words in another.
For a long time, certain learning algorithms have focused on improving algorithm performance with a limited amount of "training data"-- data you have ahead of time that you already know how it should get classified, for example. So if Netflix has some data where you told them what movies you were actually interested in, then this is training data. You can use that information to teach your algorithm your preferences. Or, you can use the training data as "testing data", to see if the algorithm predicts a movie that you actually do like.
Now, however, google is showing us that the real way to go is not to improve the algorithm carefully--but instead to give the algorithm a ridiculous amount of training data. As you increase the amount of training data, all of the algorithms can just do vastly better-- way better than any new-and-improved AI algorithm does on a small set of training data. So for example, google is working on a translation service, and they are looking for every multilingual journalistic publication out there. Wherever they can find the same stories in two languages, google algorithms can try to learn how to translate between those two languages by learning. You might wonder, what if some of the translations are wrong? Well if there are enough data, then those incorrect translations will get lost in the heap, and the algorithm will still do well.
In my field of sensor networks, we are collecting data and hope to create technologies that can make all kinds of decisions for us-- hopefully, better decisions than we could even make ourselves, because they incorporate both human knowledge and a vast resource of collected data. For example, in the santa monica mountains nature preserve, rangers are collecting a lot of data using sensors. Because of it, they are better able to decide on properties to buy and add to the reserve for the best plant and animal preservation, building codes for developing property nearby, and developer requests.
(I don't know where I am going with this. But here you go.)
Let me give you some examples... Spam filters try to classify email as spam. Netflix or Amazon (and others) try to suggest new products based on what you and others like. Alarm systems decide when a home has been broken into and notify the police. GPS boxes for your car give you directions and then adjust to your own choices or mistakes and give you a new route to follow. Google tries to find the best website match for your search terms. Translators try to find the best match from a set of words in one language to a set of words in another.
For a long time, certain learning algorithms have focused on improving algorithm performance with a limited amount of "training data"-- data you have ahead of time that you already know how it should get classified, for example. So if Netflix has some data where you told them what movies you were actually interested in, then this is training data. You can use that information to teach your algorithm your preferences. Or, you can use the training data as "testing data", to see if the algorithm predicts a movie that you actually do like.
Now, however, google is showing us that the real way to go is not to improve the algorithm carefully--but instead to give the algorithm a ridiculous amount of training data. As you increase the amount of training data, all of the algorithms can just do vastly better-- way better than any new-and-improved AI algorithm does on a small set of training data. So for example, google is working on a translation service, and they are looking for every multilingual journalistic publication out there. Wherever they can find the same stories in two languages, google algorithms can try to learn how to translate between those two languages by learning. You might wonder, what if some of the translations are wrong? Well if there are enough data, then those incorrect translations will get lost in the heap, and the algorithm will still do well.
In my field of sensor networks, we are collecting data and hope to create technologies that can make all kinds of decisions for us-- hopefully, better decisions than we could even make ourselves, because they incorporate both human knowledge and a vast resource of collected data. For example, in the santa monica mountains nature preserve, rangers are collecting a lot of data using sensors. Because of it, they are better able to decide on properties to buy and add to the reserve for the best plant and animal preservation, building codes for developing property nearby, and developer requests.
(I don't know where I am going with this. But here you go.)
10 May 2007
Generation M
I just read part of this good article on how to parent "the media generation." I feel really lucky that I used email and IM starting when I was 16 and that I was right on the bandwagon and thick into technology when friendster and google happened.
There are two main thoughts I had to supplement the article.
First of all, media technology may be the way of the future, and kids are learning early online social skills, research skills, and creative skills--ie, they are "playing in information" as the article says. However, from being in the workplace after college I saw a problematic form of performance metric in our jobs-- hours with your butt in the chair. 15 years ago, when you sat down in your office job, the only thing you could do to distract yourself is pick up the landline phone. Otherwise you had to just sit at your desk and either daydream or just get your work done. No one can daydream all day, and anyway if you stare out the window all day people get suspicious. So it was easier for people to get work done because there was nothing else to distract them.
I think that now it is possible for people to sit at their desk--and in fact look quite busy-- all while using internet and networking media technology. And this practice is not only bad for the company, but it's horrible for the person practicing it-- work becomes a constant struggle to learn how to focus.
I believe virtual worlds and multitasking are not better, only alternatives to real worlds and focus. In the end I think both will be needed. And for someone to teach their media kid how to focus, I think one of the best ways would be to find something cool and exciting on the web-- and print it out and take it to a quiet place where there are no distractions. For example, your kid could learn how to design sound canceling headphones or practice drawing.
Secondly, the article refers to "cell phone etiquette" as if this is something which has been defined by my parents' generation. The truth is, kids often don't care if their friends answer their cell phone on the first ring, interrupting the conversation (even at the dinner table!). Etiquette is not something set in stone, but instead something that involves being sensitive to how the people around you feel about your actions. I think old fogies (I unfortunately have to include myself here) will just have to accept the fact that what makes them uncomfortable may not make other people uncomfortable, and to teach their kids to have some sensitivities to all the different types of reactions. For example I think (hope) it's still safe to say that you shouldn't answer your phone at Thanksgiving dinner or at dinner with grandma, but otherwise you might just teach them to extend a courteous, "Do you mind if I answer this?" the first time it happens in uncertain circumstances.
There are two main thoughts I had to supplement the article.
First of all, media technology may be the way of the future, and kids are learning early online social skills, research skills, and creative skills--ie, they are "playing in information" as the article says. However, from being in the workplace after college I saw a problematic form of performance metric in our jobs-- hours with your butt in the chair. 15 years ago, when you sat down in your office job, the only thing you could do to distract yourself is pick up the landline phone. Otherwise you had to just sit at your desk and either daydream or just get your work done. No one can daydream all day, and anyway if you stare out the window all day people get suspicious. So it was easier for people to get work done because there was nothing else to distract them.
I think that now it is possible for people to sit at their desk--and in fact look quite busy-- all while using internet and networking media technology. And this practice is not only bad for the company, but it's horrible for the person practicing it-- work becomes a constant struggle to learn how to focus.
I believe virtual worlds and multitasking are not better, only alternatives to real worlds and focus. In the end I think both will be needed. And for someone to teach their media kid how to focus, I think one of the best ways would be to find something cool and exciting on the web-- and print it out and take it to a quiet place where there are no distractions. For example, your kid could learn how to design sound canceling headphones or practice drawing.
Secondly, the article refers to "cell phone etiquette" as if this is something which has been defined by my parents' generation. The truth is, kids often don't care if their friends answer their cell phone on the first ring, interrupting the conversation (even at the dinner table!). Etiquette is not something set in stone, but instead something that involves being sensitive to how the people around you feel about your actions. I think old fogies (I unfortunately have to include myself here) will just have to accept the fact that what makes them uncomfortable may not make other people uncomfortable, and to teach their kids to have some sensitivities to all the different types of reactions. For example I think (hope) it's still safe to say that you shouldn't answer your phone at Thanksgiving dinner or at dinner with grandma, but otherwise you might just teach them to extend a courteous, "Do you mind if I answer this?" the first time it happens in uncertain circumstances.
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