Another Sisyphus Job

In this entry I was talking about the mechanics of why multitaskers don't do things faster, nor that they seem to do things better. This interesting article seem to be saying the same. On top of the parallel computing idea that in order to multitask you need to constantly switch between different tasks, you also need to reinitialize your RAM everytime (by no means a simple process), it seems that humans are not efficient at constantly switching their RAMs. In other words, the constant RAM loading process seems less efficient as the day go by. Knowing that we seem to learn things after having been exposed to it only if we let six to eight hours to the brain to sleep on it, it would seem that most of us are condemned to relearn the same thing everyday...

It's not 'sixth sense' if it's smell

It looks like most animals were not affected by the Tsunami as evidenced in this story. Is this urban legend or just that our sense of smell is not good enough compared to other species. Remarkably, if birds are also able to sense this phenomena, it maybe a magnetic detection capability rather than smell.

Treacherous Solitons

If you think that it is just enough to think you have a warning system then you should probably think twice. In fact, it looks like, we really have no warning system in the Atlantic Ocean where a recent research paper show that a larger Tsunami to the one that hit South Asia could occur
and devastate the U.S. eastern sea shore, part of Europe, South America and Africa.

But be reassured some people tell us that no such mega tsunami can exist, well.... until something like MN4 hit us.
As expected, the internet that was supposed to survive in a nuclear war as a means of communication is doing so as seen in this E-mail sent from one of the worst hit part of Indonesia. It also seems to be a good idea to have a GSM phone when traveling.

Merci la Pologne

Vous pouvez les remercier ici, ma traduction francaise est:

Je sousigne veut exprimer mes plus sinceres remerciements au gouvernement de Pologne pour leur action qui a permit d'enlever la directive sur les brevets se rapportant aux programmes d'ordinateurs (Software Patent Directive) de l'agenda de la reunion du Conseil de l'Agriculture le 21 Decembre 2004. Il aurait ete tres dommageable pour l'Union Europeenne d'adopte ce texte.

Metallic Parachutes

No I do not mean to talk about the Golden parachutes at Merck or DoubleClick. Rather, I am refering to this story on CNN about how a small company called BRS is designing parachutes to save crashing planes. Technology Review on the other hand tells us about a company using Nanotechnology to develop rubber tires into having more metalic properties. And while both of them receive funding from the government, you'd think that matching the two technologies might actually do some good to providing parachutes for entire Jumbo jets.

Thought compression

This week, a code of 15 lines was produced that enables a computer to run a P2P service like Kazaa. It is here. What are the lessons from this ? Well for one, it lowers the barrier to entry so that groups of friends can now set this type of system with each other. You cannot trust anybody on the internet, but at least you could trust your friends. The second point is that I believe it takes about 15 lines of written text to explain to somebody what a P2P service is. In other words, compressing the concept of P2P sharing into a thought is close to the amount of writing needed to implement it. And it takes about 60+ lines to explain in detail to a specialist what it really does. It is what makes Python a high level language.

We don't care about sleeping like babies no more. Part deux.

In a previous entry, I mentionned how bad it would be to build a business around better sleeping facilities since most people were willing to go the chemical route anyway. This article from Forbes (thanks Cable), shows that it will become actually worse that than:

For the first time, the U.S. Food and Drug Administration has approved a sleeping pill without restrictions warning doctors not to prescribe the medicine for long-term use. Lunesta, formerly referred to as Estorra, will be available in pharmacies in January. It will be marketed with a $60 million direct-to-consumer advertising campaign.

A $60 million ad campaign, uh ? What are the chances the average doctor will resist the pressure of his customers to prescribe the medicine for long-term use ? My take is: very few will. Don't worry though, if you have any apnea and your heart stops beating, you just need to have one of these defibrillators from amazon.com next to your bed and expect somebody to use it properly.

The pollution that blinds you

We already knew of the pollution induced smog, a hazy condition produced by particle pollution. We also knew of light pollution due to the atmosphere scattering of city lights and radio FM signals. It used to be that only astronomers were disturbed by this phenomena, but now the RF apectrum is so overwhelmed with new RF sources (cell phones, 802.11...) that it now has an ability to pollute the readings made by meteorology satellites who have intruments that can detect only a few frequency bands.

Thermal Shadowing

Using the Monte Carlo ray tracer of RadCAD (a package in the Thermal Desktop suite), Olivier Godard and Tejas Shah came up with this simulation. What you see is the view of the belly of the Space Shuttle as it rotates around the Earth from the international space station. The Space Shuttle orbiter has its with the payload bay looking Nadir. Above it and traveling at the same speed is the International Space Station (ISS) which shadows the Space Shuttle whenever both of them are lit by the sun. The 1354 number in the legend is the Sun's heat flux -in Watt per meter square (W/m2)- received by the Shuttle from the Sun. The blue color shows most of the ISS blocking the Sun's heat flux. In other words what you see is the shadow of the ISS on the Shuttle. We could have done it with a raytracer used for animated movie rendering but what the nice feature here is that you can obtain a similar result that is directly usable for other thermal related computations.

The pursuit of matching employees

Google seems to try several ways to hire people they consider very good. So they tried proximity and small challenges like this billboard announcement. But in the end, they also need to refine their needs and the only way to do this efficiently seems to be the use of Adwords with the right keywords or series of keywords. Take for instance a Google search on basis pursuit. As evidenced in the lack of Google Adwords on matching pursuit, they already know one algorithm is doing better than the other.

GPUs as supercomputers

EE Times has a series of articles on using graphics chip as supercomputers (part 1, part 2, part 3, part 4) or using other chips for computations not initially designed for that purpose.

(the summary page is here).

Outrageous behavior

In this entry, one is told that two outsiders have been discredited as shown in a recent peer review publication. The outrageous behavior is not the fact that there is a controversy, nor the fact that mentionning somebody's occupation is clearly irrelevant when it comes to scientific discourse but rather that the authors state the following outrageous comments:

It should be noted that some falsely reported putative errors in the Mann et al.(1998) proxy data claimed by McIntyre and McKitrick (2003) are an artifact of (a) the use by these latter authors of an incorrect version of the Mann et al. (1998) proxy indicator dataset, and (b) their misunderstanding of the methodology used by Mann et al. (1998) to calculate PC series of proxy networks over progressively longer time intervals.

For argument a)

If they are using an incorrect version of the proxy indicator dataset, does it mean that this data is not freely available ? Do these people mean to say that major climate modeling issues decided on a worldwide policy level are dependent on data that are properties of some researchers ?

For argument b)

How can a methodology be misunderstood if it is clearly published in the first place? How come the algorithm used to obtained these data is not freely available ?

If treaties are being negociated with every nation on this earth, one should at least make sure that the data from which these policies are developed follow the principles of reproducible research. As Donoho and Buckheit point out when they developed the Wavelab toolbox:

An article about computational science in a scientific publication is not the scholarship itself, it is merely advertising of the scholarship. The actual scholarship is the complete software development environment and the complete setof instructions which generated the figures

The outrageous behavior is not the criticism of datasets dating back to 1998 but rather the inability for a mining industry specialist and an economist to have access to the initial data and the means of producing the data of the paper.

Now, I will not comment on the fact that neither side of the issue seem to be addressing the fact that none of them can explain HOW components found through the PCA technique are indicative of an actual physical phenomena.

Questions to ask yourself: Wine, Women and Song.

In a previous entry, I mentionned Richard's Hamming quote coming out of his obituary. I was wrong, it was extracted from a colloquium seminar at Bell Communications Research entitled "You and Your Research". The quotes have been summarized by Todd Proebstring in his talk at LL1.

Even though some of what he says seem trivial, it is nonetheless important to have it in writing. Quotes, or entire paragraphs I like include:

Knowledge and productivity are like compound interest.

That's the trouble; drive, misapplied, doesn't get you anywhere.

Darwin writes in his autobiography that he found it necessary to write down every piece of evidence which appeared to contradict his beliefs because otherwise they would disappear from his mind. When you find apparent flaws you've got to be sensitive and keep track of those things, and keep an eye out for how they can be explained or how the theory can be changed to fit them. Those are often the great contributions. Great contributions are rarely done by adding another decimal place.

Over on the other side of the dining hall was a chemistry table. I had worked with one of the fellows, Dave McCall; furthermore he was courting our secretary at the time. I went over and said, "Do you mind if I join you?" They can't say no, so I started eating with them for a while. And I started asking, "What are the important problems of your field?" And after a week or so, "What important problems are you working on?" And after some more time I came in one day and said, "If what you are doing is not important, and if you don't think it is going to lead to something important, why are you at Bell Labs working on it?" I wasn't welcomed after that; I had to find somebody else to eat with! That was in the spring.

In the fall, Dave McCall stopped me in the hall and said, "Hamming, that remark of yours got underneath my skin. I thought about it all summer, i.e. what were the important problems in my field. I haven't changed my research," he says, "but I think it was well worthwhile." And I said, "Thank you Dave," and went on. I noticed a couple of months later he was made the head of the department. I noticed the other day he was a Member of the National Academy of Engineering. I noticed he has succeeded. I have never heard the names of any of the other fellows at that table mentioned in science and scientific circles. They were unable to ask themselves, "What are the important problems in my field?"

We didn't work on (1) time travel, (2) teleportation, and (3) antigravity. They are not important problems because we do not have an attack. It's not the consequence that makes a problem important, it is that you have a reasonable attack. That is what makes a problem important. When I say that most scientists don't work on important problems, I mean it in that sense. The average scientist, so far as I can make out, spends almost all his time working on problems which he believes will not be important and he also doesn't believe that they will lead to important problems.

Most great scientists know many important problems. They have something between 10 and 20 important problems for which they are looking for an attack. And when they see a new idea come up, one hears them say "Well that bears on this problem." They drop all the other things and get after it. Now I can tell you a horror story that was told to me but I can't vouch for the truth of it. I was sitting in an airport talking to a friend of mine from Los Alamos about how it was lucky that the fission experiment occurred over in Europe when it did because that got us working on the atomic bomb here in the US. He said "No; at Berkeley we had gathered a bunch of data; we didn't get around to reducing it because we were building some more equipment, but if we had reduced that data we would have found fission." They had it in their hands and they didn't pursue it. They came in second!

You should do your job in such a fashion that others can build on top of it, so they will indeed say, "Yes, I've stood on so and so's shoulders and I saw further." The essence of science is cumulative. By changing a problem slightly you can often do great work rather than merely good work. Instead of attacking isolated problems, I made the resolution that I would never again solve an isolated problem except as characteristic of a class.

I have now come down to a topic which is very distasteful; it is not sufficient to do a job, you have to sell it. `Selling' to a scientist is an awkward thing to do. It's very ugly; you shouldn't have to do it. The world is supposed to be waiting, and when you do something great, they should rush out and welcome it. But the fact is everyone is busy with their own work. You must present it so well that they will set aside what they are doing, look at what you've done, read it, and come back and say, "Yes, that was good." I suggest that when you open a journal, as you turn the pages, you ask why you read some articles and not others. You had better write your report so when it is published in the Physical Review, or wherever else you want it, as the readers are turning the pages they won't just turn your pages but they will stop and read yours. If they don't stop and read it, you won't get credit.

There are three things you have to do in selling. You have to learn to write clearly and well so that people will read it, you must learn to give reasonably formal talks, and you also must learn to give informal talks.

Well I now come down to the topic, "Is the effort to be a great scientist worth it?" To answer this, you must ask people. When you get beyond their modesty, most people will say, "Yes, doing really first-class work, and knowing it, is as good as wine, women and song put together," or if it's a woman she says, "It is as good as wine, men and song put together." And if you look at the bosses, they tend to come back or ask for reports, trying to participate in those moments of discovery. They're always in the way. So evidently those who have done it, want to do it again. But it is a limited survey. I have never dared to go out and ask those who didn't do great work how they felt about the matter. It's a biased sample, but I still think it is worth the struggle. I think it is very definitely worth the struggle to try and do first-class work because the truth is, the value is in the struggle more than it is in the result. The struggle to make something of yourself seems to be worthwhile in itself. The success and fame are sort of dividends, in my opinion.

In summary, I claim that some of the reasons why so many people who have greatness within their grasp don't succeed are: they don't work on important problems, they don't become emotionally involved, they don't try and change what is difficult to some other situation which is easily done but is still important, and they keep giving themselves alibis why they don't. They keep saying that it is a matter of luck.

Amazing discoveries.

Sometimes you read a series of paper and you know that there is something big behind it. Here are two examples:

The first one is by Emmanuel Candes and Dave Donoho: A Surprisingly Effective Nonadaptive Representation for Objects with Edges. As Bruno Olshausen has shown, most natural images seem to be made of edges and the human eye seem to be good a detecting those. What this article says is that there is no need for our eye system to be adaptive to figure out an image. This is an impressive result because most people think otherwise.

The second series of papers by Emmanuel Candes, Justin Romberg and Terence Tao entitled Robust Uncertainty Principles: Exact Signal Reconstruction from Highly Incomplete Frequency Information and Near Optimal Signal Recovery From Random Projections: Universal Encoding Strategies? show that the right type of signal, decomposed with the right bases, can be reconstructed using an simple linear optimization algorithm. This finding is tied to ubiquitous power laws.

We still need better maps

Here is a way to deal with navigation in towns: Use cell phones as tour guides. With the ubiquity of cell phones, one can definitely think of a cell phone as replacing previous more expensive solutions.

Weather patterns influenced by wind farms

With all the talk about renewable energy not affecting the environment, here is one article that seems to say otherwise. Evidently, it would be easier to go after the real polluters than the ones directly warming the atmosphere, right ?

On the one hand...

One day, we are still trying to figure out why left handed people have been able to survive with evolution and then a day later, we find out that they are likely to win in a hand-to-hand combat. Correlation much ?

Interesting way of teaching

Via Lemonodor, here is a very funny but effective way to learn some LISP through comics.