31 May 2009

Lolcat to legalese translation

icanhascheezburger.com is sponsoring the Best RAWR Contest in conjunction with the movie Land of the Lost:

OHAI!!1! Kitteh halpers! Sekretly taek a snapshot of ur kitteh in his/her/their best "RAWR" pose and send it in to our "Best RAWR Contest"!

Of course, it sounds a lot less entertaining in the official fine print contest rules:

2. HOW TO ENTER: [...] complete the required information and upload a photo related to the theme of "Roaring" in compliance with these Rules ("Photo") via the supplied upload form page.

24 May 2009

When You Are Engulfed in Flames; The Fabric of the Cosmos

When You Are Engulfed in Flames is David Sedaris's latest book, and the first of his works that I've read. A couple of the stories are quite endearing, especially the ones about Sedaris's close encounters with death, as well as his quest to quit smoking. But many of the others just strike me as "Ha ha, look how quirky we were or are." While When You Are Engulfed in Flames is at least mildly amusing and entertaining throughout, it only rises to the level of laugh-out-loud funny in a couple of places.

As an aside, I noted that David Sedaris was puzzled by some of the same things in Japan that puzzled me during my recent trip to Taiwan, namely, (1) Why is everyone so exceedingly polite? and (2) Why is green salad served at breakfast?

The Fabric of the Cosmos: Space, Time, and the Texture of Reality is Brian Greene's sort-of followup to The Elegant Universe. Fabric of the Cosmos covers the principles of relativity and quantum mechanics and the attempts to unify them (with string theory and its variants). One overarching theme that Greene considers is how all these different theories have different implications about the true nature of space and time— are they purely artificial constructions, or are they fundamental concepts, or are they emergent phenomena arising from something more fundamental? And considering these alternative theories about the nature of the universe is a lot more interesting than just asking "Can we smash tiny particles into tinier particles?" (Although, high-energy physics is indeed still an important apparatus.)

Having not yet totally forgotten my undergraduate physics classes, I was pretty impressed by Greene's treatment of relativity and quantum mechanics. He makes quite lucid analogies that convey the basic principles without much math. His treatment of string theory and the possibility of extra space dimensions was pretty enlightening, too.

The part where my eyes started to glaze over was during the chapters in the middle about the Higgs field and cosmology. At this point it seemed like the analogies that Greene used were just analogies for the sake of not using scary terminology. They seemed to me kind of hollow and didn't really provide any interesting insights about the underlying phenomena.

Overall, Fabric is a well-written guided tour of modern physics and is worth a read (especially if you have not read The Elegant Universe). My only complaint is that after reading so much physics without any math I feel sort of swindled. I feel compelled to go purchase a proper string theory textbook, which, I suppose, is pretty high praise for Professor Greene.

23 May 2009

Human sensorimotor cognition is Bayesian!

In tasks involving hand-eye coordination (for example, returning a serve in tennis), the brain has to estimate a quantity u based on an observation v. Bayes' rule tells us that the optimal estimate of u's distribution depends on both the prior distribution of u as well as on the evidence v:

P(u | v) ∝ P(u) P(v | u)

Intuitively we know that anytime we make an decision based on evidence, the decision critically depends on the uncertainty associated with the evidence (how "trustworthy" the evidence is). This is actually encoded in the equation above. If the observation contains little information about the actual value, then we put more weight on the prior. In the extreme case, if the distribution P(v | u) is independent of (i.e. contains no information about) u then the estimate is exactly the prior:

P(u | v) ∝ P(u)

But if the evidence tells us a lot, then we put less weight on the prior. In the extreme case, if P(v | u) = δ(v, u), we can actually ignore the prior:

P(u | v) = δ(v, u)

So, we have to integrate the two pieces of information— the prior and the evidence— to make an estimate, while accounting for the reliability of the evidence.

Now, if this sounds complicated, you can take some consolation in the fact that you actually already know all this stuff. In a paper published in Nature, Körding and Wolpert (1994) described an experimental setup in which they asked volunteers to complete a hand-eye coordination task. The subjects' task performance indicates that the human brain maintains estimates of the prior distribution and the evidence uncertainty, and combines them in a way that is consistent with the Bayesian estimate above (and inconsistent with a couple of alternative models of cognition).

That's right: we appear to be hard-wired for Bayes' rule. This is pretty amazing, if you ask me.

Konrad P. Körding and Daniel M. Wolpert, Bayesian integration in sensorimotor learning. Nature vol. 427, pp. 244-247 (15 January 2004)

04 May 2009

Office 2007 ODF support

Not content to discredit the OpenDocument format with FUD, Microsoft has now resorted to poisoning the well with its own ODF filter for Office 2007.

Rob Weir computed this compatibility matrix for Microsoft Excel:

Now critics might argue that the ODF format is underspecified, but that's true in some sense of every standard. It's almost as if Microsoft did not even make a good faith effort here (I know, shocking):

Remember, it is not particularly difficult or clever to to take an adverse reading of a standard to make an incompatible, non-interoperable product. [...] The difference between minimal conformance and interoperability is well illustrated in these tests.