Thursday, March 31, 2005

Fake fly

"Engineering gene networks to emulate Drosophila embryonic pattern formation" is a recently-published paper that describes an implementation of an idea I'd been thinking about as an application of synthetic biology to studying animal development [and while it's kind of annoying to see somebody else publish the results of an experiment I was thinking of trying, at least it means I'm thinking about the right things :-)]. The basic idea is this: animal development, from the single fertilized cell to the fully-developed animal, is a really complicated, poorly-understood process. Maybe if we can build our own, simplified version of certain aspects of the development process, we can learn something about how it all works. That's what the authors of this paper did: they built a system that mimics certain aspects of fruitfly development, in an attempt to get some insights into how the chemical concentration gradients that are known to exist in Drosophila embryos are established and maintained.

After reading the paper [in an admittedly rather cursory fashion], though, I must say I'm a bit disappointed. I can't really place my finger on why, other than the vague feeling that somehow their artificial system is too artificial -- they didn't use live cells, they glued bits of DNA into specific locations to mimic localized protein production etc. So, in the end, I don't know whether their results really tell me much about what's actually going on in living cells or just what's going on in their little artificial system. While that's always a question when you perform experiments entirely in vitro [ie not in actual cells], in some cases it's easier to argue that your results are relevant to living cells than in other cases. In this instance, I think it'd be hard to make a very convincing argument.

All that said, I still think it's an interesting paper, at least in terms of helping to clarify my thinking on how I would do this [or not do it] if I were to tackle a similar problem.

Wednesday, March 30, 2005

Ouch, that's going to leave a mark

You know something went wrong when a professor says [paraphrased] "And now I want to talk a bit about the midterm exam. Some of you will see scores that you're not at all used to seeing, that you haven't actually seen since, oh, your 13th birthday. Your first response to getting your results should not be to drop the class; rather, it should be to blame me for being a bad teacher. This is the first time we've actually had exams in this course and it's clear that we have a lot to learn. So, if you scored less than 25%, don't freak out, please come and see me".

This little speech referred to the results of the midterm in my cell bio class [in which I was hoping for partial credit], where the mean score was 51%, with a standard deviation of 16%. So, assuming a normal distribution, that means close to 70% of all the students in the class scored between 35% and 67%. Not exactly the sort of thing MIT grad students [or any grad students, I would think] are used to, hence his mea culpa.

That distribution is pretty closely aligned with what happened on the midterm in my molecular biology class, which had a mean of 54%, with a standard deviation of 14%. But at least in that case, the low mean was [mostly] intentional -- the professors told us at the beginning of the semester that they tend to give hard exams, and the mean usually hovers around 60%. In this case, I guess they overshot a little [or undershot, as the case may be].

This is in stark contrast with one of my other classes, which is computational and hence has more of a cut-and-dried, no-matters-of-opinion-and-interpretation -- the mean on the midterm in that class was 82%.

I take all this as further confirmation of my growing suspicion that "no, really, biology is hard" ;-) If only it weren't so interesting and useful [as opposed to being interesting but not useful, at least not yet].

Sunday, March 27, 2005

The Hunt For Red Eggtober

Since we don't get to spend Easter with Christina's family, like we've done the past few years, Christina and I made ourselves an Easter basket, colored some eggs and put on our own Easter egg hunt. I was originally a bit concerned that I wouldn't be able to find the eggs she'd hidden, but that's because I was ignorant of the rules: apparently, you have to hide the eggs in such a fashion that they can be found by little kids ie sort of in plain sight [if you know where to look] but odd places. This means you have to exploit "natural" camouflage, like putting the egg on a surface that matches its color. Maybe next year we'll expand the rules and allow things like enclosure in a single container [eg a drawer]; anything more than that, and I think you start getting into "Ok, this isn't fun anymore, just frustrating" territory.

The best part about all this, of course, is all the candy in the basket. Colored eggs are cool and all, but the high concentration of chocolate, marzipan and gummy race cars [Haribo rules !] is really the key part of an Easter basket.

Saturday, March 26, 2005

Whoa, where'd that gene come from ?

There's a paper in this week's edition of Nature magazine that talks about a surprising finding made by scientists at Purdue, namely that Arabidopsis, a plant, seems to be able to fix a defective gene that it shouldn't be able to fix. [Here's the link to the NYT article describing this, or, if you have a subscription, to the actual Nature paper] Basically, the information needed to fix the defective gene doesn't appear to be anywhere in the plant's DNA, yet the plant magically retrieves it from somewhere. The paper's author's speculate that the "missing" information is encoded in RNA [instead of DNA], and that there are RNA copies of the plant genome that act as a "cache" of genes that used to be around in earlier generations. When the plant is under stress and needs to fix a defective gene for which it doesn't have a working version in its DNA, it goes up to the attic [RNA], so to speak, blows the dust off some old genes that it "knows" used to work, and uses those to fix the broken gene. Certainly an interesting idea, we'll have to wait and see what else comes out of this line of inquiry.

My impressions, in no particular order:

- Score another one for RNA. In the last few years, it's become increasingly apparent that RNA isn't just a boring intermediate in the path from DNA to protein: small interfering RNAs [siRNAs], microRNAs and riboswitches are very active in regulating gene expression [microRNAs regulating up to a third of all human genes, by some estimates]; RNA molecules can act as enzymes to catalyze chemical reactions [a role normally reserved for proteins] and can be used instead of antibodies to bind tightly to specific proteins for therapeutic and experimental purposes etc. With the publication of this paper, there's now another putative role for RNA, namely that it acts as a "backup copy" of the genes of previous generations.

- I suspect this will provide fodder for the Intelligent Design folks, in the form of "Look, not even something as supposedly unassailable and 'simple' as the fact that DNA encodes our inherited information is really true ! How can the theory of evolution be accurate ?"

- It makes me wonder how many decades it will be before we can be sure that we really understand the genome, its maintenance, expression and evolution [and if we ever really will]. The more we learn about it, the more complicated it gets. Not too surprising, I guess, given the heavy burden it has to carry, generating all that species-level and individual variety, but from an engineering "I want to understand it so I can control it" standpoint, it's a bit daunting.

Thursday, March 24, 2005

Don't hate the player, hate the game

My answer to Bill Tozier's "What are you going to do about it ?" question is: not play.

Ever since I started down the graduate school path, I've always been pretty clear about the fact that there's no way I'm going to try to become an academic. The notion of spending 5+ years getting a PhD, 1-3 years as a postdoc slave working for minimum wage, hopefully getting a tenure-track position and then having to bust my @$$ for another 4-7 years trying to get tenure has never made sense for me. Partially that's because of my "life stage": I've had a real life that I want to get back to as soon as possible, Christina and I want to start having kids and so there's no way I want to end up 40+ years old, with kids and a mortgage, and looking for a job because I didn't get tenure. However, to a large extent that decision is also because
of my belief that the risk/reward profile of academia makes no sense -- it's like a job-related version of the Chewbacca defense.

Let's take compensation, based on
this survey of professor salaries at various universities:

- MS pays people coming straight out of undergrad, with no advanced degrees, almost the same as assistant professors get at MIT & Havard. For 6-8 years less school, that's a tradeoff definitely worth making.
- A full Harvard professor makes $150K/year [neglecting income from consulting gigs etc]. Becoming a full professor takes [I think] 5-10 years. Somebody who has a successful career at MS would make about $150K after 6-7 years there. And, on average, the probability of having that successful a career at MS is higher than there is of becoming a full professor at Harvard. There are more opportunities and the competition is less intense.

Ah, but what about getting to be your own boss, doing what you want, advancing science etc ? In other words, all the "intangible" benefits of being an academic ? Let's tackle these one by one:

i) "I'm my own boss". Sure, but you're not a slave in industry either. At a certain level of seniority in industry, you in many ways end up getting to decide what you want to spend your time on. As a dev manager, I had considerable freedom in deciding whether to spend my time attending code & design reviews, think about future product direction etc.
ii) "I can work purely on stuff that interests me". It's not clear to me that that's entirely true in academia. You have to pick a research topic that'll pull in grants. You have to teach classes. Again, in industry you can also generally always find something that's interesting -- either within the company [if it's big enough] or by moving to a different company.
iii) "I'm not selling my soul to the devil by working for a big, evil corporation": Short of working for an organization that makes weapons [and possibly Wall Street], working in industry won't really taint your eternal soul either. Ok, maybe if you're responsible for writing the advertising jingles for toilet paper, you'll have occasional doubts about whether this is the most productive way of spending your life, but is that really that much worse than yet another paper analyzing the postmodern symbolism inherent in the relationship between Beowulf and Grendel ?
iv) "I'll make important scientific contributions that will change the world !": Uhm. Yeah. Maybe. If you're Bob Langer. But you're probably not, so your chances of actually doing something that will impact other people are probably higher if you're working in industry than in academia. I mean, how many people will actually care about that paper on "DNA polymerase processivity in Arabidopsis under conditions of amino acid starvation and high-intensity X-ray bombardment" that you spent a year of your life on ? No, really, be honest with yourself.
v) "I can't be fired or downsized once I have tenure !": Chances are, if you're good/lucky enough to get tenure, you're good enough to never be out of work in industry either. And in industry, you still have more job security, year-to-year, than adjunct faculty seem to have.

A lot of this analysis [certainly the compensation bit] assumes you're in an engineering/scientific field. Maybe academia makes more sense if you're not, but somehow I doubt that.

So: don't play. There are easier ways to make a decent living and still have a job you like.

Saturday, March 19, 2005

Final rotation

As of about a week and a half ago, my rotation with Tom Knight [or TK, as he’s generally known around here] is over and I’ve moved on to my next rotation. Executive summary of my rotation with TK: he rocks ! The man seems to have detailed knowledge about everything related to prokaryotes [ie bacteria and such] and, I suspect, quite a bit about higher organisms too. What makes this all the more impressive is that he was a “pure” computer scientist for 20+ years and then basically retrained himself to become a biologist. Now that’s what you call mental flexibility ...

I originally had grandiose plans to do some work on an idea I had about programmed cell-cell communication, but after actually working through the details on paper, I realized that a) it was going to require a huge amount of lab work b) I’d be lucky if it worked at all and c) the system I was thinking about wasn’t really as powerful as I’d originally hoped [but if anybody has ideas about how to get in vivo non-templated synthesis of DNA, let me know :-)]. In other words, it wasn’t something that made sense to try during a 2-month rotation while also taking classes. So I went to TK and offered to be his monkey if he needed any experimental work done – I figured whatever I ended up doing for him would be educational since I still barely know the difference between the blunt and the sharp ends of a pipette, so to speak.

And was it ever educational: since Tom only has 3 students and isn’t teaching any classes, he’s around a lot of the time and still does all his own lab work. Couple that with the aforementioned prodigious knowledge and willingness to impart it [and answer dumb questions] and you get what I had: one-on-one instruction from somebody who really knows what he’s doing, which is priceless. Unfortunately I didn’t get a chance to work with him as much as I would have liked, but, let me repeat: TK rocks !

My next rotation is with Prof. David Gifford, who is one of the instructors in my “Computational Functional Genomics” class. His group comes up with all kinds of smart algorithms to answer the “You’ve got a mountain of experimental data. What is it telling you ?” question that I alluded to in an earlier post – lots of machine learning-type stuff. Conveniently enough, I can reuse the work I do in this rotation for my class project in his class and the TA for that class [in which I’ve “understood trainstation” a few times] is also in his lab, so I’ll be able to pester him more easily [Yea, verily, he shall come to dread the sound of my rough feet slouching towards his office door ... or something like that].

My rotation/class project is to try to [re]discover protein-DNA binding motifs based on ChIP-chip binding data. Running this through the degobbledygookifier produces this explanation: in order for a gene to be expressed [ie to make a protein], a bunch of other molecules have to bind to [ie “land on and stick to”] the DNA. The places on the DNA where these other molecules bind are something like “landing strips” where these molecules can land and stick firmly. These landing strips tend to have common features, just like most landing strips have common features like lights, asphalt etc, and the common features are called “motifs”. Based on this idea of common features, people have looked for motifs by basically looking for [relatively short] areas of DNA that seem to have things in common eg they all have the sequence “GGGTGCA”. However, one of the problem with finding these motifs just by looking at the DNA is that the fact that something looks like a motif [ie the molecules could land there] doesn’t mean it’s actually a place where the molecules do land. So, biologists being the smart people they are, they came up with a way to actually trap the molecules after they land, kind of a molecular flypaper. So now you can look for motifs by trapping the molecules after they’ve landed and then seeing whether the places they’ve landed have anything in common. If they do, well, son, you’ve just found yourself a motif ! [Sort of]

So the plan for my rotation is to find some of these motifs using some data Dr.Gifford’s group has for yeast DNA and then, depending on how well things go, maybe for human or mouse DNA. Along the way, it looks like I’ll get a chance to dig into the code behind a popular motif-finding tool called MEME and hopefully finally really understand how an Expectation Maximization [EM] algorithm works. We’ve talked a lot about EM algorithms in class but I currently feel a bit like Justice Potter Stewart felt about pornography: “I can’t define it, but I know it when I see it”. Hopefully at the end of this rotation, I’ll not only be able to define it but also create my own ;-)

The Skunkfather

Sometimes, a blocked nose is a good thing to have. This includes instances when a skunk has just vented its displeasure in the vicinity of your abode, which is what happened last night around 1 am. Both Christina and I happened to be semi-awake and she got a whiff of it first and it pretty much woke her up all the way. Now, bear in mind that our apartment is on the third floor and we didn’t have any windows open, so, assuming that we’re not dealing with a monkey skunk [or skunk monkey], the smell must have diffused up 3 floors and through some pretty small cracks and yet was still strong enough to cause Christina to want to cut off her nose. I didn’t actually really smell it because I still have a cold, but even I could tell it was a mighty discharge indeed. Ten hours later, the smell still lingers, which causes me to conclude that this wasn't just any skunk, but rather The Skunkfather, who occupies a position in the skunk pantheon of deities similar to the one occupied by Odin All-Father in Norse mythology. In any case, while Christina was gasping for air, we had a brief conversation on skunk-generated topics. Some highlights:

- Christina thinks that there must be some way of extracting energy from something that smelly and she’s probably right. I wonder how hard it would be to get funding for a project designed to extract energy from skunk juice. I guess there’s the cow dung-methane precedent for trying to extract good things from bad smells.
- Somehow, we got on to the topic of spider silk and the fact that people are trying to get goats to produce spider silk in their milk [that link, btw, is courtesy of "Capricorn Publications -- The largest circulation goat magazine in the world". What an awesome tag line.]. That brought to mind the image of Spidergoat, Spiderman’s animal sidekick.
- Another good point from Christina: if a cat gets sprayed by a skunk, it has to lick it off. That sounds like just about the worst thing in the world.
- I was wondering what the effect of the smell was on the puppy that our neighbors have. As in, do dogs ever smell something and think “Daaaaammmnnn, what the hell is that awful %#$%#$ smell ?”. Once again, Christina provided insight: dogs seek out dead things and roll in them, so it’s probably fair to say that if there are smells they dislike, they’re not the same ones that humans dislike. [She was on a roll. Like I said, the smell –really- woke her up ...]

Some random biological facts about smell:
- Smell receptors are instances of what are called “G-protein coupled receptors” (aka GPCRs). GPCRs are one of the three largest classes of receptors in humans, and most/many drugs target GPCRs.
- Smell desensitization: in theory, persistent exposure to a smell makes you less sensitive to it due to something called "receptor desensitization". Basically, the GPCRs that detect the odorant molecules stop responding as strongly as they initially did. This happens in a few ways [for example, the GPCR is "endocytosed" ie sucked into the cell so it can't react with any more smelly stuff], but they're all triggered by detecting the smell in the first place. In other words, it's one of the many examples of negative feedback mechanisms in biological systems: one of the chemicals produced in a particular set of reactions ends up stopping the reactions. Unfortunately, there wasn't a whole lot of "receptor desensitization" happening for Christina last night.
- Here's a nice article on the chemical components of skunk spray of various skunk species. Also includes helpful hints about how to defunkify pets that have been caught in the toxic emission. Personally, if one of our cats got sprayed, I'd wait a bit before detoxifying it [while keeping it outside] just to see what kind of face it made when it tried to lick itself.

Wednesday, March 16, 2005

Some days, partial credit is all you can hope for

I just finished my Cell Biology midterm; last week, I had my Molecular Biology midterm. Extrapolating based on these two data points [and you can always draw a perfectly straight line through two points =)], my takeaways are:

- It's a totally different way of thinking than I'm used to. The majority of both exams consisted of questions of the type "Here is some experimental data. What does it tell you ?", which is a very different tack from the [more straightforward] "Here's a problem, go solve it"-style of engineering-type exams. On the one hand, that allows you to be somewhat more creative when answering the question, but on the other hand, you don't have the safety net of mathematical logic to stop you from saying something that isn't logically coherent. There are no externally-imposed consistency checks, it's all up to you to make sure you don't leave any loopholes and don't draw unwarranted conclusions. It also left me feeling vaguely unsatisfied with a lot of my answers because I wasn't sure that they were "totally" correct.

- I have a huge problem writing something down when I can see holes in it. This very strong desire for completeness/correctness on my part was first pointed out to me by Christina when we were in Costa Rica: I refused to say anything in Spanish unless I was totally sure it was correct and so I spent lots of time piecing together sentences by consulting the dictionary etc. By the time I got one sentence together, Christina had usually already had a full "conversation" and figured out what we wanted to know. What this meant for my two biology exams is that I had to really force myself to write down answers that I knew weren't fully correct [but would hopefully get me a few pity points] instead of just leaving the question totally unanswered.

- Interpreting experimental data is hard. Probably all the more so when you've only slept a total of about 6-7 hours in the last two nights because of raging insomnia and as a result have a stuffed-up nose, a sore throat and trying to logically think through a problem feels like wading through thigh-high mud.

Very, very ready for spring break. Not that we're going anywhere, but a break from getting information stuffed down my throat is sorely needed.

Tuesday, March 15, 2005

Redesigning the curriculum

When I was choosing between PhD programs, one of the things that appealed to me about the PhD program I ended up in was its flexibility, both in terms of the huge number of professors affiliated with the program [any of whom I could, at least in theory, choose to work with/for] and the fact that there are really only two specific required courses and you get to pick the rest in almost whatever manner you choose. Now, you can interpret the lack of a larger number of required courses in at least a couple of ways: it could mean that the program is aimed at allowing people maximum freedom in how they structure their education [a good thing] or that it really doesn't have a core set of knowledge that everybody who comes out of it will possess [a bad thing, to some extent].

After thinking about the "core knowledge" issue and the name of the PhD program ["Computational and Systems Biology"] a bit more, I now wonder whether it wouldn't make sense to add 2 specific courses to the required course list: "Systems Biology" and "Computational Functional Genomics". With the addition of those two courses to the "Foundations of Computational and Systems Biology" course that's already required, I think the program would end up with a pretty coherent computational core that covers a lot of the bases that fall under the "computational and systems biology" monicker:

- The "Foundations" course introduces what were [some of] the first applications of computational methods to biological problems: sequence analysis, of DNA, RNA and protein sequences. This is a set of methods that don't really tell you much/anything about the "systems level", but they continue to be instrumental in helping to provide pieces of the puzzle.

- "Systems Biology" is a good overview of a set of methods for getting to a mechanistic system-level understanding, namely modeling a set of interacting entities either deterministically [via ODEs and PDEs] or stochastically [the Gillespie algorithm etc]. These techniques allow you to build and test "mechanistic" models, in which you can specify precisely how components of the system interact and see what effect changing a set of interactions has on the behaviour of the system as a whole.

- "Computational Functional Genomics", while ostensibly about, well, genomics, serves as a good introduction to [a Bayesian approach to] answering the general question "You have a big pile of experimental data. How do you go about extracting the underlying patterns that produced this data ?". This leads you to a different kind of systems-level of understanding: you don't necessarily know how all the components interact, but you can extract overall patterns of behavior and influence [eg "when X goes up, Y goes down and Z stays the same"] and what probability your conclusions have of being correct. That sort of knowledge can then help you build a mechanistic model.

So, there you have it -- my prescription for redesigning a PhD program in which I haven't even finished the first year, a contribution to the "complex problem, simple solution" paradigm.

Country cat comes to the big city

[Since I can't sleep, I figured I'd kill some time and maybe put myself to sleep by writing an entry that falls solidly into the "cute things my cat did" category. Tune out now unless you too have nothing better to do.]

The integration of our new cat into the household is proceeding reasonably smoothly so far. We still haven't really settled on a name for him -- we alternate between "Sandeep", "Sandy", "The Sandman" and "Country" [for reasons that will become clear later].

Sandy appears to have been weaned at a really early age, because he's so affectionate it's almost like he's a dog in a cat's body -- he follows you around from room to room, has no objection to being picked up and held for extended periods of time, starts purring pretty much as soon as you look at him etc. Of course, maybe we've just been conditioned not to expect any of that by Sushi and Mooshi who act like they're doing you a favor by letting you pet them. It's a nice change to have an appreciative cat, a somewhat similar sentiment to Larry David's statement "
It's not every day that you get to be affectionate around something German, it just doesn't happen that often. "

The Sandman is also rather "country" in a Will Ferrell-in-"Elf" sort of way -- he climbs onto [and falls off] everything, is insanely curious and not at all shy. He demonstrated that last part this evening by getting into his litter box and proceeding to do his business while Christina was in the process of cleaning the litter box. Usually cats want a bit of privacy for that sort of thing. Not this boy. Needless to say, Christina was a bit taken aback. Again, this sort of childish enthusiasm is in sharp contrast to our other two cats, who are kind of like jaded Romans and adopt the "Another orgy ? How dreadfully boring ... could we maybe feed another slave to the lions ?" approach to just about everything, including their food -- they refuse to eat the same flavor of cat food several days in a row, or a can of opened cat food that's been in the refrigerator, so we have to make sure we have enough variety for them. Sandeep just hoovers it all up -- old, new, warm, cold, fish flavor, chicken flavor ...

The most interesting thing to observe has been how Sushi and Mooshi react to this new addition to the household. So far, we've kept them mostly separate so they can get used to each other's smell prior to being put in physical proximity. We've put him and Sushi [the more mellow of the two] together to see what happens and it confirmed my long-standing opinion: Sushi is a punk. Instead of taking the "This is my house and don't you forget it" approach, he miaows in a tone that conveys "Why are you torturing me ?" and backs away from Sandy as quickly as he can, sometimes flat out turning around and running away [despite the fact that he weighs at least 1.5 times as much as Sandy and is just generally bigger]. Sandy, in his naive way, of course thinks Sushi wants to play and chases him, which just makes Sushi more desperate to get away ... mayhem ensues, usually ending with Sushi backed into a corner and us taking Sandy away. Mooshi, on the other hand, isn't taking shit from anybody [as shown by the fact that he put Christina into the hospital a few months ago] -- when he sees Sandy, he hisses, growls like a dog and basically conveys "Come get some, if you want some -- there's nothing but space and opportunity between us". So far, we haven't let Sandy take him up on that [he doesn't seem to understand that hissing means "I don't like you very much"], but we'll have to just let them work out their differences [in a supervised environment, of course :-)] sometime soon.

Friday, March 11, 2005

Bam ! Kapow ! Splat !

I've always been a bit of a comic book fan. Over the last few months, I've managed to get through a lot of the "mainstream classics", like The Dark Knight Returns, The Long Halloween, The Phoenix Saga, World Without A Superman, Return of Superman etc. [It's a bit embarrassing to put comics on your Christmas wish list when you're an adult, but I did it anyway =)].

I'm now moving a bit further afield and have started reading Neil Gaiman's "Sandman" series. I've gotten through the first two volumes and have to say that a) they kick ass and b) Neil Gaiman has a pretty twisted imagination -- the "24 Hours" story in "Preludes and Nocturnes" is one of the most disturbing things I've ever read. I've also started reading "Maus", which deals with the Holocaust, based on the stories of a survivor -- the Jews are mice, the Nazis are cats.

So, if you're ever wondering what to get me for a birthday/Christmas present, comics are a good bet, hint, hint ;-)

A fool and his money are soon parted

Sometimes, just to see what insanity is going on in the Manhattan housing market, I read pieces from the Real Estate section of the New York Times. There's an article today about how co-op boards are requiring buyers to have a ridiculous amount of liquid assets, beyond the down payment, in order to approve their bids. While the whole article just demonstrates that [in my opinion] you have to be slightly mentally deficient to live in Manhattan, here's my favorite quote from it:

Ms. Kleier said she is working with a client in his 20's who is shopping for a condo in the $4 million range because he doesn't have the liquid assets to buy a co-op. He is typical of clients who are "making several million a year but also spending several million a year and just haven't gotten ahead and accumulated the liquid assets that they need," she said. For young people with that kind of money, she said, these condos are stepping stones to the life they eventually envision.

Never mind the "in his 20's and shopping for a $4 million condo" bit. What I want to know is -- how exactly do you spend several million a year, especially when you're in your 20s and don't have a family ? Even while earning, at a guess, 10-30 times less than this young man, my MS income supported Christina and me, plus lots of toys, comfortably. I can't even begin to imagine what I would have done with millions of dollars a year. And I don't fully buy the "Well, it's Manhattan, everything is crazy expensive" defense either; sure, that counts for some, but, c'mon, it's not 10-30 times more expensive than Seattle. This guy must be using $100 bills to light cigarettes.

The only conclusion I can come to is: money, like youth, is wasted on the young. Or at least people in their 20's; I, at the ripe old age of 30, would definitely know what to do with it ;-)

Tuesday, March 08, 2005

Small bits, totally unjoined

Random stuff that's been floating around in my head:

Ah-nuhld: I think Arnold Schwarzenegger's life is, in many ways, a fairy tale. The man won 5 Mr.Universe and 7 Mr.Olympia titles, came to the US with little more than the [admittedly very large] muscles on his back, became a major action movie star, married a Kennedy and then ended up as the governor of California ... not your run-of-the-mill life, exactly. Of course, there are also some not-so-shiny parts about him [as described here]. In any case, it's the marrying-a-Kennedy bit that got me to thinking. In general, I think it's fair to say that being a Kennedy, or marrying one, increases your chances of you and/or your spouse meeting with an unfortunate accident by a factor of about, oh, 230 billion. Roughly speaking. [There's actually a book about this.]

Here's the thing, though: if ever there was a man able to withstand the Kennedy Curse, it's Arnold. The man has had to fight aliens, destroy a couple later-model killer androids, fight Batman [ok, fine, he lost that fight], been exposed to vacuum on Mars, defeat evil sorcerers ... and that's not even mentioning all the times he's had to deal with "normal" ordnance ie run-of-the-mill guns, rockets, knives etc. In short, the man is indestructible. Bring it on, Kennedys !

Los pantalones del gato con queso: We've acquired a new cat. He's a stray that Christina has been feeding for a while now and that we've been unable to find a home for. Christina has been pushing for us to adopt him for a while, but I was resistant on the grounds that having 2 cats is fine, but once you get to 3, you're in danger of becoming a crazy cat person, the type that ends up on "Animal Cops" because there are 200 cats living in your house etc. In any case, I finally gave in to the badgering and we've adopted him.

I now have the "honor" of naming him and I'm trying to figure out what moniker to give him. The tricky thing about naming an animal is that there are really very few boundaries -- it's not like you have to worry about the cat not liking the name, or getting teased at school. And that lack of restrictions is somewhat problematic because I find myself coming up with increasingly ridiculous names. The short list so far is:

- "Pantalones": this comes from my predilection towards nonsense Spanish sentences [like the one above], which tend to be permutations of the Spanish words for "cat","milk", "cheese", "pants" and "red", mainly because those are pretty much my entire Spanish vocabulary. In any case, for some reason I think calling a cat "Pantalones" would be funny.
- "Three": this is how we referred to him while he was still a stray, as in "Cat Number Three".
- P.Kitty: fairly self-explanatory, I think.
- Sandeep: hey, why not ? See what I mean about lack of boundaries ?
- Luscious: this one is kind of hard to explain. You'd have to see the "Krazyee-Eyez Killa" episode of "Curb Your Enthusiasm" to even begin to understand.
- Raekwon: another entry from the "Hey, why not ?" line of reasoning.

CSBi Demographics: The 4 CSBi students [including me] that make up the entire first year of the CSB program have a somewhat unusual demographic for a science/engineering program in that I'm the only male, and I'm black. When I first heard about this, I made a joke along the lines of "Hmm, I guess they're covering their diversity basis for a few years with the first set of students they admit", not because I think any of us are underqualified for the program, but just because the demographics seemed rather odd.

I've now had the chance to meet the CSBi interviewees for the next year and, well, the numbers are a bit more "normal": of 12-14 people, there are 2 women and of the men, 80% or so are white males.
Not that I think that my tongue-in-cheek remark is totally true, but it did make me chuckle a bit.

And, as final bit, here's a quote I found rather funny, encountered while googling the title of this post: "XML is like violence -- if it doesn't solve your problem, you're not using enough of it", courtesy of

Friday, March 04, 2005

Keeping the restroom assembly line rolling

The NY Times has a story about the increasing pressure in some quarters for gender-neutral restrooms, to make life easier for transgendered individuals. While I have no objection to this in principle, I do have a slightly tongue-in-cheek objection in practice: I really like the fact that the line for men's restrooms moves much more quickly, and is much shorter, than that for women's restrooms. If, in the process of "de-gendering" bathrooms, you take away the urinals and men-only restrictions that allow the higher "throughput" in men's restrooms, well, then we'd all have to wait in line a long time and I'm against that. 'Coz when I gotta go, I gotta go ;-)

[I actually remember reading something in the New Scientist years ago about a study that claimed/showed that women take some factor of time X longer in public restrooms than men, leading to a queue for women's restrooms that's X-squared as long as that for men's restrooms. Can't find that article anywhere online, though.]

Thursday, March 03, 2005

Update on the "Distinguished Engineers" bit

According to this MicrosoftWatch article, MarkL is really unhappy with Microsoft. The article has a link to a post on what's supposed to be MarkL's blog where he tears into MS, but that post has been pulled and the blog is empty. Curioser and curioser.

A proposed nomenclature change

One of the less fun parts of being in a management role [for me at least] was that I always had to try to put a positive spin on things that, in a frank discussion with friends, I would probably have characterized as "sucking", for lack of a better word. One of my favorite [sarcastic] remarks was this attempted Jedi mind trick phrase: "It's not a problem, it's an opportunity". Or, as Uncle Max reminds us, a "probortunity". [How appropriate that Uncle Max is a monkey.]

In keeping with this, I would like to propose a nomenclature change: problem sets at MIT should no longer be called problem sets. Rather, they should be called opportunity sets. And MIT would thus truly be the land of opportunity.

Wednesday, March 02, 2005

Even Distinguished Engineers get the blues

It appears that Google has managed to lure away one of Microsoft's top engineers, Mark Lucovsky. Mark is [was ?] one of the few, the proud, the chosen: Microsoft's Distinguished Engineers [aka "DE"s]. DEs have an almost-mythical status at MS; they're pretty much a law unto themselves and can [within reason] do pretty much whatever they want. Getting into a technical argument with one of them may result in your co-workers finding nothing but a smoking pile of ashes in your office after you've been smitten by the DE lightning bolt -- Dave Cutler especially has been known to reach out and b!tchslap people in email when he disagrees with them. I've personally had the ... opportunity, shall we say, to get into a debate about the technical merits of a particular solution with a [different] DE and, while I didn't get totally pummeled, it was a lot like going into a gunfight armed with a [small] knife. Of course, at the time I didn't know that all I had was a knife so I charged in full-bore.

In any case, what struck me about this was: if a DE, who must have been getting paid a truckload of money [not that he needed it], and could pretty much have had his pick of any project he wanted at MS, decided to move to Google, they must have something pretty damn cool for him to work on. And MS, by contrast, apparently didn't. That's gotta worry somebody, somewhere at MS.