Tim Bray’s high-tech monastic cell

Nicholas Carr has an interesting post entitled simply Clutter. The post begins by discussing Tim Bray’s vision of a sort of high-tech monastic cell and moves into an explanation of why electronic books are fundamentally different from paper books.

Tim Bray has gotten rid of his CD cases and is now talking about getting rid of his books. From Nicholas Carr’s blog post:

He [Tim Bray] has a sense that removing the “clutter” of his books, along with his other media artifacts, will turn his home into a secular version of a “monastic cell”: “I dream of a mostly-empty room, brilliantly lit, the outside visible from inside. The chief furnishings would be a few well-loved faces and voices because it’s about people not things.” He is quick to add, though, that it will be a monastic cell outfitted with the latest data-processing technologies. Networked computers will “bring the universe of words and sounds and pictures to hand on demand. But not get dusty or pile up in corners.”

(Tim Bray’s ideal of a secular monastery  made me think of musician John Michael Talbot, a real monk living in a real monastery. I heard someone describe Talbot’s living quarters as a sparse cell with a fantastic sound system.)

Carr is dubious that Bray can achieve his goal by digitizing his books. Paper books are more conducive to the serenity Bray desires.

The irony in Bray’s vision of a bookless monastic cell is that it was the printed book itself that brought the ethic of the monastery — the ethic of deep attentiveness, of contemplativeness, of singlemindedness — to the general public.

I find Tim Bray’s ideal attractive, but I would selectively digitize books. For example, I would be fine converting my copy of The Python Cookbook to digital form. But I cannot imagine reading Will Durant’s Story of Civilization from a screen.

Related posts

Dave Brubeck mass

Judging from the comments on previous posts, it seems a good number of Dave Brubeck fans read this blog. Everyone familiar with Dave Brubeck knows about Take Five from his album Time Out.

But I wonder how many know about his album “To Hope! A Celebration.”

The album is a Roman Catholic mass containing beautiful mixture of classical and jazz music. It features the Cathedral Choral Society Chorus & Orchestra as well as the Dave Brubeck Quartet. It was recorded live at Washington National Cathedral on June 12, 1995.

According to Wikipedia, Brubeck was not a Catholic when the mass was commissioned but joined the Catholic church shortly after the piece was finished.

More Dave Brubeck posts

Status report questions

The latest .NET Rocks podcast interviews Pat Hynds on why projects fail. Toward the end of his interview he mentions a simple template for status reports.

  1. What did you work on?
  2. What did you get done?
  3. What did you do that you didn’t anticipate having to do?
  4. What did you plan to do that you didn’t get done?
  5. What do you plan to do?
  6. What do you need from others?

When I started managing a group of programmers, I’d focus on #1 and #2. But in some ways #3 is the most important question. That question can alert you to a major time sink that’s not include in your project estimates. That question can let you know of problems beyond an individual developer’s ability to resolve. That question that can tell you it’s time to buy something you were planning on building yourself.

Bayesian statistics is misnamed

I’m teaching an introduction to Bayesian statistics. My first thought was to start with Bayes theorem, as many introductions do. But this isn’t the right starting point. Bayes’ theorem is an indispensable tool for Bayesian statistics, but it is not the foundational principle. The foundational principle of Bayesian statistics is the decision to represent uncertainty by probabilities. Unknown parameters have probability distributions that represent the uncertainty in our knowledge of their values.

Once you decide to use probabilities to express parameter uncertainty, you inevitably run into the need for Bayes theorem to work with these probabilities. Bayes theorem is applied constantly in Bayesian statistics, and that is why the field takes its name from the theorem’s author, Reverend Thomas Bayes (1702-1761). But “Bayesian” doesn’t describe Bayesian statistics quite the same way that “Frequentist” described frequentist statistics. The term “frequentist” gets to the heart of how frequentist statistics interprets probability. But “Bayesian” refers to a Bayes theorem, a computational tool for carrying out probability calculations in Bayesian statistics. If frequentist statistics were analogously named, it might be called “Bernoullian statistics” after Jacob Bernoulli’s law of large numbers.

The term “Bayesian” statistics might imply that frequentist statisticians dispute Bayes’ theorem. That is not the case. Bayes’ theorem is a simple mathematical result. What people dispute is the interpretation of the probabilities that Bayesians want to stick into Bayes’ theorem.

I don’t have a better name for Bayesian statistics. Even if I did, the name “Bayesian” is firmly established. It’s certainly easier to say “Bayesian statistics” than to say “that school of statistics that represents uncertainty in unknown parameters by probabilities,” even though the latter is accurate.

More Bayesian posts

Captured by Somali pirates without knowing it

I was captured by Somali pirates a couple weeks ago, or so some friends thought.

Captain Richard Phillips

When I went to the library this evening, one of the librarians stopped me as soon as I walked in. She said “John! Wait, I’ve got to show you something.” She brought me a newspaper clipping with a photo of Richard Phillips, captain of the Maersk Alabama who was rescued by U. S. Navy SEAL snipers earlier this week.

She told me that she and her grandmother were watching the news the other day and thought that she saw my face on the TV. She hadn’t seen me at the library in a while and was certain that I had been captured by pirates.

After I told my wife about the story, she said other people had commented on how much I resemble Captain Phillips.

Now the librarian calls me “Captain.”

A note to new subscribers

Thank you for subscribing to my blog. I wanted to say a little about the blog for those of you who have just subscribed recently.

I post a little more than one article a day on average. I write about a variety of topics. Here’s a list of some of the most popular posts by category. If a few posts are not your cup of tea, please just ignore these but keep subscribing. I’ll write again soon about the topic that brought you here.

Here’s a list of books mentioned on the blog with links back to the post(s) where they came up.

Here’s my contact info. If you submit a comment and it doesn’t appear in a few hours, please send me a note. (I get thousands of spam comments, and so I filter spam aggressively and sometimes a legitimate comment gets blocked.) I enjoy hearing from you.

Math blog carnivals

It looks as though the Carnival of Mathematics is dead. The Blog Carnival site says “It appears that this carnival is no longer accepting submissions.” I may have had the honor of hosting the last Carnival of Mathematics unless the carnival is resurrected.

But there’s a new carnival in town, one devoted to math education. The fifth edition of the Math Teachers at Play carnival was posted this morning, hosted at Let’s Play Math.

By the way, I also wanted to mention the previous blog post on Let’s Play Math. Denise links to a TED presentation by Robert Lang on origami and math. She pulls out this quote from the talk:

The secret to productivity in so many fields … is letting dead people do your work for you. … take your problem and turn it into a problem that someone else has solved and use their solutions.

Update: According to Jason’s comment below, rumors of the death of Carnival of Mathematics have been greatly exaggerated.

Metabolism and power laws

Bigger animals have more cells than smaller animals. More cells means more cellular metabolism and so more heat produced. How does the amount of heat an animal produces vary with its size? We clearly expect it to go up with size, but does it increase in proportion to volume? Surface area? Something in between?

A first guess would be that metabolism (equivalently, heat produced) goes up in proportion to volume. If cells are all roughly the same size, then number of cells increases proportionately with volume. But heat is dissipated through the surface. Surface area increases in proportion to the square of length but volume increases in proportion to the cube of length. That means the ratio of surface area to volume decreases as overall size increases. The surface area to volume ratio for an elephant is much smaller than it is for a mouse. If an elephant’s metabolism per unit volume were the same as that of a mouse, the elephant’s skin would burn up.

So metabolism cannot be proportional to volume. What about surface area? Here we get into variety and controversy. Many people assume metabolism is proportional to surface area based on the argument above. This idea was first proposed by Max Rubner in 1883. Others emphasize data that supports the theory that suggests metabolism is proportional to surface area.

In the 1930’s, Max Kleiber proposed that metabolism increases according to body mass raised to the power 3/4. (I’ve been a little sloppy here using body mass and volume interchangeably. Body mass is more accurate, though to first approximation animals have uniform density.) If metabolism were proportional to volume, the exponent would be 1. If it were proportional to surface area, the exponent would be 2/3. But Kleiber’s law says it’s somewhere in between, namely 3/4. The image below comes from a paper by Kleiber from 1947.

Kleiber M. (1947). Body size and metabolic rate. Physiological Reviews 27: 511-541.

The graph shows that on a log-log plot, the metabolism rate versus body mass for a large variety of animals has slope approximately 3/4.

So why the exponent 3/4? There is a theoretical explanation called the metabolic scaling theory proposed by Geoffrey West, Brian Enquist, and James Brown. Metabolic scaling theory says that circulatory systems and other networks are fractal-like because this is the most efficient way to serve an animal’s physiological needs. To quote Enquist:

Although living things occupy a three-dimensional space, their internal physiology and anatomy operate as if they were four-dimensional. … Fractal geometry has literally given life an added dimension.

The fractal theory would explain the power law exponent 3/4 simply: it’s the ratio of the volume dimension to the fractal dimension. However, as I suggested earlier, this theory is controversial. Some biologists dispute Kleiber’s law. Others accept Kleiber’s law as an empirical observation but dispute the theoretical explanation of West, Enquist, and Brown.

To read more about metabolism and power laws, see chapter 17 of Complexity: A Guided Tour.

More power law posts

Intellectual traffic jam

Imagine you’re on a highway with two lanes in each direction. Two cars are traveling side-by-side at exactly the speed limit. No one can pass, and so the cars immediately behind the lead pair go a little slower than the speed limit in order to maintain a safe distance. This process cascades until traffic slows down to a crawl miles behind the pair of cars responsible for the traffic jam.

Something similar can happen in organizations. Suppose the person at the top of a company is afraid to hire anyone smarter than himself. He wants to hire people who are talented, but not quite as talented as he is. If each of his subordinates follows his lead, the result can be a lack of talent at the bottom of the org chart.