I Write Like…

Statistical analyzer that takes a sample of your (or anyone’s) writing and claims to match it based on similarity to a known author: I Write Like.

I pasted an excerpt from an email I had written a while back, and I got the result “I write like Cory Doctorow”. Really? My emails read like Doctorow? This sounded too good to be true, so I dug up my recipe for mushroom-peanut lasagna and pasted that in, and I got the result “I write like Mario Puzo”!

I swear this thing was written by a wise guy.

Fourth of July Fireworks [Pictures]

Fourth of July 2010, at Lafayette / West Lafayette, Indiana. Fireworks seen from the Myers footbridge. Fireworks launched from the Brown Street overlook.

(Mouse over images to enlarge).

You know the arXiv. Here’s the snarXiv.

As its name indicates, snarXiv is a parody of arXiv. You can test your bogus-title detection skills at snarXiv vs arXiv. I didn’t get over 60-65% myself (after some 15-20 trials); I could detect the really blatant fakes (“Towards some general examples”), but really my performance is only modestly better than a coin-flip. In my own defense, I’m not a physicist, leave alone a high-energy theoretical physicist. How did you do?

When Thermodynamics Goes Meta

While running a simulated annealing program, lowering the simulated temperature too slowly will make the CPU temperature rise too much. That’s thermodynamics.

Law of computer thermodynamics

The other lesson in here, particularly for systems engineers, is: “The system always kicks back”. (Paraphrased from John Gall’s satirical takedown of systems-thinking in his three Systemantics books, which are a little over the top but nevertheless recommended).

Sustainable Energy – without the hot air

I’m currently reading through Sustainable Energy – without the hot air by David J.C. MacKay, FRS, which I recommend to anyone interested in energy or energy policy. I’m particularly impressed by the graphs and diagrams in the book, both for the laboriously-collected data they represent and for their power to convey important points quickly and clearly. (Example).

The visual imagery evoked by the prose is powerful too: in a section discussing the merits (and lack thereof) of having a large number of people make a small saving each, here is what MacKay has to say:

The “if-everyone” multiplying machine is a bad thing because it deflects people’s attention towards 25 million minnows instead of 25 million sharks. The mantra “Little changes can make a big difference” is bunkum, when applied to climate change and power. [link]


Citation: David J.C. MacKay. Sustainable Energy – without the hot air. UIT Cambridge, 2008. ISBN 978-0-9544529-3-3. Available free online from www.withouthotair.com.

The Dunbar Number

This post is a collection of links about the existence and consequences of the Dunbar number.


Dunbar’s number is a theoretical cognitive limit to the number of people with whom one can maintain stable social relationships. No precise value has been proposed for Dunbar’s number, but a commonly cited approximation is 150.

The Wall Street Journal:

there is reason to believe that the social-networking sites will enable their users to burst past Dunbar’s number for friends, just as humans have developed and harnessed technology to surpass their physical limits on speed, strength and the ability to process information.

The Economist:

What mainly goes up [in the number of Facebook contacts], therefore, is not the core network but the number of casual contacts that people track more passively. This corroborates Dr Marsden’s ideas about core networks, since even those Facebook users with the most friends communicate only with a relatively small number of them.

The Monkeysphere:

So how many monkeys would you have to own before you couldn’t remember their names? At what point, in your mind, do your beloved pets become just a faceless sea of monkey? Even though each one is every bit the monkey Slappy was, there’s a certain point where you will no longer really care if one of them dies.

Zhou, Sornette, Hill & Dunbar:

Using fractal analysis, we identify with high statistical confidence a discrete hierarchy of group sizes with a preferred scaling ratio close to 3: rather than a single or a continuous spectrum of group sizes, humans spontaneously form groups of preferred sizes organized in a geometrical series approximating 3, 9, 27,…

Bruce Schneier:

The smallest, three to five, is a “clique”: the number of people from whom you would seek help in times of severe emotional distress. The twelve to 20 group is the “sympathy group”: people with which you have special ties. After that, 30 to 50 is the typical size of hunter-gatherer overnight camps, generally drawn from the same pool of 150 people. No matter what size company you work for, there are only about 150 people you consider to be “co-workers.” The 500-person group is the “megaband,” and the 1,500-person group is the “tribe.” Fifteen hundred is roughly the number of faces we can put names to, and the typical size of a hunter-gatherer society.