Nerdy Perry

Your tiny accountant is ready to complete your taxes. He’s disappointed that you didn’t prepare your documents! He ponders how to proceed. There’s no use just sitting on the information he already has. Finally, he leaps to action! Something seems askew. Time to crunch some numbers… Success! You’re getting a refund 🙂 Lefteris and I are both big, big nerds, so it was only a matter of time before something like this happened. By the way, I’m doing everything I can not to *constantly* post photos of my (supremely adorable) son; instead I’m limiting myself only to extra-special shoots. In[…]

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I am such a nerd

…that for my birthday last weekend, we went to Geneva solely for the purpose of taking a tour of CERN. I’m very excited to process these photos, but just haven’t had the time yet – so here’s a preview of my full nerdiness! Speaking of nerdiness, and CERN, this is one of my favorite videos of all time. I would like to hang out with these people. So much more to come from Geneva and CERN!

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Learning the first 1,000 prime numbers

I have: A (possibly unhealthy) love of numbers A photographic memory A brain that likes to think about about patterns …so, I’ve decided to see if I can learn the first 1,000 primes by printing them out and keeping them on my dresser for awhile. I want to see how well I can do at this without actually studying. I don’t intend to memorize them in a “recite the first 1,000 primes” kind of way–I would rather be able to answer “is this number prime?” up to 7,919 (the 1,000th prime). Well really, I should be able to answer it[…]

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I’ve just taken my geekiness to a new level

…by getting the joke in this xkcd comic: http://xkcd.com/599/. Thank you, The Man Who Loved Only Numbers! Currently in my reading rotation–it’s the bigraphy of Hungarian mathematician Paul Erdös. He was an author of about a bazillion papers and proofs and was known for a few things in particular: 1, being a great collaborator, 2, the elegance of his thinking, and 3, his itinerant lifestyle–he traveled all the time and would often show up on the doorsteps of fellow mathematicians with the pronouncement, “My brain is open.” He’d stay long enough to work on a problem together and then move[…]

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What I’ve just read: The Predictors

The Predictors: How a Band of Maverick Physicists Used Chaos Theory to Trade Their Way to a Fortune on Wall Street, by Thomas Bass, managed to combine my excitement about two recent books I’ve read, Chaos and The Black Swan. Two things: One, I was really glad to realize that several of the predictive models I built for a recent analytics client followed some of the same methods of looking for patterns and of building models that would evolve automatically over time. Two, how can I invest with these guys? Because this is my style.

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Number spirals

Why didn’t I know about this sooner? Number spirals are beautiful and fascinating. I love it that there is still so much to discover these ancient concepts called numbers. I mean–there’s no higher math required for number spirals whatsoever, just simple arithmetic, drawing, and spatial thinking. I keep coming back to something from the end of Chaos: Making a New Science: the idea that patterns are so eager to express themselves that they’ll do so even if you don’t know what you’re looking for, or don’t even really know where to look. I mean, look at that thing…it’s beautiful… It[…]

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What I’m reading: The Black Swan

In addition to a steady diet of fashion magazines, I’m reading a lot of math stuff. (Obviously.) This book by Nassim Nicholas Taleb, The Black Swan: The Impact of the Highly Improbable, is sort of a cross between math, probability, philosophy, biology, and history. The thing that’s getting me about this is the description of two different types of systems: one where things cluster in the middle, and one where they cluster at the outer edges (the author refers to them as “Mediocristan” and “Extremistan”). The second reminds me of the Lorenz attractor–a system where values cluster around two values[…]

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Bayesian search theory rulz

Bayesian search theory uses the work of mathematician Thomas Bayes to find lost objects–particularly objects lost at sea. For example, submarines. What’s great about this method is that it works with hunches. In the search for the USS Scorpion, John Craven used Bayesian search theory, along with Vegas-style rounds of betting by a group of experienced submariners, to construct a theory about where the Scorpion could be found. The key elements of Bayesian search theory are: Creating a variety of hypotheses, and probabilities, about where the object might be Determining the likelihood of finding the object in each of those[…]

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