• “Don’t taze me, bro!” with a Monty Python twist!
• This anywhere.fm player looks pretty awesome
• The food families eat in a week.
• I may have linked to this awesome algorithmic art page before, but fuck, it deserves two links.
• Docking simulator
• Burning man from the top
• Awesome timeline of evolution
• Tree illusion
• God found out!
• I want the airzooka or the megazooka! I want a lot of them! I want airzooka warfare! More airzooka!
• Yay!

The iPhone… she is good for many things, but no so good for the vanity shot. What is nearly impossible is when you try that thing where you hold the camera away from you then point it back at you and take a photo — because there’s no real “button” to push to take the photo, so you can’t really tell if it has been taken or not. Plus I’m finding it difficult to really tell where that little camera eye is pointing.

I just re-read the Kurt Vonnegut short Harrison Bergeron and found that in my first reading, when I was twelve, I had overlooked that the couple watching TV were Harrison’s parents. KV mentions it more than once, so my pubescent mind must have been so regularly addled with lust that I could barely concentrate.

Funny the irony: the sex-thoughts pulsing in my brain had just the same effect as the disruptor bursts sent over the government channels to the headphones worn in the world of Harrison Bergeron. How funny that we are made to read that story at a time in our lives when we are similarly handicapped and therefore unable to fully appreciate the message least of all the similarities.

Thanks to Forrest Young of UNC, my software now is well on its way to being functional. When I feed the program this matrix of flight distances between cities, and have it project that data onto a plane, it gives me this image:

It looks like the US, which is exactly what is supposed to happen. The colors… the colors are for a feature that I’ll talk about later.

I want to take multivariate data and represent it in 2-dimensional Euclidean space while minimizing distortion inherent in such a lossy projection. If there’s something on the web about how to do this, it’s proving difficult to find as there are many keyphrases that may or may not be used on such a page:

• Classical Multidimensional Scaling (There are other, non classical versions, but I’m not a New Coke kind of guy).
• MDS
• CMDS
• Plane Fitting
• Dimension Reduction
• Matrix Approximation
• Matrix Fitting
• 2D Projection
• Singular Value Decomposition
• SVD
• matrix of similarity data

There are probably more. I’ve seen many pay-to-play style sites that will sell you academic articles, but it is difficult to tell if these articles will properly address my needs…

Update: At the end of my rope I thought maybe I could find a local mathematician who could at least help point me in the right direction, so I searched on “site:unc.edu multidimensional scaling” which lead me right to a professor who has some really helpful papers on his site. It’s crazy that the best resource that I’ve found on the web is from a guy right down the street.

• Dubai friggin’ explods in 14 years!
• I don’t know what this helix fucking thing is, but it looks cool.
• Purty
• Seeing this makes me feel better about my domain-buying binges. It’s all about the benjees, baby.
• Pretty awesome picture-zoomy thing.
• Poor man’s 3D. Everyman’s nauseator.
• Yet another place I’d like to go.
• A real anaconda? It was my understanding that they didn’t want none unless you got buns, hun.
• Classic con.
• List of countries by beer consumption per capita.
• Nevermind? Nevermind?
• This is probably one tenth of one percent of all shipped items on that day.
• Manhattan post global-warming.
• A lightweight javascript window. This link is more for me (so I can remember it) than for you. This will happen every once in a hoo.
• Another one: web APIs.

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