resources
visualizations
presentations
lunch break
Distractions and amusements, with a sandwich and coffee.
fun + amusement
Dummer — Like Nothing Else
The Hummer font is a slightly modified Antique Olive Nord. The Like Nothing Else tag line is Trade Gothic. Both have character widths increased to 110-120% and individually adjusted kerning. Get the Illustrator CS5 file for both logos.
Download high-resolution images.
This project might give you the impression that I don't like Hummers. You'd be right.
update
The Maurauder. Over 25,000 lb — five times what an H3 weighs. Enough said.
Dummer - Like Nothing Else
Hummers are a cultural equivalent of a toxic warning label and have the same effect on me as bug spray on mosquitoes.
I am not the first one to satirize this automotive aberration, so there's some hope.
GM's advertisement images require no modification for the satire, which makes it all that much better.
I could have just as well used the Lincoln Navigator or Cadillac Escalade, but they don't embody the superlative like the Hummer.
The Hummer brand proved itself to be aesthetically, rationally and economically unsustainable and collapsed after a failed attempt to sell it to China. There continues to be a robust market for used Hummers. Let the farce continue.
I'm hated
It delights me that this project produced my first hate mail.
Only a Canadian and a liberal professor, would set up a website as ludicrous as Dummer.com.
Extremely Dumb!
If you are going to make fun of a Hummer, what about a Dodge powerwagon that obtains less miles per gallon? Many other vehicles on the road with worse mileage. But, I guess your location, and your profession tells it all.
Have a great day in BC...
Doug
I want to meet Doug and give him a hug for adding another dimension to this project.
I'm loved
The images got picked up by the New York Times laughlines blog, which drew a couple of fan mails.
Excellent work. One of the best ad parodies I've seen.
Gil
I don't normally write people to tell them I think their web work is good/bad, but I had to write and just say I think these are fucking brilliant. Should probably look into getting them made into billboards.
Dave
But neither made me feel as good as Doug's email.
Dummer Images
news + thoughts
`k` index: a weightlighting and Crossfit performance measure
Similar to the `h` index in publishing, the `k` index is a measure of fitness performance.
To achieve a `k` index for a movement you must perform `k` unbroken reps at `k`% 1RM.
The expected value for the `k` index is probably somewhere in the range of `k = 26` to `k=35`, with higher values progressively more difficult to achieve.
In my `k` index introduction article I provide detailed explanation, rep scheme table and WOD example.
Dark Matter of the English Language—the unwords
I've applied the char-rnn recurrent neural network to generate new words, names of drugs and countries.
The effect is intriguing and facetious—yes, those are real words.
But these are not: necronology, abobionalism, gabdologist, and nonerify.
These places only exist in the mind: Conchar and Pobacia, Hzuuland, New Kain, Rabibus and Megee Islands, Sentip and Sitina, Sinistan and Urzenia.
And these are the imaginary afflictions of the imagination: ictophobia, myconomascophobia, and talmatomania.
And these, of the body: ophalosis, icabulosis, mediatopathy and bellotalgia.
Want to name your baby? Or someone else's baby? Try Ginavietta Xilly Anganelel or Ferandulde Hommanloco Kictortick.
When taking new therapeutics, never mix salivac and labromine. And don't forget that abadarone is best taken on an empty stomach.
And nothing increases the chance of getting that grant funded than proposing the study of a new –ome! We really need someone to looking into the femome and manome.
Dark Matter of the Genome—the nullomers
An exploration of things that are missing in the human genome. The nullomers.
Julia Herold, Stefan Kurtz and Robert Giegerich. Efficient computation of absent words in genomic sequences. BMC Bioinformatics (2008) 9:167
Clustering
Clustering finds patterns in data—whether they are there or not.We've already seen how data can be grouped into classes in our series on classifiers. In this column, we look at how data can be grouped by similarity in an unsupervised way.
We look at two common clustering approaches: `k`-means and hierarchical clustering. All clustering methods share the same approach: they first calculate similarity and then use it to group objects into clusters. The details of the methods, and outputs, vary widely.
Altman, N. & Krzywinski, M. (2017) Points of Significance: Clustering. Nature Methods 14:545–546.
Background reading
Lever, J., Krzywinski, M. & Altman, N. (2016) Points of Significance: Logistic regression. Nature Methods 13:541-542.
Lever, J., Krzywinski, M. & Altman, N. (2016) Points of Significance: Classifier evaluation. Nature Methods 13:603-604.