Transcendental Generalization

The phenomenon of lock-in is known by business academics, but few seem to realize how pervasive it is. It is understood to apply to customer-vendor relationships, but it is extensible to economic relationships of all kinds: when a relationship produces some kind of mutual benefit, both sides begin to depend on it. The cost of breaking or changing the relationship is allowed to rise, and they become locked in to it. Both parties engage in supply chain optimization, consciously or unconsciously. As they attempt to minimize their (perceived) costs and maximize their (perceived) benefits, some of the relationship’s benefits may erode.

My favorite example is the modern American food supply chain. In pre-modern times, successful delivery of food was an unsolved problem, leading to starvation and malnutrition. As supply chains grew, they succeeded in reducing (but not eliminating) these problems. In doing so, participants in the supply chain (farmers, transporters, and grocers) successfully pursued important optimizations, trading natural taste and nutritional value in favor of sweetness, appearance and shelf-life.

Unfortunately, the supply chain became optimized for the efficient delivery of sugar, which maximizes sweetness and has a long shelf-life. Indeed, sugar can now be gotten for free. In recent times, due to this optimization of the supply chain, obesity is an epidemic, and it is in fact difficult and expensive to find and purchase fruits, vegetables, and meats that have the same taste and complete nutrition as their pre-modern ancestors.

This article from NPR illustrates lock-in and food supply chain optimization.

Greg Hughes posted a very interesting video on his blog. It is a presentation from SIGGRAPH on novel ways to re-size an image. Normally, an image is simply scaled: every nth pixel is removed, and this uniformly alters the image size. It can also be cropped, which results in complete loss of information contained in rectangular regions of the image.

The SIGGRAPH presentation proposes a third way. The importance of certain pixel paths (from top to bottom or left to right) is determined. The least important paths eliminated as and when the image is shrunk.

Many years ago, I invented a technology that used the same principle on text (US Patent #6,172,685). To present text in a smaller space, it assigned importance to words and eliminated less important words. The visual impact was not quite as dramatic, but it was interesting to see the “gist” of the text preserved and communicated in far fewer words.

Avidan and Shamir had to find some way to measure the importance of pixel paths. Similarly, I had to find some way to measure the importance of words. At the time, I was immersed in the study of information retrieval, which provided solutions like tf-idf. However, such solutions completely ignored the meaning of the words. My technology used text that had been parsed into grammatical structures. The subject (word or phrase) and verb (word or phrase) of each sentence could be treated as most important. Adjectives and adjective phrases and prepositions and prepositional phrases could be treated as less important. The less important words could then be eliminated, and a useful summary of the text could be presented in fewer words.

As far as technology to successfully and accurately parse the text into grammatical structures, I left that to some one else. I demonstrated the technology with text that had been manually parsed.

Avidan and Shamir addressed a similar problem: pixel paths that went through faces were more important than any automated algorithm would reveal. They showed a tool to manually circumscribe faces and assign paramount importance to those pixels. They also mentioned automatic face recognition algorithms could be used.

I got up at 3:00 AM yesterday to view the lunar eclipse. It was interesting to view with the naked eye as well as through a telescope. National Geographic had a very nice infographic on the event.

In high school, I had learned to touch-type, and as an avid computer user, I got pretty good at typing fast. Soon after I started my first job out of school, a co-worker described to me how the standard QWERTY layout was specifically designed to slow down the typist, while the Dvorak layout was optimized for speed. It became a challenge between us to learn the Dvorak layout.

Our workstations were XWindows-based, and I wrote a program to re-map the keyboard. (Soon, I discovered that a built-in program, with the right configuration file, achieved the same effect far more easily.)

It took me about a month to learn the new layout. Every morning, I would map the keyboard to Dvorak, and type by consciously thinking about the fingering for each letter. My typing was slow and error-prone. To keep myself from getting completely stuck, I actually put stickers on the keys for the Dvorak layout. After a period of time, I would grow frustrated and switch back to the QWERTY layout. But, that period of time grew longer as the weeks went by. Eventually, I could go the whole day in Dvorak layout. I also found myself typing significantly faster. Today, I can type with both layouts, but find Dvorak faster and more comfortable.

I was fortunate that the new operating systems continued to support alternative keyboard layouts, so I was never far from a Dvorak keyboard.

I later discovered two additional benefits of the Dvorak layout.

• It reduces repetitive stress injury by requiring less motion from the typist
• It has (slight) security and privacy benefits: people can’t tell what I am typing by watching my fingers. I read an article in CIO magazine saying Berkeley researchers can piece together what you are typing from the sound of your keyboard, but I doubt their method will work on me.

While learning Dvorak, I might have benefited from the Optimus Maximus keyboard. Cool idea, but why is it completely flat? Even my old Commodore 64 keyboard was sculptured for easier typing:

Apple introduced the hinged Adjustable Keyboard allowing a more natural typing posture. Microsoft introduced its Natural Keyboard for the same reason.

Why are modern keyboards returning to the flat style? It is, I believe, the old mistake of allowing function to follow form.