The 1990s were a challenging era in many ways. There were unusual products like Crystal Pepsi, catchy dances such as the Macarena, and let’s not forget the craze around Tickle Me Elmo. However, one of the most exasperating aspects of that decade was the painfully slow Internet. Whenever I needed to send a PowerPoint presentation for school, I would connect the modem, endure the familiar beeping sounds, initiate the upload, and often head off for dinner, hoping my email would send by the time I returned.
In urgent situations, I had a little trick to speed things up: file compression, better known as “zipping.” Programs like WinZip can take an 80 MB PowerPoint file, work its magic, and shrink it down to a ZIP file that retains the original content but is now only one-third the size.
Initially, I thought little of this process, but the more I pondered it, the more it felt like a form of sorcery. The file had decreased in size, yet no actual data had vanished; the recipient could still reconstruct the original presentation. It was akin to fitting a 6-foot package into a 2-foot box for shipping, only to have it reemerge intact on the other side. So, where did all that data go during transit?
Eliminating Redundant Information
The package analogy provides a glimpse into the answer. It’s reasonable to think that a package could shrink if it contained something inflatable—imagine a large exercise ball. Rather than send it fully inflated, you could deflate it and pack it into a smaller box, including instructions for reinflation upon arrival. However, this comparison only gets us so far: while deflating a ball may not bother anyone, I would be quite upset if WinZip started removing bits from my meticulously crafted presentation. What’s the “air” that can be extracted from a PowerPoint file?
Computers utilize strategies similar to those we humans use to process information. Consider a scenario where a person must memorize a great deal of data, like a snare drummer performing Ravel’s “Boléro.” This piece is notable for its repetitive drumbeats—4,050 in total. While that’s a lot to remember, the snare part is almost painfully redundant. It consists of a single sequence of 24 beats, repeated continuously. Psychologically, this means you only need to remember one unit of information. Rather than memorizing every note, you can simplify it to “chunk chunk chunk…”
This method mirrors how your computer compresses files. Just as a musician identifies structure in music, a compression program seeks out repeating segments within a file and condenses them into shorthand. For instance, if my school project included the phrase, “How much wood could a woodchuck chuck if a woodchuck could chuck wood?” (I was an odd child), the program would recognize that “wood,” “could,” and “chuck” repeat, replacing them with symbols like “X,” “Y,” and “Z.” These redundant segments are the “air” that gets removed from the document.
The receiving computer needs to decode these shortcuts, so the compression program also saves a symbol table that defines each shorthand—similar to those instructions for reinflating the ball. This table is crucial for reconstructing the original file.
The Balance of Redundancy and Convenience
While redundancy allows for compression, it also raises a question: why are original PowerPoint files so verbose? Why keep an 80 MB file when 30 MB suffices? The creators of PowerPoint were fully aware that compression was possible, but size wasn’t their only concern. Imagine if you had to inflate your exercise ball every time you wanted to use it and deflate it afterward. It would certainly save space, but it would also be highly inconvenient. This trade-off is akin to how we manage cognitive resources; while you could calculate the number of cups in a pint each time you cook, it’s more practical to memorize it.
Similarly, if your computer had to decompress files every time it accessed them, it would feel like those agonizing 56K modem days. Retaining some redundancy means more data, but it also translates to a lot less hassle.
For both computers and humans, redundancy is a delicate balance. Too little redundancy forces us to keep reprocessing information, while too much can overwhelm our internet connections with massive media files. Fortunately, we often strike that balance right. It’s thanks to both redundancy and compression that I can smoothly download movies like Shawshank Redemption and enjoy them on my laptop along with other classics. Perhaps the ’90s weren’t so terrible after all.
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Summary:
This article explores the concept of data compression, using analogies and examples to illustrate how redundancy in information allows for file size reduction without losing data. It discusses the balance between convenience and efficiency in both computational processes and human cognition, ultimately highlighting the importance of redundancy in our digital experiences.