Jamie Collins is a Ph.D. candidate in computer science at Stanford University and the founding president of the Public Communication for Researchers initiative.
The 1990s were a chaotic era. Crystal Pepsi graced our shelves, the Macarena dominated dance floors, and Tickle Me Elmo was all the rage. Yet, what stands out most vividly in my memory from that time is the painfully sluggish nature of the Internet. Whenever I needed to email a PowerPoint for school, I’d power up the modem, endure the symphony of beeps and static, initiate the upload, and then head off to dinner. By the time I returned, I hoped my solitary email had finally sent.
However, if I was pressed for time, I had a nifty trick: file compression, often referred to as “zipping.” Software like WinZip could take an 80 MB PowerPoint and, after a brief moment of work, shrink it down to a ZIP file that contained the same presentation, now reduced to a mere one-third of its original size.
Initially, I brushed this magic trick aside. But the more I pondered it, the more it felt like a form of sorcery. The file was indeed smaller, yet no actual data disappeared because the recipient could effortlessly recreate the original. It was like placing a 6-foot package into a 2-foot box for shipping, only to retrieve the full-sized package at the destination. So where did all that data go in the meantime?
Extracting the Air
The package metaphor offers a potential explanation. Imagine if the package contained something inflatable, like a large exercise ball. Instead of shipping it whole, you could deflate the ball, tuck it into a smaller box, and include instructions for re-inflation on the other side. Yet, this analogy has limitations: while deflating a ball may not cause distress, I would be extremely unhappy if WinZip started omitting parts of my presentation that I had painstakingly crafted over two days. What’s the “air” that can be removed from a PowerPoint file?
Computers utilize similar techniques to those we use as humans to navigate our world. For example, when memorizing a complex piece of music, like Ravel’s “Boléro,” you’d quickly realize that the snare drum part contains an overwhelming amount of repetition—specifically, 4,050 drumbeats. This might seem daunting until you recognize that the entire part is just one sequence of 24 beats, repeated endlessly. In psychological terms, you only need to remember one unit of information rather than every single note. Instead of memorizing each beat individually, you simplify it to “chunk chunk chunk…”
This is precisely how file compression operates. Just as a musician identifies patterns within a composition, a compression program seeks out repetitive chunks within a file and replaces them with shorthand notations. For instance, if my school project included the classic tongue-twister, “How much wood could a woodchuck chuck if a woodchuck could chuck wood?” (I had unique interests as a child, okay?), the software would recognize the repeated words “wood,” “could,” and “chuck.” It would replace them with placeholders—let’s say “X,” “Y,” and “Z.” These redundant elements are the “air” extracted from the document.
Of course, the receiving computer needs to understand what these shorthand notations mean, so the compression program also saves a table defining each shorthand—akin to instructions for re-inflating that exercise ball. This table is crucial for reconstructing the original document.
Redundancy and Its Implications
The concept of redundancy illuminates the enigma of data compression while also indicating further avenues for reducing file sizes. Our tendency to share massive media files like songs and videos is made feasible by inventive methods to eliminate even more redundancy. However, this raises another question: If so much redundancy exists, why do my original PowerPoint files seem excessively bloated? Why not just store a 30-megabyte version instead of an 80-megabyte one?
The creators of PowerPoint were well aware of the potential for compression, but file size wasn’t their only concern. Imagine if every time you wanted to use your deflated exercise ball, you had to pump it up first and then deflate it afterward. While this method would conserve space, it would be quite inconvenient. We face a similar dilemma with cognitive resources: while you could calculate how many cups are in a pint each time you cook, it’s often easier just to memorize it. Similarly, if your computer had to decompress a file each time it accessed it, the user experience would revert to the frustrating days of 56K modems. Retaining some redundancy means more data, but it also results in a far more user-friendly experience.
Just as in human cognition, redundancy presents a trade-off for computers. Too little redundancy leads to constant re-calculation of the same information, while excessive redundancy can bog down your internet connection, flooding it with data.
Fortunately, we usually strike a balance. It’s thanks to redundancy and compression that I can download a copy of The Shawshank Redemption and watch it smoothly on my laptop. Oh, and let’s not forget Braveheart, The Matrix, and Schindler’s List. Perhaps the ‘90s weren’t so terrible after all.
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Summary
In summary, the intricacies of data compression reveal how redundancy can be both beneficial and burdensome in our digital lives. By employing clever techniques, computers can shrink files without losing essential information, much like our brains simplify complex data. Achieving the right balance between redundancy and efficiency is crucial for a seamless user experience, enabling us to enjoy media and navigate digital tasks with ease.
Keyphrase: data compression
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