Alex Thompson is a computer science Ph.D. candidate at Carnegie Mellon University and the founding president of the Public Communication for Researchers initiative.
The 1990s were an interesting era. We had phenomena like Crystal Pepsi and the Macarena, not to mention the obsession with Tickle Me Elmo. Yet, one of the most irritating aspects of that decade was the painfully slow Internet. Whenever I needed to email a PowerPoint for school, I’d connect the modem, endure the beeps and chirps, initiate the upload, and then head off to dinner. By the time I returned, I might have managed to send that one email.
However, I had a secret weapon for urgent situations: file compression, often referred to as “zipping.” Applications like WinZip would take an 80 MB PowerPoint and compress it down to about one-third of its original size without losing any data. The first time I encountered this phenomenon, I thought little of it. But the more I contemplated it, the more it appeared to be magic. The file was smaller, yet the recipient could still recreate the original. It’s akin to fitting a 6-foot package into a 2-foot box and retrieving it intact on the other side. What happens to all that data in the meantime?
Removing the Excess Air
The package analogy offers a glimpse into the mechanics of compression. Imagine packing something inflatable, like a large exercise ball. Instead of shipping it fully inflated, you could deflate it and place it in a smaller box, with a note instructing the recipient to re-inflate it. Yet this analogy only scratches the surface: while the air in the ball is expendable, I’d be quite upset if WinZip started trimming parts of my meticulously crafted presentation. So what is the “air” that can be extracted from a PowerPoint file?
To achieve this compression, computers employ strategies similar to those humans use to make sense of information. Consider, for instance, a musician memorizing a complex piece of music. Imagine you’re the snare drummer for Ravel’s “Boléro,” which features 4,050 drumbeats. That’s a lot to memorize! However, the snare part is largely redundant, repeating the same 24-beat sequence throughout. Instead of remembering every note, you can simplify it to a single chunk: “chunk chunk chunk…”
This mirrors how compression software works. Just as a musician finds structure, a compression program identifies repetitive elements in a file and replaces them with shorthand. For example, if my presentation contained the tongue-twister, “How much wood could a woodchuck chuck if a woodchuck could chuck wood?” (yes, I was a quirky kid), the program would recognize the recurring words and substitute them with placeholders—let’s say “X,” “Y,” and “Z.” These redundant segments are the “air” squeezed out of the document.
Naturally, the receiving computer needs to understand these shorthand terms, so the compression software saves a symbol table that clarifies what each shorthand means. This is akin to providing instructions for reinflating the ball; it guides the receiving computer in reconstructing the original document.
Redundancy reveals the secret behind data compression and suggests various methods to further minimize data size. Our tendency to share large media files, like music and videos, relies heavily on sophisticated techniques designed to eliminate even more redundancy. However, we must ask: if so much redundancy exists, why do original PowerPoint files seem so unnecessarily large?
The creators of PowerPoint knew they could compress files, but they faced more than just size. Imagine needing to inflate your exercise ball every time you wanted to use it—while efficient in terms of space, it would be quite inconvenient. We often encounter similar trade-offs concerning convenience and efficiency. Instead of recalculating how many cups are in a pint every time you cook, it’s easier to memorize it. Likewise, if a computer had to decompress files constantly, every task would feel reminiscent of those slow 56K modem days. Retaining some redundancy means more data but significantly less hassle.
For both humans and computers, redundancy is a balancing act. Insufficient redundancy leads to constant re-evaluation of information, while too much can overwhelm our internet connections with heavy data loads. Thankfully, we usually strike the right balance—thanks to both redundancy and compression, I can effortlessly download movies like “Shawshank Redemption” and enjoy them on my laptop. Perhaps the ‘90s weren’t so bad after all.
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Summary
The article explores the concept of data compression, explaining how redundancy allows for the reduction of file sizes without losing information. It compares the process to inflating and deflating an exercise ball and discusses the balance between convenience and efficiency in both human cognition and computer processing.