This is actually an insightful question.
The practical answer is no. There is an unimaginable amount of possible 3:30 minute vidoes—far more than the number of possible 4kb or even 40kb files.
To be fair, most of those possible vidoes are just noise. We don't have to be able to compress those because people don't care if one video of noise is different from another. We also don't have to reconstruct the video perfectly: as long as it looks more or less the same, the audience is happy. (This is called "lossy compression".)
But even with these caveats, there is no realistic method for compressing realistic 3:30 minute videos that well on a computer. We likely can't do all that much more than current compression algorithms without a different set of tradeoffs. (Like being better at some videos but worse at others.)
That said, a big part of how compression works is by relying on information already present when decompressing. This demo relies on having a particular kind of chip with certain capabilities (ie a CPU and a GPU) and presumably some standard library functions... etc.
How well could we "compress" videos if we had more information available when decompressing? Here's a fun thought experiment: what if we had a model of a human mind? We could then feed in a pretty sparse description and have the model fill in the details in a natural intuitive way. It would be very lossy, but the results would be compelling.
And you know what? That's a decent mental model of how speech works! If you just look at information content, spoken words are not very dense. But if I describe a scene you can imagine it almost as if you're seeing a video. This works because we both have the same sort of brain as well as shared experiences and intentions.
You can think of speech as incredibly effective—but also rather lossy—compression.
The practical answer is no. There is an unimaginable amount of possible 3:30 minute vidoes—far more than the number of possible 4kb or even 40kb files.
To be fair, most of those possible vidoes are just noise. We don't have to be able to compress those because people don't care if one video of noise is different from another. We also don't have to reconstruct the video perfectly: as long as it looks more or less the same, the audience is happy. (This is called "lossy compression".)
But even with these caveats, there is no realistic method for compressing realistic 3:30 minute videos that well on a computer. We likely can't do all that much more than current compression algorithms without a different set of tradeoffs. (Like being better at some videos but worse at others.)
That said, a big part of how compression works is by relying on information already present when decompressing. This demo relies on having a particular kind of chip with certain capabilities (ie a CPU and a GPU) and presumably some standard library functions... etc.
How well could we "compress" videos if we had more information available when decompressing? Here's a fun thought experiment: what if we had a model of a human mind? We could then feed in a pretty sparse description and have the model fill in the details in a natural intuitive way. It would be very lossy, but the results would be compelling.
And you know what? That's a decent mental model of how speech works! If you just look at information content, spoken words are not very dense. But if I describe a scene you can imagine it almost as if you're seeing a video. This works because we both have the same sort of brain as well as shared experiences and intentions.
You can think of speech as incredibly effective—but also rather lossy—compression.