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A Fictional Compression Metric Moves Into the Real World
Tekla Perry (3034735) writes The 'Weissman Score' — created for HBO's "Silicon Valley" to add dramatic flair to the show's race to build the best compression algorithm — creates a single score by considering both the compression ratio and the compression speed. While it was created for a TV show, it does really work, and it's quickly migrating into academia. Computer science and engineering students will begin to encounter the Weissman Score in the classroom this fall."
Niggers. Coons. Jigaboos. Porchmonkeys. Yard apes.
That is all.
From 2 days ago
A "combined score" for speed and ratio is useless, as that relation is not linear.
Most ACs are not even worth the keystrokes to insult them. Be generically insulted by this and ignored otherwise.
I thought I read an article the other day that said their algorithm seemed plausible on the surface but would eventually would begin to fall apart?
The so-called Weissman score is just proportional to (compression ratio)/log(time to compress).
I guess the idea is that twice as much compression is always twice as good, while increases in time become less significant if you're already taking a long time. For example, taking a day to compress is much worse than taking an hour, but taking 24 days to compress is only somewhat worse than taking one day since you're talking offline/parallel processing anyway.
The log() seems kind of an arbitrary choice, but whatever. It's no better or worse than any other made-up metric, as long as you're not taking it too seriously.
"They were pure niggers." – Noam Chomsky
Somebody should explain that to Professor Tsachy Weissman and Ph.D student Vinith Misra, who specifically stated it doesn't really work, and then school them on it then.
Guns don't kill people; Physics kills people! - John Lithgow as Dick Solomon on Third Rock From The Sun
From the article:
Misra came up with a formula
An algorithm can compress data quickly and fit it into a small number of bytes, but that doesn't mean what comes out the other end is recognizable. Without adding a weighting for lossiness, this "Weissman Score" has no merit whatsoever. Using the "Weissman Score", MP3 is always better than FLAC, and that's completely untrue for anyone who cares about audio.
Additionally, new generations of video encoders would arguably be "worse" under this weighting system compared to older generations, as improvements in video encoding are currently rather incremental, generally with massive speed penalties as they require significantly higher numbers of CPU cycles to burn through the algorithms required to compress efficiently at low bitrates while maintaining very little distortion/lossiness.
Again, this score doesn't matter because in the end, a compression algorithm is only as good as what comes out the other side.
Not only does it fail to account for loss or distortion, but also fails to consider the time to decompress. If a compression algorithm with a high Weissman score is applied to a video, it is useless if it cannot be decompressed fast enough to show the video at an appropriate frame rate.
Two scores would be useful, one for compression_time:size and decompression_time:size, since for many applications the latter is more important in compress-once consume-many applications.
IIRC, the Drake equation was also a 'spitball' solution whipped off the cuff to address an inconvenient interviewer question. Subsequent tweaks have made it as accurate and reliable as when it was first spat out upon the world - and about as useless.
Show About Self-Absorbed Assholes Who Think Their Stupid Ideas Are The Bees Knees Gains Popularity By Making Their Stupid Idea Sound Like Its The Bees Knees
Somebody should explain that to Professor Tsachy Weissman and Ph.D student Vinith Misra, who specifically stated it doesn't really work, and then school them on it then.
The compression algorithm is fictional and does not work. That is what your linked article discusses.
This is about the Weissman Score.
No metric is adequate for all purposes. This one is adequate for the task it was designed for, and is adequate for some other purposes as well. That's the best that can be expected of any tool. Always use the appropriate tools for the task at hand, of course.
"Convictions are more dangerous enemies of truth than lies."
Where's our TV show?
Why am I reminded of this Mexican ad when I read this?
https://www.youtube.com/watch?v=vqgSO8_cRio
The posts here reflect ZERO entrepreneurship. This apparent lack of respect, curiosity and ambision is why most of you will be relegated to the "workforce" for the rest of your lives. You may be happy, but there are some folks who has to create "your jobs".
I'd love to be in a community of open-minded peers, but of course this is /.. We have ego's to protect. Failures to avoid. Etc.
Weak.
Sounds a bit like the f1 measure used in classification systems, where the F-score is the harmonic mean of precision and recall. (where trying to higher precision yields lower recall and vice-versa) ;-)
however, I'm wondering how stable this Weissman score is. Compression algorithms might not all perform O(n) where n is size of data to compress.
Or it may actually give a very high score to something that doesn't compress at all.
public byte[] compress( byte[] input) { return input;}
I bet this gets a high Weissman score
Oh boy. A useless metric!
Compression ratio: Sure. But the problem is, it's possible to increase compression ratio by "losing" data. So you can obtain a high ratio, but the images as rendered will be blurry/damaged.
Compression Speed: This is just as dumb since compression speed is partially a function of the compression ratio, partially a function of the efficiency of the algorithm and partially a function of the amount of "grunt power" hardware you throw at it. So one portion of this is a nebulous "hardware norm" factor that can be gamed. The other is a function of the other factor (compression ratio) which can ALSO be gamed (and creates a bias towards lossy compression).
Basically something with a high Weismann number would be extremely lossy compression on high power hardware. Which basically negates the point of high resolution viewing, as any idiot can reduce a 1920x1080 frame to 19px by 11px, and then compress it. I can already take precompressed (and lossy) JPEG files, resample down to 19x11, then back up to 1920x1080. I can wind up reducing a 930K file down to 40K (basically a 95+% savings). And the image is completely indecipherable.
Take a look at an original image versus the same image on the above-described UCCT (UltraCrappyCompressionTechique).
http://cox-supergroups.com/The...
The above image is a PNG to prevent further compression artifacts from creeping into the sample.
The top portion of the image is the original 930K JPEG file.
The bottom portion is the resampled 40K JPEG file.
Chas - The one, the only.
THANK GOD!!!
Given that only a subset of Slashdot users are HBO subscribers, how is this relevant?
I want to delete my account but Slashdot doesn't allow it.
The reason there's no single metric available is because bandwidth isn't constant.
I'll and solve for a "best algorithm" given some different bandwidths, ignoring decompression time.
F1(X): 14 + X*(1- 0.00001%)
F2(X): 20 + X*(1-15%)
F3(X): 29*60*60 + X*(1-15.1%)
solving pairwise:
F1(40 seconds) = F2(40 seconds)
F1(8 days) = F3(8 days)
F2(3.31 years) = F3(3.31 years)
If the file can be transferred in 7 seconds, algorithm 1 is the clear winner (23.6% faster than algorithm 2, and nearly 5000x faster than algorithm 3).
If the file can be transferred in 7 days, algorithm 2 is the clear winner (17.6% faster than algorithm 1, and 20.2% faster than algorithm 3).
If the file can be transferred in 7 years, algorithm 3 is a marginal winner (0.062% faster than algorithm 2, and it's 17.8% faster than algorithm 1); also note that 0.062% is in the 30-40 hours range (you can get different answers depending on the number of seconds you use to compute 7 years).
I couldn't watch the first episode. Quit maybe 10 minutes into it. Does anyone here actually enjoy the show and think it's any good?