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djdyyz | 1 year ago
The sample data compresses poorly, getting down to 4.5 bits per sample easily with very simple first-order difference encoding and an decent Huffman coder.
However, lets assume there is massive cross-correlation between the 1024 channels. For example, in the extreme they are all the same, meaning if we encode 1 channel we get the other 1023. That means a lower limit of 4.5/1024 = about 0.0045 bits per sample, or a compression rate of 2275. Viola!
If data patterns exist and can be found, then more complicated coding algorithms could achieve better compression, or tolerate more variations (i.e. less cross-correlation) between channels.
We may never know unless Neuralink releases a full data set, i.e. 1024 channels at 20KHz and 10 bits for 1 hour. That's a lot of data, but if they want serious analysis they should release serious data.
Finally, enforcing the requirement for lossless compression has no apparent reason. The end result -- correct data to control the cursor and so on -- is the key. Neuralink should allow challengers to submit DATA to a test engine that compares cursor output for noiseless data to results for the submitted data, and reports the match score, and maybe a graph or something. That sort of feedback might allow participants to create a satisfactory lossy compression scheme.
djdyyz|1 year ago
It's 2275X
That's the compression ratio for complete cross correlation. It's (10 bits uncompressed / 4.5 bits compressed on 1 channel) * 1024 channels