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Neuralink Compression Challenge

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Re: Neuralink Compression Challenge

#21
post #18
post #12

why should it be lossless when presumably there is a lot of noise you don't really need to preserve

exactly, when you look at the data it looks entirely like noise without any signal, why transmit that in the first place. And why losslessly.

That's the thing. First principles thinking would say to look at that 200Mb/s and figure out what you can lose, before compressing.

Re: Neuralink Compression Challenge

#23
200X is possible.

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.

Re: Neuralink Compression Challenge

#24
post #23

200X is possible. 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 p…

Sorry, corrected an error.

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

Re: Neuralink Compression Challenge

#26
Apparently, someone solved it and achieved an 1187:1 compression ratio. These are the results:

All recordings were successfully compressed. Original size (bytes): 146,800,526 Compressed size (bytes): 123,624 Compression ratio: 1187.47

The eval.sh script was downloaded, and the files were decode and encode without loss, as verified using the "diff" function.

What do you think? Is this true?

https://www.linkedin.com/pulse/neuralink-compression-challen... context: https://www.youtube.com/watch?v=X5hsQ6zbKIo

Re: Neuralink Compression Challenge

#27
Analyzing the data it becomes clear that the A/D used by Neuralink is defective, i.e. very poor accuracy. The A/D introduces a huge amount of distortion, which in practice manifests as noise.

Until this A/D linearity problem is fixed, there is no point pursuing compression schemes. The data is so badly mangled it makes it pretty near impossible to find patterns.

Re: Neuralink Compression Challenge

#28
post #26

Apparently, someone solved it and achieved an 1187:1 compression ratio. These are the results: All recordings were successfully compressed. Original size (bytes): 146,800,526 Compressed size (bytes): 123,624 Compression ratio: 1187.47 The eval.sh script was downloaded, and the files were decode and encode without loss, as verified using the "diff" function. What do you think? Is this true? https://www.linkedin.com/pu…

Bogus. But a nice spoof.

Re: Neuralink Compression Challenge

#29
post #27

Analyzing the data it becomes clear that the A/D used by Neuralink is defective, i.e. very poor accuracy. The A/D introduces a huge amount of distortion, which in practice manifests as noise. Until this A/D linearity problem is fixed, there is no point pursuing compression schemes. The data is so badly mangled it makes it pretty near impossible to find patterns.

It's actually amazing that Neuralink can use this badly distorted data. I imagine that fixing the A/D would improve their results dramatically -- lower latency and higher precision. Why Neuralink has continued work with such an obvious hardware defect is a serious question. Do they actually analyze the A/D to make sure its working properly?

Re: Neuralink Compression Challenge

#30
post #28
post #26

Apparently, someone solved it and achieved an 1187:1 compression ratio. These are the results: All recordings were successfully compressed. Original size (bytes): 146,800,526 Compressed size (bytes): 123,624 Compression ratio: 1187.47 The eval.sh script was downloaded, and the files were decode and encode without loss, as verified using the "diff" function. What do you think? Is this true? https://www.linkedin.com/pu…

Bogus. But a nice spoof.

In the video, it’s clear that the results were downloaded from the Neuralink website, no errors occurred, and the results are displayed correctly. Could you specify why you believe it’s Bogus?
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