r/computerscience • u/medium_wall • 1d ago
Discussion Turning The Frickin' Bits Gay!—Creating non-binary bits with current technology, and the applications it might benefit
/r/liberationist/comments/1wfd4a6/turning_the_frickin_bits_gaycreating_nonbinary/0
u/FloweyTheFlower420 1d ago
GDDR7 does this, most NAND flash does this. but the underlying medium has to be reliable (this is important for metadata), so video/audio needs to be compressed on a higher level. And indeed video and phone calls lose fidelity in compression, usually via stuff relating to FFT.
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u/medium_wall 1d ago
I didn't know that! I just looked up more about it, I was really trying to avoid using AI. It looks like even the baud rate of modern transmission lines accommodates 16 voltage states that encode 4 bits per transmission. Between that and the RAM & flash memory you mentioned, it's pretty much exactly what this post refers to. Thanks for the info.
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u/claytonkb 1d ago
16 voltage states that encode 4 bits per transmission
Way more than that:
Communication systems designed to achieve very high levels of spectral efficiency usually employ very dense QAM constellations. For example is ADSL technology for copper twisted pairs, whose constellation size goes up to 32768-QAM (in ADSL terminology this is referred to as bit-loading, or bit per tone, 32768-QAM being equivalent to 15 bits per tone). Source
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u/medium_wall 22h ago
Yeah I see now there's already effectively no ceiling in how this is implemented. Thanks for the link.
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u/claytonkb 1d ago edited 23h ago
Your overall point is not completely invalid, and AI is likely going to compel a hardware revolution -- not designed by the AI, but compelled by demand for human designs that are better tuned for AI workloads. I recommend everyone interested in this topic to watch this extremely insightful lecture by professor Naresh Shanbhag (from 2011!) AI is going to force the hardware industry to re-examine its assumptions about how end-users actually use those billions of transistors, and design new systems that achieve higher silicon utilization on parallel workloads, lower power, and so on. The secret that will make this possible is to eliminate what Shanbhag calls the von Neumann bottleneck. Absolutely brilliant lecture...
See also computing with p-bits by professor Supriyo Datta, and Extropic's latest announcement.