Talk:Computer performance by orders of magnitude

Discussion
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1024 and above
The statements here, like "Strong AI in this computing era will probably drive scientific innovation" and "It will be at least of the level of human intelligence" seem overly bombastic given the ammount of uncertainty and debate around strong AI, not to mention the inherent uncertainty in speculating on things so far into the future. I have moderated the wording a bit and added a "dubious" tag until someone can come up with more sources to back up the statements or rewrite it.

Knuthove 02:57, November 2, 2010 (UTC) —Preceding undated comment added 02:57, 2 November 2010 (UTC).

Symbolic Processing in the Brain
Talking about the processing power of the brain is stepping in quicksand. The "graphics processing subsystem" that presents us with a clear image based on raw input is extremely powerful and hasn't yet been fully simulated in a computer, so we can't even use that as a yardstick. The aural processing subsystem is probably almost as complex. But a key difference between human consciousness and the way digital computers work is that the brain thinks in symbols - layers of abstraction above raw data. For example: catching a baseball involves real time processing from the eyes, calculation of the trajectory from that data and motor neuron commands to place the hand in the right place at the right time. Forcing the brain to do simple arithmetic (the forte of a digital computer) is not a simple thing - the brain must abstract the concepts of number, build a virtual symbolic computing engine that simulates the activities of an Arithmetic Processing Unit with stacks, buffers, lookup tables, etc. and then force data through it. The result in real time is as though this virtual engine has a processing speed of something on the order of 100 bits/second - which is not the point (though some fool might claim that this proves how stupid people are). We may manipulate symbolic abstractions slowly but give real time outputs to data that is directly processed. Which is more important? In a survival sense real time processing is paramount. In the appreciation of a theoretical sense symbolic processing comes out ahead.

Mccainre (talk) — Preceding undated comment added 16:40, 18 August 2014 (UTC)

What’s the unit??
It’s not FLOPS, from what I can tell, is it…?

This list is pointless, without a unit! — Preceding unsigned comment added by 85.197.40.14 (talk) 16:49, 19 March 2014 (UTC)

74.98.216.253 (talk) 17:20, 14 January 2017 (UTC) The unit is inverse seconds (hertz) because the quantity being measured is frequency.

Discussion of the scope of the subject matter in the pre-amble
I feel there are too many oversimplified choices made here as to theoreticaly calculations of human-brain capacity. Specifically ref. Ray Kurzweil's speculative calculation dated 1999 for "roughly the hardware-equivalent of the human brain" in the "Exascale" section, and also ref. the focus on the 1997-dated theoretical Matrioshka brain called out in the "Post zettascale" section. Modern supercomputers exist, but they are massively-parallel. Lots of these epic (not EPYC!) chips working together. Please consider bolstering this page with two graphs - one graph showing single-chip performance over time (FLOPs works I guess.. - but memory retrieval time, cache levels and new algorithms, core counts, fast I/O channels - these and I'm sure many more measures, that don't directly pertain to the FLOPs count, should be captured too, maybe in a separate graph). And please add the latest graphics cards then in yet another graph... Graphics cards that pair well with modern AMD/Intel chips and implement vastly-parallel, e.g. n-dimensional matrix multiplication compute capability, over a fast bus. Hope this makes sense. Paid into the fund for this site a few times, I feel this article could and should be strengthened... YaWha (talk) 01:29, 23 August 2023 (UTC)