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When will computer hardware match the human brain? (1998)

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Re: When will computer hardware match the human brain? (1998)

#31

Post by geysersam »

pulvinar wrote: post #8
smusamashah wrote: post #4

Quote from article At the present rate, computers suitable for humanlike robots will appear in the 2020s. Can the pace be sustained for another three decades? The graph shows no sign of abatement. If anything, it hints that further contractions in time scale are in store. But, one often encounters thoughtful articles by knowledgeable people in the semiconductor industry giving detailed reasons why the decades of phen…

Today we'd include the GPU. If we include supercomputers, we really have to compare total global capacity, which is on the order of 1 million times that of 1997 [0]. That basically fits his trend line. [0]: https://ourworldindata.org/grapher/supercomputer-power-flops

The graph in the article showing computing power per $1000, doesn't that make the comparison to supercomputers misleading?

Re: When will computer hardware match the human brain? (1998)

#32

Post by beautifulfreak »

kolinko wrote: post #5
smusamashah wrote: post #4

Quote from article At the present rate, computers suitable for humanlike robots will appear in the 2020s. Can the pace be sustained for another three decades? The graph shows no sign of abatement. If anything, it hints that further contractions in time scale are in store. But, one often encounters thoughtful articles by knowledgeable people in the semiconductor industry giving detailed reasons why the decades of phen…

M1/M2s are around 2-4 trillion if I’m not mistaken

~2.6 teraflops FP32 (CPU) for the M3 Max.

Re: When will computer hardware match the human brain? (1998)

#33

Post by geysersam »

The estimate for how many operations per second the brain does is quite a wild guess. It starts out very reasonable, estimating the amount of information the eyes feed to the brain. But from there on it's really just a wild guess. We don't know how the brain processes visual input, we don't know what the fundamental unit of processing in the brain is, or if there is one.

Re: When will computer hardware match the human brain? (1998)

#35

Post by FrustratedMonky »

jll29 wrote: post #3

Moravac (in the linked paper): "In both cases, the evidence for an intelligent mind lies in the machine's performance, not its makeup." Do you agree? I'm much less keen to ascribe "intelligence" to large, pretrained language models given that I know how primitive their training regime is compared to a scenario where I might have been "blended" by their ability to "chat" (double quote here since I know ChatGPT and the…

"ChatGPT and the likes do not have a memory"

Can't we consider the context window to be memory?

And eventually wont we have larger and larger context windows, and perhaps even individual training where part of the context window 'conversation' is also fed back into the training data?

Seems like this will come to pass eventually.

Re: When will computer hardware match the human brain? (1998)

#36

Post by ElectronCharge »

visarga wrote: post #25
djokkataja wrote: post #10

Earlier quoted context omitted.

I agree with Moravec. As he points out a bit later on: > Only on the outside, where they can be appreciated as a whole, will the impression of intelligence emerge. A human brain, too, does not exhibit the intelligence under a neurobiologist's microscope that it does participating in a lively conversation. We only have fuzzy definitions of "intelligence", not any essential, unambiguous things we can point to at a minu…

> The intelligence of a system is a measure of its skill-acquisition efficiency over a scope of tasks, concerning priors, experience, and generalization difficulty. (Chollet, 2019, https://arxiv.org/pdf/1911.01547.pdf ) Priors here means how targeted is the model design to the task. Experience means how large is the necessary training set. Generalization difficulty is how hard is the task. So intelligence is defined…

Your final paragraph is a poor definition of human level intelligence.

Yes, learning is an important aspect of human cognition. However, the key factor that humans possess that LLMs will never possess, is the ability to reason logically. That facility is necessary in order to make new discoveries based on prior logical frameworks like math, physics, and computer science.

I believe LLMs are more akin to our subconscious processes like image recognition, or forming a sentence. What’s missing is an executive layer that has one or more streams of consciousness, and which can reason logically with full access to its corpus of knowledge. That would also add the ability for the AI to explain how it reached a particular conclusion.

There are likely other nuances required (motivation etc.) for (super) human AI, but some form of conscious executive is a hard requirement.

Re: When will computer hardware match the human brain? (1998)

#37

Post by thangalin »

2038.

* 86 billion neurons in a brain [1]

* 400 transistors to simulate a synapse [2]

That's 34 trillion, 400 billion transistors to simulate a human brain.

As of 2024, the GB200 Grace Blackwell GPU has 208 billion MOSFETs[3]. In 2023, AMD's MI300A CPU had 146 billion transistors[3]. In 2021, the Versal VP1802 FPGA had 92 billion transistors[3]. Intel projects 1 trillion by 2030; TSMC suggests 200 billion by 2030.

We'll likely have real-time brain analogs by 2064.

(Aside, these are the dates I've used in my hard sci-fi novel. See my profile for details.)

[1]: https://pubmed.ncbi.nlm.nih.gov/19226510/

[2]: https://historyofinformation.com/detail.php?id=3901

[3]: https://en.wikipedia.org/wiki/Transistor_count

Re: When will computer hardware match the human brain? (1998)

#38

Post by almostnormal »

BitwiseFool wrote: post #15
cs702 wrote: post #2

Moravec's plots (from 1998!) are looking more and more like prophecies: https://www.jetpress.org/volume1/power_075.jpg https://www.jetpress.org/volume1/All_things_075.jpg

What I find incredible about the progress of computing power is that there isn't anything that actually makes Moore's law a given. Engineers keep discovering advances in materials science and manufacturing that enable advancements on such a consistent pace. Is this a fluke? Luck? What enables this?

The market does. New stuff needs to be sold every year, and needs to be some amount faster to find a buyer. The cost of development is minimized while still reaching that goal, limiting the gain to no more than necessary.
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