I think we need to be careful with considering LLM parameters as analogous
to synapses.   Biological neuronal systems have very significant
differences in terms of structure, complexity, and operation compared to
LLM parameters.

Personally, I don't believe it is a given that simply increasing the
parameters of a LLM is going to result in AGI or parity with overall human
potential.

I think there is a lot more to figure out before we get there, and LLMs
(assuming variations on current transformer based architectures) may end up
a dead end without other AI breakthroughs combining them with other
components, and inputs (as in sensory inputs)..

We may find out that the singularity is a lot further away than it seems,
but I guess time will tell.    Personally, I would be very surprised to see
it within the next decade.

On Thu, Mar 28, 2024 at 9:27 PM Russell Standish <[email protected]>
wrote:

>
> So to compare apples with apples - the human brain contains around 700
> trillion (7E14) synapses, which would roughly correpond to an AI's
> parameter count. GPT5 (due to be released sometime next year) will
> have around 2E12 parameters, still 2-3 orders of magnitude to
> go. Assuming continuation of current rates of AI improvement
> GPT3->GPT5 (4 years) is one order of magnitude increase in parameter
> count, it will take to 2033 for AI to achieve human parity.
>
>
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