From: Rafal Smigrodzki (rafal@smigrodzki.org)
Date: Wed Jun 18 2003 - 20:23:15 MDT
Mez wrote:
>
> This suggests that you're right in that additional processing power
> will enable the creation of software and robots with higher levels of
> sensory and locomotor intelligence.
>
> However it's not clear to me how we'll bridge the gap between that
> kind of intelligence and the abstract reasoning that we humans have.
>
> Right now if I had infinite computing power and wanted to do it I'd
> employ an evolutionary technique. Unfortunately, this is Eliezer's
> worst nightmare - a new form of intelligence grown by evolution and
> not necessarily friendly to us.
### I understand that Bayesian networks can be used to approximate the
behavior of both low-level motor/sensory neural networks, and high-level
semantic networks. Ben Goertzel is working on a system using probabilistic
inference on "atoms" (simple nodes) and "maps"(mapping of ensemble of atoms)
to achieve AGI. He believes that 3 to 5 years might be sufficient to build a
system capable of supervised learning with real-world input (e.g. scientific
journals). This is a bit like evolution but more amenable to oversight.
---------------------------
>
>> Human-level computing power is going to be available to
>> SingInst in about 15 years, so we can expect the recursive
>> self-enhancement of the FAI to take off around that time.
>
> I'm not convinced of this. You're basing this on Moravec's
> extrapolation of computing power necessary to replace the retina to
> the whole brain? I think that's a pretty rough model. The retina
> lacks much of the complexity of the cortex.
### The estimate of the number of synapses and their firing rates is taken
directly from histological and neurophysiological analysis of the cortex.
The equivalence coefficient between computing power needed to emulate the
retina and the number of retinal synaptic events is also a direct
observation (subject to uncertainties of whether the retinal emulator is
really emulating the retina). The main leap of faith is applying the
FLOP/synapse equivalence coefficient from the retina to the cortex, but then
the increased complexity of the cortex is accounted for by the enumeration
of synapses. We have no reason to believe that the cortical synapses are
more computationally efficient that the retinal ones (they have similar
structures, similar evolutionary pressures for optimization). In fact, since
retinas have been around much longer than the prefrontal cortex, the former
might better optimized than the latter.
In any case, while I am not a totally gung-ho near-term Singularity apostle,
I do think the UFAI should figure very high on Brett's and most of other
people's lists of future problems.
Rafal
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