James,
For relevance to type theories in programming I like Bartosz
Milewski's take on it here. An entire lecture series, but the part
that resonates with me is in the introductory lecture:
"maybe composability is not a property of nature"
Cued up here:
Category Theory 1.1: Motivation and Philo
Historically the AGI community has not really embraced neural networks --
and the cost has been that the AI explosion has come from the mainstream
more or less.
On Thu, May 16, 2024 at 7:01 PM Quan Tesla wrote:
> Without neural networks, a symbolic approach wouldn't be effective. My
> view is th
Without neural networks, a symbolic approach wouldn't be effective. My view
is that, depending on the definition of what "symbolic approach" means in
the context of AGI, in the least both such operational schemas would be
required to achieve the level of systems abstraction that would satisfy a
sci
First, fix quantum logic:
https://web.archive.org/web/20061030044246/http://www.boundaryinstitute.org/articles/Dynamical_Markov.pdf
Then realize that empirically true cases can occur not only in multiplicity
(OR), but with structure that includes the simultaneous (AND) measurement
dimensions of t
It seems like most approaches including symbolic only could eventually lead
to "true AI" if you mean ~ passing the Turing test, but it might take 100
years. There is a race to the finish aspect to AI though.
On Thu, May 16, 2024 at 8:27 AM wrote:
> What should symbolic approach include to entire
On 5/16/24 17:26, ivan.mo...@gmail.com wrote:
What should symbolic approach include to entirely replace neural
networks approach in creating true AI? Is that task even possible?
What benefits and drawbacks we could expect or hope for if it is
possible? If it is not possible, what would be the
On Wednesday, May 15, 2024, at 8:01 PM, stefan.reich.maker.of.eye wrote:
> Is it AGI?
I believe, what they currently have, is a true AI, but they re taking a wrong
approach. They "train" it on a vast of data of questionable quality, hoping to
earn a big money while spending the least resources p
Seems unlikely as the first approach. ANNs help us bridge things we have
little understanding of via brute force and lots of data.
Perhaps AFTER we get to ASI the ASI can figure out how to recode itself
symbolically, at huge gain (likely) in performance.
On Thu, May 16, 2024 at 11:27 AM wrote:
What should symbolic approach include to entirely replace neural networks
approach in creating true AI? Is that task even possible? What benefits and
drawbacks we could expect or hope for if it is possible? If it is not possible,
what would be the reasons?
Thank you all for your time.
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