Re: AI for optimization?

On Sun, 25 May 2025 03:52:17 +0000, arnold@freefriends.org wrote:


>In article 25-05-016,
> <anton@mips.complang.tuwien.ac.at> wrote:
>>I am just surprised that I read and hear so much about work based on LLMs, which
>>seems to be a dubious technology for doing things where correctness is
>>important. What am I missing?
>
>The fact that AI is "hot" right now? "Sexy"? "Good for getting
>startup capital"? Who cares about correctness?


ANNs can be made into excellent pattern matchers. The probem IMO is
that too many "applications" are not simply matching patterns and
acting upon them, but rather are matching pattern /prefixes/ or
subsets of the complete pattern, and then acting /as if/ the complete
pattern exists.


This is what "generative" LLMs are doing: e.g., the AI sees the words
"brown" and "jumped", assumes "The quick brown fox jumped over the
lazy dogs", and bases its responses on that sentence.


If it turns out that, in fact, the user was seeking information on
"Encyclopedia Brown"[1] and the pickup truck rather than on different
species of canines interacting ... well, too bad.




>Pardon my cynicism.


Neural AI has been around since the 1950s ... I've been following it
since the late 1980s. It just wasn't practical to train even small
ANNs until (relatively) low cost SIMD became available.


Now ANNs have grown to scales where, even having cheap SIMD, once
again the computational costs have become an issue for training (and
retraining when relevant).
[The costs can be an issue even for deployment, though less so.]


ANNs are best used as high speed probablistic pattern matchers - which
includes use as associative memories. The problems are in relevant
scoring/comparison of multiple possible matches [stability], dealing
with low scoring matches [guessing], trusting that the ANN
usually/always will be correct [non-technical users], and how the
responses are being used [again, non-technical users].


I think a rule based logic system using ANN for input matching is a
good combination with a lot of potential. You don't need to resort to
ANN logic - rule based systems can account for probabilities ["fuzzy"
logic]. I remain unsold on ANN logic because - at least currently -
it neither can be verified, nor easily changed. Having to retrain
your ANN logic every time some conditional in the problem set changes
is a non-starter for me.


YMMV.


>Arnold
George




[1] https://en.wikipedia.org/wiki/Encyclopedia_Brown

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