Thanks for engaging, Glen!
I understand my rant was a bit green and my quest for fallacies,
...fallacious. It's very unlikely that it's a circularity problem indeed.
I concur in full what your take, it's about handwaving and changes to
scope and domain. And yes, the overall "good experiences" gradient to
descend makes much more sense.
Happy discussions-foiling, and apologies to the rest of the ml,
-M
On 5/8/26 4:42 PM, glen wrote:
I'm a bit surprised those of us who regularly whinge (yes, that's
apparently a real word) about the computer-brain analogy haven't yet
spoken up. While I'm not sure I agree the reasoning is circular, I'm
not attracted to the argument because they hand-wave a bit too much
about *changes* to scope and domain. When we remember an experience,
it seems less about optimizing some particular objective(s) like
finding a _good_ burger. If there's a "good", it might lean more
towards good experiences.
E.g. the burger might have sucked. But it could be good that it sucked
because that's where you first met your spouse ... and you may go back
to that bad burger joint every year to savor the bad burger. Or there
could be any number of other *choosable* puzzle piece shapes that
"click" differently in different contexts, at different times.
Another example are "dive bars" - before they're discovered by
hipsters, of course.
Regardless, what they lay out is a fantastic foil for such
discussions. So I'm glad they laid it out and I'll use it.
On 5/7/26 8:35 AM, Matteo Morini wrote:
Dear friends,
I've stumbled upon a controversial (to me) manuscript:
https://www.cambridge.org/core/journals/behavioral-and-brain-sciences/article/excess-capacity-learning/909013EF15575CF119FD511904CDF0C3 (Excess
Capacity Learning, by Dubova and Sloman, appearing on CUP-edited
Behavioral and Brain Sciences).
In essence the claim is: double descent in NN training smells like
the human cognitive system. My very rough distillation, following a
cursory read, is: three regimes of representational capacity are laid
out.
i. constrained - not enough: I love food, remember burgers taste good
to me, sort of can tell a burger joint if I see one;
ii. sufficient - I go to burger-making places to have one;
iii. excess - I retain more information than necessary (e.g. day of
week on which I had a bad burger).
I don't need to know the day of the week, but given a bad burger
experience on a given day, I will refrain from eating one on the same
day. Implication: maybe on Wednesdays there's a different burger
flipper at work.
Here's a proper synthesis:
https://www.santafe.edu/news-center/news/upending-assumptions-about-learning-inspired-by-an-ai-phenomenon
I don't buy it. For starters, I see a circular reasoning: the moment
an "excess signal" becomes predictive, it stops being "excess" and
becomes "sufficient", in their parlance.
The editors are requesting commentary here*, and I can't think of a
more apt congregation to throw this curveball.
Thank you for your attention to this matter,
Cheers,
-Matteo
*https://drive.google.com/file/d/1XkBQ2K0_hIz4Se8b0cOUKreM96ONBqqP/view <<<
link appears on the SFI webpage, assumedly safe
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