So you use non-existent telepathy. Well I guess that's easiest kind to
obtain.
I'm quite clear on the meaning of epistemology and ontology. Having
knowledge of Cosmin Visan does mean he exists.
Brent
On 12/15/2024 2:37 AM, 'Cosmin Visan' via Everything List wrote:
You make the classical confusion between epistemology and ontology.
Only because you can use something, it doesn't mean that that
something exists. Only because you watch a movie with Spider-Man, it
doesn't mean Spider-Man exists.
Also, I highly recommend you to perform for yourself such telepathy
experiment. Thank you for reading my papers!
On Saturday, 14 December 2024 at 22:57:55 UTC+2 Brent Meeker wrote:
I can successfully test my belief in matter. The fact that you
did not already know this casts strong doubt on your telepathic
powers.
"The second reason was that I already knew that I have telepathies
when I’m in relationships, thus I wanted to see what kind of
telepathies appear if I involve more than one girl."
From https://philpapers.org/archive/VISMAC-3.pdf
I guess if I were to write such stupid drivel I wouldn't use my
real name either.
Brent
On 12/14/2024 1:21 AM, 'Cosmin Visan' via Everything List wrote:
@Brent The only woo-woo is your belief in "matter".
On Saturday, 14 December 2024 at 01:46:07 UTC+2 Brent Meeker wrote:
On 12/13/2024 1:18 AM, 'Cosmin Visan' via Everything List wrote:
When you base an invention on the world of finite forms, of
course that invention will be limited. You will never
replicate the powers of consciousness, because consciousness
draws its powers from the infinite world of the formless.
And drawing from an infinite source, it is able to produce
infinite forms and it doesn't need quazillions of forms to
learn.
Let's see you produce and infinite form or two.
A baby learns to speak from just a few examples, because
what the parents to is not to provide raw data to the baby,
Twins often invent their own language which the speak to each
other. Evolution has provided the raw data to create language.
but to stimulate the baby's consciousness to access the
formless source and to draw from there whatever forms it
needs in order to be able to speak and generally learn anything.
Woo-Woo magic.
Brent
On Friday, 13 December 2024 at 09:29:37 UTC+2 Alan Grayson
wrote:
On Thursday, December 12, 2024 at 7:38:11 PM UTC-7 Brent
Meeker wrote:
Magic is always the explanation of those who can't
understand.
Brent
*There's plenty of magic, under a different name, in
physics. Another pitfall is religating hidden knowledge,
aka occult knowledge, such as the Chakras in Yoga, to de
facto magic or someone's overactive imagination. AG *
*
*
On 12/12/2024 1:39 PM, 'Cosmin Visan' via Everything
List wrote:
Magic!
On Thursday, 12 December 2024 at 20:00:58 UTC+2
John Clark wrote:
*The number of "tokens" (words or parts of
words) used to train LLMs is 100 times larger
than it was in 2020, the largest are now using
tens of trillions. if you only consider text
then the entire Internet only contains about
3,100 trillion tokens. The amount of text LLMs
train on is doubling every year but the amount
of human generated text on the Internet is only
growing at about 10% a year, if that trend
continues AIs will run out of text somewhere
around 2028. Does that mean AI progress is
about to hit a wall? I don't think so for the
following reasons:*
*For one thing, because of improvements in
algorithms, the computing power needed for a
Large Language Model to achieve the same
performance has halved about every 8 months. *
*
*
*ALGORITHMIC PROGRESS IN LANGUAGE MODELS*
<https://arxiv.org/pdf/2403.05812>
*And computer chips specialized for AI rather
than general computing, like those made by
Nvidia and other companies, are getting faster
even more rapidly than Moore's Law. Also, the
rate of growth of specialized data sets, such
as astronomical and biological data, are
growing much much more quickly than text is;
that's how AIs got so good at predicting how
proteins fold up. *
*And there is vastly more information if AI's
are trained on other types of data besides
text, and some AI's are already being trained
on unlabeled images and videos. Yann LeCun,
chief AI scientist at Meta, said that
"/although the 10^13 tokens used to train a
LLM sounds like a lot /(it would take a human
170,000 years to read that much)/, a 4-year-old
child has absorbed a volume of data 50 times
greater than that just by looking at objects
during his waking hours. We’re never going to
get to human-level AI by just training on
language, that’s just not happening/".*
*And then there's synthetic data. AlphaGeometry
was trained to solve geometry problems using
100 million computer generated synthetic
examples with no human demonstrations, and it
ended up being as good at solving difficult
geometry problems as the very best high school
students in the entire nation. *
*Solving olympiad geometry without human
demonstrations*
<https://www.nature.com/articles/s41586-023-06747-5>
*AI researchers are starting to change their
strategy and have their AI's reread their
training set many times because AI's operate in
a statistical way so rereading improves
performance *
*Scaling Data-Constrained Language Models*
<https://arxiv.org/pdf/2305.16264>
*Andy Zouat Carnegie Mellon Universitysays
"/once //an AI has got a foundational knowledge
base that’s probably greater than any single
person could have,it no longer needs more data
to get smarter. It just needs to sit and think.
I think we’re probably pretty close to that
point/.”*
*
*
*John K Clark See what's on my new list at
Extropolis
<https://groups.google.com/g/extropolis>*
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