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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