What makes you lie about the existence of telepathy ? Does it make you 
happy ? Does it replace the lack of vvahmen in your life ?

On Monday, 16 December 2024 at 21:45:15 UTC+2 Brent Meeker wrote:

> 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 Zou at Carnegie Mellon University says  "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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