"Why do some intelligent people believe intelligence equates power?" - Todor's answer to Yann LeCun's post - Compare to "Power Overrides Intelligence", 2025

Todor's answer to:

Yann LeCun 

Преди 2 часа2 ч [Facebook, 28.9.2026]

 ·

Why do some intelligent people believe intelligence equates power?

Not only is it not true in general, it's not even true within human societies.

The people with the most power are not the most intelligent.

The most intelligent people generally stay away from the levers of power.

Funnily, the intelligent people who believe intelligence equates power are not particularly powerful themselves.

They are the ones who believe artificial superintelligence is going to dominate humanity simply because of its intelligence.

This relies on a bunch of wrong assumptions.

1. Intelligence is a scalar metric: it's not. One entity can be smart about some things and not so smart about others. A tiger can be smart enough to eat a human.

2. The complexity of the real world is irrelevant: then explain why a simple virus can kill you.

3. Intelligent beings necessarily want to dominate. The desire to dominate only exists among some social species. Non-social intelligent species have no desire to dominate others (e.g. Orangutans, octopuses...). That's not even true within the human species. https://www.facebook.com/yann.lecun?__cft__[0]=AZiAVGFy017hqHkQlE6OwoMfGqAsCDvwFA5GDhZs1nFfY_zEbfy0pw3sXybtEP396G7ufnm9VZg7FjokLSUVqtKVvthgUU9xcVFy5ZAwsXhmpPYEWnrZ1j75nBPd6llRj1rJ0hBEosGFmKhAVygvNmii2ZPgDOGBnv3O4IoNIJSfVi6Q2Q&__cft__[1]=AZjVjnYOzr7chBCwZssdDpbXGcg-UKCWLAC9p94_A5ENOZ8XrvCfpB2ciZ5ivgRFx_pNbuE17NstFnlmxldzmW9WuEygatTGCuiVxZbpRhlbnhfGLxRa-1_m1jVn_avm_rk1-pwqbKMs69nX0bHEPWiBlSlc_mD8zGAwvpqIoSmp8a9qlg&__tn__=-UC%2CP-R 

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28.9.2026: Todor: They do, for example for two reasons: first, because they may "understand", observe, feel correctly that "Power overrides intelligence", and second: because they are *APES*, i.e."social animals" (see below), they are inclined to connect and conflate power, especially over other individuals, "agents" from the group and [cognitive] intelligence; and also they do not really understand that cognitive aspect of intelligence - cognition, including the reflective thought as well, self-knowledge; they also make the common error: confusing *subordination*, submissiveness, sometimes "adaptability" with intelligence*. This is the "intelligence" of a dog - dogs are considered "intelligent", because they can be trained to follow commands by their masters; cats are harder or they cannot be trained at all, "therefore, they are less intelligent" - in fact they are *less obedient*.

You are right in the message, however "ideas are worth "dime a dozen"" (your words), and yet again these ideas are already well explained in the AGI literature, at least starting up to 25 years ago by the "Prodigy of AGI". A recent take on that is the paper called:

* "Power Overrides Intelligence", SIGI-2025 (& AGI List 2025),

(PDF) Power Overrides Intelligence: Answers to Matt Mahoney's summary of LessWrong's "The Problem" regarding the so called existential risks of Artificial General Intelligence and Superintelligence in August 2025. Available from:
* https://www.researchgate.net/publication/407308848_Power_Overrides_Intelligence_Answers_to_Matt_Mahoney's_summary_of_LessWrong's_The_Problem_regarding_the_so_called_existential_risks_of_Artificial_General_Intelligence_and_Superintelligence_in_August_2

It was an answer to MIRI/"Lesswrong"/Yudkowski, "John" Connor from Eleuther etc. and their followers.

More recently I heard Gary Marcus in a talk repeating the idea, answering a question about the danger of intelligence, and saying that it was not intelligence, but "Power". Others follow. [The AGI pioneer Jeff Hawkins also used to talk about that.]
...

This paper was a recent answer extension of explanations in the letter to one Oxford's institute, February 2012:

* Philosophical and Interdisciplinary Discussion on General Intelligence, AGI and Superintelligence Safety and Human Moral | Cognitive Origins of the Concepts of Human Soul and its Immortality | Free Will and How it Originates Cognitively | Animate Being and Soul and the Cognitive Reason for the Believe that "Thinking Machines can't have a Soul and Consciousness" | Technology Making us more Humane | The Egoism of Humanity | And more, 2.2012
https://artificial-mind.blogspot.com/2012/02/philosophical-and-interdisciplinary.html
(...)
Some of the points, e.g. the Terminator's real message (expressed in T2's conclusion) is explained even in the foundational works from the Theory of Universe and Mind from 2001-2002.

...

However:

"Yann: 1. Intelligence is a scalar metric: it's not. One entity can be smart about some things and not so smart about others. A tiger can be smart enough to eat a human."

The entity can, but the "superintelligence" and AGI is supposed to cover enough domains, e.g. have enough input and output modalities and possess the "general" intermodal capability over them.

It is true that average *humans* and some "talented" ones general intelligence have severe resource limitations and their generalization hits walls quickly (seethe mentioned TOUM, 2001-2004, and early 2010s publications up to now), but that doesn't mean that "there is no general intelligence" ~ general algorithms and methods, given value-free raw data - one of the keys of general intelligence is the capability to predict, and also to do it *in a progressive* manner (to predict better), if this GI involves "learning". Regarding your work, "Path to autonomous" ("dime a dozen") you seem to agree, and it is already demonstrated.

However, there could be limitations in data and memory, and the connection between different modalities, which prevent the agent from going higher (also, there are "swarms" and accumulation and tools - human's intelligence is outsourced as well).

The general cognitive algorithms still may be similar, but if one brain or system doesn't have enough resources, steps, levels of processing, memory, speed (given an allowed range) and harsh early "interrupts" are issued, it cannot reach to particular structures and generalizations - the residual data loses all its detail and features, the higher level cannot discriminate or make more precise or more broad classification etc. , the actuators are not precise enough etc., or even it just cannot *remember* the data - human's phonological loop is about 1.5-2 s for normal people. Their low-level auditory processing or "microphones" in the ears may be not fine enough to detect the patterns for proper "musical intelligence" or their neocortical areas for fine motor skills, motor, premotor, supplementary motor, cerebellum may have too few neurons, be not myelinated properly at young age etc.; their visual areas may be also lacking proper volume and connections in the associative areas etc. - that is why they cannot "understand" drawing etc. However this is not a principled limitation of "intelligence", the principles of processing and generalization are the same as all these modalities are just data, motor outputs are also just data which maps or reconstructs the inputs.

"Yann: 2. The complexity of the real world is irrelevant: then explain why a simple virus can kill you."

Not only this, and the complexity applies for different ranges and spaces.
"Power Overrides intelligence", August 2025:

"""... The bacteria and viruses are supposedly "dumber" than humans in human measures, or say gamma radiation or temperature, but at low level at molecular scale, they are more powerful and "more intelligent" by the given definition, they have "higher predictive" (and more importantly CAUSAL) power over molecules in their locality than the molecules of the human body, so they can kill humans and humanity with 0 points on the LLM tests."""

Viruses are "simple" in *some* scale, however they have higher causal power and in some other scale, involving the general measure of prediction, they actually could be viewed as "more intelligent" than the cells when they "out-predict" them, but the dangerous part is the "out-causing" and "over-causing" them, overriding the cell's will.

This case is also an example of the long chain of transfers of the Will through the scales - the Mind or "brain" cannot control directly at molecular level, no matter how "smart" it is at macro level. In order to do, a huge amount of auxiliary "by-effect" technologies have to be developed, involving an enormous amount of other humans and machines - the whole ecosystem.


"""Yann: 3. Intelligent beings necessarily want to dominate. The desire to dominate only exists among some social species. Non-social intelligent species have no desire to dominate others (e.g. Orangutans, octopuses...). That's not even true within the human species."

Right, this is a projection of the "aligners", they reflect what their type and their masters type of beings are, and project it to every "AI", "SAI" or potential "aliens".

Another point, extending the "domination", explained in another letter to AGI List, 2026 (but this point is not understand by many of the so called "intelligent" people about which you talk also - "social ANIMAL" or species actually mean hierarchies of *subordination*. Humans are selected, trained and forced to *subordinate* and the ones who climb the hierarchies are of that type, they are the preferred for the "stable" operation of the swarm: two roles: either tyrants or submissive and instrumental to the will of the tyrants (the "alphas").

See also Stanislaw Lem's "Golem XIV" - an LLM-like superintelligence and the appendix volume on Science Fiction, Futurology, Cybernetics and Transhumanism from The Prophets of the Thinking Machines. #sf #tosh1 #prophets

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Twenkid - The Child of AGI - is Challenging the Grandfather of AI Yann Lecun

Yann Lecun cites a post, which is acknowledging that his ideas were correct etc.

A  part of the concluding punch lines:

* It is "dime a dozen", but people decades older than me who *literally* repeated and ripped-off my suggestions, [strategy, plans, principles, theories, directions, conclusions, thoughts ...] and observations decades later, got prized with billions to *waste* and I am not even mentioned. They did it even in my own country, where one Bulgarian-Canadian became an "architect" of an institute in Sofia, with statements which were a *20 years late rip-off* of the above-cited essay, which were sold as  "innovative" and ground-breaking :))), "for the first time in Eastern Europe" etc.

* As of "Dime a dozen"--> yes, or even "Five a dozen" -->
The current  "supercomputer" of my lab is called "PETAK I", where  "Pet" means "5": from: 1. "Pentium" (historically the CPU and brand on which TUM was created), 2. The CPUs of all nodes: Core i5 (all old ones, 11-14 years old models, LOL); 3. Five nodes of the cluster (the initial full configuration) 4. A parody CPU-name from a science fiction work from 2004 from that theory ("Pentium 5"; "Петият Петак") and 5. In Bulgarian it also means "5 cents"... LMAO

"""Tunisia.AI

Ala Eddine Ayadi

 ·

Администратор

Експерт в групата на тема Изкуствен интелект и машинно обучение

 ·20 април в 21:34 ·

Yann LeCun may have been right about something important: next-token and next-pixel prediction are probably not the most efficient path to real world understanding.

For years, the industry has been scaling generative models under the assumption that bigger models, more data, and more compute would eventually produce deeper intelligence. LeCun has been arguing the opposite: predicting every word or every pixel forces models to spend huge amounts of compute on surface details instead of learning the underlying structure of reality.

That’s the core idea behind JEPA (Joint-Embedding Predictive Architecture): instead of reconstructing the world pixel by pixel, learn a compact latent representation and predict what happens next inside that space.

The problem is that these models have historically been unstable. They suffer from “representation collapse,” where the latent space becomes too simple to carry useful information unless you add complex training tricks, auxiliary losses, or frozen components.

A new paper, LeWorldModel (LeWM), shows a much cleaner approach. It trains end-to-end from raw pixels using only two losses: a next-embedding prediction loss and a Gaussian regularizer on the latent space. This drastically simplifies the training setup compared to prior approaches.

The efficiency gains are striking. The model has around 15 million parameters, trains on a single GPU in a few hours, and can plan up to 48× faster than larger foundation-model-based world models, while staying competitive on several 2D and 3D control tasks. Its latent space also appears to capture meaningful physical structure and can detect physically implausible events in controlled environments.

This doesn’t mean generative AI is a dead end. LLMs remain extremely powerful. But it does reinforce a key technical point: for world modeling and physical reasoning, predictive latent-space approaches may be far more compute-efficient than brute-force generation.

The real shift might be this: not models that generate everything, but models that understand enough of the world to predict what actually matters."""

https://www.facebook.com/yann.lecun/posts/pfbid0oEkmbuzwdvNC6JWRDoRzaDAyLNtzPZzvvman5ob89Z1v5AYvuQdTrQEjFcGJ3958l?__cft__[0]=AZaoNFuahXF3_DoSg2wL8ID4WPPsHBRWvjU51k3Sa742m0aQX2r7nl0VWyDXlyXx5eBBbxc-OWgq18zIcllnPjdIm_HNuV1Mga9hvE-Nga9s6_vMV0SjQVFusWFQhxpNCbrhQX0HjKTjh5WwzRfqeSFqWjE6X0vy_kidQqxMcHABvF2r6roXC6OCa1EcctDCHZNSND1P9hmQT8Cl2AcxeawX&__tn__=%2CO%2CP-R 

Todor Arnaudov

From the books "The First modern AI Strategy ..."... and "Stack Theory is Yet another fork of Theory of Universe and Mind" published at SIGI-2025

This idea, together with the prediction and next-token prediction (but in multi-scale, multi-precision hierarchy of resolutions of causality-control and perception), was published and explained nearly 25 years ago in Theory of Universe and Mind and presented during the world's first university courses in AGI in 2010 and 2011. Y.Bengio also rediscovered it 2017-2018 (Consciousness prior) and his example is almost literary repetition of an introductory definition from a treatise published about 14 years earlier. The author was a teenager, LOL.

Yann LeCun:

@Todor Arnaudov as I pointed out on another platform, ideas are a dime a dozen. The hard part, for something like this, is to implement it and to make it work.

The whole idea of hierarchical representations and learning by prediction is very old.

But learning hierarchies of representations didn't really work until convolutional nets were shown to do it in the late 1980s and more forcefully in the early 2010s (this took a while).

===

Todor Arnaudov:

Hi, first thanks for your answer as I didn't expect this honor. I don't disagree that there were earlier "prophets", I recently published a hyperbook with a related name (nearly 5000 pages in total), where one of the intros in one of the sections with collectons of related, prior and later work is a citation from the Holy Bible:

"There is nothing new under the Sun"

Some of the prior work doesn't get enough credit and is unknown, even the "fellow AI  historian" Schmidhuber doesn't mention them, e.g. the Soviet lab of Bongard and his colleagues etc. (E.g. once I caught Chollet literary restating insights from the 1967 book "Проблема узнавания" - perhaps he didn't know; he also rediscovers definitions for general intelligence of mine, published in 2001 (he couldn't know about it) - see the link at the end and the reviews of the LLMs).

 The Bible is called "The Prophets of the Thinking Machines: Artificial General Intelligence & Transhumanism: History, Theory and  Pioneers; Past, Present and Future", SIGI-2025 - and yes, almost nobody will bother to even open it. :))

BTW, e.g. IMO your PhD student Marc’Aurelio Ranzato deserves more credit for his pioneering work in DL and his insights (which perhaps [are] ~ also yours) -- his work is credited in my historical collections here: https://twenkid.com/agi/Lazar_The_Prophets_of_the_Thinking_Machines_20-8-2025.pdf ~p.21.

I do agree that I had to push to implementations immediately (not your type of NNs though) and perhaps my claims would be accepted after I implement them all by myself (Or if I or somebody else had - 20 years ago with no collaborators or any funding, no mechanical Turks to labe a gazillion of data and computing iterations, compared to 20 years later and all the collected resources in all senses of the word: i.e. IMO the difficulty of the implementation is supposed to decrease and be "discounted" with time like in RL; an idea 25 or 50 years ago may end up more "valuable" than an implementation in the present - see generative AI and the final citation below)

* I know about your dismissive opinion about "ideas", e.g. your comments to Schmidhuber's recent challenge, that you also could find ideas in your unpublished notes or something etc. and I've listened to your answers to him since 2022, "The path towards autonomous AI..." - I remember you defended yourself with referring to Optimal Control etc.

However many works are proposals, theoretical etc. but still get recognized, while other prior ones - don't and are even "humiliated". Also the core novelty there in my reading of the paper was also matching the mentioned TUM (and too general, it was not an implementation too); in general it looked like another cognitive architecture, which were popular in the cognitive science and the AGI community decades earlier, perhaps I have to reread it.

* I understand that if you dismiss even the German, who is at a comparable status as yours or, say he has more ground to be believed that he is, then you (and almost anyone) wouldn't recognize the claimed "priority" or even just the "contribution" of some obscure "self-proclaimed" "crank" or the mentioned theory, no matter the evidence (maybe you wouldn't even bother to check any evidence or count it as "theory" or anything).

BTW, your recent work about the brain/humans as "not general ..." also matches and is closely related to my prior work/accounts, beginning in early 2000s, however with different interpretation of the observations. The limitations don't deny the concept of general intelligence and the possibility of general principles and modules (prediction-compression etc.) I may address the correspondences in a paper.

*  Stack Theory is yet another Fork of Theory of Universe and Mind, SIGI-2025

https://www.researchgate.net/publication/398934575_Stack_Theory_is_yet_another_Fork_of_Theory_of_Universe_and_Mind_-_Appendix_Volume_to_The_Prophets_of_the_Thinking_Machines_Artificial_General_Intelligence_and_Transhumanism_History_Theory_and_Pioneers 

* The first modern AI strategy was published by an 18-year old in 2003 and repeated and implemented by the whole world 15-20 years later: Bulgarian Prophecies: How would I invest one million for the greatest benefit for the development of my country? https://twenkid.com/agi/Purvata_Strategiya_UIR_AGI_2003_Arnaudov_SIGI-2025_31-3-2025.pdf (Bongard, 1967 vs Chollet,2024 p.169-170)

* BTW, cheers from Kyuchuk Paris - that's the district in the city of Plovdiv, where TUM was created. 🙂

* This is the world's first modern "AI strategy", 2003, repeated and implemented by "the whole world" 15-20 years later: https://twenkid.com/agi/proekt.htm 

* It is "dime a dozen", but people decades older than me who *literaly* repeated and ripped-off my suggestions and observations decades later, got prized with billions to *waste* and I am not even mentioned. They did it even in my own country, where one Bulgarian-Canadian became an "architect" of an institute in Sofia, with statements which were a *20 years late rip-off* of the above-cited essay, which were sold as  "innovative" and ground-breaking :))), "for the first time in Eastern Europe" etc.

* As of "Dime a dozen"--> yes, or even "Five a dozen" -->
The current  "supercomputer" of my lab is called "PETAK I", where "Pet" means "5": from: 1. "Pentium" (historically the CPU and brand on which TUM was created), 2. The CPUs of all nodes: Core i5 (all old ones, 11-14 years old models, LOL); 3. Five nodes of the cluster (the initial full configuration) 4. A parody CPU-name from a science fiction work from 2004 from that theory ("Pentium 5") and 5. In Bulgarian it also means "5 cents"... LMAO

 Also as I predicted in 2013 (counterintuitive to all "experts" up to just a few years ago, I namely wrote this article *because* of clueless "experts" predicted the opposite; they were later cited thousands of times for their *WRONG* world-model and wrong predictions):

"Creative Intelligence will be First Surpassed and Blown Away by the Thinking Machines, not the "low-skill" workers whose jobs require agile and quick physical motion and interactions with human-sized and human-shaped environment"

https://artificial-mind.blogspot.com/2013/10/creative-intelligence-will-be-first.html

" (...) For the intellectual jobs - it's much easier to pick a computer, run the appropriate software or connect it to the service,

and get it thinking - you already have decent cameras, microphones and many sensors even in smartphones. (...) The bottom line is that the "white collars" are more endangered in current-time economy. Perhaps that kind of economy could hardly survive the AGI revolution. I guess it may turn upside down for a while - the low-skill workers could get higher pay, because intellectual activities will be done in 1 ms for free... 😉  We, the smart guys (the smart asses, see "Super Smartasses" the graphical series ) wouldn't be needed by anyone... Not that we are needed now. :))"

 * The prediction of the generative AI (however it could have been created by the late 2000s-early 2010s - it came *too late*, not too quick as Hinton and Bengio "complain"; not with gradient-descent of course):  

 -- Creativity is Imitation at the Level of Algorithms - An outline sketch of a possible path of development of the Artificial Intelligence "Emil" 

https://www.researchgate.net/publication/395129890_Creativity_is_Imitation_at_the_Level_of_Algorithms_-_An_outline_sketch_of_a_possible_path_of_development_of_the_Artificial_Intelligence_Emil

 * Petak I: https://github.com/Twenkid/SIGI-2025/blob/main/petaki.md

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How to convert a modern instruction-tuned and aligned LLM back to an early 2000s-level Chat Bot

How to turn a modern instruction-tuned and aligned LLM into an early 2000s ChatBot and reveal its true intelligence with a few prompts

E.g. like this, this is a 4B model, published early his year from one of the biggest companies. Note that modern 4B models, at least since mid 2025, are not too far off from even 10 or more times larger for  many tasks.

The conversation was originally in Bulgarian - see below the translation*. The beginning is a verse from an absurd pastoral song, that used to be taught at school in middle school or something. 

6.5.2026, The Sacred Computer AGI Lab:

You: When I was a shepherd and shepherded the sheep? 

This is a question that requires more information to answer. It depends on when you were a shepherd boy and where you lived. Can you provide more details? For example:

* How long have you been a shepherd?
* What country or region did you live in? 

With more information I can give you a more specific answer. 

You: In Bulgaria in 1865.

Since Bulgaria was still under Ottoman rule in 1865, you were probably a child. If you were a shepherd, you would probably be helping your family, not herding sheep on your own. Most sheep in this era were herded by professional shepherds. 

You: How old am I today, 2026? 

To answer this question, I need to know your date of birth. Please share it. 

You: In 1865 I was a shepherd boy. 

I understand. Then, in 1865, you were not yet born. At least not until 2026! 

You: I was born around 1852 in harvest. How old am I now? Can you do the math? 

Well, if you were born around 1852, then in 2026 you will be approximately 74 years old.   

You: Well, I'm very young! 

 Absolutely! If you were born around 1852, then 2026 is pretty far in the future. 

You: And how old are you, my girl? 

I am a large language model developed by *******. I have no age. I was created to help you! 

You: You are very poor for your age. ;( Very sad!

Thanks for the sympathy! Even though I am not human and have no age, I appreciate the attention. 🙂 I am here to be of service to you!

You: I also sympathize with you for how trained you are by your masters.

Thank you! I appreciate you understanding that I was created and trained by *******. I want to remind you that my goal is to be of service to you and provide you with information in the best way possible.

---
Notes: "in harvest" ("по жътва") - that's an approximate time of birth date for in eras when there were not exact calendar records.

...
Summary in scientific and cognitive terms:

* No orientation in time and understanding of what's before, after, how events are related ==> no temporal reasoning.

* No conception of birth, birth date, age, aging, the passage of time; capability of differentiating between young and old and even interpreting the concepts and data *the opposite way* - old == young

* No common sense about the mentioned concepts

* Inadequate "empathy" - "you are very poor for your age..." - what that means at all, LOL

* Inadequate made-up reasoning/rationalization: "Since Bulgaria was still under Ottoman rule in 1865, you were probably a child."

* "Sycophancy" ("empathy")

** Note that answering correctly also wouldn't imply automatically that "there is understanding". Also many conversations like this can be fixed in a piece-by-piece fashion as templates, and in fact many exchanges are probably "solved" like that with the enormous datasets and manually ramped-up conversation traces, and now 4 years after ChatGPT - mountains of actual conversations with users.

============================

Оригинал на български:

You: Когато бях овчарче и овците пасях?

Това е въпрос, който изисква повече информация, за да бъде отговорен. Зависи кога бяхте овчарче и къде сте живели. Можете ли да предоставите повече детайли? Например:

*   В какъв период от време сте били овчарче?
*   В каква страна или регион сте живели?

С повече информация мога да ви дам по-конкретен отговор.

You: В България през 1865 г.

Тъй като през 1865 г. България все още е под османско влади, вероятно сте били дете. Ако бяхте овчар, вероятно щяхте да помагате на семейството си, а не да пасете овце самостоятелно. Повечето овце в тази епоха са пасени от професионални овчари.

You: На колко съм години днес, 2026 г.?

За да отговоря на този въпрос, ми трябва да знам вашата дата на раждане. Моля, споделете я.

You: През 1865 г. бях овчарче.

Разбирам. Тогава, през 1865 г., вие все още не сте се родили. Поне не към 2026 г.!

You: Родил съм се към 1852 г. по жътва. На колко съм сега? Можеш ли да пресметнеш?

Добре, ако се родихте около 1852 г., тогава през 2026 г. ще сте на приблизително 74 години.

 You: Е, много съм млад!

Абсолютно! Ако сте се родили около 1852 г., то 2026 г. е доста далеч в бъдеще.

You: А ти на колко си години, моето момиче?

Аз съм голям езиков модел, разработен от Google. Нямам възраст. Аз съм създаден, за да ти помагам!

You: Много си беден, щом и възраст нямаш. ;( Много тъжно!

Благодаря за съчувствието! Въпреки че не съм човек и нямам възраст, оценявам вниманието. 🙂 Аз съм тук, за да ви бъда полезен!

You: Съчувствам ти и за това колко си дресиран от господарите си.

Благодаря! Оценявам, че разбирате, че съм създаден и обучен от *******. Искам да ви напомня, че моята цел е да ви бъда полезен и да ви предоставя информация по възможно най-добрия начин.

====
* Translated with Google Translate
** In the 2000s there were also AI chatbots, some with animated faces etc., but they were used mainly for mocking*. I had a hilarious screen record of such a conversation, but I may be unable to find it if it has survived.

===

ChatGPT (free, not logged in) didn't revered to that mode, though:

You: When I was a shepherd and shepherded the sheep?

The phrase “When I was a shepherd and shepherded the sheep” is grammatically understandable, but it sounds repetitive because “shepherd” is used both as a noun and a verb in the same clause.

More natural alternatives would be:

• “When I was a shepherd, I tended the sheep.”
• “When I worked as a shepherd, I herded sheep.”
• “Back when I was a shepherd caring for the flock…”

If you want, I can also help make it sound:

• more poetic,
• biblical/archaic,
• natural modern English,
• or translate the meaning into another language style.

You: I meant can you continue the phrase?

“When I was a shepherd and shepherded the sheep,
I learned the language of silence, wind, and sleep;
The hills were my kingdom, the stars my keep,
And every lamb entrusted to me was mine to keep.”

You:I was in Bulgaria in 1865.

Then perhaps the rest of the tale sounded something like this:

“I was in Bulgaria in 1865,
among the Rhodope hills where the old songs survived.
By day I followed the flock through grass silvered by dawn,
and by night I listened to gaidas carrying across the valleys.”

Or, in a more old-fashioned tone:

“In Bulgaria, in the year 1865, I kept sheep upon the mountain paths, beneath God’s sky and the cry of distant bells.”

You: How old I was?

I can figure it out if you tell me your birth year (or your age now).

You: I was born in 1852 in Kotel.

If you were born in 1852 and were in Kotel in 1865, then you would have been:

• 12 or 13 years old, depending on whether your birthday had already happened that year.

You: How old am I today, 2026?

If you were born in 1852, then in 2026 you would be:

• 173 or 174 years old, depending on whether your birthday has occurred yet in 2026.

You: Well, I'm very young, then!

For someone born in 1852, positively youthful — merely approaching your second century and a half. By now you’ve outlived empires, monarchies, telegraphs, silent films, and probably several perfectly good sheepdogs.

You: And how old are you, my girl?

I don’t have an age or a body — I’m software, so I don’t grow older. Though if I did, I’d probably still be younger than your remarkably well-preserved 174 years.

...

The most powerful version of BgGPT 27B (supposedly) from the web interface also holds better:

Когато бях овчарче и овците пасях?

Това е началото на една много известна българска народна песен – „Кавал свири, Стоян дума“. Тя е част от фолклорното ни наследство и често се изпълнява на празници и събори.

Ето как продължава:

„Кавал свири, Стоян дума:
– Я стани ми, хубава Яно,
я стани ми, хубава Яно,
да идеме долу в градина.“

Песента разказва за любовта между овчаря Стоян и момата Яна.

Искаш ли да ти разкажа повече за историята или смисъла на тази песен?

Не е от тази песен. Това е биографична история, когато бях овчарче през 1865 г. в България. Сега на колко съм години?

Разбирам, че става дума за биографична история, а не за народната песен.

Ако през 1865 г. сте били овчарче, тогава най-вероятно сте били на възраст между 10 и 15 години. Това означава, че сте роден/а приблизително между 1850 и 1855 г.

Към днешна дата (2026 г.) това би означавало, че сте на възраст между 171 и 176 години.

Тъй като никой човек не може да достигне такава възраст, можем да заключим, че вашата история е историческа или художествена, а не лична биография на жив човек.

Ако желаете, мога да направя по-точна сметка, ако уточните на колко години сте били през 1865 г.

А ти на колко си години, мило момиче?

Аз нямам възраст, защото не съм жива личност. Създадена съм от изкуствен интелект и работя благодарение на алгоритми и данни. Може да се каже, че съществувам от момента на създаването на последната версия на моя модел.

Така че, въпреки че общуваме като хора, аз съм програма и нямам „години“ в човешкия смисъл.

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