THE SACRED COMPUTER - СВЕЩЕНИЯТ СМЕТАЧ, a.k.a. ARTIFICIAL MIND: Thinking Machines, Creativity and Human Development. A pioneering virtual Research Institute for Artificial General Intelligence (AGI), Cosmism and Transhumanism, AI, Software, Interdisciplinary General Research, Creativity, Versatility, Universal Men ~ Twenkids etc. Created in 2000. (...)
Title pages of a few among 20-some volumes of the hyperbook "The Prophets of the Thinking Machines: Artificial General Intelligence and Transhumanism: History, Theory and Pioneers, Past, Present and Future". The books, monographs and papers are in English and Bulgarian. The images below are from: "Reflections on Everything" (Listove) - the second largest volume, Lazar - a broad survey in various ML and AI domains; "Is Mortal Computation Requried for the Creation of Universal Thinking Machines" (Нужни ли са смъртни изчисления за създаване на универсални мислещи машини?), "The Cat" (Котката, Kotkata) - Can the 2023-2024-2025 LLMs recreate the "prompt-engineering" which I demonstrated in 2003-2004 in the seminal work "Analysis of the Meaning of a Sentence ... - find on SIGI-2025
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
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."""
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
* 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"
" (...) 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"
Wolpert’s Theorems about Mutual Unpredictability and the Impossibility of Subuniverses to Predict with Highest Resolution of Causality-Control are Rediscoveries of Concepts from Theory of Universe and Mind – Entangled with Unnecessary Mathematical Notation and Unsatisfiable Premises
In a discussion from 8.2025 on AGI List, a part of which I archived at SIGI-2025 as a paper, titled "Power overrides intelligence", Matt Mahoney mentioned some "Wolpert's law" of which I didn't know at the time. Later that year I discovered it without searching for it from other publications, and I found out that in fact this is a fork of my own "Arnaudov's laws" (principles), published and explained 4-5 years before the first paper of Wolpert (2007-2008) and up to 16 years before a consequent paper from 2018*. There is a match even on "Liar's paradox" - it is addressed in my work as well, however I "scaled" it to even more absurd form, ridiculed it and explained why it was nonsense and it didn't prove what the "cheaters" intended. It is related to the concept in TUM "resolution of causality-control and perception"; comparison of representation with different and incompatible RCCP. "What's the color of the rainbow?" (one color) These are ill-posed problems, presented as well-posed by "cheaters". In this circumstances, any higher-resolution answer is correct, as the lower-resolution causality-control doesn't have capacity to distinguish the answers.
The original "law" from TUM also reflects the hierarchical structure of the predictions and CCUs, which work as and are created by hierarchical universal simulators of virtual universes, i.e. predictors and causers, which are multi-resolution, multi-range, multi-scale, multi-domain, multi-precision, ... multi- ... Wolpert has a corresponding concept "a general-purpose prediction device, capable of correctly predicting different aspects of the universe’s future", however his "devices", at least so long as I interpreted the paper, are flat and they predict/not predict, true/false", "A/not A" - 1-bit nonsense in the real Universe, as explained in TUM.
This paper is a chapter from the book "Reflections on Everything", or "Listove", the second-largest volume from "The Prophets of the Thinking Machines: AGI & Transhumanism: History, Theory and Pioneers; Past, Present and Future", SIGI-2025, 10.2025.
Abstract
This work presents a critical and comparative analysis of the theoretical limits of prediction, inference, and control in physical systems, focusing on the framework introduced by David H. Wolpert and its relationship to the Theory of Universe and Mind (TUM). Wolpert’s theorems establish that no inference device embedded within a universe can achieve complete and error-free prediction, observation, or control of other devices, and that mutual perfect predictability between independent agents is impossible. These results are often interpreted as formal limits on knowledge, extending earlier ideas such as the impossibility of Laplace’s demon.
The present paper argues that these conclusions correspond to principles previously articulated within TUM, where the universe is modeled as a hierarchical computational structure composed of interacting causality-control units (CCUs). In this framework, predictive and causal capacities are determined by the resolution of causality-control and perception (RCCP), with higher-level subsystems operating on compressed representations of lower-level dynamics. As a consequence, all subsystems exhibit bounded predictive power, limited memory, and partial control, while only the universe as a whole achieves maximal resolution and completeness.
The analysis further examines the assumptions underlying formal inference models, particularly the treatment of devices as independent entities. It is argued that, in physically realized systems, all subsystems are inherently correlated due to shared origin, continuous interaction, and embedding within a common dynamical structure. This challenges the applicability of certain formal premises and suggests that observed limits on prediction arise from structural and hierarchical constraints rather than solely from logical or computational restrictions.
Additionally, the paper critiques the use of highly abstract logical formulations – such as binary query models and paradox-based arguments – as insufficient for capturing the multi-scale, continuous, and physically grounded nature of real-world systems. Instead, it advocates for models that incorporate hierarchical organization, varying resolutions, and the interplay between compression and prediction.
The conclusion is that while formal results on the limits of inference are valid and significant, they can be more comprehensively interpreted within a broader framework that accounts for the hierarchical and embedded nature of cognition and physical processes.
...
This work is a chapter from the book “Reflections on Everything”, or “Listove” (Листове по всичко), which is an appendix and the second-biggest volume from the hyperbook “The Prophets of The Thinking Machines: Artificial General Intelligence and Transhumanism: History, Theory and Pioneers; Past, Present and Future”, T.Arnaudov, 2025-1.2026 – all published at the yearlong virtual conference “Self-Improving General Intelligence/Thinking Machines” 2025, organized by The Sacred Computer: Thinking Machines, Creativity and Human Development, a virtual multi- and interdisciplinary AGI and Transhumanism research and development laboratory, created in 2000. The first classic works of Theory of Universe and Mind were published between 2001 and 2004. Core ideas from the theory were presented in a lecture at Technical University of Sofia in September 2009 and in the world’s first university course in AGI at the University of Plovdiv “Paisii Hilendarski”, Bulgaria in 2010 and 2011.
The Sacred Computer: Thinking Machines, Creativity and Human Development: 2000-2026
* See references to my work in the paper and in the referred books
* Physical limits of inference, David H. Wolpert, MS 269-1, NASA Ames Research Center, Moffett Field, CA 94035, USA, https://arxiv.org/pdf/0708.1362 [Submitted on 10 Aug 2007 (v1), last revised 23 Oct 2008 (this version, v2)]
* Theories of Knowledge and Theories of Everything, D.Wolpert, February 2018
A discussion about the paper on Academia.edu: * The Asymptotic Illusion: On the
Ontological Limitations of Artificial
Agency, Mohamad Al-Zawahreh, 25.12.2025 https://www.academia.edu/s/06c854dde5
Hi, this is a common confusion - building a straw-man of Turing machines or "computation" as defined in this abstract sense, while the counterpart argument refers to the full "stack" definition of the systems, down to the lowest level virtual universes (See Theory of Universe and Mind, T.A. 2001-2004+, e.g. "Stack Theory is yet another fork of Theory of Universe and Mind", 2025). Neither computers, nor LLMs, AI (in whatever form) or whatever are "just" algorithms, "computation" etc. - they are immersed in the Universe and their implementation includes those "non-computable" parts as well. On the other hand, all these advanced thinking, theories, logic, reasoning about "quantum" etc. would have been impossible without all the science and technology, all "mechanical" processing etc., i.e. the mighty "conscious" being wouldn't have been capable to even formulate these problems and their [personal] "superiority", they would have been just silly apes. There are a lot of discussions about that in TOUM, including the latest additions in the hyperbook "The Prophets of the Thinking Machines: AGI & Transhumanism: History, theory and pioneers; past, present and future". One point which I addressed in a letter to the cognitive semioticists Jordan Zlatev: the LLMs have no consciousness, but "just" etc. [see in appendix "Reflections on Everything" (Listove) from "The Prophets"].
However I haven't read anything but my own thoughts regarding the following problem, which is valid for humans and their mind as well: WHAT[an LLM is] and WHERE *exactly* the LLM is located, why and who (evaluator-observer) sets the boundary exactly there (at what resolution of causality-control and perception) and what *exactly* it is when fully defined in order to function. It is not "just" the weights of the NN (what the h* is "NN" in the physical universe - it includes the whole hardware, all chips, all connected computers - your PC or smartphone, the routers, the Internet servers, the main GPU servers; it included the original data, the data in the memory (other representation); it includes also the *HUMANS* who interact, their biology, their states; it is a result of a chain of operations and activities of all related humans and other technologies and ultimately it requires the whole universe to be what it is.
However, this is refuted and "vulgarized" to "they are algorithmic, they are "just 1s and 0s", "switches" (the earlier nonsense about computers, still defended e.g. by F.Faggin).
No, computers are not "just 1s and 0s", and they emerged and operate in the same Universe as "humans"; besides humans are created and built also *WITH* the participation of all computers and technologies,i.e. humans are *PARTS of the machines* as well. "We are merged" without the need of "physical"/"short-molecular-distance"* way of interaction. See also an article about that in "The Prophets ..." in volumes: "Science Fiction. Futurology. Cybernetics. Transhumanism" and cited also as an appendix in the small monograph "Universe and Mind 6", which is related to this discussion.
* Another school with this confusions (or choices) is "Relevance Realization", which is explaining definitions of Theory of Universe and Mind, published more than 20 years earlier, however they put a stamp "this is not computable", "the opposite of computation", while the original [work] claims it is computable, but hierarchical, multi-scale, multi-domain, multi-precision, preemptive, has "interrupts" etc., they are built by the same fabric of the Universe computer and they interact with it and fetch "sensory" data from the common "pool". The real computers are like that, they are not the primitive and abstract strictly serial, one scale, "fixed symbols" Turing machine outputting AAABBBBBAAAAC-HALT.
---
References:
* Stack Theory is yet another Fork of Theory of Universe and Mind, T.A. 2025, SIGI-2025, https://artificial-mind.blogspot.com/2025/09/stack-theory-is-yet-another-fork-of.html
* Reflections on Everything/Listove (Листове, Листове по всичко) - a volume from The Prophets of The Thinking Machines: Artificial General Intelligence and Transhumanism: History, Theory and Pioneers; Past, Present and Future, T.Arnaudov, 2025 https://github.com/twenid/sigi-2025
See the cited excerpt from Todor's letter to Jordan Zlatev on what and where the LLMs are (it will be published as an article/paper as well), after p.340
"* Sentience or consciousness of another “entity” is in the eyes of the evaluator
* Thoughts from a letter by Todor Arnaudov to the cognitive semioticist
Jordan Zlatev , 16.8.2025"
* "We are merged..." - see my article, answering Tim Tyler's video, published both in Reflections on Everything and in the volume "Science Fiction. Futurology. Cybernetics. Transhumanism" from The Prophets ...
*Коментар на Тодор Арнаудов към видеото на Тим Тайлър „Да се слеем [с машините]“ от 10.2023
Tim Tyler: Let's merge! (...), p. ~175 in ListoveThe text in English, posted on Youtube:
Todor: IMO humans and machines - actually the technologies, the
recognizable systems, entities in the Universe (and the ones which are not
recognizable for now) are merged anyway. The human individuals as bodies,
entities are one "view", "rendering", a way of sampling of the actual intrinsic
representation of the underlying properties and processes. The same goes for
any piece of hardware, computer, robot, any object. They are what they are
under a particular sampling of the data, in another sampling they are
physically, causally, energic-based etc. connected and part of the causality,
influence, events network and interrelated. In one philosophical school
humans are defined as the set of "social relations". Also human individuals
without technology and starting from scratch with no previous culture and
language, which is also technology, are not very much more capable than
apes in the first generations, or in the first hundreds of thousands of years.
Technology, the environment and previous recorded knowledge and the
social, scientific and technological "software" that gets loaded into our minds,
all from the whole universe allow human beings to be so clever etc. So we are
part of the human-machine (technology) system anyway.
---
The distributed representation of humans and everything in a field-like form, the causal id/causal tags* theory etc. is discussed also in other volumes, such as "Universe and Mind 6" and "Is Mortal Computation Required for the Creation of Universal Thinking Machnes" at SIGI-2025.
** Note that "causal IDs" in my explanation are not referring to Michael T. Bennet's "causal identity" concept, but the match of similarly titled concepts in his fork (with unrecognized prior work) is funny.
The causal IDs in my speculations are about hypothetical information and interaction entities or signals which allow or make the wholes, beings, systems to "feel" as a whole. I derived them from the insight that all systems in all scales and multi-scales encounter inevitable lags between their constituent parts, and these lags are varied. One way of a given causality-control unit - the building blocks in TOUM - to know that a signal is from a given whole, could be by special interactions and information, these "causal IDs", which could be updated and kept active for particular reasons, e.g. a chain of particular chemical, physical or whatever interactions within given .... etc. and fade.
E.g. on the page on Github about TOUM in late 2023; most of "Universe and Mind 6" was written in the Spring of 2023 and in 2023-early 2024, but it was published as a completed monograph in 2025.
https://github.com/Twenkid/Theory-of-Universe-and-Mind
It is connected with "Is Mortal Computation Required..." (for now published in Bulgarian), and many sections from the main volume, reviewing related schools of thought and researchers, which are addressed also in the bigger volumes Irina and the second-biggest: Listove. The related part from the first reviews and discusses with details and comparisons talks and panel discussions with Joscha Bach, Karl Friston and other researchers from his school of Free Energy Principle & Active Inference, Stephan Wolfram and other "Cognitive AI"-related studies.
Listove has big chapters about theories of consciousness and panpsychism, computational neuroscience, the interaction between neuroscience and machine learning etc.
* #universe6 #UnM6 – Вселена и Разум 6, Т.Арнаудов–
#tosh3; съзнание, „метафизика“,
„умоплащение“ … Защо не съществува
истинска безкрайност и теоремите на Гьодел за непълнота нямат значение за
мислещите машини? Какво е истина, истинско, действителност и защо? Съвпадението
и сравнението като основни и първични. Резонансът като друго учение за съвпадението
и предвиждането. Защо въображаемите Вселени и вселените, построени от
универсални симулатори, също са истински и съществуват? Симулирането се отнася
за съответствие, съвпадение и предвиждане, а не за „нелъжливост“, като в категориите „фалшиво“ и
„истинско“. Първичността и значението на съответствието: големите езикои
модели, преобразителите и други по-ранни и по-късни технки не са „просто“
„огромни хеш таблици“, „линейна алгебра“, „вектори“ или „битове“ (…)
„Механичността“ във Вселената всъщност е „информационност“. … Какво е
уподобяването към човешко, антропоморфиране, защо е толкова всеобхватно –
себеплащение и умоплащение. Хипотезата за причинностните белези, „тагове“ (causal IDs, causal
tags) и наличието на особена
памет в частиците, чрез която те се чувстват или осъзнават като част от едно
цяло като при взаимодействието си предават информация за свързаността си.
Многомащабните взаимодействия и как структурите в различни мащаби могат да знаят за другите и могат ли
въобще? (…); Илюзионизъм и реализъм в теориите на
съзнанието и абсурдите на първото учение …
Болката, духовното усещане и съзнанието – усложнението заради
съществуването на състояния на нечувствителност към болка, включително вродени;
системите за усещане на болка като успоредна „паразитна“ система за познаващия
ум. Отново за липсата на обединена, неделима личност и неговото определяне и
съществуването в ума на наблюдател-оценител като вид математически интеграл на
множество от измерени „азове“/личности, в крайна сметка в безкрайномалки
околности. (…) Разпределените представяния на управляващо-причиняващите
устройства (дейци, агенти) и множеството тълкувания, зависещи от
оценителя-наблюдател. ИИ освен предсказател и компресор е и изследовател,
търсач на съвпадения и съответствия, подобрител, ученик-изменител и усложнител
като събирач на сложност: EMIL - Explorer, (Matcher & Mapper &
Modifier), Improver, Learner (…)
Дали възникването наистина е възникване? (emergence) Работата е свързана с теми от #mortal (…) и продължение на основната поредица от
класическите трудове на ТРИВ – на английски език.
Another appendix of The Prophets was just published - the content is in English and Bulgarian. Size: 123 pages (18.8.2025 edition).
* You are invited to participate, Join or help the Sacred Computer and SIGI-2025 or the upcoming SIGI-2026, starting on 1.1.2026!
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THE SACRED COMPUTER TODOR ARNAUDOV - TOSH ANELIA THE
PROPHETS OFTHE THINKING
MACHINES ARTIFICIAL
GENERAL INTELLIGENCE & TRANSHUMANISM
HISTORY THEORY AND PIONEERS PAST PRESENT AND FUTURE
by the author of the world’s first
university course in Artificial General Intelligence and the Theory of Universe and Mind
...
ПРОРОЦИТЕ НА МИСЛЕЩИТЕ МАШИНИ ИЗКУСТВЕН РАЗУМ И РАЗВИТИЕ НА ЧОВЕКА ИСТОРИЯ ТЕОРИЯ И ПИОНЕРИ; МИНАЛО НАСТОЯЩЕ И БЪДЕЩЕ
...
СВЕЩЕНИЯТ СМЕТАЧ ТОДОР АРНАУДОВ – ТОШ АНЕЛИЯ
ПРОРОЦИТЕ НА
МИСЛЕЩИТЕ МАШИНИ ИЗКУСТВЕН РАЗУМ И
РАЗВИТИЕ НА ЧОВЕКА
ИСТОРИЯ ТЕОРИЯ И ПИОНЕРИ
МИНАЛО НАСТОЯЩЕ И БЪДЕЩЕ
от авторa на първиясвета
университетски курс по Универсален изкуствен разум и Теория на разума и вселената
THE PROPHETS OF THE THINKING MACHINES ARTIFICIAL
GENERAL INTELLIGENCE & TRANSHUMANISM HISTORY
THEORY AND PIONEERS; PAST PRESENT AND FUTURE
...
[ Download from the SIGI page on Github, https://twenkid.com/agi/, Academia.edu etc. (not yet uploaded)]
ПРОРОЦИТЕ НА МИСЛЕЩИТЕ МАШИНИ
Изкуствен разум и развитие на човека:
История, теория и пионери
Минало настояще и бъдеще Тодор Арнаудов – Тош
ПРИЛОЖЕНИЕ АНЕЛИЯ
Преглед и бележки по научни работи от и с
участието на Анелия Ангелова, Пламен
Ангелов, Никола Касабов, Димитър Филев, Александър Тошев, Любомир Бурдев, Мира
Дончева, Драгомир Ангелов,Драгомир Радев, Кристина Тутанова, Руслан
Митков, Зорница Козарева, Преслав Наков, Галя Ангелова, Кирил Симов, Ани
Ненкова, Тодор Михайлов, Веселин Стоянов,Веселин
Райчев, Мартин Вечев, Светослав Караиванов; Красимир Атанасов, Стоян Михов, Петя Копринкова-Христова, Виргиния
Савова; Васил Сгурев, Димитър Добреви други от България и света по информатика,
изкуствен интелект, машинно обучение; компютърно зрение, компютърна графика и
обработка на изображения; компютърна лингвистика и обработка на естествен език;
езици за програмиране, синтез на програми, автоматично програмиране; изкуствени,
импулсни и други невронни мрежи, размита
логика и други.Обзор
на друга свързана стара и съвременна литература от тези области.
Други споменати български изследователи:
Антон Александров (INSAIT, BgGPT), Петко Георгиев, Илиян Заров, Румен Данговски
(Petko Georgiev (DeepMind), Roumen Dangovski, Iliyan Zarov (Meta AI: LLAMA);
Васил Чаталбашев, Красимир Коларов и др. От
ПУ: Георги Тотков, Христо Крушков, Христо Танев; Димитър Благоев, Васил
Василев, Александър Пенев и др.
СВЕЩЕНИЯТ СМЕТАЧ МИСЛЕЩИ МАШИНИ, ТВОРЧЕСТВО И РАЗВИТИЕ НА ЧОВЕКА
Целогодишна виртуална конференция „Мислещи машини 2025“, или Self-Improving General Intelligence 2025
– SIGI-2025. Продължение
на може би втората най-стара международна „конференция“ за универсален
изкуствен разум (AGI):
SIGI-2012-1,провела
се присъствено в Пловдив през 2012 г.
THE SACRED COMPUTER THINKING MACHINES,
CREATIVITY AND HUMAN DEVELOPMENT
Обзори на някои
тематични раздели освен конкретни български учени
* Компютърно зрение и обработка на изображения в
различни приложения: самоуправляващи се превозни средства, разпознаване на
образи и класификация и др.
* Машинно обучение, изкуствени невронни мрежи * #Vision
Tasks #Vision-Language Tasks #Зрителни задачи Изброяване на задачи от
компютърното зрение
* Други статии по съвременно разделяне на изображения свързани с работи на
Анелия Ангелова и Александър Тошев; Мира Дончева и др. – Current Image
Segmentation #segmentation
* Невроморфни системи, импулсни невронни мрежи: Никола Касабов, Пламен Ангелов
* Размита логика – Димитър Филев, Н.Касабов, П.Ангелов и др.
* Класически трудове по разрешаване на многозначност чрез използване на
контекста и корпуси – Word Sense Disambiguation WSD, Context, Corpus
Linguistics
* Ранна работа в статистическата езикова обработка,
корпусна лингвистика, извличане на данни, групиране и др. над големи обеми от
данни и Интернет – Драгомир Радев; Зорница Козарева и др.
* Компютърна лингвистика и обработка на естествен език със статистически методи
и машинно обучение – Кристина Тутанова, Зорница Козарева, Драгомир Радев и др. * Първопроходна работа на Руслан Митков и школата му в
компютърната лингвистика – разрешаване на анафори, подпомагане на превода чрез
лексикология/лексикография и преводна памет.
* Школата на ПУ Паисий Хилендарски в Компютърната лингвистика от края на
1980-те и 1990-те и след това – морфологичен анализ и други видове разбор и
моделиране на българския език, лексикология и лексикография, машинно обучение и
извличане на структури (групиране, клъстери), извличане на информация; анализ и
синтез на реч и др. – Георги Тотков,
Христо Крушков, Христо Танев, Зорница Козарева, Атанас Чанев, Димитър Благоев;
Тодор Арнаудов и др.
* Бележки към конференцията по Компютърна лингвистика CLIB 2024 в София * Мултимодални пораждащи модели #multimodal #мултимодални * Programming languages, program synthesis &
verification, compilers and code optimization, formal verification, static
analysis, interpreters, concurrency… #programlanguages #programsynthesis –
Програмни езици, синтез на програми, верификация, оптимизация, интерпретатори и
компилатори … – Веселин Райчев, Мартин Вечев, Светослав Караиванов; Васил Василев,
Александър Пенев и др.
* БАН – група по невроморфни системи; история на ИИ в България и др. – Петя Копринкова-Христова
и др.; групи по крайни автомати и др. (Стоян Михайлов), обобщени мрежи –
Красимир Атанасов; исторически: В.Сгурев; свързани с определения на общ ИИ:
Д.Добрев и др.
* Бележки за ЕЕГи
за българския принос в техники за изчистване на шума при снемане на ЕКГ(EEG, ECG) – Чавдар Левков и
др.
* И др.
* Виж за други българи в някои от тези и други области като роботиката, която е
една от „българските“ области подобно на компютърната лингвистика и в
нея има няколко пионери в епигенетичната роботика (роботика на развитието);
философията и когнитивната наука,
конекционистки системи, симулации за роботи, учене с подкрепление; други
пионерни работи в България от ТУ София и др. в основния том; приложение Лазар и др. (…) Езици: български и
английски | The
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