Causes and reasons for human actions. Searching for causes. Whether higher or lower levels control. Control Units. Reinforcement learning.

Analysis of the meaning of a sentence, based on the knowledge base of an operational thinking machine. Reflections about the meaning and artificial intelligence.

Part 2 of 4 - Comment #1 and a part of #2 of:

Part 1 (и български): http://artificial-mind.blogspot.com/2010/01/semantic-analysis-of-sentence.html

One of the milestones of my AGI research. I wrote this particular article and the comments in Bulgarian as a 19-year old freshman in Computer Science at Plovdiv University.

By Todor Arnaudov | 13 March 2004 @ 21:49 EET | 340 reads |
First published at bgit.net and the e-zine “Sacred Computer” in Bulgarian

Comment #1 by Konstantin Spirov | 15 March 2004 @ 20:25 | EET

(…) I'm a classical programmer and I haven't really dealt with AI. However I reflected about how I would define “meaning”.

To me, the thirst and urge for finding a meaning does not prune contradictions, in contrary – it's searching for the cause, for the prime mover, the initial force. This is not related to contradictions.

For example, a tawdry clock with a thermometer is not incompatible, contradictory – it can hang on the wall, and neither the clock, nor the thermometer disturbs the other. However, to me this object is pointless, meaningless – you can't tell me any reason to put it on the wall.

On the other hand, the opposite phenomenon happens every day. People do absurd things, which however appear to be full of deep meaning. Programmers sing - out of tune... A banker who owns millions and visits luxury restaurants once passes next to an old lady who is selling donuts; then he takes one from a dirty bag and buys a donut for 30 cents. No doubt this donut was made by a poor snotty baker, but... For the banker, this is the best food and the best thing in the world!

There we are! For him, this is an act that is filled with deep meaning, but how would you persuade a computer program? Especially if the program is counting the number of viruses and bacterias that has entered the banker's organism in that very moment. How does the banker would explain it - “I felt a thrill, I remembered once when I was a child...”. From the viewpoint of the computer, this is a non-sense, just a random association – especially if from this little moment eventually grow up a serious decision for his life and career; how would you explain to a computer what's in common between the donuts and the money?

As we know, AI has many directions – the most of the researchers belong to the “weak” one, that is – not trying to model an AI, but just aiming to make the behavior of the computers to appear human, in order to make the life of the users easier – nothing more. These researchers discuss like this – the problem is complex and often vague, but we know tricks that would help us to cope it very well – we just have to spend some time and be more …. There are also researchers from the Strong direction, like the respectable Marvin Minskyor the clown prof. Kevin Warwick (sorry if you like him), who are aiming at goals which are much more interesting for the media. Some of them probably do, because of problems with funding, others do really believe, because this sounds more heroically.

I personally support the Weak AI and I think that the questions posed in this article very precisely describe the reasons – you can model non-contradictory system, learning and even something that looks like freedom (at least external unpredictability), but I cannot imagine how the thirst for a meaning can ever be modeled.

Scientists can invent any formal systems, to analyze and replay words, but we cannot give them a meaning (“да ги оглосим“ - an ancient Bulgarian word used). The meaning is a deeper concept than us, it is discussed by the ancient Greek philosophers. The whole human civilization from all the times deals with the meaning. (…) In the bible “слово“ (logos) means also meaning, cause. … “Logos“ - the First Cause, which can't be understood or explained (…other stuff about another explanation of a cat and an uphill about a real cat that has gone wild; usage of “to drink” in a metaphorical sense (to drink a stone with a gaze), hard to translate an not relevant:

P.S. за "котката и нанагорнището" ми хареса. Замислих се, че мога да дам неизчанчено обяснение за него. А компютърът - не.

Та сетих се, че за мен "котката изпи камъка и литна под нанагорнището" си е съвсем смислено изречение. Всеки, който си има котарак знае, че те са загадъчни същества и имат странни способности. Освен това мога да докажа, че съм виждал веднъж как котката пие камъка и лети под нанагорнището. Беше миналото лято на Варна. Тъст ми и тъщата ми си имат виличка на 30 километра от града, в една сушава местност с изглед към Варненското езеро. Пълен пущинак. Вилата име с картонени стени и се състои от две стаи.

Участникът в действието не е "котката", а една конкретна котка - котаракът Марти. Всяка дама би казала, че е и мил пухльо, http://polly-and-kosio.net/_predi/pages/bulkata_s_mama_i_tatko_jpg.htm, и в същото време, когато попадне в своята среда - той се превръща щастлив и див кръвопиец. До вилата има едно дере - когато Марти отиде на Варна, в него се събужда Хищника. Веднага избягва в дерето и по цяла седмица оттам не се чува нищо друго освен воя на вълците, лаенето на кучетата и крясъка на птиците. Точно, когато "родителите му" (тъст ми и тъщата ми) са изгубили всяка надежда, че ще го видят отново, той се завръща горд, с чувството на победител, ветеран, преживял своята неразбираема война.

Та изречението: "котката изпи камъка и литна под нанагорнището" много точно описва, какво се случи последния път, преди да изчезне в дерето. Зад камъка стоеше Иванчо, моят син, който току що беше проходил. Откакто "навлекът" бе там, Марти не получаваше достатъчно внимание. Преди да избяха на хълма и след това да литне под нанагорнището (към дерето), Марти за последен път изпи със завистлив поглед камъка, зад който се криеше Иванчо.

Regards, Kosio

#########

Comment # 2 by Todor Arnaudov | 18 March 2004 @ 21:58 EET | 0

Control Units, Causes, Goals, Achieving goals of a Control Unit == Pleasure

“Reasonable behaviour” - a search for local maxima of alterating and changing functions of expected pleasure and many more

[In brief, the concept of "Control unit" or CU means something like a causal force, it's more complex, but explanation is in the bigger theory of Universe and Mind to be translated.]

Thanks for the opinion and for the opportunity to post some more reflections on the topic... (...)

I agree that “meaning” has other meanings in different contexts and circumstances. E.g. “a purpose”, “goal”. “There is no purpose” means that I don't have a reason to do it, there is nothing that I want to achieve, linked to this “item”. With “reason” or “cause” - you cannot find a cause that could cause you to do this particular thing.

However, the first, primary causes are something with many features, as well. E.g.:

I feel thirst, I want to drink some water. Then, my goal becomes “to satisfy” my thirst. Then I start to search for means to achieve this goal in the possibly closest spatio-temporal area around me. I found this location is the sink, which is a few seconds away. I'm moving my chair a bit, get up, walk, open the door, pass through the corridor, open another door, turn around, take a cup, put the cup under the fountain, catch the tap for the cold water with my right hand, turn it; water spills; the cup gets filled, I turn the tap back; bend my hand back; prepare my mouth to drink; bend the cup, spill its content in my mouth; swallow....

Ready! The thirst was satisfied...

Machine: Why did he drink some water?

Human: Why, really I did?
Inpatient one: Because he was thirsty... It's obvious!

Machine: I don't think so. Why not the cause to be that because one or another Nuclear World power DID NOT send Hell just a moment before, so that he couldn't drink? Or why because there WAS NOT an earthquake etc. [Right, this is also because of Occam's Razor, complex examples – 2010 addition, but the point is that there are zillions of possible reasons and causes, and we're pruning them because we're searching for simple explanations.] There are simpler meaningful possibilities – if on the table next to him there was a bottle of a juice or another soft drink, he might haven't drunk water, but this beverage. In the situation's definition, it was not told that there was not such a bottle. This is an assumption, you don't even think that it is possible.

So it is possible that there was a bottle of soft drink, a Coke, and he has realized in this very moment, that those kind of soft drinks cause bad teeth and he has recalled the visit to his dentist. This is not mentioned in text, but it is not denied either.

And why not say that he drank water, because:
- He is a human? Or because...
- He is a living being? Or because
- It was hot? Or because...
- There was a schedule of the water supply, and in this very moment there was water in the tubes. Or.. because not him, but his throat was dry then!!!  //[dried then.] !!!! пресъхнало

Or because last day he did forget to fill the bottle that he keeps next to the computer.
And the reason, the cause not to fill the bottle was that previous night he was too much into commenting in an Internet forum. The reason to be so concentrated in this forum was that...

And so on... You, poor humans, there are endless number of possible reasons, not just those simple one, that you short-sighted humans see next to your nose.

Impatient one 2: Shut up, you stupid piece of metal. What the heck you know? You're a machine, machines can't think... Everything is formalized in you, so you're stupid. And there was a sentence... the more you know, the less you know.... Errr..

Impatiant one 3: He drank water, because he was thirsty. It's so simple!

Human: It seems so, because when one is searching for reasons, for causes, he is limiting the space of the search the way that fits his own desires in the particular case. If one has read “He wanted to drink some water”, the first and easy plausible explanation we see is written in direct words. Immediately, while one is creating the virtual world of this situation, he is setting precomputed, biased reasons, based on his initial impression. Then, when one seems to search for the causes, he finds them immediately – nice and easy, there are right there in the root of the search tree..

Impatient one 2: Did you believe this machine? You shouldn't! Never be persuaded by a computer, no matter as smart it seems to discuss. No matter how it appears to be, it cannot think, because it doesn't have a soul. I don't know what exactly a soul is, but .. Blah-blah...

Human: But you cannot drink water, if there is no a sink and a tap. The reason and cause he drank water was both his desire and the existence of a mean, a source to achieve its goal!

Machine: Good. And why did he bend your arm before he drank?

Impatient one: Why... In order to drink! You are so dumb!

Machine: But the arm doesn't know what is “to drink”. It is just a lever. He bended his arm, because his brain instructed the arm to bend. But this instruction was sent, because the human decided to drink, without bending the whole body and drink directly from the water jet. And there could be a reason not to do it, because he has a trauma in his back.... Why did he have the trauma? Because a few days ago he attempted to lift a too heavy weight; he did, because he wanted to practice, because he saw his girlfriend looking too much strong men's asses. Therefore, if we stop the search for a cause right here, then the reason, the cause that the man has bended his arm was his girlfriend, and her looks to the strong men's asses. However, why not saying that those strong men are the reason? The woman wouldn't look them, if they didn't exist. Or they muscles? The mere existence of muscles. Or these specific circumstances – in a specific moment they met strong men in the park, the woman looked at their asses, the man was jealous, he tried to lift heavy weights in order to practice, then this caused a trauma to his back, then he wanted to drink some water, and he used to bend his back and drink without a cup, but this time he couldn't, so that's why he bended his arm...

The conclusion is that there are many and many possible reasons and causes that are actually true in the same time, because the reason and cause for every event could be assumed to be everything that has happened, and depends on the moment we decide to stop and simplify. In the total, common cause there is no meaning – there is no specific reason/purpose/meaning/cause. The intelligent beings make sense and choose causes/reasons/purposes/meanings, based on their knowledge (and aim; knowledge = their biases/structure/configuration/state/development...).

(The intelligent beings are fitting reality to their virtual reality - fitting the laws in their virtual worlds to the laws they assume to be laws to the real world, comment from 2010).

Impatient one: The question was, what the brain has instructed the arm...

Patient one: Why what the brain has instructed? The cause the arm bended was that the muscles bended, then they pulled the bones, which are supporting the soft tissue of the arm and the hand, which is holding the cup.

Machine: Human call “reasons/causes/purposes” those ones that he himself, in particular, has accepted to call “causes”. In this specific case – the first items that appear in his mind. The first items that appear to a mind are his thoughts and feelings, linked to a particular event he recalls. And if a plausible enough cause/reason/purpose is found (usually “enough” is really a small ammount), the search is concluded and the searcher doesn't ask for more.

Patient: I see, but I'm tired already...

Konstantin: (…) There we are! For him, this is an act that is filled with deep meaning, but how would you persuade a computer program? Especially if the program is counting the number of viruses and bacterias that has entered the banker's organism in that very moment.

The persuasion depends on the both sides. If nobody can persuade you to do something means this only this, not that a reason/cause/purpose to do what he want you to do does not exist at all. If a man wants to do something, the most frequent reason he finds is... because he wants! Usually one doesn't know why he wants exactly this, or if he knows a little, he can “prove” it with explanations like “I want it, because I like to do it!”, “I enjoy it” or so. If, for some reason, one has to explain it in a more persuasive way, usually one searches for a plausible explanation why would someone want to do it and why would do it. If one doesn't want to do something, he says “I don't like to do something” - and always can find a reason why he don't want to do it.

If this imaginary program is intelligent, it could easily find many explanations.

Imaginary_AI: What a dummy program would deny that the act of the banker was meaningless? This banker, this is the richest man in Bulgaria and according to statistics, a few months later he has considerably enlarged his wealth. That means, he has reached a higher local maximum of his wealth (see below). Therefore, according to the behavioral model of his virtual control unit (see below) and the statistics, he has selected reasonable/meaningful actions and has taken good decisions in his spatio-eventual(based on events)-temporal region. His actions and decisions has led him to his the goal, which easily can be implied as “possessing more money”.

Imaginary_AI: There is no reason not to accept that buying the donut was not a part of his strategy to reach the general goal “being wealthier” (for example, it made him feel good, you give yourself such an explanation), because all and every actions and events, happening to a person, are linked and related to the way he thinks/reasons and to his following actions and decisions. All actions, done with a desire of the virtual control unit itself, intentionally and not forced - are meaningful and reasonable to itself. That means they are target actions, goals. Usually such target actions are caused by specific desires, initiated by a search of local maxima or high plateaus [of a reward]. My living friend will explain you this stuff below. [Reinforcement learning.]

Konstantin: To me, the thirst and urge for finding a meaning does not prune contradictions, in contrary – it's searching for the cause, for the prime mover, the initial force. This is not related to contradictions. For example, a tawdry clock with a thermometer is not incompatible, contradictory – it can hang on the wall, and neither the clock, nor the thermometer disturbs the other. However, to me this object is pointless, meaningless – you can't tell me any reason to put it on the wall.

It is possible that no one can tell you a reason to put in on the wall, because you think that it is tawdry and apparently this is "bad" and undesirable to you. Indeed - contradictions have to be searched and checked in the whole memory - of the evaluating unit (the agent, the human) together with the environment. [All history and possible relations.]

For example, one can find bad memories, related to such objects. [Which one does not realize, but they are fixed in the patterns of his mind.]

Konstantin: On the other hand, the opposite phenomenon happens every day. People do absurd things, which however appear to be full of deep meaning. Programmers sing - out of tune... A banker who owns millions and visits luxury restaurants once passes next to an old lady who is selling donuts; then he takes one from a dirty bag and buys a donut for 30 cents. No doubt this donut was made by a poor snotty baker, but... For the banker, this is the best food and the best thing in the world!

I don't think that any action or decision of any control unit is actually "absurd".

An evaluator calls it "absurd" when he or it doesn't really know the model of control unit's behaviour, or when the evaluator assumes that it knows how the evaluated unit/being "should behave" in a given situation.

However, if something unexpected or thought to be absurd/impossible has happened, it is apparent not that it is "absurd", but that the evaluator was WRONG. Either his model is wrong/not precise enough/confused or it could be precise, but it lacks the data required to make correct, complete and precise predictions.

If any Control Unit does anything, it has a particular meaning/reason/cause/goal behind it, even if it can be vague or unintelligible for an external evaluator.

The meaning/reason/cause is specific, it belongs to a particular working Virtual Control Unit. It is not a generalization, it is not a set of rules, written in a textbook. This is a specific model of something, that runs somewhere

The meaning of "meaning" right here is a GOAL. Any action of a Control Unit (CU), done because of instruction given by itself alone (and not forced by external CU, e.g. moving a hand with a wire) is tautologically target action for this Control Unit, and it displays the urge of the CU to achieve the "purpose/meaning/reason" of it to exist, according to its own understanding about what its goal is in the moment of decision. [Here "its own understanding includes also implied in the specific construction/architecture/the way the device/being works]

See my Teenage Theory of Mind and Universe for more. To be translated and published... http://research.twenkid.com

The purpose - the GOAL - especially for the compound CU is changeable and the more complete information about the exact event and circumstances we have, the more precise that GOAL could be guessed by an external evaluator.

A human are individuals in the sense that its indivisible - indivisible is what he understands "he is", but even theoretically he is incapable to know or understand exactly why it does what it does with the maximum possible resolution of control.

I think human [can be modeled as it...] is a complex of Control Units (virtual computers, simulators), where each of them is aiming at completing at maximum precision its program, the purpose of its existence (it's implied by its architecture and operation).

An indication of reaching to a goal of behaviour - finding of an optimum in the learning function - is the feeling of pleasure.

When a Control Unit detects that it has reached the goal, it “feels pleasure” and aims to fly about this part of the graph of its [reward] function.

Therefore I believe that human mind can be built as a mixture, a system of multilayer [hierarchical] control units, where each CU at a higher level controls with a lower resolution that the one below. The higher level control unit controls more imprecisely than the lower one.

For example, the top level of control sends a command with a length of 16 bits, while the description of the precise action to be done requires 128 bits or even... 2^128 bits. The details, the rest of those bits - 112 or 2^128 - 16 are actually completed by the "controlled" unit.
(It only seems that it's controlled, because the action is more dependent on its operation that on the operation of the top unit. [When the evaluations is done, evaluator probably usually starts from the top level, giving it “will”, initial cause... - comment from 2010]

(See "Abstract theory of the exceptions of the rules in computers", to be translated and published... http://research.twenkid.com )

A more specific example:

They say, that we can consciously control the moves of our fingers. Therefore our mind, our conscious can cause the finger to move...

Really?

We are free in the sense that when we think that if we want "I'll bend my finger right now!", then the miracle happens - exactly that finger bends. It seems that it moves, because of our free will. (This can be interpreted also as a coincidence, a match, and not a real control (causal relation), in terms of other articles from my theory from the time – comment from 2010).

This is power and control. However, in order the finger to bend in the reality and not just one to notice it in his mind, an enormous amount of information needs to be sent somewhere.

Not just selection of a finger (say 20 or 30 bits) and a definition of the a momentum, how strongly to bend the finger or so - this is just a virtual definition of a finger in our minds!

In the reality, the information that needs to be "entered" in order to execute that simple action includes the exact description of the precise movements and changes in every single particle that builds the finger, with the maximum possible resolution of the Universe.

Every single particle has a particular acceleration and it is in a particular place. Mind doesn't posses all that information and it can't, because it doesn't control in the strong sense of the world.

"Control" in its strong sense means with the highest possible resolution of control. [In the given environment/world/virtual world].

So measured as an amount of information, the cause of the movement of the finger is contained more in the finger itself than in the mind, the apparent control unit, because the description of the finger and the muscles that are acting on it is much longer than the description of the simple abstract instruction that we can realize and control [consciously].

Each CU assumes that it is the cause for the events to happen, that it is "free" and does what it wants, because each CU is similar to the only really free Control Unit - the whole Universe; it includes all details together. The whole Universe controls in the strong sense - what it "wants" happens, because it defines what is possible or not, and executes what's supposed to.

However, not every CU is complex enough in order to declare "I do control". Human mind is complex enough to do it, but actually the body is what controls it, not the reverse. The conscious can embrace only a part of the causes for its own existence, and no matter how hard it is searching for the deep ultimate causes of its own actions and decisions, it can't reach to them.

This is the free will, the freedom. The Control Unit (a human mind) cannot find the causes and reasons for its behaviour in the way [the precision, the domain ...] that it assumes that it should, if they had existed, and that's how the control unit proves that its own behaviour is free and unpredictable not only for an external evaluator, but universally.

Also, this is a convenient conclusion, when the CU intentionally aims not to find proves for the predictability, because one of the major goals of every CU is to feel as a MASTER. No matter how simple or complex (built by many simpler) the CU is. CU aims to feel as a MASTER and not to put this in doubt. CU are similar to Universe and they aim to be like it.

TO BE CONTINUED.... with part 3/4

http://research.twenkid.com
http://artificial-mind.blogspot.com
http://eim.hit.bg/razum (Bulgarian)

Other keywords: Universal AI, Twenkid Research

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Semantic analysis of a sentence. Reflections about the meaning of the meaning and the Artificial Intelligence

Analysis of the meaning of a sentence, based on the knowledge base of an operational thinking machine. Reflections about the meaning and artificial intelligence

By Todor Arnaudov | 13 March 2004 @ 21:49 EET | 340 reads | First published at bgit.net and the e-zine “Sacred Computer”

Оригиналът на български: http://artificial-mind.blogspot.com/2008/02/2004.html или: Анализ на смисъла на изречение въз основа на базата знания на действаща мислеща машина. Мисли за смисъла и изкуствената мисъл. Една от основополагащите ми статии от тийнейджърските ми години. Тази е от късните, продължава с два дълги коментари, добавки, включващи и размисли върху принципи на ученето с подкрепление (reinforcement learning)

Included in “Unverse and Mind 4": a search of the meaning (http://eim.hit.bg/razum, in Bulgarian only yet) Finally I started to translate my old articles, including my teenage Theory of Mind and Universe - all were milestones of my AGI research. I wrote this particular one as a 19-year old freshman in Computer Science at Plovdiv University.

• Natural Language Processing, NLP.
• An example of a search through the linguistic knowledge base of the author.
• Many different meanings of "meaning" defined for different uses.
• Quasi-formal semantic analysis - from words to chunks (expressions) to clauses to complex sentences. A search for relations, links.
• Criticism of the usage of short ambiguous sentences as a way to explain the "impossibility" of creation of an AI and machine translation; the lacking context is filled by human imagination and could be filled with machine's imagination. A discussion about the artificial pruning of the set of interpretations that humans are doing when translating or interpreting, and the implicit denial of expecting unknown meanings.
• Thought experiment of how a 3-year old toddler boy interprets unknown sentence (tme flies) and how does he search for a meaning and maps meanings to his senses. It is told as a real story, what he knows, what he experiences and what he would experience if...
• The style in not really academic, there are some dialogues, discussions with a virtual opponent, when this is appropriate to display human biases.
• Others...
• Continues with long comments with additions about reinforcement learning and other topics (to be translated and linked)

Part 1 (и български):(This Post) Semantic analysis of a sentence. Reflections about the meaning of the meaning and the Artificial Intelligence 

Part 2 (и български): Causes and reasons for human actions. Searching for causes. Whether higher or lower levels control. Control Units. Reinforcement learning. 

Part 3 (и български): Motivation is dependent on local and specific stimuli, not general ones. Pleasure and displeasure as goal-state indicators. Reinforcement learning.

Part 4 : Intelligence: search for the biggest cumulative reward for a given period ahead, based on given model of the rewards. Reinforcement learning.

Some of the conclusions:

• More complex (smarter) the system – More Meaningless the Meaning

Because the interpretation depends more on the system.

• „What is possible to be done with” is yet another meaning of the concept of “meaning”.

Happy reading and enjoy the story of the little Johny and the flies that are flying around the watch... ;)

BEGIN...

This article starts with the definition of “meaning” of a friend of mine, Ilian Georgiev, we shared thoughts an year ago.

Meaning/Sense (Ilian Georgiev's definition): Meaning of a sentence (a thought) is a function that searches for controversy between the knowledge base of the evaluator (the one who thinks) and the thought being analyzed. All elements from the knowledge base and their connections are juxtaposed with the new thought, the one that is analyzed. If any of the elements of the thought has a connection with another element, and the connection cannot be found in the knowledge base, then the sentence is classified as a non-sense (has an error).

Using this definition, let's search for the meaning of a weird sentence, that I made up don't know how. I'll use also a made-up semi-formal syntax of NLP analysis, that you'll grasp on-the-fly.

(The original paper is in Bulgarian, and the author is not a native English speaker; it is possible that there are some mistakes in some of the senses used.) SENTENCE = “The cat drank the stone and flew out under the uphill.” ИЗРЕЧЕНИЕ == "Котката изпи камъка и литна под нанагорнището."

SENTENCE == SENTENCE_1 + SENTECNE_2 (clauses)

SENTENCE_1 == "The cat drank the stone" 

- Agent_1 == The cat

- Action == drank 

- Object == the stone

SENTENCE_2 == "Литна под нанагорнището". 

- Agent + Preposition + Object --

- Agent_2 == Agent_1 - Preposition == under - Object == the uphill Basic syntactic parsing check passes. Moving to the Semantic Analysis. 

  Semantic Analysis

This is a quasi-formal sample semantic analysis, using author's personal linguistic knowledge base An improvised approach 1. Word-by-word semantic analysis "Котката изпи камъка и литна под нанагорнището."

The cat drank the stone and flew out under the uphill.

Do I know what does mean:
 -- the cat -- :: YES, a defined “cat”, I know what “cat” means
 -- drank -- :: YES, pass tense of the verb “to drink”
 -- the stone -- :: YES, Noun, ...
 -- и -- :: YES, Conjuction
 -- flew out -- :: YES, Verb, past tense
 -- under -- :: YES, Preposition
 -- the uphill -- :: YES, Noun

This stage passes, connections are found in the knowledge base.

2. Chunks, Expressions, Multi-word Semantic Analysis

2.1. Two words, except cases where the first word is Noun and the second is a Conjunction.

– the cat drank ...- YES (AGENT + VERB)
-- (Someone) drank the stone - YES (AGENT + VERB + NOUN/OBJECT)
-- and flew out -- YES (CONJUNCTION + VERB)
-- flew out under -- YES (VERB + PREPOSITION)
-- under the uphill -- YES (PREPOSITION + NOUN/OBJECT)

Passed.

3. Semantic analysis of the clauses and the whole sentence. "Котката изпи камъка и литна под нанагорнището." Let's analyze all the clauses, this would give clues for the meaning of earlier clauses and the whole sentence.

„The cat drank the stone” Is "the cat" linked to the verb “to drink”? - YES. What are the links? - Usually “to drink” is linked with objects, which are linked to liquidity or semi-liquidity of a substance. In general, in the definition of an object, that is linked to the verb “to drink”, usually there's a morpheme or semantics of liquidity.

“Liquid” is linked to:

1. Flow
2. Run
3. Stream down
4. Roll down
5. Trickle down
6. Pour out
7. Pour into
8. Infuse

... „To Drink” is linked specifically with:
1. To drink + water.
2. To drink + juice.
3. To drink + tea.
4. To drink + cold tea.
5. To drink + alcohol.
6. To drink + beer.
7. To drink + wine.
8. To drink + scotch.
9. To drink + vodka.
10. To drink soup. ...

The examples are checked easier if they are put down in a unified way: Verb + Object/Noun for quick comparisons. I don't know whether to check the general concepts/meanings first (like liquidity), or after all specific cases are checked first (as colocations, like “drink vodka”). „Drink” is used in some other cases, where the object is not a liquid.

1. Drink some poison.
2. Take a pill. (Take == Drink)
3. Take a medicine. (Take == Drink)

In this cases the object is:
1. On the surface of a liquid.
2. Floats in a liquid.
3. Dropped in a liquid.
4. Sunk in a liquid.
5. Absorbed in a liquid. The most common meaning of “to drink” is linked with an AGENT which is a living being. Living beings have a throat, where the drunk object passes. The liquid assists the object to pass through the throat, when the object is not a liquid itself. I recall an idiom (Bulgarian, this is a literal translation) "A duck has drunk his sense."

So, what about the linkage between “to drink” and the object “stone”? Stone has direct links to verbs as "to throw” and “to crack” and similar, “to kick” and others. Direct links are examples of usage which I have ever encountered in texts or speeches. „Stone” can play different roles: AGENT (subject) or an object, that clarifies/specifies an ACTION, done by another AGENT. Is it possible to drink a stone?

One can assume also, that if something is said, then this is a special kind of stone. If a meaning should be found in any price, it is possible for the searcher to invent meaning that matches the given sentence. It is possible also to add additional sense, using experience, so that the sentence that is “meaningless” up to now to get its explanation. This point will be discussed again later.

STONE, without a preposition

1. Kick a stone
2. Throw a stone
3. Push a stone.
4.... Lift, Roll, Hit, Crack, Break, Catch, Leave, Heat, ….

Etc... but “To drink a stone” is lacking.

However, this doesn't make the sentence meaningless, yet, because it was found above, that “drink” could be linked to objects which are not liquid, and in this sense, “to drink something” is a reference to “to swallow something” (to pass it through the throat) Drink == Swallow

Therefore: “The cat drank the stone” == “The cat swallowed the stone”

Therefore this clause makes sense according to my KB. Next clause: "...flew out under the uphill" Cat + fly?... No basic connections... Cat + jump, scratch, bite, drink, eat, … push, walk, run, fall, hide, pull, climb, jump over, hit, meaow, stalk, ... „Jump”, “Jump over” and “fall” captured my attention:

"Jump” is an action where the AGENT reaches to a state, where its body doesn't touch the ground.

It is the same for “Fly”. Therefore, “to jump” partially covers the meaning of “to fly”. Besides, I know examples of “flying” where to fly is used with the sense of “to jump” - directly or implicitly suggested by the context.

“Air Jordan” (in Bulgarian - "Въздушният Майкъл Джордан.") The basketball player Michael Jordan jumps and stays in the air for long enough to impress people more than the typical jumpers, this has caused his jumps to be linked with the morpheme “air”, which is used in words for flying (airplane, air force).

Therefore “(the cat) flew below the uphill” can be interpreted as:

(the cat) jumped below the uphill. Now, is it possible “jump” to be used with “below”. Can you jump below? To.. - Jump over s.t. - Jump into - Jump out

...

No “jump below”, but it doesn't mean that this expression is meaningless. (Actually there is jump below something, but say, not jump below the uphill) „Jump” has other meanings, like: doing something faster than usual, or moving fast. So... “[The cat] flew below the uphill” may mean:

[The cat] jumped below the uphill? Is it possible to jump below an uphill? Why not?

Uphill is an object, it can be located in а mountain, but we can imagine it to be any other object, over which somebody can move “up”, walking on. This “uphill” object can be made of wood or metal and can have a hollow inside, where a cat can hide.

The cat jumped under the thing, that had an uphill over itself... The whole sentence can turn to: "Котката изпи камъка и литна под нанагорнището." "The uphill had a hollow inside. The cat swallowed the stone and jumped below it. The additional clause fills up the uncertainty in the scenario.

Another interpretation, based on “to fall” could turn: "...flew below the uphill" to “..felt below the uphill". Also, “below the uphill” may mean below the part of the uphill, that is steep, i.e. just before the uphill starts to climb. Then: "The cat swallowed the stone and felt below the uphill." This gives a rise of another interpretation – stone is often linked with “heavy”. There is a proverb (Bulgarian) “Hang a stone on my neck”. Then: "The cat was climbing the uphill, but it swallowed the heavy stone - it threw it down below the uphill...” Or: While the cat was climbing the uphill, weird little balls felt down from the sky. They seemed like meet balls and smelled the same way. The poor cat was tired of hunger and the hard walk, and she bit one of the sky meet balls. A moment after she was frightened – the meet ball appeared to be as heavy as a stone. The cat was rolling down, until she stopped on the flat land under the uphill.

When searching for a meaning in very short pieces of information, such as single sentences, it is expected for the mind to invent, to imagine in order to fill up what is unknown with probable sets of circumstances. If the source doesn't deny, we can invent any plausible imagined circumstances. Short sentences as a way to deny creation of AI Actually, one very rarely meets single sentences in the reality, out of context to constraint and direct translation or interpretation of the meaning. However, short “nonsenses” – which one cannot interpret unambiguously or are often used to disprove the possibility of creation of an AI. Let's check out a classic from the NLP. Time flies. "It's so hard to translate to another language!”

How would we translate it in Bulgarian? "Времето лети" (Vremeto leti - The time is flying) or „Времеви мухи" (Vremevi muhi - Flies which are related to time)

Or another way - "time" doesn't mean only “time”, and “flies” doesn't mean only the little flying bug. These are just the first two items that came up to my mind! The search was obviously had been pruned up to two items, two possible interpretations.

This kind of unconscious pruning, limitation of the number of variants, will be discussed below.

Virtual Colleague: “The time is flying” is the correct translation. There's neither such an expression as “flies, related to time”, nor any other.

Author: Why do you think so?

V. Colleague: The other translations don't make any sense. Me myself, I would translate it that way, I think I'm good enough in English. Check out my personal web page. 

 Author: And why would you translate it that way? 

 Colleague: Because... I haven't heard of an expression meaning “flies, related to time”... 

  Author: Therefore you have excluded the possibility to hear a new sentence, where this expression is used in a meaning that was unknown for you before? 

  Colleague: Well, I think so... 

  Author: Who did tell you that sentence? 

  Colleague: I'm not quite sure... You? But... Well... It is possible that this is an idiom. Can you explain it to me? Maybe this is a special kind of flies? Or more likely... (What a SF fan I am not to guess this one!) Flies through time! Time travel! The ambiguity is caused by the lack of a criterion for pruning. Until the moment when an action is executed – an action caused by the input data, which are said to be ambiguous – the ambiguity is not an issue. The system can remember the whole sentence, word-by-word and until the moment of action, a decisive single action, it is known that all interpretations are possible.

And when the action should be done, e.g. a robot to capture the right cube or the middle cylinder – then the system should use an additional feature in order to disambiguate, to choose. However, since the input is not decisive, but ambiguous, then turning any of the interpretations to action is not a “mistake”, regarding the input.

Perhaps the Natural Language, or as the author calls it – The Language of Mind – allows ambiguity, because there are many “correct” possibilities. There are many cases, where each of the possible solutions/interpretations is “right” in the sense that the device (human) who took the decision continues to function after executing in effect, for real, an action, caused by the given interpretation.

So, if a given system continues to function – according to a given definition of “functions”, e.g. its heart continues to work at least for so-and-so long period after executing the given action – then this action was “right”, i.e. this action is assumed to have had followed laws that don't lead to malfunction. More complex control units have larger space of correct decisions, they have wider “freedom”, i.e. possibilities for future actions, after which they will continue to function right.

(see … @ quote “Conception for the Universal Predetermination”, a.k.a. “The Universe-Computer” or “The Mind and Universe”)

По-сложните управляващи устройства (виж "Схващане за всеобщата предопределеност": http://eim.hit.bg/razum).

I think that everything makes sense, colleagues. One can always find meaning/sense, i.e. a connection between items. The meaning is the connection between things. (The relations between things)

The easiest thing to do is to redraw an already known, drawn line, and this is what is done initially when one is doing a semantic check – whether precomputed links/connections/relations with the given expression do exist. If such links do exist, they are seen like “gray lines”, which mind can darken, one can do it when given a piece of paper with gray lines and is being told to draw lines without thinking a lot or planning. This is what the virtual colleague did above, he rejected the possibility that “time flies” has meanings, that are yet unknown to him, and need to be computed, “drawn” in his memory. Let's overview a case with the same sample expression in another case.

Time Flies... A three year-old little native English speaker – Johny. He knows, that “a fly” means the flying bug (something little, black, that is flying and when it land on your face it's !!! гъделичка and you're trying to let it go by waving your hands.

Johny knows how to create a multiple of fly – flies, but he doesn't know that “a fly” means also “a fly of an airplane”. For Johny, “time” means just “a watch”. Johny knows, that “a clock” and “a watch” have similar meanings – something circular, with a long things, that are rotating... and the longer things are rotating faster than the shorter and the thicker; the thicker ones sometimes appear not to move at all, but after you have played for a while with your toy cars and look to them – they seemed to be at another place...

All the times when Johny has heard talks about time, he has seen clocks or watches.

Johny has heard his father saying “I don't have time, we have to hurry up!” and when his father has told that, he has looked to his watch.

That way, the conception of “time” is linked to the image of “watch”, when hearing time, he sees a watch, no abstract concepts. Johny himself doesn't have a watch.

Now let's assume that we put on our hand a big and shiny colourful watch and go to play with Johny on the playground. What he is going to do, if we tell him “Time flies!” and he hears this for the first time in his life?

Colleague: Perhaps he will look to our shiny watch and will search for flies around it... 

Author: Exactly! Can you imagine what he would do if we didn't have a watch on our wrist? Colleague: Maybe he would look to our hand, searching for a watch and flies... If he has remembered the pattern of watches being on the left wrist, he may first check there, or he may check both... 

The images Johny has for “time” and “flies” are recalled, and Johny searches the expression of these images in the environment, accessible by his senses. The specific mean is not important.

The machine needs an external environment, where to search for meaning and senses – MATCHES of images, names, features, coincidences, patterns.

Author: What Johny is going to do, after realizing that there are no flies around the watch, or even there is not a watch? Colleague: It depends what behavioral models have been developed so far. He could remember the expression "time flies" as an image that represent what he has thought then - “flies which are flying around a watch”, but not to do anything further; Johny could wait, expect to face usage of this expression in an environment, which is richer of details and features, so that he would be able to extract or approve the meaning.

Details, specific cases are what limits the space of search, the domain. Details are forces for pruning...

Author: Johny may also not make any conclusion, but just taking the expression as a non-sense so he wouldn't remember it. Also, he can ask us immediately: - What does “time flies” mean? The machine should also be able to do like that, as we do, it will need teachers and supervisors, while it develops.

Our explanations and the degree of trust he has to what we explain to him will determine how the child is going to limit the space of search, but also how he will expand the space, by adding possibilities which he didn't thought of before.

If one explains to Johny, that “time flies” means “time is never enough”, the child may remember this explanation as a whole sentence, without interpretation. Just a reference, a link: “time flies” redirects to “time is never enough” and then he would search for a meaning for the new sentence. On the other hand, one can also explain to Johny, that “flies” means also “to fly”, to move like birds or like Superman or so (recall that he didn't know the verb; it's strange not to know it, but that's the assumption), but not explaining him about the abstract concept of time.

In this case, Johny could keep linking “time” to “watch” and may start to imagine “time flies” as “the watch flies”. He may look around, searching for a watch that is flying – generally, this is a search of features, input data/senses which could confirm the link that was made. Or... just anytime he hears “time flies” Johny would imagine a flying watch and would ask himself “Whether the flying watches have wings or they are magically flying?”

Imagination is a the point here. When searching for a meaning, we should be able to imagine, to fantasize. That means, one kind of inputs/senses to cause other kinds of inputs/senses. The primary may be “real”, taken from raw data from the reality, linked to what the machine or human takes for “Reality”; while the secondary input/sense could be imagined, fantasized, unreal. Talking about reality, humans usually take for “real” input channels such as vision, hearing, touch, taste, smell; when he is receiving data at the maximum possible rate (max resolution, raw data). Vision is a primary sensory input, when we're sensing images, where we can recognize individual pixels. Letters, numbers and any symbols come from a secondary sensory input, because from the primary sensory input, containing raw pixels, each one containing an independent value, are extracted data with a smaller size (in raw bits) – letters, digits, geometric shapes etc. ... In order a system to find a meaning and make sense of things, it is very useful the system to have at least two different kinds of sensory inputs, and each of them to be able to invoke, to link to the other one. The images and relations between images (e.g. motion); sounds and relations between them can “generate” words: interpretations, which are described with smaller quantity of bits. When Johny hears “a watch”, he can imagine, somehow to see the image of the watch and what is possible to be done with it.

„What is possible to be done with” is yet another meaning of the concept of “meaning”. There is no sense in meaning, if you can't do anything with it.

Actually, everything “makes sense”, or “has a meaning”, in the sense that it causes something to be done. It is so, because even the so called “non-procedural knowledge/data” are only “non-procedural”, non-active, in the sense that they are not causing a type of action that is formally defined as “procedural”. In a computer, an information processing system, any data cause actions. Data defines what happens in the machine's “mind”. For example, the descriptive data of a page of text determines what exactly the machine is supposed to do, while it's CPU is reading the data from the memory, processes it, displays it, prints the page.

The meaning is the action, that the “thing” which is evaluated invokes/causes/turns, and this meaning can be different, depending how deep we are searching and more – how and what.

How and What we do the search is more dependent on our past experience, than on the short input being evaluated. Finally... Let's assume that the meaning of a message/sentence is an action to be taken, assuming that it was caused by the meaning that was found (if another meaning was found, another action would be taken).

Higher the complexity of the system, higher the weight of memories/experience in the decision how and what to search, therefore – what could be found. It's a paradox, but:

More complex the system – More Meaningless the Meaning

The Smarter the system – the Meaningless the meaning

Because the system - the Artificial Intelligence or human - can more freely search and find meaning – links between the items, things, phenomenon, events, messages, memories, objects, images, sounds or whatever.

Continues with long comments after the article, about reinforcement learning and other topics... (to be published, when translated)

http://research.twenkid.com 

http://artificial-mind.blogspot.com 

http://eim.hit.bg/razum (Bulgarian)

...

This is my favorite picture from the time... :-P

Tosh in 2004 posing as "The Terminator"

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I will Create a Thinking Machine that will Self-Improve (an Interview with Todor): Dreamers and adventurers make the great discoveries. The scepticists' job is to deny their visions, and eventually not to believe their eyes

An interview for “Obekti” magazine, november/december 2009.
See and download the original Bulgarian version: https://artificial-mind.blogspot.com/2009/11/dreamers-and-adventurists-do-big.html

[A note about the title and the usage of "self-improvement": the Bulgarian title, chosen by the editor, for "Self-Improve", is "Самоусложнява" - literally translated it would sound as "Will Self-Complicate", it "Will Make itself More Complex", "will self-complexify", because I explained, that the system would create more and more complex models of its sensory inputs [and motor outputs - intentions] and the "Seed" AI will collect complexity and it will make itself more complex.]

Todor Arnaudov's Bio:

Todor is 25, born in the city of Plovdiv, Bulgaria. MS in Software Engineering and BS in Computer Science from the University of Plovdiv (highest average grades); he was an intern at RIILP, Wolverhampton, UK where he studied Natural Language Processing. Todor started to play with computers as a boy, his first experiments with computer graphics and digital signal processing were as early as late 90-ies on his Pravetz-8M (Apple][e clone); he has developed a communication system for disk transfer between Pravetz-8M and a PC, based on sound frequency modulation-demodulation. Todor is an author of a Speech Synthesizer (“Glas”) and a context-sensitive English-Bulgarian dictionary “Smarty”, that participated in LREC 2008 and IMCSIT 2008 conferences. He was also a software developer, and a verification engineer in a semiconductor start-up.

Todor's biggest scientific thrill, though, is Artificial General Intelligence, and at the moment he's an Independent Researcher, aiming at founding a private research company. He's also an artist, a writer and an independent filmmaker and is searching for ways to fund his research by doing show business. In the “Researchers' Night” in Sofia's Technical University, he presented ideas from his Theory of Intelligence, that he has created as a teenager.

Todor Arnaudov: I will create a thinking machine that will self-improve Dreamers and adventurers make the great discoveries. The scepticists' job is to deny their visions, and eventually not to believe their eyes.

- Artificial Intelligence, or AI, is a wide field. Would you explain to the readers for example what is the difference between “Weak AI” and “Strong AI”?

AI is a science about systems that solve complex problems, which are assumed to require human intelligence. Weak AI solves specific tasks such as image and speech recognition, machine translation, self-driving cars. Strong AI is much more ambitious and it's aim is answering the general question – What is Intelligence? - and how to create universal systems, capable to reach and overpass humans in all cognitive aspects. Strong AI is called also Artificial General Intelligence or Universal AI.

- Did a particular event pushed you start to deal with the concept of Thinking Machine?

Yes, the movie “Terminator 2”, when I was 7. The concept of thinking machines excited me. As a teenager I had an inspiration – I wrote some SF and philosophical prose about AI and developed my own general philosophy and theory of the principles of Mind (intelligence) and the Universe. Yes, it was weird... I realized, that AI is a Universal Science and strategically the most important task, because solving it would be an accelerator of any possible research.

- Do you have colleagues in Bulgaria in this field?

Maybe yes, maybe no... Boicho Kokinov and Moris Grinberg are doing Cognitive Science at NBU, Sofia, they work on the cognitive architecture DUAL. A research laboratory called “Sphere” is doing sort of intelligence research, but the material I've read quite abstract. During my presentation in the Researcher's Night at Technical University of Sofia, I met Yordan Yankov from the Center or for Research of Global Systems; Yordan is working on his theory of intelligence and he mentioned about a special logic system, something related to Quantum Logic and Hegel's dialectic, if I'm not mistaken. Maybe you know about “Kibertron” - an intelligent humanoid robot project. They claim that they have a model of “natural intelligence”, but they require 5 million euros in order to implement it.

- Where do the researchers' efforts should be focused in order to achieve Artificial General Intelligence (AGI)?

First of all, research should be lead by interdisciplinary scientists, who are seeing the big picture. You need to have a grasp of Cognitive Science, Neuroscience, Mathematics, Computer Science, Philosophy etc. Also, creation of an AGI is not just a scientific task, this is an enormous engineering enterprise – from the beginning you should think of the global architecture and for universal methods at low-level which would lead to accumulation of intelligence during the operation of the system. Neuroscience gives us some clues, neocortex is “the star” in this field. For example, it's known that the neurons are arranged in sort of unified modules – cortical columns. They are built by 6 layers of neurons, different layers have some specific types of neurons. All the neurons in one column are tightly connected vertically, between layers, and are processing a piece of sensory information together, as a whole. All types of sensory information – visual, auditory, touch etc. is processed by the interaction between unified modules, which are often called “the building blocks of intelligence”.

- If you believe that it's possible for us to build an AGI, why we didn't manage to do it yet? What are the obstacles?

I believe that the biggest obstacle today is time. There are different forecasts, 10-20 years to enhance and specify current theoretical models before they actually run, or before computers get fast and powerful enough. I am an optimist that we can go there in less than 10 years, at least to basic models, and I'm sure that once we understand how to make it, the available computing power would be enough. One of the big obstacles in the past maybe was the research direction – top-down instead of bottom-up, but this was inevitable due to the limited computing power. For example, Natural Language Processing is about language modeling; language is a reduced end result of so many different and complex cognitive processes. NLP is starting from the reduced end result, and is aiming to get back to the cognitive processes. However, the text, the output of language, does not contain all the information that the thought that created the text contains.

On the other hand, many Strong AI researchers now are sharing the position that a “Seed AI” should be designed, that is a system that processes the most basic sensory inputs – vision, audition etc. Seed AI is supposed to build and rebuild ever more complex internal representations, models of the world (actually, models of its perceptions, feelings and its own desires and needs). Eventually, these models should evolve to models of its own language, or models of human's natural language. Another shared principle is that intelligence is the ability to predict future perceptions, based on the experience (you have probably heard of Bayesian Inference and Hidden Markov Models), and that intelligence development is improvement of the scope and precision of its predictions.

Also, in order the effect of evolution and self-improvement* to be created, and to avoid intractable combinatorial explosion, the predictions should be hierarchical. The predictions in an upper level are based on sequences of predictions (models) from the lower level. Similar structure is seen in living organisms – atoms, molecules, cellular organelles, cells, tissues, organs, systems, organism. The evolution and intelligence are testing which elements are working (predicting) correctly. Elements that appeared to work/to predict are fixed, they are kept in the genotype/memory, and are then used as building blocks of more complex models at a higher level of the hierarchy.

                                                                                    [ *in Bulgarian: making itself more complex]

- What exactly is done in the field? Globally, in Bulgaria?

Yet a few researchers and organizations are so confident to put officially that AGI is their goal, but the number is progressively increasing. Jeff Hawkins is probably the most popular guy in the field, he's author of the famous book “On Intelligence”, explaining his theory of intelligence. Jeff is a founder of a neuroscience institute, focused on the neocortex, and his company Numenta is working on a new computer architecture, inspired by the neocortex – hierarchical temporal memory, implementing so called memory-prediction framework. Another important figure in AGI is Ben Goertzel - an author of  numerous books about intelligence. Ben is trying to build an AGI in his company Novamente and plans to use virtual worlds of massive multiplayer games to teach it. Boris Kazachenko investigates intelligence as a universal algorithm for generalization and cognition as a part of the meta-evolution of the Universe, he's developing a theory of intelligence. If you want to join the AGI research community, you should consider also the work of Juergen Schmidhuber, Markus Hutter, Tomaso Poggio, Hugo de Garis. The Singularity Institute organizes a world conference each year about the so called “Technological Singularity”, including the advent of Universal artificial intelligence and its effect on humanity in the future.

I can't tell what my colleagues in Bulgaria are doing in the field; me myself, right now I'm warming up – clarifying my own ideas from the past and studying the theories of the others. Afterward, I'll continue with improving and specifying my theory of intelligence. I plan to start to do experiments with simple seed AI. My ambition is to found a research company, like Hawkins and Goertzel, but I don't have partners and capital yet – I'm searching for them.

- What would these experiments look like?

I will create intelligent agents and will watch their development in virtual worlds. Such an agent would have a “brain”, where I'll implement ideas from mine and the others' theories, as well as part of human brain architecture - cortex and old brain. The cortex has several main types of “zones”, functional units – sensory, motor (linked with “will”) and associative (connections/dependencies between different zones). The old brain is responsible for the emotions and the feeling of satisfaction/dissatisfaction of the basic instincts and needs. The agent would have sensors and feelings - vision, hearing, touch, hurt, hunger, pleasure and others, and a virtual body, which will allow it to interact with the virtual reality, to feed itself, to avoid troubles etc. Just after its “birth”, the agent would be controlled entirely by the old brain and would act mostly chaotically, driven only by the basic instincts, such as: pulling out of hot or cold places, attraction to the smell of food. The cortex will constantly watch and record the agent sensory inputs and motor commands and will search for patterns that link them. The cortex' goal is to find the patterns of better satisfaction of its basic needs. If the simple experiment are successful, I will make the virtual worlds and the virtual body more dynamic and will fill them with a higher variety of stimuli and patterns. That is supposed to lead to emergence of a more complex behavior. Eventually the virtual world is supposed to turn to real inputs – from camera, microphones etc.

- Many people believe, that an AI should know everything in order to convince them that it is intelligent. However, raw knowledge is not the most important aspect, isn't it? How do you think the Artificial General intelligence machine would look like, also the Ultimate AI?

The most important capabilities of the artificial general intelligent machine are in the self-improvement, learning and universality. A system, that interacts with people and its environment, and like a baby develops from a helpless state to a mental level of, say, a 2-year old toddler is much closer to my vision of a Thinking Machine, than current robots and specialized, narrow AI tools such as speech recognition, image recognition, search engines etc.

The Ultimate AGI is capable to self-improve even the most basic algorithms of itself and is ever reorganizing itself in order to work better and better, reaching to the ultimate limits. In humans, there's a similar mechanism, called neuroplasticity, which however is declining after the very early years.

- The ethical issues about creation of intelligent machines are a lot. Don't you think we would need to separate machines as “good” or “bad” in the future?

I believe that the thinking machines would be the most similar to us creations that we have ever met so far, because the intelligence is our most special quality - our bodies are not so special. It is true, that machines could do evil things, like in the movies, if they go out of control or fall in the hands of “bad guys”. Unfortunately this is true for all big inventions. Robots would create new and complex cases for the lawyers, as well.

- What would you tell to all the scepticists, who deny that AGI can be ever created?

I wish them good health. Dreamers and adventurers make the great discoveries. The job of the scepticists is to deny, but afterwards not to believe their eyes.

Twenkid Research
https://github.com/Twenkid/Smarty

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Сватбата - експериментална комедия (The Wedding, a short film)

Сватбата - експериментална комедия (The Wedding) from Todor Arnaudov on Vimeo.

Във Вимео е най-добро качество, но ако не работи: http://vbox7.com/play:b89de846
Или: http://twenkid.com/film/svatbata/svatbata_480x360.avi

Български - виж по-долу.

"The Wedding" - my first complex movie. (The film is in Bulgarian, not yet subtitles)
Genre: experimental surrealistic comedy.
Synopsis: a young reporter is visiting a mass wedding of the Sect of FMI to make a report, however he makes the terrifying discovery that he's also supposed to be married, without knowing who. The nightmare goes worst, when he finds out that everybody seems to be making fun of him. However, how it is going to end?
...

Синопсис

Млад репортер отива да заснеме масова сватба в Сектата на ФМИ в Пловдив, където прави ужасяващото откритие, че той също е заплануван за Сватбата и не се знае за коя ще го оженят. Това е само началото на неговия кошмар, защото изглежда, че всички се подиграват с него... Как обаче ще завърши всичко?

Повече инфо в блога на Twenkid Studio

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Reinforcement learning - comments on a Ben Goertzel's blog article

About: "Reinforcement Learning: Some Limitations of the Paradigm"

Bulgarian readers could also check out my article: Анализ на смисъла на изречение въз основа на базата знания на действаща мислеща машина. Мисли за смисъла и изкуствената мисъл.

...

You're right that if the system can alter or "re-wire" its circuitry that computes "reward", this confuses the mechanism, but I believe humans actually can do that - person's values are changing during life time, and even during the decision processes themselves.

I think "reward" is looked in a too narrow sense, because mind is not as solid and... single-minded to have one-single type of rewards. You've spoken about the "sub-selves" in the blog, I would say "virtual control units" that take control over the body.

Body is what makes mind to look uniform, even if it's not, mind can want 1000 things, body can't do them in the same time.

I've speculated on that in my old article, but it's in Bulgarian, I have to translate it in English (eventyally citing it).

E.g. let's consider a boy which is hesitating whether to eat up a chocolate or not. This could be an immediate high taste reward in a near future and if the boy plans only for 1 minute ahead, this is a right decision.

However, what if the boy widen the period of prediction to one year? He remembers his pain while visiting his dentists and reminds his notes, that eating too much chocolate causes bad teeth and pain. So if he plans for one year and reminds this, and decides that this will happen (it couldn't be sure), then the highly rewarding decision would stop being rewarding in the equation and the boy wouldn't take it.

Overall, the maximum reward depends on the set of predicting sub-units, scenarios, values taken into account in the very moment of decision, and the period of time they are predicting ahead.

They are changing, depending on attention, context, mood or even chance - there are so many scenarios that the brain can think of.

The set of predicting sub-units may change, they can switch at different levels of hierarchies and predicted periods, while the behaviour could still keep being reward-driven. It could be reward-driven for the particular "reward-driven virtual unit that took control over the body in this very moment".

This implies the mind is not uniform and there is not single "greatest reward".

...

And another comment on another comment:

I mean, e.g. if you're 18, you may think that making random sex right now is "cool". When you are 28, you may think it's not, even though making sex still would bring you immediate pleasere - however, higher level controls would inhibit your urge for lower level rewards and generally shift your behaviour to higher level rewards.

My point is that reward is not only dopamine, endorphin or so. Higher the ingelligence, higher the abstraction of reward could be. A reward is what the one that receives it considers "a reward", and even the altruism could also be taken as egoism, because one is doing what is "good" regarding its own values and desires, sometimes it's against what the other wants.

E.g. when a lover dies to save his beloved one. Is it really an altruism? How she will feel when seeing him dying, wouldn't she prefer them to die together?

And if you're doing something "against yourself" isn't it to prevent something that you consider worst. When you feel moral responsibility of doing something, fear of not fulfilling your duty might be bigger than the fear of pain.

...

На български - учене с подкрепление, машинно обучение, изкуствен интелект, силно направление, Бен Гьорцел

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How to merge/append/join wav segments/files into one?

Appending two or a few Wav files is easy with sound editors such as Audacity, Cool Edit and SoundForge. However, what if you need to join hundreds of files in different directories? Doing this manually is insane...

Recently I needed to do this with a bunch of records in Italian I wanted to put in my mp3-player. I found only a commercial solution, but I decided to code mine.

Todor's WaveAppender 0.01

Platform:Windows.License: Freeware.Warranty: No.

Download:Wave Appender 0.01

Please, post a comment if you find it useful.

Manual 

- Unzip files.
- Open scan.bat and edit the second string to point the path to the base folder with Wav files. E.g.:

scan.exe l:\italian\wave\1\ >list.txt

scan.exe your_full_path_here >list.txt

- Run scan.bat - it generates list.txt.
- Open list.txt and put on top a line pointing to the target directory. The merged files will be created there, e.g.:

l:\wav

l:\italian\wave\0\1b.wav
l:\italian\wave\0\1i.wav
l:\italian\wave\0\2b.wav
l:\italian\wave\0\2i.wav
l:\italian\wave\0\3b.wav
l:\italian\wave\0\3i.wav
l:\italian\wave\0\4b.wav
l:\italian\wave\0\4i.wav
l:\italian\wave\0\5b.wav
l:\italian\wave\0\5i.wav

#
$


- Run append.bat
- Voila! Files from each folder will be merged in 1.wav (first folder in the list), 2.wav, ... N.wav.


Using only appWav.exe

You can edit the list file manually, then you don't need to run the scanner.
The syntax is:

First line - target path
Next - N lists of path to files to be merged in N.wav. A list ends with "#".
The file ends with "$".

Eg.:

l:\wav

l:\italian\wave\0\1b.wav
l:\italian\wave\0\1i.wav
l:\italian\wave\0\2b.wav
l:\italian\wave\0\2i.wav
l:\italian\wave\0\3b.wav
l:\italian\wave\0\3i.wav
l:\italian\wave\0\4b.wav
l:\italian\wave\0\4i.wav
l:\italian\wave\0\5b.wav
l:\italian\wave\0\5i.wav

#
l:\italian\wave\2\1b.wav
l:\italian\wave\2\1i.wav
l:\italian\wave\2\2b.wav
l:\italian\wave\2\2i.wav
l:\italian\wave\2\3b.wav
l:\italian\wave\2\3i.wav
l:\italian\wave\2\4b.wav
l:\italian\wave\2\4i.wav
l:\italian\wave\2\5b.wav
l:\italian\wave\2\5i.wav
l:\italian\wave\2\6b.wav
l:\italian\wave\2\6i.wav
l:\italian\wave\2\7b.wav
l:\italian\wave\2\7i.wav
l:\italian\wave\2\8b.wav
l:\italian\wave\2\8i.wav
l:\italian\wave\2\9b.wav
l:\italian\wave\2\9i.wav
l:\italian\wave\2\10b.wav
l:\italian\wave\2\10i.wav

#
$

Notes:

- Files in each merge group should have the same format, code is pretty simple yet.
- Files in one list can be from different folders.


Thanks

Thanks to Srinivas Varukala (basic code for scanning directories in C#) and Vasian Cepa (Numeric Sorter in C#) for the Scanner part; you can find their code in CodeProject.

Appender code is in C++, written by me.

Keywords: How to merge wav files? How to append wav files. How to join wav files. Merging wav files.

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Сборник с разкази и стихове с участието на Тош | A book with Todor's co-autorship

Last month was issued a compilation with prose and poetry, where Todor participates with two short stories.

"Три години БГлог", "3 години Бглог", "Авторът си ти"

Повече инфо

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Шофьорът на Москвич 2 - Тодор Арнаудов и Ангел Янев | The Moskvich Driver 2

Филм на Тош

Продължение на "Шофьорът на Москвич", който беше донякъде филмово начало на Twenkid Studio през 2008 г. и беше "ням", не го озвучих. Този път с Ангел, с говор, сочен звук и дори малко музика от мен.

"Шофьорът на Москвич 2" стана най-сетне и дебютът на Ангел. :) Има много хляб в него като комик.

Шофьорът на Москвич

Други ключови думи: москвич, 1500, АЗЛК, комедия, късометражни, филми, 408, 407, копач, джуган, таратайка, соц., комиците

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DARPA PAL, CALO, RADAR - Cognitive Assistants that Learn and Organize

Other ambitious AGI projects, and these ones belong to DARPA. Scary!

I have a project for a similar tool that I call "Research Accelerator" or "Cognitive Accelerator", that initially would be an integration of various NLP, Machine Learning and Computer Vision techniques which assist and speed up in searching, reading, information extraction and any cognitive taks. This system also would be capable to work with GUI on its own, controlling the mouse and keyboard to do some job instead of user.

Time is ticking away and I need partners...

http://www.calosystem.org/

http://www.darpa.mil/IPTO/programs/pal/pal.asp
http://www.calosystem.org/team/

PAL - Personalized Assistant that Learns
RADAR - Reflected Agents with Distributed Adaptive Reasoning
CALO - Cognitive Assistant that Learns and Organizes

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How to make VirtualDub to append videos encoded at different frame rates?

It's very annoying, isn't it?

In my case, I had 15 fps video, recorded when I had tiny 1GB memory card. Up to now when I found the solution, it was impossible to append them with video shot at 30 fps (All with my sweet Canon Powershot A540, mjpeg 640x480x30fps at about 15 Mbit/s).

VirtualDub of course can convert the framerate to 30 or whatevever. This is the first step:

Video -> Framerate

Also, in order to append to the native AVI, you should use the same compression scheme like in the file you want to append to. In my case - MJPEG.

It's a bit hard to find - MJPEG is in ffdshow section. I suggest you to use high setting to the JPEG like 90 or more to minimize quality losses. (Lossless jpg is best, but different compression.)

Video -> Compression

However, this is still not enough...

When you try to append the resulted 30 fps to a "native" 30 fps produced by the camera, a non-sense error message appears.


It's a rounding error, actually both values are equal to 30.


Solution

Actually, these numbers are values in the AVI headers of the files.
Find the position of these numbers in the files and make them equal.

For Canon A540 and probably the other Powershots it is best to set the values to the "native" values. For other cameras the exact values are probably different.


I located the position there::

0x80: 35 82 00 00

0x84: 40 42 0F 00



You can use a hexeditor, e.g.: XVI32



If you're not a hacker, look on the down-left, this is the position in hexadecimal (80 == 128 in decimal). Put on that places the "magic numbers" (for Canon A540).

And now edit your 15 fps records with the 30 fps ones! :)

PS. Of course it could/should be automated, the easiest way by telling Avery to fix it... ;)


Other keywords: Tricks, Hacks, Solutions, Tricky, Videos running at different framerates, append videos, concatenate videos

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Фантазьори и авантюристи правят великите открития | Dreamers and Аdventurers Make the Great Discoveries (An interview with Todor)

Todor Arnaudov: I'll create a thinking machine that will self-improve.

Dreamers and adventurers make the great discoveries. The sceptics' job is to deny their visions, and eventually not to believe their eyes.

An interview I gave for "Obekti" magazine about Artificial General Intelligence and the research I do in this direction.

Read the Interview in English

Тодор Арнаудов: Ще създам мислеща машина, която ще се самоусложнява*

Фантазьори и авантюристи правят великите открития. Работата на скептиците е да отричат, а след това да гледат и да не вярват на собствените си очи

Прочети интервюто на български

Или от тук

* моето предложение за заглавие беше "самоусъвършенства", но "самоусложнява" също е вярно и е по-просто за обективно измерване

Четете в брой 5, ноември/декември на списание "Обекти"!

Keywords: Artificial General Intelligence, Cognitive Computing, Thinking Machines, Seed Intelligence, Bottom-top approach, Self-improving AGI, AI, Artificial intelligence, Researchers in AG, Todor Arnaudov, Изкуствен интелект, универсален изкуствен интелект, мислещи машини, изкуствен разум


* Бях съкратил подзаглавието тук на "а после да не вярват на собствените си очи"

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