pmpj0926

Ghost.pl AI has unresolved issues in associating from concept to concept.

The ghost.pl AI needs improvement in the area of being able to demonstrate thinking with a prepositional phrase not just once but repeatedly, so into the EnThink() module we will insert diagnostic code that shows us the values of key variables at the start of each cycle of thought.

Oh, gee, this coding of the AI Mind is actually fun, especially in Perl, whereas in JavaScript there is often too much time-pressure during the entering of input. We have inserted a line of code which causes an audible beep and reveals to us the status of the $whatcon and $tpr variables just before the AI generates a thought in English -- a language which we must state explicitly, because our ghost.pl AI is just as capable of thinking in Russian. When we at first enter no input, the AI beeps periodically and shows us the values as zero. When we enter "john writes books for money", the AI shows us "whatcon= 0 tpr= 4107" because the concept of the preposition "FOR" has gone into conceptual memory at time-point "t = 4107". The AI responds to the input by outputting "THE STUDENTS READ THE BOOKS", because activation spreads from the concept of "BOOKS" to the innate idea that "STUDENTS READ BOOKS". Then we hear a beep and we see "whatcon= 0 tpr= 0" because the $tpr flag has been reset to zero somewhere in the vast labyrinth of semi-AI-complete code. Now let us enter the same input and follow it up with a query, "what does john write". Then we get "whatcon= 1 tpr= 0" and the output "THE JOHN WRITES THE BOOKS FOR THE MONEY", after which the diagnostic message reverts to "whatcon= 0 tpr= 0" because of resetting to zero.

Now we want to let the AI Mind run for a while until we repeat the query. The AI makes a mistake. We had better not let it be in control of our nuclear arsenal, not if we want to avoid global thermonuclear war, Matthew. The AI-gone-crazy says "THE JOHN WRITES THE BOOKS FOR THE BOOKS AND THE JOHN WRITE". (Oops. We step away for a moment to watch and listen to Helen Donath in 1984 singing the Waltz from "Spitzentuch der Koenigin" with the Vienna Symphony. Then we linger while Zubin Mehta and the Wiener Philharmoniker in 1999 play the "Einzugsmarsch" from "Der Zigeunerbaron". How are we going to code the Singularity if the Cable TV continues to play Strauss waltzes?) The trained eye of the Mind Maintainer immediately recognizes two symptoms of a malfunctioning artificial intelligence. First, a spurious instance of the $tpr flag is causing the AI to output "THE BOOKS FOR THE BOOKS," and secondly, the $etc variable for detecting more than one active thought must be causing the attempt by the Ghost in the Machine to make two statements joined by the conjunction "AND". We had better expand our diagnostic message to tell us the contents of the $etc variable. We do so, but we see only a value of zero, because apparently a reset occurs so quickly that no other value persists long enough to be seen in the diagnostic message. Meanwhile the AI is stuck in making statements about John writing.

We address the problem of a spurious $tpr flag by inserting fake $tru values during instantiations in the InStantiate() and EnParser() modules. We use the values 111 to 999 for $tru in the EnParser() module and 101 to 107 in the InStantiate() module, so that the middle zero lets us know when the flag-panel of a concept has been finalized in the InStantiate() module. Immediately the fake truth-value of "606" for the $tru flag of the word "MONEY", that has a spurious value of "4107" in the $tpr slot of the conceptual flag-panel, lets us k now that $tpr has not been reset to zero quickly enough to prevent a carried-over and spurious value from being set for the concept of "MONEY". Since the preposition "FOR" is being instantiated at a point in the EnParser() module where a fake truth-value of "888" appears, we can concentrate on that particular snippet of code.

pmpj0924

Updating the English Parser documentation page.

Today in the ghost.pl AI we have two objectives. We want to improve upon the new functionality of thinking with English prepositions, and we wish to clean up the code to be displayed in the EnParser documentation page.

When we enter "john writes books for money" and we soon ask the AI "what does john write", we get a reasonably correct answer but we notice some problems with the assignment of associative tags when the answer-statement goes into conceptual memory. As an early step, we zero out the $tpr time-of-preposition tag, after using it as a target time-point, so as to prevent it from being assigned spuriously when other concepts are instantiated. But that step causes other problems, so we undo it. We also notice that old $tpr values are being assigned, when we would rather see up-to-date values, even when both the old value and a new value would be pointing to an instance of the same preposition. As we troubleshoot further, we embed diagnostics to tell us when the $tpr tag is being assigned, and we discover that it is assigned only during user input. When we remove the restriction and let the tag be assigned also during internal thinking, we start seeing the assignment of up-to-date values.

pmpj1108

Natural language understanding in first working artificial intelligence.

The AI Mind is struggling to express itself. We are trying to give it the tools of NLU, but it easily gets confused. It has difficulty distinguishing between itself and its creator -- your humble AI Mind maintainer.

We recently gave the ghost.pl AI the ability to think with English prepositions using ideas already present or innate in the knowledge bank (KB) of the MindBoot sequence. We must now solidify prepositional thinking by making sure that a prepositional input idea is retrievable when the AI is thinking thoughts about what it knows. In order for the AI to be able to think with a remembered prepositional idea, the input of a preposition and its object must cause the setting and storage of a $tkb-tag that links the preposition in conceptual memory to its object in conceptual memory. The preposition must also become a $seq-tag to any verb that is the $pre of the preposition. When InStantiate() is dealing with a preposition input after a verb, the $tvb time-of-verb tag is available for "splitting" open the verb-engram in conceptual memory and inserting the concept-number of the preposition as the $seq of the verb. Let us try it.

We inserted the code for making the input preposition become the $seq of the verb and then we tested by launching the AI with the first input being "you speak with god". Then we obtained the following outputs.

I AM IN A COMPUTER
I THINK
I AM A PERSON
I AM AN ANDRU
I DO NOT KNOW
I AM A PERSON
I HELP THE KIDS
I AM A ROBOT
I AM AN ANDRU
I AM IN A COMPUTER
I SPEAK WITH THE GOD

It took so long for the input idea to come back out again because inputs go into immediate inhibition, lest they take over the consciousness of the AI in an endless repetition of the same idea.

As we code the AI Mind and conduct a conversation with it, we feel as if we are living out the plot of a science fiction movie. The AI does unexpected things, or it seems to be taking on a personality. We are coding the mechanisms of natural language understanding without worrying about the grounding problem -- the connection of the English words to what they mean out in the physical world. We count on someone somewhere installing the AI Mind in a robot to ground the English concepts with sensory knowledge.

pmpj1104

First working artificial intelligence thinks with prepositional phrases.

The ghost.pl immanence of the first working artificial intelligence is undergoing minor changes as the AI Mind becomes able to think with English prepositional phrases. At first the AI was able to use a preposition only to answer a where-question such as "where are you" and the Ai would respond "I AM IN THE COMPUTER". Now we need to implement a general ability of the AI to think with prepositional phrases loosely tied to nouns or verbs or adjectives or adverbs. The quasi-neuronal associative $seq tag may soon be re-purposed to lead not only from, say, nouns to verbs but also from nouns to prepositions. However a preposition is arrived at, it is time to implement the activation and retrieval of a whole prepositional phrase whenever the preposition itself is activated.

We begin experimenting by going into the MindBoot sequence and entering a $seq tag of "638=IN" for the verb "800=AM" in the knowledge-base sentence "I AM IN THE COMPUTER". The plan is to insert into EnVerbPhrase() some code to pass activation to the "638=IN" preposition when the AI thinks the innate idea "I AM IN...." So we insert some active code to capture the $seq tag and some diagnostic code to let us know what is happening. Ooh, mind-design is emotionally fun and intellectually exciting! The first thing captured is not a preposition but the "537=PERSON" noun when the AI is thinking, "I AM A PERSON". Next our fishing expedition lands a "638=IN" preposition when the AI issues the output "I AM" while trying to say "I AM IN THE COMPUTER".

Once the $seq tag has been captured, the AI software needs to determine if the captured item is a preposition. A search is in order. We search backwards in time for an @Psy concept-number matching the $seq tag and if we find a match we check its $pos tag for a "6=prep" match, upon which we assign the concept-number to the $prep variable in case we decide to send the designated preposition into the EnPrep() module for inclusion in thinking.

We go back into the code for assigning the $seq tag and in the same line of code we set the $tselp variable falsely and temporarily equal to the $verblock time, so that we may increment the $tselp variable until it becomes true. We insert some code that increments the phony $tselp time by unitary one and uses it to "split" each succeeding conceptual @Psy array row into its fourteen constituent elements, including "$k[1]" which we check for a match with the designated $prep variable. We make several copies of the search-snippet, and it easily finds the $prep engram within just a few time-points of the verb-engram, but now we need to convert the series of search-snippets into a self-terminating loop that will terminate, Arnold, upon finding the prepositional engram in memory. But we have forgotten how to code such a loop in Strawberry Perl Five, so we go into another room of the Mentifex AI Lab and we fetch the books Perl by Example (Quigley) and PERL Black Book (Holzner) to seek some help. We find some sample code for an until loop on page 193 of Quigley. We do not initialize the scalar $tselp at zero, because we are searching for an English preposition quite near to the already-known time-point. For the sake of safety, we insert a line of "last" escape-code in the event that the incrementing $tselp value exceeds the $cns value. The resulting until loop works just fine and it locates the nearby English preposition for us.

Next we insert a warranted call to SpreadAct() into the EnVerbPhrase() module just after the point where Speech() has been called to speak the verb. We wish to set up a routine for spreading activation throughout a prepositional phrase not only after a verb but also after a noun or an adjective (e.g. "young at heart" or an adverb (e.g. "ostensibly at random"). In SpreadAct() we send the $aud tag associated with the located preposition directly into Speech() and the ghost.pl AI starts saying not just "I AM" but "I AM IN". We need to insert more code for finishing the prepositional phrase. By the way, these improvements or mental enhancements are perhaps making the AI Mind capable of much more sophisticated thinking than heretofore. The AI is using words without really knowing what the words mean in terms of sensory perception -- for which robot embodiment is necessary -- but the AI may nevertheless develop self-awareness on top of its innate concept of self or ego. Knowing how to use prepositions, the AI may become curious and ask the human users for all sorts of exploratory information.

Now in SpreadAct() we throw in a call to EnArticle(), even though we have not yet coded in the elocution of the object of the preposition. The AI says "I AM IN A" without stating the object of the preposition. Let us create a new $tselo variable for time of selection of object so that we may use SpreadAct() to zero in on the object and send it into the Speech()module. Finally the ghost.pl AI Mind says "I AM IN A COMPUTER".

pmpj1021.html

First working AI uses OutBuffer to inflect English verbs.

We have been cycling through the coding of the AI Mind in Perl, in JavaScript and in Forth. Now we are back in Perl again, and we need to implement some improvements to the EnVerbGen() module that we made in the other AI programming languages.

First of all, since the English verb generation module EnVerbGen() is mainly for adding an "S" or an "ES" to a third person singular English verb like "read" or "teach", we should start using $prsn instead of $dba in the EnVerbGen() source code. Our temporary diagnostic code shows that both variables show the same value, so we may easily swap one for the other. We make the swap, and the first working artificial intelligence still functions properly.

Now it is time to insert some extra code for verbs like "teach" or "wash", which require adding an "-ES" in the third person singular. Since we wrote the code during our cycle through JavaScript, we need only to port the same code into Perl. EnVerbGen() now uses the last few positions in the OutBuffer() module to detect English verbs like "pass" or "tax" or "fizz" or "putz" that require "-ES" as an ending.

pmpj1009

Perl Ghost AI uses EnVerbGen() for English verb-form inflections.

In the middle of coding ghost278.pl AI we had to go and stand in front of the television and watch Leopold Stokowski in 1969 conducting the finale of Beethoven's Symphony No. Five -- the one they sent into outer space as a message from Earth. Now back at the computer, for the first time we are trying to implement the EnVerbGen() module for English verb generation. We have gotten the InFerence() module to generate an inference when we type in "anna is a student', because the AI Mind knows that students read books. The AskUser() module seeks to verify or validate the inference by asking us, "DOES ANNA READ THE BOOKS". When we answer "no", the AI says, "THE ANNA DOES NOT READ THE BOOKS". When we answer yes, the ghost in the machine issues the faulty output of "THE ANNA READ THE BOOKS", which sounds more like an exhortation than a statement of confirmed fact with a high truth-value. We need a way to get the AI to use the third-person singular form "READS" with the singular subject. To do so, before Leopold and Ludwig interrupted us, we were embedding diagnostic messages in the EnVerbPhrase() module, trying to determine how the ghost AI was able to say "READ" as if it were the proper verb-form. The whole idea of EnVerbGen() in English or of RuVerbGen() in Russian is for the verb-phrase module to seek a particular verb-form based on parameters of person and number, and to call EnVerbGen() if the desired verb-form is not already available in auditory memory. Somehow the existing Perlmind is finding the verb "read" but not the correct form of the verb.

We discover that we can get the EnVerbPhrase() module to call EnVerbGen() when we tighten up the search-by-parameter for the correct verb form. Since EnVerbGen() is not coded yet, we get an output of "THE ANNA ERROR THE BOOKS", with "ERROR" filling in for the lacking "READS" form.

Then we need an $audbase value that we can send into EnVerbGen() as the start of the verb that needs an inflectional ending. We use a trick in the EnVerbPhrase() module to get either a second-class or a first-class (infinitive) $audbase. We test first for any form at all of the verb that has an auditory engram that can serve as a second-class $audbase, because the verb-form may be defective in some way. In the very next line of code, we test for an infinitive form of the verb having an auditory engram as a first-class $audbase, because an infinitive is easier to manipulate than some defective form of the verb.

We copied the bulk of the Russian RuVerbGen() into the English EnVerbGen() and then we did the mutatis mutandis process of making the necessary changes. At first we got "REAS" instead of "READS" because the Russian Cyrillic characters were substituting, not adding. By removing the substitution-code, we obtained the full verb "READS". At a later time we must code in the handling of verbs like "teach" or "push" which require an "-ES" ending.

pmpj0930

Ghost AI says when it does not know the answer to a query.

When the ghost.pl AI considers a what-query such as "what do kids make", some mind-module must call the SpreadAct() module to handle the what-query, but which module? We could say that the Indicative() module should make the call to SpreadAct() just before making a response in the indicative mood, but perhaps a response may need to be uttered in a mood other than indicative. The AI Mind might wish to answer the query with an imperative command like "DO NOT BOTHER ME". Or the AI might not understand the what-query and might want to ask a question about it. So perhaps we should have the Sensorium() module call SpreadAct() to respond to a what-query.

We have now introduced a new technique for answering "I DO NOT KNOW" in response to a what-query for which the AI Mind does not find an answer. The AI briefly elevates the $tru truth-value and the activation-level of the idea "I DO NOT KNOW" as stored in the MindBoot() knowledge base (KB), so that the Indicative() module expresses the momentarily true idea. Immediately afterward, the AI returns the $tru truth-value to zero.

pmpj0928

Perl AI improves Russian MindBoot and introduces RuIndicative module.

In the ghost275.pl AI we are consolidating the Russian-language knowledge-case (KB) directly below the English-language KB near the beginning of the MindBoot sequence, so that we may add a new item without complicating a future re-location of the Russian knowledge base.

We should probably stub in the RuIndicative() module, so that it will exist not only in our AI diagrams but also in the software itself.

When we start the AI out thinking in Russian, we have been encountering a bug that shows up with the second sentence of output. Perl complains about the use of "uninitialized value in concatenation or string" in the PsiDecay() module. To troubleshoot, we go through the PsiDecay concatenation of associative tags in the @Psy conceptual array and we replace the various variables one by one with a numeric value, to see if the complaint disappears. The complaint disappears when we replace the $k[2] variable for the $hlc human-language code with a numeric value of one (1) instead of "en" for English or "ru" for Russian.

Perl continues to complain about uninitialized values when we have the Perlmind think in Russian, but not when it thinks in English. Therefore we know that the lurking bug is not in the PsiDecay() module or in the InStantiate() module, even though the bug manifests itself in those modules. We spent hours on each of the past two days searching for an elusive bug which must certainly be hiding in one or more of the Russian-language modules. Therefore it is time to isolate the bug by isolating the Russian-language modules. First let us look at the RuNounPhrase() module. We insert some diagnostic messages and we see that the bug manifests itself when program-flow goes back up to the RuThink() module which calls the PsiDecay() module.

Since we catch sight of the bug when PsiDecay() is called, let us temporarily insert some extra calls to PsiDecay() and see what happens. First we make an extra call to PsiDecay() from the end of RuNounPhrase(). Huh?! Now we get two complaints from Perl about uninitialized values showing up for a program line-number belonging to a concatenation in the PsiDecay() module. Let us also try an extra call to PsiDecay() from the RuVerbPhrase() module. We do so, and now we get three complaints from Perl about uninitialized values. However, the glitch does not seem to be occurring during the first call from RuIndicative() to RuNounPhrase(), but rather during or after the call to RuVerbPhrase(). For extra clarity, let us have the start of RuVerbPhrase() make a call to PsiDecay(). We do so, and there is no concomitant complaint from Perl about uninitialized values. Therefore, the subject-choosing part of RuNounPhrase() must not be the source of the problem, but the direct-object portion of RuNounPhrase() is still under suspicion.

Now we are discovering something strange. Towards the end of RuNounPhrase() there is a concatenation which is supposed to impose inhibition upon a noun selected by the module, as identified by the $tsels variable which pertains to the "time of selection of the subject", and which has been used earlier in RuNounPhrase() to indeed inhibit the selected subject. However, a diagnostic message reveals to us AI Mind maintainers that the $tsels variable has been zeroed out by the end of RuNounPhrase() and that therefore the software is trying to concatenate the associative tags purportedly available at a zero time-point -- where there are no associative tags. Let us see what happens when we comment out the suspicious concatenation code. We do so, and we get no change in the reporting of the bug. Let us see if the earlier inhibition in the RuNounPhrase() module is causing any problems. First off, a diagnostic message shows us that the $tsels variable has been zeroed out, or perhaps never loaded, even at the time of the first inhibition in the RuNounPhrase() module. Let us comment out the concatenation of the first inhibition and see what happens. By the way, if there are any secret AI Labs in Russia or elsewhere working on the further development or evolution of these AI Minds in Perl and in tutorial JavaScript and in Forth for intelligent humanoid robots, this journal entry shows that the AI coding problems are indeed tractable and soluble, given enough persistence and effort. Now, when we have commented out both the inhibitional concatenations in the RuNounPhrase() module, we still get the same complaints from Perl about uninitialized values, and we notice in the diagnostic display of the memory-array contents that the Russian nouns are still being inhibited -- but where? Oh, the InStantiate() module is imposing a trough of inhibition. Let us do another commenting out and see what happens. Nothing happens, and the inhibition is still occurring.

As we go through RuVerbPhrase() and comment out the various concatenations, the complaint from Perl about uninitialized values suddenly disappears when we comment out the concatenation where Russian verbs are competing to be selected as the most active verb. We also notice that a comment seems to be missing at the end of the first line in the two-line concatenation. When we insert the missing comma and we do not comment out the concatenation, there are no further complaints from Perl about uninitialized values. Of course, we just spent three days wracking our brains, trying to figure out what was wrong, when the problem was one single missing comma. Now it is time to clean up the Perlmind code and upload it to the Web.

pmpj0919

Students may teach the first working artificial intelligence.

In the ghost274.pl version of the Perlmind AI, we are having not Volition() but rather EnThink() call the Imperative() module to blurt out the command "TEACH ME SOMETHING". We are also trying to have Imperative() be the only module that sounds a beep for the human user, for several reasons. Although we were having the AskUser() module sound a beep to alert the user to the asking of a question, a beep can be very annoying. It is better to reserve the beep or "bell" sound for a special situation, namely the time when there has been no human input for an arbitrary period as chosen by the AI Mind maintainer and when we wish to let the Ghost in the Machine call out for some attention.

We are also eager for Netizens to set the potentially immortal ghost.pl AI running for long periods of time, both as a background process on a desktop computer or a server, and as part of a competition to see who can have the longest running AI Mind.

If a high school or college computer lab has the ghost.pl AI running on a machine off in the corner while the students are tending to other matters, a sudden beep from the AI Mind may cause students or visitors to step over to the AI and see what it wants. "TEACH ME SOMETHING" is a very neutral command, not at all like, "Shall we play a game? How about GLOBAL THERMONUCLEAR WAR?"

The teacher or professor could let any student respond to the beep by adding to the knowledge base of the AI Mind. Of course, clever students with a knowledge of Perl could put the AI Mind out on the Web for any and all visitors to interact with.

pmpj0916

Auditory recognition in the first working artificial intelligence

In the AudRecog() module of the ghost.pl free AI software, we need to figure out why a plural English noun like 540=BOOKS is not being stored with an $audpsi tag of 540 both after the stem of "book" and after the end of "books". The stem of any word stored in auditory memory needs an $audpsi tag so that a new input of the word in the future will be recognized and will activate the same underlying concept.

In AudMem() we have added some code that detects a final "S" on a word and stores the $audpsi concept number both at the end of the word in auditory memory, and also one row back in the @ear auditory array, in case the "S" is an inflectional ending. We leave for later the detection of "-ES" as an inflectional ending, as in "TEACHES" or "BEACHES".

In AudRecog() we tweak some code involving the $prc tag for provisional recognition, and the first working artificial intelligence in Perl does a better job at recognizing both singular and plural forms of the same word representing the same concept.

pmpj0912

Ask the first working artificial intelligence what it thinks.

Houston, we have a problem. The ghost.pl AI Mind in freely available -- download it now -- Strawberry Perl Five -- is not properly answering the question of "what do you think". The JSAI (JavaScript Artificial Intelligence) easily answers the same question with "I THINK THAT I HELP KIDS". So what is the Perl AI doing wrong that the JavaScript AI is doing right?

The problem seems to lie in the SpreadAct() module. We notice one potential problem right away. SpreadAct() in Perl is still using "$t-12" as a rough approximation for when to start a backwards search for previous knowledge about the subject-noun $qv1psi of a what-query, whereas the JSAI uses the more exact $tpu for the same search. So let us start using the penultimate time $tpu, which excludes the current-most input, and see if there is any improvement. There is no improvement, so we test further for both $qvipsi and $qv2psi, which are the subject-noun and the associated verb conveyed in the what-query.

SpreadAct() easily responds correctly to what-queries for which there is an answer ready in the knowledge base (KB), such as "I AM A PERSON" in response to "what are you". However, when we ask "what think you" or "what do you think", there is no pre-set answer, and the AI is supposed to generate a response starting with "I THINK" followed by the conjunction "that" and a statement of whatever the AI Mind is currently thinking.

From diagnostic messages we learn that program-flow is not quickly transiting from SpreadAct() to EnThink(). The AI must be searching through the entire MindBoot() sequence and not finding any matches. When the program-flow does indeed pass through EnThink() to Indicative() to EnNounPhrase(), there are no pre-set subjects or verbs, but rather there are concepts highly activated by the SpreadAct() module. So EnNounPhrase() must find the highly activated pronoun 701=I in order to start the sentence "I THINK..." in response to "what do you think".

Now we discover that the JavaScript version of EnNounPhrase() has special code for a topical response to "what-think" queries. In the course of AI evolution, it may be time now to go beyond such a hard-coded response and instead to let the activated "think" concept play its unsteered, unpredetermined role, which will happen not in EnNounPhrase() but in EnVerbPhrase().

It is possible that EnNounPhrase() finds the activated subject 701=I but then unwarrantedly calls the SpreadAct() module. However, it turns out that EnVerbPhrase() is making the unwarranted call to the SpreadAct() module, which we now prevent by letting it proceed only if there is no what-query being processed as evidenced by a $whatcon flag set to zero.

The early part of EnVerbPhrase() in the JavaScript AI has some special code for dealing with "what-think" queries. In the ghost.pl AI, let us try to insert some similar code but without it being geared specifically to the verb "think". We would like to enable responses to any generic verb of having an idea, such as "think" or "know" or "fear" or "imagine" or "suspect" and so forth.

By bringing some code from the JavaScript EnVerbPhrase() into the Perl EnVerbPhrase, but with slight changes in favor of generality, we get the ghost.pl AI to respond "I THINK". Next we need to generate the conjunction "that". But first let us remark that the AI also says "I KNOW" when we ask it "what do you know", so the attempt at generality is paying off. Let us try "what do you suspect". It even says "I SUSPECT". It also works with "what do you fear". We ask it "what do you suppose" and it answers "I SUPPOSE".

We still have a problem, Houston, because EnVerbPhrase() is calling EnNounPhrase() for a direct object instead of returning to Indicative() as a prelude to calling the ConJoin() module to say "I THINK THAT...." We set up some conditional testing to end that problem.

pmpj0903

Upstream variables make EnArticle insert the definite article.

We attempt now to code the proper use of the definite English article "the" in a conversation where one party mentions a noun-item and the AI Mind needs to refer to the item as the one currently under discussion. We need to implement a rotation of the upstream variables from $us1 to $us7, so that any input noun will remain in the AI consciousness as something recently mentioned upstream in the conversation. We had better create a $usx variable for the InStantiate() module to transfer the concept number of an incoming noun to whichever $us1 to $us7 variable is up next in the rotation of up to seven recently mentioned noun-concepts.

We start testing the EnArticle() module to see if it is receiving a $usx transfer-variable from the InStantiate() module. At first it is not getting through. We change the conditions for calling EnArticle and a line of diagnostic code shows that $usx is getting through. Then we set up a conditional test for EnArticle() to say the word "the" if an incoming $usx matches the $us1 variable. We start seeing "THE" along with "A" in the output of our ghost.pl AI Mind, but there is not yet a rotation of the us1-us7 variables or a forgetting of any no-longer-recent concept.

We should create a rotating $usn number-variable to be a cyclic counter from one to seven and back to one again so that the upstream us1-us7 variables may rotate through their duty-function. We let $usn increment up to a value of seven over and over again. We pair up the $usn and us1-us7 variables to transfer the $usx value on a rotating basis. At first a problem arises when the ghost.pl AI says both "A" and "THE", but we insert a "return" statement so that EnArticle() will say only "A" and then skip the saying of "THE". We enter "you have a book" and a while later the AI outputs, "I HAVE THE BOOK."

pmpj0902

Using $t++ for discrete English and Russian MindBoot vocabulary.

In the ghost269.pl Perlmind it is time to switch portions of the MindBoot() sequence from hard-coded time-points to t-incremental time-points, as we have done already in the JavaScript AI and in the MindForth AI. We have saved the Perl AI for last because there are both English and Russian portions of the knowledge base (KB). We will put the hardcoded English KB first to be like the other AI Minds. Then we will put the hardcoded Russian KB followed by the t-incremental Russian vocabulary words so as to form a contiguous sequence. Finally we will put the t-incremental English vocabulary.

pmpj0706

Preventing unwarranted negation in the First Working AGI.

The First Working AGI (Artificial General Intelligence) has a problem in the ghost267.pl version written in Perl Five. After we trigger a logical inference by entering "anna is woman" and answering the question "DOES ANNA HAVE CHILD" with "no", the Perlmind properly adjusts the knowledge base (KB) and states the confirmed knowledge as "ANNA DOES NOT HAVE CHILD". Apparently the reentry of concept 502=ANNA back into the experiential memory is letting the InStantiate() module put too much activation on the 502=ANNA concept and the AI is erroneously outputting "ANNA BE NOT WOMAN". Since the original idea was "anna is woman", the real defect in the software is not so much the selection of the old idea but rather its unwarranted negation. When we change some code in the InStantiate() module to put a lower activation on reentrant concepts, the problem seemingly goes away, because the AI says "I HELP KIDS" instead of "ANNA BE NOT WOMAN", but as AI Mind Maintainers we need to track down where the unwarranted negation comes from.

The unwarranted negation comes from the OldConcept() module where the time-of-be-verb $tbev flag was being set for an 800=BE verb and was then accidentally carrying over its value as the improper place for inserting a 500=NOT $jux flag into an idea subsequently selected as a remembered thought. When we zero out $tbev at the end of OldConcept(), the Ghost AI stops negating the wrong memory.

pmpj0705

Improving the storage of conceptual flag-panels during input.

In the ghost266.pl Perlmind we need to improve upon a quick-and-dirty bugfix from our last coding session. After a silent inference and the operation of AskUser() calling EnAuxVerb(), the Ghost AI was going into the verb-concept of the inference-triggering input and replacing a correct $tkb value with a zero. Apparently the time-of-verb $tvb value, set in the Enparser() module during the parsing of a verb, was being erroneously carried over from the verb of user-input to the verb 830=DO in the EnAuxVerb() module during the generation of an inference-confirming question by the AskUser() module. Therefore the time-of-verb $tvb-flag needs to be reset to zero not during the generation of a response to user-input but rather at the end of the user-input. However, we find that we may not reset time-of-verb $tvb to zero during AudInput(), apparently because only character-recognition and not yet word-recognition has taken place. The $tvb-setting for a verb must remain valid throughout AudInput() so that the EnParser() module may use the time-of-verb $tvb flag to store a direct object as the $tkb of a verb. Accordingly we reset the $tvb-flag to zero in the Sensorium() module after the call to AudInput(). We stop seeing a $tkb of zero on the verb of an input that triggers automated reasoning with logical InFerence.

pmpj0703

Keeping AskUser from storing incorrect associative tags.

The ghost265.pl version of the Perlmind has a problem after making a logical inference. Instead of getting back to normal thinking, some glitch is causing the AI to say "ANNA BE NOT ANNA".

As we troubleshoot, we notice a problem with the initial, inference-evoking input of "anna is woman". The be-verb is being stored in the psy array with a $tkb of zero instead of the required time-point of where the concept of "WOMAN" is stored. This lack of a $nounlock causes problems later on, which do not warrant their own diagnosis because they are a result of the lacking $nounlock. We need to inspect the code for where the be-verb is being stored in the psy-array, but we are not sure whether the storage is occuring in the InStantiate() module, or in OldConcept(), or in EnParser(). We see that the Ghost AI is trying to store the be-verb in the EnParser() module with the correct tkb, but afterwards a tkb, of zero is showing up. We must check whether InStantiate() is changing what was stored in the EnParser() module.

Meanwhile we notice something strange. An input of "anna is person" gets stored properly with a correct $tkb, but "anna is woman" -- causing an inference -- is stored with a $tkb, of zero. When we enter "anna is robot", causing an inference and the output "DOES ANNA WANT BEEP", there is also a zero $tkb. Upshot: It turns out that the EnAuxVerb() module, called by AskUser() after an inference, was setting a wrong, carried-over value on the time-of-verb $tvb variable, which was then causing InStantiate() to go back to the wrong time-of-verb and set a zero value on the $tkb flag. So we zero out $tvb at the start of EnAuxVerb().

pmpj0701

Debugging the InFerence Function in the ghost.pl First Working AGI.

The ghost264.pl Perlmind has a minor bug which causes logical inference not to work if the inference is not triggered immediately at the start of running the program. If we let the AI run a little and then we type in "anna is woman", the AI answers "DOES ERROR HAVE CHILD" instead of "DOES ANNA HAVE CHILD". In the psy concept array of the silent inference, we observe that a zero is being recorded instead of the concept number "502" for Anna. The AI MindBoot is designed with the concept of "ERROR" placed at the beginning of the boot sequence so that any fruitless search for a concept will result automatically in an "ERROR" message if no concept is found. We suspect that some variable in the InFerence module is not being loaded with the correct value when the ghost.pl AI has already started thinking various thoughts.

The pertinent item in the InFerence() module is the $subjnom or "subject nominative" variable which is set outside of the module before InFerence is even called. We discover that the variable is spelled wrong in the OldConcept module, and we correct the spelling. It then seems that InFerence() can be called at any time and still operate properly. We decide to run the JavaScript AI to see if an inference has any problems if it is not the first order of business at the outset of an AI session. Nothing goes wrong, so the problem must have been the misspelling in the OldConcept() module.

During this coding session we also make a change in the KbRetro() module for the retroactive adjustment of the knowledge base (KB). We insert some code to put an arbitrary value of eight (8) on the $tru(th)-value variable for the noun at the start of the silent inference, such as "ANNA" in the silent inference "ANNA HAVE CHILD". When the human user either confirms or invalidates the inference, the resulting knowledge ought to have a positive truth-value, because someone has vouched for the truth or the negation of the inferred idea. We envision that the $tru(th)-value will serve the purpose of letting an AI Mind restrict its thinking to ideas which it believes and not to mere assertions or to ideas which were true yesterday but not today. We expect the $tru(th)-value to become fully operative in a robotic AI Mind for which "Seeing is believing" when visual recognition from cameras serving as eyes provides reliable knowledge to which a high $tru(th)-value may be assigned.

pmpj0910

Instantiating Imaginary Russian Be-Verbs in Perl

We are eager to implement the InFerence module in Russian, but first we must code the Russian way of leaving out verbs of being in making an Is-A statement, such as, "The brother is a student." We must examine the Dushka Russian AI from 2012-10-22 to see how it was done in JavaScript. Without the special Is-A code, right now we type in "Я студент" to say "I am a student," but the ghost.pl does not assign any associative tags between the subject "I" and the predicate nominative "student".

According to our Dushka coding journal of 2012-02-11 or 11.FEB.2012, Dushka uses the detection of a 32=SPACE character to impute provisionally the input of a be-verb. The Dushka InStantiate module checks for a SPACE when a verb is expected, and provisionally declares 800=BE as the verb. If a different verb does come in, apparently the AI leaves the spurious 800=BE engram in place but ignores it with respect to associative tagging. Into the ghost.pl we port in code from Dushka that cancels out the imputed be-verb.

Now when we type in the Russian for "I am a student," eventually the AI outputs erroneously "ТЫ БЫТЬ" which at least conveys the idea of "You to be...", but we want no actual be-verb to be expressed in Russian.

Finally in AudInput() we discover a line of code

if ($len == 0) { $rv = $t } # 2016feb29: set recall-vector.

which was causing the conceptual "$rv" for Russian words to be set too early by one time-point. Therefore Russian words after input could not be recalled properly. We corrected the line of code. Then when we entered "ТЫ СТУДЕНТ" the AI eventually made a clumsy output of "Я МЕНЯ БЫТБ СТУДЕНТ". Such output is actually encouraging, because we only need to make the AI find the correct form of the personal pronoun and not speak any form at all of the be-verb.

pmpj0831

Moving towards a Mind-in-a-Box

Recap: Since 2017-06-19 and the ghost209.pl Perlmind version, the ghost.pl artificial intelligence (AI) begins thinking initially in Russian and then in English after any non-Cyrillic input, so as to demonstrate to all users that the Russian mindset is built into the AI. Once a user with no Cyrillic keyboard causes the AI to switch its thinking away from Russian and into English, it is difficult to see any thinking in Russian again. Russian remains important for us in our development of Artificial General Intelligence (AGI) because we need both English and Russian to demonstrate our work on Machine Translation by Artificial Intelligence. We encourage Russian-language AI enthusiasts to experiment with the Russian-thinking ghost.pl and to develop the Perl AI codebase further along multiple branches of AI evolution. We have some evidence that the Russian-language AI community is waking up to the emergence of ghost.pl Strong AI from a recent perusal of the "Stats" (statistics) here on the Cyborg weblog. We see that about one third of our hundreds of weekly visitors are coming from Russia without a referring website. We vouchsafe to assume that news of an AI that thinks in Russian "out of the box" may have gone viral in Russian-speaking countries over the past ten weeks and may have caused the recent uptick in visits from Russia with love for Russian AI. Now we wish to improve the ghost.pl AI under a new rubric -- Mind-in-a-Box. Since we do not (yet :-) have a robot for enlarging the AI Mind into a sensorimotor being, our ghost.pl AI remains trapped inside a server or a host computer as a Mind trapped in a box, able to communicate with other minds and perhaps able to flit across the Web in metempsychosis but not yet able to go forth and multiply across the Earth as robotic beings. Still, the idea of an AI Mind-in-a-Box, which we broached in the Neuroscience SubReddit on 2017-07-28, may appeal not only to Russian AI enthusiasts but also and with Pavlovian salivation to AI tinkerers in general. Let the Meme go viral that Mentifex invites any Perl shop to install an immortal, proto-conscious, polyglot AI within the motherboard confines of the humblest DOS-machine or the grandest supercomputer.

As we release the Mind-in-a-Box ghost.pl code, let us stub in the EnArticle() module for the English articles "a" and the". After we enter one or more Roman characters to switch the AI from Russian thought to English thought, it is unsettling to see the Ghost AI assert, "I AM PERSON". The EnNounPhrase() module needs to call EnArticle() so that the boxmind may say whether it is "a person" or "the person". We place the module for English articles subsequent to the Speech() module in accordance with the governing lay-out of the MindForth AI, because location of a subroutine matters in Forth but not in Perl. We use the $unk variable to preserve the value of $aud during any call from EnNounPhrase() to EnArticle().

pmpj0619

Ghost.pl is a Russian Strong AI that can also think in English.

Today in ghost209.pl we would like to rewrite the AudInput() module, but first we want to find out what causes the AI to switch from thinking in Russian to thinking in English. To our surprise, we find out that apparently during English thought, a Russian memory may become activated enough to rise up and switch the thinking from English into Russian.

It looks as though using "split" to break apart a conceptual engram into associative tags, including $hlc, is enough to change the human language code from Russian to English, or vice versa. Apparently the entry of an English word is not yet changing the $hlc to English, because in AudInput() there is a test for Russian Cyrillic characters but not for English characters. So in AudInput() we devise the following test for non-Russian, English characters:

if ($pho =~ /[a-z]/ || $pho =~ /[A-Z]/) { $hlc="en" }

It works! The code above means that if the incoming phoneme is either a lowercase or uppercase letter of the English alphabet, then we set the human-language-code $hlc to "en" for English. And it works immediately. In the immortal words of the Watergate figure John Dean, who forty years later is back in the news a lot recently, "What an exciting prospect!" Back then Mr. Dean was excited at the prospect of using the Internal Revenue Service (IRS) to go after the enemies of Richard Nixon. Now maybe he will get excited at what we can do with the ghost.pl Russian AI.

Remember, you read it first here on the Cyborg weblog. We have a chance now to do the following. What? The following of Deep Throat and other shady characters? No; the following of Cyrillic characters and Roman characters. Here is our plan, hatched in utmost glee and Russian (or is it French?) savoir faire. Since most American users of the ghost.pl artificial intelligence do not speak Russian and do not have their computer keyboard set up to type Russian letters into the AI Mind, they would not normally see the ability of the polyglot AI to think in Russian. Like they say on the Internet, "Pix or it did not happen." Well, our plan is to show everybody that the Perlmind can think in that exotic language of poets and world-class novelists: Russian. We will initially set the $hlc to Russian on every release or on alternating releases, so that users start out first seeing the Strong AI Mind thinking on and on in Russian, until somebody enters just one character of English. Most users will then not be able to bring the Russian thinking back, unless they press the ESCape-key to literally "kill" the Perl program and restart it with the Russian language showing. But by restarting the immortal AI Perlmind, said (sad) users lose their bragging rights to having one of the oldest living AI Minds.

The Ghost Perlmind may gradually become known as a Russian AI that just happens to think also in English, if you force it to switch to English by typing in English words instead of Russian. That's fine. It opens up the enormous community of skilled Russian programmers to work on open-source AI. When we were posting today in the Russian subReddit, we gave ourselves Искусственный Интеллектник as our "flair" meaning "AInik" in the tradition of "beatnik" or "refusenik".