EnParser English Parser Module of the
English and Russian bilingual ghost.pl AI in Perl
Mens Latina in Latin -- MindForth for Robots

1. Diagram of the EnParser English Parser Module

/^^^^^^^^^\ EnParser Tags Subject-Verb-Object /^^^^^^^^^\
/ EYE \ MINDCORE _____ / EAR \
/ \ CONCEPTS /New- \ / \
| _______ | | | | _____ (Concept)-|-------------\ |
| /old \ | | | | /Old- \ \_____/ | Audition | |
| / image \---|-----+ | (Concept)------|---|----------\ | |
| \ recog / | | | | \_____/-------|---|-------\ | | |
| \_______/ | a| | | |________V | c | | | |
| | b|C| | / EnParser \ | a | | | |
| visual | s|O|f| \__________/ | t | | | |
| | t|N|i| |noun? | s-/ | | |
| memory | r|C|b| |verb? | | | |
| | a|E|e| |adj.? | e | | |
| channel | c|P|r| |adverb? | a | | |
| | t|T|s| |prep.? | t-----/ | |
| _______ | | | | |conj.? | | |
| /new \ | |_|_| ______V____ | f | |
| / percept \ | / \ / \ | i | |
| \ engram /---|--\ Psi /-----( InStantiate ) | s | |
| \_______/ | \___/ \___________/ | h-------/ |

2. Purpose of the EnParser English Parser Module

EnParser serves the purpose of not only identifying a part of speech such as a noun, preposition or verb, but also of comprehending the part of speech in context by helping to assign associative tags among concepts in the Psy conceptual array. Thus
EnParser and its Russian counterpart RuParser serve the purpose of Natural Language Understanding (NLU).

3. Algorithm of the EnParser AI Mind-Module

Since the main feature of the concept-based AI Minds is their demonstration of solving the AI-hard problem of natural language understanding (NLU), the EnParser module for parsing English is the main instrument of achieving the NLU goal.

The ghost.pl AI Mind in Strawberry Perl Five is becoming a conversational agent that may be installed to run in either the background or the foreground on any host computer.

The JavaScript AI Mind requires no download of either source code or programming language. Simply clicking on the link brings the tutorial AI Mind into your MSIE browser, where you may use the AI to teach students or AI coders.

If you want to issue verbal instructions to your autonomous humanoid robot, MindForth as the robot brain enables you and the robot to engage in a discussion of what work the robot should be doing, and how the work should be done, and how the robot should
engage in back-and-forth communication using English for you to clarify youe instructions and for the robot to report to you its completion of tasks.

3.A. Words included in the MindBoot sequence lighten the load of EnParser.

Populating the MindBoot sequence with English words, the AI mind maintainer tries to include the most frequent English nouns and verbs, all the conjunctions, all the prepositions, and all the pronouns. Except for disambiguation, the embedded words do not
need further parsing as to their parts of speech.

3.B. The first AI Minds could only parse SVO sentences into nouns and verbs.

The subject-verb-object (SVO) format of admissible inputs made it simple for the earliest AI Minds to classify English words as nouns or verbs. The parsing module could skip over the known English articles and an important adverb like the word "NOT"
being used to negate an English sentence.

3.C. The ghost112.pl AI became able to parse prepositional phrases.

Since the MindBoot sequence innately contains all the English prepositions identified as such, the AI Mind easily detects the input of a known English preposition and sets the $prepcon flag to a positive number one and loads the $tpp time-of-preposition
flag with the ending time-point at which the input preposition is being instantiated as a node in conceptual memory. Then $tpp is used to zero in on the associative-tag flag-panel of the preposition, filling in the next noun or pronoun as the $seq of the
preposition. Then the $tvb time-of-verb flag is used to insert the concept-number of the preposition as a $seq of the verb.

3.D. The ghost114.pl AI began to parse the indirect objects of verbs.

To parse and comprehend an indirect object, EnParser tentatively fills the time-of-indirect-object $tio flag with the input-time of the first noun being input after a verb. The $tio flag is set only once by requiring that it be at zero for it to be set.
Simultaneously, the time-of-direct-object flag $tdo is filled with the same value as the $tio flag for an indirect object, because it is not yet known whether one noun or two nouns are being entered subsequent to the input of a transitive verb. If and
when a second noun comes in, the value for the time-of-direct-object $tdo flag, originally filled with the same value as the indirect-object $tio flag, is replaced or overwritten with the new time of the second post-verb noun in the input stream.

If only one noun comes in after the verb, the identifier of the direct object is set only once. If two post-verb nouns come in, the first noun becomes the indirect object and the second noun becomes the direct object.

3.E. The ghost309.pl AI became able not only to parse the input of a prepositional phrase but also to think with a prepositional phrase.

4. Code of EnParser() from ghost327.pl AI source code in Perl

# 2017-09-03: Requirements of English Parser module:
# 2017-09-13: EnParser shall at first assume that a new word is a noun.
sub EnParser() { # http://ai.neocities.org/EnParser.html
if ($pos == 5 || $pos == 7) { # 2019-10-19: if noun or pronoun...
if ($tsj == 0) { $dba = 1; } # 2019-10-19: if not subject has been declared...
if ($tult == $tdo) { $dba = 4; } # 2019-10-19: acc. dir. obj.
} # 2019-10-19: end of test for noun or pronoun.
$act = 48; # 2016apr27: an arbitrary activation for InStantiate()
$bias = 5; # 2015jun04: Expect a noun until overruled.
$tkb = 0; # 2019-10-22: BUGFIX
if ($fyi > 2) { # 2016feb08: if mode is Diagnostic
# 2018-07-01: Diagnostic or tutorial message.
} # 2016feb07: end of test for Diagnostic or Tutorial mode.
InStantiate(); # 2019-08-08: first instantiation during parsing Stage One
if ($pos == 5) { $bias = 8 } # 2016feb10: after noun, expect verb.
if ($pos == 7) { $bias = 8 } # 2016feb10: after pronoun, expect verb.
if ($pos == 8) { $bias = 5 } # 2016feb10: after verb, expect noun
if ($prepcon == 0) { # 2017-09-13: if not handling a preposition...
if ($pos == 5 || $pos == 7) { # 2016mar21: expanding then-clause
# $tsj = ($t - 1); # 2017-09-13: subject?
# $tsj = ($t - 1); # 2019-10-19: declare subject-time elsewhere?
if ($verbcon == 1) { # 2017-09-13: if a verb has come in...
if ($tvb > 0) { $tdo = $tult; } # 2019-10-19: a default value.
if ($tio == 0) {$tdo = $tult} # 2017-09-13: set once or twice
if ($tio == 0) {$tio = $tult} # 2017-09-13: set only once
if ($tio > 0) { # 2017-09-13: if $tio previously set...
$tdo = $tult; # 2017-09-13: second noun sets time of dir.obj.
} # 2017-09-13: end of test to make 2nd noun the direct object.
$tkb = $tdo; # 2019-10-18: let verb have a "nounlock" to direct object.
my @k=split(',',$psy[$tvb]); # 2017-09-13: expose flag-panel of verb
$pre = $k[1]; # 2017-09-13: verb psi will be $pre of direct object
@k=split(',',$psy[$tio]); # 2017-09-13: expose flag-panel of indir.obj.
$iob = $k[1]; # 2019-08-01: excerpt indirect-object concept for k[13]
$psy[$tio]="$k[0],$k[1],$k[2],$k[3],$k[4],$k[5],$k[6],"
. "3,$k[8],$k[9],$k[10],$k[11],$k[12],$k[13],"
. "$k[14],$k[15],$k[16],$k[17],$k[18],$k[19],$k[20]"; # 2019-08-01: panel
# 2017-09-13: Above lines insert k7 dba=3 for dative-case indirect object.
@k=split(',',$psy[$tdo]); # 2017-09-13: expose flag-panel of dir.obj.
$psy[$tdo]="$k[0],$k[1],$k[2],$k[3],$k[4],$k[5],$k[6],"
. "4,$k[8],$k[9],$k[10],0,$k[12],$k[13],"
. "0,$k[15],$k[16],$k[17],$k[18],$k[19],$k[20]"; # 2019-08-02: no $tkb for dir.obj.
# 2017-09-13: Above lines insert verb-$psi as k10 $pre of direct object.
@k=split(',',$psy[$tvb]); # 2017-09-13: expose flag-panel of main verb.
if ($k[5]==250) { $k[7]=0;$k[8]=0; } # 2019-10-23: negated verb is dba=0 infinitive.
$tdo = $t - 1; # 2017-09-13: insert time-of-direct-object for nounlock;
$tkb = $tdo; # 2017-09-13: TEST
# 2017-09-13: Next two lines create psy-array row for a verb.
$psy[$tvb]="$k[0],$k[1],$k[2],$k[3],$k[4],$k[5],$k[6],"
. "$k[7],$k[8],$k[9],$k[10],$psi,$k[12],$iob,"
. "$tkb,$k[15],$k[16],$k[17],$k[18],$k[19],$k[20]"; # 2019-08-01: panel.
@k=split(',',$psy[$tdo]); # 2019-10-19: expose flag-panel of direct object
$psy[$tdo]="$k[0],$k[1],$k[2],$k[3],$k[4],$k[5],$k[6],"
. "4,$k[8],$k[9],$k[10],$k[11],$k[12],$k[13]," # 2019-10-19: acc. dba=4 dir.obj.
. "$k[14],$k[15],$k[16],$k[17],$k[18],$k[19],$k[20]"; # 2019-10-19: tdo-panel
} # 2017-09-13: end of test for a condition following a verb.
} # 2017-09-13: end of test for noun not object of a preposition.
} # 2017-09-13: end of test for a non-prepositional condition.
if ($pos == 6) { $prepcon = 1 } # 2019-09-24: prepare for noun.
if ($pos == 5 || $pos == 7) { # 2017-09-13:
if ($prepcon == 1) { # 2017-09-13:
my @k=split(',',$psy[$tpr]); # 2019-08-06: expose flag-panel of preposition;
$pre = $k[1]; # 2017-09-13: Let $pre briefly be the preposition.
$prep = $k[1]; # 2018-11-08: identify prep. to be the $seq of the verb.
$k[14] = $tult; # 2019-08-01: establish $tkb between preposition and its object.
@k=split(',',$psy[$tult]); # 2017-09-13: expose flag-panel of obj of prep.
$psy[$tult]="$k[0],$k[1],$k[2],$k[3],$k[4],$k[5],$k[6],"
. "4,$k[8],$k[9],$pre,0,$k[12],$k[13],"
. "$k[14],$k[15],$k[16],$k[17],$k[18],$k[19],$k[20]"; # 2019-08-01: panel.
$prep = 0; # 2018-11-08: Reset to prevent carry-over.
$prepcon = 0; # 2017-09-13: Reset to prevent carry-over.
} # 2017-09-13: end of test for a positive $prepcon.
} # 2017-09-13: end of test for a noun or pronoun.
if ($pos == 8 && $psi != 800 && $psi != 818) { # 2019-08-06: not "BE" or "DO"
$tvb = ($t - 1); # 2017-09-13: hold onto time-of-verb for flag-insertions.
$verbcon = 1; # 2017-09-13: verb-condition is "on" for ind. & dir. objects.
my @k=split(',',$psy[$tsj]); # 2017-09-13: expose flag-panel of subject noun
$subjpre = $k[1]; # 2017-09-13: Hold onto $subjpre for the pos=8 verb
$psy[$tsj]="$k[0],$k[1],$k[2],$k[3],$k[4],$k[5],$k[6],"
. "1,$k[8],$k[9],$k[10],$psi,$k[12],$k[13],"
. "$tvb,$k[15],$k[16],$k[17],$k[18],$k[19],$k[20]"; # 2019-08-01
@k=split(',',$psy[$tult]); # 2017-09-13: expose flag-panel of verb.
$psy[$tult]="$k[0],$k[1],$k[2],$k[3],$k[4],$k[5],$k[6],"
. "$k[7],$k[8],$k[9],$subjpre,0,$k[12],$k[13],"
. "$k[14],$k[15],$k[16],$k[17],$k[18],$k[19],$k[20]"; # 2019-08-01
$subjpre = 0; # 2017-09-13: Reset for safety.
} # 2017-09-13: end of test for a pos=8 verb.
# if ($pos == 8 && $psi == 800) { # 2019-10-18: if 800=BE verb...
if ($pos == 8) { # 2019-10-19: any verb...
$tvb = ($t - 1); # 2019-10-18: hold onto time-of-verb for flag-insertions.
my @k=split(',',$psy[$tsj]); # 2019-10-18: expose flag-panel of subject noun
$psy[$tsj]="$k[0],$k[1],$k[2],$k[3],$k[4],$k[5],$k[6],"
. "$k[7],$k[8],$k[9],$k[10],$psi,$k[12],$k[13]," # 2019-10-18: verb is "seq" of noun.
. "$tvb,$k[15],$k[16],$k[17],$k[18],$k[19],$k[20]"; # 2019-10-18: verb "tkb" of noun.
} # 2019-10-18: end of test for 800=BE verb.
# if ($tpr > 0 && $pos == 5) { # 2019-08-11: if a noun follows a preposition...
if ($tpr > $vault && $pos == 5) { # 2019-10-22: if a noun follows a preposition...
my @k=split(',',$psy[$tpr]); # 2019-08-10: expose flag-panel at time-of-prep.
$tkb = ($t-1); # 2019-08-11: time of object of preposition
$psy[$tpr]="$k[0],$k[1],$k[2],$k[3],$k[4],$k[5],$k[6],"
. "$k[7],$k[8],$k[9],$k[10],$k[11],$k[12],$k[13],"
. "$tkb,$k[15],$k[16],$k[17],$k[18],$k[19],$k[20]"; # 2019-08-11
} # 2019-08-11: end of test for a noun after a preposition.
if ($pos == 6 && $mri > 0) { # 2019-09-24: removing restriction to input-only.
$tpr = ($t - 1); # 2019-08-11: time-of-preposition for back-tag insertion.
my @k=split(',',$psy[$mri]); # 2019-08-10: expose flag-panel of most-recent word
$psy[$mri]="$k[0],$k[1],$k[2],$k[3],$k[4],$k[5],$k[6],"
. "$k[7],$k[8],$k[9],$k[10],$k[11],$k[12],$k[13],"
. "$k[14],$k[15],$k[16],$k[17],$k[18],$tpr,$k[20]"; # 2019-08-11
$etc = 0; # 2019-09-26: thwart compounding of thought at first after a preposition.
$tpr = 0; # 2019-10-22: prevent carry-over. TEST; TRUNCATE
} # 2019-09-24: end of test for preposition part-of-speech and positive $mri value.
if ($pos == 8) { # 2019-10-19: if part-of-speech is 8=verb...
if ($psi != 818) { # 2019-10-19: if verb other than auxiliary 818=DO...
$verbcon = 1; # 2019-10-19: verb condition is "on" for indir. and dir. objects.
} # 2019-10-19: end of test for not auxiliary 818=DO.
my @k=split(',',$psy[$tsj]); # 2019-10-19: expose flag-panel at time-of-subject
$psy[$tsj]="$k[0],$k[1],$k[2],$k[3],$k[4],$k[5],$k[6],"
. "$k[7],$k[8],$k[9],$k[10],$psi,$k[12],$k[13]," # 2019-10-19: seq = verb.
. "$k[14],$k[15],$k[16],$k[17],$k[18],$k[19],$k[20]"; # 2019-10-20
} # 2019-10-19: end of test for a pos=8 verb.
if ($pos == 5 || $pos == 7) { # 2019-10-22: noun or pronoun as direct object
my @k=split(',',$psy[$tdo]); # 2019-10-19: expose flag-panel of direct object
$psy[$tdo]="$k[0],$k[1],$k[2],$k[3],$k[4],$k[5],$k[6],"
. "4,$k[8],$k[9],$svo2,0,$k[12],$k[13]," # 2019-10-22: dba=4 pre=verb seq=0
. "$k[14],$k[15],$k[16],$k[17],$k[18],$k[19],$k[20]"; # 2019-10-22: tdo-panel
} # 2019-10-22: end of test for a noun or pronoun.
if ($pos == 1) { # 2019-10-22: if adjective
$tult = ($t -1); # 2019-10-22: certify
my @k=split(',',$psy[$tult]); # 2019-10-22: expose flag-panel
$psy[$tult]="$k[0],$k[1],$k[2],$k[3],$k[4],$k[5],$k[6],"
. "$k[7],$k[8],$k[9],$k[10],$k[11],$k[12],$k[13]," # 2019-10-22
. "$k[14],$k[15],$k[16],$k[17],$k[18],0,$k[20]"; # 2019-10-22: no tpr for adjective.
} # 2019-10-22: end of test for pos=1 adjective
if ($pos == 6) { # 2019-10-22: if preposition
$tult = ($t -1); # 2019-10-22: certify
my @k=split(',',$psy[$tult]); # 2019-10-22: expose flag-panel
$psy[$tult]="$k[0],$k[1],$k[2],$k[3],$k[4],$k[5],$k[6],"
. "$k[7],$k[8],$k[9],$k[10],$k[11],$k[12],$k[13]," # 2019-10-22
. "$k[14],$k[15],$k[16],$k[17],$k[18],0,$k[20]"; # 2019-10-22: no tpr for prep.
} # 2019-10-22: end of test for pos=6 preposition.
} # 2019-10-19: EnParser() returns to OldConcept() or NewConcept().

5. Variables for EnParser Module with NLU

$act -- quasi-neuronal activation-level

$bias -- EnParser(); NewConcept(): expected part-of-speech POS

$fyi -- (for your information) display mode, which the user selects by pressing the Tab key and toggling through the modes: 1 = Normal; 2 = Transcript; 3 = Tutorial mode; 4 = Diagnostic mode

$mri -- -- most-recent-instantiation. The mri is a time-point which may be used for the insertion of an associative tag into the conceptual flag-panel of a previous concept in order to establish a link between a newly input concept being instantiated and
the previously instantiated concept. The designation of the time-point of the mri concept may be qualified or restricted by code that requires the mri concept to be a special ("pos") part-of-speech, such as either a noun or a verb. Thus a preposition
being instantiated may be back-linked to a noun or a verb as a mental point of departure leading to the preposition within a chain of thought. For example, if we say "John writes books for money", the preposition "for" could be linked backwards to a tpr (
time-of-preposition) tag in the flag-panel of the verb "writes" or in the flag-panel of the noun "books", depending on whether the basic idea is "writes for money" or "books for money" -- especially if "John writes books for money and poems for fun."

$pos -- (part of speech) 1=adj 2=adv 3=conj 4=interj 5=noun 6=prep 7=pron 8=verb

$pre -- pre(vious) associated @psy concept, such as the subject of a verb, or such as the verb of a direct object.

$prep -- a preposition used in the EnPrep mind-module for English prepositions.

$prepcon -- prepositional condition-flag for parsing.

$subjpre -- subject-$pre to be held for verb in parsing.

$tdo -- time-of-direct-object for a parser module.

$tio -- time-of-indirect-object for parser module.

$tkb -- time-in-knowledge-base of an idea. The EnParser() module stores time-of-verb $tvb in the k[13] $tkb slot of the subject of a sentence being stored at the time-of-subject $tsj time-point in the Psy conceptual array. The EnParser module stores $tkb
as equal to $tdo (time of the direct object) in the Psy array row of the verb at time-of-verb $tvb. Thus for subjects $tkb means "verb" and for verbs $tkb means "direct object". No $tkb is stored for a direct object, because the associative tags go from
subject to verb to object (SVO) but no further.

$tpr -- time-of-preposition for parsing.

$tsj -- conceptual flag-panel tag for time-of-preposition.

$tult -- t penultimate, or time-minus-one.

$tvb -- time-of-verb for parsing. The EnParser module sets "t - 1" as the tvb if the word being parsed is a verb by part-of-speech. InStantiate uses the time-of-verb tvb to fill the tkb-slot in a verb-panel with the time-location of the direct object of
the verb. EnParser uses the time-of-verb tvb to find the numeric verb-concept that will be the pre of a direct object being parsed. EnParser also uses the time-of-verb tvb to store the time-of-direct-object tdo as the tkb in the flag-panel of the verb.
Therefore the tvb-flag needs to be reset to zero not during but after AudInput, when program-flow has returned to the Sensorium module.

$verbcon -- verb-condition for seeking (in)direct objects. $verbcon is set to a positive unitary one in the EnParser module when a verb comes in during input and remains at one while any indirect or direct object comes in. After an input sentence, $
verbcon is reset to zero.

6. Troubleshooting and Debugging for AI Mind Maintainers

6.1.a. Symptom: (Something goes wrong.)
6.1.b. Solution: (AI Mind Maintainer devises solution.)

To debug the function of assigning indirect and direct objects, the AI Mind Maintainer enters a typical sentence such as "I give the boy a robot" that contains both an indirect object and a direct object, and presses Escape to halt the AI after the input.
Then the Maintainer examines the display of the conceptual array to see if $iob and $seq have been properly assigned. The AI coder may also insert diagnostic "print" messages into InStantiate() and EnArticle() so as to observe the process of assigning a
tag during the input and comprehension of a sentence.

7. Future Development of EnParser Module with NLU

Considerations:
- For future development. EnPronoun could be used to replace a noun with a relative pronoun and to introduce a subordinate clause, such as;

"I know a man who loves music."

EnParser must deal with the NLU of such a sentence, using the incoming relative pronoun as a trigger to treat the ensuing verb as referring back to the relative pronoun.

Roadmap to Artificial Intelligence

8. Resources for EnParser Module with NLU

http://duriansoftware.com/joe/Constructing-human-grade-parsers.html

http://www.scholarpedia.org/article/Word_sense_disambiguation

http://github.com/PriorArt/AGI/wiki/MindGrid

9. Spread the News on TikTok and Other Venues

Are you on TikTok? Are you eager to be a ThoughtLeader and Influencer?
Create a TikTok video in the following easy steps.

I. Capture a screenshot of https://ai.neocities.org/EnParser.html
for the background of your viral TikTok video.

II. In a corner of the screenshot show yourself talking about the EnParser module.

III. Upload the video to TikTok with a caption including all-important hash-tags which will force governments and corporations to evaluate your work because of FOMO -- Fear Of Missing Out:
#AI #ИИ #brain #мозг #ArtificialIntelligence #ИскусственныйИнтеллект #consciousness #сознание #Dushka #Душка #psychology #психология #subconscious #подсознание
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A sample video is at https://www.tiktok.com/@sullenjoy/video/7230082904812981546


10. AiTree of Mind-Modules for Natural Language Understanding
MainLoop of Mind-Modules for Natural Language Understanding
TabulaRasa -- wipe memory clean
MindBoot of English and Russian vocabulary
KbLoad -- load the Knowledge Base
LangLearn -- habituate new syntax; learn a language
ReJuvenate -- recycle memory space
Sensorium -- sensory input with associative tagging to concepts
AudInput -- auditory input
AudListen -- listen for input
AudMem -- English auditory memory
AudRecog -- auditory recognition
OldConcept -- recognize a known old concept
EnParser -- preposition? (in)direct object?
InStantiate -- create new instance of concept
RuParser -- expect first a noun, then a verb
InStantiate -- create new instance of concept
NewConcept -- create a new concept
EnParser -- preposition? (in)direct object?
InStantiate -- create instance of new concept
RuParser -- expect first a noun, then a verb
InStantiate -- create instance of new concept
FileInput -- read files on a server
GusRecog -- sense of taste
OlfRecog -- sense of smell
TacRecog -- sense of touch
VisRecog -- sense of vision
Volition -- free will resulting from emotion and thought
Emotion as influence on thought and free will
EnThink -- think in English
KbRetro -- retroactively adjust knowledge base
Imperative -- mood for issuing commands
Indicative -- mood for declarative statements
InFerence -- automated reasoning
AskUser -- validate an inference
EnNounPhrase -- think with a noun
EnPrep -- insert an English preposition
EnArticle -- use "a" or "the"
EnAdjective -- insert an adjective
EnPronoun -- substitute a pronoun for a noun
ConJoin -- insert a conjunction
EnVerbPhrase -- think with a verb
EnAuxVerb -- use auxiliary verb
EnAdverb modifies a verb
EnAdverb modifies another adverb
EnVerbGen -- generates an English verb-form
AudBuffer -- stores English phonemes
OutBuffer -- right-justifies English verb-form
VisRecog -- visual recognition by feature extraction
SpreadAct -- spreads activation from concept to concept
Subjunctive -- mood for conditional phrases
ConJoin -- insert a conjunction if two thoughts are active
RuThink -- think in Russian
RuImperative -- needs to be coded
RuIndicative -- mood for declarative Russian sentences
InFerence -- automated reasoning
AskUser -- validate an inference
RuNounPhrase -- think with a Russian noun
RuAdjective -- insert a Russian adjective
RuAdjGen -- to generate a Russian adjective-form
RuAdverb -- insert a Russian adverb
RuPrep -- insert a Russian preposition
RuPronoun -- substitute a Russian pronoun for a noun
ConJoin -- insert a conjunction
RuVerbPhrase -- think with a Russian verb
RuVerbGen -- generate a Russian verb-form
AudBuffer -- stores Russian phonemes
OutBuffer -- right-justifies Russian verb-form
Speech -- output to screen or loudspeaker
RuAdverb -- insert a Russian adverb
VisRecog -- visual recognition inserts a noun
RuNounPhrase -- direct-object noun
RuNounGen -- to generate a Russian noun-form
ConJoin -- insert a conjunction
PsiDecay lowers conceptual activation
Motorium (MotorOutPut) -- for AI-Minded robots
MetEmPsychosis -- AI soul travel from webserver to webserver
PortScan -- find a receptive open port for relocation of the Ghost AI
Spawn -- AI Go FOOM
MindMeld -- merge two AI Minds by sharing memories
Consciousness -- emergent property, not a module

Nota Bene: This webpage is subject to change without notice. Any Netizen may copy, host or monetize this webpage to earn a stream of income by means of an affiliate program where the links to Amazon or other booksellers have code embedded which generates
a payment to the person whose link brings a paying customer to the website of the bookseller.

This page was created by an independent scholar in artificial intelligence who created the following True AI Minds with sentience and with limited consciousness.

http://ai.neocities.org/mindforth.txt -- MindForth Robot AI in English.

http://ai.neocities.org/DeKi.txt -- Forth Robot AI in German.

http://ai.neocities.org/perlmind.txt -- ghost.pl Robot AI thinks in English and in Russian.

http://ai.neocities.org/Ghost.html -- JavaScript Robot AI Mind thinks in English.

http://ai.neocities.org/mens.html -- JavaScript Robot AI Mind thinks in Latin.

http://ai.neocities.org/Dushka.html -- JavaScript Robot AI Mind thinks in Russian.

The following books describe the free, open-source True AI Minds.

AI4U -- https://www.iuniverse.com/BookStore/BookDetails/137162-AI4U

AI4U (paperback) -- http://www.amazon.com/dp/0595259227

AI4U (hardbound) -- http://www.amazon.com/dp/0595654371

The Art of the Meme (Kindle eBook) -- http://www.amazon.com/dp/B007ZI66FS

Artificial Intelligence in Ancient Latin (paperback) -- https://www.amazon.com/dp/B08NRQ3HVW

Artificial Intelligence in Ancient Latin (Kindle eBook) -- https://www.amazon.com/dp/B08NGMK3PN
https://redditfavorites.com/products/artificial-intelligence-in-ancient-latin

Artificial Intelligence in German (Kindle eBook) -- http://www.amazon.com/dp/B00GX2B8F0

InFerence at Amazon USA (Kindle eBook) -- http://www.amazon.com/dp/B00FKJY1WY

563 Mentifex Autograph Postcards were mailed in 2022 primarily to autograph collector customers at used bookstores to press the issue of whether or not the Mentifex oeuvre and therefore the autograph is valuable. These artwork-postcards with collectible
stamps may be traded at various on-line venues.
https://www.ebay.com
https://galaxycon.com/search?q=Mentifex

See AI 101 AI 102 AI 103 year-long community college course curriculum for AI in English.
See Classics Course in Latin AI for Community Colleges or Universities.
See College Course in Russian AI for Community Colleges or Universities. Collect one signed Mentifex Autograph Postcard from 563 in circulation.
See Attn: Autograph Collectors about collecting Mentifex Autograph Postcards.

Return to top; or to
Image of AI4U found at a book store
The collectible AI4U book belongs in every AI Library as an early main publication of Mentifex AI.

https://ai.neocities.org/EnParser.html

Mentifex
--
http://old.reddit.com/r/mentifex
http://github.com/PriorArt/AGI/wiki/MindGrid
http://cyborg.blogspot.com -- Mentifex weblog https://www.tiktok.com/tag/mentifex -- TikTok

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