Artificial General Intelligence (AGI) is awakening across the universe and
across cyberspace. Your mission, should you choose to accept it, is to hire
and assign programmers to create your own in-house branch of the emerging
phenomenon of AGI Minds using Natural Language Understanding for automated
reasoning with logical inference. Don't look back -- survival of the
fittest may be gaining on you.

1. Code the MainLoop module -- http://ai.neocities.org/MainLoop.html

Use either an actual loop with subroutine calls, or make a ringlet of
perhaps object-oriented module stubs, each calling the next stub. Provide
the ESCAPE key or other mechanisms for the user to stop the AI.

2. Code the Sensorium module or subroutine --
http://ai.neocities.org/Sensorium.html

Start a subroutine or module that is able to sense something coming in from
the outside world, i.e., a key-press on the keyboard.

3. Stub in the EnThink module for English thinking --
http://ai.neocities.org/EnThink.html

4. Initiate the AudInput module for keyboard or acoustic input.

Drop any [ESCAPE] mechanism down by one tier, into the AudInput module, but
do not eliminate or bypass the quite essential Sensorium module, because
another programmer may wish to specialize in implementing some elaborate
sensory modality among your sensory input stubs. Code the AudInput module
initially to deal with ASCII keyboard input. If you are an expert at speech
recognition, extrapolate backwards from the storage requirements (space and
format) of the acoustic input of real phonemes in your AudInput system, so
that the emerging robot Mind may be ready in advance for the switch from
hearing by keyboard to hearing by microphone or artificial ear.

5. The TabulaRasa loop.

Before you can create an auditory memory AudMem subroutine for storing
input from the keyboard, you may need to code a "TabulaRasa" loop that will
fill the mental memory of the AI with blank engrams, thus reserving the
memory space and preventing error messages about unavailable locations in
the AI memory.

6. MindBoot English +/- Russian bootstrap --
http://ai.neocities.org/MindBoot.html

The knowledge base (MindBoot) module makes it possible for the Strong AI
Mind to begin thinking immediately when you launch the more advanced AI
program. Here we stub in the EnBoot subroutine with an English word or two
before the AudMem module begins to store new words coming from the AudInput
module. The EnBoot stub shows us that the first portion of the AI mental
memory is reserved for the innate concepts and the English words that
express each concept. If you use the same Unicode that Perl enjoys to
create a Strong AI Mind in Arabic, Chinese, Hungarian, Indonesian,
Japanese, Korean, Swahili, Urdu or any other natural human language, you
will need to create a bootstrap module for your chosen human language.

7. AudMem (Auditory Memory) -- http://ai.neocities.org/AudMem.html

Into the auditory array that was filled with blank spaces by the TabulaRasa
sequence and primed with some bootstrap content by the EnBoot or MindBoot
sequence, insert some new memories with the AudMem auditory memory module.
Modify the AudInput module to prompt for English words and modify the
EnThink module to display words stored in memory as if they were a thought
being generated in English (or in your chosen natural human language).


8. NewConcept Module -- http://ai.neocities.org/NewConcept.html

The NewConcept module addresses the symbol grounding problem by creating a
new concept for any unrecognized word in the input stream, even a
misspelled word entered by mistake. In Symbolic AI, each word of natural
language is the symbol of a concept, and as such is the key to accessing
the concept. Of course, a recognized image may also grant access to a
concept.


9. EnParser English Parsing Module -- http://ai.neocities.org/EnParser.html

The EnParser (English parser) module does not so much determine the part of
speech of a word of input, but more importantly it assigns to an input word
its grammatical role in the complete phrase being processed during Natural
Language Understanding.


10. InStantiate -- -- http://ai.neocities.org/InStantiate.html

The InStantiate module creates a new instance or node of a concept in
Symbolic AI when a word of input activates the concept. The created
instance is subject to change by the possibly delayed action of the English
EnParser or Latin LaParser or Russian RuParser module, because Natural
Language Understanding must often wait for the end of an idea before the
whole idea can be understood.


11. AudRecog auditory Recognition Module --
http://ai.neocities.org/AudRecog.html

The AudRecog module for auditory recognition recognizes various forms of a
word, such as singular or plural nouns, or verbs with various inflected
endings.


12. TacRecog Module -- http://ai.neocities.org/TacRecog.html

The TacRecog module for tactile recognition in robots implements the haptic
sense for an AI Mind directly to touch and feel the external world. Even an
AI Mind not yet embodied in a physical robot may use TacRecog directly to
sense and feel a number-key pressed by the human user on a computer
keyboard. With philosophic implications for the learning of mathematics, an
AI Mind may directly sense numeric quantities through the numeric keys on
the keyboard.


13. OldConcept Module -- http://ai.neocities.org/OldConcept.html

If the AudRecog module recognizes a particular word, then the AudInput
module calls the OldConcept module to create a new instance of the
previously known concept. If a word is not recognized, AudInput calls the
NewConcept module to create a new concept for the word as a symbol.


14. SpreadAct Spreading Activation Module --
http://ai.neocities.org/Spreadact.html

The SpreadAct module for Spreading Activation performs both simple
spreading activation between concepts and also an extremely sophisticated
role of responding to various input queries posed by human users.


15. PsiDecay -- -- http://ai.neocities.org/PsiDecay.html

The PsiDecay module lets the activation on "Psi" concepts decay gradually
over time, so that mind-modules which impose or spread activation may
operate more effectively and so that artificial Consciousness may emerge as
the seearchlight of attention shifts from one highly activated concept or
sensation to other highly activated concepts or sensations.


16. Speech Module -- http://ai.neocities.org/Speech.html

The Speech module fetches characters from a starting point in auditory
memory and displays the characters on-screen until a blank space occurs to
signify the end of the word stored in memory.


17. Indicative -- http://ai.neocities.org/Indicative.html

The Indicative Mood module, as opposed to the Imperative Mood module for
expressing commands, calls linguistically generative modules such as
EnNounPhrase and EnVerbPhrase to express a thought indicating an idea or a
belief.


18. EnNounPhrase English Noun-Phrase Module --
http://ai.neocities.org/EnNounPhrase.html

The English noun-phrase module selects the most activated noun-concept to
be the subject of a phrase or sentence.


19. ReEntry -- http://mind.sourceforge.net/reentry.html

The ReEntry module is used in the various JavaScript Minds to facilitate
the reentry of an output word back into the AI Mind.


20. EnVerbPhrase English Verb-Phrase Module --
http://ai.neocities.org/EnVerbPhrase.html

The English verb-phrase module fetches from memory a verb that has
basically been pre-ordained to be expressed as the verb in a
Subject-Verb-Object (SVO) phrase or sentence. EnVerbPhrase also calls a
module like EnVerbGen to generate an inflected form of an indicated verb.
EnVerbPhrase is designed with a view to calling the VisRecog module to
supply the English word for the visually recognized object of the action of
a verb, such as in a sentence like "I see... (a dog)."


21. EnAuxVerb English Auxiliary Verb Module --
http://ai.neocities.org/EnAuxVerb.html

The English auxiliary-verb module calls auxiliary verbs such as "do" or
"does" for use in the generation of such sentences as a negated idea, such
as "God does not play dice."


22. AskUser Module -- http://ai.neocities.org/AskUser.html

The AskUser module works in conjunction with the logical InFerence module
to ask a human user to confirm or deny a logical inference being proposed
inside an AI Mind.

23. ConJoin Module -- http://ai.neocities.org/ConJoin.html

The ConJoin module inserts a conjunction during the generation of a
compound thought. For instance, if an AI Mind has two or more higjly
activated subjects of thought, the ConJoin module will insert the
conjunction "and" to join two active ideas together.


24. EnArticle Module -- http://ai.neocities.org/EnArticle.html

The English article module inserts the article "a" or the article "the"
before a noun in a sentence being generated.


25. EnAdjective Module -- http://ai.neocities.org/EnAdjective.html

The English adjective module recalls and inserts an adjective during the
generation of a thought.


26. EnPronoun Module -- http://ai.neocities.org/EnPronoun.html

The English pronoun module replaces a noun with a pronoun.

27. AudBuffer Module -- http://ai.neocities.org/AudBuffer.html

The auditory buffer module stores a word in memory for transfer to the
OutBuffer module for inflectional processing.


28. OutBuffer Module -- http://ai.neocities.org/OutBuffer.html

The OutBuffer module holds a word in a right-justified framework where the
ending of the word may be modified by a module like the EnVerbGen module
for generating a required English verb-form.


29. KbRetro Module -- http://ai.neocities.org/KbRetro.html

The KbRetro module retroactively adjusts the knowledge base (KB) of the AI
in response to user input responding to a question from the AskUser module.


30. EnNounGen English-Noun Generating Module

The English noun-generating module shall modify a singular English noun
into its proper plural form by adding "s" or "es".


31. EnVerbGen EnGlish Verb Generating Module --
http://ai.neocities.org/EnVerbGen.html

The verb-generation module operates when the verb-phrase module fails to
find a needed verb-form in auditory memory.


32. InFerence Module -- http://ai.neocities.org/InFerence.html

The InFerence module engages in automated reasoning with logical inference.
For instance, if the user inputs 'John is a student," the AI may infer the
possibility that John reads books, The AskUser module asks the user, "Does
John read books?" Depending on a "yes" or "no" answer, the KbRetro module
retroactively adjusts the knowledge base (KB), either discarding the
unwarranted inference or by leaving intact a true inference or inserting
"not" into a negated inference such as "John does not read books."


33. EnThink English Thinking Module -- http://ai.neocities.org/EnThink.html

The English thinking module calls such subordinate modules as the
Indicative module for a declarative sentence or the InFerence module for
automated reasoning.


34. Motorium Robot Motor Memory Module --
http://ai.neocities.org/Motorium.html

As soon as you have sensory memory for audition, it is imperative to
include motor memory for action. The polarity of robot-to-world is about to
become a circularity of robot - motorium - world - sensorium - robot. If
you have been making robots longer than you have been making minds, you now
need to engrammatize whatever motor software routines you may have written
for your particular automaton. You must decouple your legacy motor output
software from whatever mindless stimuli were controlling the robot and you
must now associate each motor output routine with memory engram nodes
accreting over time onto a lifelong motor memory channel for your mentally
awakening robot. If you have not been making robots, implement some simple
motor output function like emitting sounds or moving in four directions
across a real or virtual world.

35. Volition module for robot free will --
http://ai.neocities.org/Volition.html

In your robot software, de-link any direct connection that you have
hardcoded between a sensory stimulus and a motor initiative. Force motor
execution commands to transit through your stubbed-in Volition module, so
that future versions of your thought-bot will afford at least the option of
incorporating a sophisticated algorithm for free will in robots. If you
have no robot and you are building a creature of pure reason, nevertheless
include a Volition stub for the sake of AI-Complete design patterns.


36. Imperative -- http://ai.neocities.org/Imperative.html

The Imperative Mood module, called by the free-will Volition module, issues
commands such as "Teach me something" to the human user.


37. The SeCurity module --
http://github.com/kernc/mindforth/blob/master/wiki/SeCurity.wiki

The SeCurity module is not a natural component of the mind, but rather a
machine equivalent of the immune system in a human body. When we have
advanced AI robots running factories to fabricate even more advanced AI
robots, let not the complaint arise that nobody bothered to build in any
security precautions. Stub in a SeCurity module and let it be called from
the MainLoop by uncommenting any commented-out mention of SeCurity in the
MainLoop code. Inside the new SeCurity module, insert a call to ReJuvenate
but immediately comment-out the call to the not-yet-existent ReJuvenate
module. Also insert into SeCurity any desired code or diagnostic messages
pertinent to security functions.


38. The HCI module in JavaScript manages human-computer interaction.


39. Spawn -- http://ai.neocities.org/Spawn.html

The Spawn module issues commands to the operating system to make copies of
an AI Mind that include experiential memories up to the point of the
spawning of each new AI Mind.


40. MetEmPsychosis -- http://ai.neocities.org/MetEmPsychosis.html

The module of MetEmPsychosis or soul travel is designed to spawn a remote
copy of an AI Mind while immediately deleting the previous version of the
software and memories so that the remote new version of the AI Mind is
effectively the same AI traveling across cyberspace in a metastatic process
akin to mind uploading.

http://ai.neocities.org/AiSteps.html

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