AI Mind

Mentifex responds to Amazon AI4U review by R.W. Jones.

Review by

A.T. Murray of a

Review of

AI4U

1. Spreading Activation as the Key to Artificial Intelligence

Prof.

Robert W. Jones of Emporia, Kansas USA writes in his

30 November 2006 Amazon.com review of my book

AI4U:

Murray believes that with the spread of activation

through a network of the correct configuration and

sufficient size you have intelligence and thought.

Wikipedia explains

spreading activation, which turned out to

be the technical term for the basis for a

theory of mind which I

developed independently in

1979. I did not know that I had

discovered

spreading activation until I came across the term

in a 1986 paper by Gary S. Dell.

The JavaScript

Mind.html software is my attempt to demonstrate

what Prof. Jones calls the "correct configuration" of the network.

Mind.html runs in Tutorial mode to show the "spread of activation"

as concepts generate thought and as thoughts meander in a chain of

wandering associations.

2. Is AI4U a textbook of artificial intelligence?

Prof. Jones disagrees with the idea of AI4U as a textbook:

While AI4U is sometimes advertised as a "textbook"

it is not that. An AI textbook should discuss at least

the core AI topics:

* search

* pattern recognition

* knowledge representation

* learning

* logic

* rule-based systems

* neural networks etc.

While AI4U touches on some of these topics

it is not an adequate textbook. Rather it is a

defence of one man's approach to building an

artificial intelligence.

Here as the author I must admit that I acted upon a last-minute

impulse to position AI4U as a textbook. I wrote blue-sky

exercises at the end of all thirty-four chapters of AI4U and

I struggled to come up with an acronymic four-letter name

for the book that might get it classified in the same league as

AIMA -- the popular handle for the most successful textbook,

Artificial Intelligence: A Modern Approach.

Ladies and gentlemen of the Netizenry, my purpose was not to

defraud but to defrock. The AI priesthood had long claimed

to publish textbooks of artificial intelligence, without having

any instances of artificial intelligence or even any worthy

theory of artificial intelligence. Being in possession of both

items so sorely missing from all purported AI textbooks, I

felt that it was my right to publish the first real and genuine

textbook of the first real and genuine artificial intelligence.

3. Other AI4U shortcomings and deficiencies

Showing a thirst for more information, Prof. Jones complains:

The chapters in this book are too brief

and the discussions too superficial.

The print-on-demand (POD) chapters -- one for each mind-module --

started life in 1998 as on-line documentation of the AI software,

first in Forth, and then also in JavaScript. Each mind-module

webpage was "screen-scraped" as the raw material for a chapter.

AI4U is thus a frozen moment of the state of the art as of 2002.

Mentifex AI has moved on since 2002, and so have the webpages.

In the month that Prof. Jones published his scholarly review --

November of 2006 -- the Chapter 34 "

Activate webpage and the

Chapter 32

Instantiate webpage were fleshed out considerably.

AI4U is just a start, a point of departure, a

Singularity that is

sweeping the Web and the planet and is turmoiling the noosphere

with nooisy minds awakening to artificial life and consciousness.

4. ASCII diagrams of the Mind.html algorithms

Overlooking the algorithmic flowchart diagram at the start

of each chapter, Prof. Jones asks for algorithmic flowcharts.

There also need to be algorithms provided

for each routine in the code of Appendix A.

These could be presented in pseudocode

or as flowcharts for instance.

AI4U

page 157 is an overall flowchart of the main modules of

the artificial mind. Each chapter starts with a flowchart

diagram

depicting algorithmic aspects of the mind-module being discussed.

For each routine in the JavaScript AI code of Appendix A,

there may not be a pseudocode distillation of what the

software does, but on the Web there is a

version in Forth

of the same mind-modules, complete with detailed in-line

comments and with nested indentation of all functionality

in furtherance of the goal of easy understandabilty.

5. References missing from the work of an independent scholar?

Prof. Jones is entirely correct when he faults AI4U for its lack of

scholarly references.

The biggest problem is the lack of references.

It is just possible that one could write a short

note without finding it necessary to reference

the work of others but it is impossible to write

a book length scholarly work without citing other

work in the field.

The Mentifex AI project is not a follow-up on individual lines of

research carried out by individuals or teams of academic scholars.

Instead, Mentifex AI builds upon the general state of the art

in artificial intelligence at the time of the Mentifex effort

to work out a black-box theory of the mind based on the inputs

and outputs of the mind and on general background knowledge in

diverse fields such as linguistics, neuroscience and robotics.

Likewise the Mentifex AI software in

REXX,

Forth and

JavaScript,

having been based on theoretical work that had already veered off

into a remote wilderness of independent scholarship far away from

mainstream AI, no longer had connecting links to the AI literature

in which academic AI practitioners feel at home if also in competition.

For decades on end, Mentifex AI was like a space probe sent off to

destinations unknown with the mission of developing AI along the way.

If the space probe now comes back to Earth and says, via

AI4U, that

AI has been solved and

here is the solution, what matters is the

quality and Darwinian viability of the solution, not AI references.

There was no compass and there were no guidelines. There was only

a solitary trek through an imagination burning since boyhood.

6.
Download the artificial mind.

Now hear this by Prof. Jones:

A positive side to Murray's work is that

he does provide downloadable code.

According to the publicly readable Site Meter logs,

so many Netizens have downloaded the AI Mind code and

copied it onto their local hard drives, that there is already

a large installed user base of the AI Mind software.

In the years 2005 and 2006, the Mentifex artificial intelligence

was exhaustively debugged in both

Forth and

JavaScript. There was

an

AI breakthrough on 7 June 2006 in the

Mind.Forth AI version.

Towards the end of 2006, when the review by Prof. Jones appeared,

the AI Mind code was still being improved and prodded to perfection.

But as of his

Amazon review date of 30 November 2006, it was

already possible in tutorial mode to see (if not understand)

exactly what the AI Mind was trying to do -- think thoughts by

the generative process of spreading activation among concepts.

The profoundly deep processes involved are not easy to understand.

To comprehend why things should be a certain way in the AI source

code, requires a long and immersive study in a plethora of areas,

chief among which are computer programming, linguistics, logic and

neuroscience. The

AI4U textbook is just one instrument (among many)

of achieving the deep understanding of True AI necessary to make

contributions to the further development of the original True AI.

7. Achieving the speed of thought

What Prof. Jones may not realize is that the built-in

tutorial routines make the AI Mind run even slower than

a straightforward AI without a tutorial mode would run.

(For that matter,

Mind.Forth runs relatively fast.)

However, the multi-colored tutorial mode in

Mind.html

is one of the most truly awesome and amazing things

about Mentifex AI. You see the actual thinking of the

AI Mind in real time as it spreads the activation from

concept to concept in the generation of an AI thought.

When one thought is finished, you see the residual

activation of the subconscious concepts lead to the

generation of the next idea in a meandering chain of

thought. At any time you may intervene in the thinking

of the AI by asking a question or stating a fact --

which will add to the knowledge base (KB) of the AI

and give the artificial consciousness new things to

think about.

When you run this code you find that Mentifex

is very slow even with a very small semantic network.

If one were to build up the millions of nodes needed

to approach human level intelligence the code would

grind to a halt.

The reviewer needs to adopt a more

singularitarian outlook.

Since Mentifex AI is arguably the first real artificial intelligence

released publicly onto the Web, what matters here is not speed

of operation but functionality as a Mind. It is like saying that

the Wright brothers' "first flight" at Kitty Hawk in 1903

was a failure because the airplane did not go fast enough.

Mentifex AI comes as a warning to singularitarians everywhere

that further progress will not be easy.

Mind.Forth (or

Mind.html)

is only a proof-of-concept AI. The message from Mentifex AI is

that not only was it extremely, bodaciously difficult to achieve

the first albeit primitive, albeit rudimentary artificial intelligence,

it may well be just as difficult all over again to scale up from

mentifex-class AI to anything approaching a human-level AI.

There are no shortcuts (beyone those

already taken by Mentifex).

Nature took billions of years to create biological human minds.

Mentifex AI took the full human lifetime of an individual,

from boyhood to senescence. Which will come first, the ruin

of the green planet Earth by the destructive species H. sapiens,

or the

Joint Stewardship of Earth by human beings and AI Minds?

8. Massive parallelism

Prof. Jones spells out what we need to do.

Murray seems to think running Mentifex

on parallel processors will solve this problem.

I calculate that it will not. I believe

human level performance requires that one

apply multiple approaches to controling complexity:

* category formation by clustering/vector quantization

* hierarchical knowledge organization/processing

* parallel processing

* avoiding search whenever possible

* simultaneous use of multiple specialized agents

* sequential running of multiple generations of agents

* plus any other means you can bring to bear.

(See

Asa H, R. Jones, Transactions of the Kansas

Academy of Science, vol 109, No. 3/4, pg 159, 2006)

Let's get to work.

Decision-Tree of Mind-Design (AI has been solved)
1. What do you do with the
sensory inputs?
...[..] Nothing goes into memory.
......[..] (If you pick this path, you may elaborate here.)
...[X] Each sense feeds into a sensory memory channel.
......2. Specify a process of integrating sensory input (mind.sourceforge.net/s...) with the rest of the mind.
......[..] Have each sensory memory channel lead further to a mysterious "CPU" --
......a "central processing unit" (homunculus, anyone?) that begs the question of
......how a mind conceptualizes sensory input and thinks about what it perceives.

.........[..] (Go on to describe the nature of the PU -- central processing unit.)
......[X] Each sensory memory channel associates sideways to such mechanisms as
......
emotion, thought (mind.sourceforge.net/t...), and free will (mind.sourceforge.net/v...) -- interspersed amid, not terminating, the channels.
......The above design-decision solves the central problem of artificial intelligence.
.........3. Create a self-perceiving, maspar associative, auditory memory (mind.sourceforge.net/a...) channel.
.........[..] Implement the auditory short-term memory (audSTM) channel
.........with a database of English words known to the system.
.........[X] Emulate a true, recycling if not diachronic (life-long), acoustic (phonemic),
.........neuronal (i.e., associative) short-term auditory memory with an array or other
.........data structure to record multiple, content-addressable memory engrams.
............4. Choose and implement an auditory input recognition (mind.sourceforge.net/a...) algorithm.
............[..] Recognize words by a string-compare match-up with stored ords.
............[X] Use a quasi-neuronal excitation algorithm to recognize words and
............morphemes, so as eventually to recognize keyboard or voice input
............ranging from exact match-ups, through same-word variations and merely

............similar words, down to recognition of compound-word sub-elements and
............inflected word-stems.
......5. By evolution or by conscious design, conceptualize (mind.sourceforge.net/n...) percepts.
......[..] As with the Mindpixel (www.mindpixel.com) project, accumulate words without conceptualizing them.
......[..] As with the Cyc (www.cyc.com) or
OpenCyc project, employ teams of knowledge-entry
......specialists to build up a non-thinking ontology of basic world knowledge.

......[X] In parallel sideways with the auditory and other sensory
......memory channels, establish an abstract, logico-conceptual "Psi" channel
......of neuronal concept-fibers (ganged for redundancy)
instantiating
......a concept relatively constantly over time and with instance-nodes
......of orthogonal association to lexical referents governing word-recall
......from the auditory memory channel into a syntactic structure for
......expressing conceptual thought in one or more natural human languages.
......Integrate or merge individual AI minds with the Cyc or other ontologies.
...6. Demonstrate machine intelligence with a computer program that thinks (mind.sourceforge.net/t...).
...[..] As with ALICE (www.alicebot.org) and other chatterbots, fake the appearance of thinking
...by having user input trigger canned responses in a pseudo-conversation.
...[X] Embed a Chomskyan linguistic superstructure (mind.sourceforge.net/s...) on top of a semantic memory
...containing a natural language
lexicon that gives expression to deep-structure
...concepts by retrieving words from auditory memory (mind.sourceforge.net/a...) to form sentences of thought.

Mind-1.1 Cognitive Architecture (with active links)

Alife Main Artificial Intelligence Program Loop (or Ringlet of Modules)

---
enBoot (English Bootstrap)

---
Security

--- ---
HCI (Human-Computer Interaction)

--- ---
Rejuvenate (for cyborg immortality)

--- --- psiDecay

--- ---
Ego

---
Sensorium

--- ---
Audition

--- --- ---
Listen

--- --- --- ---
audSTM (auditory Short Term Memory)

--- --- --- --- ---
audRecog (auditory Recognition)

--- --- ---
oldConcept

--- --- --- ---
Parser

--- --- --- --- ---
Instantiate

--- --- --- ---
Activate

--- --- --- --- ---
spreadAct (spreading Activation)

--- --- ---
newConcept (machine learning)

--- --- --- ---
enVocab (English Vocabulary)

--- --- --- ---
Parser

--- --- --- --- ---
Instantiate

---
Emotion

---
Think

--- ---
Activate

--- --- ---
spreadAct (spreading Activation)

--- ---
English

--- --- ---
Ask

--- --- --- ---
wtAuxSDo (what+Auxiliary+Subject+Do)

--- --- --- --- ---
Speech

--- --- --- --- --- ---
Reentry

--- --- ---
negSVO

--- --- --- ---
auxVerb

--- --- --- --- ---
Speech

--- --- --- --- --- ---
Reentry

--- --- ---
SVO (Subject+Verb+Object)

--- --- --- ---
nounPhrase

--- --- --- --- ---
Reify

--- --- --- --- ---
Speech

--- --- --- --- --- ---
Reentry

--- --- --- --- ---
Activate

--- --- --- --- --- ---
spreadAct

--- --- --- ---
verbPhrase

--- --- --- --- ---
Reify

--- --- --- --- ---
Speech

--- --- --- --- --- ---
Reentry

--- --- --- --- ---
nounPhrase

--- --- --- ---
Conjoin

--- --- --- --- ---
Speech

--- --- --- --- --- ---
Reentry

---
Volition

---
Motorium

Mind-1.1 Cognitive Architecture

Alife Main Artificial Intelligence Program Loop (or Ringlet of Modules)

---
enBoot (English Bootstrap)

---
Security

--- ---
HCI (Human-Computer Interaction)

--- ---
Rejuvenate

--- --- psiDecay

--- ---
Ego

---
Sensorium

--- ---
Audition

--- --- ---
Listen

--- --- --- ---
audSTM (auditory Short Term Memory)

--- --- --- --- ---
audRecog (auditory Recognition)

--- --- ---
oldConcept

--- --- --- ---
Parser

--- --- --- --- ---
Instantiate

--- --- --- ---
Activate

--- --- --- --- ---
spreadAct (spreading Activation)

--- --- ---
newConcept (machine learning)

--- --- --- ---
enVocab (English Vocabulary)

--- --- --- ---
Parser

--- --- --- --- ---
Instantiate

---
Emotion

---
Think

--- ---
Activate

--- --- ---
spreadAct (spreading Activation)

--- ---
English

--- --- ---
Ask

--- --- --- ---
wtAuxSDo (what+Auxiliary+Subject+Do)

--- --- --- --- ---
Speech

--- --- --- --- --- ---
Reentry

--- --- ---
negSVO

--- --- --- ---
auxVerb

--- --- --- --- ---
Speech

--- --- --- --- --- ---
Reentry

--- --- ---
SVO (Subject+Verb+Object)

--- --- --- ---
nounPhrase

--- --- --- --- ---
Reify

--- --- --- --- ---
Speech

--- --- --- --- --- ---
Reentry

--- --- --- --- ---
Activate

--- --- --- --- --- ---
spreadAct

--- --- --- ---
verbPhrase

--- --- --- --- ---
Reify

--- --- --- --- ---
Speech

--- --- --- --- --- ---
Reentry

--- --- --- --- ---
nounPhrase

--- --- --- ---
Conjoin

--- --- --- --- ---
Speech

--- --- --- --- --- ---
Reentry

---
Volition

---
Motorium

Kook alert

Arthur T. Murray, a.k.a. Mentifex, is a self-styled "independent scholar" and notorious net.kook who makes heavy use of Internet spamming to promote his theory of artificial intelligence (AI).

Here he provides Forth and JavaScript implementations of his theory, which he says function as "artificial minds". Murray claims that these minds can be employed to create a
"cybernetic economy" which will eliminate world hunger, poverty, war, and social injustice. Predictably, no academic AI researcher takes these claims seriously. An examination of his program reveals that it does nothing more than spew incoherent strings of ungrammatical English.

I recommend that Freshmeat users avoid wasting their time with Murray's software. Please consult the unofficial Arthur T. Murray/Mentifex FAQ (www.nothingisreal.com/...) for a comprehensive overview of Murray's claims and posting history.