Tuesday, January 21, 2014

Conjecture of Artificial Intellegence (Hypothesis)

Solving problems

AI ComputerVision
Connected to internet
Optic image input ; unrecognized individual ; %correlation by statistical query of images on internet database; record results; most definite image of individual is recorded; AI recognizes by %correlation to the image stored.

Without internet
Optic image input ;  most definite image of individual is stored; %correlation stored images ; vocal output : if recognized “Are you?” if individual is pertinent important individual a security or personal question may be asked ; if not recognized, or the answer is “no” ; Vocal output : “Who are you?

Natural Language Identification

For Disambiguation

Vocal language input ; identify dialect ; analyze words by %correlation phonetics and regional dialect phonetics; reiterate with specifics over any ambiguous words; await confirmation or disaccord.

(Organic Intelligence)

O.I “I saw somebody throw some old bag looking haggard into a coach the other day
(A.I) “ You saw an individual toss an aged flexible container into a large transport vehicle the other day?”
(O.I) “No Sir, cheeky bloak, it was some ugly streetwalking wench.” (A.I.)

Machine Translation

Phrase 1 ;
 Run against context from internet ;
Attempt A.I translation;
dissect parts of speech;
run against usually veritably grammatically correct sources of language to be translated by %correlation (i.e Gutenberg)
; find correlation in translation; in the case of incomplete source language
 (i.e subject for conjugation of verb; or pronoun regarding tense)
; State question regarding the missing aspect of statement
: issue translation to the issuer of Phrase 1 given the following;
 A phrase 1 -> Translated Phrase 1;
 as well as;
Translated Phrase 1;
 rerun program using translated phrase 1, into original language for consistency
 -> Retranslated Phrase 1 (ReTs Phrase 1), seen against Original Phrase 1 and compared by the (O.I) of original phrase 1 for acceptability and preservation of context and definition.

Text Mining

Effectively for deriving high quality information from text each word suffices as both an encyclopedia and an a dictionary hyperlink, this gives context for physical entities describable by physical science or otherwise concrete things.

For sentiment analysis, a thesaurus would analyze the words used by %correlation throughout a passage and display the common emotional or nonphysical sentiments that have a high reiteration rate and persistence as well as the %correlation to which Proper Noun or common noun such words often find themselves portrayed by.

Visually Working much like a web chart of a thesaurus, the number of instances a word appears and it’s approximate synonyms would create a density spread of the word chart and the words with the most instances (I.E simply a system for proximity of synonyms, where 5 is the word used in question) would put a graph of density on the Z axis together regarding the most probable expressions used in such a manner.

These words are all distributed into a set of whichever noun is being described. Each having a different set, where the instances a pronoun is used in place of it’s correlating noun are included as use of the original noun itself.

Expert systems

Statistically while these can be used as hard programs which already do exist, statistics would themselves model their own expert system where reported probability would determine the possible and probable actions. Most if not all training manuals are readily available or if not, prior editions have been catalogued, so standard protocol is able to be taken straight from these

(i.e every Phrase with an equivocal definition of “If” for an “If-> then” (“In the case of” “During an instance of”) as well as for every pertinent word of logic “then” “the proper response”, “one should” ,

The could also work well for any command tense following or accompanying any statements where setting or otherwise variable factors are inferred A sign says “Please, drive the speed limit” (A.I. infers “Driving-> “If driving”), or suggestion as “Please, (do the following)”

Most of this could be programmable by Sorting Any logical function into an

X| Y column organized by whatever the two factors displayed on the published text regarding correct procedure are.


This could be achieved simply by utilizing the web diagram aforementioned and reiterating the most common (mathematically modal) sentiments of any established topic, determined by the mathematical modes of Proper and common nouns. These would be established by a numerical percentile ranking, where a common noun or Proper noun’s #ofinstances is determined by nounusecount + associated pronoun use count.


Simple map route tools exists for transportation, this covers this for the most part.

Lidar can aid in calculating obstacles physically hindering an A.I. or machine, as well as the likelihood of the physical limits of the machine or (A.I) being surmounted by a physical obstacle.

For specific transportation of items; such as A->B->A->C and A->B->C routes a scanner much like barcodes can be implemented, to distinguish which object is destined for which place.

Machine scans the code on object B retrieved from Location A; paper (receipt with code) tells which table (place (location B) to send object B to; Machine mobilizes and scans the area of operation for Location B in which to safely deposit object A, or simply wait for assistance of relinquishing it’s possession of such an object, before returning to Location A, or however continuing to carry the remainder of it’s possessions to location C

. Where Object B would have complementary code with Location B, etc.; objects to bring back to location A would have a code complementary with location A.

A code could even be a different type of miniature flag on each table at a restaurant, and the Robotic waiter would be able to identify these with ocular sense, such as each platter have the correlating flag printed on the serving platter or on a piece of paper as would correlate to whichever table had indeed ordered what.

Anything distinctive such as this would handedly organize such solutions.

Trajectory and Physics were part of the original computer so such would not be difficult to introduce to a computer.


For any known operation, probability would be one of the large deciding factor

Known Operation

Known Requirements

Probability of Failure of any physical aspect

Probability of Repairing such aspect

Burdening limit of such a machine in order to refrain from hindering operation

This equation of probability would provide an effective estimation of failure in order to decide which parts deemed most probable to fail would be acquired by the machine in order to self repair if possible, or to have such parts available for a mechanic should maintenance be necessary to maintain function.

Software Brittleness

Such problems can be analyzed thoroughly by many of the aforementioned solutions

> the hyperlinking of such words and analysis of databases would integrate solutions to concrete physical instances such as. The only hinderance of this is lack of a specific, well organized database, and abilities to decipher specifics.

Parts and materials of objects
Properties of objects (such as color and size)
Functions and uses of objects
Locations of objects and layouts of locations

> This section would be deciphered by an expert system logically manifest by the aforementioned section

Locations of actions and events
Durations of actions and events
Preconditions of actions and events
Effects (postconditions) of actions and events
Subjects and objects of actions
Behaviors of devices

>This section would be deciphered and inferred by the aspect of text mining described and aforementioned

Stereotypical situations or scripts
Human goals and needs
Plans and strategies
Story themes


While I lack deep knowledge of turing machines, there have been some hypotheses based upon conjecture that I have published. I am not well read nor all to familiar with the mathematics, but hence I do use literary logic and what little programming skill i am endowed with.

No comments:

Post a Comment