Human Artificial Intelligence Machine

• US 20080256008A1
• Filed: 05/29/2008
• Published: 10/16/2008
• Est. Priority Date: 03/31/2007
• Status: Abandoned Application

• Current Assignee: Mitchell Kwok
• Original Assignee: Mitchell Kwok
• Inventors: Kwok, Mitchell
• Application Number:
  US12/129,231
• Publication Number:
  US 20080256008A1
• Time in Patent Office: Days
• US Class Current: 706/20
• CPC Class Codes: G06N 3/004 Artificial life, i.e. computing arrangements simulating life

Abstract

A method of creating human artificial intelligence in machines and computer software is presented here, as well as methods to simulate human reasoning, thought and behavior. The present invention serves as a universal artificial intelligence program that will store, retrieve, analyze, assimilate, predict the future and modify information in a manner and fashion which is similar to human beings and which will provide users with a software application that will serve as the main intelligence of one or a multitude of computer based programs, software applications, machines or compilation of machinery.

Claims

1. A method of creating human artificial intelligence in machines and computer software to predict the future and past with pinpoint accuracy, the method comprising:

an artificial intelligent computer program repeats itself in a single for-loop to;

receive input from the environment based on the 5 senses called the current pathway,

use an image processor to dissect said current pathway into sections called partial data,

generate an initial encapsulated tree for said current pathway; and

prepare variations to be searched,

average all data in said initial encapsulated tree for said current pathway,

execute two search functions, one using breadth-first search algorithm and the other using depth-first search algorithm,

target objects found in memory will have their element objects extracted and all element objects from all said target objects will compete to activate in said artificial intelligent program'"'"'s mind,

find best pathway matches,

find best future pathway from said best pathway matches and calculate an optimal pathway,

generate an optimal encapsulated tree for said current pathway,

store said current pathway and its'"'"' said optimal encapsulated tree in said optimal pathway, said current pathway comprising 4 different data types;

5 sense objects, hidden objects, activated element objects, and pattern objects,

follow future instructions of said optimal pathway,

retrain all objects in said optimal encapsulated tree starting from the root node,

universalize pathways or data in said optimal pathway; and

repeat said for-loop from the beginning;

a 3-dimensional memory to store all data received by said artificial intelligent program; and

a long-term memory used by said artificial intelligent program.

2. A method of claim 1, wherein said artificial intelligent program further comprising:

a 3-dimensional grid to store and organize predicted future pathways in a hierarchical manner, which serves to minimize repeated future predictions as well as making future predictions easier for said artificial intelligent program.

3. A method of claim 2, wherein organization of predicted future pathways can also be structured in any manner or style, according to a problem being analyzed, by using current algorithms or mathematical functions by said artificial intelligent program.

4. A method of claim 1, in which said artificial intelligent program will predict the future using 6 prediction functions:

predict future pathways by using hierarchical data analysis;

predict future pathways by using linear and universal pathways;

predict future pathways by reconstructing forgotten pathways;

predict future pathways by using external reconstructive programs;

predict future pathways by using a time machine; and

predict future pathways by using logical learning.

5. A method of claim 4, wherein said universal pathways comprising at least one of the following:

pattern strategies, computer programs, tasks, task sequences, the 4 data types, comprising;

5 sense objects, hidden objects, activated element objects and pattern objects, and language to represent future events.

6. A method of claim 4, wherein said external reconstructive programs comprising various computer software targeted at certain sensed data in pathways to reconstruct forgotten future pathways to its original state, for example, the sense of sight requires a video software to sharpen sequential images to its original state.

7. A method of claim 6, wherein said external reconstructive programs further reconstruct forgotten future pathways by changing aspects of objects in the forgotten future pathway to objects in the current pathway, said aspects of objects comprising at least one of the following:

color, size, 3-d shape, length, width, texture and object traits.

8. A method of claim 7, in which forgotten pathways reconstructed by said external reconstructive programs create imaginary future pathways based on the current pathway and pathways in memory to the exact future the robot will experience from the environment;

and serves as a benchmark to aid said artificial intelligent program to fabricate more realistic future pathways.

9. A method of claim 4, in which said time machine comprising:

a virtual world that emulates physical objects, chemical interactions and physic laws from the real world; and

creating realistic and accurate targeted virtual environments based on objects in pathways in memory.

10. A method of claim 9, wherein said time machine further comprising additional features including:

embedded software, the internet, machinery, computer hardware and integrated circuits, which help said artificial intelligent program to predict the future accurately and realistically.

11. A method of claim 10, in which said artificial intelligent program searches predicted future pathways sequentially, starting from the current state, and to provide predicted results to unpredictable events, whereby if an unpredictable event is difficult to provide a predicted result said artificial intelligent program will skip said unpredictable event and move on to the next unpredictable event in sequence order.

12. A method of claim 4, wherein said predict future pathways by using logical learning comprises the steps of:

using human intelligence to create an outline or plan of a sequence of future events; and

capturing said sequence of future events in a fixed tangible media, said fixed tangible media comprising one of the following;

a book, report papers, a video, an audio, a calendar, a computer file, a hologram and a canvas.

13. A method of claim 12, in which said predict future pathways by using logical learning further comprises the steps of:

searching in pathways for any patterns between data in fixed tangible media and future events; and

if patterns are found, designating reference pointers between data in fixed tangible media and future events.

14. A method of claim 13, wherein said artificial intelligent program predicts the future by predicting the steps to creating a fixed tangible media, whereby data in said fixed tangible media contains reference pointers to future events.

15. A method of claim 1, wherein said artificial intelligent program form complex human intelligence comprising:

pathways in memory learn knowledge by a bootstrapping process, whereby new knowledge builds on previously learned knowledge;

pathways in memory go through trial and error to keep pathways that lead to pleasure and forget pathways that lead to pain;

pathways in memory are structured in a hierarchical manner; and

similar pathways or pathways stationed in various local areas in memory self-organize to structure intelligent pathways in a hierarchical manner.

16. A method of claim 15, in which pathways in memory can form human intelligence to solve a universal problem by using conscious thoughts from said artificial intelligent program, the method comprising the steps of activating conscious thoughts to:

identify a problem to solve;

set goals;

plan steps to achieve goals;

use trial and error to bypass obstacles; and

finalizing the method by at least one of the following;

accomplish goals and abort goals.

17. A method of claim 16, in which said universal problem is moving an object from a start location to a destination location,

18. A method of claim 15, wherein knowledge is learned by said artificial intelligent program attending school from kindergarten through college.

19. A method of claim 1, wherein said artificial intelligent program is adaptable and can be applied to at least one of the following:

a machine, a software program, an electronic device and a network, wherein compatibility of external and internal sensors or controls is interfaced with said artificial intelligent program through modification of data recorded in pathways in memory.

20. A method to predict the future actions of a human being, comprising the steps of:

predicting the physical atoms and motion of said human being every fraction of a millisecond;

predicting what said human being is sensing from the environment including sight, sound, taste, touch and smell;

predicting what said human being is thinking of as a result of their 5 senses;

predicting random or systematic behavior taken by said human being;

predicting the physical structure of said human being'"'"'s brain including;

every pathway in memory and the functions of the brain;

simulating said human being and simulating an environment in a computer to predict what kind of action said human being will take in the future;

simulating said human being in a virtual world and interrogating and asking said human being questions about what they would do in such and such environments;

analyzing said human being'"'"'s brain structure and how he creates new pathways in memory; and

how sensed data modifies pre-existing pathways in memory and observing forgetting of data in pathways in said human being'"'"'s brain;

predicting said human being'"'"'s surrounding objects and their actions, said surrounding objects comprising at least one of the following;

intelligent object, non-intelligent object, imaginary object and digital object.