FAQSearchEmail

humanlevelartificialintelligence.com   

  
 Home

Home | Videos | Contact Us   

 
Home
HLAI
UAI
Videos
Books
Patents
Notes
Donation

  Welcome to my website!  

" I have taken the human brain, reversed engineered it, and turned it into a software program. According to the patent office, I am the scientist who filed the first copyrights, first patent applications, and first youtube videos on this technology (2006 onward). I am not trying to patent portions of the human brain like deep learning applied to visual images. Instead, I'm trying to patent the whole human brain. All documents I have sent to the United States government describe every single aspect of a digital human brain and how it works. The most important thing is showing the public how my robot thinks -- what does my digital brain software output. I made 200 videos on youtube showing how my robot thinks while doing various human tasks, like cooking, playing videogames, flying an airplane or solving complex problems.

In 2015, Google tried to build software to play videogames. Fortunately for me, their software can only play simple games like Atari, using reinforcement and deep learning. In 2016, Google tried to build a UNIVRSAL AI called AlphaGo to play the ancient Chinese game, Go. This is a big achievement in Artificial Intelligence. However, their software can't play goal-driven games like pac-man, super mario or more complex games like Zelda. Google made an annoucement in 2016 proposing a plan to solve this problem:

Deep learning + reinforcement planning + human-level AI

If you look carefully at my invention and compare it to Google's proposed idea in 2016, they look strikingly similiar. I have sent this idea to the US copyright office and patent office way back in 2006. The big craze in 2015 is deep learning. However, deep learning is a very small part of my invention (about 10 percent). There is a whole lot more components to a human brain than simply deep learning.

Human-level Artificial Intelligence is the official term used to describe a robot that can think and act like a human with college level intelligence. There is another recently coined term called AGI, which stands for artificial general intelligence.

When you apply human-level AI to videogames, the robot is thinking like a human. He is idenifying objects in the game, making decisions, planning strategies to beat the game, generating common sense knowledge, doing simultaneous tasks, doing recursive tasks, brainstorming new strategies, correcting itself, setting recursive goals and so on. By using Human-level AI, the robot is able to play any videogame because he is using human intelligence to play and not pre-defined instructions by a programmer. The robot can play new games that it has never played before.

In fact, this robot can do any human task. If he doesn't know how to drive a car, the robot can spend time reading books or attending driving school to learn this skill. He will need to practice driving in order to refine his skills. All knowledge in the robot's brain comes from attending school. No human programmers are needed to predefine language skills, or problem solving skills, or rules of life, etc. This robot simply goes to school to learn grammar or problem solving or decision making skills. "

NEW!!!!      Videos on Human Level Artificial Intelligence

     
 

    Human Artificial Intelligence:  Book4

    by Mitchell Kwok

     entitled -- Building super intelligent robots

                 

 

Before I explain how my invention works, The viewer needs to see how my robot thinks. Basically, this video proves my robot has Human-Level AI.

 

 

The current artificial intelligence theories donít work (2006)
Some people think that building a robot to open a door is a very easy thing to do.  Reality is that it is very difficult to program a robot that can open a door (under any circumstances).  MIT and Stanford University have been emphasizing this problem for a very long time.  They use hierarchical recursive planning programs, such as the strip program to solve the problem.  The robot needs to fulfill preconditions, such as possession of a key,  in order to open a door. What if the robot can't find the key? or the key chain has 20 different keys and only one key can unlock the door?  Even more difficult is the fact that the robot might not find the key and uses alternative methods to get into the room (such as breaking a window or calling a locksmith).  Expert programmers have to program in all the possibilities of opening a door and the possibilities run infinitely.

If scientists can't build a robot to do a simple task like open a door, then what makes you think they can build a robot to replace a janitor or nurse.  A human janitor can open a door under any circumstances.  In addition, the human janitor can do many other tasks like clean a room, mop the floors, answer questions, wash dishes, pick up a package from the post office, report incidents, and drive a car.  Robots have to be pre-programmed with specific instructions, both knowledge and procedures, for every single human task.  This is the main reason why software companies have not commercially sold robots to replace basic human jobs yet (janitors, nurses, teachers, construction workers, factory workers, farm workers, etc).

 

Human Level Artificial Intelligence

The human brain is a recording device that records 5 sense movie sequences, called pathways. These movie sequences store the 5 senses: sight, sound, taste, touch, and smell. Muscle movements and pain/pleasure is a part of the touch sense and included in the pathways.

The purpose of the pathways is to store both static information and linear information. A picture is considered static information, while the steps to cook a hamburger is considered linear information. Pathways are structured hierarchically and this is where deep learning is applied to each pathway experienced by the robot. Deep learning store static information, like a picture, or sequence data, like the instructions to cook a hamburger, in an optimal manner where information is shared (using hierarchical trees) and repeated information are minimized.

If the robot experiences 10 million cat images, his digital brain isn't storing all 10 million cat images in memory. The robot's brain stores several cat objects in memory and said 10 million cat images share information in hierarchical tree/s. A more complex type of deep learning is applied to movie experiences, aka pathways. In the example below are 3 pathways that are very similar. The words used in each pathway is different, but the meaning is very similar/same. After learning many examples, only the meaning is stored in memory.

Finally, the robot's brain forget information in a hiearchical manner. In terms of deep learning, the lower levels are forgotten first, but the higher levels are harder to forget.

 

The key to human intelligence

Language is the key to how these pathways are structured in an intelligent manner. Language will define the functions and behaviors of each pathway in the robot's brain. In FIG. 3, the sentence: "shoot the basketball until it goes into the hoop" is a for-loop that will loop itself based on a condition/s.

in this example, the sentence: "constantly drive between the 2 white lines" is a constant rule that tells the pathway to constantly follow this rule while driving.

in this example, the sentence: "cook hamburger and talk on the phone simultaneously" manage 2 tasks simultaneously by switching between tasks until both tasks are completed.

in this example, the sentence: "the world is round, not flat... and Hawaii is the 50th state and not the 49th state." is forcing the robot's brain to correct wrong information stored in memory. In this case, the correct data is created in memory (marked as correct) and the wrong data will have a forget function next to it (marked as wrong). Thus, the next time the robot retrieves the fact, the correct data will be present. This example shows pathways can do complex database functions.

in this example, the sentence: "cook lobster roll. first, prepare the lobster meat" manages recursive tasks. The 2 sentences basically manages recursive tasks. It knows it is currently making a lobster roll. At the same time, it also knows that the first step is to prepare the lobster meat. After finishing the first task the second task will pop up in the robot's brain.

in this example, the sentence: "cook hamburger" is a constant task. The pathway will contain the beginning and ending of the task.

If you think about it, these intelligent pathways can form any type of state machine or computer program. Pathways can form for-loops, while-loops, procedures, recursive functions, multiple tasks, simultaneous tasks, complex if-then statements, and combinations of operations. It can also reference other pathways in memory. Data in pathways are also changeable, whereby data can be deleted, added or modified as the robot learns from the environment.

Here is a visual image of what pathways in the robot's brain look like:

Basically pathways in the robot's brain are dendrites in a human brain, they look like branches and trees. These dendrites are constantly changing and modifying itself based on life experiences.

The robot learns information in terms of a bootstrapping process, whereby data is built on top of each other. First the robot has to go to elementary school, then intermediate school, then high school, and finally, college. Every single Artificial Intelligence subject matter, like decision making, planning, natural language processing (NLP), recursive planning, hierarchical planning, generating common sense knowledge, induction/deduction, predicting the future, physical motor skills, speech, language understanding, and so forth will be learned in school. There are no human programmers writing codes in the robot's brain regarding any of the subject matters mentioned above, such as NLP or decision making. This robot learns all of lifes' skill by going to school and interacting with the environment. Things like walking or climbing stairs is learned by teachers. No programmers are needed to write codes to make the robot walk or climb stairs.

As the robot learns information from school, pathways in its brain become more complex and intelligent. It becomes self-awared after a certain point (about age 3) when it begins to make its own decisions based on pain and pleasure. FIG.13 shows a really complex pathway to play a game. This pathway contains linear instructions and decision making in terms of playing "any" game. I will go into the details of this diagram later on.

 

Now, let's look at how the robot's brain works. It senses information from the environment called the current pathway. Next, it finds a similar match to said current pathway in memory. The pathways found in memory are not necessarily based on the robot's 5 senses, but primarily on the robot's thoughts (called activated thoughts). For example, if the robot is thinking of cooking a hamburger, his brain will find pathways to cook hamburger, and not pathways based on what he is currently seeing or sensing from the environment. Next, the robot's brain will predict the future for each intelligent pathway found in memory and rank them. The optimal pathway will be the pathway it will select to take action. These functions repeat itself every second the robot is alive. It allows the robot's brain to correct itself based on the current environment. For example, if the robot is riding a bike and a rock jams the front wheel, the robot will take "split second" action to avoid any physical harm. That's why it has to constantly update itself every second to find the best course of action. The purpose of the robot is to select pathways in memory that will lead to pleasure and avoid pathways in memory that will lead to pain.

So as it senses information from the environment over a short period of time, the robot's conscious is created, which is a computer program that manages tasks and rules. the robot's conscious is the imaginary voice that provides instructions to take action; it can: do human tasks, do multiple simultaneous tasks, solve interruptions of tasks, solve conflicts of tasks, provide knowledge about an object/s, give meaning to language, generate common sense knowledge, solve problems, learn information, answer questions, follow commands given, search memory for information, or take any human action.

 

The human concious (self-awareness)

The medical community has tried to define what a human conscious is for hundreds of years. No psychologist will tell you the meaning to a conscious because they donít know what it is. My theory on the human conscious is based on a rudimentary analysis of human behavior. I basically use myself as the guinea pig to find out what the conscious is. I had to brainstorm and ask myself many questions in order to come up with a conclusion.

"The term, human conscious (n), used on this website means: a human being who is self-awared, alive, and thinking".

The conscious is something that took a lifetime to accumulate. The conscious you have right now started the moment you were born. As you grew older the knowledge you accumulated from all your teachers are stored in memory and ďaveraged outĒ. The conscious for you is the result of the average lessons learned in life. All the teachers you had, all the lessons taught by them are stored in memory (when I say teachers I mean parents, friends, strangers, teachers, tv lectures, etc). For example, if you were crossing the street, the first thing your conscious will tell you is: ďstop, look left, look right, and make sure there are no cars before crossing the streetĒ. This lesson in crossing the street isnít a specific lesson taught to you by one teacher. This lesson is the average lessons taught by numerous teachers. The conscious is a construction of intelligence from a lifetime worth of learning. If you recall all the lessons taught to you about crossing the street, the average of these lessons gives you the knowledge to cross the street.

 

Examples of the robot's conscious (aka activated thoughts)

The three pictures below show different types of robots: a robot driver, a robot soldier, and a robot cook. The robot's conscious is the imaginary voice in his head that: provide information, think, give instructions, recall information, make decisions, solve problems, predict the future, generate future steps to reach a goal and so forth. The robot's conscious is usually represented by internal sentences (sound data) or simple visual data.

PictureA

PictureD

PictureE

Referring to PictureE, every frame of the robot's 5 senses are stored in memory. These pathways store the linear data that the robot goes through to do a certain task. There are certain goals and rules that are automatically done by the robot without given the instructions. For example, the robot knows it has to stay a certain distance from the stove or the current task is to cook spagetti. These tasks are implied in the pathways and doesn't require the robot's conscious to remind the robot all the different rules and goals it needs to do. Only the most important facts/rules are activated by the conscious. The human brain is very primitive and it can only focus on several things at any given moment in time. The pathways guide the robot to do things automatically, while the robot's conscious gives the most important facts/rules during specific times.

 

Details of the robotís conscious

The robot selects intelligent pathways in memory based on the current environment. After a short period of time, these intelligent pathways construct one or more computer programs to take action. These computer programs represents the robotĎs conscious. Also, the robot's conscious is the imaginary voice that provides instructions to take action; it can: do human tasks, do multiple simultaneous tasks, solve interruptions of tasks, solve conflicts of tasks, provide knowledge about an object/s, give meaning to language, generate common sense knowledge, solve problems, learn information, answer questions, follow commands given, search memory for information, or take any human action.

These computer programs in the robotís conscious was created by lessons learned by teachers in school. This method is called unsupervised learning in the real world (for more information about how the robotís conscious works refer to my books).

Within these computer programs are functions and procedures to process information. If we go deeper into the conscious, there are systems that uses information in containers and process them to output intelligence. These containers include: the task container, the rules container, the identity container, the planning container and others (FIG. 6). Furthermore, there is an empty space where work is done, images are extracted from memory, lines are drawn on the image to produce meaningful information, images are manipulated, words are written down, logical sequences are generated, etc (FIG. 5B). The entire computer program inside the conscious was designed so that the robot is able to learn all information from teachers; and no programmers were needed to manually input information into the robot's brain.

Example:

In terms of the 4 containers, if a pathway contains a sentence like: "constantly drive between the 2 white lines", that constant rule will be stored in the rules container. if a pathway contains a sentence (or implied visually) like: "cooking hamburger", that constant task is put in the task container. If a pathway contains a sentence (or implied visually) like: "cook hamburger and talk on the phone simultaneously", that 2 simultaneous task will be stored in the task container. Other sentences in pathways like: "do the tasks on the list in linear order", will instruct the task container on how and when to do certain tasks. Thus, the 4 containers is like an operating system that manages tasks and rules.

 

The robotís conscious applied to a videogame

The task of playing a videogame is a good example of how human robots act intelligently in a dynamic environment. When playing a game, the robot has to use logic and common sense knowledge in order to past the game. Playing a racing game or a RPG game is very difficult and the player has to understand the rules of the game, the objectives of the game, how the controls work according to the game, how to solve problems in the game, how to get the character from one destination to the next, how to come up with plans to beat the game and so forth.

The legend of Zelda is a very good example because the robot has to use human-level intelligence in order to past the game. The Zelda game isnít like a side-scrolling action game, whereby the player accomplishes levels in linear order. In Zelda, the player has to talk to characters in the game and these characters will tell the player what to do next. If the player doesnít follow the instructions from characters, he will get lost and will not past the game. The key to passing the Zelda game is to use human logic to come up with planned strategies and to take action; and through countless trial and error.

The intelligence in the robotís brain comes from a bootstrapping process, whereby new data is built on top of old data. When we play a videogame, we are actually using our knowledge of playing a general game. The lessons of playing sports games in real life, the lessons of playing chase master, the lessons of playing a board game, the lessons of driving a car, the lessons of an occupation actually comes from one universal way of playing a game.

Referring to FIG. 13, pathway B1 is a universal pathway to play any game. The steps in B1 are very general, in that, all games played have these linear steps. If you observe a sports game or a board game, they have these general steps. B2 is a more specific pathway to play a game. In this case, B2 represent playing a videogame. All the intelligent pathways (B1-B3) are all encapsulated and structured in a hierarchical manner so that the data goes from general to specific. Intelligent pathway B3, on the other hand, record detailed steps to play a specific game. If the game is the legend of Zelda, the steps to playing this game are different from the steps to playing a racing game.

In intelligent pathway B2, the player has to set goals in terms of the type of videogame played and based on the playerís goals in the game. Next, in the videogame are various rules and boundaries the player has to follow. Then, the player has to also know what buttons control what actions in the videogame. When playing a videogame, the controller controls the actions of the character on the monitor the robot is seeing. On the other hand, if the robot was playing a real sports game, he has to use his body to take action.

 

Conscious thoughts of the robot (2nd type)

Following the instructions in the optimal pathway is one type of conscious thoughts of the robot. The second type of conscious thoughts is based on activated element objects.

Activated thoughts of the robot works by the following steps:

1. The robot receives 5 sense data from the environment.

2. Objects recognized by the robot are called target objects and element objects are objects in memory that have strong association to the target object.

3. The robot's brain will collect all element objects from all target objects and determine which element objects to activate. Each target object might have multiple copies in memory so each target object will gather element objects from all or most same copies in memory.

4. All element objects will compete with one another to be activated and the strongest element object/s will be activated.

5. These activated element objects will be in the form of words, sentences, images, or instructions to guide the robot's brain to do one of the following: provide meaning to language, solve problems, plan tasks, solve interruption of tasks, predict the future, think, or analyze a situation.

6. The activated element object/s is also known as the robotís conscious.

FIG.2A

                

 

Referring to FIG. 2A, when the robot's brain locates the three visual objects: A, B, C in memory it will run electricity through these nodes and all of its connections.

The mind has a fixed timeline. Only one element object can be activated at a given time in this timeline. This is how we prevent too much information from being processed and allow the robot's brain to focus on the things that it senses from the 5 senses

The robotís pathways (also called the robotĎs experiences) store 5 sense data, activated thoughts, hidden data, and pattern objects. Muscle movements and pain/pleasure is a part of the touch sense and included in the pathways. In addition to the 5 senses, the pathways are also storing linear activated thoughts and other vital data, such as hidden visual data and patterns. Refer to my books for further details.

 

-------------- Other topics ≠----------------

Referencing pathways

English sentences stored in pathways can reference other pathways. The diagram below shows a pathway to reference other individual pathways. In this case, pathway20 is a pathway that does 2 simultaneous tasks (R1 and R2). The sentence: "cook hamburger and play a racing videogame simultaneously" manage 2 tasks simultaneously by switching between tasks until both tasks are completed. Pathway20 is known as a universal pathway because R1 and R2 can be any task. Pathway20 simply references individual task pathways in memory to manage 2 simultaneous tasks. For example, R1 can be cook pizza or R2 can be clean the living room.

In pathway20 there is also another task, which is to temporarily change the rules of the racing game. The instructions include following a temporary rule: red light is green light and green light is red light. The dominant information in memory is green light is go and red light is stop. However, the temp rule allows the robot to temporarily follow the opposite rule. This shows that pathway20 can temporarily change the rules and goals of pathway R2.

Also, English sentences stored in pathways basically define how data is stored, configured, and searched. The robot goes to school to learn knowledge and that knowledge define how data is stored, configured and searched in the robot's brain (refer to my books for details).

 

   

Inventions by Mitchell Kwok (patents filed)


email: amember1234@yahoo.com
 

 

 

Home | HLAI | UAI | Books | Patents | Notes | Donation

Copyright 2006 (All rights reserved)