Artificial Intelligence And Intuition

The intuitive algorithm.

Roger Penrose considered it impossible. Thinking could never imitate a computer process. He said as much in his book, The Emperor's New Mind. But, a new book, The Intuitive Algorithm, (IA), suggested that intuition was a pattern recognition process. Intuition propelled information through many neural regions like a lightning streak. Data moved from input to output in a reported 20 milliseconds. The mind saw, recognized, interpreted and acted. In the blink of an eye. Myriad processes converted light, sound, touch and smell instantly into your nerve impulses. A dedicated region recognized those impulses as objects and events. The limbic system, another region, interpreted those events to generate emotions. A fourth region responded to those emotions with actions. The mind perceived, identified, evaluated and acted. Intuition got you off the hot stove in a fraction of a second. And it could be using a simple algorithm.

Is instant holistic evaluation impossible?

The system, with over a hundred billion neurons, processed the information from input to output in just half a second. All your knowledge was evaluated. Walter Freeman, the famous neurobiologist, defined this amazing ability. "The cognitive guys think it's just impossible to keep throwing everything you've got into the computation every time. But, that is exactly what the brain does. Consciousness is about bringing your entire history to bear on your next step, your next breath, your next moment." The mind was holistic. It evaluated all its knowledge for the next activity. How could so much information be processed so quickly? Where could such knowledge be stored?

Exponential growth of the search path

Unfortunately, the recognition of subtle patterns posed formidable problems for computers. The difficulty was an exponential growth of the recognition search path. The problems in the diagnosis of diseases was typical. Normally, many shared symptoms were presented by a multitude of diseases. For example, pain, or fever could be indicated for many diseases. Each symptom pointed to several diseases. The problem was to recognize a single pattern among many overlapping patterns. When searching for the target disease, the first selected ailment with the first presented symptom could lack the second symptom. This meant back and forth searches, which expanded exponentially as the database of diseases increased in size. That made the process absurdly long drawn ? theoretically, even years of search, for extensive databases. So, in spite of their incredible speed, rapid pattern recognition on computers could never be imagined.

The Intuitive Algorithm

But, industry strength pattern recognition was feasible. IA introduced an algorithm, which could instantly recognize patterns in extended databases. The relationship of each member of the whole database was coded for each question.

(Is pain a symptom of the disease?)

Disease1Y, Disease2N, Disease3Y, Disease 4Y, Disease5N, Disease6N,
Disease7Y, Disease8N, Disease9N, Disease10N, Disease11Y, Disease12Y,
Disease13N, Disease14U, Disease15Y, Disease16N, Disease17Y, Disease18N,
Disease19N, Disease20N, Disease21N, Disease22Y, Disease23N, Disease24N,
Disease25U, Disease26N, Disease27N, Disease28U, Disease27Y, Disease30N,
Disease31U, Disease32Y, Disease33Y, Disease34U, Disease35N, Disease36U,
Disease37Y, Disease38Y, Disease39U, Disease40Y, Disease41Y, Disease42U,
Disease43N, Disease44U, Disease45Y, Disease46N, Disease47N, Disease48Y

(Y = Yes: N = No: U = Uncertain)

The key was to use elimination to evaluate the database, not selection. Every member of the database was individually coded for elimination in the context of each answer.

(Is pain a symptom of the disease? Answer: YES)

Disease1Y, xxxxxxN, Disease3Y, Disease4Y, xxxxxx5N, xxxxxx6N, Disease7Y,
xxxxxx8N, xxxxxx9N, xxxxxx0N, Disease11Y, Disease12Y, xxxxxx13N,
Disease14U, Disease15Y, xxxxxx16N, Disease17Y, xxxxxx18N, xxxxxx19N,
xxxxxx20N, xxxxxx21N, Disease22Y, xxxxxx23N, xxxxxx24N, Disease25U,
xxxxxx26N, xxxxxx27N, Disease28U, Disease27Y, xxxxxx30N, Disease31U,
Disease32Y, Disease33Y, Disease34U, xxxxxx35N, Disease36U, Disease37Y,
Disease38Y, Disease39U, Disease40Y, Disease41Y, Disease42U, xxxxxx43N,
Disease 44U, Disease45Y, xxxxxx46N, xxxxxx47N, Disease 48Y

(All "N" Diseases eliminated.)

For disease recognition, if an answer indicated a symptom, IA eliminated all diseases devoid of the symptom. Every answer eliminated, narrowing the search to reach diagnosis.

(Is pain a symptom of the disease? Answer: NO)

xxxxxx1Y, Disease2N, xxxxxx3Y, xxxxxx4Y, Disease5N, Disease6N, xxxxxx7Y,
Disease8N, Disease9N, Disease10N, xxxxxx11Y, xxxxx12Y, Disease13N,
Disease14U, xxxxxx15Y, Disease16N, xxxxxx17Y, Disease18N, Disease19N,
Disease20N, Disease21N, xxxxxx22Y, Disease23N, Disease24N, Disease25U,
Disease26N, Disease27N, Disease28U, xxxxxx27Y, Disease30N, Disease31U,
xxxxxx32Y, xxxxxx33Y, Disease34U, Disease35N, Disease36U, xxxxxx37Y,
xxxxxx38Y, Disease39U, xxxxxx40Y, xxxxxx41Y, Disease42U, Disease43N,
Disease 44U, xxxxxx45Y, Disease46N, Disease47N, xxxxxx48Y

(All "Y" Diseases eliminated.)

If the symptom was absent, IA eliminated all diseases which always exhibited the symptom. Diseases, which randomly presented the symptom were retained in both cases. So the process handled uncertainty ? the "Maybe" answer, which normal computer programs could not handle.

(A sequence of questions narrows down to Disease27 - the answer.)

xxxxxx1Y, xxxxxx2N, xxxxxx3Y, xxxxxx4Y, xxxxxx5N, xxxxxx6N, xxxxxx7Y,
xxxxxx8N, xxxxxx9N, xxxxxx10N, xxxxxx11Y, xxxxxx12Y, xxxxxx13N,
xxxxxx14U, xxxxxx15Y, xxxxxx16N, xxxxxx17Y,xxxxxx18N, xxxxxx19N,
xxxxxx20N, xxxxxx21N, xxxxxx22Y, xxxxxx23N, xxxxxx24N, xxxxxx25U,
xxxxxx26N, xxxxxx27N, xxxxxx28U, Disease27Y, xxxxxx30N, xxxxxx31U,
xxxxxx32Y, xxxxxx33Y, xxxxxx34U, xxxxxx35N, xxxxxx36U, xxxxxx37Y,
xxxxxx38Y, xxxxxx39U, xxxxxx40Y, xxxxxx41Y, xxxxxx42U, xxxxxx43N,
xxxxxx44U, xxxxxx45Y, xxxxxx46N, xxxxxx47N, xxxxxx48Y

(If all diseases are eliminated, the disease is unknown.)

Instant pattern recognition

IA was proved in practice. It had powered Expert Systems acting with the speed of a simple recalculation on a spreadsheet, to recognize a disease, identify a case law or diagnose the problems of a complex machine. It was instant, holistic, and logical. If several parallel answers could be presented, as in the multiple parameters of a power plant, recognition was instant. For the mind, where millions of parameters were simultaneously presented, real time pattern recognition was practical. And elimination was the key.

Elimination = Switching off

Elimination was switching off - inhibition. Nerve cells were known to extensively inhibit the activities of other cells to highlight context. With access to millions of sensory inputs, the nervous system instantly inhibited ? eliminated trillions of combinations to zero in on the right pattern. The process stoutly used "No" answers. If a patient did not have pain, thousands of possible diseases could be ignored. If a patient could just walk into the surgery, a doctor could overlook a wide range of illnesses. But, how could this process of elimination be applied to nerve cells? Where could the wealth of knowledge be stored?

Combinatorial coding

The mind received kaleidoscopic combinations of millions of sensations. Of these, smells were reported to be recognized through a combinatorial coding process, where nerve cells recognized combinations. If a nerve cell had dendritic inputs, identified as A, B, C and so on to Z, it could then fire, when it received inputs at ABC, or DEF. It recognized those combinations. The cell could identify ABC and not ABD. It would be inhibited for ABD. This recognition process was recently reported by science for olfactory neurons. In the experiment scientists reported that even slight changes in chemical structure activated different combinations of receptors. Thus, octanol smelled like oranges, but the similar compound octanoic acid smelled like sweat. A Nobel Prize acknowledged that discovery in 2004.

Galactic nerve cell memories

Combinatorial codes were extensively used by nature. The four "letters" in the genetic code ? A, C, G and T ? were used in combinations for the creation of a nearly infinite number of genetic sequences. IA discusses the deeper implications of this coding discovery. Animals could differentiate between millions of smells. Dogs could quickly sniff a few footprints of a person and determine accurately which way the person was walking. The animal's nose could detect the relative odour strength difference between footprints only a few feet apart, to determine the direction of a trail. Smell was identified through remembered combinations. If a nerve cell had just 26 inputs from A to Z, it could receive millions of possible combinations of inputs. The average neuron had thousands of inputs. For IA, millions of nerve cells could give the mind galactic memories for combinations, enabling it to recognize subtle patterns in the environment. Each cell could be a single member of a database, eliminating itself (becoming inhibited) for unrecognized combinations of inputs.

Elimination the key

Elimination was the special key, which evaluated vast combinatorial memories. Medical texts reported that the mind had a hierarchy of intelligences, which performed dedicated tasks. For example, there was an association region, which recognized a pair of scissors using the context of its feel. If you injured this region, you could still feel the scissors with your eyes closed, but you would not recognize it as scissors. You still felt the context, but you would not recognize the object. So, intuition could enable nerve cells in association regions to use perception to recognize objects. Medical research reported many such recognition regions.

Serial processing

A pattern recognition algorithm, intuition enabled the finite intelligences in the minds of living things to respond holistically within the 20 millisecond time span. These intelligences acted serially. The first intelligence converted the kaleidoscopic combinations of sensory perceptions from the environment into nerve impulses. The second intelligence recognized these impulses as objects and events. The third intelligence translated the recognized events into feelings. A fourth translated feelings into intelligent drives. Fear triggered an escape drive. A deer bounded away. A bird took flight. A fish swam off. While the activities of running, flying and swimming differed, they achieved the same objective of escaping. Inherited nerve cell memories powered those drives in context.

The mind ? seamless pattern recognition

Half a second for a 100 billion nerve cells to use context to eliminate irrelevance and deliver motor output. The time between the shadow and the scream. So, from input to output, the mind was a seamless pattern recognition machine, powered by the key secret of intuition ? contextual elimination, from massive acquired and inherited combinatorial memories in nerve cells.

Abraham Thomas is the author of The Intuitive Algorithm, a book, which suggests that intuition is a pattern recognition algorithm. This leads to an understanding of the powerful forces that control your mind. The ebook version is available at http://www.intuition.co.in. The book may be purchased only in India. The website, provides a free movie and a walk through to explain the ideas.

---

Recovering Microsoft Great Plains Customization ? Tips for IT Director

Remember nice and prosperous Clinton era? When you implemented innovative... Read More

Microsoft Great Plains Customization Tools ? Overview

Former Great Plains Software Dynamics/eEnterprise, and currently Microsoft Business Solutions... Read More

Microsoft Great Plains Implementation: Collection Management ? Overview For Consultant

Microsoft Business Solutions Great Plains is very good fit for... Read More

Microsoft Great Plains: Data Conversion & Migration Scenarios ? Overview for Consultant

Microsoft Business Solutions Great Plains serves multiple industries in the... Read More

Microsoft Navision Customization and Reporting ? Tips For Programmer/IT Specialist

C/SIDE (Client/Server Integrated Development Environment) - The core of... Read More

Algebra Help Software

Need help making sense of algebra? Have algebra lectures in... Read More

Crystal Reports for Microsoft Great Plains ? Overview for Developer

Microsoft Great Plains is main accounting / ERP application... Read More

Microsoft Great Plains RW: Report Writer

Microsoft Business Solutions Great Plains is marketed for mid-size companies... Read More

How the Firefox: How to... Manual Helped Me

A few months back I really got sick of my... Read More

Know Linux

Linux essentials:It's free for download but you have to pay... Read More

Free Preventive Maintenance Software

While several preventive maintenance software manufacturers offer free trials for... Read More

How Do I Get Rid Of That Darn Spyware?

Ad-Aware and Spybot are probably the two most well known... Read More

Microsoft C# vs. VB.Net

Hi, Guys,I believe a lot of programmers are trying to... Read More

Great Plains Custom Development: Dexterity, VBA, SQL, Crystal, eConnect ? Overview For Programmer

Microsoft Great Plains is main Microsoft Business Solutions accounting package... Read More

5 Mac Security Tips You Can?t Live Without

So, you've bought a new Macintosh, and now you may... Read More

Microsoft Great Plains Implementation in Russia ? Overview for Consultant

Microsoft Business Solutions Great Plains is very popular ERP platform... Read More

Groupware and Online Collaboration: Collaboration Series #4

This article is the fourth of a series of articles... Read More

Software Development in 2005 - Back to the Future

2005 ? Back to the Future.What does the future hold?... Read More

MicroWorld Releases New Version of MailScan Ver. 4.5 - Antivirus and Content Security Software

MicroWorld Technologies, Inc. the leading solutions provider in the area... Read More

Start Developing Your Own Software

Learning how to program software seems like a daunting task... Read More

Monitoring Software Can be Used for Spying as Well

We all already got used to computer monitoring both at... Read More

Groupware: Answers the 5 Questions of Document Collaboration

Every organization which creates collaborative documents, whether they are budgets,... Read More

Most Common Ways to Accumulate Spyware (where It is Downloaded to Your PC)

It is possible that if one avoided all sources of... Read More

Microsoft Great Plains international implementation ? USA / Mexico ? overview for consultant

Microsoft Business Solutions Great Plains was purchased from Great Plains... Read More

Groupware: Avoid the Ad Hoc Shuffle

GroupwareEfforts are continually made to manage the unavoidable ad hoc... Read More

Assertion in Java

Assertion facility is added in J2SE 1.4. In order to... Read More

10 Steps To Secure And Manage Your Passwords

Passwords protect your most sensitive personal, financial and business information.... Read More

Rapid Application Development - Is it Really a Need of Today?

Rapid Application Development (RAD) is a software development methodology. In... Read More

Microsoft Great Plains: Government & Non-Profit Organization ? Workflow Implementation

Usually workflow & messaging is realized in CRM and then... Read More

Selecting Microsoft Great Plains Partner/VAR/Reseller: ERP Implementation & Customization ? Overview

In the case when you represent mid-size or mid-size-to-large business,... Read More

Microsoft CRM for Large Corporation ? Security

Microsoft Business Solutions CRM proved to be reliable solution in... Read More

Five Reasons for Using an O/R Mapping Tool

So, why should you use any O/R mapping tool? I... Read More

Great Plains Dexterity: Customizations & Source Code Programming

Great Plains Software Dynamics, Dynamics C/S+, eEnterprise were written on... Read More