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.
|
|
|
The Bluebird Project
The objective for Zandi Digital is to make available clever programs to end-users that want and need something more diverse. Bluebird is the current application being developed by Zandi Digital. Bluebird will have the ability to compress multimedia(image, audio, or video) and text into one single file and later opened for reading or editing with Bluebird on Microsoft Windows® operating systems. A illustration is at http://www.videonotepad.netThe ongoing design of the Bluebird file format has given insight and future perspective on what can be achieved with xml. Different approaches to features not purposed during the pre-stage of development have wel...(related: Software)
How To Make Own Cms
Every day millions of new web documents emerge on the Internet, and the amount of web management tools is growing simultaneously. These tools are usually referred to as Content Management Systems, CMS for short. If you have a web site and still do not use any CMS, you will definitely face a choice to buy or to develop an enterprise content management solution in the near future. What would you do if you wanted to develop a CMS, your own software that has a WYSIWYG editor and perfectly meets all your requirements and security standards? Can this task be fulfilled? Which ROI should you expect? You will have to answer all those questions all by yourself. Your chance to success can be increased if you gain an understanding of basi...(related: Software)
Microsoft Crm For Corporate Business ? Working Offline
If your company has regional and worldwide operations, you might already realized that it is very hard to get decent internet connection in your remote locations. In this small article we will try to give you highlights on how to implement Microsoft Business Solutions CRM for worldwide operations with restricted internet connection.? Outlook Client. This was very bright idea from Microsoft side to have outlook client as a presentation for Microsoft CRM data. Outlook has such nice features as synchronization and then working offline. If you have outlook client for CRM ? you can download your customers, leads, contacts, and event properly programmed custom features, then work with them and finally synchronize them back to MS CRM database? MS CRM Integration. As the task itself it is not difficult or challenging ...(related: Software)
The Truth: Netzero 3g
We've all seen the ads on TV for Netzero 3G. You know the ones, "speeds so fast you sworn it was broadband" Well if your using it, you may not think it really is. We're going to break down the truth behind, Netzero 3G.Netzero explains the idea of their service perfectly. It can be found on the 3G website, but is hidden, you have to push the "More Details and Limitations" button at the very bottom. To save you some time here's what it says?"Speed reference based upon comparison to nationally available dial-up ISPs. NetZero HiSpeed 3G accelerate...(related: Software)
Osi Layers Model
IntroductionDuring the early years of our modern computer era, very few standards and protocols existed between various manufacturers. However, as time went on and computer technology continued to improve and become more widespread, it became apparent that standards would be necessary to ensure compatibility. This was especially true with regard to networks, and networking technology. Since the main purpose of a network i...(related: Software)
The Truth About Colossus: Are You Just A Magnetic Image?
What is Colossus?Colossus is software licensed to about twenty-five insurance companies to aid in predicting the settlement value of claims. The insurance industry maintains it is a useful tool because it considers a great many fa...(related: Software)
A Guide To Purchasing Professional Xp Icons Online And Enhancing Your Applications
Icons are used everywhere; right from software applications, to internet browsers, to operating systems to websites and even in print media. But businesses have to waste a good deal of money and time in manufacturing icons on their own. Professional icons are tough to create and need expertise in terms of creative artists, lots of ti...(related: Software)
Where To Find Free Fleet Maintenance Software
Costs of fleet maintenance software can vary widely. It is generally expected that the fleet manager will look at the needs of the company to determine what software package is best suited for their particular needs. Depending upon the size of the company, number of vehicles to be maintained and services of ...(related: Software)
A Symons Mark Ii Function Point Counting Example
I provide, here clear explanations and a count of function points, using the Symons Mark II method.We start by identifying the subprocesses (entry, exit, read, write) for each functional process; The size of a functional process is the sum of its data movements (entry, exit, read, write) and the size of a piece of software is the sum of the sizes of all of its functional processes.So the Function Point Index (FPI) for an application is:FPI = Wi * SNi + We * SNe + Wo * SNo,where ‘S‘ means the sum over all Logical Transactions, and the industry average weights per Input Data Element Type, Data Entity Type Reference and Output DataElement Type are, respectively:Now here is an example of this in practise, intended to demonstrate the practicalities of performing the count, see the Simmons counting point manual (...(related: Software)
site-map - Copyright © 2008 | Contact Webmaster | All Rights Reserved. | Software