Way back in 1989, one day, I knew this was Intuition.
Abraham Thomas

KNOW YOURSELF PODCAST Listen each week, to one podcast. Based on practical self improvement principles. From the insight of an engineer, back in 1989, about the data processing structure of the human mind, recognizing, filtering, storing patterns, without stopping.  Patterns of guilt, shame, fear.  How to silence painful subconscious patterns and become self aware.

Watson Jeopardy
Finally, Strong AI!

Is Watson Jeopardy A Software Mutation?
In February 2011, TV viewers around the world watched the computer programs DeepQA and UIMA, irrevocably prove the "Weak AI” camp wrong by demonstrating the viability of “Strong AI.” Computers could ultimately do better than the human mind in any field! The software granted IBM's Watson supercomputer the key enabling quality of the mind – the ability to arrive swiftly at decisions, based on a multifaceted perception of the world. By retaining numerous parallel views of possible solutions in its processing memory, the machine exhibited actual “awareness” of other answers. Displaying the power of this approach to the world community, the machine defeated two human champions in a popular US game show called Jeopardy!

The new skill enabled the machine to beat humans with its swift and sensible answers to ambiguously worded questions about a wide range of subjects. The answers were delivered within seconds after the machine had pored systematically through a million books. With its holistic access to vast knowledge, Watson demolished the “Weak AI” view, most persuasively voiced by the philosopher John Searle, that computers would always be inferior to humans, because they could never truly understand the world.

  • In the popular quiz show Jeopardy!, a reversed question and answer format tests the ability of contestants to spot trivial facts in a huge range of fields.
  • To win the game, IBM used DeepQA & UIMA to recognize data in millions of pages of raw text data.
  • UIMA stored all the data as XML codes and DeepQA algorithms extracted answers in real time.
  • Algorithms identified the types of data, parsed words, used semantic detection, language analysis and stored the the results as cross linked XML codes.
  • By tackling raw text, Watson became a General Problem Solver.
  • By storing and evaluating all the data Wason follows a holistic process, similar to the mind.
  • The process produced and verified the relevance of multiple questions and answers to the Jeopardy! questions.
  • By eliminating the irrelevant, Watson bypassed the combinatorial explosion in standard search processes.
  • With 2880 core processors, Watson presents immense computing power.
  • Searle argued that a computer could never understand.
  • Understanding is an "awareness" of thousands of connected issues. Watson "understands" a problem better than humans.
  • DeepQA/UIMA can be applied in so many areas of human knowledge.
  • The process can understand the deep implications of emotions by sifting through millions of novels.
  • By tackling a more advanced semantic expressions stage of pattern recognition, Watson bypasses a need for sensory inputs.
  • Malicious use of the Watson technology poses new dangers.

This hypothesis is unique in accounting for the striking speed of human intuition; in offering simple new routines to control the mind; in revealing hope for the future of Artificial Intelligence (AI).  Does the mind contain a treasure trove of knowledge?  How does it retrieve solutions to topical problems from such a store?  These proposed explanations have been gathering millions of page views from around the world.  The 1989 beginning of this exciting mission was a revealing insight from a Prolog AI Expert System.  The Expert System could diagnose one out of 8 diseases hinged on the user entering answers to a long string of questions.  In contrast, a doctor could identify a disease out of 8000, without questions, with just a glance.  The ideas in this unconventional hypothesis stem from an "Aha!" moment, when the Expert System revealed a singular algorithm, which could be enabling the mind to identify and act on perceived patterns in milliseconds.

The Prolog Expert System could diagnose 8 diseases, which shared 13 symptoms. It used an algorithm, a step by step procedure, for the diagnosis. Out of curiosity, I began testing an alternate algorithm in a spreadsheet.  Its first step was to SELECT all diseases WITH a particular symptom. Contrary to my plan, the algorithm would DELETE all diseases WITHOUT the symptom. That reverse was caused by a chance double twist in its "if/then" logic.

So, when I clicked "Yes" for one particular symptom to test the first step, the spreadsheet DELETED 7 out of the 8 diseases, leaving behind just one disease.  Surprise!  That disease was indicated by that symptom.  In just one leap, it had proffered the correct diagnosis. As with the doctor, it was a split second verdict!  The algorithm had ELIMINATED all diseases without the symptom.  Was selective elimination from a known list the trick used by nature for its intuitions?

Could elimination provide a faster search strategy?  Since elimination shortened the steps, a programmer coded for me a new, more ambitious Expert System.  Instead of 8 diseases, it dealt with 225 eye diseases.  Its algorithm eliminated both irrelevant diseases and their connected questions, for each answer.  The Expert System was presented to a panel of doctors. "It identified Angular Conjunctivitis, without asking a single stupid question," said a doctor. The Expert System was satisfactorily diagnosing all the eye diseases in the textbook!  The algorithm was an impressive AI tool!  The year 1989 catalogued the premises, set out in these pages, explaining how the algorithm could be enabling the mind of a doctor to achieve split second diagnosis.

Can An Algorithm Be Controlling The Mind?
I am not a physician, but an engineer. Way back in 1989, I catalogued how the ELIMINATION approach of an AI Expert System could reveal a way by which the nervous system could store and retrieve astronomically large memories.  That insight is central to the six unique new premises presented in this website. 

These new premises could explain an enigma.  A physician is aware of thousands of diseases and their related symptoms.  How does he note a symptom and focus on a single disease in less than half a second?  How could he identify Disease X out of 8000 diseases with just a glance?  

First, the total born and learned knowledge available to the doctor could not exist anywhere other than as the stored/retrieved data within the 100 billion neurons in his brain.  The perceptions, sensations, feelings and physical activities of the doctor could only be enabled by the electrical impulses flowing through the axons of those neurons.  The data enabling that process could be stored as digital combinations.

Second, combinatorial decisions of neurons cannot be made by any entity other than the axon hillock, which decides the axonal output of each neuron.  The hillock receives hundreds of inputs from other neurons.  Each hillock makes the pivotal neuronal decision about received inputs within 5 milliseconds.  A
xon hillocks could be storing digital combinations.  It could be adding each new incoming digital combination to its memory store.  The hillock could fire impulses, if it matched a stored combination. If not, it could inhibit further impulses.  Using stored digital data to make decisions about incoming messages could make the axon hillocks intelligent.

Third, combinations are reported to enable a powerful coding mode for axon hillocks.  Olfactory combinatorial data is known (Nobel Prize 2004) to store memories for millions of smells.  Each one of 100 billion axon hillocks have around a 1000 links  to other neurons.  The hillocks can mathematically store more combinations than there are stars in the sky. Each new digital combination could be adding a new relationship link.  In this infinite store, specific axon hillocks could be storing all the symptom = disease (S=D) links known to the doctor as digital combinations.

Fourth, instant communication is possible in the nervous system.  Within five steps, information in one hillock can reach all other relevant neurons.  Just 20 Ms for global awareness.  Within the instant the doctor observes a symptom, 
feedback and feed forward links could inform every S=D link of the presence of the symptom. Only the S=D link of Disease X could be recalling the combination and recognizing the symptom.

Fifth, on not recognizing the symptom, all other S=D hillocks could be instantly inhibiting their impulses. The S=D links of Disease X could be continuing to fire. Those firing S=D link would be recalling past complaints, treatments and signs of Disease X, confirming the diagnosis.  This could be enabling axon hillocks to identify Disease X out of 8000 in milliseconds.

Worldwide interest in this website is acknowledging its rationale. Not metaphysical theories, but processing of digital memories in axon hillocks could be explaining innumerable mysteries of the mind.  Over three decades, this website has been assembling more and more evidence of the manipulation of emotional and physical behaviors by narrowly focused digital pattern recognition.  It has also been receiving over 2 million page views from over 150 countries.

Watson Jeopardy
What Is "Jeopardy!"?

Jeopardy! is a popular American quiz show, in which a reversed question and answer format tests the ability of contestants to instantly spot trivial facts in history, literature, the arts, pop culture, science, sports, geography and wordplay. Clues are presented as answers and the responses of contestants have to be in a question form. Usually there are six selected subjects, with five questions asked in each subject. Each question is an answer, or clue. The player's correct answer has to be a question.

If the category is "geometry," a question may be, "An angle that measures 90 degrees." The right answer could be, "What is a right angle?" The contestants have to ring in to indicate their ability to respond within five seconds after a buzzer confirms that the host has completely finished reading the clue. Ringing in before, loses points. In this historic man vs. machine game, Watson, powered by DeepQA & UIMA, took early lead. From the very beginning, the supercomputer rang in first and produced the correct answers. Its human opponents tried valiantly to catch up, but, in the end, it was a clear win for Watson.

Watson Jeopardy
How Are DeepQA & UIMA Different?

DeepQA & UIMA were different, because they were not mechanically “computing” structured inputs. The programs were drawing their replies from a wealth of accumulated human knowledge. They were recognizing patterns in millions of pages of raw text, retrieved from an assembly of documents from around the world. In the case of Watson, that text included the Wikipedia (14 billion characters), an encyclopedia, a dictionary, a thesaurus, the Bible, a movie database, a geographic database and much more. The machine could ingest this vast library and reply correctly to a query in less than 3 seconds.

DeepQA & UIMA had changed the man vs. machine world. Civilization could now draw sensible answers, culled from the accumulated wisdom of history assembled on the internet. Web crawlers could continually feed the maws of such powerful machines. They opened a new door into the secrets hidden in diverse fields, including science, politics, government, medicine, defense and internal security.

Watson Jeopardy
What Are The DeepQA/UIMA Algorithms?

The programs were imitating the human brain. The nervous system communicates all data as neural combinatorial codes and an intuitive process extracts contextual answers in real time. One region of the brain identifies an object by touching it; another, by defining its visual edges; a third by smelling it. A fourth region assembles such evaluations to instantly identify a person.

UIMA stores all data as XML codes and DeepQA extracts answers in real time. Numerous special purpose algorithms in UIMA evaluated sentences and paragraphs to identify the concepts buried within them in numerous ways. Statistical as well as rule-based analysis of languages classified and summarized documents.

Algorithms allocated legal, biological, or medical data to the related domains, or industry verticals. Algorithms parsed words, used semantic detection and translated documents from other languages. The languages used in the documents, the specific method of their construction and the boundaries of its sentences were identified. They located references to persons, organizations, events, times, concepts and opinions. Numerous views of the same documents were stored as cross linked XML type codes in the memory of the computer.

Watson Jeopardy
Can A Math Program Solve A Biology Problem?

Older computer programs required specialized languages and structures to produce answers in each domain. A maths program could not solve a biology problem. But, UIMA could boast of a world wide view. It could add new algorithms to identify and integrate newer and newer fields. Codes could seamlessly link connected fields, such as persons, organizations, events, times, concepts and opinions, in medicine, biology or law.

The codes also defined the precise locations of various categories of data and the software processes needed to feed in the data, to process it and to access the results. DeepQA & UIMA carried out their main processes, including repeated searches and optimizations on the XML codes and not on the raw text. By identifying the domain of a problem and converting all data to a common set of codes, the software became a General Problem Solver, as dreamed of by the early AI researchers, Allen Newell and Herbert Simon, way back in 1957.

Watson Jeopardy
What Was The UIMA Process?

The neurobiologist Walter Freeman had highlighted an enigma of the mind. “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.” DeepQA & UIMA proved that even a computer could achieve this seeming miracle. Everywhere, they used the total available knowledge for their evaluation. They listed all the possible interpretations of an incoming question. The questions were parsed to get their logical meanings. All the possible meanings of each word, as well as key words and phrases, in the question were listed. They then generated all the possible questions, which could be implied in this question.

DeepQA then searched all the facts in the million books available to it to assemble hundreds of answers, which could reasonably answer the questions. It then rechecked the million books again for evidence supporting these results, generating more links to suitable answers. It added these new links into its memory, learning during the answering process. All answers were then statistically scored for their suitability. Based on the highest score, the machine delivered the answer. DeepQA & UIMA had evaluated every piece of knowledge available to them to reach an answer. The programs had achieved the crucial holistic quality of the mind.

Watson Jeopardy
How Was The Combinatorial Explosion Bypassed?

The mind invariably accessed instant answers, despite its need to search a vast database. Ordinary search processes in computers became hopelessly mired in a combinatorial explosion, when trying to isolate patterns, which could fit many parameters. Typically, an answer, which suited two conditions would not meet a third one. To solve this problem, DeepQA used a statistical evaluation of the thousands of parallel answers stored in its memory. Watson did many iterations of questions and answers and attributed such scores to possible answers. It finally eliminated all answers which scored less than the highest.

The game changing mutation was the statistical evaluation of confidence scores. That process became a powerful new programming competence, which had become the basis of the future applications of this software. It was this evaluation routine, which imitated the intuitive processes of the mind, which also inhibits irrelevant activity in entire regions to focus on the current concern.

Watson Jeopardy
How Was Watson Structured?

Named after IBM founder Thomas J. Watson, the Watson supercomputer is one of the most advanced systems on Earth. It has 2880 core processors and is powered by 10 racks of IBM Power 750 servers and a network-attached storage (NAS) cluster with 21.6TB of data. It can carry out 80 trillion operations per second. Watson used only about 1TB of data to process real-time answers to Jeopardy questions. It can integrate data in 15 terabytes of memory into a single process using Hadoop, a hardware integrating software. Researchers had scanned some 200 million pages of content (about one million books) into the system. The hardware occupied a space equivalent to about 10 refrigerators. Considering the scales at which memories and processing power are increasing, Watson could be sitting in a laptop, or in the head of a lissome robot, in the not too distant future.

Watson Jeopardy
How Was The Turing Difficulty Overcome?

According to Alan Turing, it was not the internal state of either the mind, or the machine, but their outward behavior, which defined intelligence. He offered a famous thought experiment to prove his point. A human judge could exchange messages with one human and one machine, each pretending to be human. If the judge could not tell the difference, then, the machine was intelligent, regardless of its internal processes. But the philosopher John Searle countered that intelligence demanded both outward behavior as well as internal understanding. A computer, merely programmed to output seemingly intelligent messages, did not understand those messages.

Searle offered a second thought experiment, where an English speaking person in a closed room, accepted Chinese messages through a window and followed specific instructions to return the correct Chinese answers. Since the person merely followed the instructions, he understood neither the questions nor the answers. So also, computers, which merely processed inputs without understanding their significance, were not truly intelligent. But, Watson, with its processing access to thousands of relationships of each question and answer, could make a better than human assessment of the implications of what was being communicated. Internal workings were not really important. Watson could understand and process data.

Watson Jeopardy
Can DeepQA/UIMA Diagnose Diseases?

DeepQA with UIMA can peruse millions of medical documents the same way in which it dealt with trivial facts. New algorithms are being developed to categorize medical terms and processes. But the DeepQA/UIMA language of questions and answers will remain the same. Cases from around the world will be evaluated to discover unusual complications in diseases. The program will uncover incompatibility between drugs in the rarest of rare cases, if it comes to light anywhere in the world. Computers will warn of incipient epidemics. They will be able to digest the entire medical history of a patient and search for the best treatments from world wide records. They will point out dangers in particular modes of treatment. By choosing the most important answers, DeepQA will not overwhelm doctors and patients with an excess of data.

Watson Jeopardy
Can DeepQA/UIMA Understand Feelings?

DeepQA/UIMA will one day be able to peruse millions of magazine articles and novels to categorize the nuances of emotions. Emotions are merely patterns of behavior, which enable people to interact in society. They control complex behavior in even exceptional circumstances. A caring action has clear behavioral patterns, whether in the jungle, or in a space ship. Suitable algorithms will identify the gamut of physical and behavioral responses, which accompany anger, sadness, humor or joy. They will be able to predict criminal behavior, crowd behavior, or public responses to policies of government and internal security agencies. The applications of emotions will become a major frontier for DeepQA/UIMA.

Watson Jeopardy
Is Human Access To Sensory Inputs Critical?

Since Watson had access only to the recorded experiences of people, it could be imagined that it would have difficulty in dealing with some subjects. But, Helen Keller, the celebrated author, who was both deaf and blind had no access to either visual or sound information. Yet, she became a celebrated author through the medium of text, which her tutor taught her by “spelling” letters out on her hand. Text based information contains the encapsulated culture and knowledge of the human race. It has incredible detail in definition and content. Global Language Monitor, a company which documents, analyzes and tracks trends in English, reports that, currently one million words are being used in English. Access to an overwhelming variety of meanings and the ability to relate them in thousands of ways can grant DeepQA/UIMA a pattern recognition competence, which can far exceed human skills.

Watson Jeopardy
What Are The Danger Posed By DeepQA/UIMA?

As in every field of technology, this game changing competence brings with it very powerful threats. There are reports that the UIMA resources will become freely available on the internet. Terrorists can query those computers about lethal and commonly available weapons, or about maliciously manipulating people. Policing systems may be able to keep a better track of criminal trends around the world, but new discoveries have an unfortunate way of surprising even the best prepared organizations.

This page was last updated on 02-Jan-2014.



KNOW YOURSELF PODCAST Listen each week, to one podcast. Based on practical self improvement principles. From the insight of an engineer, back in 1989, about the data processing structure of the human mind, recognizing, filtering, storing patterns, without stopping.  Patterns of guilt, shame, fear.  How to silence painful subconscious patterns and become self aware.


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