User talk:ZENDELBACH

Abstract of the Disclosure. The invention's name is CAMBO an acronym for Computer Aided Management By Objective. The title is a "multi-EXPERT System Generator", and the vision an “artificial intelligent bridge” between technology and the ability to automate the instruments of the MBO methodology, namely: Charters, Organization Charts, Operational Plans, Project Management, Performance Planning and others all containing the knowledge, expressed in 'English Grammatical Sentences', upon which an enterprise conducts business. It would require the design of a unique combination of advanced methodology and technology capabilities built upon and work in concert with current state of the art, 'Data Normalized', Relational Data Base structure. The “AI Bridge” would include an advanced methodology for Normalizing Knowledge, a unique definition for a unit or element of knowledge, an advanced structure for a Spatial Relational Knowledge Base and a 5th generation programming language to support a Natural Language Processing interface. A successful CAMBO installation video is available Video: http://www.youtube.com/watch?v=Z53OiHFCpAg

Knowledge Normalization.

The following pages contain excerpts from Wikipedia, the free encyclopedia. The excerpts represent the most widely accepted methodology for the normalization of Data Elements. Those readers unfamiliar with the discipline of normalizing data elements are advised to review the methodology described. However, keep in mind that while this methodology for data normalization will remain as a standard for developing a relational data base, the processes described will be integrated with the processes for knowledge normalization. Data element: definitions, profiles, format, relationships, where-used and ontological associations are all derived from the processes of knowledge normalization. The status or condition of an individual data element is the result of a program executing a series of knowledge elements. Knowledge elements contain the logic by which data elements are manipulated.

The CAMBO methodology for knowledge normalization expresses a knowledge element as an “English Grammatical Sentence”. CAMBO codifies business and engineering knowledge into its most basic form, the English Grammatical Sentence (EGS). Each EGS is grouped into rule-sets that become part of a knowledge domain and because the knowledge normalization process will establish cross domain relationships, the knowledge of many disciplines are united in answering questions. The procedure for asking questions is a simple intuitive and interactive menu (Web Site) system that leads the user through a 'Question and Answer' review of the cross discipline issues leading to a final answer. It is as though you were asking questions of many engineers or business managers, in different disciplines, to contribute their knowledge towards identifying and answering issues about a specific business or engineering requirement.

The real breakthrough is communicating in "English grammatical sentences," thereby allowing the machine to level the playing field of human interaction.

EXAMPLE ONE. In a video tape presentation of this work at Industrial Design Corp.(IDC), Tempe, AZ, (a 300mil engineering division of a 2bil parent engineering firm in Portland), the IDC Knowledge Engineers (trained on the product CAMBO, a Multi-EXPERT system generator) demonstrate their Multi-EXPERT system, called ROSE. A system that allows senior engineers to teach the computer the rules and judgment used to make engineering decisions; that can then be used by less experienced engineers to arrive at senior level decisions. IDC engineers produce blueprints for the "building" construction and production line equipment assembly of a semiconductor wafer fab facility. The rules and judgment used to make engineering decisions are codified into English Grammatical Sentences (EGS, a natural language structure), related into iambic pentameter, (verse form) paragraphs that allow the user to interact with the system in conversational English (note. the EGS code structure includes: ontology relationships as well as process management and control functions).

The TURING  TEST

CONSIDER THAT a Multi-EXPERT System (CAMBO, a Multi-EXPERT System generator), that interactively communicates with a user, in English Grammatical Sentences (in iambic pentameter, verse form, conversational English), ABOUT A SPECIFIC DOMAIN OF KNOWLEDGE, SATISFIES THE FRAMEWORK FOR THE TURING TEST REQUIREMENT: …“that a human may interact with an intuitive computer system, in conversational English, limited only by the domains of knowledge contained in the computer.”

To take this framework to the next level of human to machine interaction, is imbedded in CAMBO’s architecture, in which rules manage rules in a rules processing schema allow for colloquial grammatical sentence enhancements. This process has several levels of control based upon the user’s selection of an interactive session profile. The user’s session profile will direct the Multi-EXPERT system to respond in different attitudes of questions and answers. This enhancement draws closer to satisfying the Turing Test, but is still limited by the knowledge domains taught to the Multi-EXPERT system. NJZ

The TURING  TEST

"........The Turing Test was introduced by Alan M. Turing (1912-1954) as "the imitation game" in his 1950 article (now available online) Computing Machinery and Intelligence (Mind, Vol. 59, No. 236, pp. 433-460) which he so boldly began by the following sentence:

I propose to consider the question "Can machines think?" This should begin with definitions of the meaning of the terms "machine" and "think."

Turing Test is meant to determine if a computer program has intelligence. Quoting Turing, the original imitation game can be described as follows:

The new form of the problem can be described in terms of a game which we call the "imitation game." It is played with three people, a man (A), a woman (B), and an interrogator (C) who may be of either sex. The interrogator stays in a room apart from the other two. The object of the game for the interrogator is to determine which of the other two is the m an and which is the woman. He knows them by labels X and Y, and at the end of the game he says either "X is A and Y is B" or "X is B and Y is A." The interrogator is allowed to put questions to A and B.

When talking about the Turing Test today what is generally understood is the following: The interrogator is connected to one person and one machine via a terminal, therefore can't see her counterparts. Her task is to find out which of the two candidates is the machine, and which is the human only by asking them questions. If the machine can "fool" the interrogator, it is intelligent. This test has been subject to different kinds of criticism and has been at the heart of many discussions in AI, philosophy and cognitive science for the past 50 years.

The CAMBO  TEST.

The CAMBO test is a theorem that postulates the increase in the multi-EXPERT system to emulate the exchange of knowledge with an SME (Subject Matter Expert), as though the multi-EXPERT system were the SME, relative to the accumulation of the SME knowledge and colloquial grammatical sentence enhancements.

The Process of Knowledge Normalization.

The CAMBO knowledge engineering: Methodology, Techniques and Tools are used to produce knowledge engineering models (KEM) to populate a story board layout for the design of a Multi-EXPERT system. Each knowledge engineering model (KEM) is a view of a particular life cycle of activity that has been modeled to example the functionality of a knowledge engine that drives the events contained in the life cycle. It is the function of these models to: identify, capture, profile and relate the language of the enterprise for which the Multi-EXPERT system will support.

CAMBO codifies business and engineering knowledge into its most basic form, the English Grammatical Sentence (EGS). Each EGS is grouped into rule-sets that become part of a knowledge domain and because the knowledge normalization process will establish cross domain relationships, the knowledge of many disciplines are united in answering questions.

As a computer programming tool, I would best describe this new technology as a, 'learning and teaching tool' for business and engineering knowledge.

1. The Company will never lose the 'learned knowledge' of all its managers and engineers, and through attrition will increase manpower capability without increasing staff.

2. The Company management team will have access to real world, real time process and procedural management controls. This includes the following business disciplines: ERP all modules; Charters, Process, Procedures and job description reengineering controls; Project Management controls and IT Application and Systems controls.

3. The Company’s business operation and engineering knowledge is saved, protected and made available to all authorized employees.

4. Junior engineers can ask CAMBO business operations and engineering questions, as though they were speaking with a senior manager or engineer, to make senior level decisions.

5. Senior managers and engineers can teach CAMBO the knowledge they use to make business and engineering decisions.

Computer technicians versus Computer technologists.

Computer technicians are folks that belong to a team that supports a computer system. Computer technologists are computer technicians that want to look beyond today's technology to understand what is next?

I've been designing new technology (AI) for forty years and been blessed and very lucky to be successful in the development of a piece of the science called artificial intelligence. My success has been in the discipline of knowledge normalization, the same concept as data normalization, but with a different methodology. Historically we rely on methodologies like: canonical synthesis, entity relationship, etc. to normalize data elements into relationships, which can be projected onto a data base. Knowledge normalization performs the same function to normalize knowledge elements as the methodologies that normalize data elements.

What this means to you is that perhaps something like knowledge engineering could improve the technology tools you provide to your management team. It's at least worth a look to see what new technology can do!

Let's see if you can make a mental model of a computer system that allows source experts (employees with an understanding how to perform a business activity) to teach the computer the: What, How, When, Who, Where and any ontological relationships of a particular business activity. And that same computer system can answer any question about any business activity it has been taught, as though the original source experts were inside the computer.

Now extend that mental model to include the definition of a knowledge element as an "English grammatical sentence". Now compare a data element to a knowledge element to see the difference between normalizing the relationships between a street address versus an English grammatical sentence.

Now perhaps your mental model has allowed you to see the relationship between normalizing data elements and normalizing knowledge elements. And that a Knowledge Base contains knowledge elements (a single knowledge element is an English grammatical sentence) that are related through a methodology different from those that normalize data elements.

This difference allows the computer to have a conversation with the user in conversational English. That's right! Iambic pentameter, verse form... paragraphs made up of English grammatical sentences that have been grouped together to respond to the user's questions and their answers.

Nicholas Zendelbach President International Cognitive Computing Scottsdale, Arizona Lab: 480-948-9240 email: cambo9@aol.com web:   cambo1.com