FRONT COVER





                              Teknowledge




                     Knowledge Engineering Services






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								Teknowledge

Teknowledge is in the Knowledge Engineering business--providing clients
with training and software tools for building Expert Systems. Expert
Systems are Artificial Intelligence computer programs that embody the
specialized knowledge and experience of human experts in scientific,
engineering, or medical applications.  The Teknowledge staff, pioneers
in this emerging technology with experience dating back to the
mid-1960s, formed the company to bring Expert Systems out of the
research laboratory and into the commercial world.

Teknowledge offers three services to facilitate the transfer of
Expert Systems technology to industry:

o Training Programs, ranging from a one-day seminar that introduces
managers to the commercial potential of this new technology to an
extensive 48-week training course aimed at training an in-house
technical staff.

o Software Tools for building Expert Systems, on a sale or lease
arrangement.

o Consultation Services to supplement a companies' in-house capability
and to develop customized systems.




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What is Knowledge Engineering?


Recent public attention to Artificial Intelligence reflects the
fact that tools for symbolic reasoning and problem solving by computer
have progressed beyond the state of experimental laboratory prototypes
to practical systems of considerable commercial potential.  Artificial
Intelligence research groups, once confined to a handful of universities
and large research institutions, now exist in a wide spectrum of
industrial and government settings.

Expert Systems -- computer programs that embody the specialized
knowledge and experience of a human expert -- are the first major
commercial application of Artificial Intelligence.  Since research on
Expert Systems began in the mid-1960s, programs have been produced which
provide expert-level performance in many technical areas, such as
isolating and correcting malfunctions in computer equipment, monitoring
patients in intensive care facilities, analyzing sonar reflections, and
selecting drug therapies.


Expert Systems provide essential services in settings where competent
human experts are either scarce, unable to react as quickly as required,
or are not cost-effective.  With the increasing sophistication of Expert
Systems and decreasing cost of hardware, an explosion in their
availability and practicality for a wide variety of applications is
expected in the coming decade.

The process of designing and implementing Expert Systems is known as
Knowledge Engineering. The unique nature of Knowledge Engineering
requires specialized judgement and management skills beyond those
normally associated with software development projects: The ability to
recognize and evaluate potential applications; select appropriate
knowledge representations and problem solving models; build and test a
knowledge base; etc. Teknowledge provides the tools and services
required for a company to develop an in-house Knowledge Engineering
capability. 



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			                    The Teknowledge Training Program


	Knowledge Engineering requires a substantial commitment of human
and material resources.  Teknowledge provides a comprehensive program of
seminars and tutorials ranging from one-day introductory seminars
designed for technical managers, to a 48-week course for those
interested in acquiring in-depth training in Knowledge Engineering.  

	The curriculum is designed to train the following members of a
typical Knowledge Engineering team:

	Technical Manager: organizes and manages Knowledge Engineering
			projects.

	Knowledge Engineer (Project Leader): initiates, designs, and
			implements Knowledge Engineering projects.

	Application Engineer (Software Engineer): implements Expert
			systems under the direction of the Knowledge
			Engineer.


	Teknowledge offers a confidential consulting service to help
firms identify suitable personnel and select appropriate training
programs.


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The Tutorials


	Teknowledge is now accepting participants for its training
programs scheduled to begin in March and September, 1982.

Tutorial I:  Fundamentals of Knowledge Engineering		(1 week)

	The purpose of this tutorial is to acquaint the participants
with the fundamentals of Knowledge Engineering.  It presents the basic
techniques and contrasts this approach with more conventional
programming methods.  The objective of this course is to provide
participants with sufficient information to identify potential
applications of Knowledge Engineering in his field and to decide whether
further training and investment is desirable.  The course is aimed at
technical managers and requires some experience with data processing.
Tutorial I will be offered more frequently as a stand-alone program and
is available as an in-house course for those companies interested in
on-site training.



Tutorial II: Fundamentals of Artificial Intelligence		(4 weeks)

	This four-week intensive course, which includes Tutorial I, is
intended to give participants a working understanding of the fundamental
ideas and techniques of Artificial Intelligence.  Topics include
knowledge representation, automated reasoning, search, and planning.  A
thorough familiarity with these ideas is essential to Knowledge
Engineering and to the understanding of existing software tools.


Tutorial III:  Knowledge Engineering for Software Engineers	(24 weeks)

	This course is designed to provide participants with experience
in Knowledge Engineering.  In addition to learning the basic ideas and
techniques of Artificial Intelligence, the course provides training in
the use of software packages and hands-on experience with existing
programs.  It is designed for software engineers and provides them with
the skills and knowledge necessary to implement Knowledge Engineering
projects.


Tutorial IV:  The Art and Practice of Knowledge Engineering	(48 weeks)

	The purpose of this course is to provide participants with the
skills and experience necessary to design and implement substantial
Knowledge Engineering projects.  In addition to the training provided in
Tutorial III, it provides participants with broader and deeper
understanding of the ideas and techniques of Knowledge Engineering.
While in residence at Teknowledge, participants are expected to design
and implement an Expert System of relevance to their sponsoring
organizations.  Participants are expected to have a solid understanding
of at least one potential application area.



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One-Day Seminars


	In addition to the extensive program of tutorials, Teknowledge
offers a series of one-day introductory seminars.


Executive Briefing:  Knowledge Engineering In the 1980's

	The Executive Briefing provides executives and senior technical
personnel with an introduction to the concepts of Knowledge Engineering
and Expert Systems.  The seminar assesses the power of Knowledge
Engineering and pinpoints areas of particularly high impact.  It
outlines costs and strategies for initiating Knowledge Engineering
efforts.


Medical Seminar I:  Introduction to Clinical Decision Making


	The aim of this one day seminar is to introduce physicians and
other interested participants to the computational approaches used to
assist with clinical decision making.  Bayesian statistics, decision
theory, reasoning from data bases, and Artificial Intelligence
techniques are assessed for areas of successful application.  The course
is an introduction to the state of the art in computer-based clinical
decision making and is intended to supply the background necessary for
further detailed study of medical consultation systems.  Particular
attention is paid to program features that are likely to heighten the
acceptability of such systems to the physicians for whom they are
designed.  The course assumes no background in computer programming or
data processing.


Medical Seminar II:  Artificial Intelligence Applications to Medicine

	This seminar, designed as a follow-up to "Introduction to
Clinical Decision Making", introduces participants to the techniques and
methods of Knowledge Engineering that are relevant to the medical
community.  It covers design issues in the area of intelligent human
interface, explanation, knowledge acquisition and representation, and
performance.  The seminar is aimed at an audience already familiar with
some medical computation methods.  Emphasis will be on case studies of
currently existing Expert Systems, design considerations, psychological
issues, available software packages, and technical problems.


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			                     Expert System Software Tools


	Teknowledge is developing several software packages to support
the construction of Expert Systems.  The first of these to become
available is the ES series, based on EMYCIN, the pioneering tool for
Knowledge Engineering developed at Stanford University.  These tools are
uniquely suited to the development of Expert Systems and reflect many
years experience gained in applying Knowledge Engineering techniques.

ES-100 will allow users to run consultations (with explanations)
using a knowledge base developed with ES-200 or ES-300.

ES-200 will allow users to develop Expert Systems using a production
rule representation.

ES-300 is an advanced tool for experimenting with Knowledge Engineering.
It provides facilities for augmenting ES-200 programs with user-defined
special purpose functions and programs.


	The Teknowledge system-development software (including
documentation and maintenance) is available through individual sales
and leasing arrangements.

Teknowledge Technical Staff

Edward A. Feigenbaum, PhD (Chairman of the Board) -
Chairman of the Computer Science Department of Stanford University, and
president of the American Association for Artificial Intelligence;
founder of the Heuristic Programming Project.

Bruce G. Buchanan, PhD (Principal Scientific Advisor) - Co-principal
investigator of the Heuristic Programming Project at Stanford
University; developer of DENDRAL, an Expert System for elucidation of
chemical structures.





Avron Barr, MS - Editor of the three-volume Handbook of Artificial
Intelligence; research experience in Artificial Intelligence
applications to computer-based instruction.

James S. Bennett, MS - Developer of several Expert Systems in the such
areas as medicine, structural analysis, and computer fault diagnosis.

Harold D. Brown, PhD - Specialist in intelligent aids for integrated circuit
design;  expert in applied combinatorics and graph theory.

William J. Clancey, PhD - Specialist in explanation and knowledge
representation for Intelligent Tutoring Systems; co-developer of MYCIN's
antibiotic therapy and explanation programs; designer of GUIDON, a
domain-independent program for rule-based tutorials.


Randall Davis, PhD - Professor of Computer Science at MIT;
specialist in knowledge acquisition and control strategies for Expert
Systems.

Robert S. Engelmore, PhD - Specialist in applications of Artificial
Intelligence techniques to problems in the physical sciences; former
Program Manager of Intelligent Systems research at the Defense Advanced
Research Projects Agency.

Peter E. Friedland, PhD - Developer of MOLGEN, an Expert System for
planning Genetic Engineering experiments; founder of Intelligenetics, a
company which serves the symbolic computing needs of the biotechnology
industry.


Michael R. Generereth, PhD - Professor of Computer Science at Stanford
University; specialist in knowledge representation and planning;
developer of Expert Systems in computer aided design and computer fault
diagnosis.

Frederick Hayes-Roth, PhD - Founding Director of the Rand Corporation's
Information Processing Systems program; a principal designer of
Hearsay-II, the first 1000-word continuous speech understanding system;
specialist in management and planning applications of Artificial
Intelligence. 

S. Jerrold Kaplan, PhD - Specialist in Natural Language access to
computer systems; cooperative user interfaces; database theory and
practice.

Ingeborg M. Kuhn, MBA, PhD - Management scientist specializing in
technology transfer, health economics and planning; experience in
planning and evaluation of national programs supporting bio-technological
research resources and health care technology.

Douglas B. Lenat, PhD - Professor of Computer Science at Stanford
University; 1977 Computers and Thought Award recipient; specialist in
automated discovery systems.

H. Penny Nii, MS - Project manager and designer of HASP, a signal
interpretation program, and AGE, a domain independent Knowledge
Engineering tool; specialist in signal/data interpretation and complex
information integration.

Thomas C. Rindfleisch, MS - Director of the SUMEX computing facility, a
national biotechnology computing resource; expert in problems of large
computer systems.

A. Carlisle Scott, MS - Primary software development coordinator and
designer for the MYCIN projects; expert in rule-based systems.

Edward H. Shortliffe, MD, PhD - Recipient of the Grace Murray Hopper
Award from the ACM; developer of MYCIN and expert on applications of
Artificial Intelligence to Medicine; clinician and Professor of Medicine
at Stanford University School of Medicine.

William van Melle, PhD  - Systems and software expert for Artificial
Intelligence applications; principal designer and implementor of
EMYCIN.

William C. White, MS - Software engineering consultant for large LISP-based
systems.



For more information please send the attached reply card to:

		Teknowledge
		Suite 401
		151 University Avenue
		Palo Alto, Ca. 94301

or call (415) 326-6827.

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A Glossary of Common Terms


Artificial Intelligence - The sub-field of Computer Science that is
concerned with symbolic reasoning and problem solving.

Knowledge Engineering - The process of achieving expert-level
performance from programs by bringing together a large body of knowledge
about a specific application area.

Expert Systems - Computer programs that embody the specialized knowledge
and experience of a human expert; the results of Knowledge Engineering.

Knowledge Representation - A formalism for representing in a
data-structure facts and heuristics about a subject or specialty.

Knowledge Base - A database of information encoded in a knowledge
representation for a particular application.

Inference Technique - A methodology for reasoning about information in a
knowledge representation and drawing conclusions from that knowledge.

Task Domain - An application area for an Expert System, such as analysis
of pulmonary function disorders, identification of computer system
failures, etc.

Heuristics - The informal, judgmental knowledge of an application area
that constitutes the "rules of good judgment" and the "art of good
guessing" in the field. Heuristics also encompass the knowledge of how
to solve problems efficiently and effectively, how to plan steps in
solving a complex problem, how to improve performance, etc.

Production Rules - A widely-used knowledge representation in which
knowledge is formalized into "rules" containing an "IF" part and a
"THEN" part (also called a condition and an action).  The knowledge
represented by the production rule is applicable to a line of reasoning
if the IF part of the rule is satisfied; consequently, the THEN part can
be concluded or its problem-solving action taken.


---------------------- [Response Card]


Name:	------------------------------
Title:  ---------------------------------
Organization:------------------------------

Address:------------------------------
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Telephone: ---------------------------


Please send information on:

	------  One-day Executive Briefing
	------  Medical Seminars
	------	Teknowledge Training Program
	------	In-house Training
	------	Teknowledge Software Packages
	------	Teknowledge Consultation Services