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Thinknowlogy
A fundamental approach to Artificial Intelligence / knowledge technology
A webinar initiated by Compegence
December 15, 2012
© 2012 Menno Mafait http://mafait.org
Thinknowlogy - A fundamental approach to Artificial Intelligence / knowledge technology
A fundamental approach 3
Demo 4
Questions 5
Introduction 1
The current approach to AI 2
Thinknowlogy - A fundamental approach to Artificial Intelligence / knowledge technology
Short CV
• Name: Menno Mafait
• Education: Computer science (undergraduate level)
specialization: telecommunications;
• Experience: Software Tester with several companies,
currently developing Thinknowlogy.
Introduction 1
Thinknowlogy - A fundamental approach to Artificial Intelligence / knowledge technology
Some rules during this session
• Questions can be posed during this session in the
chatbox of TeamViewer. I will have a look now and then,
and try to answer your question before switching topics;
• Only if your question is important to your understanding,
enable your microphone in the TeamViewer window and
interrupt me with your question;
• Please try to describe your question briefly.
Introduction 1
Thinknowlogy - A fundamental approach to Artificial Intelligence / knowledge technology
The relation between Artificial Intelligence (AI) and
knowledge technology
Semantics / meaning is a subset of intelligence.
• Artificial Intelligence is (or should be) based on
intelligence;
• Knowledge technology is (or should be) based on
Semantics / meaning.
So, knowledge technology is a subset of AI.
Introduction 1
Thinknowlogy - A fundamental approach to Artificial Intelligence / knowledge technology
A fundamental approach 3
Demo 4
Questions 5
Introduction 1
The current approach to AI 2
Thinknowlogy - A fundamental approach to Artificial Intelligence / knowledge technology
A few questions:
• Why is Siri considered stupid by some users?
• Why do search engines still show lists with links -
rather than just answer the question of the user?
• Why does Watson need 2800 CPU cores “to find
a needle in the haystack of unstructured texts”?
Why doesn't it just structure those texts while the
knowledge is acquired? Wouldn't that use significantly
less CPU power during the search?
The current approach to AI 2
Thinknowlogy - A fundamental approach to Artificial Intelligence / knowledge technology
What is Siri?
Siri is an iPhone app that allows the user to speak to
their iPhone. Siri will then respond with text on the screen
as well as a voice. Siri is able to read, write and send text
messages (emails, tweets, etc.) on the user's command,
to read and organize the user's agenda, to answer some
questions like about the weather forecast, and to find
shops and restaurants in the neighborhood.
The current approach to AI 2
Thinknowlogy - A fundamental approach to Artificial Intelligence / knowledge technology
But why is Siri considered stupid by some users?
Siri is a clever combination of speech technology, GPS,
search engines and pre-programmed responses. It gives
the user a feeling that the system is quite human.
However, the combination of technologies is intelligent,
not the app itself. For example, Siri will probably respond
to the sentence “The Chinese is near the restaurant” by
providing the location of the nearest Chinese restaurant
rather than processing this knowledge.
The current approach to AI 2
Thinknowlogy - A fundamental approach to Artificial Intelligence / knowledge technology
Why do search engines still show lists with links -
rather than just answer the question of the user?
Because current technologies filter down the sentences
to mainly keywords and discard the “useless” words,
by which most of the meaning is lost irrecoverably.
So, despite all effort done to develop the Semantic Web,
current knowledge technologies are still unable to
understand the human language.
The next best thing: Let the user be the intelligent factor,
guided by current semantic technologies.
The current approach to AI 2
Thinknowlogy - A fundamental approach to Artificial Intelligence / knowledge technology
What is Watson?
Watson is a supercomputer system developed by IBM
to support professionals by finding a keyword from a
description, e.g. by providing a list of possible deceases
from a description of symptoms. In fact, Watson is a
reversed Wikipedia.
To prove the power of Watson, IBM initiated a Jeopardy
competition between human competitors and Watson.
The current approach to AI 2
Thinknowlogy - A fundamental approach to Artificial Intelligence / knowledge technology
What is Watson?
Jeopardy is a quiz show in which a cryptic description
must be answered by a keyword, in the form of:
“What is {noun}?” or “Who is {proper noun}?”.
So, Watson isn't able to answer in sentences, only to
find keywords.
The current approach to AI 2
Thinknowlogy - A fundamental approach to Artificial Intelligence / knowledge technology
• But why did Watson need 2800 CPU cores to find
“a needle in the haystack of unstructured texts”
(quote from IBM) in order to beat human competitors?
• Why didn't IBM just structure the knowledge base
of Watson before playing Jeopardy? Wouldn't that
speed-up the search itself, using significantly less
CPU power during the game?
Because science (and IBM) fails to develop techniques
to structure or organize knowledge autonomously.
The current approach to AI 2
Thinknowlogy - A fundamental approach to Artificial Intelligence / knowledge technology
More into depth:
Search engines, chatbots (including Siri) and other
natural language systems degrade the sentences to
interlinked keywords and throw away the rest of the
words, by which a lot of the meaning is discarded
irrecoverably. Therefore, such systems are only
able to find texts containing given keywords.
Besides that, current AI systems are only able to act
intelligently on pre-programmed situations – and
therefore – chatbots fail to keep focus.
The current approach to AI 2
Thinknowlogy - A fundamental approach to Artificial Intelligence / knowledge technology
But what about Artificial Neural Networks (ANN)?
Using a metaphor to describe an ANN: a building.
Neurons are not more then bricks, and an ANN isn't
more than a pile of interconnected bricks,
which is no building.
An architect is required to design a building. However,
nobody knows how to design a high-level architecture
for an ANN.
The current approach to AI 2
Thinknowlogy - A fundamental approach to Artificial Intelligence / knowledge technology
But what about Artificial Neural Networks (ANN)?
And therefore, an ANN:
• is limited to execute one task – and one task only;
• will always be a slave, and will never become a master;
• will never show intelligent behavior, because intelligence
should be gained autonomously, and nobody knows how
to design an ANN architecture that gains its intelligence
autonomously.
The current approach to AI 2
Thinknowlogy - A fundamental approach to Artificial Intelligence / knowledge technology
And what about the Semantic Web?
The Semantic Web is assumed to add meaning to
the Web, by which knowledge technology is assumed
to understand the human language.
The Semantic Web is a commercial success,
but it still fails to understand the user,
because scientists don't know what semantics is.
The current approach to AI 2
Thinknowlogy - A fundamental approach to Artificial Intelligence / knowledge technology
What is implemented then by AI and knowledge
technology experts?
• Nice – but baseless – techniques.
AI is only:
– “inspired by nature”;
– fooling the customer;
– marketing;
– earning big bucks.
The current approach to AI 2
Thinknowlogy - A fundamental approach to Artificial Intelligence / knowledge technology
So, what went wrong?
AI has a fundamental problem:
• AI scientists started to develop techniques
without defining and developing a foundation first.
So, in fact, the field of AI / knowledge technology
is baseless (has no foundation) and isn't scientific.
The current approach to AI 2
Thinknowlogy - A fundamental approach to Artificial Intelligence / knowledge technology
Can you prove that AI is not fundamental?
Of course.
Characteristics of a mature science:
• A mature science is defined unambiguously;
• A mature science is based on a natural foundation;
• A mature science integrates all its disciplines.
The current approach to AI 2
Thinknowlogy - A fundamental approach to Artificial Intelligence / knowledge technology
A mature science is defined unambiguously
Using the metaphor of a building again:
– Before an architect starts to draw,
the client's requirements must be specified clearly.
• However, science started to build Artificial Intelligence
without defining of intelligence first;
• And science started to build knowledge technology
without defining Semantics / meaning first.
So, on what is AI / knowledge technology based then?
The current approach to AI 2
Thinknowlogy - A fundamental approach to Artificial Intelligence / knowledge technology
A mature science is defined unambiguously
Why does science fail to define intelligence and
semantics?
• According to science, intelligence should have been
emerged “by itself”, like by complexity and chaos;
• And natural language should have been evolved
from the primal sounds of cave men.
However, bright people like Leonardo da Vinci and
Albert Einstein taught us the exact opposite:
Intelligence is in simplicity and structure.
The current approach to AI 2
Thinknowlogy - A fundamental approach to Artificial Intelligence / knowledge technology
A mature science is defined unambiguously
Why does science fail to define intelligence and
semantics?
• So, what if the evolution theory is nonsense?
• What if intelligence and natural language aren't the
chaotic result of evolution, but the organized result
of an intelligent design by God?
The current approach to AI 2
Thinknowlogy - A fundamental approach to Artificial Intelligence / knowledge technology
A mature science is based on a natural foundation
For example, the science of electricity is based on
the natural phenomenon of a flow of electrically
charged particles.
However,
• the current approach to AI doesn't define a natural
source of intelligence. So, AI has no natural foundation;
• and knowledge technology fails to understand the
meaning of the user, because it isn't based on a natural
source of Semantics.
The current approach to AI 2
Thinknowlogy - A fundamental approach to Artificial Intelligence / knowledge technology
A mature science integrates all its disciplines
For example: The basic rules of electricity apply from
micro-electronics to high-voltage systems.
However, the disciplines of AI / knowledge technology
are separate “islands”. For example:
Ontology (automated reasoning) is based on formal
(=cryptic) language and Natural Language Processing
(NLP) is based on natural language. So, Ontology and
NLP have no common foundation, and therefore they
are incompatible.
The current approach to AI 2
Thinknowlogy - A fundamental approach to Artificial Intelligence / knowledge technology
Summary:
• AI is not defined unambiguously;
• AI has no natural foundation;
• AI doesn't integrates all its disciplines.
Conclusion:
The current approach to AI and knowledge technology
is not fundamental, and therefore not scientific.
The current approach to AI 2
Thinknowlogy - A fundamental approach to Artificial Intelligence / knowledge technology
From a positive point of view:
The field of AI and knowledge technology is still
completely open, and provides an unprecedented
opportunity for those who will succeed to develop a
scientific foundation for AI and knowledge technology.
The current approach to AI 2
Thinknowlogy - A fundamental approach to Artificial Intelligence / knowledge technology
• But what is the definition of intelligence and semantics?
• How can a fundamental base then be developed for
AI and knowledge technology?
• And how can intelligence and semantics be
implemented on a natural foundation?
The current approach to AI 2
Thinknowlogy - A fundamental approach to Artificial Intelligence / knowledge technology
Any questions so far?
The current approach to AI 2
Thinknowlogy - A fundamental approach to Artificial Intelligence / knowledge technology
A fundamental approach 3
Demo 4
Questions 5
Introduction 1
The current approach to AI 2
Thinknowlogy - A fundamental approach to Artificial Intelligence / knowledge technology
Using a metaphor: the dream to fly like a bird.
The dream of flight had:
• an experimental phase;
• and a fundamental phase.
A fundamental approach 3
Thinknowlogy - A fundamental approach to Artificial Intelligence / knowledge technology
The experimental approach to the dream of flight
For a many centuries, people tried to fly like a bird.
“Inspired by nature”, a few covered themselves with
feathers or strapped a wing construction to their arms
in the hope they could fly. But they failed, because
feathers and flapping wings aren't essential for flight.
Proof: Airplanes can fly, but they no feathers, nor
flapping wings.
Also the current approach to AI is “inspired by nature”.
A fundamental approach 3
Thinknowlogy - A fundamental approach to Artificial Intelligence / knowledge technology
The fundamental approach to the dream of flight
The Wright brothers however, experimented for years
to understand the essence of flight:
• Lift (air lifting);
• Thrust (propulsion);
• Drag;
• Weight (including center of gravity).
(No feathers, nor flapping wings.)
A fundamental approach 3
Thinknowlogy - A fundamental approach to Artificial Intelligence / knowledge technology
The fundamental approach to the dream of intelligent
machines / information systems
How can we achieve a fundamental approach for the
dream of intelligent machines / information systems,
like the Wright brothers did for the dream of flight?
A fundamental approach 3
Thinknowlogy - A fundamental approach to Artificial Intelligence / knowledge technology
Characteristics of a mature science:
• A mature science is defined unambiguously;
• A mature science is based on a natural foundation;
• A mature science integrates all its disciplines.
A fundamental approach 3
Thinknowlogy - A fundamental approach to Artificial Intelligence / knowledge technology
A fundamental approach 3
A mature science is defined unambiguously
So, let's define:
• Intelligence (for Artificial Intelligence);
• Semantics (for knowledge technology).
Thinknowlogy - A fundamental approach to Artificial Intelligence / knowledge technology
A fundamental approach 3
A mature science is defined unambiguously
The definition of intelligence (for Artificial Intelligence):
“Intelligence is a naturally occurring phenomenon,
which can be described as the capability of autonomously
associating (combining),
discriminating (differentiating, distinguishing),
learning (from mistakes),
planning and
predicting,
with the aim to reach a predefined goal.”
Thinknowlogy - A fundamental approach to Artificial Intelligence / knowledge technology
A fundamental approach 3
A mature science is defined unambiguously
The definition of semantics (for knowledge technology):
“Semantics is a naturally occurring phenomenon,
which can be described as the capability of autonomously
associating (combining) and
discriminating (differentiating, distinguishing),
with the aim to reach a predefined goal.”
So, Semantics is actually a subset of Intelligence,
and knowledge technology is a subset of AI.
Thinknowlogy - A fundamental approach to Artificial Intelligence / knowledge technology
A fundamental approach 3
A mature science is based on a natural foundation
“Intelligence is a naturally occurring phenomenon …”
So, an intelligent system should derive its intelligence
from a natural source – rather than artificially created
sources, like semantic vocabularies and statistics.
Thinknowlogy - A fundamental approach to Artificial Intelligence / knowledge technology
A fundamental approach 3
A mature science is based on a natural foundation
“Intelligence […] can be described as the capability
of autonomously […]”
But what is autonomy?
Thinknowlogy - A fundamental approach to Artificial Intelligence / knowledge technology
A fundamental approach 3
A mature science is based on a natural foundation
To illustrate autonomy by a known Chinese saying:
“Give a man a fish and you feed him for a day.
Teach a man to fish and you feed him for a lifetime.”
So, an intelligent system should be able “to fish” –
e.g. building its own semantics autonomously from a
natural source – rather than being fed constantly from an
artificial source, like semantic vocabularies and statistics.
Thinknowlogy - A fundamental approach to Artificial Intelligence / knowledge technology
A mature science is based on a natural foundation
Thinknowlogy is able “to fish”:
by deriving its intelligence autonomously from a
natural source (grammar):
There are rules of intelligence contained within grammar.
(will be explained later in this presentation),
by which it is able to preserve the meaning at
natural language level throughout the system.
A fundamental approach 3
Thinknowlogy - A fundamental approach to Artificial Intelligence / knowledge technology
A fundamental approach 3
A mature science integrates all its disciplines
Proof of the pudding!
Thinknowlogy integrates several disciplines with natural
language:
• Programming in natural language;
• Reasoning in natural language;
• Intelligent answering of “is” questions in full sentences;
• Detecting some cases of semantic ambiguity.
Thinknowlogy - A fundamental approach to Artificial Intelligence / knowledge technology
A fundamental approach 3
What is Thinknowlogy?
Thinknowlogy is grammar-based software, designed
to utilize the intelligence contained within grammar,
in order to create intelligence
through natural language in software,
which is demonstrated by:
Thinknowlogy - A fundamental approach to Artificial Intelligence / knowledge technology
A fundamental approach 3
• Programming in natural language;
• Reasoning in natural language
(=reasoning expressed in natural language):
• drawing conclusions,
• making assumptions
(with self-adjusting level of uncertainty),
• asking questions (about gaps in the knowledge),
• detecting conflicts in the knowledge;
• Building semantics autonomously (no vocabularies):
• detecting of some cases of semantic ambiguity;
• Intelligent answering of “is” questions
(by providing alternative answers as well).
Thinknowlogy - A fundamental approach to Artificial Intelligence / knowledge technology
A fundamental approach 3
Demo – Programming in natural language:
• Playing the game Connect-Four only by reading
the playing rules, written as readable language;
• Greeting program written as readable text;
• Solving the Tower of Hanoi problem with the rules
written as readable text.
Remark: With some additional development,
the system will be able to execute business rules,
written as readable text.
Thinknowlogy - A fundamental approach to Artificial Intelligence / knowledge technology
A fundamental approach 3
Demo – Reasoning in natural language:
Most reasoners work at the level of linked keywords.
And therefore, they are unable to produce in sentences
in natural language.
The reasoning capability at natural language level of
Thinknowlogy is worldwide unique:
• Drawing conclusions;
• Making assumptions (self-adjusting level of uncertainty);
• Asking questions (about gaps in the knowledge);
• Detecting conflicts in the knowledge.
Thinknowlogy - A fundamental approach to Artificial Intelligence / knowledge technology
A fundamental approach 3
Demo – Intelligent answering of “is” questions
• Most scientific Question Answering (QA) systems are
only able to provide a keyword as answer;
• Other QA systems – like chatbots – are able to answer
in full sentences. However all its sentences are written
by humans.
Only Thinknowlogy is able to answer with knowledge
(either from humans or from the reasoner) in a full
sentences. And in case no answer could be found,
it tries to find an alternative, that could answer the
question of the user.
Thinknowlogy - A fundamental approach to Artificial Intelligence / knowledge technology
A fundamental approach 3
Demo – Detecting cases of Semantic Ambiguity
Disambiguation (solving ambiguity) is the biggest problem
in Natural Language Processing.
There are two types of ambiguity:
• Grammatical ambiguity, like:
“The man hit the dog with a stick”.
(Did the man hit with a stick, or had the dog a stick?);
• Semantic ambiguity, like “former president Bush”.
George H. W. Bush, or his son George W. Bush?
Thinknowlogy - A fundamental approach to Artificial Intelligence / knowledge technology
A fundamental approach 3
Demo – Detecting cases of Semantic Ambiguity
Several techniques are developed to solve semantic
ambiguity at keyword level.
However, only Thinknowlogy is able to detect
– not yet to solve – some cases of semantic ambiguity
at natural language level.
From 2013 I will start to implement solving some cases of
semantic ambiguity to prove my approach in fundamental.
Thinknowlogy - A fundamental approach to Artificial Intelligence / knowledge technology
A fundamental approach 3
From 2013 – Solving cases of Semantic Ambiguity
When a sentence is entered and its context (semantics)
is not clear, the system can either:
• use deduction to determine which context is meant by
the user;
• make an assumption, when the meant context cannot
be determined, but when it is quite obvious;
• or ask a question, when the system has no clue about
the context.
Thinknowlogy - A fundamental approach to Artificial Intelligence / knowledge technology
How to build semantics autonomously?
• By autonomously associating (combining) the
new information with existing information,
• and by autonomously discriminating (differentiating,
distinguishing) the new information from existing
information,
using the rules of intelligence contained within grammar.
A fundamental approach 3
Thinknowlogy - A fundamental approach to Artificial Intelligence / knowledge technology
Some rules of intelligence contained with grammar
to associate and discriminate knowledge:
• Indefinite article (“a”) represents a definition, a static
structure;
• Definite article (“the”) represents a dynamic structure,
similar to a variable in a programming language;
• A series of words are all from the same word type:
noun, proper noun, adjective, etc;
• Conjunction “or” marks a choice;
• Conjunctions like “and” and “or” mark a set (an
association), and distinguishes from other sets.
A fundamental approach 3
Thinknowlogy - A fundamental approach to Artificial Intelligence / knowledge technology
Some rules of intelligence contained with grammar
to associate and discriminate knowledge:
• Indefinite article (“a”) represents a definition, a static
structure: “A son is a male.” (no assignment);
• Definite article (“the”) represents a dynamic structure,
similar to the assignment of a variable in programming
languages:
“John is the father of Paul, Joe and Laura.”.
A static structure can be derived from a dynamic
structure: “John is a father.”.
A fundamental approach 3
Thinknowlogy - A fundamental approach to Artificial Intelligence / knowledge technology
Some rules of intelligence contained with grammar
to associate and discriminate knowledge:
• A series of words are all from the same word type:
noun, proper noun, adjective, etc., like in:
“0, 1, 2, 3, 4, 5, 6, 7, 8 and 9 are numbers.”.
People will get confused by a list – a series of words –
having different grammatical word types, like in:
“0, 1, 2, 3, 4, 5, 6, 7, 8 and blue are numbers.”.
A fundamental approach 3
Thinknowlogy - A fundamental approach to Artificial Intelligence / knowledge technology
Some rules of intelligence contained with grammar
to associate and discriminate knowledge:
• Conjunction “or” marks a choice, like in:
“A person is a man or a woman.”.
Using such a choice is an act of intelligence:
When given the specification: “John is a person.”, a
substitution of both sentences will result in the question:
“Is John a man or a woman?”.
A fundamental approach 3
Thinknowlogy - A fundamental approach to Artificial Intelligence / knowledge technology
Some rules of intelligence contained with grammar
to associate and discriminate knowledge:
• Conjunctions (like “and” and “or”) associate a set:
“Humans have two arms and two legs.”
and
“Humans have constructed roads and bridges.”.
However, the set of “arms” and “legs” doesn't belong to
the set of “roads” and “bridges”. So, by associating
one set, at the same time we make a distinction with
other sets, which is an act of intelligence.
A fundamental approach 3
Thinknowlogy - A fundamental approach to Artificial Intelligence / knowledge technology
When will Thinknowlogy deliver revenue?
The current approach to knowledge technology is far
from fundamental. So, we need to redo basically most
AI research done in the last 60 years:
I estimate an additional 100 man years (10 developers
during 10 years) is required to develop Thinknowlogy
as a foundation for knowledge technology. And it will be
difficult to find developers able to think outside the box.
A fundamental approach 3
Thinknowlogy - A fundamental approach to Artificial Intelligence / knowledge technology
When will Thinknowlogy deliver revenue?
However, after those 10 years of development,
Thinknowlogy will deliver a monopoly position
in knowledge technology,
with a situation comparable to men covered with
feathers and having complex wing constructions
strapped to their arms, against a fundamentally
designed airplane of the Wright brothers.
A fundamental approach 3
Thinknowlogy - A fundamental approach to Artificial Intelligence / knowledge technology
A fundamental approach 3
Demo 4
Questions 5
Introduction 1
The current approach to AI 2
Thinknowlogy - A fundamental approach to Artificial Intelligence / knowledge technology
Demo 4
Thinknowlogy integrates several disciplines with
natural language:
• Programming in natural language;
• Reasoning in natural language;
• Intelligent answering of “is” questions in full sentences;
• Detecting some cases of semantic ambiguity.
Thinknowlogy - A fundamental approach to Artificial Intelligence / knowledge technology
Thinknowlogy at startup
Thinknowlogy - A fundamental approach to Artificial Intelligence / knowledge technology
Programming in natural language:
Reading the playing rules of Connect-Four as text
Thinknowlogy - A fundamental approach to Artificial Intelligence / knowledge technology
Programming in natural language:
The playing rules of Connect-Four are executed
Thinknowlogy - A fundamental approach to Artificial Intelligence / knowledge technology
Programming in natural language:
The system has gains knowledge and keeps track of history
Thinknowlogy - A fundamental approach to Artificial Intelligence / knowledge technology
Programming in natural language:
Greeting program written as readable text (1)
Thinknowlogy - A fundamental approach to Artificial Intelligence / knowledge technology
Programming in natural language:
Greeting program written as readable text (2)
Thinknowlogy - A fundamental approach to Artificial Intelligence / knowledge technology
Programming in natural language:
Reading the rules to solve the Tower of Hanoi problem
Thinknowlogy - A fundamental approach to Artificial Intelligence / knowledge technology
Programming in natural language:
The rules of the Tower of Hanoi problem are executed
Thinknowlogy - A fundamental approach to Artificial Intelligence / knowledge technology
Reasoning in natural language:
Reading definitions about a family as readable text
Thinknowlogy - A fundamental approach to Artificial Intelligence / knowledge technology
Reasoning in natural language:
Autonomous conclusions, assumptions and questions
Thinknowlogy - A fundamental approach to Artificial Intelligence / knowledge technology
Reasoning in natural language:
When questions are answered by the user
Thinknowlogy - A fundamental approach to Artificial Intelligence / knowledge technology
Reasoning in natural language:
Another reasoning example (1)
Thinknowlogy - A fundamental approach to Artificial Intelligence / knowledge technology
Reasoning in natural language:
Another reasoning example (2)
Thinknowlogy - A fundamental approach to Artificial Intelligence / knowledge technology
Reasoning in natural language:
The assumptions have a self-adjusting level of uncertainty
Thinknowlogy - A fundamental approach to Artificial Intelligence / knowledge technology
Reasoning in natural language:
Correcting an invalidated assumption
Thinknowlogy - A fundamental approach to Artificial Intelligence / knowledge technology
Reasoning in natural language:
Justification report for the self-generated knowledge
Thinknowlogy - A fundamental approach to Artificial Intelligence / knowledge technology
Reasoning in natural language:
When conflicting knowledge is entered
Thinknowlogy - A fundamental approach to Artificial Intelligence / knowledge technology
Question Answering:
Intelligent answering of “is” questions by providing alternatives
Thinknowlogy - A fundamental approach to Artificial Intelligence / knowledge technology
Detecting some cases of semantic ambiguity:
City Boston – Multiple instances
Thinknowlogy - A fundamental approach to Artificial Intelligence / knowledge technology
Detecting some cases of semantic ambiguity:
President Bush – Re-occurrence or multiple instances? (1)
Thinknowlogy - A fundamental approach to Artificial Intelligence / knowledge technology
Detecting some cases of semantic ambiguity:
President Bush – Re-occurrence or multiple instances? (2)
Thinknowlogy - A fundamental approach to Artificial Intelligence / knowledge technology
A fundamental approach 3
Demo 4
Questions 5
Introduction 1
The current approach to AI 2
Thank you
A webinar initiated by Compegence
December 15, 2012
© 2012 Menno Mafait http://mafait.org