CONTEXT and KNOWLEDGE
Irina Codreanu and Monica GavrilaStudents at Bucharest University
Socrates Students at Hamburg University
CONTEXT and KNOWLEDGE
Irina Codreanu and Monica GavrilaStudents at Bucharest University
Socrates Students at Hamburg University
Summary
Context Knowledge Human brain Human brain vs. computer Can computers be considered intelligent?
Positive examplesDeepBlue MYCIN
Negative examples Expressing knowledge through language
ContextDefinition
Several definitions
– Discourse that surrounds a language unit and helps to determine its interpretation
– The set of facts or circumstances that surround a situation or an event
Context
Some context related properties Contexts increase inferential power Learning (new information) occurs in specific
context Knowledge can be generalised from specific
contexts to more general ones Contexts themselves can be objects of inference Different contexts can be selected depending on
previous contexts Whether something acts as a context or not could
itself be context dependent
KnowledgeDefinition The act or state of knowing; clear
perception of fact, truth or duty; cognition The psychological result of perception of
learning and reasoning Knowledge is information that has been
pared, shaped, interpreted, selected and transformed (Ray Kurzweil) Facts alone do not constitute knowledge
KnowledgeHuman vs. Computer Human intelligence
– Remarkable ability of creating links between ideas
– Weak at storing information on which knowledge is based
The natural strengths of computers are roughly the opposite powerful allies of the human intellect
Human Knowledge
Abstract concepts When we come in contact with a new concept we add new
links Knowledge structures are not affected by the failure of the
hardware (50000 neurons die each day in an adult brain, but our concepts and ideas do not necessary deteriorate)
We are capable of storing apparently contradictory ideas Unless a new idea is reinforced it will eventually die out Strong links between our emotions and our knowledge Our knowledge is closely tied to our pattern-recognition
capabilities We are able to change our minds change our internal
networks of knowledge
Computer Knowledge
Propaedia A section of the 15th edition of Encyclopaedia Britannica
(1980) An ambitious attempt to organize all human knowledge in
a single hierarchy Allows multiple classifications Takes time to understand but it is successful in view of the
vast scope of the material it covers
Such data structures provide a formal methodology for representing a broad class of knowledge easily stored and manipulated by the computer
Human brain and knowledge
Human brain
Highly parallel early vision circuitsVisual cortex neuron clustersAuditory cortex circuitsThe hippocampusThe amygdala
Human Brain
Human brain on the order of 100 billion neurons One neuron thousands of synaptic connections There is a speculation that certain long-term
memories are chemically coded in neuron cell bodies
The capacity of each neuron 1000 bits the brain has the capacity of 1014 bits
If we assume an average redundancy factor of 104, that gives us 1010 bits per concept 10 6 concepts per human brain
Human Brain
It has been estimated that a “master” of a particular domain of knowledge has mastered about 50000 concepts, which is about 5 percent of the total capacity, according to the above estimate
Human Brain vs. Computer
The human brain uses a type of circuitry that is very slow
For tasks as vision, language or motor control, the brain is more powerful than 1000 super computers
For certain tasks simple tasks such as multiplying digital numbers it is less powerful that the 4-bit microprocessor found in a ten dollar calculator
Computer Learning vs. Biological Learning
The brain is wired to learn in interaction with the world, re-programming themselves over time
Computers don’t learn easy by experience A human child
– Starts out listening to and understanding spoken language– Learns to speak– Learns written language
Computer – Starts with the ability to generate written languge– Learning to understand it– Speak with synthetic voices– Understand continuous human speech (recently)
Deep Blue
Its predecessor Deep Thought appeared at Carnegie Mellon University. In 1989 it was beaten by Kasparov in 41 moves
Project continued at IBM’s T.J. Watson Research centre
Improvements every year: now it has 30 Power Two Super Chip Processors
Is capable of 200 million positions / second (Kasparov of 3 positions / second)
Almost no use of psychology
Deep Blue
Its strenghts are the strenghts of a machine: it has a database of opening games played by grandmasters over the last 100 years
It does not think, it reacts Only one specific job It considers before deciding on a move 4
parameters: material, position (control of the centre), King safety and tempo (losing tempo= wasting time by indecision, and the opponent making productive moves)
MYCIN
Created in mid 1970’s by E.H. Shortliffe at Standford University
Medical diagnosis tool (attempts to identify the cause of infection)
Suggests a course of medication It uses 500 rules Each rule has assigned a number its users
can assess the validity of it’s conclusion (WHY) Can recognise approximate 100 causes of
bacterial infection
MYCIN
Fragment of a dialog between Mycin and a doctor
>> What is the patient’s name? John Doe >>Male or female? Male >>Age? 52 >>Let’s call the most recent positive culture C1 From what site was C1 taken? …… >>My recommendation is as follows: give gentamycin using a
dose of 119 mg…
Other intelligent programs in medicine: PUFF: a system for interpreting pulmonary
tests ONCOCIN: a system for the design of
oncology chemotherapy protocols CADUCEUS (former Internist): a system for
diagnosis within a broad domain of internal medicine; it contains over 100,000 associations between symptoms (70% of the relevant knowledge in the field)
Other domains
Teknowledge is creating a system for General Motors that will assist garage mechanics
ISA (Intelligent Scheduling Assistant): schedules manufacturing and shop floor activity
DENDRAL: embodied extensive knowledge of molecular structure analysis (Meta-DENDRAL)
SCI (Strategic Computing Initiative): several prototypes, among which is Vision System (will provide real-time analysis of imaging data from intelligent weapons and reconnaissance aircraft))
Expressing Knowledge through Language Language is the principal means by which
we share knowledge Language in both its auditory and written
forms is hierarchical with multiple levels To respond intelligently to human speech,
one need to know, among other things:– The structure of the speech sounds– The way speech is produced– The patterns of sound– The rules of word usage
Expressing Knowledge through Language Computers sentence-parsing systems
can do good jobs at analysing sentences that confuses humans:
“This is the cheese that the rat that the cat that the dog chased bit ate”
Expressing Knowledge through Language
But with other types of sentences it has difficulties:
“Time flies like an arrow”
or
“Squad Helps Dog Bite Victim” The difficulties appear when a word has
several meanings or are used idiomatic expressions
Expressing Knowledge through Language Explanation to the first sentence:
For the computer this sentence it might mean:The time passes as quickly as an arrow passes,Or maybe it is a command telling us to time flies
the same way that an arrow flies - Time flies like an arrow would
Or it could be a command telling us to time only those flies that are similar to arrows - Time flies that are like an arrow
Or perhaps it means that the type of flies known as time flies have a fondness for arrows - Time flies like (that is cherish) an arrow.
Expressing Knowledge through Language
The ambiguity of language is far grater than may appear.
At MIT Speech Lab, a researcher found a sentence published in a technical journal with over 1,000,000 syntactically correct interpretations!!!!!!!!
Expressing Knowledge through Language TRANSLATION:
one of the challenges in developing computerized translation system
Each pair of languages represents a different translation problem
Best solution known was given by a Dutch firm named DLT
Expressing Knowledge through Language Solution found by DLT:
– Developed translators for six languages to and from a standard root language (ESPERANTO)
– A translation from English to German would be accomplished in 2 steps: from English to Esperanto and from Esperanto to German
– Esperanto was selected because it is particularly good at representing concepts in an unambiguous way
– Translating among 6 different languages would ordinarily require 30 different translators, but with the DLT approach only 12 are required
R2D2
Robot in Star Wars Designed to operate in deep space, interfacing
with fighter craft and computer systems to augment the capabilities of ships and their pilots
Monitors flight performance, well-versed in star ship repair, a.s.o.
Converses in a dense electronic language (beeps, chirps, whistles)
Can understand most forms of human speech, but must have his own communication interpreted by other computers