manton matthews department of computer sc. & engr. scholar’s day april 5, 2008 how computers...

Manton MatthewsDepartment of Computer Sc. & Engr.

Manton MatthewsDepartment of Computer Sc. & Engr.

Scholar’s Day April 5, 2008

How computers think; but do they understand?

– 2 – Scholar’s Day April 2008

What is Thinking? What is Thinking?

Merriam-Webster DefinitionsMerriam-Webster Definitions

Thinking- The action of using one’s mind to produce Thinking- The action of using one’s mind to produce thoughtsthoughts

Can a machine think?Can a machine think?

http://www.merriam-webster.com/dictionary/


What is Intelligence?What is Intelligence?

1.1. the ability to learn or understand or to deal with new the ability to learn or understand or to deal with new or trying situationsor trying situations

2.2. the ability to apply knowledge to manipulate one's the ability to apply knowledge to manipulate one's environment or to think abstractly as measured by environment or to think abstractly as measured by objective criteria (as tests) objective criteria (as tests)

http://www.merriam-webster.com/dictionary/


Computers Acting IntelligentlyComputers Acting Intelligently

• Interacting with humansInteracting with humans

• Analyzing situations and making appropriate Analyzing situations and making appropriate decisionsdecisions


Examples of Intelligence? Interact with customers in a business Examples of Intelligence? Interact with customers in a business Worker must be able to:Worker must be able to:

Understand customer’s wishes Address the request Maybe handle the details of the

sale


More Specifically a Bank TellerMore Specifically a Bank Teller

Teller must be able to:Teller must be able to: Understand customer’s wishes Count checks/money Give cash and receipts to the

customer


Computer Bank TellerComputer Bank Teller

Teller must be able to:Teller must be able to: Understand customer’s wishes Count checks/money Give cash and receipts to the

customer


Chess PlayerChess Player

““chess is gymnastics of the mind” chess is gymnastics of the mind”


Evolution of Chess Playing ComputersEvolution of Chess Playing Computers


Deep Blue defeats World Chess ChampionDeep Blue defeats World Chess Champion

"You have to be on full guard every move of the game, "You have to be on full guard every move of the game, which means it is more exhausting. I think Deep Blue which means it is more exhausting. I think Deep Blue is stronger than all but a handful of top human is stronger than all but a handful of top human players." - Garry Kasparov players." - Garry Kasparov


AiboAibo

..


..


Examples of Aibo’s “thinking”Examples of Aibo’s “thinking”

1.1. Waking up on back Waking up on back (1:14)(1:14)

2.2. Picking up the Aibone (= Aibo’s bone) Picking up the Aibone (= Aibo’s bone) (3:03/2:00)(3:03/2:00)

3.3. Aibo juggling ball Aibo juggling ball (3:51/2:12)(3:51/2:12)

4.4. Aibo ball balancing trick Aibo ball balancing trick (5:05/1:42)(5:05/1:42)

5.5. Time for rest and recharge. Time for rest and recharge. (1:26)(1:26)

6.6. Solving a maze Solving a maze (2:59)(2:59)

7.7. Following DirectionsFollowing Directions

8.8. Remote photographerRemote photographer


Aibo’s “maze solving”Aibo’s “maze solving”

Aibo’s sensors:Aibo’s sensors:

Solve a maze:Solve a maze:

1.1. Walk forward till we sense an obstacleWalk forward till we sense an obstacle

2.2. Pan head from left to right looking for longest Pan head from left to right looking for longest distance that is unobstructeddistance that is unobstructed

3.3. Turn that direction and repeat 1-3Turn that direction and repeat 1-3

Else if all directions obstructed turn 180 degrees Else if all directions obstructed turn 180 degrees and repeat 1-3and repeat 1-3


Email me a photo!Email me a photo!

xx


Star Trek’s DoctorStar Trek’s Doctor

Why consider him here?Why consider him here?

http://en.wikipedia.org/wiki/Doctor_(Star_Trek)


Practical Computers Acting IntelligentlyPractical Computers Acting Intelligently

Expect computers to do some things well (even better than a human):Expect computers to do some things well (even better than a human):

1.1. Number crunchingNumber crunching

2.2. Combinatorial search (chess)Combinatorial search (chess)

3.3. ……

But how about tasks requiring subjective judgment?But how about tasks requiring subjective judgment?

Example: Predict success of a student in a training programExample: Predict success of a student in a training program

1955 Paul Meehl showed simple statistical learning algorithms out 1955 Paul Meehl showed simple statistical learning algorithms out performed experts in 19 or 20 studiesperformed experts in 19 or 20 studies

Since 1999 ETS has used a program to grade essay questions on the Since 1999 ETS has used a program to grade essay questions on the GMAT, 97% agreement with human expert graders (the same as GMAT, 97% agreement with human expert graders (the same as with other human experts)with other human experts)


Alan TuringAlan Turing

1912 (23 June): Birth, Paddington, London1912 (23 June): Birth, Paddington, London1931-34: Undergraduate at King's College, Cambridge University1931-34: Undergraduate at King's College, Cambridge University1932-35: Quantum mechanics, probability, logic1932-35: Quantum mechanics, probability, logic1935: Elected fellow of King's College, Cambridge1935: Elected fellow of King's College, Cambridge1936: The Turing machine, computability, universal machine1936: The Turing machine, computability, universal machine1936-38: Princeton University. Ph.D. Logic, algebra, number theory1936-38: Princeton University. Ph.D. Logic, algebra, number theory1938-39: Return to Cambridge. Introduced to German Enigma 1938-39: Return to Cambridge. Introduced to German Enigma cipher machinecipher machine1939-40: The Bombe, machine for Enigma decryption1939-40: The Bombe, machine for Enigma decryption1939-42: Breaking of U-boat Enigma, saving battle of the Atlantic1939-42: Breaking of U-boat Enigma, saving battle of the Atlantic1943-45: Chief Anglo-American crypto consultant. Electronic work.1943-45: Chief Anglo-American crypto consultant. Electronic work.1945: National Physical Laboratory, London1945: National Physical Laboratory, London1946: Computer and software design leading the world.1946: Computer and software design leading the world.1947-48: Programming, neural nets, and artificial intelligence1947-48: Programming, neural nets, and artificial intelligence1950: The Turing Test for machine intelligence1950: The Turing Test for machine intelligence1954: Death (suicide) by cyanide poisoning1954: Death (suicide) by cyanide poisoning


Turing’s Imitation GameTuring’s Imitation Game

Version 1Version 1

Three participants A,B and the interrogatorThree participants A,B and the interrogator

One of A and B is a woman, the other a manOne of A and B is a woman, the other a man

In separate rooms, communicate only through terminal In separate rooms, communicate only through terminal

Assuming the man tries to fool the interrogator, can he still Assuming the man tries to fool the interrogator, can he still identify the woman?identify the woman?

Version 2Version 2

Replace the man with a computer.Replace the man with a computer.

Turing’s claim: If the computer can make the interrogator miss 50% Turing’s claim: If the computer can make the interrogator miss 50% of the time, then the computer has acted intelligently.of the time, then the computer has acted intelligently.


Loebner PrizeLoebner PrizeLoebner PrizeLoebner Prize

The Loebner Prize is an annual competition that awards The Loebner Prize is an annual competition that awards prizes to the prizes to the Chatterbot considered by the judges to considered by the judges to be the most be the most humanlike


John Searle's Chinese room John Searle's Chinese room

Thought experiment By John Searle 1980

to show that a symbol processing machine like a computer can never be properly described as understanding

Suppose a computer that behaves as if it understands Chinese so well it passes the Turing Test

Chinese characters program Chinese response means pages with the characters are slid under the door

Now suppose Searle is in the room reading a book in English that has the program instructions in it And he follows them to produce the output character


But can a computer understand?But can a computer understand?

Circle of terms revisitedCircle of terms revisited

IntelligenceIntelligence

ThinkThink

UnderstandUnderstand

MindMind

Conscious Conscious

This is the realm of philosophers!This is the realm of philosophers!


Weak AI vs Strong AIWeak AI vs Strong AI

Weak AI hypothesis: Weak AI hypothesis:

It is possible for a machine to act intelligently or even It is possible for a machine to act intelligently or even less objectionable “to act as if it were intelligent.”less objectionable “to act as if it were intelligent.”

Strong AI hypothesisStrong AI hypothesis

It is possible for a machine to actually think; to It is possible for a machine to actually think; to understand; to be conscious; understand; to be conscious;


Examples of Quirkiness in MeaningsExamples of Quirkiness in Meanings

Consider the definitions of two forms of locomotion: Consider the definitions of two forms of locomotion:

flying through the air and swimming through water.flying through the air and swimming through water.

• Fly - 1 a: to move in or pass through the air with Fly - 1 a: to move in or pass through the air with wings wings

• So airplanes fly

• Swim - 1 a: to propel oneself in water by natural Swim - 1 a: to propel oneself in water by natural means (as movements of the limbs, fins, or tail)means (as movements of the limbs, fins, or tail)

• But boats don’t swim

Norvig and Rusell: AI a Modern Approach


So now do we agree?So now do we agree?

Computer can act intelligently but they can’t Computer can act intelligently but they can’t understand.understand.


The Human MindThe Human Mind

How do humans:How do humans: thinkthink rememberremember understandunderstand


Your BrainYour Brain

100 billion nerve cells, neurons100 billion nerve cells, neurons

InterconnectionsInterconnections

Neurons have:Neurons have: Cell bodyCell body AxonAxon DendritesDendrites SynapsesSynapses Neuro-transmittersNeuro-transmitters

They stimulate each other by “firing”They stimulate each other by “firing”


http://health.howstuffworks.com/brain1.htm


Neurons FiringNeurons Firing

Neurons that fire together Neurons that fire together get better at it; they get better at it; they form associationsform associations

The Brain Fitness Program


Hebb’s LawHebb’s Law

Donald Hebb a Neuro-psychologist (1949)Donald Hebb a Neuro-psychologist (1949)

““When an axon of cell A is near enough to excite cell B When an axon of cell A is near enough to excite cell B and repeatedly or persistently takes part in firing it, and repeatedly or persistently takes part in firing it, some growth process or metabolic change takes some growth process or metabolic change takes place in one or both cells such that A's efficiency, as place in one or both cells such that A's efficiency, as one of the cells firing B, is increased.one of the cells firing B, is increased.”

"Neurons that fire together wire together."


Organic vs Inorganic ChemistryOrganic vs Inorganic Chemistry

1828 Wohler wrote1828 Wohler wrote "I must tell you that I can make urea without the use of "I must tell you that I can make urea without the use of

kidneys, either man or dog. Ammonium cyanate is urea."kidneys, either man or dog. Ammonium cyanate is urea."

““This organic synthesis dealt a severe blow to a This organic synthesis dealt a severe blow to a widespread belief called ‘vitalism’ which maintained widespread belief called ‘vitalism’ which maintained that organic chemicals could be modified by that organic chemicals could be modified by chemistry but could only be produced through the chemistry but could only be produced through the agency of a vital force present in living plants and agency of a vital force present in living plants and animals.”animals.”

http://www.3rd1000.com/urea/urea.htm


Organic vs Inorganic MindsOrganic vs Inorganic Minds

Can we build an artificial Neuron?Can we build an artificial Neuron? Not yet certainlyNot yet certainly But artificial hearts, …But artificial hearts, …

Suppose we could and further suppose that we could Suppose we could and further suppose that we could replace one in the brainreplace one in the brain

And replace anotherAnd replace another

……

Did that mind lose its ability to understand when we Did that mind lose its ability to understand when we replaced the first artificial neuron? the 2replaced the first artificial neuron? the 2ndnd ? … the ? … the lastlast


Moore’s Law 1965 for next 10 yearsMoore’s Law 1965 for next 10 yearsThe number of transistors in an Integrated Circuit is The number of transistors in an Integrated Circuit is

doubling approximately every two yearsdoubling approximately every two years

http://en.wikipedia.org/wiki/Moore's_law

manton matthews department of computer sc. & engr. scholar’s day april 5, 2008 how computers...

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