Introduction

28
Introduction Natural intelligence Artificial intelligence (AI) History of AI Characteristics of AI system AI tasks AI roots and applications

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Introduction. Natural intelligence. Artificial intelligence (AI). History of AI . Characteristics of AI system. AI tasks. AI roots and applications. WHAT A BRAIN CAN DO?. Solve maths problem. Recognize a ball. Predict weather. Search solution. Diagnose disease. Plan. - PowerPoint PPT Presentation

Transcript of Introduction

Page 1: Introduction

Intr

oduc

tion Natural intelligence

Artificial intelligence (AI)History of AI

Characteristics of AI systemAI tasks

AI roots and applications

Page 2: Introduction

natural

WHAT A BRAIN CAN DO?

Recognize a ball

Plan

Search solution

Understand speech/language

Diagnose disease

Predict weather

Solve maths problem

Learn

Make decision

Commonsense reasoning……………………………

Page 3: Introduction

natural

Page 4: Introduction

AI is ….an ‘imitation’ of human intelligence into a

machine

naturalartificial

Page 5: Introduction

natural

Not consistentCannot be copied

or transferredHigh cost

Difficult to bedocumented

CreativeWider focus

Page 6: Introduction

artificial

ConsistentCan be copiedor transferred

Low costCan be

documentedLimited focus

Page 7: Introduction

DEF

INIT

ION

“science and engineering of making intelligent machines”

“science of making computers DO things

that require intelligence if they are done by humans”

“science of making a computer REASON

in a manner similar to humans”

John McCarthy

Marvin Minsky

Durkin Jackson

Page 8: Introduction

DIM

ENSI

ON System

thinks like human

System acts

like human

System thinks

rationally

System acts

rationally

Page 9: Introduction

DIM

ENSI

ON Cognitive

Science perspective(thinking process)

Engineering perspective(behavior)

Page 10: Introduction

DIM

ENSI

ON System

thinks like

humanSystem acts

like human

System thinks rationally

System acts rationally

Page 11: Introduction

DIM

ENSI

ON

Compare system

against real concept of intelligence

Compare system against human

Page 12: Introduction

HIS

TORY

1st AI winterLISP

Dartmouth workshopPeriod of enthusiasm

Turing test1st NN computer built

1st commercializationRebirth

2nd AI winterRe-emergence

1966-197319581956

1952-196219501950

19801969-1979

19882000s

Page 13: Introduction

AI

EVO

LUTI

ON Embedded application

Multiple integration

Domain knowledge

General method

Naïve solution

2000 onwards

1990s

1980s

1970s

1960s

Page 14: Introduction

This game ends when the interrogator made his guess

Turing machine pass the test if the interrogator fails to recognize with

whom (or with what) he is communicating.

TURING MACHINE

TURI

NG

TE

ST

Page 15: Introduction

1 - Knowledge processing

on(a,b)on(b,c)

on(c,table)clear(a)

ABC

CHAR

ACTE

RIST

IC The birds fly

D VN

VPNP

S

the birds flys(np(det(the),noun(birds)),vp(v(fly)))

Page 16: Introduction

2 - Focus on heuristic

4 - Possess inference ability

3 - Symbolic processing

5 - Learns

CHAR

ACTE

RIST

IC

Page 17: Introduction

Mundane

Formal

ExpertAI T

ASKS

Page 18: Introduction
Page 19: Introduction

“We may not have full-

functioning robots that cater our

every need, but AI is

embedded in our everyday

lives.”- Computer

WorldAPPL

ICAT

ION

Page 20: Introduction

“Once tools get far

enough out of the lab,

they’re no longer AI,

just common computer science.”

- Prof. George LugerAP

PLIC

ATIO

N

Page 21: Introduction

Household gadgets

• washing machine• rice cooker• microwave

• vacuum cleaner

APPL

ICAT

ION

Page 22: Introduction

Autonomous vehicle

Hi, my name is Stanley

APPL

ICAT

ION

Page 23: Introduction

Search engine crawlers

NewsFinder

FlipDog

NetFlix

(natural language processing technology)APPL

ICAT

ION

Page 24: Introduction

Automobile safety system

self-parking

intelligent

cruisecontrol

lanedeparturewarning

APPL

ICAT

ION

Page 25: Introduction

Voice response system(IVR)

Speech recognition Natural language understanding

APPL

ICAT

ION

Page 26: Introduction

Chatter botJenn

Alex

Eva

Captain Kirk

Alice

George

(natural language processing technology)APPL

ICAT

ION

Page 27: Introduction

Resource allocation problem

Optimizing airport schedule

(genetic algorithm technology)AP

PLIC

ATIO

N

Page 28: Introduction

Credit card fraud detectionFalcon

(neural network technology)

Pap smear screeningFocalPoint

(expert system technology)

APPL

ICAT

ION


Introduction Chapitre 1 · Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Introduction Chapitre 1 · Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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