Slide tiếng Anh thuyết trình về artificial intelligence (trí thông minh nhân tạo)

HANOI UNIVERSITY OF
SCIENCE AND TECHNOLOGY

Technical Writing
and Presentation
Class:
Lecturer:

Artificial Intelligence
Student:


INTRODUCTI
ON

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5

EVOLUTION
OF AI

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2

TYPES OF AI

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6

FUTURE OF
AI

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3

SUBFIELDS
OF AI

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7

PROS AND
CONS

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4

APPLICATION
OF AI

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8

CONCLUSIO
N

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1


INTRODUC

TION

0


What is
Artificial
Intelligence?
AI (Artificial Intelligence) is a machine’s ability to perform cognitive
functions as humans do, such as perceiving, learning, reasoning, and
solving problems.


HISTORY

1956:
Dartmouth
Conference –
“AI” adopted

1974-1980:
AI Winter

1980s: New
Hopes

1997: IBM
Deep Blue
beat a world
chess

champion


02
TYPES
OF AI


Threes types of AI

AI

ANI

Artificial Narrow
Intelligence – Narrow
range of abilities

AGI

Artificial General
Intelligence – On par with
human capabilities

ASI

Artificial Super
Intelligence – More
capable than a human

Artificial Narrow Intelligence

Goal Oriented

Predefined
Parameters,
Constraints,
Contexts

Single Task

NLP;
Versi


Examples of
narrow AI
Siri by Apple, Alexa by Amazon,
Cortana by Microsoft and other virtual
assistants.

Image / facial recognition
software

Marketing content
recommendations

Self-driving cars

Artificial
General
• Similar to human intelligence.
Intelligence
•

Also known as strong AI or full
AI.

•

Has human-like consciousness
and cognitive abilities.

•

Yet to become a reality.

•

Can solve unfamiliar problems.


Artificial Superintelligence
An intellect that is much smarter than the
best human brains in practically every
field.
An ASI system would be able to surpass
all human capabilities; include decision

making, taking rational decisions, and
includes things like making better art and
building emotional relationships


03

SUBFIEL
DS OF AI


•

Artificial Intelligence is the concept of
creating smart intelligent machines.

•

Machine Learning is a subset of
artificial intelligence that helps you
build AI-driven applications.

•

Deep Learning is a subset of machine
learning that uses vast volumes of
data and complex algorithms to train
a model.

WHAT IS MACHINE LEARNING ?

Machine learning is a
discipline of computer science
that uses computer algorithms
and analytics to build
predictive models that can
solve business problems.


Types of Machine Learning


Machine
Learning
Processes


Machine Learning Applications


WHAT IS DEEP LEARNING?

A subset of machine learning that deals with algorithms inspired by
the structure and function of the human brain.
Deep learning algorithms can work with an enormous amount of both
structured and unstructured data.
Deep learning’s core concept lies in artificial neural networks, which
enable machines to make decisions.

Neural
Network


Difference between Machine
Learning and Deep Learning


Types of Deep Neural Networks


04
APPLICAT
ION OF
AI


Applications
E-Commerce
Lifestyle
Robotics

Education

Social Media

Marketing

05

EVOLUTI
ON OF AI


1950’s to 1990’s

Rising Period
195
0’s

196
0’s

Starting Period

197
0’s

Steady
Development
Period
198
199
0’s

Low Development
Period

0’s