Introduction to AI

ARTIFICIAL INTELLIGENCE
Introduction to
By Sathittham Sangthong
Aug 19, 2017

Product Development Engineer
Innovation Technology Office
SCG Building Materials Co.,Ltd.
M.Eng. - Information Engineering
King Mongkut’s Institute of Technology Lardkrabang (KMITL)
B.Eng - Computer Engineering
King Mongkut’s Institute of Technology Lardkrabang (KMITL)
Quality Persons of The Year 2010
Foundation of Science and Technology Council of Thailand (FSTT)
1st Runner Up, Popular Vote, Top Score Day 4 & 5
TESA Top Gun Rally 2010
1st Runner up & Judge Choice Award
Internationa Design Contest (IDC ROBOCON 2008)@ Brazil
1st Runner up
Robot Design Contest (RDC) 2008 @Thailand
SATHITTHAM SANGTHONG (PHOO)

Startup Wantrepreneur (Want + Entrepreneur)
Maker, DIYer, BloggerEmbedded System Engineer, System Integrator

Agenda
• Introduction to Artificial Intelligence (AI)
• Why should you learn Artificial Intelligence?
• What is Human Intelligence?
• What is Artificial Intelligence?
• Getting to know a little bit more about Artificial Intelligence
• Artificial Intelligence Glossary
• Machine Learning(ML) & Natural Language Processing(NLP)
• Machine Learning
• Natural Language Processing
• Robotics & Internet of Things(IoT)
• Robotics
• Internet of Things
• AI & The Future of Work
• The machines are coming

KNOWLEDGE
IS POWER
SIR FRANCIS BACON (1561 - 1626)

EXABYTE?
bytes
18exabyte
1,000,000,000,000,000,000

Library of Congress = Largest in The world
ALL Text Content x 100,000 = 1 Exabyte
But, we now create this
much information every6
hours
!

Annual global IP Traffic will pass the
Zettabyte([ZB]; 1000 Exabyte[EB]) threshold
by the end of 2016,and will reach 2.3 ZB
per year by 2020
The Zettabyte Era — Trends and Analysis – Cisco

IS KNOWLEDGE
STILL POWER?
SIR FRANCIS BACON (1561 - 1626)

WHY SHOULD YOU LEARN
ARTIFICIAL INTELLIGENCE ?

“Artificial Intelligence would be the ultimate version of Google.
We’re nowhere near doing that now.
However, we can get incrementally closer to that, and that is
basically what we work on”
- Larry Page
CEO, Google, October 2000
“We’ve been building the best AI team and tools for
years, and recent breakthroughs will allow us to do
even more.
We will move from mobile first to an AI first world.”
- Larry Page
CEO, Alphabet, April 28, 2016

AI in Google I/o 2017
1. TensorFlow
Google’s Machine learning System
2. 2nd Generation TPU (Tensor Processing Unit)
for TensorFlow Research Cloud
3. Machine Learning API
• Google Cloud Machine Learning Engine
• Google Cloud Jobs API
• Google Cloud Vision API
• Google Cloud Speech API
• Google Cloud Natural Language API
• Google Cloud Translation API
• Google Cloud Video Intelligence API
4. AI in Google’s Products
• Google Assistant
• Google Lens
Google.ai
May 17,2017 – May 19, 2017

Facebook CEO Mark Zuckerberg talks about the company's 10-year road map during
@ Facebook’s F8 developers conference in April,2016

Top 10 Hot AI Technologies, Q1 ‘17
The 10 Hottest AI Technologies:
1. Natural Language Generation
2. Speech Recognition
3. Virtual Agents
4. Machine Learning Platforms
5. AI-optimized Hardware
6. Decision Management
7. Deep Learning Platforms
8. Biometrics
9. Robotic Process Automation
10. Text Analytics and NLP
38% of enterprises are already using AI,
growing to 62% by 2018

Introduction to
Artificial Intelligence (AI)

Learning
What is Human Intelligence ?
Understanding of Language FeelingPerceiving
Reasoning

WHAT IS
ARTIFICIAL INTELLIGENCE ?

What is Artificial Intelligence ?
AI = Machine Intelligence
• Artificial Intelligence is the science and engineering of making
intelligence machine
• A computer performing tasks that are normally though to require
human intelligence
• Getting a computer to do in real life what computers do in the movies
-John McCarthy

TURING TEST
• Can Machine think ?
• A way to test machine intelligence. To determine
w/ ?s whether responses come from computer
or human

“Now you decide am I a machine,
am I a human, am I a war hero,
or am I a criminal.”
- Alan Turing, The Imitation Game (2014)

Artificial Intelligence Evolution

“Success in creating AI would be the biggest event in human history.
Unfortunately, It might also be the last, unless we learn how to avoid
the risks”
- Steven Hawking

Getting to know a little bit more about

Thinking
Goals of AI
System that think like humans System that think rationally
System that act like humans System that act rationally
Acting
Human
This model from Russell and Norving.
Rational

Thinking
Goals of AI
System that think like humans
“Cognitive Science”
• Neuron Level
• Neuroanatomical Level
• Mind Level
Acting
Human Rational

Thinking
Goals of AI
• Neuron Level
• Mind Level
System that act like humans
“The Turing Test”
• Understand language
• Game AI, Control NPCs
• Control the body
Acting
Human Rational

Thinking
Goals of AI
• Neuron Level
• Mind Level
System that think rationally
“Laws of thought”
• Logic
• A is X and X are Y then A is Y
Acting
Human Rational

Thinking
Goals of AI
• Neuron Level
• Mind Level
System that think rationally
“Laws of thought”
• Logic
• A is X and X are Y then A is Y
System that act rationally
“Doing the right thing”
• Maximize the goal achievement, given
information
• Doesn’t necessary involve thinking
• It involve solving
Acting
Human Rational

What’s required for a machine to be Intelligent ?

Glossary of

• Artificial Intelligence (AI) :
A field of computer science dedicated to the study of computer software making
intelligent decisions, reasoning, and problem solving.
• Machine Learning (ML) :
A field of AI focused on getting machines to act without being programmed to do
so. Machines "learn" from patterns they recognize and adjust their behavior
accordingly.
• Natural Language Processing (NLP) :
The ability of computers to understand, or process natural human languages and
derive meaning from them. NLP typically involves machine interpretation of text
or speech recognition.
AI Terms you should know

• Data Mining :
The process by which patterns are discovered within large sets of data
with the goal of extracting useful information from it.
• Deep Learning (DL):
A subset of machine learning that uses specialized algorithms to
model and understand complex structures and relationships among
data and datasets.

• Big Data:
The VOLUME, VARIETY and VELOCITY of the data creates challenges for data
processing systems
• Algorithm:
Formula that represents a relationship between things. It’s self-contained, step-
by-step set of operations that automates a function, like a process,
recommendation or analysis.
• Neural Network:
Computational approach that loosely models how the brain solves problems with
layers of inputs and outputs. Rather than being programmed, the networks are
trained with several thousand cycles of interaction.

• Intelligent Agents
• An Agent is Anything
• Can be Viewed as Perceiving its Environment
Through Sensors
• Acting upon that Environment through Actuators
The different types of agent
• Human Agent
• Robotic Agent
• Software Agent
• Generic Agent
𝑓: 𝑃 ∗ → 𝐴
• Agent Function which maps every
possible precepts sequence to a
possible action the agent can perform
Agent = Architecture + Program

• Intelligent Agents - Example : Taxi Driver
• Performance Measure:
Safe, Fast, Legal, Comfortable Trip, Maximize profits
• Environment:
Roads, other traffic, pedestrians, customers
• Actuators:
Steering wheel, accelerator, brake, signal, horn
• Sensors:
Cameras, Sonar, Speedometer, GPS, engine sensor

Uses of AI spreading Rapidly and Widely

A Supercomputer called Deep Blue beat world chess champion Garry Kasparov
Deep Blue by IBM Garry Kasparov
KASPAROV VS DEEP BLUE in 1997

2 All-time Greatest
Jeopardy champions
VS IBM Watson in 2011

• A Sub-Field of AI
• Construction and study of systems that can learn from data
What is Machine Learning?

• Evolved from pattern recognition and computational learning theory
• Subfield of Artificial Intelligence
• Study of Algorithms that iteratively learn form data
• Make predictions
• Find hidden insights without explicit programming

• Types of Learning
• Supervised Learning:
Reliance on algorithm trained by human input, reduce expenditure on manual
review for relevance and coding
• Unsupervised Learning:
High reliance on algorithm for raw data, large expenditure on manual review
for review for relevance and coding
• Semi-Supervised Learning:
Reliance on analytics trained by human input, automated analysis using
resulting model
• Reinforcement Learning:
Algorithm is continually trained by human input, can be automated once
maximally accurate

In other words …
“Learning is any process by which a system improve
performance from experience”
“Machine Learning is concerned with computer
programs that automatically improve their
performance through experience”
- Herbert Simon

Google Voice Search
Google’s Self Driving Car Google Translate
Gmail Spam Detection

YouTube Playlist - Content Curation

https://experiments.withgoogle.com/ai

Pinterest – Improved Content Discovery

• Machine Learning has a wide spectrum of applications including:
• Spam Email Detection
• Machine Translation (Language Translation)
• Image Search (Similarity)
• Clustering (KMeans) : Amazon Recommendations
• Classification : Google News
• Text Summarization : Google News
• Fraud detection : Credit card Providers
• Speech Understanding : iPhone with Siri
• Face Dectection : Facebook’s Photo tagging
ML Applications

https://www.youtube.com/watch?v=SUbqykXVx0A

• Google
• TensorFlow
• Keras
• Facebook
• Caffe2
• Amazon
• DSSTNE
• Microsoft
• CNTK
Deep Learning Framework by Big Tech Companies
Credit - https://twitter.com/fchollet/status/776455778274250752/photo/1

Natural Language Processing (NLP)
• What is NLP?
• Study of interaction between computer and human languages
• A Sub-Field of AI
• Aim : To build intelligent computer that can interact with human being like a human being !!
NLP = Computer Science + AI + Computational Linguistics
Language Language
Understanding
Generation
(NLG)
(NLU)

What Makes NLP so Hard?
• Ambiguity
• Non-Standard Language
• Complex entity names
• Phrasal verbs/idioms
• More Complex Language than English
• German
• Chinese
• Japanese
• Thai

Recap
AI
ML
DL
• Artificial Intelligence (AI) = Machine Intelligence
• Machine Learning (ML) is a computational method
that allow machines to act or think without being
explicitly directed to perform specific functions.
• Deep Learning (DL) is a branch of ML that uses
neural network models to understand large amounts
of data

• “A reprogrammable, multifunctional manipulator designed to move
material, parts, tools, or specialized devices through various
programmed motions for the performance of a variety of tasks”
- Robot Institute of America, 1979
• “An Intelligent robot is a mechanical creature which can function
autonomously”
What is Robot?

• The word robot was first used in 1921 by Czech playwright Karel
Capek in his satirical drama titled Rossum’s Universal Robots
- Derived from Czech word robota which literally means ‘forced labor’
• The term robotics was coined by American author and professor of
biochemistry at Boston University, Isaac Asimov in his short story
titled Runaround.
Historical Perspective

• Manipulator
• Series of rigid members, called links, connected by joints
• Actuators
• Provide power to the manipulator
• Sensory Devices
• To monitor position, speed, acceleration, torque etc.
• Controller
• Provides the intelligence to make the manipulator perform in a certain manner
• Power Conversion Unit
• Takes signal form controller and converts it into meaningful power level so the
actuators can move
Basic Components of a robot system

• Used to do repetitive (boring) actions or jobs
• Perform a variety of tasks
• Improve in quality
• Increase in production
• Perform dangerous tasks that humans can’t do
• Robots do not get sick, they can work 24/7 without complaining
Advantages

• Expense
• No guarantee
• Expertise: training on to use robots takes time
• safety
Disadvantages

Types of Robots
INDUSTRIAL ROBOTS EDUCATIONAL ROBOTS MEDICAL ROBOTS
HOUSEHOLD ROBOTS AND
HELPER ROBOTS
Used for repetitive tasks and
inspection of pipes or sites not
easily accessible to humans
Used for teaching and
training
Carry out household tasks and assist
aged and infirm people
Doctors use robotic surgical arm in
precision surgery, telemedicince, et.

Types of Robots
MILITARY ROBOTS SCIENTIFIC OR RESEARCH ROBOTS
Used in war zones to support troops
Used in chemically contaminated areas,
outer space, etc.
Robots used for
clean-up operation
at Fukushima
Nuclear Reactor Fukushima
JAPAN
Robots used for surveillance as DRONES
Drones used to locate
Osama Bin Laden

ASIMO : Advanced Step in Innovation Mobility

BigDog : Advanced Rough-Terrain Robot

WildCat : The Fastest Quadruped Robot

Hybrid Assistive Limb (HAL): Powered Exoskeleton

Robots
• Sewbo robot
• Kengoro robot
• Henn-na Hotel
• Spot, a four-legged robotic dog
• MIT’s Running, Jumping Cheetah
• RoboHon
• Sphero BB-8 RC Toy
• Sword-Swinging, Slicing Robot Arm
• Geminoid F
• Origami Robot

The top 10 IoT application areas – based on real IoT projects

Amazon Echo Family
Echo Look - $199.99
Hands-Free Camera and Style Assistant, available
by invitation only. Love your look. Every day.
Echo Show - $199.99
Everything you love about Alexa and now she can
show you things.
Echo Dot - $49.99
Add Alexa to any room in the house. Can connect to your
speakers over Bluetooth or 3.5 mm stereo cable.
Amazon Echo - $179.99
Hands-free speaker that fills any room with immersive
360⁰ audio.

AI & THE FUTURE OF WORK
WORK & LIFE IN THE AGE OF ROBOTS
Original from TEDx Manchester: AI & The Future of Work (2017), Volker Hirsch

How likely is it AI
will steal your job?

THE MACHINES
ARE COMING

FACTORY WORKER
Tesla factory, Fremont, CaliforniaOriginal from TEDx Manchester: AI & The Future of Work (2017), Volker Hirsch

https://www.chinatechnews.com/2016/10/13/24329-no-more-humans-foxconn-deploys-40000-robots-in-china
$5/day > Technology

http://www.prachachat.net/news_detail.php?newsid=1462349882Original from TEDx Manchester: AI & The Future of Work (2017), Volker Hirsch

https://www.brandbuffet.in.th/2017/05/thaibev-4-0-using-robot-and-automation-to-upgrade-factories/

Amazon Automated Warehouse
WAREHOUSE LOGISTICS

http://www.scmp.com/news/china/society/article/2086662/chinese-firm-cuts-costs-hiring-army-robots-sort-out-200000

Amazon Prime Air
POSTMAN

KALMAR AUTOMATED VEHICLES, PORT OF LOS ANGELES, CALIFORNIA
SHIPPING LOGISTICS

BOSTON DYNAMICS WILDCAT
POLICEMAN

KNIGHTSCOPE K5
SECURITY GUARD

GENERAL ATOMICS MQ-9 REAPER
SNIPER

HADRIAN X
BUILDER
TEDx Manchester: AI & The Future of Work (2017), Volker Hirsch

FLIRTEY DRONE
PIZZA DELIVERY GUY

PIZZA DELIVERY GUY

moley robotic
CHIEF

HADRIAN X
DRIVER

LONG-HAUL TRUCKING

MUSICIAN

Magnum Autonomous Tractor
FARMER

ROBEAR
Care Taker

4 jobs that will never be phased out by technology
HR managers
Psychologists and therapists
Government leadership positions
Morticians and funeral services

13 Things Everyone should do to catch up with
the world of AI,Big data, Cloud and IoT

13 สิ่งที่คนนอกสาย IT ควรเริ่มทา เพื่อตามโลกของ
AI, Big Data, Cloud และ IoT ให้ทัน
1. ยอมรับให้ได้ก่อนว่าการทางานในอนาคตจะเปลี่ยนไปอย่างสิ้นเชิง
2. เรียนรู้ภาษาต่างประเทศให้ดี
3. เริ่มศึกษาเทคโนโลยีที่ใช้ในการทางานให้มากขึ้น
4. เริ่มศึกษาเทคโนโลยีที่เกี่ยวข้องกับอุตสาหกรรมที่ธุรกิจของตนทาอยู่ให้มากขึ้น
5. หัดทาการวิเคราะห์ข้อมูลบ้าง
6. ทาความเข้าใจกับการเขียนโปรแกรมเบื้องต้น
7. หัดรักษาความปลอดภัยของอุปกรณ์ IT ที่ตนเองใช้งานอยู่ให้เป็น
https://www.techtalkthai.com/12-things-everyone-should-do-to-catch-up-with-the-world-of-ai-big-data-cloud-and-iot/

13 สิ่งที่คนนอกสาย IT ควรเริ่มทา เพื่อตามโลกของ
AI, Big Data, Cloud และ IoT ให้ทัน
7. ดูแนวโน้มว่าในอุตสาหกรรมหรืองานที่ทาอยู่นั้น AI จะเข้ามามีบทบาทอย่างไร
8. ดูแนวโน้มว่าในอุตสาหกรรมหรืองานที่ทาอยู่นั้น IoT จะเข้ามามีบทบาทอย่างไร
9. ดูแนวโน้มว่าในอุตสาหกรรมหรืองานที่ทาอยู่นั้น หุ่นยนต์จะเข้ามามีบทบาทอย่างไร
10. ค้นหาว่าปัจจุบันมีบริการ Cloud อะไรที่เกี่ยวข้องกับงานที่ตนทาบ้าง และทดลองใช้งานดู
11. ออกไปพูดคุยกับผู้คนสาย IT และธุรกิจรอบตัวให้มากขึ้น
12. วางแผนชีวิตตัวเองและองค์กรที่ทางานอยู่ เตรียมตัวเองและพนักงานในองค์กรให้พร้อม
https://www.techtalkthai.com/12-things-everyone-should-do-to-catch-up-with-the-world-of-ai-big-data-cloud-and-iot/

Resource
• http://web.stanford.edu/class/cs221/
• https://classroom.udacity.com/courses/cs271
• https://www.edx.org/course/artificial-intelligence-ai-columbiax-
csmm-101x-0#!
• https://snips.ai/content/intro-to-ai/#deep-learning
• http://www.cs.princeton.edu/courses/archive/fall01/cs302/schedule.
html

THANK YOU
Sathittham Sangthong (Phoo)
Business – sathitts@scg.com
Personal – s.sathittham@gmail.com
Blog - https://medium.com/sathittham
Line ID – scuta

Introduction to AI

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