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Artificial Intelligence In the Real World

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Title: Artificial Intelligence In the Real World

1
Artificial IntelligenceIn the Real World
Computing Science University of Aberdeen
2
Artificial IntelligenceIn the Real World
Artificial IntelligenceIn the Movies
3
Artificial IntelligenceIn the Real World
Artificial IntelligenceIn the Movies
4
Artificial IntelligenceIn the Real World
Artificial IntelligenceIn the Movies
?
5
Artificial Intelligence Began in 1956

Great expectations

Machines will be capable, within twenty years,
of doing any work that a man can do. Herbert
Simon, 1965.
6
Machines will be capable, within twenty years,
of doing any work that a man can do. Herbert
Simon, 1965.
What Happened?
7
Machines will be capable, within twenty years,
of doing any work that a man can do. Herbert
Simon, 1965.
What Happened?

Machines cant do everything a man can do
People thought machines could replace
humansinstead they are usually supporting humans

8
Machines will be capable, within twenty years,
of doing any work that a man can do. Herbert
Simon, 1965.
What Happened?

Machines cant do everything a man can do
People thought machines could replace
humansinstead they are usually supporting
humans
Healthcare, Science, Government, Business,
Military

9
Machines will be capable, within twenty years,
of doing any work that a man can do. Herbert
Simon, 1965.
What Happened?

Machines cant do everything a man can do
People thought machines could replace
humansinstead they are usually supporting
humans
Healthcare, Science, Government, Business,
Military
Most difficult problems are solved by
humanmachine
astronomy, nuclear physics, genetics, maths, drug
discovery

10
Neural Networks

Neural Networks are a popular Artificial
Intelligence technique
Used in many applications which help humans
The idea comes from trying to copy the human
brain

11
Fascinating Brain Facts

100,000,000,000 1011 neurons -100 000 are
irretrievably lost each day!
Each neuron connects to 10,000 -150,000 others
Every person on planet make 200 000 phone calls
same number of connections as in a single human
brain in a day
Grey part folded to fit - would cover surface of
office desk
The gray cells occupy only 5 of our brains
95 is taken up by the communication network
between them
About 2x106km of wiring (to the moon and back
twice)
Pulses travel at more than 400 km/h (250 mph)
2 of body weight but consumes 20 of oxygen
All the time! Even when sleeping
What about copying neurons in Computers?

Artificial Neural Network (ANN)
loosely based on biological neuron
Each unit is simple, but many connected in a
complex network
If enough inputs are received
Neuron gets excited
Passes on a signal, or fires
ANN different to biological
ANN outputs a single value
Biological neuron sends out a complex series of
spikes
Biological neurons not fully understood

Image from Purves et al., Life The Science of
Biology, 4th Edition, by Sinauer Associates and
WH Freeman
13

Now play with the flash animation to see how
synapses work

http//www.mind.ilstu.edu/curriculum/neurons_intro
/flash_summary.php?modGUI232compGUI1828itemGUI
3160
14
The Perceptron
input1
weight1
input2
weight2
add
output
weight3
(threshold)
weight4
input3
input4
15
The Perceptron
input1
weight1
input2
weight2
add
output
weight3
(threshold)
weight4
input3
Save Graph and Data
input4
16
The Perceptron
student first last year male works hard Lives in halls First this year
1 Richard 1 1 0 1 0
2 Alan 1 1 1 0 1
3 Alison 0 0 1 0 0
4 Jeff 0 1 0 1 0
5 Gail 1 0 1 1 1
6 Simon 0 1 1 1 0
Save Graph and Data
Note example from Alison Cawsey
17
The Perceptron
First last year _
0.2
add
_ output
Male _
0.2
Threshold 0.5
0.2
0.2
_ hardworking
_ Lives in halls
student First last year male works hard Lives in halls First this year
1 Richard 1 1 0 1 0
Note example from Alison Cawsey
18
The Perceptron
First last year _
0.15
add
_ output
0.15
Male _
Threshold 0.5
0.2
0.15
_ hardworking
_ Lives in halls
student First last year male works hard Lives in halls First this year
1 Richard 1 1 0 1 0
Note example from Alison Cawsey
19
The Perceptron
First last year _
0.15
add
_ output
0.15
Male _
Threshold 0.5
0.2
0.15
_ hardworking
_ Lives in halls
student First last year male works hard Lives in halls First this year
2 Alan 1 1 1 0 1
Note example from Alison Cawsey
20
The Perceptron
First last year _
0.2
add
_ output
Male _
0.2
0.25
Threshold 0.5
0.15
_ hardworking
_ Lives in halls
student First last year male works hard Lives in halls First this year
2 Alan 1 1 1 0 1
Note example from Alison Cawsey
21
The Perceptron
First last year _
0.2
add
_ output
Male _
0.2
0.25
Threshold 0.5
0.15
_ hardworking
_ Lives in halls
student First last year male works hard Lives in halls First this year
3 Alison 0 0 1 0 0
Note example from Alison Cawsey
22
The Perceptron
First last year _
0.2
add
_ output
Male _
0.2
0.25
Threshold 0.5
0.15
_ hardworking
_ Lives in halls
student First last year male works hard Lives in halls First this year
4 Jeff 0 1 0 1 0
Note example from Alison Cawsey
23
The Perceptron
First last year _
0.2
add
_ output
Male _
0.2
0.25
Threshold 0.5
0.15
_ hardworking
_ Lives in halls
student First last year male works hard Lives in halls First this year
5 Gail 1 0 1 1 1
Note example from Alison Cawsey
24
The Perceptron
First last year _
0.2
add
_ output
Male _
0.2
0.25
Threshold 0.5
0.15
_ hardworking
_ Lives in halls
student First last year male works hard Lives in halls First this year
6 Simon 0 1 1 1 0
Note example from Alison Cawsey
25
The Perceptron
First last year _
0.2
add
_ output
0.15
Male _
0.20
Threshold 0.5
0.10
_ hardworking
_ Lives in halls
student First last year male works hard Lives in halls First this year
6 Simon 0 1 1 1 0
Note example from Alison Cawsey
26
The Perceptron
First last year _
0.2
add
_ output
0.15
Male _
0.20
Threshold 0.5
0.10
_ hardworking
_ Lives in halls
student First last year male works hard Lives in halls First this year
1 Richard 1 1 0 1 0
Note example from Alison Cawsey
27
The Perceptron
First last year _
0.2
add
_ output
0.15
Male _
0.20
Threshold 0.5
0.10
_ hardworking
_ Lives in halls
student First last year male works hard Lives in halls First this year
2 Alan 1 1 1 0 1
Note example from Alison Cawsey
28
The Perceptron
First last year _
0.2
add
_ output
0.15
Male _
0.20
Threshold 0.5
0.10
_ hardworking
_ Lives in halls
student First last year male works hard Lives in halls First this year
3 Alison 0 0 1 0 0
Note example from Alison Cawsey
29
The Perceptron
First last year _
0.2
add
_ output
0.15
Male _
0.20
Threshold 0.5
0.10
_ hardworking
_ Lives in halls
student First last year male works hard Lives in halls First this year
4 Jeff 0 1 0 1 0
Note example from Alison Cawsey
30
The Perceptron
First last year _
0.2
add
_ output
0.15
Male _
0.20
Threshold 0.5
0.10
_ hardworking
_ Lives in halls
student First last year male works hard Lives in halls First this year
5 Gail 1 0 1 1 1
Note example from Alison Cawsey
31
The Perceptron
First last year _
0.25
add
_ output
0.15
Male _
0.25
Threshold 0.5
0.15
_ hardworking
_ Lives in halls
student First last year male works hard Lives in halls First this year
5 Gail 1 0 1 1 1
Note example from Alison Cawsey
32
The Perceptron
First last year _
0.25
add
_ output
0.15
Male _
0.25
Threshold 0.5
0.15
_ hardworking
_ Lives in halls
student First last year male works hard Lives in halls First this year
6 Simon 0 1 1 1 0
Note example from Alison Cawsey
33
The Perceptron
First last year _
0.25
add
_ output
0.10
Male _
0.20
Threshold 0.5
0.10
_ hardworking
_ Lives in halls
student First last year male works hard Lives in halls First this year
6 Simon 0 1 1 1 0
Note example from Alison Cawsey
34
The Perceptron
First last year _
0.25
add
_ output
0.10
Male _
0.20
Threshold 0.5
0.10
_ hardworking
_ Lives in halls

Finished

Note example from Alison Cawsey
35
The Perceptron
First last year _
0.25
add
_ output
0.10
Male _
0.20
Threshold 0.5
0.10
_ hardworking
_ Lives in halls

Finished
Ready to try unseen examples

Note example from Alison Cawsey
36
The Perceptron
First last year _
0.25
add
_ output
0.10
Male _
0.20
Threshold 0.5
0.10
_ hardworking
_ Lives in halls
student First last year male works hard Lives in halls First this year
James 0 1 0 1 ?
Note example from Alison Cawsey
37
The Perceptron
0.25
_ output
0.10
add
0.20
Threshold 0.5
0.10

Simple perceptron works ok for this example but
sometimes will never find weights that fit
everything
In our example
Important Getting a first last year, Being
hardworking
Not so important Male, Living in halls
Suppose there was an exclusive or -
Important (male) OR (live in halls), but not
both
Cant capture this relationship

38
Stock Exchange Example
Company Name Company less than 2 years old Paid dividend gt10 last year Share price increases in following year
1 Robot Components Ltd. 1 1 0
2 Silicon Devices 1 0 1
3 Bleeding Edge Software 0 0 0
4 Human Interfaces Inc. 1 1 0
5 Data Management Inc. 0 1 1
6 Intelligent Systems 1 1 0
39
Multilayer Networks

We saw perceptron cant capture relationships
among inputs
Multilayer networks can capture complicated
relationships

40
Stock Exchange Example
Hidden Layer
41
Neural Net example ALVINN

Autonomous vehicle controlled by Artificial
Neural Network
Drives up to 70mph on public highways

Note most images are from the online slides for
Tom Mitchells book Machine Learning
42
Neural Net example ALVINN

Autonomous vehicle controlled by Artificial
Neural Network
Drives up to 70mph on public highways

Note most images are from the online slides for
Tom Mitchells book Machine Learning

43
ALVINN
Sharp right
Straight ahead
Sharp left
30 output units
4 hidden units
1 input pixel
Input is 30x32 pixels 960 values
44
ALVINN
Sharp right
Straight ahead
Sharp left
30 output units
4 hidden units
Learning means adjusting weight values
1 input pixel
Input is 30x32 pixels 960 values
45
ALVINN
Sharp right
Straight ahead
Sharp left
30 output units
4 hidden units
1 input pixel
Input is 30x32 pixels 960 values
46
ALVINN
47
ALVINN