march 2016 4 - artificial intelligence lightning talk
TRANSCRIPT
March 2016
Syed Husain
Contextual Applications:
An Artificial Intelligence
Capability Perspective
3Copyright © 2016 Accenture All rights reserved.
Artificial Intelligence – Some Heuristics
Artificial Intelligence
Expert RulesNeural NetworksCase Based
Learning
A learning
system, that
uses context to
modify the
output.
Learning from
past cases.
Inductive
reasoning.
Explicit Rules
based
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The Basic Architecture of A.I.
Agent
(Memory)Environment
Sensors
Actuators
State
V
A
R
I
A
B
L
E
Observability Partially Observable Fully Observable
Randomness Stochastic Deterministic
Type of Change Continuous Discrete
Type of Environment Adversarial Benign
VALUE
The Perception Action Cycle
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An Example: Autonomous Vehicle
V
A
R
I
A
B
L
E
Observability Partially Observable Fully Observable
Randomness Stochastic / Random Deterministic
Type of Change Continuous Discrete
Type of Environment Adversarial Benign
VALUE
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Problem Selection
Integration:• Virtual Call Centre Agents.
Innovation:• Creating news articles (Quill)
• Creating Music (Iamus)
• Autonomous Vehicles (Google)
• Drug Development
Efficiency:• Automated Credit Card
Decisions.
• Food preparation.
Expert:• Financial Portfolio Building
(Deutsche Bank AG, Bank of
America etc)
• Beauty Contest Judges
• Financial Trading
Data Complexity
(Observability & Randomness)
Measured through
Kolmogorov complexity
Task Complexity
(Type of Environment & Type of Change)
Measured through Big O, VC Dimension
Unstructured, Volatile,
High Volume
Structured, Stable, Low
Volume
Low High
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Model Building & Training
Architecture
What?
- Establish Goal.
- Define Inputs.
- Define Principles & Constraints.
Solutions
How?
- Everything on the left.
- Break the problem down and solve it.
Art
ific
ial In
telli
ge
nce
Tra
ditio
na
l Pro
ble
m S
olv
ing
Declarative Functional
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Example – Image Compression using A.I.
01
11
01
11
11
10
10
11
01
01
10
Discrete
Cosine
TransformQuant
Entropy
coding
Entropy
decodingInverse
DCT
01
11
01
11
11
10
10
11
01
01
10
f(x)
Encoder
Function
g(x)
Decoder
Function
Traditional Engineering Approach
Machine Learning Approach
Reconstruction Error
9Copyright © 2016 Accenture All rights reserved.
Appendix A – Data Sources
1. Accenture research on AI adoption: https://www.accenture.com/us-en/insight-
intelligent-machines-workforce-of-the-
future.aspx?c=stg_stratsmctwt_10000104&n=smc_1015
2. Accenture paper on artificial intelligence: https://www.accenture.com/us-
en/insight-artificial-intelligence-software.aspx
3. Computer, Iamus, composed music, performed by LSO in 2012:
https://soundcloud.com/new-scientist/iamus-computer-transits-to-an