March 2016

Syed Husain

s.husain@accenture.com

Contextual Applications:

An Artificial Intelligence

Capability Perspective

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Me

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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

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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