evolution of modeling from ignorance to knowing ali ishaq march 22 nd, 2007

Evolution of ModelingFrom Ignorance to Knowing

Ali IshaqMarch 22nd, 2007

2Copyright © 2007 Deloitte Development LLC. All rights reserved.

History of Modeling from Antiquity to the Present

Three Condensed Versions:

1. A Progression Towards Mathematical Sophistication

2. A Progression Towards Non-Linearity

3. A Progression Towards Complexity


A Progression Towards Increasing Mathematical Sophistication

• The capricious gods

• The beginnings of rationality and order

• Greek mathematics and the rigorous world

• 17th Century: Pascal and Fermat

• 18th Century: Bernoulli and the beginnings of statistics

• 19th Century : Keynes and collective human behavior

• 20th Century : Game Theory, and stochastic models


A Progression Towards Non-Linearity

• Linear models – everything in its right place

• Linear thinking has its limitations

• Non-Linear Models – everything is connected

• Who moved my cheese?

• Multivariate non-parametric models to the rescue


A Progression Towards Complexity

• Rudimentary models with no common framework

• Simple Mathematics: a common framework and quantifies reality

• Complex Mathematical allows more robust models of real world phenomena

• Growing complexity, cybernetics, and hierarchical models

• Neural Networks, Connection Machines, Cellular Automata, and Genetic Algorithms

• Patterns within patterns – Chaos Theory


A Progression Towards Complexity

• My head is bursting: expert systems and automatic rule generation

• Are there shape-shifting computers with a non-linear soul in your future?

• Complexity and the limits of computation


The Logarithmic Growth In Computation Speed

Source: Ray Kurzweil – Age of Spiritual Machines


Speed of Change is Accelerating

Paradigm shifts parallel the growth in compuatation

Source: Ray Kurzweil – Age of Spiritual Machines


The End is Near


Looking to the Future

• The struggle between ‘explain-ability’ and better models

• Expert systems + statistical models = A better brain in the box

• Some sign-posts to a better future

• Future is self organizing, goal seeking, and adaptive

• Solutions less linear

• Solution elements are highly interdependent

• Solution uses the shape of the problem

• Solution evolves with observation



• Genetic algorithms: evolving and adaptive

• The Hive Mind : A democracy of models

• Silicon + Carbon : You will be assimilated:



• Human beings as parts of a bigger mind (The Matrix)


The End

• "Everything should be made as simple as possible, but no simpler."- Albert Einstein


Bibliography and Acknowledgements(or Everything I know About Modeling I Learnt From The Movies)

• Peter L. Bernstein - Against The Gods

• W. Daniel Hillis - The Connection Machine, Massachusetts Institute of Technology, September, 1981.

• Nigel Snoad and Terry Bossomaier - MONSTER - the Ghost in the Connection Machine: Modularity Of Neural Systems in Theoretical Evolutionary Research

• Anita M. Flynn and John G. Harris - Recognition Algorithms for the Connection Machine, MIT Artificial Intelligence Laboratory

Thanks to my colleagues Ray Stukel, Christina Sung, and Jim Guszcza for corrections, encouragement, and friendship.

evolution of modeling from ignorance to knowing ali ishaq march 22 nd, 2007

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