presentation about the sp theory

Introducing the SP Theory

An Intelligent machine

Results

Smart Machines and the SP Theory of Intelligence

Maverick Chardet

cole Normale Suprieure de Lyon

Colloquium ENS Lyon, 2015

Maverick Chardet SP Theory of Intelligence

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Outline

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Background and Objectives

Computing by Compression

2

Unsupervised Learning

Computing in a Dierent Way

3

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What Is Done

What Is Yet To Be Done

Potential applications

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Outline

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What Is Done

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Simplicity and Power

The objectives of every scientic theory.

Power rst...

And for equivalent power, simplicity.

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Power rst...

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Power rst...

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A New Theory of Computing

Turing-equivalent, but more addapted to today's challenges:

Articial intelligence.

Big data.

Energy eciency.

ICMAUS: information-compression-by-multiple-alignment-

unication-and-search

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Big data.

Energy eciency.

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Big data.

Energy eciency.

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Big data.

Energy eciency.

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The Objective

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Outline

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What Is Done

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Lossless Compression

Denition

Lossless data compression is a class of data compression algorithms

that allows the original data to be perfectly reconstructed from the

compressed data.

(source: Wikipedia, 05/2015)

Example

By using short codes for long patterns: cole Normale Suprieure

de Lyon -> ENSL.

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Lossless Compression

Denition

Lossless data compression is a class of data compression algorithms

that allows the original data to be perfectly reconstructed from the

compressed data.

(source: Wikipedia, 05/2015)

Example

By using short codes for long patterns: cole Normale Suprieure

de Lyon -> ENSL.

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Compression Is the Key

Facilitating the storage and management of data.

Economies in the transmission of big data.

Can be used as a way of computing and reasoning, in a more

ecient way in the use of energy.

Used to manage errors and uncertainty in data.

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Inspired by the Human Brain

The memory and the neural structure of the brain is modelled

by old and compressed data.

The information that comes to the brain via our senses is

modelled by new and uncompressed data.

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Inspired by the Human Brain

The memory and the neural structure of the brain is modelled

by old and compressed data.

The information that comes to the brain via our senses is

modelled by new and uncompressed data.

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Outline

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What Is Done

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Smart Machines?

Quote

While traditional computers must be programmed by humans to

perform specic tasks, cognitive systems will learn from their

interactions with data and humans and be able to, in a sense,

program themselves to perform new tasks.

J. E. Kelly and S. Hamm, Smart machines: IBM's Watson and the

era of cognitive computing, p7.

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From Pattern Matching...

Discovering generative grammars from data.

Parsing data using a grammar.

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From Pattern Matching...

Discovering generative grammars from data.

Parsing data using a grammar.

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...To Multiple Alignment

Similar to the Multiple Alignment concept in Bioinformatics

(with some modications).

Good alignement: when there are a lot of hits (positive

matches between symbols) and few and short gaps.

More exible, allows to parse incomplete information for

instance.

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instance.

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instance.

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SP Version of Multiple Alignment

Two categories of patterns to be aligned: new information and

old information.

Good alignement: leads to a large amount of compression of

new patterns in terms of old patterns.

An old pattern may appear several times.

No mismatches between old patterns.

In the future: generalisation in 2D.

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old information.

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old information.

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old information.

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old information.

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Example of Multiple Alignment

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Outline

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What Is Done

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Astounding Figures

Human brain:

20 billion neurons.

20 watts of energy.

The size of a grapefruit.

A conventional computer with comparable cognitive capacity:

A gigawatt of electricity.

The size of a football eld.

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Astounding Figures

Human brain:

20 billion neurons.

20 watts of energy.

The size of a grapefruit.

A conventional computer with comparable cognitive capacity:

A gigawatt of electricity.

The size of a football eld.

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Optimising Processing

In the SP machine: processing = compression of information

using matching and unication.

Optimising compression leads to better processing and faster

search.

The SP computer uses its dierent levels of compression,

along with heuristics, as a guide to search.

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search.

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search.

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Data-Centric Computing

To take inspiration from the human brain, the processing and

the memory should be more closely integrated.

Storing data is the same as computing for an SP machine.

To implement this system, two possible solutions are being

considered:

Computing with light.

Computing with DNA.

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considered:

Computing with DNA.

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considered:

Computing with DNA.

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considered:

Computing with DNA.

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considered:

Computing with DNA.

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What Is Done

Outline

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What Is Done

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What Is Done

Done

A lot of problems have been overcome during the rst

implementations.

The 1D multiple alignment framework is working.

A working and stable version has been published (SP70).

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What Is Done

Done

implementations.

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What Is Done

Done

implementations.

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What Is Done

Outline

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What Is Done

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What Is Done

To Be Done

Improving the global framework.

Mathematics.

Graphical User Interface.

Developping an SP machine.

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What Is Done

To Be Done

Mathematics.

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What Is Done

To Be Done

Mathematics.

...

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What Is Done

To Be Done

Mathematics.

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What Is Done

To Be Done

Mathematics.

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What Is Done

Outline

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What Is Done

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What Is Done

Potential Applications

Automatic learning of natural language grammars.

Medical diagnosis.

Processing streams of data.

Representation and processing of graphical or audio

information.

Achieving human-like exibility and adaptability in robots.

The semantic web.

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What Is Done

Medical diagnosis.

information.

The semantic web.

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What Is Done

Medical diagnosis.

information.

The semantic web.

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What Is Done

Medical diagnosis.

information.

The semantic web.

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What Is Done

Medical diagnosis.

information.

The semantic web.

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What Is Done

Medical diagnosis.

information.

The semantic web.

Appendix

For Further Reading

J. Gerard Wol.

Unifying Computing and Cognition.

CognitionResearch.org.uk, 2006.

J. E. Kelly and S. Hamm.

Smart Machines: IBM's Watson and the Era of Cognitive

Computing.

Columbia University Press, 2013.

J. Gerard Wol.

Smart Machines and the SP Theory of Intelligence.

arXiv. 1401.1669v1 [cs.AI], 2014.

J. Gerard Wol.

The SP Theory of Intelligence and the SP Machine, In Brief.

2015.

Appendix

To Be Done (Honest Version)

Generalisation of the multiple alignment framework in 2D.

Create a more user-friendly system for using variables and

types.

Improving the framework for unsupervised learning:

Example: No capability for learning recursive structures or

exploiting symmetries.

Take account of the eect of recency in learning.

Verifying the coherence of entities in time and space.

Mathematics.

Appendix

Example of Multiple Alignment (Readable Version) - 1

Appendix

Example of Multiple Alignment (Readable Version) - 2

Introducing the SP TheoryBackground and ObjectivesComputing by Compression

An ``Intelligent'' machineUnsupervised LearningComputing in a Different Way

ResultsWhat Is DoneWhat Is Yet To Be DonePotential applications

Appendix

presentation about the sp theory

Documents

sp theorybackground

scientic theory

equivalent power

articial intelligence

big data

energy eciency

todays challenges

powerthe objectives