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Artificial Intelligence Basics March 2017 Frederic Molina Consultant, Technical Integration Platform Integration

Artificial Intelligence Basics, Emergent properties where the magic happens !

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Page 1: Artificial Intelligence Basics, Emergent properties where the magic happens !

Artificial Intelligence Basics

March 2017Frederic MolinaConsultant, Technical IntegrationPlatform Integration

Page 2: Artificial Intelligence Basics, Emergent properties where the magic happens !

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Agenda• Biologyinspireddesign

• Braitenberg vehicleexample• Emergentproperties• MultiAgentSystems

• Machinelearningtype• Asample:LinearRegressionModel

• CurrentAwesomeApplications

• What’snext?

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ARTIFICIAL INTELLIGENCE BASICS

• Braitenberg vehicleexample

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ARTIFICIAL INTELLIGENCE BASICS

• Braitenberg vehicleexample

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ARTIFICIAL INTELLIGENCE BASICS

• Emergentproperties

L R

L R

2assignments- IfLeftSensorisactivatedbyanobstacleReduceRightmotor speed- IfRightSensorisactivatedbyanobstacleReduceLeftmotorspeed

Nocollision!WithoutembeddinglocalGPSandbeingawareofotherGPScoordinates

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ARTIFICIAL INTELLIGENCE BASICS

• Emergentproperties

L R

L R

2assignments- IfLeftSensorisactivatedbyanobstacleReduceRightmotor speed, swingfromanangle

- IfRightSensorisactivatedbyanobstacleReduceLeftmotorspeed, swingfromanangle

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ARTIFICIAL INTELLIGENCE BASICS

• Emergentproperties2assignments- IfLeftSensorisactivatedbyanobstacleReduceRightmotor speed, swingfromanangle

- IfRightSensorisactivatedbyanobstacleReduceLeftmotorspeed, swingfromanangle

Emergentproperties:Itemsarealigned!

L R

L R

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Video : vehicles

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Itemsaregrouped !Itemsareseparated Vehiclesmovewithonly1rule“turnwhenyou“see”something”

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ARTIFICIAL INTELLIGENCE BASICS

• MultiAgentSystems

Groundshaping

Watersourcing

Airqualitycontrol

Emergentproperties:possibleforhumantosettle!

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ARTIFICIAL INTELLIGENCE BASICS

• Machinelearningtype

Unsupervised Supervised

• Trainusing theexpectedresults• Should beabletogeneralize=newdatawillbeclassified

•Theexpectedresultarenotknown inadvance

•ModelCluster/Group theinput inclasses

Split:test&controlgroups

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ARTIFICIAL INTELLIGENCE BASICS

Machine learning : Neural Network and reinforcement learning

Lessthan20codeline

Reinforcementlearning increment

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ARTIFICIAL INTELLIGENCE BASICS

Machine learning : Neural Network and reinforcement learning

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ARTIFICIAL INTELLIGENCE BASICS

Machine learning : Neural Network and reinforcement learning PictureGreyscaleEachColorisaNeuronEachtimeapixelhasthecolortheneuronvalueincrement+1

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Machine learning : Neural Network and reinforcement learning PictureGreyscaleSobel HorizontalBlurHough=>straightLinedetectionTheneuron isthe“HorizontalLine”

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ARTIFICIAL INTELLIGENCE BASICS

Machine learning : Neural Network and reinforcement learning PictureGreyscaleSobel HorizontalBlurHough=>straightLinedetectionTheneuron isthe“HorizontalLine”

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ARTIFICIAL INTELLIGENCE BASICS

Simple Neural Network Text

Drawing

Photo

Std dev.histogrm

Horiz.Lines(Hough)

Grey

Hough

Sobel

Histogram

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ARTIFICIAL INTELLIGENCE BASICS

Simple Neural Network

Text

Drawing

Photo

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ARTIFICIAL INTELLIGENCE BASICS

Simple Neural Network

Text

Drawing

Photo

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ARTIFICIAL INTELLIGENCE BASICS

Simple Neural Network Text

Drawing

Photo

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Simple Neural Network: this is a drawing

Text

Drawing

Photo

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ARTIFICIAL INTELLIGENCE BASICS

Simple Neural Network : FALSE this is a drawing

Text

Drawing

Photo

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ARTIFICIAL INTELLIGENCE BASICS

• Asample:LinearRegressionModel

QuitegoodoutputNotidealoutput

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ARTIFICIAL INTELLIGENCE BASICS

CurrentAwesomeApplications

• Imagerecognition:Cancerdetection(here )• NLP:personalassistant,Chatbots ,Pilotearphonetranslator(here )• CybersecurityandSecurityrobots(here )• Robotics:Factory,humanhelp(here &here &here )• Robotics:Autonomoustransportation(here &here )• Finance:Forecasting• Military:Drones,Robots,NLPLanguagerecognition

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ARTIFICIAL INTELLIGENCE BASICS

Prospective perspective• Biologyinspireddesign:tobecomethecreator?

• Braitenberg vehicleexample• Emergentproperties:here’sthemagiccouldhappens?• MultiAgentSystems:PerfectCollaborationandCollectiveIntelligence?

• TheoryMachinelearning:superv,unsuperv.• Practiceexample:LinearRegressionModel

• CurrentAwesomeApplications

• What’snext?• Currentperf silotoperformance• ArtificialvsEmotionalIntelligence

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Questions?

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ARTIFICIAL INTELLIGENCE BASICS

Bonus• Recommendedmovies

Her2013