artificial intelligence basics, emergent properties where the magic happens !
TRANSCRIPT
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Artificial Intelligence Basics
March 2017Frederic MolinaConsultant, Technical IntegrationPlatform Integration
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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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ARTIFICIAL INTELLIGENCE BASICS
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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ARTIFICIAL INTELLIGENCE BASICS
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