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Artificial Intelligence Brittany Coffer Artificial Intelligence Brittany Coffer

Artificial Intelligence Brittany Coffer - PowerPoint Presentation

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Uploaded On 2018-09-17

Artificial Intelligence Brittany Coffer - PPT Presentation

Nick Deheck Chelsey Eglseder Joshua Lewis David Summey What is Artificial Intelligence  Simulation of human intelligence Alexa Watson Machines learn from experience Netflix Ability to adjust to new inputs and perform humanlike tasks ID: 667967

www intelligence https artificial intelligence www artificial https industry http 2017 human cancer data machine limitations law learning healthcare

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Slide1

Artificial Intelligence

Brittany Coffer

Nick

Deheck

Chelsey

Eglseder

Joshua Lewis

David SummeySlide2

What is Artificial Intelligence? 

Simulation of human intelligence

"Alexa"; "Watson

"Machines learn from experienceNetflixAbility to adjust to new inputs and perform human-like tasksDriver-less carsAllows machines to learn without explicit directionsAutomates data modelingUberSlide3

Why Do We Need AI? 

Unlimited applications

Usefulness in any industry

Potential to remove human error Problem Solving Adds intelligence to existing products Automates repetitive learning and discovery through data Achieves high accuracy through deep neural networks Gets the most out of dataUnbiased Data ResultsEliminates impromptu data manipulationSlide4

Limitations & Challenges  

"Narrow AI"

Designed to perform a defined task

Limited to specific industriesTechnology unlimitedCould fall into "wrong hands"Currently no overarching laws/regulationsAI could be programmed to do something beneficial, but...Arrives at a devastating conclusion"Who do I hit?" scenario

Rapidly escalating international competition over AI

Wars of future will use algorithms like ammunitionSlide5

Healthcare Industry 

Ability to detect colorectal cancer early with 86% accuracy 

Significant as colorectal cancer is the second deadliest form of cancer, behind lung cancer.

Ability to detect brain bleeds and tuberculosis 

Behavior-based security system  

Clinical documentation 

Smart Tissue Autonomous Robot (STAR) 

Benefits 

Potentially save lives 

Increase security 

Better patient experience 

Limitations

Behavior changes 

Difficulty in normalizing data sets Slide6

Rail Industry

Positive Train Control

Reduce human-factor incidents

GE Smart LocomotivesIncrease efficiency and velocityPredictive Signal SystemsDetect problem in signals before accidents occurFacial RecognitionCommuter rail Merchandise railTrain Delay ReportingIncrease on-time performance LimitationsNot shared

Exploration phaseSlide7

Defense Industry

Aircraft Intelligence

F-35 is example of human-machine collaboration

Automated Recovery/EgressALIS (Autonomic Logistics Information System)Machine LearningIdentify correct targets—reduces risksSolve logistics challengesSpeeds weapon developmentSoftware ProcessingAnalyzes large data quickly

Immersive training 

Support war games and generate countless scenarios 

Data Mining

SAP HANASlide8

Defense Industry Cont.

Challenges/Limitations of AI

Testing

Relatively new technologiesLifecycle maintenanceAI alone with not solve all concernsCollaboration of human-system neededOperator still neededDecision making Unknown gapsCyber security Trust factorSlide9

Law Enforcement Industry

Investigation Support

Capable identifying: Key Words in Speech, Facial and Object Features

Provides more thorough search, enables investigators to "multi-task"

Limitations

Identifies only what it has been "shown"

Learning phase is slow, many objects are very similar

Identification across accents (language), angles (photos), and video clarity

Overcome

Dedicated work by users to detail searches and expand database

Exposure is keySlide10

Sources

http://www.healthcareitnews.com/slideshow/how-ai-transforming-healthcare-and-solving-problems-2017?page=1

http://www.healthcareitnews.com/news/aetna-replacing-security-passwords-machine-learning-tools

http://fortune.com/2017/10/30/ai-early-cancer-detection/https://www.inverse.com/article/37873-artificial-intelligence-colorectal-cancer-detectionhttps://www.fbi.gov/news/testimony/law-enforcements-use-of-facial-recognition-technologyhttp://www.policemag.com/channel/technology/articles/2017/10/artificial-intelligence-and-law-enforcement.aspx

https://www.nanalyze.com/2017/11/8-companies-ai-law-enforcement/

http://searchcio.techtarget.com/definition/AI

https://en.wikipedia.org/wiki/SAP_HANA

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ttps://www.rand.org/blog/2017/09/artificial-intelligence-and-the-military.html

http://www.information-age.com/trains-brains-how-artificial-intelligence-transforming-railway-industry-123460379/

https://economictimes.indiatimes.com/industry/transportation/railways/railways-to-use-artificial-intelligence-for-preventing-signal-failures/articleshow/61737103.cms

https://aibusiness.com/ai-revamp-rail-industry-facial-recognition-technology/

http://railwayinnovation.com/tag/artificial-intelligence/

http://www.amadeus.com/blog/16/02/technology-trends-railways/

https://magazine.startus.cc/disrupting-rail-industry-breakdown-startup-driven-innovation/

https://venturebeat.com/2017/10/09/ge-using-ai-to-build-locomotives-that-think/

https://blog.willis.com/2017/05/the-impact-of-artificial-intelligence-in-transportation/

https://www.sas.com/en_us/insights/analytics/what-is-artificial-intelligence.html

https://www.topbots.com/healthcare-ai-opportunities-challenges-policy-workflow/

http://www.gnshealthcare.com/5-challenges-applying-ai-machine-learning-healthcare/

https://hcss.nl/sites/default/files/files/reports/Artificial%20Intelligence%20and%20the%20Future%20of%20Defense.pdf