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Artificial Intelligence: Disruption by Machine part 1 of 3

  1. ARTIFICIAL INTELLIGENCE Disruption by machine based intelligence 1
  2. Intelligent Systems Covers Everything From: Chess-playing programs Siri Spam filters (AI) = Building systems that can do intelligent things 2 Any task performed by a computer that would normally require human intelligence Compiled by author from source:
  3. Paving The Growth Of The AI Market The evolution of various other supplementary technologies are paving the growth of the AI market such as: Cloud Computing Machine Learning Cognitive Computing Once considered a topic for intellectuals only With development of various technologies, AI has turned into reality and is influencing many lives and businesses 3 Compiled by author from source:
  4. Artificial Intelligence These Include: Language Translation Image Recognition Voice Recognition Machine Learning AI performs cognitive functions that mimic the way the brain works 4 Compiled by author from source: Image Source: Google Images
  5. Machine Learning A subfield of AI (ML) = Building systems that can learn from experience 5 The science of getting computers to learn and improve over time in autonomous fashion, by feeding them data and information in the form of observations and real-world interactions Most AI work now involves ML because intelligent behavior requires considerable knowledge, and learning is the easiest way to get that knowledge Compiled by author from source: Image Source: Google Images
  6. Why Is (ML) So Important? Quickly and automatically produce models that can analyze bigger, complex data Giving more accurate By building precise models, a company can better identify profitable opportunities Avoiding unknown risks Addresses: Growing volumes and varieties of data Computational processing that is cheaper and more powerful Affordable data storage 6 Compiled by author from source:
  7. Who’s Using (ML)? Financial Services Identify important insights in data, prevent fraud Health Care Identify trends that may lead to improved diagnoses and treatment Marketing Capture data, analyze, personalize Oil & Gas Streamlining distribution, making it efficient and cost-effective Transportation Making routes more efficient and predicting problems 7 Compiled by author from source: Image Source: Google Images
  8. Deep Learning (DL) = Allows the system to build complex concepts out of simpler concepts 8 Compiled by author from source: Deep learning is a subset of ML It uses some ML techniques to solve real-world problems Taps into neural networks that simulate human decision-making Deep learning can be expensive, and requires massive datasets to train itself on
  9. Deep Learning Vehicle, pedestrian and landmark identification for driver assistance Image recognition Speech recognition and translation Natural language processing Life sciences Used in research to solve many big data problems such as computer vision, speech recognition, and natural language processing Practical examples include: 9 Compiled by author from source:
  10. Natural Language Processing (NLP) = Building systems that can understand language 10 Compiled by author from source: Image Source: Google Images NLP is a component of artificial intelligence The ability of a computer program to understand human speech
  11. Natural Language Processing This will include various applications: Smartphones Navigation systems Car-infotainment systems Personal assistants Computers usually require humans to “speak” in a precise, clear-cut and highly structured programming language 11 Expected to increase at the highest rate in the next five years Compiled by author from source:
  12. AI As Core Component Predictive analytics Automated laboratories Factories Unmanned vehicles 12 Online communication Digital content Commerce AI will become a core component of: It will be used extensively in: Compiled by author from source:
  13. Areas Of Expansion Create custom learning profiles for students and enhance teaching approach Used for diffusing bombs, moving equipment in dangerous zones, and surveillance and recon missions In the future, it will be used to reduce workloads, increase patient safety, and minimize costs Education Defense Sector Medicine 13 Compiled by author from source: Image Source: Google Images
  14. Augmented Reality Used to enhance our environment 14 (AR) is a growing field, with many diverse applications ranging from: TV Film production Industrial maintenance Medicine Education Entertainment and gaming Compiled by author from source: Image Source: Google Images
  15. CONTACT US FOR THE FULL PRESENTATION: Mediacontact USA Inc. 13575 58TH Street North #160 Clearwater, Fl. 33760 T: 727 538 4112 E:
  16. Sources Cited • "Artificial Intelligence Market - Impact of $16 Billion by 2022 in Semiconductor Industry." PR Newswire: Press Release Distribution, Targeting, Monitoring and. Marketsandmarkets, 15 Feb. 2017. Web. 18 May 2017. < semiconductor-industry-613843073.html>. • "Deep Learning Market by Application (Image Recognition, Signal Recognition - 2022 | MarketsandMarkets." Market Research Reports, Marketing Research Company, Business Research by MarketsandMarkets. N.p., Nov. 2016. Web. 18 May 2017. <>. • "Deep Learning." NVIDIA Developer. N.p., 2017. Web. 23 May 2017. <>.
  17. Sources Cited • "The Marketing Impact of AI & Machine-Learning: 3 Predictions." MarketingProfs. N.p., 17 May 2017. Web. 17 May 2017. < by-51-ml-marketing-executives?adref=nlt051617>. • "Machine Learning: What It is and Why It Matters | SAS." Analytics, Business Intelligence and Data Management | SAS. N.p., n.d. Web. 23 May 2017. <>. • Schmidt, Sarah. "Artificial Intelligence Market Forecast, Plus Top Companies." Market Research Blog. N.p., 1 May 2017. Web. 17 May 2017. < companies?utm_campaign=Blog%20Subscription&utm_source=hs_email&utm_medium=email&utm_content=51366130& _hsenc=p2ANqtz-_yuNuD1RHeU0nWqBy3UfzhqXoXFLKQl8JkQ4QocAvYFzDsqOIfTis-LXtG_Z- dMlwFLZ0tjef3MeOChkKwI48yqSKvZg&_hsmi=51366130>.

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