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Aptage future of ai webinar slides

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Our co-founder and CTO, Murray Cantor Ph.D, gave an introductory presentation on the history of Artificial Intelligence (AI). In the presentation he explains what AI means for business today.

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Aptage future of ai webinar slides

  1. 1. Welcome to AI and the Future of Analytics Webinar! Presented by Murray Cantor, Ph.D, Aptage CTO John Gonzalez, Aptage VP of Sales All participants are currently muted. Please use the Q&A feature to interact with the presenters. Questions can be e-mailed to hello@aptage.com
  2. 2. APTAGE.COM | 2 Topics • AI history and technology at 100,000 ft. • AI and the future of analytics • The economics of AI • Aptage as an example Risk Burndown
  3. 3. APTAGE.COM | 3 AI Precursors • Neural Nets • were developed in mid 20th century to model brains. • Based on experiments, MRI • Until recently , too computationally intensive to be useful • Back propagation algorithm • GPUs, the cloud • Inference Engines • Early successes (e.g. Theorem provers) • Used in expert systems • Evolution of analytics • From descriptive to prescriptive • Resurgence of Bayes Neuroscience
  4. 4. APTAGE.COM | 4 AI is the convergence of three fields Inference Engines Rules Based Bayesian, Predictive Methods Computational Neuroscience Wash U Alchemy Neuro Nets AI AI and HI understanding are predictions based on the input and innate rules. Examples • Natural language processing predict the word based on the detected sound wave. • Self-driving cares predict whether there will be an accident
  5. 5. APTAGE.COM | 5 AI is the convergence of three fields Inference Engines Rules Based Bayesian, Predictive Methods Neuro Science Alchemy Neuro Nets AIAI and Humans both predict the answer based on the inputs and innate rules and acts accordingly. Examples • natural language processing predict the word based on the detected sound wave. • Self-driving cares predict whether there will be an accident Uber has discovered the reason why one of the test cars in its fledgling self-driving car fleet struck and killed a pedestrian earlier this year … The software was tuned in such a way that it “decided” it didn’t need to take evasive action, and possibly flagged the detection as a “false positive.” The Verge, May 8, 2018, https://bit.ly/2FWTGlM
  6. 6. APTAGE.COM | 6 Kinds of AI • Narrow • Does one thing really well: • Cognition, playing games (strategy), predictions • Wide (AKA Artificial General Intelligence) • Alexa, Siri, Google Assistant, Cortana • Supposed to do what’s asked • Conscious machines • Supposed to do what you (it) need(s) • Lots of philosophical debates( • Reductionism,….
  7. 7. APTAGE.COM | 7 The state of the art Not yet very good (‘nuff said) Not impossible – no laws of physics are broken. May need at quantum computing Better than we should expect. E.g. AlphaGO Turned a corner on practicality • Narrow • Does one thing really well: • Cognition, playing games (strategy), predictions • Wide (AKA Artificial General Intelligence) • Alexa, Siri, Google Assistant, Cortana • Supposed to do what’s asked • Conscious machines • Supposed to do what you (it) need(s) • Lots of philosophical debates( • Reductionism,….
  8. 8. APTAGE.COM | 8 The state of the art • Narrow • Does one thing really well: • Natural language, play games, analysis • Self driving cars • Specific tools to augment workers • Great recent progress • Wide (combination of Narrow, bag of tricks) • AKA Artificial General Intellegnece • Alexa, Siri, Google thing • Supposed to do what’s asked • Conscious machines • Lots of philosophical angst (Body and Soul) • Is it even possible? • How would we know? Not yet very good yet, not anywhere near as smart as my 3 yr old grandson Just Wait “Ali Rahimi, a researcher at Google, … said researchers often don't know why some algorithms work while other ones don't. "Many of us feel like we're operating on an alien technology," Rahimi explained.” Android Police, May 5, 2018, https://bit.ly/2jEkUF0
  9. 9. APTAGE.COM | 9 AI both uses, and generates needs for, new analytics AI IQ Measures the quality of AI offerings Needed to make AI a science Descriptive Monitoring what has happened Predictive What is likely to happen Prescriptive Recommends actions Autonomous Trusted to Take Actions ImmaturityBayseian
  10. 10. APTAGE.COM | 10 For most businesses , the money is in narrow AI • Current AI is much analogous to first industrial revolution • It carries out mental tasks well enough to be more efficient than humans • Replace workers to managed risk routine • Issuing insurance policies • Issuing credit • Taking sales orders • Enhance workers • Reading medical images • Code Migration • Dealing with uncertainty • Thinking slow ”AI Could Kill 2.5 Million Financial Jobs – And Save Banks $1Trillion” Fast Company, May 8, 2018 (https://bit.ly/2jFUUJr)
  11. 11. APTAGE.COM | 11 For business, AI leads the “service industrial revolution” • Current AI is much analogous to first • It carries out mental tasks well enough to be more efficient than humans • Replace (routine) • Issuing insurance policies • Issuing credit • Taking sales orders • Enhance • Reading medical images • Code Migration • Dealing with uncertainty • Thinking slow: Augment probability skills ”AI Could Kill 2.5 Million Financial Jobs – And Save Banks $1 Trillion” Fast Company, May 8, 2018 (https://bit.ly/2jFUUJr) Lets discuss Aptage
  12. 12. APTAGE.COM | 12 Aptage AI enhances the skills of development managers Strategic Investment J to S Projections Build Risk/Reward Portfolio Risk/Reward Portfolio Early Days Churn Analysis Detect Disruption Risk of Disruption Deliver Innovation Risk Burndown
  13. 13. APTAGE.COM | 13 Final thoughts • AI is the evolution and convergence of several technologies • Breakthroughs come from computation neuroscience • AI, as people will always make mistakes – need to decide what is good enough • For most of us the money is in narrow AI • Kicking off the service industrial revolution • Business should and often do treat it as any automation • AGI and conscious machines • AGI – huge investments by big guys • Conscious – may take quantum computers • Analytics will evolve to measuring AI • Aptage is AI for development organizations Risk Burndown
  14. 14. APTAGE.COM | 14 References • Chistof Kock, Consciousness: Confessions of a Romantic Reductionist, MIT Press), 2012 • Pedro Domingos, The Master Algorithm: How the Quest for the Ultimate Learning Machine Will Remake Our World, Basic Books, 2015 • Aurélien Géron, Hands-On Machine Learning with Scikit-Learn and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems, O’Reilly Media, 2017 • Cade Metz, “The Rise of AI and the end of code” in Wired, May 2016 ( https://www.wired.com/2016/05/google- alpha-go-ai/) • “Googles Researchers Call Machine Learning Alchemy” in Android Police, https://www.androidpolice.com/2018/05/06/googles-researchers-call-machine-learning-alchemy/ • Alchemy site: https://alchemy.cs.washington.edu • TensorFlow site: https://www.tensorflow.org
  15. 15. Questions? Aptage Intro v31
  16. 16. Thank You Murray Cantor, Ph.D, Aptage CTO murray@aptage.com John Gonzalez, Aptage VP of Sales john.gonzalez@aptage.com Aptage Intro v31

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