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AGI, Machine Learning, and Deep Learning - All Hungry for Data

Explore the concepts of Artificial General Intelligence (AGI), Machine Learning, and Deep Learning and their increasing reliance on data. Delve into the relationship between these techniques and their potential value.

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AGI, Machine Learning, and Deep Learning - All Hungry for Data

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  1. “Artificial General Intelligence (AGI), Machine Learning, andDeep Learning – All Hungry for Data”  David Joffe & Tim Bendel March 13, 2018

  2. What is Artificial General Intelligence (AGI)? “I propose to consider the question, “Can machines think?” This should begin with definitions of the meaning of the terms “machine” and “think”…The new form of the problem can be described in terms of a game which we call the “imitation game.” “Computing Machinery and Intelligence,” A. M. Turing (1950), Mind 49, pp. 433 – 460. • Hmmm…what can I ask to distinguish the intelligent human from the intelligent machine? • CAPTCHA – Completely Automated Public Turing Test to tell Computers and Humans Apart Bank of America

  3. What is Machine Learning? “Field of study that gives computers the ability to learn without being explicitly programmed.” Arthur Samuel, 1959, citation from Andrew Ng Machine Learning, https://www.coursera.org/learn/machine-learning “A computer program is said to learn from experience E with respect to some task T and some performance measure P, if its performance on T, as measured by P, improves with experience E.” Machine Learning, Tom Mitchell, McGraw Hill, 1997 Bank of America

  4. What is Deep Learning? “deep learning [is] … a pipeline of modules all of which are trainable. … deep because [has] multiple stages in the process of recognizing an object and all of those stages are part of the training”” Yann LeCun, 2016, “Accelerating Understanding: Deep Learning, Intelligent Applications, and GPUs,” talk at Lawrence Livermore National Laboratory YannLeCun, 2016 Bank of America

  5. What is the relationship of AGI, ML, and DL? These are techniques which some would categorize as machine learning techniques. Bank of America

  6. The COBIT 5 Metadata Information Lifecycle: System Complexity Yet Potential High Value Source: ISACA, COBIT 5, USA, 2012 Bank of America

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