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Artificial Intelligence for Business

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Artificial Intelligence for Business

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These deck contains an overview of what is commercially available in terms of Artificial Intelligence for business applications. Be aware: it was created on April 2017 and this is a very fast moving industry....

These deck contains an overview of what is commercially available in terms of Artificial Intelligence for business applications. Be aware: it was created on April 2017 and this is a very fast moving industry....

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Artificial Intelligence for Business

  1. 1. BY - NC - nicolamattina.it Artificial Intelligence for Business Nicola Mattina April 2017
  2. 2. BY - NC - nicolamattina.it In our imagination…
  3. 3. BY - NC - nicolamattina.it Artificial Intelligence in everyday products…
  4. 4. BY - NC - nicolamattina.it Why is AI becoming usable for business? Algorithms Data Computing Power
  5. 5. BY - NC - nicolamattina.it Investors are interested. A lot!
  6. 6. BY - NC - nicolamattina.it Investors are interested. A lot!
  7. 7. BY - NC - nicolamattina.it AI is rapidly moving from inflated expectations to productivity
  8. 8. BY - NC - nicolamattina.it Technologies and Services
  9. 9. BY - NC - nicolamattina.it Technologies and Research What is available on the market Platforms, SaaS and APIs Services built on AI
  10. 10. BY - NC - nicolamattina.it What is available on the market
  11. 11. BY - NC - nicolamattina.it What is available on the market
  12. 12. BY - NC - nicolamattina.it Defining Artificial Intelligence
  13. 13. BY - NC - nicolamattina.it A definition of human intelligence
  14. 14. BY - NC - nicolamattina.it A definition of artificial intelligence The capacity of a computer to perform operations analogous to learning and decision making in humans.
  15. 15. BY - NC - nicolamattina.it 3 levels of Artificial Intelligence Artificial Narrow Intelligence Specialized in one area. Artificial General Intelligence Specialized in all area. Artificial Super Intelligence Smarter than humans in every way.
  16. 16. BY - NC - nicolamattina.it 3 levels of Artificial Intelligence Artificial Narrow Intelligence Specialized in one area. Artificial General Intelligence Specialized in all area. Artificial Super Intelligence Smarter than humans in every way.W ork in Progress Singularity
  17. 17. BY - NC - nicolamattina.it What are (some of) the skills of Artificial Intelligence today? Natural Language Processing Knowledge Representation Machine Learning Automatic Reasoning Automatic Planning
  18. 18. BY - NC - nicolamattina.it What are (some of) the skills of Artificial Intelligence today? AI understands inputs Natural Language Processing Image Recognition Speech to Text AI manages knowledge Ontologies and Linked Data Pre-Trained Datasets AI learns Machine Learning Deep Learning AI executes tasks Automatic Reasoning Automatic Planning
  19. 19. BY - NC - nicolamattina.it Understanding inputs: Speech recognition Speech recognition can be used to allow applications to take commands from humans, to transcribe conversations or even participate in them. Popular commercial examples are Apple’s Siri, Google Now and Amazon’s Alexa.
  20. 20. BY - NC - nicolamattina.it Understanding inputs: Speech recognition https://cloud.google.com/speech/ https://www.microsoft.com/cognitive-services/en-us/speech-api
  21. 21. BY - NC - nicolamattina.it Understanding Inputs: Natural Language Processing http://www.moshebergman.com/study-notes/text-retrieval/week1.html Natural Language Processing can be used to analyse any text to extract topics, sentiment, meaning and ultimately to gain knowledge. It is used to read the sentiment in financial markets, to analyse product reviews, monitor social media,...
  22. 22. BY - NC - nicolamattina.it Understanding inputs: Natural language processing
  23. 23. BY - NC - nicolamattina.it Understanding inputs: Image recognition A technology that identifies and understands what can be seen in images and video. It assigns labels to objects and situations. Best known applications of Image Analysis are facial recognition, quality controls and self-driving technology.
  24. 24. BY - NC - nicolamattina.it Understanding Inputs: Image recognition https://cloud.google.com/vision/ https://clarifai.com
  25. 25. BY - NC - nicolamattina.it Managing knowledge: Ontologies and Linked Data An ontology is a formal naming and definition of the types, properties, and interrelationships of the entities that really or fundamentally exist for a particular domain of discourse.
  26. 26. BY - NC - nicolamattina.it Nicola teaches many different things, including user experience to many different audiences, including students at Roma Tre University. Managing knowledge: Ontologies and Linked Data Ontologies work very well but are domain-specific. Professor Teaching Topic Univesity
  27. 27. BY - NC - nicolamattina.it Managing knowledge: Ontologies and Linked Data
  28. 28. BY - NC - nicolamattina.it Managing knowledge: Ontologies and Linked Data http://dbpedia.org/page/God_Save_the_Queen
  29. 29. BY - NC - nicolamattina.it Managing knowledge: Ontologies and Linked Data
  30. 30. BY - NC - nicolamattina.it Managing knowledge: Data Sets and Models
  31. 31. BY - NC - nicolamattina.it Machine Learning: Basics Machine learning provides computers with the ability to learn without being explicitly programmed Today it is used to better detect diseases, recommend content, improve products and services and many other applications.
  32. 32. BY - NC - nicolamattina.it Machine Learning: Types of learning
  33. 33. BY - NC - nicolamattina.it Machine Learning: Problem Types Classification is a general process related to categorization, the process in which ideas and objects are recognized, differentiated, and understood. Regression analysis is a statistical process for estimating the relationships among variables. Clustering is the task of grouping a set of objects in such a way that objects in the same group (called a cluster) are more similar (in some sense or another) to each other than to those in other groups (clusters) Anomaly detection is the identification of items, events or observations which do not conform to an expected pattern or other items in a dataset.
  34. 34. BY - NC - nicolamattina.it Machine Learning: Platforms https://aws.amazon.com/it/machine-learning/https://studio.azureml.net/
  35. 35. BY - NC - nicolamattina.it Machine Learning: Deep Learning Deep Learning is part of the machine learning field of learning representations of data. Exceptional effective at learning patterns. It utilizes learning algorithms that derive meaning out of data by using a hierarchy of multiple layers that mimic the neural networks of our brain. If you provide the system tons of information, it begins to understand it and respond in useful ways.
  36. 36. BY - NC - nicolamattina.it Machine Learning: Deep Learning A deep neural network consists of a hierarchy of layers, whereby each layer transforms the input data into more abstract representations (e.g. edge -> nose -> face). The output layer combines those features to make predictions
  37. 37. BY - NC - nicolamattina.it Executing tasks: Filter spam
  38. 38. BY - NC - nicolamattina.it Executing tasks: Play games DeepMind DP Q-Learning outperform humans in over 30 Atari games just by receiving the pixels on the screen with the goal to maximize the score (Reinforcement Learning).
  39. 39. BY - NC - nicolamattina.it Executing tasks: Suggest things
  40. 40. BY - NC - nicolamattina.it Executing tasks: Labeling images Neural Image Caption Generator generates fitting natural-language captions only based on the pixels by combining a vision CNN (convolutional neural Network) and a language-generating RNN (recurrent neural network ).
  41. 41. BY - NC - nicolamattina.it Executing tasks: Trasform movies in 3D Deep3D can automatically convert image/video from 2D-to-3D with Convolutional Neural Networks. It learns to infer 3D representations of the world based on training set of 3D movies.
  42. 42. BY - NC - nicolamattina.it Executing tasks: Drive a car
  43. 43. BY - NC - nicolamattina.it Executing tasks: Conversate
  44. 44. BY - NC - nicolamattina.it Building an AI product
  45. 45. BY - NC - nicolamattina.it Developers Data Scientists Data Platforms Starting an AI project
  46. 46. BY - NC - nicolamattina.it Sources To make this presentation, I consulted many sources. Among these, the most relevant are: • Sam Wouters, Demystifying Artificial Intelligence • Luke Masuch, Deep Learning - The Past, Present and Future of Artificial Intelligence • Nathan Pacer, Venture Scanner - AI Report Q1 2017 This deck was used for a lecture at Tag Innovation School in Milan on April 28, 2017. It is released under a Creative Commons BY NC excepct for the contents that are extracted from the presentations listed above. Those contents are property of their authors.
  47. 47. BY - NC - nicolamattina.it nicolamattina.it ciao@nicolamattina.it Want more? Write me :)

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