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Artificial Intelligence explained simplistically

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NBC Bearings
NBC Bearings

The training content covers: - Basics of Artificial Intelligence - Penetration of AI in our daily lives - Few examples and Use cases - A brief on how future with AI looks like

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Artificial Intelligence
16 April 2020 NEI Digital Office 2 Disclaimer The material and Information contained here are for general information purpose only. You should not rely upon the material or information provided herein for any basis for making any business, legal or other decisions. Fair usage: This material might contain some copyrighted material, the use of which has not always been specifically authorised by the copyright owner. We have given the source information, wherever available. While we make every endeavour to keep the information accurate and correct, National Engineering Industries Ltd. makes no representations and warranties of any kind either express or implied about the correctness, accuracy, suitability, reliability or productivity with respect to information or concepts contained in the presentation for any purpose. Any reliance on such material is solely at your risk and consequences.
Glimpse into the future - AI by 2030 16 April 2020 NEI Digital Office 3 80%executives say AI boosts productivity Mobiles using voice assistants Virtual Assistants: Google, Cortant, Siri, Alexa 6billion devices need AI support Customer / Employee interactions driven by Chat-bots $ 5.4 Bn invested in AI start ups Robots to outnumber humans AI to be powered by GPUsnot CPUs AI to replace 16% jobs in a decade
AI- part our lives today 16 April 2020 NEI Digital Office 4 Maps can more easily incorporate user-reported traffic incidents like construction and accidents. Access to vast amounts of data being fed to its proprietary algorithms means Maps can reduce commutes by suggesting the fastest routes to and from work. AI-powered personal assistant that accepts voice commands to create to-do lists, order items online, set reminders, and answer questions (via internet searches) Google uses artificial neural networks to power voice search. Microsoft claims to have developed a speech- recognition system that can transcribe conversation slightly more accurately than humans. Voice – to – text “Ok Google” “Hey Siri” Smart Personal Assistants AI-Powered Predictions Source(s): • https://emerj.com/ai-sector-overviews/everyday-examples-of-ai/
Starters 16 April 2020 NEI Digital Office 5 What is AI ?
Starters 16 April 2020 NEI Digital Office 6 What is AI ? Where have you seen / experienced AI ?
What is AI ? Where have you seen / experienced AI ? 16 April 2020 NEI Digital Office 7 Starters - Programs that behave externally like humans ? - Programs that operate internally as humans do ? - Computational systems that behave intelligently ? - Rational behaviour ? - Human beings are intelligent - To be called intelligent, a machine must produce responses that are indistinguishable from those of a human - Autonomous planning and scheduling of tasks aboard a spacecraft - Beating Gary Kasparov in a chess match - Steering a driver-less car - Understanding language - Robotic assistants in surgery - Monitoring trade in the stock market to see if insider trading is going on Source: https://www.coursehero.com/file/47104889/Week-8-Artificial-Intelligencepdf/
16 April 2020 NEI Digital Office 8 Are there tasks which cannot be automated ? If so, what are the limitations ? OR How do computers’ ability compare to that of humans?
16 April 2020 NEI Digital Office 9 What is Artificial Intelligence Branch of computer science concerned with building smart machines capable of performing tasks the typically require human intelligence Interdisciplinary science with multiple approaches, but advancements in machine learning and deep learning are creating a paradigm shift in virtually every sector of industry
A 70 year Rich History 16 April 2020 NEI Digital Office 10 “Can machines think?” “Study of artificial intelligence” 1950 1956 John McCarthyAlan TuringTuring test A test to empirically determine whether a computer has achieved intelligence It simply shows that it generated behaviour consistent with thinking. Weak equivalence: the two systems (human and computer) are equivalent in results (output), but they do not necessarily arrive at those results in the same way Strong equivalence: the two systems use the same internal processes to produce results Source(s) / Picture Credit: • https://cs.slu.edu/~fritts/CSCI140_F12/schedule/csci140_artificial_intelligence.pdf
Compare the way Humans and Machines Work 16 April 2020 NEI Digital Office 11 Artificial Intelligence Machine Learning Deep Learning Any technique that enables machines to mimic human behaviour Subset of AI technique which uses statistical methods to enable machine to improve with experience Subset of ML which make the computation of multi-layer neural networks feasible Source(s) / Picture Credit: • https://www.slideshare.net/grigorysapunov/artificial-intelligence-past-present-and-future-64586944
Typical Machine Learning Tasks 16 April 2020 NEI Digital Office 12 Classification Regression Clustering Dimensionality reduction Ranking Recommendatio n Predict a class of an object (cat / dog from an image; Male / female from user’s web activity; Spam / Ham from an email contents etc. Predicts a continuous value for an object (Sales in the next month, price of a house with specific features, energy consumption for a household Group similar objects together find user groups different by their behaviour on site cluster customers into meaningful groups etc. “Compress” the data from a high dimensional representation into a lower- dimensional one (useful for visualization) Arrange a list of objects to maximize some utility (i.e. by click probably, or by relevance to a query) Filter a small subset of objects from a large collection and recommend them to a user (increase hits / user loyalty; time spent on service etc.)
16 April 2020 NEI Digital Office 13 Deep Learning / Neural Nets: Overview Ability to learn hierarchical representations of features (and for images they do resemble some neuroscience data on how does visual system work Source(s) / Picture Credit: • https://medium.com/@RaghavPrabhu/understanding-of-convolutional-neural-network-cnn-deep-learning-99760835f148
16 April 2020 NEI Digital Office 14 Deep Learning Tasks Speech, Images, Video Text/NLP Reinforcement Learning Other Research Simple tasks (classification, localization) almost done on super-human level Complex tasks (semantic segmentation, style transfer, image generation, …) are in progress with exciting examples Robot perception is in progress Some good basic technologies are in use (word embeddings, language models, sequence to sequence learning for machine translation, etc) Even more in progress (translation, q&a and conversational nets, etc) Great achievements exist: Go playing, Atari playing One-shot learning, multi- modal and multi-task learning, memory and attention, unsupervised learning, and many many more Source(s) / Picture Credit: • https://www.slideshare.net/grigorysapunov/deep-learning-and-the-state-of-ai-2016
16 April 2020 NEI Digital Office 15 Use Cases Source(s) / Picture Credit: • https://www.datacamp.com/community/tutorials/object-detection-guide
16 April 2020 NEI Digital Office 16 Use Cases Source(s) / Picture Credit: • https://azati.ai/image-detection-recognition-and-classification-with-machine-learning/
16 April 2020 NEI Digital Office 17 Use Cases Source(s) / Picture Credit: • https://www.slideshare.net/grigorysapunov/deep-learning-and-the-state-of-ai-2016
16 April 2020 NEI Digital Office 18 Use Cases Source(s) / Picture Credit: • https://www.slideshare.net/grigorysapunov/deep-learning-cases-text-and-image-processing
16 April 2020 NEI Digital Office 19 Use Cases Source(s) / Picture Credit: • https://www.slideshare.net/grigorysapunov/deep-learning-cases-text-and-image-processing
16 April 2020 NEI Digital Office 20 Use Cases Source(s) / Picture Credit: • https://www.slideshare.net/grigorysapunov/deep-learning-cases-text-and-image-processing
16 April 2020 NEI Digital Office 21 Use Cases Source(s) / Picture Credit: • https://www.slideshare.net/grigorysapunov/deep-learning-and-the-state-of-ai-2016
16 April 2020 NEI Digital Office 22 AI- part our lives today Mobile Use Voice – to – text “Ok Google” “Hey Siri” Google uses artificial neural networks to power voice search. Microsoft claims to have developed a speech- recognition system that can transcribe conversation slightly more accurately than humans. Smart Personal Assistants AI-powered personal assistant that accepts voice commands to create to-do lists, order items online, set reminders, and answer questions (via internet searches) AI-Powered Predictions Maps can more easily incorporate user-reported traffic incidents like construction and accidents. Access to vast amounts of data being fed to its proprietary algorithms means Maps can reduce commutes by suggesting the fastest routes to and from work. Source(s) / Picture Credit: • https://emerj.com/ai-sector-overviews/everyday-examples-of-ai/
16 April 2020 NEI Digital Office 23 Glimpse into the future social messaging tool typically used in the workplace, also allows third parties to incorporate AI- powered chatbots Soon, our day-to- day tasks may be completed within a conversation with an AI chatbot Source(s) / Picture Credit: • https://emerj.com/ai-sector-overviews/everyday-examples-of-ai/
16 April 2020 NEI Digital Office 24 Source(s) / Picture Credit: • https://emerj.com/ai-sector-overviews/everyday-examples-of-ai/ Glimpse into the future
16 April 2020 NEI Digital Office 25 Glimpse into the future 90%reduction in accidents 75%reduction in number of cars on road through ride sharing 40%reduction in wait time through smart traffic lights 26%reduction in overall travel time through smart traffic lights 2028 is the year for mass production of such vehicles - UBER CEO Self Driving Cars
16 April 2020 NEI Digital Office 26 How does the future look like ? ? ? His decisions aren’t any better than yours - But they are WAY faster The good news is I have discovered inefficiencies. The bad news is that you’re one of themSource(s) / Picture Credit: • https://timoelliott.com/blog/cartoons/artificial-intelligence-cartoons
16 April 2020 NEI Digital Office 27 Key Contact details for any queries: Ashutosh Basotia NEI Digital Office (E) ashutosh.basotia@nbcbearings.in (P) +91 141 2223221

More Related Content

Artificial Intelligence explained simplistically

  • 2. 16 April 2020 NEI Digital Office 2 Disclaimer The material and Information contained here are for general information purpose only. You should not rely upon the material or information provided herein for any basis for making any business, legal or other decisions. Fair usage: This material might contain some copyrighted material, the use of which has not always been specifically authorised by the copyright owner. We have given the source information, wherever available. While we make every endeavour to keep the information accurate and correct, National Engineering Industries Ltd. makes no representations and warranties of any kind either express or implied about the correctness, accuracy, suitability, reliability or productivity with respect to information or concepts contained in the presentation for any purpose. Any reliance on such material is solely at your risk and consequences.
  • 3. Glimpse into the future - AI by 2030 16 April 2020 NEI Digital Office 3 80%executives say AI boosts productivity Mobiles using voice assistants Virtual Assistants: Google, Cortant, Siri, Alexa 6billion devices need AI support Customer / Employee interactions driven by Chat-bots $ 5.4 Bn invested in AI start ups Robots to outnumber humans AI to be powered by GPUsnot CPUs AI to replace 16% jobs in a decade
  • 4. AI- part our lives today 16 April 2020 NEI Digital Office 4 Maps can more easily incorporate user-reported traffic incidents like construction and accidents. Access to vast amounts of data being fed to its proprietary algorithms means Maps can reduce commutes by suggesting the fastest routes to and from work. AI-powered personal assistant that accepts voice commands to create to-do lists, order items online, set reminders, and answer questions (via internet searches) Google uses artificial neural networks to power voice search. Microsoft claims to have developed a speech- recognition system that can transcribe conversation slightly more accurately than humans. Voice – to – text “Ok Google” “Hey Siri” Smart Personal Assistants AI-Powered Predictions Source(s): • https://emerj.com/ai-sector-overviews/everyday-examples-of-ai/
  • 5. Starters 16 April 2020 NEI Digital Office 5 What is AI ?
  • 6. Starters 16 April 2020 NEI Digital Office 6 What is AI ? Where have you seen / experienced AI ?
  • 7. What is AI ? Where have you seen / experienced AI ? 16 April 2020 NEI Digital Office 7 Starters - Programs that behave externally like humans ? - Programs that operate internally as humans do ? - Computational systems that behave intelligently ? - Rational behaviour ? - Human beings are intelligent - To be called intelligent, a machine must produce responses that are indistinguishable from those of a human - Autonomous planning and scheduling of tasks aboard a spacecraft - Beating Gary Kasparov in a chess match - Steering a driver-less car - Understanding language - Robotic assistants in surgery - Monitoring trade in the stock market to see if insider trading is going on Source: https://www.coursehero.com/file/47104889/Week-8-Artificial-Intelligencepdf/
  • 8. 16 April 2020 NEI Digital Office 8 Are there tasks which cannot be automated ? If so, what are the limitations ? OR How do computers’ ability compare to that of humans?
  • 9. 16 April 2020 NEI Digital Office 9 What is Artificial Intelligence Branch of computer science concerned with building smart machines capable of performing tasks the typically require human intelligence Interdisciplinary science with multiple approaches, but advancements in machine learning and deep learning are creating a paradigm shift in virtually every sector of industry
  • 10. A 70 year Rich History 16 April 2020 NEI Digital Office 10 “Can machines think?” “Study of artificial intelligence” 1950 1956 John McCarthyAlan TuringTuring test A test to empirically determine whether a computer has achieved intelligence It simply shows that it generated behaviour consistent with thinking. Weak equivalence: the two systems (human and computer) are equivalent in results (output), but they do not necessarily arrive at those results in the same way Strong equivalence: the two systems use the same internal processes to produce results Source(s) / Picture Credit: • https://cs.slu.edu/~fritts/CSCI140_F12/schedule/csci140_artificial_intelligence.pdf
  • 11. Compare the way Humans and Machines Work 16 April 2020 NEI Digital Office 11 Artificial Intelligence Machine Learning Deep Learning Any technique that enables machines to mimic human behaviour Subset of AI technique which uses statistical methods to enable machine to improve with experience Subset of ML which make the computation of multi-layer neural networks feasible Source(s) / Picture Credit: • https://www.slideshare.net/grigorysapunov/artificial-intelligence-past-present-and-future-64586944
  • 12. Typical Machine Learning Tasks 16 April 2020 NEI Digital Office 12 Classification Regression Clustering Dimensionality reduction Ranking Recommendatio n Predict a class of an object (cat / dog from an image; Male / female from user’s web activity; Spam / Ham from an email contents etc. Predicts a continuous value for an object (Sales in the next month, price of a house with specific features, energy consumption for a household Group similar objects together find user groups different by their behaviour on site cluster customers into meaningful groups etc. “Compress” the data from a high dimensional representation into a lower- dimensional one (useful for visualization) Arrange a list of objects to maximize some utility (i.e. by click probably, or by relevance to a query) Filter a small subset of objects from a large collection and recommend them to a user (increase hits / user loyalty; time spent on service etc.)
  • 13. 16 April 2020 NEI Digital Office 13 Deep Learning / Neural Nets: Overview Ability to learn hierarchical representations of features (and for images they do resemble some neuroscience data on how does visual system work Source(s) / Picture Credit: • https://medium.com/@RaghavPrabhu/understanding-of-convolutional-neural-network-cnn-deep-learning-99760835f148
  • 14. 16 April 2020 NEI Digital Office 14 Deep Learning Tasks Speech, Images, Video Text/NLP Reinforcement Learning Other Research Simple tasks (classification, localization) almost done on super-human level Complex tasks (semantic segmentation, style transfer, image generation, …) are in progress with exciting examples Robot perception is in progress Some good basic technologies are in use (word embeddings, language models, sequence to sequence learning for machine translation, etc) Even more in progress (translation, q&a and conversational nets, etc) Great achievements exist: Go playing, Atari playing One-shot learning, multi- modal and multi-task learning, memory and attention, unsupervised learning, and many many more Source(s) / Picture Credit: • https://www.slideshare.net/grigorysapunov/deep-learning-and-the-state-of-ai-2016
  • 15. 16 April 2020 NEI Digital Office 15 Use Cases Source(s) / Picture Credit: • https://www.datacamp.com/community/tutorials/object-detection-guide
  • 16. 16 April 2020 NEI Digital Office 16 Use Cases Source(s) / Picture Credit: • https://azati.ai/image-detection-recognition-and-classification-with-machine-learning/
  • 17. 16 April 2020 NEI Digital Office 17 Use Cases Source(s) / Picture Credit: • https://www.slideshare.net/grigorysapunov/deep-learning-and-the-state-of-ai-2016
  • 18. 16 April 2020 NEI Digital Office 18 Use Cases Source(s) / Picture Credit: • https://www.slideshare.net/grigorysapunov/deep-learning-cases-text-and-image-processing
  • 19. 16 April 2020 NEI Digital Office 19 Use Cases Source(s) / Picture Credit: • https://www.slideshare.net/grigorysapunov/deep-learning-cases-text-and-image-processing
  • 20. 16 April 2020 NEI Digital Office 20 Use Cases Source(s) / Picture Credit: • https://www.slideshare.net/grigorysapunov/deep-learning-cases-text-and-image-processing
  • 21. 16 April 2020 NEI Digital Office 21 Use Cases Source(s) / Picture Credit: • https://www.slideshare.net/grigorysapunov/deep-learning-and-the-state-of-ai-2016
  • 22. 16 April 2020 NEI Digital Office 22 AI- part our lives today Mobile Use Voice – to – text “Ok Google” “Hey Siri” Google uses artificial neural networks to power voice search. Microsoft claims to have developed a speech- recognition system that can transcribe conversation slightly more accurately than humans. Smart Personal Assistants AI-powered personal assistant that accepts voice commands to create to-do lists, order items online, set reminders, and answer questions (via internet searches) AI-Powered Predictions Maps can more easily incorporate user-reported traffic incidents like construction and accidents. Access to vast amounts of data being fed to its proprietary algorithms means Maps can reduce commutes by suggesting the fastest routes to and from work. Source(s) / Picture Credit: • https://emerj.com/ai-sector-overviews/everyday-examples-of-ai/
  • 23. 16 April 2020 NEI Digital Office 23 Glimpse into the future social messaging tool typically used in the workplace, also allows third parties to incorporate AI- powered chatbots Soon, our day-to- day tasks may be completed within a conversation with an AI chatbot Source(s) / Picture Credit: • https://emerj.com/ai-sector-overviews/everyday-examples-of-ai/
  • 24. 16 April 2020 NEI Digital Office 24 Source(s) / Picture Credit: • https://emerj.com/ai-sector-overviews/everyday-examples-of-ai/ Glimpse into the future
  • 25. 16 April 2020 NEI Digital Office 25 Glimpse into the future 90%reduction in accidents 75%reduction in number of cars on road through ride sharing 40%reduction in wait time through smart traffic lights 26%reduction in overall travel time through smart traffic lights 2028 is the year for mass production of such vehicles - UBER CEO Self Driving Cars
  • 26. 16 April 2020 NEI Digital Office 26 How does the future look like ? ? ? His decisions aren’t any better than yours - But they are WAY faster The good news is I have discovered inefficiencies. The bad news is that you’re one of themSource(s) / Picture Credit: • https://timoelliott.com/blog/cartoons/artificial-intelligence-cartoons
  • 27. 16 April 2020 NEI Digital Office 27 Key Contact details for any queries: Ashutosh Basotia NEI Digital Office (E) ashutosh.basotia@nbcbearings.in (P) +91 141 2223221