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Artificial Intelligence and Machine Learning

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Artificial Intelligence and Machine Learning

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Presented By JBIMS Marketting Batch (2017-2020).
Application Artificial Intelligence in MIS(Management Information System). Presented By Trilok Prabhakaran , Aditya Singh , Shashi Yadav, Vaibhav Rokade. Presentation have live cases of two different industry.

Presented By JBIMS Marketting Batch (2017-2020).
Application Artificial Intelligence in MIS(Management Information System). Presented By Trilok Prabhakaran , Aditya Singh , Shashi Yadav, Vaibhav Rokade. Presentation have live cases of two different industry.

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Artificial Intelligence and Machine Learning

  1. 1. MAIL ????
  2. 2. Prerequisite
  3. 3. The 10 Vision
  4. 4. How AI Started?• The term artificial intelligence was first coined by John McCarthy in 1956 when he held the first academic conference on the subject. • But the journey to understand if machines can truly think began much before that. In Vannevar Bush’s seminal work As We May Think. he proposed a system which amplifies people’s own knowledge and understanding. • Five years later Alan Turing wrote a paper on the notion of machines being able to simulate human beings and the ability to do intelligent things, such as play Chess. • No one can refute a computer’s ability to process logic. But to many it is unknown if a machine can think. The precise definition of think is important because there has been some strong opposition as to whether or not this notion is even possible.
  5. 5. The Chinese paradox • For example, there is the so-called ‘Chinese room’ argument. Imagine someone is locked in a room, where they were passed notes in Chinese. Using an entire library of rules and look-up tables they would be able to produce valid responses in Chinese, but would they really ‘understand’ the language? The argument is that since computers would always be applying rote fact lookup they could never ‘understand’ a subject. This argument has been refuted in numerous ways by researchers, but it does undermine people’s faith in machines and so-called expert systems in life-critical applications.
  6. 6. The Invisible Intelligence • The main advances over the past sixty years have been advances in search algorithms, machine learning algorithms, and integrating statistical analysis into understanding the world at large. • However most of the breakthroughs in AI aren’t noticeable to most people. Rather than talking machines used to pilot space ships to Jupiter, AI is used in more subtle ways such as examining purchase histories and influence marketing decisions. • In the field of AI expectations seem to always outpace the reality. After decades of research, no computer has come close to passing the Turing Test (a model for measuring ‘intelligence’); Expert Systems have grown but have not become as common as human experts; and while we’ve built software that can beat humans at some games, open ended games are still far from the mastery of computers.
  7. 7. Can machines think???
  8. 8. Imitation Game • The original game upon which Turing’s idea was based required a man, a woman and an interrogator. The goal was for the interrogator to identify which of the participants was a man and which was a woman. Since the interrogator would be able to identify the gender of the respondent by their voice (and maybe handwriting) the answers to the interrogator’s questions would be typewritten or repeated by an intermediary. For the Turing Test, one of those two participants would be replaced by a machine and the goal of the interrogator would not be to identify the gender of the participants, but which is human and which is a machine.
  9. 9. Journey So Far
  10. 10. Deep Blue • The computer program, Deep Blue, beat world chess champion Garry Kasparov in a six-game chess match in 1997. This feat has not been repeated, and it does not yet represent the end of human supremacy at this game.
  11. 11. • • What kinds of problems that humans find difficult do you think computers are particularly well suited to solve? • Are there any such problems that you know of that computers cannot currently solve but which you believe computers will one day be able to solve? • What advances in technology or understanding are necessary before those problems can be solved?
  12. 12. • One of the most famous fictional accounts of Artificial Intelligence comes in the film 2001: A Space Odyssey, based on the story by Arthur C. Clarke. • One of the main characters in the film is HAL, a Heuristically programmed Algorithmic computer. • In the film, HAL behaves, speaks, and interacts with humans in much the same way that a human would (albeit in a disembodied form). In fact, this humanity is taken to extremes by the fact that HAL eventually goes mad. • In the film, HAL played chess, worked out what people were saying by reading their lips, and engaged in conversation with other humans. • How many of these tasks are computers capable of today? HAL—Fantasy or Reality?
  13. 13. Alpha Go
  14. 14. AI in Action
  15. 15. Aviation • The Air Operations Division (AOD) uses AI for the rule based expert systems. The AOD has use for artificial intelligence for surrogate operators for combat and training simulators, mission management aids, support systems for tactical decision making, and post processing of the simulator data into symbolic summaries. • In 2003, NASA's Dryden Flight Research Center, and many other companies, created software that could enable a damaged aircraft to continue flight until a safe landing zone can be reached.[5] The software compensates for all the damaged components by relying on the undamaged components. The neural network used in the software proved to be effective and marked a triumph for artificial intelligence.
  16. 16. Computer science • AI can be used to create other AI. For example, around November 2017, Google's AutoML project to evolve new neural net topologies created NASNet, a system optimized for ImageNet and COCO. According to Google, NASNet's performance exceeded all previously published ImageNet performance.
  17. 17. Education • There are a number of companies that create robots to teach subjects to children ranging from biology to computer science, though such tools have not become widespread yet. There have also been a rise of intelligent tutoring systems, or ITS, in higher education. • Ex:- an ITS called SHERLOCK teaches Air Force technicians to diagnose electrical systems problems in aircraft. Another example is DARPA, Defense Advanced Research Projects Agency, which used AI to develop a digital tutor to train its Navy recruits in technical skills in a shorter amount of time. • This led to an explosion in popularity of MOOCs, or Massive Open Online Courses, which allows students from around the world to take classes online. Data sets collected from these large scale online learning systems have also enabled learning analytics, which will be used to improve the quality of learning at scale.
  18. 18. Finance • Algorithmic trading:-Automated trading systems are typically used by large institutional investors. • Market analysis and data mining:-BlackRock’s AI engine, Aladdin, is used both within the company and to clients to help with investment decisions. Goldman Sachs uses Kensho, a market analytics platform that combines statistical computing with big data and natural language processing.
  19. 19. Personal finance • Several products are emerging that utilize AI to assist people with their personal finances. • For example, Digit is an app powered by artificial intelligence that automatically helps consumers optimize their spending and savings based on their own personal habits and goals • The app can analyze factors such as monthly income, current balance, and spending habits, then make its own decisions and transfer money to the savings account. • Wallet.AI, an upcoming startup in San Francisco, builds agents that analyze data that a consumer would leave behind, from Smartphone check-ins to tweets, to inform the consumer about their spending behavior.
  20. 20. Portfolio management • Robo-advisors are becoming more widely used in the investment management industry. • Robo-advisors provide financial advice and portfolio management with minimal human intervention. • This class of financial advisers work based on algorithms built to automatically develop a financial portfolio according to the investment goals and risk tolerance of the clients. • It can adjust to real-time changes in the market and accordingly calibrate the portfolio.
  21. 21. Underwriting • An online lender, Upstart, analyze vast amounts of consumer data and utilizes machine learning algorithms to develop credit risk models that predict a consumer’s likelihood of default. • Their technology will be licensed to banks for them to leverage for their underwriting processes as well. • ZestFinance developed their Zest Automated Machine Learning (ZAML) Platform specifically for credit underwriting as well. • This platform utilizes machine learning to analyze tens of thousands traditional and nontraditional variables (from purchase transactions to how a customer fills out a form) used in the credit industry to score borrowers. • The platform is particularly useful to assign credit scores to those with limited credit histories, such as millennials.
  22. 22. Job Search • The job market has seen a notable change due to Artificial intelligence implementation. • According to Raj Mukherjee from Indeed.com, 65% of people launch a job search again within 91 days of being hired. • AI-powered engine streamlines the complexity of job hunting by operating information on job skills, salaries, and user tendencies, matching people to the most relevant positions. • Artificial Intelligence impact on jobs research suggests that by 2030 intelligent agents and robots can eliminate 30% of the world’s human labor.
  23. 23. Heavy industry • Robots have become common in many industries and are often given jobs that are considered dangerous to humans. • Robots have proven effective in jobs that are very repetitive which may lead to mistakes or accidents due to a lapse in concentration and other jobs which humans may find degrading. • In 2014, China, Japan, the United States, the Republic of Korea and Germany together amounted to 70% of the total sales volume of robots. • In the automotive industry, a sector with particularly high degree of automation, Japan had the highest density of industrial robots in the world: 1,414 per 10,000 employees
  24. 24. Hospitals and medicine • Artificial neural networks are used as clinical decision support systems for medical diagnosis, such as in Concept Processing technology in EMR software. • Computer-aided interpretation of medical images. Such systems help scan digital images, e.g. from computed tomography, for typical appearances and to highlight conspicuous sections, such as possible diseases. • Heart sound analysis. • Companion robots for the care of the elderly. • Mining medical records to provide more useful information. • IDx's first solution, IDx-DR, is the first autonomous AI-based diagnostic system authorized for commercialization by the FDA.
  25. 25. Music • Artificial neural networks are used as clinical decision support systems for medical diagnosis, such as in Concept Processing technology in EMR software. • Computer-aided interpretation of medical images. Such systems help scan digital images, e.g. from computed tomography, for typical appearances and to highlight conspicuous sections, such as possible diseases. • Heart sound analysis. • Companion robots for the care of the elderly. • Mining medical records to provide more useful information. • IDx's first solution, IDx-DR, is the first autonomous AI-based diagnostic system authorized for commercialization by the FDA.
  26. 26. Media • While the evolution of music has always been affected by technology, artificial intelligence has enabled, through scientific advances, to emulate, at some extent, human-like composition. • Among notable early efforts, David Cope created an AI called Emily Howell that managed to become well known in the field of Algorithmic Computer Music.[31] The algorithm behind Emily Howell is registered as a US patent. • Other endeavours, like AIVA (Artificial Intelligence Virtual Artist), focus on composing symphonic music, mainly classical music for film scores. • It achieved a world first by becoming the first virtual composer to be recognized by a musical professional association. • Moreover, initiatives such as Google Magenta, conducted by the Google Brain team, want to find out if an artificial intelligence can be capable of creating compelling art. • At Sony CSL Research Laboratory, their Flow Machines software has created pop songs by learning music styles from a huge database of songs. By analyzing unique combinations of styles and optimizing techniques, it can compose in any style.
  27. 27. Telecommunications maintenance • Many telecommunications companies make use of heuristic search in the management of their workforces, for example • BT Group has deployed heuristic search in a scheduling application that provides the work schedules of 20,000 engineers.
  28. 28. Toys and games • The 1990s saw some of the first attempts to mass-produce domestically aimed types of basic Artificial Intelligence for education, or leisure. • This prospered greatly with the Digital Revolution, and helped introduce people, especially children, to a life of dealing with various types of Artificial Intelligence, specifically in the form of Tamagotchis and Giga Pets, iPod Touch, the Internet, and the first widely released robot, Furby. A mere year later an improved type of domestic robot was released in the form of Aibo, a robotic dog with intelligent features and autonomy. • Companies like Mattel have been creating an assortment of AI-enabled toys for kids as young as age three. Using proprietary AI engines and speech recognition tools, they are able to understand conversations, give intelligent responses and learn quickly. • AI has also been applied to video games, for example video game bots, which are designed to stand in as opponents where humans aren't available or desired • Alpha GO.
  29. 29. Transportation • Fuzzy logic controllers have been developed for automatic gearboxes in automobiles. For example, the 2006 Audi TT, VW Touareg and VW Caravell feature the DSP transmission which utilizes Fuzzy Logic. A number of Škoda variants (Škoda Fabia) also currently include a Fuzzy Logic-based controller. • Today's cars now have AI-based driver assist features such as self-parking and advanced cruise controls. AI has been used to optimize traffic management applications, which in turn reduces wait times, energy use, and emissions by as much as 25 percent. • In the future, fully autonomous cars will be developed. AI in transportation is expected to provide safe, efficient, and reliable transportation while minimizing the impact on the environment and communities. • The major challenge to developing this AI is the fact that transportation systems are inherently complex systems involving a very large number of components and different parties, each having different and often conflicting objectives.
  30. 30. AI geni for you • IRCTC confirm ticket prediction • Confirm tkt • Streak algo – zerodha • Google chatBot • Degit • Alexa
  31. 31. AI Hierarchy • Stages of Artificial Intelligence • Stage 1 – Machine Learning – It is a set of algorithms used by intelligent systems to learn from experience. • Stage 2 – Machine Intelligence – These are the advanced set of algorithms used by machines to learn from experience. Eg – Deep Neural Networks. • Artificial Intelligence technology is currently at this stage. • Stage 3 – Machine Consciousness – It is self-learning from experience without the need of external data.
  32. 32. Real Life Case - Lets Go Live
  33. 33. AI on Global Enterprise Scale
  34. 34. Real Time Actionable - IoT
  35. 35. AI on Global Enterprise Scale
  36. 36. Detecting Anomalies
  37. 37. How does it help Human
  38. 38. Kaptain
  39. 39. Mission Accomplished
  40. 40. Telecom - Blame Game
  41. 41. Enterprise App & Network Challenge
  42. 42. IT-WAR ROOM
  43. 43. Solution based on Machine learning 1. Netscout 2. Cisco lancope 3. CA Technology 4. HP 5. Riverbed 6. Extra Hop 7. Network Instruments
  44. 44. Solution By Netscout
  45. 45. AI - The Road Ahead

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