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Artificial intelligence
Artificial intelligence
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Artificial Intelligence

  1. 1. ARTIFICIAL INTELLIGENCE (A.I.) Narendra Kumar Institute of Pharmacy, Pt. Ravishankar Shukla University, Raipur
  2. 2. CONTENTS • INTRODUCTION • HISTORY • CURRENT STATUS • GOALS • APPLICATIONS • ADVANTAGES • DISADVANTAGES • FUTURE SCOPE • CONCLUSION
  3. 3. ARTIFICIAL INTELLIGENCE ARTIFICIAL INTELLIGENCE Intelligence: “The capacity to learn and solve problems” Artificial Intelligence: Artificial intelligence (AI) is the simulation of human intelligence by machines. • The ability to solve problems • The ability to act rationally • The ability to act like humans
  4. 4. • The artificial intelligence term was used in the year 1956, and the concept was used from the year 1950, under the topics of problem solving and symbolic methods. • Artificial Intelligence is the branch of engineering & computer science which deals with making of intelligent machines or systems that can function intelligently and independently, especially intelligent computer programs. • Artificial Intelligence is the ability of a computer or a robotic computer enabled system to process the given information and produce outcomes in a manner similar to the attention process of humans in learning, decision making, reasoning, self-correction and solving problems. Artificial intelligence is becomes an essential part of the technology industry. Research associated with artificial intelligence is highly technical and specialized.
  5. 5. Year Milestone 1943 Neurons can do logical operations like “and”, “or” or “not”, when they are connected as a network. This process was proved by Walter Pitts and Warren McCulloch. 1951 First neuronal network, which solved a problem from the real world i.e. SNARC (Stochastic Neural Analog, Reinforcement Computer) was by Marvin Minsky. 1956 At Dartmouth college conference the term “Artificial Intelligence” was coined. 1958 Perceptrons (neuronal networks that transmit information in one direction) was created by the Frank Rosenblatt which is the origin for todays AI progress. 1969 Minsky supported the symbolic representation of problems in his book - “Perceptrons”. Mile stones in the artificial intelligence process
  6. 6. Year Milestone 1974 - 1980 During this period, interest on AI was dropped, which is called as “First AI Winter”. 1986 Back propagation algorithm design was developed by Georey Hinton which is widely using in deep learning nowadays. 1987 - 1993 This phase is called as “AI winter” 1997 This year IBM Deep blue defeated the Garry Kasparov (Russian grandmaster). 2013 Google used the British technology to perform efficient research on photos. 2016 Google DeepMind, software AlphaGo defeated the Go Champion Lee Sedol. 2016 Humanoid robot developed by Hong Kong based company Hanson Robotics Sophia was activated on February 14, 2016
  7. 7. A.I. TIMELINE
  8. 8. EARLY HISTORY OF A.I. 1950 : “CAN MACHINES THINK??????” 1956 : THE TERM “ARTIFICIALINTELLIGENCE” WAS FIRST INTRODUCED.
  9. 9. • Analyse Satellite Images to identify which areas have the highest poverty level • Gate allocationfor plane while landing • Tickt price determination • Companies are creating robots to teach subjects A.I. FOR GOOD AVIATION EDUCATION
  10. 10. • Solving a variety of problems of patients, hospitals & healthcare industry overall. • Using Avatars in place of patients. • Robots have become very common in many industries • Can do repetitive laborious tasks • Algorithmic Trading • Market analysis & data mining • Personal Finance • Portfolio management HEALTH CARE HEAVY INDUSTRY FINANCE
  11. 11. • To develop algorithms that human use. • Algorithms can require enormous computational resources and problem goes beyond a certain size • Knowledge Representation : To build machine with the capability of making working assumption and common sense.
  12. 12. • Planning :  In classical planning problems, the agent can assume that it is the only system acting on the world  Multi-agent planning uses the cooperation and competition of many agents to achieve the given goal. • Learning :  Machine learning is the fundamental concept of AI search.  Unsupervised learning is the ability to find patterns in s stream of input  Supervised learning includes both classification and numerical regression
  13. 13. To understand what artificial intelligence is, we need to know how it works and what are the Subfields and components that make machines work intelligently. Speech Recognition Humans can speak and listen to communicate through language; this is the field of speech recognition. Since speech recognition is statistically based, hence it’s called statistical learning. Natural Language Processing Humans can write and read the text in a language; this is the field of NLP or natural language processing. Working, Subfields and Components
  14. 14. Machine Vision Humans can see with their eyes and process what they see; this is the field of computer vision. Computer vision falls under the symbolic way for computers to process information. Moreover, they can recognize the surroundings around them through their eyes which create images of that world. This field of image processing which even though is not directly related to AI is required for computer vision. Robotics Humans can understand their environment and move around fluidly; this is the field of robotics. Pattern Recognition Humans can see patterns such as grouping of like objects; this is the field of pattern recognition. Machines are even better at pattern recognition because they can use more data and dimensions of data, this is the field of machine learning.
  15. 15. Types of artificial intelligence:- Artificial Intelligence is a wide-ranging concept and can be classified into a number of ways. Based upon their caliber:- 1. Weak intelligence or Artificial narrow intelligence (ANI): This system is designed and trained to perform a narrow task, such as facial recognition, driving a car, playing chess, traffic signaling. E.g.: Apple SIRI virtual personal assistance, tagging in social media. 2. Artificial General Intelligence (AGI) or Strong AI : It is also called as Human Level AI. It has the ability to simplify human intellectual abilities. Due to this, when it exposed to an unfamiliar task, it has the ability to find the solution. AGI can perform all the things as humans. 3. Artificial Super intelligence (ASI): It is a brain power, which is more active than smart humans drawing, mathematics, space, etc; in each and every field from science to art. It ranges from the computer just little than the human to trillion times smarter than humans.
  16. 16. AI Representation
  17. 17. APPROACHES OF A.I.
  18. 18. Drug discovery process Health support and medication assistance Attainment of in person and online consultation Helping in repetitive jobs Maintaining of medical records Accuracy of medicine Diagnostic and imaging sector Competition & prizes Automotive Finance &Economics Video games Applications of Artificial Intelligence:
  19. 19. Health care application Representative company AI Technology platform Key benefits Analytics 4 life is pioneering digital health using AI to develop a completely new form of medical imaging. With an initial focus on coronary artery disease (CAD). It is a novel radiation free and exercise free cardiac imaging technology. Physicians can noninvasively assess the presence of significant CAD in a single office visit without radiation, exercise or pharmacological stressors using physiologic signals naturally emitted by the body. By using this platform to cardiac phase space tomography analysis (cPSTA) data and paired coronary angiography results it developed its initial product focused on CAD. Delivers an improved diagnostic solution previously available only through invasive, expensive tests providing immediate and measurable benefits to patients, payers and providers. Intelligent diagnostics
  20. 20. Health care application Representative company AI Technology platform Key benefits It offers a machine intelligence software platform, Topological data analysis (TDA), that enables organizations to analyze and build predictive models using big data or highly dimensional data sets. It allow healthcare providers and pharmaceutical companies to automatically stratify complex data and uncover relationships to optimize patent care paths., procedures and protocols for personalized medicine leading to faster and more effective outcomes. The TDA platform draws on a range of machine learning statistical and genomic algorithms to combine and synthesize them in accordance with the data. Patient and provider data base
  21. 21. Health care application Representative company AI Technology platform Key benefits It uses it's advanced proprietary AI that can be applied to manage publicly and privately available noisy data. Helps uncover valuable biology not easily translated by the traditional approaches enabling faster lead design and candidate identification while reducing development costs and attrition rates. It developed a technology that can model most important absorption, distribution, metabolism and excretion properties in the drug development process Drug discovery process with advanced analytics
  22. 22. Health care application Representative company AI Technology platform Key benefits It developed robotic assisted surgical products with a platform that includes advanced imaging, robotics, big data management and machine learning to provide advanced surgical tools and capabilities to surgeons. Expected to be only 20% the size of and considerably less expensive than current systems, while improving quality of precision and patient outcomes significantly. Focus on improving and standardizing the outcomes in challenging procedures such as thoracic lobectomy, gastrectomy and low anterior resection. Medical devices and robotics
  23. 23. Health care application Representative company AI Technology platform Key benefits It uses AI to contextualize data regarding a patient’s health status and self management behavior to provide early detection of potentially harmful health events. Significantly impacts health care quality and cost by improving self- management and enabling proactive interventions. At the core of Ibis platform lies Scio, an AI brain which allows complex health management via a continuous five-step AI process including observation, learning, discovering, anticipating and prompting With this system, upto 80% comply with their care plan versus a control 50% norm. Significantly reduces acute care utilization. Home health using A. I.
  24. 24. Artificial intelligence : healthcare diagnostic and scope
  25. 25. Error Reduction - Artificial Intelligence helps human beings to reduce the error and increases the chance of reaching accuracy with more precision. Daily Application - Artificial Intelligence is useful for the daily application purpose. Everyone widely uses the GPS system, which is helpful in long Drives. Digital Assistants - Artificial Intelligence systems ‘avatar’ which are models of digital assistants are used by advanced organizations to reduce the need for human resources. The avatars are free of emotional thinking, so they think logically and take right decisions. Human emotions are generally associated with moods that disturb the judgments and affect the human efficiency. Repetitive Jobs & multi - tasking - Humans can do only one task at a time. Machines can perform multi-tasking and can think faster than human beings. Machines can perform dangerous tasks and their parameters can be adjusted i.e. speed and time. No Breaks - Humans can work 8 hours per day with 2 or 3 breaks. Unlike human beings machines do not require frequent breaks and refreshment.
  26. 26. Medical Applications - Nowadays, the physicians are assessing the patients and analyzing the health risks with the help of Artificial Intelligence. Artificial Intelligence program is educating the physicians about various medicines and their side effects. Training surgeons are gaining knowledge with the help of simulators of artificial surgery. They are trained with the help of artificial surgery simulators viz., brain simulation, heart simulation, GIT simulation etc. No risk of harm - when human beings are working at the fire stations, if some mishap happens, it causes harm to the personnel. While in the case of machines, they don’t feel and have emotions. Also, If machines are broken, it is possible to mantle the parts. Act as aids - Machines which have AI technology can be used to serve children with disability or the elders on a 24/7 basis. They act as a source for teaching and learning. They are also useful in security alerting in fires, robbery in banks and in difficult climatic conditions. Limitless functions - Machines do not have any boundaries; they do everything better than humans. They are emotionless, more efficient, more accurate and provide more free time to us.
  27. 27.  High cost  Decrease in demand for human labour  AI may be programmed to do somethingdevastating  Machine Ethics  Thestorage and access are not as effective as human brains  No improvement with experience Disadvantages of A.I.
  28. 28.  Improved speech, voice, image, video recognition will change the way devices.  Personal assistants will become more personal and context aware.  More and more systems will run autonomously to a point  The positive impact AI research can have on humanity, will start to be across many walks of life - much of it behind the scenes
  29. 29. CONCLUSION  A.I. is a common topic in both Science Fiction & Projection.  The future of Technology & society. Rivals Human Intelligence. Raises difficult Ethical Issues
  30. 30. A.I. Is like two edged sword, at one end they can solve problems intelligently, at another end they pose a problem themselves…. So we have to handle it properly. I Am Good Or Bad ??? It’s Depends on who Created

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