Introduction to AI.pptx
- 1. AN INTRODUCTION TO ARTIFICIAL INTELLIGENCE 1 Dept of COMPUTER SCIENCE & ENGINEERING, SCMS School of Engineering & Technology
- 2. 2 • Artificial intelligence (AI), sometimes called machine intelligence, is intelligence demonstrated by machines, in contrast to the natural intelligence displayed by humans and other animals, such as "learning" and "problem solving. . ⮚ In computer science AI research is defined as the study of "intelligent agents": any device that perceives its environment and takes actions that maximize its chance of successfully achieving its goals
- 3. HOW ARE HUMANS INTELLIGENT ? • Learning • Reasoning • Problem Solving and Creativity • Social Behavior • Experiencing our Environment with our senses: • Hearing • Sight • Touch • Taste • Smelling 3
- 4. 4
- 5. 5 Ways that People Think and Learn About Things • If you have a problem, think of a past situation where you solved a similar problem. • If you take an action, anticipate what might happen next. • If you fail at something, imagine how you might have done things differently. • If you observe an event, try to infer what prior event might have caused it. • If you see an object, wonder if anyone owns it. • If someone does something, ask yourself what the person's purpose was in doing that.
- 6. This is what Humans do best Can you list the items in this picture ? A computer might have trouble identifying the cat there. Can you count the distribution of letters in a book? Add a thousand 4-digit numbers? Match finger prints? Search a list of a million values for duplicates6? For example, writing a program to pick out objects in a picture: This is what Computers do best Artificial intelligence (AI) - The study of computer systems that attempt to model and apply the intelligence of the human mind.
- 7. When we compare Humans to Machines, it is important to note that a Machine can be a car, a Smart Phone, a Digital Television, etc. 7
- 8. 8
- 9. 9 The illustration below illustrates a typical information flow between the "human" and "machine" components of a system. For a properly designed system, its important to know the capabilities and flexibilities of both. https://www.hf.faa.gov/webtraining/HFModel/HFInterModel/overview.ht
- 10. 10
- 11. KEY RESEARCH AREAS IN AI • Problem solving, planning, and search --- generic problem solving architecture based on ideas from cognitive science (game playing, robotics). • Knowledge Representation – to store and manipulate information (logical and probabilistic representations) • Automated reasoning / Inference – to use the stored information to answer questions and draw new conclusions • Machine Learning – intelligence from data; to adapt to new circumstances and to detect and extrapolate patterns • Natural Language Processing – to communicate with the machine • Computer Vision --- processing visual information • Robotics --- Autonomy, manipulation, full integration of AI capabilities 11
- 12. 12 From SIRI and Alexa, to self-driving cars, artificial intelligence (AI) is progressing rapidly. While science fiction often portrays AI as robots with human-like characteristics, AI can encompass anything from Google’s search algorithms, to IBM’s Watson, to autonomous weapons. Artificial intelligence today is properly known as narrow AI (or weak AI), in that it is designed to perform a narrow task such as only facial recognition, or only internet searches, or only driving a car). However, the long-term goal of many researchers is to create general AI (AGI or strong AI). While narrow AI may outperform humans at whatever its specific task is, like playing chess or solving equations, AGI would outperform humans at nearly every thinking task.
- 13. 13
- 14. Artificial Intelligence (AI) has entered our daily lives like never before and we are yet to unravel the many other ways in which it could flourish. All of the tech giants such as Microsoft, Uber, Google, Facebook, Apple, Amazon, Oracle, Intel, IBM or Twitter are competing in the race to lead the market and acquire the most innovative and promising AI businesses. 14
- 15. 15
- 16. 16
- 17. 17
- 18. https://www.youtube.com/watch?v=GoXp1leA5Q c Google announced their Duplex system, a new technology for conducting natural conversations to carry out “real world” tasks over the phone. The technology is directed towards completing specific tasks, such as scheduling certain types of appointments. For such tasks, the system makes the conversational experience as natural as possible, allowing people to speak normally, like they would to another person, without having to adapt to a machine. 18
- 19. 19
- 21. 21
- 22. 22
- 23. 23 The answer is all of the above. Each of these highly realistic images were created by generative adversarial networks, or GANs. GAN, a concept introduced by Google researcher Ian Goodfellow in 2014, taps into the idea of “AI versus AI.” There are two neural networks: the generator, which comes up with a fake image (say a dog for instance), and a discriminator, which compares the result to real-world images and gives feedback to the generator on how close it is to replicating a realistic image.
- 24. 24
- 25. 25
- 26. 26