artificial_intell_final

Artificial Intelligence : 

Artificial Intelligence

What is AI? : 

What is AI? The exciting new effort to make computers thinks … machine with minds, in the full and literal sense” (Haugeland 1985) “The art of creating machines that perform functions that require intelligence when performed by people” (Kurzweil, 1990) “The study of mental faculties through the use of computational models” (Charniak et al. 1985) A field of study that seeks to explain and emulate intelligent behavior in terms of computational processes” (Schalkol, 1990) Systems that think like humans Systems that think rationally Systems that act like humans Systems that act rationally

What tasks require AI? : 

What tasks require AI? AI is the science and engineering of making intelligent machines which can perform tasks that require intelligence when performed by humans …”

What do humans do well : 

What do humans do well Process information Language Images Reason Create Relate to other humans Make intuitive decisions Experience and exhibit emotion Enjoy entertainment

What do computers do well : 

What do computers do well Process data quickly Handle large amounts of data

Computers simulating humans : 

Computers simulating humans Have to understand the process Build a good model for the process Resolve complexities Examples Chess Number of possible unique chess games is 10120. In 1957, artificial intelligence pioneers Herbert Simon and Allen Newell predicted that a computer would beat a human at chess within 10 years. BELLE, a chess program by Ken Thompson and Joe Condon, became the first computer to be awarded the title of US chess master, in 1983. BELLE didn’t try to do what a human would do. Instead, BELLE took advantage of what computers do well. In May 1997, IBM's Deep Blue Supercomputer played a fascinating match with the reigning World Chess Champion, Garry Kasparov and won 3 ½ to 2 ½

Other Successes : 

Other Successes Language understanding Eliza 1967 Speech recognition Dragon Naturally speaking Phone company systems Voice mail systems Language translation

Difficulties : 

Difficulties Humans are complex beings and understand Language issues Time flies like an arrow Fruit flies like a banana Searching for tables Table table chair 98% correct is often not enough 40 typos in a page The search space can get very large

Acting Humanly: The Turing Test : 

Acting Humanly: The Turing Test Turing (1950) "Computing machinery and intelligence“ "Can machines think?"  "Can machines behave intelligently?“ Operational test for intelligent behavior: the Imitation Game Suggests major components required for AI: - knowledge representation - reasoning, - language/image understanding, - learning * Question: is it important that an intelligent system act like a human?

Typical Machine Learning Tasks : 

Typical Machine Learning Tasks Clustering Grouping similar items together Categorization Of text, images, news, into categories Recognition Speech, Voice, Handwriting Game playing Chess Autonomous performance Robots that play soccer or navigate themselves

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Typical ML Tasks Clustering

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Typical ML Tasks Categorization

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Typical ML Tasks Recognition Vincent Van Gogh Michael Stipe Mohammed Ali Ken Williams Burl Ives Winston Churchill Grover Cleveland

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Typical ML Tasks Recognition Little red corvette The kids are all right The rain in Spain Bort bort bort

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Typical ML Tasks Game playing

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Typical ML Tasks Autonomous performance

State of the Art : 

State of the Art What would happen if we kept asking the robot why it just gave the answer that it gave an infinite number of times. Could it explain? For example: Input: How are you today? Output: Good. Input: Why "good"? Output: I'm having a lovely day. Input: Why? Output: I don't know. Input: Why don't you know? ...and so on

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What is Artificial Intelligence?(John McCarthy, Stanford University) What is artificial intelligence? It is the science and engineering of making intelligent machines, especially intelligent computer programs. It is related to the similar task of using computers to understand human intelligence, but AI does not have to confine itself to methods that are biologically observable. Yes, but what is intelligence? Intelligence is the computational part of the ability to achieve goals in the world. Varying kinds and degrees of intelligence occur in people, many animals and some machines. Isn't there a solid definition of intelligence that doesn't depend on relating it to human intelligence? Not yet. The problem is that we cannot yet characterize in general what kinds of computational procedures we want to call intelligent. We understand some of the mechanisms of intelligence and not others. More in: http://www-formal.stanford.edu/jmc/whatisai/node1.html

Academic Disciplines relevant to AI : 

Academic Disciplines relevant to AI Philosophy Logic, methods of reasoning, mind as physical system, foundations of learning, language, rationality. Mathematics Formal representation and proof, algorithms, computation, (un)decidability, (in)tractability Probability/Statistics modeling uncertainty, learning from data Economics utility, decision theory, rational economic agents Neuroscience neurons as information processing units. Psychology/ how do people behave, perceive, process cognitive Cognitive Science information, represent knowledge. Computer building fast computers engineering Control theory design systems that maximize an objective function over time Linguistics knowledge representation, grammars

History of AI : 

History of AI 1943: early beginnings McCulloch & Pitts: Boolean circuit model of brain 1950: Turing Turing's "Computing Machinery and Intelligence“ 1956: birth of AI Dartmouth meeting: "Artificial Intelligence“ name adopted 1950s: initial promise Early AI programs, including Samuel's checkers program Newell & Simon's Logic Theorist 1955-65: “great enthusiasm” Newell and Simon: GPS, general problem solver Gelertner: Geometry Theorem Prover McCarthy: invention of LISP

History of AI : 

History of AI 1966—73: Reality dawns Realization that many AI problems are intractable Limitations of existing neural network methods identified Neural network research almost disappears 1969—85: Adding domain knowledge Development of knowledge-based systems Success of rule-based expert systems, E.g., DENDRAL, MYCIN But were brittle and did not scale well in practice 1986-- Rise of machine learning Neural networks return to popularity Major advances in machine learning algorithms and applications 1990-- Role of uncertainty Bayesian networks as a knowledge representation framework 1995-- AI as Science Integration of learning, reasoning, knowledge representation AI methods used in vision, language, data mining, etc

Success Stories : 

Success Stories Deep Blue defeated the reigning world chess champion Garry Kasparov in 1997 AI program proved a mathematical conjecture (Robbins conjecture) unsolved for decades During the 1991 Gulf War, US forces deployed an AI logistics planning and scheduling program that involved up to 50,000 vehicles, cargo, and people NASA's on-board autonomous planning program controlled the scheduling of operations for a spacecraft Proverb solves crossword puzzles better than most humans Robot driving: DARPA grand challenge 2003-2007 2006: face recognition software available in consumer cameras

Intelligent Systems in Your Everyday Life : 

Intelligent Systems in Your Everyday Life Post Office automatic address recognition and sorting of mail Banks automatic check readers, signature verification systems automated loan application classification Customer Service automatic voice recognition The Web Identifying your age, gender, location, from your Web surfing Automated fraud detection Digital Cameras Automated face detection and focusing Computer Games Intelligent characters/agents

What tasks require AI? : 

What tasks require AI? Tasks that require AI: Solving a differential equation Brain surgery Inventing stuff Playing Jeopardy Playing Wheel of Fortune What about walking? What about grabbing stuff? What about pulling your hand away from fire? What about watching TV? What about day dreaming?

AI History : 

AI History

Information Retrieval Problems with Keywords : 

Information Retrieval Problems with Keywords May not retrieve relevant documents that include synonymous terms. “restaurant” vs. “café” “PRC” vs. “China” May retrieve irrelevant documents that include ambiguous terms. “bat” (baseball vs. mammal) “Apple” (company vs. fruit) “bit” (unit of data vs. act of eating)

Intelligent IR : 

Intelligent IR Taking into account the meaning of the words used. Taking into account the order of words in the query. Adapting to the user based on direct or indirect feedback. Taking into account the authority of the source.

Library and Information Science : 

Library and Information Science Focused on the human user aspects of information retrieval (human-computer interaction, user interface, visualization). Concerned with effective categorization of human knowledge. Concerned with citation analysis and bibliometrics (structure of information). Recent work on digital libraries brings it closer to CS & IR.

Topography of Artificial Intelligence : 

Topography of Artificial Intelligence Diagram illustrating the topography of AI