• Study Resource
  • Explore Categories
    • Arts & Humanities
    • Business
    • Engineering & Technology
    • Foreign Language
    • History
    • Math
    • Science
    • Social Science

    Top subcategories

    • Advanced Math
    • Algebra
    • Basic Math
    • Calculus
    • Geometry
    • Linear Algebra
    • Pre-Algebra
    • Pre-Calculus
    • Statistics And Probability
    • Trigonometry
    • other →

    Top subcategories

    • Astronomy
    • Astrophysics
    • Biology
    • Chemistry
    • Earth Science
    • Environmental Science
    • Health Science
    • Physics
    • other →

    Top subcategories

    • Anthropology
    • Law
    • Political Science
    • Psychology
    • Sociology
    • other →

    Top subcategories

    • Accounting
    • Economics
    • Finance
    • Management
    • other →

    Top subcategories

    • Aerospace Engineering
    • Bioengineering
    • Chemical Engineering
    • Civil Engineering
    • Computer Science
    • Electrical Engineering
    • Industrial Engineering
    • Mechanical Engineering
    • Web Design
    • other →

    Top subcategories

    • Architecture
    • Communications
    • English
    • Gender Studies
    • Music
    • Performing Arts
    • Philosophy
    • Religious Studies
    • Writing
    • other →

    Top subcategories

    • Ancient History
    • European History
    • US History
    • World History
    • other →

    Top subcategories

    • Croatian
    • Czech
    • Finnish
    • Greek
    • Hindi
    • Japanese
    • Korean
    • Persian
    • Swedish
    • Turkish
    • other →
 
Profile Documents Logout
Upload
Beyond robotics
Beyond robotics

... Beyond Robotics New European research initiative Pekka Karp Future and Emerging Technologies DG Information Society ...
Symbolic Processing * CSCE 3210
Symbolic Processing * CSCE 3210

... 3. Understand basic principles of Search, two player games and neural networks. 4. Understand one or more application in Artificial Intelligence. Course Description: The course isn’t REALLY suppose to be about Artificial Intelligence, but a lot of symbolic processing deals with problems related to a ...
Expert System - Clydebank High School
Expert System - Clydebank High School

... Processor of a computer is known as the ‘brains’ of a computer. However, a processor cannot think or act for itself. Computers do have some form of intelligence this is know as Artificial Intelligence. ...
Jayden Clark - Young Tassie Scientists
Jayden Clark - Young Tassie Scientists

... My research in neuroscience uses this ‘tool of the trade’ to help me see the cells that are affected in motor neuron disease. This means that I can look at motor neuron cells during the disease and see at what point they start to look sick, or to see if a particular drug is starting to work. I like ...
Symbolic Processing * CSCE 3210
Symbolic Processing * CSCE 3210

... 3. Understand basic principles of Search, two player games and neural networks. 4. Understand one or more application in Artificial Intelligence. Course Description: The course isn’t REALLY suppose to be about Artificial Intelligence, but a lot of symbolic processing deals with problems related to a ...
Introduction to Artificial Intelligence
Introduction to Artificial Intelligence

... Approach (2nd edition*), Russell and Norvig • Final Exam: Tuesday, Dec 15, 2:30-4:20pm 2 ...
news summary (20)
news summary (20)

... University of Toronto. They are named after Terry Winograd, a pioneer in the field and a professor at Stanford University who built one of the first conversational ...
PPT - How do I get a website?
PPT - How do I get a website?

... 1956 Dartmouth meeting: “Artificial Intelligence” adopted ...
The Experience of a Leader in Innovation. The Case of Finland.
The Experience of a Leader in Innovation. The Case of Finland.

... Source: DG Research Data: Eurostat, Memger State, OECED Notes: ...
Why Has AI Failed? And How Can it Succeed?
Why Has AI Failed? And How Can it Succeed?

... included a tree diagram in his introduction to Aristotle’s categories. In the 14th c, Ramon Lull combined the tree of Porphyry with rotating circles as a method for relating categories to generate new ones. After studying Lull’s rotating circles, Leibniz developed an equivalent numeric method: map p ...
ai lect1
ai lect1

... discovers computational complexity Neural network research almost disappears Early development of knowledge-based systems AI becomes an industry Neural networks return to popularity AI becomes a science The emergence of intelligent agents ...
Prof
Prof

... with the interdisciplinary group of researchers she has formed, is working in parallel in vitro, in vivo and clinically, in a research institute placed in the heart of a large hospital. Yael collaborates closely with physicians from within the hospital or from other hospitals, academia from Israel a ...
Artificial Intelligence
Artificial Intelligence

... The concept of Artificial Intelligence (AI) often conjures up pop-culture images, such as HAL (9000) or the Terminator, depending upon your age. Although fictional, these machines embody the definition of AI, whereby a machine carries out functions generally associated with being human, including re ...
CISC 3410 - Brooklyn College
CISC 3410 - Brooklyn College

... Brooklyn College Department of Computer and Information Science ...
Overview and History
Overview and History

... success with expert systems, neural nets revisited, 5th Generation Project • XCON (McDermott): saved DEC ~ $40M per year • neural computing: back-propagation (Werbos), associative memory (Hopfield) • logic programming, specialized AI technology seen as future ...
Artificial Intelligence, Neural Nets and Applications
Artificial Intelligence, Neural Nets and Applications

... comeback—The Economist, March 14, 2002. The AI-development community has generated techniques that are beginning to show promise for solving real business problems involving complex data in dynamic environments—McKinsey Quarterly, Number 2, 2002. ...
Materialy/06/Lecture2- ICM Artificial Intelligence
Materialy/06/Lecture2- ICM Artificial Intelligence

... Problems of man-machine communication, robotics, expert systems, machine learning, neuronal nets, genetic algorithms... ) ...
AI Introduction PDF document
AI Introduction PDF document

... Who is Alan Turing? Who is Alan Turing? • Began Began scientific career early 1930s scientific career early 1930s • During second world war, he was key player in  g german military encoding machine y g • After war, designed automatic computing engine,  wrote first program for complete chess game p ...
Introduction to Artificial Intelligence
Introduction to Artificial Intelligence

... program, Newell & Simon's Logic Theorist, Gelernter's Geometry Engine Robinson's complete algorithm for logical ...
Artificial Intelligence BA635
Artificial Intelligence BA635

...  Narrow AI - An artificial intelligence system which is not intended to match or exceed the capabilities of human beings  Strong AI – An artificial intelligence that matches or exceeds human intelligence ...
Humans + Machines: - Tulane School of Architecture
Humans + Machines: - Tulane School of Architecture

... There is little doubt that Artificial Intelligence (AI) is at the core of many promising and exciting technologies that are shaping humanity’s relationship with its future. AI’s influential rise is responsible for very advanced systems both large and small. Many of these we interface with on a daily ...
Research - Stanford HCI Group
Research - Stanford HCI Group

... Slide courtesy Stu Card ...
The Dartmouth College Artificial Intelligence Conference: The Next
The Dartmouth College Artificial Intelligence Conference: The Next

... face, and win the DARPA Grand Challenge in a race of 132 miles in the Mojave Desert. Rus speculated that in the future we might have our own personal robots as we now have our own personal computers, robots that could be tailored to help us with the kind of activities that each of us wants to do. Ro ...
AI_Lecture_1 - Computer Science Unplugged
AI_Lecture_1 - Computer Science Unplugged

... Early AI programs, including Samuel's checkers program, Newell & Simon's Logic Theorist, ...
Ch1 - shilepsky.net
Ch1 - shilepsky.net

... 6. Answers that are neither exact nor optimal, but are in some sense “sufficient.” This is a result of the essential reliance on heuristic problem-solving methods in situations where optimal or exact results are either too expensive or not possible. ...
< 1 ... 136 137 138 139 140 141 142 >

AI winter

In the history of artificial intelligence, an AI winter is a period of reduced funding and interest in artificial intelligence research. The term was coined by analogy to the idea of a nuclear winter. The field has experienced several hype cycles, followed by disappointment and criticism, followed by funding cuts, followed by renewed interest years or decades later. There were two major winters in 1974–80 and 1987–93 and several smaller episodes, including: 1966: the failure of machine translation, 1970: the abandonment of connectionism, 1971–75: DARPA's frustration with the Speech Understanding Research program at Carnegie Mellon University, 1973: the large decrease in AI research in the United Kingdom in response to the Lighthill report, 1973–74: DARPA's cutbacks to academic AI research in general, 1987: the collapse of the Lisp machine market, 1988: the cancellation of new spending on AI by the Strategic Computing Initiative, 1993: expert systems slowly reaching the bottom, and 1990s: the quiet disappearance of the fifth-generation computer project's original goals.The term first appeared in 1984 as the topic of a public debate at the annual meeting of AAAI (then called the ""American Association of Artificial Intelligence""). It is a chain reaction that begins with pessimism in the AI community, followed by pessimism in the press, followed by a severe cutback in funding, followed by the end of serious research. At the meeting, Roger Schank and Marvin Minsky—two leading AI researchers who had survived the ""winter"" of the 1970s—warned the business community that enthusiasm for AI had spiraled out of control in the '80s and that disappointment would certainly follow. Three years later, the billion-dollar AI industry began to collapse.Hypes are common in many emerging technologies, such as the railway mania or the dot-com bubble. An AI winter is primarily a collapse in the perception of AI by government bureaucrats and venture capitalists. Despite the rise and fall of AI's reputation, it has continued to develop new and successful technologies. AI researcher Rodney Brooks would complain in 2002 that ""there's this stupid myth out there that AI has failed, but AI is around you every second of the day."" In 2005, Ray Kurzweil agreed: ""Many observers still think that the AI winter was the end of the story and that nothing since has come of the AI field. Yet today many thousands of AI applications are deeply embedded in the infrastructure of every industry."" He added: ""the AI winter is long since over.""
  • studyres.com © 2026
  • DMCA
  • Privacy
  • Terms
  • Report