• Study Resource
  • Explore
    • 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
Chapter13
Chapter13

... • Discuss types of problems that – humans do best – computers do best ...
PDF
PDF

... Forty years later, machines can’t do what we do and speech technology is far short of comprehending context at human skill levels. Fortunately, there was a hole in Negroponte’s logic. Computers are not dangerous as long as they remain tools controlled by people who understand the context. At the tim ...
CS 561: Artificial Intelligence CS 561: Artificial Intelligence
CS 561: Artificial Intelligence CS 561: Artificial Intelligence

... „ convened the Dartmouth conference that coined the term artificial intelligence (AI) (1956) and set the research agenda „ symbolic AI „ connectionism st AI language „ LISP (list processing) 1958 1 ...
Introduction to Computational Intelligence Business
Introduction to Computational Intelligence Business

... corporate information systems. Evolutionary algorithms, inspired in biological evolution and natural selection, emerged in the 1970s with the introduction of genetic algorithms [22, 23]. Many other ramifications and specializations were developed in the following decades, for instance genetic program ...
Research Priorities for Robust and Beneficial Artificial Intelligence
Research Priorities for Robust and Beneficial Artificial Intelligence

... defined with respect to a fixed and known machine model, whereas AI systems — especially robots and other embodied systems — operate in environments that are at best partially known by the system designer. In these cases, it may be practical to verify that the system acts correctly given the knowled ...
Slides - UMBC CSEE
Slides - UMBC CSEE

01 - Computer Science and Electrical Engineering
01 - Computer Science and Electrical Engineering

... which drastically limits search for solutions in large problem spaces • Heuristics don’t guarantee optimal solutions or even any solution at all: all that can be said for a useful heuristic is that it offers solutions which are good enough most of the time ...
Artificial Intelligence
Artificial Intelligence

... at the touch of a button. • Driverless trains carry passengers from city to city in Japan without the need for human help. • Google’s driverless car relies on lasers and sensors to spot obstacles, interpret signs and interact with traffic and pedestrians. • Artificial intelligence takes away the res ...
CV - Angelfire
CV - Angelfire

m1-intro
m1-intro

... Robinson's complete algorithm for logical reasoning AI 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 ...
2.04
2.04

... using the Internet or other technology Most common activities of E-Commerce: ...
1. W01-Definition
1. W01-Definition

... McCulloch & Pitts: Boolean circuit model of brain Turing’s “Computing Machinery and Intelligence” Early AI programs Dartmouth meeting: “Artificial Intelligence” adopted Robinson’s complete algorithm for logical reasoning AI discovers computational complexity Neural network research almost disappears ...
ACTIVITY DUE March 26th
ACTIVITY DUE March 26th

... future of artificial intelligence and of computers in general. To date, however, they have not lived up to expectations. Many expert systems help human experts in such fields as medicine and engineering, but they are very expensive to produce and are helpful only in special situations. Today, the ho ...
E-Learning Using Artificial Intelligence
E-Learning Using Artificial Intelligence

... and its applications in the area of e-learning have played an important role to impart intelligence in e-learning tools and techniques. For about last two decades, the internet is being used to improve communication, collaboration, sharing of resources, promoting active learning, and delivery of edu ...
To append for course “Soft computing”
To append for course “Soft computing”

... 14. Natural language processing Problems Kinds of NLP-systems Review of methods of NLP, Review of use of neural networks in NLP systems, Architecture of learning software for search of documents by query on Natural Language Introduction to speech recognition 15. Conclusions. The future of Artificial ...
An introduction to artificial intelligence applications in petroleum
An introduction to artificial intelligence applications in petroleum

... think that it is doomed by the emergence of massively parallel computing. Expert systems (Fig. 3), also known as KnowledgeBased Systems (KBS), are programs that contains a knowledge base and a set of algorithms or rules that infer new facts from knowledge and from incoming data. An expert system use ...
Ph. D RESEARCH PROPOSAL BY EWUNONU, TOOCHI CHIMA.
Ph. D RESEARCH PROPOSAL BY EWUNONU, TOOCHI CHIMA.

... activities and by extension, has become a viable area for research, implementation and development. It is also a willing tool to the clamour for automation in many activities and sectors of national existence. This research promises to be a strong voice in this evolving area of optical networks and ...
Over two decades of innovative applications of AI at AIAI
Over two decades of innovative applications of AI at AIAI

... Artificial Intelligence Applications Institute Over two decades of innovative applications of AI at AIAI. Some of our key achievements include:  Formation - a system to lay out all British Telecom Yellow Pages directories and to create a new business area for Pindar Set Ltd for responsive marketing ...
Introduction
Introduction

...  Logicians in the 19th century: a precise notation for statements about all kinds of objects and relations among them  By 1965 programs existed for solving “in principle” any problem in logistic notation ...
Datasheet (0.1MB PDF File)
Datasheet (0.1MB PDF File)

... Artificial Intelligence Applications Institute Over two decades of innovative applications of AI at AIAI. Some of our key achievements include: ⎯ Formation - a system to lay out all British Telecom Yellow Pages directories and to create a new business area for Pindar Set Ltd for responsive marketing ...
Chapter One - WordPress.com
Chapter One - WordPress.com

... thousands of years, we have tried to understand how we think; that is, how a mere handful of matter can perceive, understand, predict, and manipulate a world far larger and ARTIFICIAL more complicated than itself. The field of artificial intelligence, or AI, goes further still: it INTELLIGENCE attem ...
Perspectives on Stochastic Optimization Over Time
Perspectives on Stochastic Optimization Over Time

... Motivated by the discussion in Powell (2010), I offer a few comments on the interactions and merging of stochastic optimization research in artificial intelligence (AI) and operations research (OR), a process that has been ongoing for more than a decade. In a broad sense, decision making over time a ...
File - Justine Faith M. Tabligan
File - Justine Faith M. Tabligan

... bicentennial man, Andrew was called a household appliance. In his programming, a human can command him to do anything and he must obey. But after he jumped out of the window, he had defects that he started acting differently. He has always been nice and friendly but after the incident, he started do ...
Five ways the superintelligence revolution might happen
Five ways the superintelligence revolution might happen

P2P Distributed Artificial Intelligence
P2P Distributed Artificial Intelligence

... • Secrecy: agents keep some part of their internal state secret • Money: forwading and task completion means money income, agents try to increase their wealth • Added value: wealth coming from outside of the system • Discounts: forwarders of large amounts get lower prices • Time limitation: processi ...
< 1 ... 98 99 100 101 102 103 104 105 106 ... 143 >

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 © 2025
  • DMCA
  • Privacy
  • Terms
  • Report