Biswanath Patel Gaurav Bubna Amit Gupta Swapnesh Garg Chandra Mohan Meena.

Post on 27-Dec-2015

220 views 3 download

Tags:

Transcript of Biswanath Patel Gaurav Bubna Amit Gupta Swapnesh Garg Chandra Mohan Meena.

Biswanath PatelGaurav Bubna

Amit GuptaSwapnesh Garg

Chandra Mohan Meena

Introduction

Definition of Intelligence.

Turing’s solution.

“Machine Learning”

Views from many disciplines.

Controversial – Extreme reactions.

“Cornerstone” of AI research.

OutlineTuring’s original 1950 paper – Addressed

objections.

Subsequent discussion over the years.

Modifications to the Imitation Game.

Present state of research – Loebner prize.

State-of-the-art – CAPTCHA.

The Imitation Game The oft-repeated question – Can machines “think”?

Turing’s version – “Can machines play the imitation game?”.

Focus on intellectual capacity

Does not limit thinking to specific tasks - any topic possible.

Initial objections & refutationsThe Theological Objection

The Mathematical Objection

Various Disabilities

Continuity of the human nervous system

Informality of Behaviour arguments

Extra-sensory perception – intuition, telepathy

Later discussions (Chronological)(1) Gunderson (1964)

‘Part of what things do is how they do it’.

The classic example – Birds vs airplanes.

“In the end, the steam drill outlasted John Henry as a digger of railway tunnels, but that didn’t prove the machine had muscles; it proved that muscles were not needed for digging railway tunnels.”

Other discussions(2) Searle’s Chinese Room (1980)

Mind's role in intelligence.

(3) Michie (1996)

"How do you pronounce the plurals of the imaginary English words ‘platch’, ‘snorp’ and ‘brell’?" (‘platchez’, ‘snorpss’ and ‘brellz’.)

Other discussions (contd.) (4) Ted Block (1995)

All possible sensible conversations stored - The set of strings constituting such conversations that can be carried out in a fixed amount of time are finite and thus can be enumerated.

Simple “lookup and write-out”- just sophisticated information processing.

Variants of the Turing TestTotal Turing Test (TTT) –

“Robotic” in addition to linguistic capabilities.Chimpanzee

Totally Total Turing Test (TTTT) –“Neuromolecular Indistinguishability”

Kugel Test (KT).Application in addition to learning.

Inverted Turing Test (ITT).Truly Total Turing Test (TRTTT).

Evolution of machines.“Types” and “tokens”

Graphics Turing TestSubjects interact with real or computer

generated scene.

Judge determines if real or not.

If the judge is unable to do so, computer passes the test.

Interactive CinemaWhen watching a movie, one wishes it turned

out differently.Plug in a laptop, make movie on the fly.Similar to video games.Each frame requires 2 hrs on 2.4 GHz

Pentium processor. At 30 fps, 2 hr movie – 216,000 computers’ power required – so present computational capability is under equipped.

State-of-the-art“By the year 2000 it would be feasible to write

a program that would, after five minutes of questioning, have at least a 30% chance of fooling an average conversational partner into believing it was a human being” – Turing

Loebner Prize – • $3000 – Best in the year.• $25,000 – A text-only test.• $ 100,000 – The final prize

ELIZAJoseph Weizenbaum, MIT, 1964-1966.Simulates a psychotherapist. Urges user to

continue talking.Simple parsing to recognize keywords.Pattern matching and substitution.

ALICE

Richard Wallace. (1995)

3 times winner of Loebner prize.

Uses AIML (XML driven open source AI language)

Supervised learning.

“Stateless conversation”

CAPTCHACompletely Automated Public Turing Test to

tell Computer and Humans Apart.

Poll Results, Email registrations, etc

Types of CaptchaVisual CaptchaAudio Captcha

Break a CaptchaTo Break down a visual captcha we have

three steps:Background SubtractionSegmentationRecognition

Captcha’s like this have been solved

ConclusionHelps advance the state of AI.

Summary of the Turing Test – A new interpretation of intelligence independent of computation.

Fermat’s Last Theorem – “Better late than never”. A similar case?

Moravec’s Paradox – Chasing after the wrong thing?

A new paradigm of AI research – future direction?

References 1) A. M. Turing. "Computing machinery and intelligence", MIND - A QUARTERLY REVIEW OF

PSYCHOLOGY AND PHILOSOPHY {p.433} [VOL. LIX. No.236.] [October, 1950]

2) http://en.wikipedia.org/

3) "Turing Test: 50 Years Later". AYSE PINAR SAYGIN , ILYAS CICEKLI & VAROL AKMAN. Minds and Machines 10: 463–518, 2000.© 2001 Kluwer Academic Publishers.

4) Harnad, S. (1991) "Other bodies, Other minds: A machine incarnation of an old philosophical problem", Minds and Machines 1: 43-54. Copyright 1992 Kluwer Academic Publishers

5)Gunderson, K. (1964), ‘The Imitation Game’, Mind 73 pp. 234–245.

6) Hofstadter, D.R. (1982), ‘The Turing Test: A Coffee-House Conversation’, in D. Hofstadter and D. Dennett, eds. The Mind’s I: Fantasies and Reflections on Self and Soul, London, UK: Penguin Books, pp. 69–95.

7) AIML : http://www.alicebot.org/TR/2001/WD-aiml/

8) Book : The Anatomy of A.L.I.C.E., Dr. Richard S. Wallace, A.L.I.C.E. Artificial Intelligence Foundation, Inc., 1995.

9) arXiv:cs/0603132v1 [cs.GR] 31 Mar 2006 Graphics Turing Test. Michael McGuigan Brookhaven National Laboratory, Upton NY 11973, mcguigan@bnl.gov