The Age of Spiritual Machines: When Computers Exceed Human Intelligence (57 page)
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Authors: Ray Kurzweil
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17
Raymond Kurzweil, The Age of Intelligent Machines (Cambridge, MA: MIT Press, 1990), pp. 132-133.
Raymond Kurzweil, The Age of Intelligent Machines (Cambridge, MA: MIT Press, 1990), pp. 132-133.
18
H. J. Berliner, “Backgammon Computer Program Beats World Champion,” Artificial Intelligence 14, no. 1 (1980). Also see Hans Berliner, “Computer Backgammon,” Scientific American, June 1980.
H. J. Berliner, “Backgammon Computer Program Beats World Champion,” Artificial Intelligence 14, no. 1 (1980). Also see Hans Berliner, “Computer Backgammon,” Scientific American, June 1980.
19
To download Ray Kurzweil’s Cybernetic Poet (RKCP), go to: <
http://www.kurzweiltech.com
>. RKCP is further discussed in the section The Creative Machine in chapter 8, “1999.”
To download Ray Kurzweil’s Cybernetic Poet (RKCP), go to: <
http://www.kurzweiltech.com
>. RKCP is further discussed in the section The Creative Machine in chapter 8, “1999.”
20
See the discussion on these music composition programs in the section The Creative Machine in chapter 8, “1999.”
See the discussion on these music composition programs in the section The Creative Machine in chapter 8, “1999.”
21
See W S. Sarle, ed., “Neural Network Frequently Asked Questions,” <
ftp://ftp.sas. com/pub/neural/FAQ.html
>. This web site has numerous resources on past and current research on neural nets. G. E. Hinton’s “How Neural Networks Learn from Experience,” in the September 1992 issue of Scientific American (144-151), also provides a good introduction to neural networks.
See W S. Sarle, ed., “Neural Network Frequently Asked Questions,” <
ftp://ftp.sas. com/pub/neural/FAQ.html
>. This web site has numerous resources on past and current research on neural nets. G. E. Hinton’s “How Neural Networks Learn from Experience,” in the September 1992 issue of Scientific American (144-151), also provides a good introduction to neural networks.
22
Researchers at the Productivity from Information Technology (PROFIT) Initiative at MIT have studied the effectiveness of neural networks in understanding handwriting.
Researchers at the Productivity from Information Technology (PROFIT) Initiative at MIT have studied the effectiveness of neural networks in understanding handwriting.
The PROFIT Initiative is based at MIT’s Sloan School of Management. The mission of the initiative is to study how the private and public sectors use information technology. Abstracts of working papers on this and other research on neural networks and data mining can be found at <
http://scanner-group.mit.edu/papers.html
>.
http://scanner-group.mit.edu/papers.html
>.
23
“Miros, Inc. is located in Wellesley, Massachusetts, and specializes in providing face recognition software. Miros’ products include TrueFace PC, the first face recognition solution for computer, network and data security; and TrueFace GateWatch, a complete hardware/software security solution that allows or denies access to buildings and rooms by automatically recognizing a person’s face taken by a video camera.” From Miros Company Information at <
http://www.miros.com/About_Miros.htm
>.
“Miros, Inc. is located in Wellesley, Massachusetts, and specializes in providing face recognition software. Miros’ products include TrueFace PC, the first face recognition solution for computer, network and data security; and TrueFace GateWatch, a complete hardware/software security solution that allows or denies access to buildings and rooms by automatically recognizing a person’s face taken by a video camera.” From Miros Company Information at <
http://www.miros.com/About_Miros.htm
>.
24
For more information on BrainMaker’s aptitude to diagnose illnesses, and to predict the Standard and Poor 500 for LBS Management, see California Scientific’s home page at <
http://wwwcalsci.com/
>.
For more information on BrainMaker’s aptitude to diagnose illnesses, and to predict the Standard and Poor 500 for LBS Management, see California Scientific’s home page at <
http://wwwcalsci.com/
>.
25
The reset time stated here is an estimated average for neural connection calculations.
The reset time stated here is an estimated average for neural connection calculations.
For example, Vadim Gerasimov estimates the peak firing frequency of neurons (which significantly exceeds the average rate) to be 250-2,000 Hz (0.5-4 ms intervals) in “Information Processing in the Human Body” at <
http://vadim.www.media.mit.edu/MAS862/Project.html
>. The firing time is affected by a number of variables, including, for example, the level and duration of a sound, as discussed in Jos. J. Eggermont, “Firing Rate and Firing Synchrony Distinguish Dynamic from Steady State Sound,” NeuroReport 8, issue 12, 2709-2713.
http://vadim.www.media.mit.edu/MAS862/Project.html
>. The firing time is affected by a number of variables, including, for example, the level and duration of a sound, as discussed in Jos. J. Eggermont, “Firing Rate and Firing Synchrony Distinguish Dynamic from Steady State Sound,” NeuroReport 8, issue 12, 2709-2713.
26
Hugo de Garis maintains a web site on his research for ATR’s Brain Builder Group at <
http://www.hip.atr.co.jp/~degaris/
>.
Hugo de Garis maintains a web site on his research for ATR’s Brain Builder Group at <
http://www.hip.atr.co.jp/~degaris/
>.
27
For an intriguing account of this research, read Carver Mead, Analog VSLI and Neural Systems (Reading, MA: Addison-Wesley, 1989), 257-278. Synaptics is briefly highlighted in Carol Levin, “Here’s Looking at You,” PC Magazine (December 20, 1994): 31. Carver Mead’s web site also provides detailed information on this research at the “Physics of Computation-Carver Mead’s Group” at <
http://www.pcmp.caltech.edu/
>.
For an intriguing account of this research, read Carver Mead, Analog VSLI and Neural Systems (Reading, MA: Addison-Wesley, 1989), 257-278. Synaptics is briefly highlighted in Carol Levin, “Here’s Looking at You,” PC Magazine (December 20, 1994): 31. Carver Mead’s web site also provides detailed information on this research at the “Physics of Computation-Carver Mead’s Group” at <
http://www.pcmp.caltech.edu/
>.
28
The SETI (Search for Extraterrestrial Intelligence) Institute conducts research on other signs of life in the Universe, its primary goal being the search for extraterrestrial intelligence. The institute is a nonprofit research organization, funded by government agencies, private foundations, and individuals, which in turn provides funding for several dozen projects. For more information, see the SETI Institute web site, <
http://www.seti.org
>.
The SETI (Search for Extraterrestrial Intelligence) Institute conducts research on other signs of life in the Universe, its primary goal being the search for extraterrestrial intelligence. The institute is a nonprofit research organization, funded by government agencies, private foundations, and individuals, which in turn provides funding for several dozen projects. For more information, see the SETI Institute web site, <
http://www.seti.org
>.
29
The author is dictating portions of this book to his computer through the continuous speech recognition program called Voice Xpress Plus from the dictation division of Lernout & Hauspie (formerly Kurzweil Applied Intelligence). See note 9 on Voice Xpress Plus in chapter 2 for more information.
The author is dictating portions of this book to his computer through the continuous speech recognition program called Voice Xpress Plus from the dictation division of Lernout & Hauspie (formerly Kurzweil Applied Intelligence). See note 9 on Voice Xpress Plus in chapter 2 for more information.
30
To find out more on State Street Global Advisor’s purchase in a majority stake in Advanced Investment Technology, read Frank Byrt, “State Street Global Invests in Artificial Intelligence.” Dow Jones Newswires, October 29, 1997. The genetic algorithm system used by the AIT Vision mutual fund is described in S. Mahfoud and G. Mani, “Financial Forecasting Using Genetic Algorithms.” Applied Artificial Intelligence 10 (1996): 543-565. The AIT Vision mutual fund opened at the beginning of 1996 and has publicly available performance numbers. In its first full calendar year (1996), the mutual fund increased 27.2 percent in net asset value, compared to 21.2 percent for its benchmark, the Russell 3000 index.
To find out more on State Street Global Advisor’s purchase in a majority stake in Advanced Investment Technology, read Frank Byrt, “State Street Global Invests in Artificial Intelligence.” Dow Jones Newswires, October 29, 1997. The genetic algorithm system used by the AIT Vision mutual fund is described in S. Mahfoud and G. Mani, “Financial Forecasting Using Genetic Algorithms.” Applied Artificial Intelligence 10 (1996): 543-565. The AIT Vision mutual fund opened at the beginning of 1996 and has publicly available performance numbers. In its first full calendar year (1996), the mutual fund increased 27.2 percent in net asset value, compared to 21.2 percent for its benchmark, the Russell 3000 index.
It should be noted that outperforming its benchmark index does not in itself prove a superior level of decision making. The algorithm may have been making higher-risk investments (on average) than the average in the index.
31
There are many online resources on evolutionary computation and evolutionary and genetic algorithms. One of the best is “The Hitchhiker’s Guide to Evolutionary Computation: A List of Frequently Asked Questions (FAQ),” edited by Jörg Heitkötter and David Beasley at <
http://wwwcs.purdue.edu/coast/archive/clife/FAQ/www/
>: This guide includes everything from a glossary to links to various research groups.
There are many online resources on evolutionary computation and evolutionary and genetic algorithms. One of the best is “The Hitchhiker’s Guide to Evolutionary Computation: A List of Frequently Asked Questions (FAQ),” edited by Jörg Heitkötter and David Beasley at <
http://wwwcs.purdue.edu/coast/archive/clife/FAQ/www/
>: This guide includes everything from a glossary to links to various research groups.
Another helpful online resource is the web site for the Santa Fe Institute. The institute’s web site can be accessed at <
http://www.santafe.edu
>.
http://www.santafe.edu
>.
For an offline introduction to genetic algorithms, read John Holland’s article “Genetic Algorithms,” Scientific American 267, no. 1 (1992): 66-72. As mentioned in note 22 in chapter 1, Holland and his colleagues at the University of Michigan developed genetic algorithms in the 1970s.
For more information on the use of genetic algorithm technology to manage the development and manufacturing of Volvo trucks, read Srikumar S. Rao, “Evolution at Warp Speed,” Forbes 161, no. 1 (January 12, 1998): 82-83.
See also note 22 on complexity in chapter 1.
32
See “Information Processing in the Human Body,” by Vadim Gerasimov, at <
http://vadim.www.media.mit.edu/MAS862/Project.html
>.
See “Information Processing in the Human Body,” by Vadim Gerasimov, at <
http://vadim.www.media.mit.edu/MAS862/Project.html
>.
33
See “Information Processing in the Human Body,” by Vadim Gerasimov, at <
http://vadim.www.media.mit.edu/MAS862/Project.html
>.
See “Information Processing in the Human Body,” by Vadim Gerasimov, at <
http://vadim.www.media.mit.edu/MAS862/Project.html
>.
34
I founded Kurzweil Applied Intelligence (Kurzweil AI) in 1982. The company is now a subsidiary of Lernout & Hauspie Speech Products (L&H), an international leader in the development of speech and language technologies and related applications and products. For more information about these speech recognition products, see <
http://www lhs.com/dictation/
>.
I founded Kurzweil Applied Intelligence (Kurzweil AI) in 1982. The company is now a subsidiary of Lernout & Hauspie Speech Products (L&H), an international leader in the development of speech and language technologies and related applications and products. For more information about these speech recognition products, see <
http://www lhs.com/dictation/
>.
1
Victor L. Yu, Lawrence M. Fagan, S. M. Wraith, William Clancey, A. Carlisle Scott,
Victor L. Yu, Lawrence M. Fagan, S. M. Wraith, William Clancey, A. Carlisle Scott,
John Hannigan, Robert Blum, Bruce Buchanan, and Stanley Cohen, “Antimicrobial Selection by Computer: A Blinded Evaluation by Infectious Disease Experts,” Journal of the American Medical Association 242, no. 12 (1979): 1279-1282.
2
For an introduction to the development of expert systems and their use in various companies, read: Edward Feigenbaum, Pamela McCorduck, and Penny Nii, The Rise of the Expert Company (Reading, MA: Addison-Wesley, 1983).
For an introduction to the development of expert systems and their use in various companies, read: Edward Feigenbaum, Pamela McCorduck, and Penny Nii, The Rise of the Expert Company (Reading, MA: Addison-Wesley, 1983).
3
William Martin, Kenneth Church, and Ramesh Patil, “Preliminary Analysis of a Breadth-First Parsing Algorithm: Theoretical and Experiential Results.” MIT Laboratory for Computer Science, Cambridge MA, 1981. In this document, Church cites the synthetic sentence:
William Martin, Kenneth Church, and Ramesh Patil, “Preliminary Analysis of a Breadth-First Parsing Algorithm: Theoretical and Experiential Results.” MIT Laboratory for Computer Science, Cambridge MA, 1981. In this document, Church cites the synthetic sentence:
“It was the number of products of products of products of products of products of products of products of products?” as having 1,430 syntactically correct interpretations.
He cites the following sentence:
“What number of products of products of products of products of products of products of products of products was the number of products of products of products of products of products of products of products of products?” as having 1,430 X 1,430 = 2,044,900 interpretations.
4
These and other theoretical aspects of computational linguistics are covered in Mary D. Harris, Introduction to Natural Language Processing (Reston, VA: Reston Publishing Co., 1985).
These and other theoretical aspects of computational linguistics are covered in Mary D. Harris, Introduction to Natural Language Processing (Reston, VA: Reston Publishing Co., 1985).
1
Hans Moravec is likely to make this argument in his 1998 book Robot: Mere Machine to Transcendent Mind (Oxford University Press; not yet available as of this writing).
Hans Moravec is likely to make this argument in his 1998 book Robot: Mere Machine to Transcendent Mind (Oxford University Press; not yet available as of this writing).
2
One hundred fifty million calculations per second for a 1998 personal computer doubling twenty-seven times by the year 2025 (this assumes doubling both the number of components, and the speed of each component every two years) equals about 20 million billion calculations per second. In 1998, it takes multiple calculations on a conventional personal computer to simulate a neural-connection calculation. However, computers by 2020 will be optimized for the neural-connection calculation (and other highly repetitive calculations needed to simulate neuron functions). Note that neural-connection calculations are simpler and more regular than the general-purpose calculations of a personal computer.
One hundred fifty million calculations per second for a 1998 personal computer doubling twenty-seven times by the year 2025 (this assumes doubling both the number of components, and the speed of each component every two years) equals about 20 million billion calculations per second. In 1998, it takes multiple calculations on a conventional personal computer to simulate a neural-connection calculation. However, computers by 2020 will be optimized for the neural-connection calculation (and other highly repetitive calculations needed to simulate neuron functions). Note that neural-connection calculations are simpler and more regular than the general-purpose calculations of a personal computer.
3
Five billion bits per $1,000 in 1998 will be doubled seventeen times by 2023, which is about a million billion bits for $1,000 in 2023.
Five billion bits per $1,000 in 1998 will be doubled seventeen times by 2023, which is about a million billion bits for $1,000 in 2023.
4
NEC’s goals to build a supercomputer with a maximum performance of more than 32 teraflops is chronicled in “NEC Begins Designing World’s Fastest Computer,” N
ews-bytes News Network
, January 21, 1998, located online at <
http://www.nb-pacifica.com/headline/necbeginsdesigningwo_1208.shtml
>.
NEC’s goals to build a supercomputer with a maximum performance of more than 32 teraflops is chronicled in “NEC Begins Designing World’s Fastest Computer,” N
ews-bytes News Network
, January 21, 1998, located online at <
http://www.nb-pacifica.com/headline/necbeginsdesigningwo_1208.shtml
>.
In 1998, IBM was one of four companies chosen to participate in PathForward, an initiative from the Department of Energy to develop supercomputers for the twenty-first century. Other companies involved in the project are Digital Equipment Corporation; Sun Microsystems, Inc.; and Silicon Graphics/Cray Computer Systems (SGI/Cray). PathForward is part of the Accelerated Strategic Computing Initiative (ASCI). For more information on this initiative, see <
http://www.llnl.gov/asci
>.
http://www.llnl.gov/asci
>.
5
By harnessing the accelerating improvement in both density of components and speed of components, computer power will double every twelve months, or a factor of one thousand every ten years. Based on the projection of $1,000 of computing being equal to the estimated processing power of the human brain (20 million billion calculations per second) by the year 2020, we get a projection of $1,000 of computing being equal to a million human brains in 2040, a billion human brains in 2050, and a trillion human brains in 2060.
By harnessing the accelerating improvement in both density of components and speed of components, computer power will double every twelve months, or a factor of one thousand every ten years. Based on the projection of $1,000 of computing being equal to the estimated processing power of the human brain (20 million billion calculations per second) by the year 2020, we get a projection of $1,000 of computing being equal to a million human brains in 2040, a billion human brains in 2050, and a trillion human brains in 2060.
6
By 2099, $1,000 of computing will equal 10
24
times the processing power of the human brain. Based on an estimate of 10 billion persons, that is 10
14
times the processing power of all human brains. Thus one penny of computing will equal 10
9
(one billion) times the processing power of all human brains.
By 2099, $1,000 of computing will equal 10
24
times the processing power of the human brain. Based on an estimate of 10 billion persons, that is 10
14
times the processing power of all human brains. Thus one penny of computing will equal 10
9
(one billion) times the processing power of all human brains.
7
In the Punctuated Equilibrium theories, evolution is seen to progress in sudden leaps followed by periods of relative stability. Interestingly, we often see similar behavior in the performance of evolutionary algorithms (see chapter 4).
In the Punctuated Equilibrium theories, evolution is seen to progress in sudden leaps followed by periods of relative stability. Interestingly, we often see similar behavior in the performance of evolutionary algorithms (see chapter 4).
8
Dean Takahashi, “Small Firms Jockeying for Position in 3D Chip Market,” Knight-Ridder /Tribune News Service, September 21, 1994, p. 0921K4365.
Dean Takahashi, “Small Firms Jockeying for Position in 3D Chip Market,” Knight-Ridder /Tribune News Service, September 21, 1994, p. 0921K4365.
9
The entire February 1998 issue of Computer (vol. 31, no. 2) explores the status of optical computing and optical storage methods.
The entire February 1998 issue of Computer (vol. 31, no. 2) explores the status of optical computing and optical storage methods.
Sunny Bains writes of companies using optical computing for fingerprint recognition and other applications in “Small, Hybrid Digital/Electronic Optical Correlators Ready to Power Commercial Products: Optical Computing Comes into Focus.”
EE Times
, January 26, 1998, issue 990. This article is online at <
http://www.techweb.com/se/directlink.cgi?EET19980126S0019
>.
EE Times
, January 26, 1998, issue 990. This article is online at <
http://www.techweb.com/se/directlink.cgi?EET19980126S0019
>.
10
For a nontechnical introduction to DNA computing, read Vincent Kiernan, “DNA-Based Computers Could Race Past Supercomputers, Researchers Predict,” in the
Chronicle
of Higher Education (November 28, 1997). Kiernan discusses the research of Dr. Robert Corn from the University of Wisconsin as well as the research of Dr. Leonard Adleman. The article can be accessed online at <
http://chronicle.com/data/articles.dir/art-44.dir/issue-l4.dir/14a02301.htm
>.
For a nontechnical introduction to DNA computing, read Vincent Kiernan, “DNA-Based Computers Could Race Past Supercomputers, Researchers Predict,” in the
Chronicle
of Higher Education (November 28, 1997). Kiernan discusses the research of Dr. Robert Corn from the University of Wisconsin as well as the research of Dr. Leonard Adleman. The article can be accessed online at <
http://chronicle.com/data/articles.dir/art-44.dir/issue-l4.dir/14a02301.htm
>.
Research at the University of Wisconsin can be accessed online at <
http://corninfo.chem.wisc.edu/writings/DNAcomputing.html
> .
http://corninfo.chem.wisc.edu/writings/DNAcomputing.html
> .
Leonard Adleman’s “Molecular Computation of Solutions to Combinatorial Problems” from the November 11, 1994, issue of Science (vol. 266, p. 1021) provides a technical overview of his design of DNA programming for computers.
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