Thinking Machines Research Articles

Smart Enough to Talk With Us? Foundations and Challenges for Dialogue Capable AI Systems

Smart Enough to Talk With Us? Foundations and Challenges for Dialogue Capable AI Systems

Thinking Machines and Patent Law

This chapter focuses on the challenges that a thinking machine paradigm of invention - one in which thinking machines play significant and sometimes dominant roles in the invention process - creates for U.S. patent law. It examines the disconnect between a thinking machine paradigm and the traditional model of invention that lies at the heart of patent law, explores some of the doctrinal challenges and practical problems that result from this disconnect, and concludes with four considerations to inform a patent policy response.

Imagining the thinking machine: Technological myths and the rise of artificial intelligence

This article discusses the role of technological myths in the development of artificial intelligence (AI) technologies from 1950s to the early 1970s. It shows how the rise of AI was accompanied by the construction of a powerful cultural myth: The creation of a thinking machine, which would be able to perfectly simulate the cognitive faculties of the human mind. Based on a content analysis of articles on AI published in two magazines, the Scientific American and the New Scientist, which were aimed at a broad readership of scientists, engineers and technologists, three dominant patterns in the construction of the AI myth are identified: (1) the recurrence of analogies and discursive shifts, by which ideas and concepts from other fields were employed to describe the functioning of AI technologies; (2) a rhetorical use of the future, imagining that present shortcomings and limitations will shortly be overcome and (3) the relevance of controversies around the claims of AI, which we argue should be considered as an integral part of the discourse surrounding the AI myth.

Special report : Can we copy the brain? - The dawn of the real thinking machine

Steve sits up and takes in the crisp new daylight pouring through the bedroom window. He looks down at his companion, still pretending to sleep. Okay, Kiri, I'm up. . She stirs out of bed and begins dressing. You received 164 messages overnight. I answered all but one. . In the bathroom, Steve stares at his disheveled self. Fine, give it to me. . Your mother wants to know why you won't get a real girlfriend. . He bursts out laughing. Anything else? . Your cholesterol is creeping up again. And there have been 15,712 attempts to hack my mind in the last hour. . Good grief! Can you identify the source? . It's distributed. Mostly inducements to purchase a new RF oven. I'm shifting ciphers and restricting network traffic. . Okay. Let me know if you start hearing voices. Steve pauses. Any good deals? . One with remote control is in our price range. It has mostly good reviews.

The Limits of World Literature

AbstractThis essay examines recent work on world literature theory, with a particular focus on those theorists who treat individual texts as in dialogue with the circulations of linguistic and cultural translation. I treat world literature as the theory without an object and make the counterintuitive claim that its objectlessness makes it well suited for leaving behind antiquated modes of categorizing and canonizing so‐called world texts, in order to make room for new kinds of structured thinking about the world. The essay begins with an introduction to the manifold interconnections of the new world literature, including its broad overlap with fields of globalization, translation studies, comparative literature, and postcolonialism. I position four key theorists of 21st century world literature – Emily Apter, Rebecca Walkowitz, Berthold Schoene, and David Palumbo‐Liu – in oppositional pairs in order to show the underlying commonality in their thinking about the value of a literature of and for the world. My entry point into the “thinking machine” of the world literature text is the concept of the limit. Far from the commonplace understanding of limit as a limitation or boundary, I argue that understanding world literature at the limit allows literary texts and theory to be read as an event of thinking that is in‐process, in‐common, and incomplete, an analogue to the necessary impossibility of knowing the world.

Cinematicity: City and cinema after Deleuze

Abstract In light of Deleuze’s conception of cinema as an autonomous thinking machine – a ‘spiritual automaton’ in which moving images are substituted for human thought – the article presents the cinema as a pre-eminent thinker of the city. It contextualizes a range of scholarship committed to exploring the potential of Deleuze’s thought in relation to the ‘cinematic city’ – precipitating a Deleuzian encounter with a process that we have chosen to call cinematicity: the automatic thinking of the city by the cinema. In the course of their remarkable co-evolution, cinema’s unhinging of space– time has projected the unhinging of the space–time of the city, forcing its inhabitants to think otherwise about space, time and the human condition in the machine age. Taking these notions as a point of departure, the contributions to this issue, which variously serve to explicate the connections between city and cinema, are introduced, framed by this sense of cinematicity.

Ada’s Ideas: The Story of Ada Lovelace, the World’s First Computer Programmer by Fiona Robinson

Reviewed by: Ada’s Ideas: The Story of Ada Lovelace, the World’s First Computer Programmer by Fiona Robinson Elizabeth Bush Robinson, Fiona Ada’s Ideas: The Story of Ada Lovelace, the World’s First Computer Programmer; written and illus. by Fiona Robinson. Abrams, 2016 40p Trade ed. ISBN 978-1-4197-1872-4 $17.95 E-book ed. ISBN 978-1-6131-2913-5 $15.54 R Gr. 2-4 Children who recently became acquainted with nineteenth-century mathematician Ada Lovelace in Wallmark’s Ada Byron Lovelace and the Thinking Machine (BCCB 12/15) will find complementary information but a startlingly different pictorial approach in Robinson’s picture-book biography. Much of the same ground is covered [End Page 92] here: the absence of her father, Lord Byron; her mother’s influence in Lovelace’s gravitating toward mathematics; complications from measles that brutally interrupted her childhood. Robinson also, however, introduces historical context on the marvels of engineering and industry that distinguished this period and how their development depended on mathematics. As in the Wallmark title, there is relatively little here about Lovelace’s adult personal life, but Robinson does offer a bit more on the collaboration with Babbage, on the Difference Engine that preceded the better known Analytical Engine, and on the Jacquard loom whose punched paper patterns inspired the technology that would drive Babbage’s proposed computers. Colored and cut paper collage, with design elements stacked for depth and then photographed, underscore the theme of creativity expressed through numbers—the melding of Lovelace’s parental legacies. Smokestacks, machinery, and even a lineup of famous personages define Lovelace’s milieu, but hovering numerals, coiling flow charts, and poetry and math symbols floating among the clouds suggest that Lovelace’s mathematical ideas raced above and beyond quotidian concerns. A brief and largely expendable note on Bernoullian numbers, remarks on illustrations, and a list of adult sources are included. Copyright © 2016 The Board of Trustees of the University of Illinois

Ada Byron Lovelace and the Thinking Machine by Laurie Wallmark (review)

Ada Byron Lovelace and the Thinking Machine by Laurie Wallmark (review)

Mills Can't Think: Leibniz's Approach to the Mind-Body Problem

In the Monadology Leibniz has us imagine a thinking machine the size of a mill in order to show that matter can't think. The argument is often thought to rely on the unity of consciousness and the notion of simplicity. Leibniz himself did not see matters this way. For him the argument relies on the view that the qualities of a substance must be intimately connected to its nature by being modifications, limitations of its nature. Leibniz thinks perception is not a modification of matter because it is active and matter is passive. At the same time, there are traces in Leibniz of a different argument that relies on the notion of internal action, which may involve the notion of simplicity. Critics have sometimes charged that the Mill Argument is an argument from ignorance, but Leibniz was aware of this problem and made clear that he did not make that mistake.

Live multilingual thinking machine

The Extended Hierarchical Censored Production Rules (EHCPRs) system is presented here as an underlying methodology for representation, reasoning, learning, etc., of the proposed live multilingual thinking machine. Enriched representation scheme is a very important aspect and central to all the successful and effective Artificial Intelligence systems. An EHCPR is presented here as a unit of represented knowledge (i.e. an artificial neuron) in the knowledge treasure distributed over globally spread servers. An EHCPR is implemented with the help of extensive set of predefined pointers like dendrites in a neuron and various nodes like nucleus in a neuron, which would span a huge but efficient multilingual hierarchical network as knowledge structure. The EHCPRs system is started live at www.live-ehcprs-system.com with multilingual representation and storage at word level only. But construction of words is by starting at character level without repetition in representation of a character. It displays the stored information of any stored concept in any of the selected language. To begin with, English, French and Hindi are offered to the user which would be extended to all the languages in future.

Book Review: Google and the Culture of Search

Ken Hillis, Michael Petit, and Kylie Jarrett Google and Culture of Search. New York: Routledge, 2013. 240 pp.This book covers wide theoretical and historical terrain within its limited length, offering unique view of Google and what it calls the culture of The authors in Introduction lay out argument that Google is messianic-type leader of what it calls the culture of describes Google as a nexus of power and knowledge newly constituted through extremely rapid changes in social expectations and desires attending them (p. 6). Google has become more than an Internet engine in minds and hearts of its users, according authors:The firm's rise reflects and benefits from generational-inflected growth in perception that everything that matters is now on and that almost everything is already archived in some online database and should, in moral sense of this verb, be accessible through search. (p. 6)Although educators, as well as many over age of thirty, would refute latter claim, authors Hillis, Petit and Jarrett back up their position with reports on statistical rate of use of Google, especially by users under age twenty-nine years (p. 6). In addition, other evidence is given including listing in Oxford English Dictionary that authorizes to google as transitive verb meaning to for information about (a person or thing) (p. 6).In Chapter 3, Universal Libraries and Thinking Machines, authors state . . we offer set of intellectual histories of longstanding, Idealist desire for universal library. We begin with pre-1900 thoughts, desires, theories, and systems of belief that collectively inform contemporary search (p. 77). Here authors discuss intricacies of 1939 essay La Biblioteca (The Total Library) by Jorge Luis Borges, Judeo-Christian story of Tower of Babel, ancient Ptolemaic rulers' desire develop library collection encompassing languages and knowledge from all over world (In 283 BCE at beginning of Ptolemy's II reign library at Alexandria had collected 200,000 scrolls) and ideas of 14th century philosopher Ramon Lull's Thinking Machine. In Chapter 4, authors draw more historical comparisons between contemporary culture and ideas propagated by philosopher H. G. Wells in his work World Brain (1938). Chapter 5 covers post-WWII efforts develop ever-expanding electronic databases that utilize ever-broadening information retrieval and technologies, authors describe with foci on interplay among information, metaphysics and search (p.124).Instructors of journalism, communication, and library and information science may find aforementioned book as whole unwieldy for classroom instruction, but may find chapters 1, 2, 6, and 7 useful for upper-level undergraduate classes or graduate seminars as teaching tool help jump-start thoughtful discussions and provide interesting insights into Google, as well as into the culture of search interpretation.Welcome Googleplex, chapter 1, outlines entity of Google. Much of book revolves around Google trademark technology PageRank, which underpins Google's technologies [and] transformed practice and conceptualizations of what it was Web (p. 3), but Google is more than algorithm. The authors ask, What is Google? Their answer is, It is technology firm, media corporation, an automated ad agency, platform, financier of automated vehicles and alternative energy projects (p. 30).Google founders Sergey Brin and Larry Page were early web adopters and emerged after studying as students at Stanford University. The company has been able keep some of its do-it-yourself California ideology alongside commercialism and forprofit motivation. The following conclusion is drawn:Google's revenue stream relies on an established economic model shared by broadcast mass media-the audience is commodity sold advertisers (Smyth 1981). …

Can the Eureqa Symbolic Regression Program, Computer Algebra, and Numerical Analysis Help Each Other?

The Eureqa symbolic regression program has recently received extensive press praise. A representative quote is There are very clever 'thinking machines' in existence today, such as Watson, the IBM computer that conquered Jeopardy! last year. But next to Eureqa, Watson is merely a glorified search engine. The program was designed to work with noisy experimental data. However, if the data is generated from an expression for which there exists more concise equivalent expressions, sometimes some of the Eureqa results are one or more of those more concise equivalents. If not, perhaps one or more of the returned Eureqa results might be a sufficiently accurate approximation that is more concise than the given expression. Moreover, when there is no known closed form expression, the data points can be generated by numerical methods, enabling Eureqa to find expressions that concisely fit those data points with sufficient accuracy. In contrast to typical regression software, the user does not have to explicitly or implicitly provide a specific expression or class of expressions containiing unknown constants for the software to determine. Is Eureqa useful enough in these regards to provide an additional tool for experimental mathematics, computer algebra users and numerical analysis? Yes if used carefully. Can computer algebra and numerical methods help Eureqa? Definitely.

David L. Waltz, in Memoriam

David L. Waltz (1943–2012), was director, Center for Computational Learning Systems (CCLS), Columbia University, and a pioneer in the field of artificial intelligence. Waltz served as Association for the Advancement of Artificial Intelligence (AAAI) president from 1997 to 1999, was a Fellow of AAAI and the Association for Computing Machinery (ACM), a senior member of the Institute for Electrical and Electronics Engineers (IEEE), and former chair of the ACM Special Interest Group on Artificial Intelligence (SIGART). Prior to joining CCLS, he was president of the NEC Research Institute in Princeton, and from 1984–1993 was director of Advanced Information Systems at Thinking Machines Corporation and a professor of computer science at Brandeis University. A celebration of his life was held in the spring of 2012, and a symposium in his honor was held September 23, 2012, at Brandeis University in Waltham, Massachusetts.

Nano Technology: The Flipside of Transition Technology

The 21st century world is indisputably at intersection of a revolutionary era, ushered in by synergized confluence of biotechnology and nano technology. Whereas characteristic building blocks that were, manifested in all traditional evolutionary changes in Industrial era from flint chips to silicon chips , were technologies, now in recent times , in a quick reversal of situation, bulk technologies are on cusp of radically getting replaced by entirely new generation of molecular technologies. This necessarily pre supposes a shift in way we look at manufacturing industry. Molecular manufacturing has in this process come to mean a revolutionary gene-on-a-chip approach which seeks to manufacturing industry as we know it. It would also eliminate rural sector: farms growing food and forest plantations growing (1). In Agricultural sector, it would make a sea change as when large slabs of beef or chicken meat grown in vats by in vitro process would be available without growing any cattle or poultry in farm level . It is estimated that a single animal could provide more than a billion pounds of in vitro meat to feed world's population for at least several hundred years (2). Similarly scientists would be in a position to synthesize, wood commensurate with desirable characteristics instead of having to rely on nature's imperfect random variations, all of which are likely to have far reaching implications in land use and sustainability. As a result, unlike as of now, in nano technology enabled future, the farm will be a wide area bio-factory that can be monitored and managed from a laptop and food will be crafted from designer substances delivering nutrients efficiently to body. (3), While nanotechnology is admittedly technology enabled and atomically assembled antithesis to organic agriculture, organic agriculture on other hand places a premium on wholesome health-boosting properties of fresh, unprocessed whole foods. In contrast nanotechnology, further seeks to transform farm as a whole into an automated extension of high technology factory production line. According to Raymond Ray Kurzweil who has since been hailed by Forbes as the ultimate thinking machine as it is computing power, that renders growth in so many fields of science and technology, these improvements in computing power, ipso facto , translate themselves into exponential advancements in non-computer sciences like nanotechnology, biotechnology, and materials science. Kurzweil has chosen to refer to this concept as Law of Accelerating Returns. The goal of Agriculture is to supply all people on planet with enough food to prevent wide spread hunger and starvation. However, larger issues of food security are getting worse day by day, resulting in an increase in number of malnourished persons in world. The ever increasing population in developing and less developed countries is also coming in way, as a major constraint in eradication of poverty. While there are beneficial attributes of Nano technology there are also pitfalls in its path. David Collingridge, of University of Aston, has given us a treatise of how two conditions necessary for avoiding

Artificial General Intelligence and the Future of the Human Race

A rtificial G eneral I ntelligence and the F uture of the H uman R ace Bryon Pavlacka “Narrow AI is already used by the militaries of first world countries for war purposes.” of AGI research. Thinkers like Ray Kurzweil, Ben Goertzel, and Hugo De Garis think that we are entering into a world of extremely intelligent machines (Kurzweil 2005; Goertzel & Pennachin, 2007; De Garis, 2008). This article will discuss some of the ideas that researchers have on how AGI relates to the wellbeing of humans, including how the machines can help us and how they could potentially harm us. One scenario in which generally intelligent machines go bad and become a threat is if they end up in bad hands. Such machines, in the hands of small, politically motivated terrorist groups or large military organizations, could be used as weapons. AGI could offer such groups the ability to spy, gather, and synthesize information, as well as strategize attacks against the rest of the population. Developers of AGI will have little knowledge of whose hands their technology will end up in; they could unknowingly be constructing deadly weapons to be used against humanity. Of course, such threats are not imaginary future possibilities. Narrow AI is already used by the militaries of first world countries for war purposes. Consider drones such as the Northrop Grumman X-47B, an Unmanned Combat Aerial Vehicle that is being tested by the US Navy (DefenseTech.org, 2011). That’s right, there is no pilot. Of course, the drone can be given orders, but the exact way in which those orders are carried out will be left up to the drone’s Narrow AI system. Whether such systems will ever be extended toward general intelligence is currently unknown. However, the US military has shown interest in producing and controlling generally intelligent killing machines as well, as made evident by a paper called “Governing Lethal Behavior” by Ronald C. Arkin. The paper was commissioned by the U.S. Army Research Office and provides theory and formalisms for the implementation of a lethal AGI machine (Arkin, 2008). The paper describes a way in which a machine can be restricted to “ethical” behavior determined by the creator. The author optimistically hopes that his proposed formalisms may lead to generally intelligent battle drones that are more ethical in battle than humans are, yet the ability to define “ethical actions” remains the privilege of the machines’ engineers (Arkin, 2008, p.62). Due to the potential for AGI to be used as a weapon, the production of such machines carries many of the same moral ramifications as the production of other weapons. Another threat to humanity is the possibility that a good machine, one specifically created to be benevolent, may go bad, as was the case with Hal 9000 in 2001: A Space Odyssey. Evolutionary and learning algorithms may lead to a system that is essentially a black box, something so complicated that experts may be unable to understand its inner workings completely. As with humans, such machines may have extremely complex psychologies, so the potential for malevolence is non-zero (Goertzel & Pennachin, 2007). Even if special constraints are placed on the behavior of such systems, rules like “do not kill” could potentially be overwritten after successive updates initiated by the AGI system itself (Singularity Institute for Artificial Intelligence [SIAI], 2001, para. 2). Such a scenario may become greatly feared by the public, leading to what one researcher calls “The Artilect War.” In Hugo De Garis’ essay, “The Artilect War: B erkeley S cientific J ournal • S ave or D estroy • S pring 2012 • V olume 16 • I ssue 2 • 1 B S J Artificial Intelligence is all around us. It manages your investments, makes the subway run on time, diagnoses medical conditions, searches the internet, solves enormous systems of equations, and beats human players at chess and Jeopardy. However, this “narrow AI,” designed for solving specific, narrow problems, is something distinctly different from Artificial General Intelligence, or “AGI”, true thinking machines with human-like general intelligence (Wang, Goertzel, & Franklin, 2008, p. v). While AGI is not rigidly defined, it is often envisioned as being self-aware and capable of complex thought, and has been a staple of science fiction, appearing prominently in popular films such as 2001: A Space Odyssey, Terminator, and I, Robot. In each of these films, the machines go beyond their original programmed purpose and become violent threats to humans. This is a possibility which has been pondered extensively by those working in the field

Final Jeopardy: man vs. machine and the quest to know everything

Final Jeopardy: man vs. machine and the quest to know everything

Ticking to eternity

A 10,000-Year Clock, a monument-size mechanical clock designed to measure time for 10 millennia is discussed. Danny Hillis, an electrical engineer with three degrees from MIT who pioneered parallel super computers at Thinking Machines Corp., worked for Walt Disney Imagineering, and then cofounded the consultancy Applied Minds, dreamed up the project in 1995 to get people thinking more about the distant future. But the clock is no longer just a thought experiment. In a cluttered machine shop near a Starbucks in San Rafael, Calif., it's finally ticking to life.

From Neuroelectrodynamics to Thinking Machines

Natural systems can provide excellent solutions to build artificial intelligent systems. The brain represents the best model of computation that leads to general intelligent action. However, current mainstream models reflect a weak understanding of computations performed in the brain that is translated in a failure of building powerful thinking machines. Specifically, temporal reductionist neural models elude the complexity of information processing since spike timing models reinforce the idea of neurons that compress temporal information and that computation can be reduced to a communication of information between neurons. The active brain dynamics and neuronal data analyses reveal multiple computational levels where information is intracellularly processed in neurons. New experimental findings and theoretical approach of neuroelectrodynamics challenge current models as they now stand and advocate for a change in paradigm for bio-inspired computing machines.

The Limits of Intelligence

In this article the author discusses how the laws of physics may prevent the human brain from evolving into a more powerful thinking machine. According to the author, research suggests that human intelligence may be close to its evolutionary limit. Topics include the constraints that physics places on the mental faculties of the human brain, such as the laws of thermodynamics, the connection between brain size and intelligence, and how human beings may still be able to achieve higher intelligence collectively through writing and the use of the Internet, which enables individuals to expand their minds outside the confines of their bodies. INSETS: Brain-Size Outliers;The Physics of Thought;Why We Probably Cannot Get Much Smarter.

Brain-mind machinery: brain-inspired computing and mind opening

Brain and mind continue to be a topic of enormous scientific interest. With the recent advances in measuring instruments such as two-photon laser scanning microscopy and fMRI, the neuronal connectivity and circuitry of how the brain's various regions are hierarchically interconnected and organized are better understood now than ever before. By reverse engineering the brain, computer scientists hope to build cognitively intelligent systems that will revolutionize the artificial intelligence paradigm. Brain-Mind Machinery provides a walkthrough to the world of brain-inspired computing and mind-related questions. Bringing together diverse viewpoints and expertise from multidisciplinary communities, the book explores the human quest to build a thinking machine with human-like capabilities. Readers will acquire a first-hand understanding of the brain and mind mechanisms and machineries, as well as how much we have progressed in and how far we are from building a truly general intelligent system like the human brain.Contents: The Brain: The Center of Attraction; Neurons and Synapses: The Key to Memory and Learning; The Cortex Architecture: The Building Block of Intelligence; Many Faces of Memories -- Investigating the Human Multiple Memory Systems; Learning Like a Human: How Does Learning Take Place in Our Brain?; Emotion and Cognition; Laminar Computing; Probabilistic Computing: The Bayesian Mind; Thinking Machine: Higher Theories of Brain and Commonsense Knowledge Generation; Modeling the Entire Brain: Biologically Inspired Cognitive Architectures; Are We There? What Can the Computer Do Today and Tomorrow?; Brain -- A Forest Not Totally Explored: What are Some of the Issues?; Understanding the Brain to Build Intelligent Systems; Conclusions -- The Mind That Matters.