Super-Intelligent Machines: 7 Robotic Futures | The Singularity & Artificial Intelligence by Tia Ghose, Senior Writer | May 07, 2013 12:29pm ET Credit: photobank.kiev.ua | Shutterstock It's been the fodder for countless dystopian movies: a singularity in which artificial intelligence rivals human smarts. But though it sounds like science fiction, many computer scientists say the singularity will arrive some time in the 21st century. Still, few people agree on what that future will look like. From mass extinction to life extension, here are six potential implications of super-smart robots. Author Bio Tia Ghose Tia has interned at Science News, Wired.com, and the Milwaukee Journal Sentinel and has written for the Center for Investigative Reporting, Scientific American, and ScienceNow. Tia Ghose on
Lecture - Japan prize 2002 Commemorative Lecture - Berners-Lee TimBL Exploring Universality Abstract The most important thing about the World Wide Web is that it is universal. Hardware independence, which once meant running on mainframes, minicomputers and microcomputers, now extends to a multitude of devices from watches and speech devices to big screen televisions. Introduction The concept of the Web integrated many disparate information systems, by forming an abstract imaginary space in which the differences between them did not exist. Back in 1989, before the World Wide Web, many different information systems existed. The first breakthrough was the Internet, and I can't emphasize too often that I didn't invent the Internet! The way the Web works is very simple. The Web required everyone to give a URI to their documents: a large request. Device independence That the same information should be accessible from many devices is a core rule of the Web. The direct impact of the Web was seen in its ability to cross hardware and software boundaries. Quality
Yapay Zekanın Zaman Tüneli - Gatmer Yapay zeka geçmişten geleceği teknolojinin hayatı değiştirdiği dönemler boyunca tartışılmış ve tartışılacak olan bir ürün olarak çağın belirleyicileri arasında her zaman bulunmuştur ve bulunacaktır. Günümüze kadar neredeyse her dönem bilim kurgu sinema filmlerinin konusu olan yapay zeka artık teknolojinin ilerlemesinden dolayı geliştirilip geliştirilmemesi yönündeki tartışmaların temeline oturdu. Eskiden ütopik bir dünyanın ürünü olan yapay zeka günümüze nasıl geldi önemli uğrak noktaları nelerdir aslında hangi filmler ve teknolojik gelişmeler yapay zekanın gelişiminde ki önemli noktalar bu galerimizde bunları araştırdık.1-Isaac Asimov 1950 yılında yazdığı I Robot kitabıyla yapay zekayı düşünce yapımıza entegre eden kişi yine aynı dönemde Alan Turing tarafından bilgisayar ve makinalar için kağıt üstünde uygulanmaya başlayan Turing Testi. 2-Yapay zekanın araştırılması ve geliştirlmesi için ilk karar Dartmouth Konferansı’nda alındı IBM 702 bilgisayarlarla başladı.
The Oracle of Bacon Computer chatbot 'Eugene Goostman' passes the Turing test A computer program that pretends to be a 13-year-old Ukrainian boy called Eugene Goostman passed a Turing test at the Royal Society in London yesterday (Saturday 6 June) by convincing 33 percent of the judges that it was human during a five-minute typed conversation. The test was suggested by computer scientist Alan Turing in 1950, and the competition was held on the 60th anniversary of his death. The judges included Robert Llewellyn, who played the android Kryten in Red Dwarf, and Lord Sharkey, who led the campaign for Turing's posthumous pardon last year. Llewellyn tweeted: "Turing test was amazing. Eugene Goostman's success was not a surprise. Kevin Warwick, a visiting professor at the University of Reading, which organised both tests, said it was the first time a chatbot had passed an open-ended test, rather than one where topics or questions were set in advance. The fictional Eugene has a father who is a gynaecologist, and has a pet guinea pig. Further reading
Graph structure in the web Andrei Broder 1 , Ravi Kumar 2 , Farzin Maghoul 1 , Prabhakar Raghavan 2 , Sridhar Rajagopalan 2 , Raymie Stata 3 , Andrew Tomkins 2 , Janet Wiener 3 1: AltaVista Company, San Mateo, CA. 2: IBM Almaden Research Center, San Jose, CA. 3: Compaq Systems Research Center, Palo Alto, CA. Abstract The study of the web as a graph is not only fascinating in its own right, but also yields valuable insight into web algorithms for crawling, searching and community discovery, and the sociological phenomena which characterize its evolution. : graph structure, diameter, web measurement 1. Consider the directed graph whose nodes correspond to static pages on the web, and whose arcs correspond to links between these pages. Designing crawl strategies on the web [ Cho and Garcia-Molina 2000 ]. Understanding of the sociology of content creation on the web. Predicting the emergence of important new phenomena in the web graph. the probability that a node has in-degree is proportional to , for some . 2.
AITopics Étude du petit monde Un article de Wikipédia, l'encyclopédie libre. Le « phénomène du petit monde » (appelé aussi effet du petit monde également connu sous le vocable « paradoxe de Milgram » car ses résultats semblent contraires à l'intuition) est l'hypothèse que chacun puisse être relié à n'importe quel autre individu par une courte chaîne de relations sociales. Ce concept reprend, après l'expérience du petit monde, conduite en 1967 par le psycho-sociologue Stanley Milgram, le concept de « six degrés de séparation ». Celui-ci suggère que deux personnes, choisies au hasard parmi les citoyens américains, sont reliées en moyenne par une chaîne de six relations. Par contre, après plus de trente ans, le statut de cette idée comme description de réseaux sociaux hétérogènes reste une question ouverte. Des études sont encore menées actuellement sur le « petit monde ». Expériences menées par Milgram[modifier | modifier le code] Critiques[modifier | modifier le code] Observations[modifier | modifier le code]
Brains, Minds and Machines | MIT150 | Massachusetts Institute of Technology 150th anniversary Watch videos of this symposium This symposium was inspired by the old dream of understanding the mind and the brain, which was at the core of several new fields created at MIT during the ‘50s and ‘60s. The same dream is now the main motivation for a new Intelligence Initiative (I2). Beyond being a great intellectual mission, this research helps to develop an understanding of the origins of intelligence, build more intelligent artifacts and systems, and improve the mechanisms for collective decisions. These advances will be critical to the future prosperity, education, health, and security of our society. Key question: Over the past 50 years, research in Artificial Intelligence (AI) and Machine Learning (ML) has led to the current development of remarkably successful applications such as Deep Blue, Google search, Kinect, Shazam, Watson, and MobilEye. a) that a new effort in curiosity-driven research is needed in order to understand intelligence and the brain Faculty leads Irene R. MIT News