|
AI-complete
In the field of artificial intelligence, the most difficult problems are informally known as AI-complete or AI-hard, implying that the difficulty of these computational problems, assuming intelligence is computational, is equivalent to that of solving the central artificial intelligence problem—making computers as intelligent as people, or strong AI.Shapiro, Stuart C. (1992)Artificial IntelligenceIn Stuart C. Shapiro (Ed.), ''Encyclopedia of Artificial Intelligence'' (Second Edition, pp. 54–57). New York: John Wiley. (Section 4 is on "AI-Complete Tasks".) To call a problem AI-complete reflects an attitude that it would not be solved by a simple specific algorithm. AI-complete problems are hypothesised to include computer vision, natural language understanding, and dealing with unexpected circumstances while solving any real-world problem. Currently, AI-complete problems cannot be solved with modern computer technology alone, but would also require human computation. T ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Artificial General Intelligence
Artificial general intelligence (AGI) is the ability of an intelligent agent to understand or learn any intellectual task that a human being can. It is a primary goal of some artificial intelligence research and a common topic in science fiction and futures studies. AGI is also called strong AI,: Kurzweil describes strong AI as "machine intelligence with the full range of human intelligence." full AI, or general intelligent action, although some academic sources reserve the term "strong AI" for computer programs that experience sentience or consciousness. Strong AI contrasts with ''weak AI'' (or ''narrow AI''), which is not intended to have general cognitive abilities; rather, weak AI is any program that is designed to solve exactly one problem. (Academic sources reserve "weak AI" for programs that do not experience consciousness or do not have a mind in the same sense people do.) A 2020 survey identified 72 active AGI R&D projects spread across 37 countries. Characteristics ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Human Computation
Human-based computation (HBC), human-assisted computation, ubiquitous human computing or distributed thinking (by analogy to distributed computing) is a computer science technique in which a machine performs its function by outsourcing certain steps to humans, usually as microwork. This approach uses differences in abilities and alternative costs between humans and computer agents to achieve symbiotic human–computer interaction. For computationally difficult tasks such as image recognition, human-based computation plays a central role in training Deep Learning-based Artificial Intelligence systems. In this case, human-based computation has been referred to as human-aided artificial intelligence. In traditional computation, a human employs a computer to solve a problem; a human provides a formalized problem description and an algorithm to a computer, and receives a solution to interpret. Human-based computation frequently reverses the roles; the computer asks a person or a larg ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Fanya Montalvo
Fanya S. Montalvo (born in Monterrey, Mexico) Received the Ph.D. in ''Computer and Information Science'' at the University of Massachusetts Amherst in 1976. Her dissertation was entitled ''Aftereffects, Adaptation, and Plasticity: A Neural Model for Tunable Feature Space.'' She was advised by Michael Anthony Arbib. Montalvo has been a research scientist at Lawrence Berkeley Labs, HP, MIT, and Digital Equipment Corporation. Montalvo is a leader in the field oInconsistency Robustnesscurrently serving on the governing Board of thInternational Society for Inconsistency Robustness According to Rosalind Picard, she is involved in considerations within emotional computing. ee: Affective Computing ">Affective_Computing.html" ;"title="ee: Affective Computing">ee: Affective Computing She is known for having coined the term "AI-complete"John C. Mallery. "Thinking About Foreign Policy: Finding an Appropriate Role for Artificially Intelligent Computers" Master's thesis, M.I.T. Political ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
CAPTCHA
A CAPTCHA ( , a contrived acronym for "Completely Automated Public Turing test to tell Computers and Humans Apart") is a type of challenge–response test used in computing to determine whether the user is human. The term was coined in 2003 by Luis von Ahn, Manuel Blum, Nicholas J. Hopper, and John Langford. The most common type of CAPTCHA (displayed as Version 1.0) was first invented in 1997 by two groups working in parallel. This form of CAPTCHA requires entering a sequence of letters or numbers in a distorted image. Because the test is administered by a computer, in contrast to the standard Turing test that is administered by a human, a CAPTCHA is sometimes described as a reverse Turing test.This test has received many criticisms, from people with disabilities, but also many websites use it to prevent bot spamming and raiding, and it works effectively, and its usage is widespread. Most websites use hCaptcha or reCAPTCHA. It takes the average person approximately 10 seconds ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Machine Translation
Machine translation, sometimes referred to by the abbreviation MT (not to be confused with computer-aided translation, machine-aided human translation or interactive translation), is a sub-field of computational linguistics that investigates the use of software to translate text or speech from one language to another. On a basic level, MT performs mechanical substitution of words in one language for words in another, but that alone rarely produces a good translation because recognition of whole phrases and their closest counterparts in the target language is needed. Not all words in one language have equivalent words in another language, and many words have more than one meaning. Solving this problem with corpus statistical and neural techniques is a rapidly growing field that is leading to better translations, handling differences in linguistic typology, translation of idioms, and the isolation of anomalies. Current machine translation software often allows for customizat ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Word-sense Disambiguation
Word-sense disambiguation (WSD) is the process of identifying which sense of a word is meant in a sentence or other segment of context. In human language processing and cognition, it is usually subconscious/automatic but can often come to conscious attention when ambiguity impairs clarity of communication, given the pervasive polysemy in natural language. In computational linguistics, it is an open problem that affects other computer-related writing, such as discourse, improving relevance of search engines, anaphora resolution, coherence, and inference. Given that natural language requires reflection of neurological reality, as shaped by the abilities provided by the brain's neural networks, computer science has had a long-term challenge in developing the ability in computers to do natural language processing and machine learning. Many techniques have been researched, including dictionary-based methods that use the knowledge encoded in lexical resources, supervised machine le ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Object Recognition
Object recognition – technology in the field of computer vision for finding and identifying objects in an image or video sequence. Humans recognize a multitude of objects in images with little effort, despite the fact that the image of the objects may vary somewhat in different view points, in many different sizes and scales or even when they are translated or rotated. Objects can even be recognized when they are partially obstructed from view. This task is still a challenge for computer vision systems. Many approaches to the task have been implemented over multiple decades. Approaches based on CAD-like object models * Edge detection * Primal sketch * Marr, Mohan and Nevatia * Lowe * Olivier Faugeras Recognition by parts * Generalized cylinders (Thomas Binford) * Geon (psychology), Geons (Irving Biederman) * Dickinson, Forsyth and Ponce Appearance-based methods * Use example images (called templates or exemplars) of the objects to perform recognition * Objects ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Natural-language Understanding
Natural-language understanding (NLU) or natural-language interpretation (NLI) is a subtopic of natural-language processing in artificial intelligence that deals with machine reading comprehension. Natural-language understanding is considered an AI-hard problem. There is considerable commercial interest in the field because of its application to automated reasoning, machine translation, question answering, news-gathering, text categorization, voice-activation, archiving, and large-scale content analysis. History The program STUDENT, written in 1964 by Daniel Bobrow for his PhD dissertation at MIT, is one of the earliest known attempts at natural-language understanding by a computer. Eight years after John McCarthy coined the term artificial intelligence, Bobrow's dissertation (titled ''Natural Language Input for a Computer Problem Solving System'') showed how a computer could understand simple natural language input to solve algebra word problems. A year later, in 1965, Joseph ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Text Mining
Text mining, also referred to as ''text data mining'', similar to text analytics, is the process of deriving high-quality information from text. It involves "the discovery by computer of new, previously unknown information, by automatically extracting information from different written resources." Written resources may include websites, books, emails, reviews, and articles. High-quality information is typically obtained by devising patterns and trends by means such as statistical pattern learning. According to Hotho et al. (2005) we can distinguish between three different perspectives of text mining: information extraction, data mining, and a KDD (Knowledge Discovery in Databases) process. Text mining usually involves the process of structuring the input text (usually parsing, along with the addition of some derived linguistic features and the removal of others, and subsequent insertion into a database), deriving patterns within the structured data, and finally evaluation and inte ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
TED (conference)
TED Conferences, LLC (Technology, Entertainment, Design) is an American-Canadian non-profit media organization that posts international talks online for free distribution under the slogan "ideas worth spreading". TED was founded by Richard Saul Wurman and Harry Marks in February 1984 as a tech conference, in which gave a demo of the compact disc that was invented in October 1982. It has been held annually since 1990. TED covers almost all topics – from science to business to global issues – in more than 100 languages. To date, more than 13,000 TEDx events have been held in at least 150 countries. TED's early emphasis was on technology and design, consistent with its Silicon Valley origins. It has since broadened its perspective to include talks on many scientific, cultural, political, humanitarian, and academic topics. It has been curated by Chris Anderson, a British-American businessman, through the non-profit TED Foundation since July 2019 (originally by the non ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Autonomous Driving
A self-driving car, also known as an autonomous car, driver-less car, or robotic car (robo-car), is a car that is capable of traveling without human input.Xie, S.; Hu, J.; Bhowmick, P.; Ding, Z.; Arvin, F.,Distributed Motion Planning for Safe Autonomous Vehicle Overtaking via Artificial Potential Field IEEE Transactions on Intelligent Transportation Systems, 2022. Self-driving cars use sensors to perceive their surroundings, such as optical and thermographic cameras, radar, lidar, ultrasound/sonar, GPS, odometry and inertial measurement units. Control systems interpret sensory information to create a three-dimensional model of the surroundings. Based on the model, the car identifies appropriate navigation paths, and strategies for managing traffic controls (stop signs, etc.) and obstacles.Hu, J.; Bhowmick, P.; Jang, I.; Arvin, F.; Lanzon, A.,A Decentralized Cluster Formation Containment Framework for Multirobot Systems IEEE Transactions on Robotics, 2021. Once the techn ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Chris Anderson (entrepreneur)
Chris Anderson (born 1957) is a British-American businessman who is the head of TED, a non-profit organization that provides idea-based talks and hosts an annual conference in Vancouver, British Columbia, Canada. Previously he founded Future Publishing. Early life Anderson was born to British parents in Pakistan in 1957. His father was "an eye surgeon and evangelical Christian", and ran a mobile hospital in rural Pakistan. He has two sisters, and is the middle child. He studied at Woodstock School in the Himalayan mountains of Mussoorie, Uttarakhand, India briefly, before moving to Monkton Combe School, a boarding school in Bath, England. At the University of Oxford, Anderson first studied physics. He changed to the subjects of philosophy, politics and economics, graduating in 1978. Career Anderson began a career in journalism, working in newspapers and radio. He produced a world news service in the Seychelles. After returning in 1984 to the UK, Anderson was captivated by ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
