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Applications Of Artificial Intelligence
Artificial intelligence (AI) has been used in applications to alleviate certain problems throughout industry and academia. AI, like electricity or computers, is a general purpose technology that has a multitude of applications. It has been used in fields of language translation, image recognition, credit scoring, e-commerce and other domains. Internet and e-commerce Search engines Recommendation systems A recommendation system predicts the "rating" or "preference" a user would give to an item.Francesco Ricci and Lior Rokach and Bracha ShapiraIntroduction to Recommender Systems Handbook Recommender Systems Handbook, Springer, 2011, pp. 1-35 Recommender systems are used in a variety of areas, such as generating playlists for video and music services, product recommendations for online stores, or content recommendations for social media platforms and open web content recommenders.Pankaj Gupta, Ashish Goel, Jimmy Lin, Aneesh Sharma, Dong Wang, and Reza Bosagh ZadeWT ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
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Artificial Intelligence
Artificial intelligence (AI) is intelligence—perceiving, synthesizing, and inferring information—demonstrated by machines, as opposed to intelligence displayed by animals and humans. Example tasks in which this is done include speech recognition, computer vision, translation between (natural) languages, as well as other mappings of inputs. The ''Oxford English Dictionary'' of Oxford University Press defines artificial intelligence as: the theory and development of computer systems able to perform tasks that normally require human intelligence, such as visual perception, speech recognition, decision-making, and translation between languages. AI applications include advanced web search engines (e.g., Google), recommendation systems (used by YouTube, Amazon and Netflix), understanding human speech (such as Siri and Alexa), self-driving cars (e.g., Tesla), automated decision-making and competing at the highest level in strategic game systems (such as chess and Go). ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
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Search Engine
A search engine is a software system designed to carry out web searches. They search the World Wide Web in a systematic way for particular information specified in a textual web search query. The search results are generally presented in a line of results, often referred to as search engine results pages (SERPs). When a user enters a query into a search engine, the engine scans its index of web pages to find those that are relevant to the user's query. The results are then ranked by relevancy and displayed to the user. The information may be a mix of links to web pages, images, videos, infographics, articles, research papers, and other types of files. Some search engines also mine data available in databases or open directories. Unlike web directories and social bookmarking sites, which are maintained by human editors, search engines also maintain real-time information by running an algorithm on a web crawler. Any internet-based content that can't be indexed and sea ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
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DeepFace
DeepFace is a deep learning facial recognition system created by a research group at Facebook. It identifies human faces in digital images. The program employs a nine-layer neural network with over 120 million connection weights and was trained on four million images uploaded by Facebook users. The Facebook Research team has stated that the DeepFace method reaches an accuracy of 97.35% ± 0.25% on Labeled Faces in the Wild (LFW) data set where human beings have 97.53%. This means that DeepFace is sometimes more successful than human beings. As a result of growing societal concerns Meta announced that it plans to shut down Facebook facial recognition system, deleting the face scan data of more than one billion users. This change will represent one of the largest shifts in facial recognition usage in the technology’s history. Facebook planned to delete by December 2021 more than one billion facial recognition templates, which are digital scans of facial features. However, it did no ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
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Google Image Labeler
Google Image Labeler is a feature, in the form of a game, of Google Images that allows the user to label random images to help improve the quality of Google's image search results. It was online from 2006 to 2011 and relaunched in 2016. History Luis von Ahn developed the ESP Game, a game in which two people were simultaneously given an image, with no way to communicate, other than knowing the matching label for each picture or the pass signal. The ESP Game had been licensed by Google in the form of the Google Image Labeler and launched this service, as a beta on August 31, 2006. Players noticed various subtle changes in the game over time. In the earliest months, through about November 2006, players could see each other's guesses during play by mousing over the image. When "congenita abuse" started (see below) the player could see if their partner was using those terms, while the game was underway. The game was changed so that only at the end of the game could a player click ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
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Face Unlock
The version history of the Android mobile operating system began with the public release of the Android beta on November 5, 2007. The first commercial version, Android 1.0, was released on September 23, 2008. Android is developed by Google in which new major releases are announced at Google I/O along with its first public beta to supported Google Pixel devices and its stable version released later in the year. Overview The development of Android started in 2003 by Android, Inc., which was purchased by Google in 2005. There were at least two internal releases of the software inside Google and the Open Handset Alliance (OHA) before the beta version was released. The beta was released on November 5, 2007, while the software development kit (SDK) was released on November 12, 2007. Several public beta versions of the SDK were released. These releases were done through software emulation as physical devices did not exist to test the operating system. Both the operating system itse ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
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Face ID
Face ID is a facial recognition system designed and developed by Apple Inc. for the iPhone and iPad Pro. The system allows biometric authentication for unlocking a device, making payments, accessing sensitive data, providing detailed facial expression tracking for Animoji, as well as six degrees of freedom (6DOF) head-tracking, eye-tracking, and other features. Initially released in November 2017 with the iPhone X, it has since been updated and introduced to several new iPhone models, and all iPad Pro models. The Face ID hardware consists of a sensor with three modules; a dot projector that projects a grid of small infrared dots onto a user's face, a module called the flood illuminator that shines infrared light at the face, and an infrared camera which takes an infrared picture of the user, reads the resulting pattern and generates a 3D facial map. This map is compared with the registered face using a secure subsystem, and the user is authenticated if the two faces match suffi ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
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Facial Recognition System
A facial recognition system is a technology capable of matching a human face from a digital image or a video frame against a database of faces. Such a system is typically employed to authenticate users through ID verification services, and works by pinpointing and measuring facial features from a given image. Development began on similar systems in the 1960s, beginning as a form of computer application. Since their inception, facial recognition systems have seen wider uses in recent times on smartphones and in other forms of technology, such as robotics. Because computerized facial recognition involves the measurement of a human's physiological characteristics, facial recognition systems are categorized as biometrics. Although the accuracy of facial recognition systems as a biometric technology is lower than iris recognition and fingerprint recognition, it is widely adopted due to its contactless process. Facial recognition systems have been deployed in advanced human–comput ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
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Statistical Machine Translation
Statistical machine translation (SMT) is a machine translation paradigm where translations are generated on the basis of statistical models whose parameters are derived from the analysis of bilingual text corpora. The statistical approach contrasts with the rule-based approaches to machine translation as well as with example-based machine translation, and has more recently been superseded by neural machine translation in many applications (see this article's final section). The first ideas of statistical machine translation were introduced by Warren Weaver in 1949, including the ideas of applying Claude Shannon's information theory. Statistical machine translation was re-introduced in the late 1980s and early 1990s by researchers at IBM's Thomas J. Watson Research Center and has contributed to the significant resurgence in interest in machine translation in recent years. Before the introduction of neural machine translation, it was by far the most widely studied machine translati ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
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Neural Machine Translation
Neural machine translation (NMT) is an approach to machine translation that uses an artificial neural network to predict the likelihood of a sequence of words, typically modeling entire sentences in a single integrated model. Properties They require only a fraction of the memory needed by traditional statistical machine translation (SMT) models. Furthermore, unlike conventional translation systems, all parts of the neural translation model are trained jointly (end-to-end) to maximize the translation performance. History Deep learning applications appeared first in speech recognition in the 1990s. The first scientific paper on using neural networks in machine translation appeared in 2014. This year Bahdanau et al.Bahdanau D, Cho K, Bengio Y. Neural machine translation by jointly learning to align and translate. In: Proceedings of the 3rd International Conference on Learning Representations; 2015 May 7–9; San Diego, USA; 2015. and Sutskever et al.Sutskever I, Vinyals O, Le QV. Sequ ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
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Pragmatics
In linguistics and related fields, pragmatics is the study of how context contributes to meaning. The field of study evaluates how human language is utilized in social interactions, as well as the relationship between the interpreter and the interpreted. Linguists who specialize in pragmatics are called pragmaticians. Pragmatics encompasses phenomena including implicature, speech acts, relevance and conversation,Mey, Jacob L. (1993) ''Pragmatics: An Introduction''. Oxford: Blackwell (2nd ed. 2001). as well as nonverbal communication. Theories of pragmatics go hand-in-hand with theories of semantics, which studies aspects of meaning, and syntax which examines sentence structures, principles, and relationships. The ability to understand another speaker's intended meaning is called ''pragmatic competence''. Pragmatics emerged as its own subfield in the 1950s after the pioneering work of J.L. Austin and Paul Grice. Origin of the field Pragmatics was a reaction to structu ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
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Semantics
Semantics (from grc, σημαντικός ''sēmantikós'', "significant") is the study of reference, meaning, or truth. The term can be used to refer to subfields of several distinct disciplines, including philosophy, linguistics and computer science. History In English, the study of meaning in language has been known by many names that involve the Ancient Greek word (''sema'', "sign, mark, token"). In 1690, a Greek rendering of the term ''semiotics'', the interpretation of signs and symbols, finds an early allusion in John Locke's ''An Essay Concerning Human Understanding'': The third Branch may be called [''simeiotikí'', "semiotics"], or the Doctrine of Signs, the most usual whereof being words, it is aptly enough termed also , Logick. In 1831, the term is suggested for the third branch of division of knowledge akin to Locke; the "signs of our knowledge". In 1857, the term '' semasiology'' (borrowed from German ''Semasiologie'') is attested in Josiah W. Gibbs ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
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DeepL Translator
DeepL Translator is a neural machine translation service launched in August 2017 and owned by DeepL SE, based in Cologne. The translating system was first developed within Linguee and launched as entity ''DeepL''. It initially offered translations between seven European languages and was gradually expanded to support 29 languages. Additionally, approximations of language equivalence are proposed among all of those languages, using a two-step process via an English pivot. It offers a paid subscription for additional features and access to its translation application programming interface. Service Translation methodology The service uses a proprietary algorithm with convolutional neural networks (CNNs) that have been trained with the Linguee database. According to the developers, the service uses a newer, improved architecture of neural networks, which results in a more natural sound of translations compared to competing services. The translation is said to be generated u ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |