AI Data Center Kentucky

AI Data Center Kentucky — independent reviews, comparisons, pricing and step-by-step guides on Aizhi.

  • KeyBase

    KeyBase

    KeyBase is a database and web application for managing and deploying interactive taxonomic keys for plants and animals developed by the Royal Botanic Gardens Victoria. KeyBase provides a medium where pathway keys which were traditionally developed for print and other classical types of media, can be used more effectively in the internet environment. The platform uses a concept called "keys" which can be easily linked together, joined with other keys, or merged into larger other seamless keys groups, with each still available to be browsed independently. Keys in the KeyBase database can be filtered and displayed in a variety of ways, filters, and formats.

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  • Open Sound Control

    Open Sound Control

    Open Sound Control (OSC) is a protocol for networking sound synthesizers, computers, and other multimedia devices for purposes such as musical performance or show control. OSC's advantages include interoperability, accuracy, flexibility and enhanced organization and documentation. Its disadvantages include higher bandwidth requirements, increased load on embedded processors, and lack of standardized messages/interoperability. The first specification was released in March 2002. == Motivation == OSC is a content format developed at CNMAT by Adrian Freed and Matt Wright comparable to XML, WDDX, or JSON. It was originally intended for sharing music performance data (gestures, parameters and note sequences) between musical instruments (especially electronic musical instruments such as synthesizers), computers, and other multimedia devices. OSC is sometimes used as an alternative to the 1983 MIDI standard, when higher resolution and a richer parameter space is desired. OSC messages are transported across the internet and within local subnets using UDP/IP and Ethernet. OSC messages between gestural controllers are usually transmitted over serial endpoints of USB wrapped in the SLIP protocol. == Features == OSC's main features, compared to MIDI, include: Open-ended, dynamic, URI-style symbolic naming scheme Symbolic and high-resolution numeric data Pattern matching language to specify multiple recipients of a single message High resolution time tags "Bundles" of messages whose effects must occur simultaneously == Applications == There are dozens of OSC applications, including real-time sound and media processing environments, web interactivity tools, software synthesizers, programming languages and hardware devices. OSC has achieved wide use in fields including musical expression, robotics, video performance interfaces, distributed music systems and inter-process communication. The TUIO community standard for tangible interfaces such as multitouch is built on top of OSC. Similarly the GDIF system for representing gestures integrates OSC. OSC is used extensively in experimental musical controllers, and has been built into several open source and commercial products. The Open Sound World (OSW) music programming language is designed around OSC messaging. OSC is the heart of the DSSI plugin API, an evolution of the LADSPA API, in order to make the eventual GUI interact with the core of the plugin via messaging the plugin host. LADSPA and DSSI are APIs dedicated to audio effects and synthesizers. In 2007, a standardized namespace within OSC called SYN, for communication between controllers, synthesizers and hosts, was proposed. == Design == OSC messages consist of an address pattern (such as /oscillator/4/frequency), a type tag string (such as ,fi for a float32 argument followed by an int32 argument), and the arguments themselves (which may include a time tag). Address patterns form a hierarchical name space, reminiscent of a Unix filesystem path, or a URL, and refer to "Methods" inside the server, which are invoked with the attached arguments. Type tag strings are a compact string representation of the argument types. Arguments are represented in binary form with four-byte alignment. The core types supported are 32-bit two's complement signed integers 32-bit IEEE floating point numbers Null-terminated arrays of eight-bit encoded data (C-style strings) arbitrary sized blob (e.g. audio data, or a video frame) An example message is included in the spec (with null padding bytes represented by ␀): /oscillator/4/frequency␀,f␀␀, Followed by the 4-byte float32 representation of 440.0: 0x43dc0000. Messages may be combined into bundles, which themselves may be combined into bundles, etc. Each bundle contains a timestamp, which determines whether the server should respond immediately or at some point in the future. Applications commonly employ extensions to this core set. More recently some of these extensions such as a compact Boolean type were integrated into the required core types of OSC 1.1. The advantages of OSC over MIDI are primarily internet connectivity; data type resolution; and the comparative ease of specifying a symbolic path, as opposed to specifying all connections as seven-bit numbers with seven-bit or fourteen-bit data types. This human-readability has the disadvantage of being inefficient to transmit and more difficult to parse by embedded firmware, however. The spec does not define any particular OSC Methods or OSC Containers. All messages are implementation-defined and vary from server to server.

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  • Web syndication

    Web syndication

    Web syndication is making content available from one website to other sites. Most commonly, websites are made available to provide either summaries or full renditions of a website's recently added content. The term may also describe other kinds of content licensing for reuse. Contemporary web syndicates include: MSN, Excite, and Yahoo! News. == Motivation == For the subscribing sites, syndication is an effective way of adding greater depth and immediacy of information to their pages, making them more attractive to users. For the provider site, syndication increases exposure. This generates new traffic for the provider site—making syndication an easy and relatively cheap, or even free, form of advertisement. Content syndication has become an effective strategy for link building, as search engine optimization has become an increasingly important topic among website owners and online marketers. Links embedded within the syndicated content are typically optimized around anchor terms that will point an optimized link back to the website that the content author is trying to promote. These links tell the algorithms of the search engines that the website being linked to is an authority for the keyword that is being used as the anchor text. However the rollout of Google Panda's algorithm may not reflect this authority in its SERP rankings based on quality scores generated by the sites linking to the authority. The prevalence of web syndication is also of note to online marketers, since web surfers are becoming increasingly wary of providing personal information for marketing materials (such as signing up for a newsletter) and expect the ability to subscribe to a feed instead. Although the format could be anything transported over HTTP, such as HTML or JavaScript, it is more commonly XML. Web syndication formats include RSS, Atom, and JSON Feed. == History == Syndication first arose in earlier media such as print, radio, and television, allowing content creators to reach a wider audience. In the case of radio, the United States Federal government proposed a syndicate in 1924 so that the country's executives could quickly and efficiently reach the entire population. In the case of television, it is often said that "Syndication is where the real money is." Additionally, syndication accounts for the bulk of TV programming. One predecessor of web syndication is the Meta Content Framework (MCF), developed in 1996 by Ramanathan V. Guha and others in Apple Computer's Advanced Technology Group. Today, millions of online publishers, including newspapers, commercial websites, and blogs, distribute their news headlines, product offers, and blog postings in the news feed. == As a commercial model == Conventional syndication businesses such as Reuters and Associated Press thrive on the internet by offering their content to media partners on a subscription basis, using business models established in earlier media forms. Commercial web syndication can be categorized in three ways: by business models by types of content by methods for selecting distribution partners Commercial web syndication involves partnerships between content producers and distribution outlets. There are different structures of partnership agreements. One such structure is licensing content, in which distribution partners pay a fee to the content creators for the right to publish the content. Another structure is ad-supported content, in which publishers share revenues derived from advertising on syndicated content with that content's producer. A third structure is free, or barter syndication, in which no currency changes hands between publishers and content producers. This requires the content producers to generate revenue from another source, such as embedded advertising or subscriptions. Alternatively, they could distribute content without remuneration. Typically, those who create and distribute content free are promotional entities, vanity publishers, or government entities. Types of content syndicated include RSS or Atom Feeds and full content. With RSS feeds, headlines, summaries, and sometimes a modified version of the original full content is displayed on users' feed readers. With full content, the entire content—which might be text, audio, video, applications/widgets, or user-generated content—appears unaltered on the publisher's site. There are two methods for selecting distribution partners. The content creator can hand-pick syndication partners based on specific criteria, such as the size or quality of their audiences. Alternatively, the content creator can allow publisher sites or users to opt into carrying the content through an automated system. Some of these automated "content marketplace" systems involve careful screening of potential publishers by the content creator to ensure that the material does not end up in an inappropriate environment. Just as syndication is a source of profit for TV producers and radio producers, it also functions to maximize profit for Internet content producers. As the Internet has increased in size it has become increasingly difficult for content producers to aggregate a sufficiently large audience to support the creation of high-quality content. Syndication enables content creators to amortize the cost of producing content by licensing it across multiple publishers or by maximizing the distribution of advertising-supported content. A potential drawback for content creators, however, is that they can lose control over the presentation of their content when they syndicate it to other parties. Distribution partners benefit by receiving content either at a discounted price, or free. One potential drawback for publishers, however, is that because the content is duplicated at other publisher sites, they cannot have an "exclusive" on the content. For users, the fact that syndication enables the production and maintenance of content allows them to find and consume content on the Internet. One potential drawback for them is that they may run into duplicate content, which could be an annoyance. == E-commerce == Web syndication has been used to distribute product content such as feature descriptions, images, and specifications. As manufacturers are regarded as authorities and most sales are not achieved on manufacturer websites, manufacturers allow retailers or dealers to publish the information on their sites. Through syndication, manufacturers may pass relevant information to channel partners. Such web syndication has been shown to increase sales. Web syndication has also been found effective as a search engine optimization technique.

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  • ISO/IEC 11801

    ISO/IEC 11801

    International standard ISO/IEC 11801 Information technology — Generic cabling for customer premises specifies general-purpose telecommunication cabling systems (structured cabling) that are suitable for a wide range of applications (analog and ISDN telephony, various data communication standards, building control systems, factory automation). It is published by ISO/IEC JTC 1/SC 25/WG 3 of the International Organization for Standardization (ISO) and the International Electrotechnical Commission (IEC). It covers both balanced copper cabling and optical fibre cabling. The standard was designed for use within commercial premises that may consist of either a single building or of multiple buildings on a campus. It was optimized for premises that span up to 3 km, up to 1 km2 office space, with between 50 and 50,000 persons, but can also be applied for installations outside this range. A major revision was released in November 2017, unifying requirements for commercial, home and industrial networks. == Classes and categories == The standard defines several link/channel classes and cabling categories of twisted-pair copper interconnects, which differ in the maximum frequency for which a certain channel performance is required: Class A: Up to 100 kHz using Category 1 cable and connectors Class B: Up to 1 MHz using Category 2 cable and connectors Class C: Up to 16 MHz using Category 3 cable and connectors Class D: Up to 100 MHz using Category 5e cable and connectors Class E: Up to 250 MHz using Category 6 cable and connectors Class EA: Up to 500 MHz using category 6A cable and connectors (Amendments 1 and 2 to ISO/IEC 11801, 2nd Ed.) Class F: Up to 600 MHz using Category 7 cable and connectors Class FA: Up to 1 GHz (1000 MHz) using Category 7A cable and connectors (Amendments 1 and 2 to ISO/IEC 11801, 2nd Ed.) Class BCT-B: Up to 1 GHz (1000 MHz) using with coaxial cabling for BCT applications. (ISO/IEC 11801-1, Edition 1.0 2017-11) Class I: Up to 2 GHz (2000 MHz) using Category 8.1 cable and connectors (ISO/IEC 11801-1, Edition 1.0 2017-11) Class II: Up to 2 GHz (2000 MHz) using Category 8.2 cable and connectors (ISO/IEC 11801-1, Edition 1.0 2017-11) The standard link impedance is 100 Ω. (The older 1995 version of the standard also permitted 120 Ω and 150 Ω in Classes A−C, but this was removed from the 2002 edition.) The standard defines several classes of optical fiber interconnect: OM1: Multimode, 62.5 μm core; minimum modal bandwidth of 200 MHz·km at 850 nm OM2: Multimode, 50 μm core; minimum modal bandwidth of 500 MHz·km at 850 nm OM3: Multimode, 50 μm core; minimum modal bandwidth of 2000 MHz·km at 850 nm OM4: Multimode, 50 μm core; minimum modal bandwidth of 4700 MHz·km at 850 nm OM5: Multimode, 50 μm core; minimum modal bandwidth of 4700 MHz·km at 850 nm and 2470 MHz·km at 953 nm OS1: Single-mode, maximum attenuation 1 dB/km at 1310 and 1550 nm OS1a: Single-mode, maximum attenuation 1 dB/km at 1310, 1383, and 1550 nm OS2: Single-mode, maximum attenuation 0.4 dB/km at 1310, 1383, and 1550 nm Grandfathered === OM5 === OM5 fiber is designed for wideband applications using SWDM multiplexing of 4–16 carriers (40G=4λ×10G, 100G=4λ×25G, 400G=4×4λ×25G) in the 850–953 nm range. === Category 7 === Class F channel and Category 7 cable are backward compatible with Class D/Category 5e and Class E/Category 6. Class F features even stricter specifications for crosstalk and system noise than Class E. To achieve this, shielding was added for individual wire pairs and the cable as a whole. Unshielded cables rely on the quality of the twists to protect from EMI. This involves a tight twist and carefully controlled design. Cables with individual shielding per pair such as Category 7 rely mostly on the shield and therefore have pairs with longer twists. The Category 7 cable standard was ratified in 2002, and primarily introduced to support 10 gigabit Ethernet over 100 m of copper cabling. Like the earlier standards, it contains four twisted copper wire pairs rated for transmission frequencies of up to 600 MHz. However, in 2006, Category 6A was ratified for Ethernet to allow 10 Gbit/s while still using the conventional 8P8C connector. Care is required to avoid signal degradation by mixing cable and connectors not designed for that use, however similar. Most manufacturers of active equipment and network cards have chosen to support the 8P8C for their 10 gigabit Ethernet products on copper and not GG45, ARJ45, or TERA connectors as Class F would have originally called for. Therefore, the Category 6 specification was revised to Category 6A to permit this use; products therefore require a Class EA channel (ie, Cat 6A). As of 2019, some equipment has been introduced which has connectors supporting the Class F (Category 7) channel. Note, however, that Category 7 is not recognized by the TIA/EIA. === Category 7A === Class FA (Class F Augmented) channels and Category 7A cables, introduced by ISO 11801 Edition 2 Amendment 2 (2010), are defined at frequencies up to 1000 MHz. The intent of the Class FA was to possibly support the future 40 gigabit Ethernet: 40GBASE-T. Simulation results have shown that 40 gigabit Ethernet may be possible at 50 meters and 100 gigabit Ethernet at 15 meters. In 2007, researchers at Pennsylvania State University predicted that either 32 nm or 22 nm circuits would allow for 100 gigabit Ethernet at 100 meters. However, in 2016, the IEEE 802.3bq working group ratified the amendment 3 which defines 25GBASE-T and 40GBASE-T on Category 8 cabling specified to 2000 MHz. The Class FA therefore does not support 40G Ethernet. As of 2025, there is no equipment that has connectors supporting the Class FA (Category 7A) channel. Category 7A is not recognized in TIA/EIA. === Category 8 === Category 8 was ratified by the TR43 working group under ANSI/TIA 568-C.2-1. It is defined up to 2000 MHz and only for distances up to 30 m or 36 m, depending on the patch cords used. ISO/IEC JTC 1/SC 25/WG 3 developed the equivalent standard ISO/IEC 11801-1:2017/COR 1:2018, with two options: Class I channel (Category 8.1 cable): minimum cable design U/FTP or F/UTP, fully backward compatible and interoperable with Class EA (Category 6A) using 8P8C connectors; Class II channel (Category 8.2 cable): F/FTP or S/FTP minimum, interoperable with Class FA (Category 7A) using TERA or GG45. == Abbreviations for twisted pairs == Annex E, Acronyms for balanced cables, provides a system to specify the exact construction for both unshielded and shielded balanced twisted pair cables. It uses three letters—U for unshielded, S for braided shielding, and F for foil shielding—to form a two-part abbreviation in the form of xx/xTP, where the first part specifies the type of overall cable shielding, and the second part specifies shielding for individual cable elements. Common cable types include U/UTP (unshielded cable); U/FTP (individual pair shielding without the overall screen); F/UTP, S/UTP, or SF/UTP (overall screen without individual shielding); and F/FTP, S/FTP, or SF/FTP (overall screen with individual foil shielding). == 2017 edition == In November 2017, a new edition was released by ISO/IEC JTC 1/SC 25 "Interconnection of information technology equipment" subcommittee. It is a major revision of the standard which has unified several prior standards for commercial, home, and industrial networks, as well as data centers, and defines requirements for generic cabling and distributed building networks. The new series of standards replaces the former 11801 standard and includes six parts: == Versions == ISO/IEC 11801:1995 (Ed. 1) ISO/IEC 11801:2000 (Ed. 1.1) – Edition 1, Amendment 1 ISO/IEC 11801:2002 (Ed. 2) ISO/IEC 11801:2008 (Ed. 2.1) – Edition 2, Amendment 1 ISO/IEC 11801:2010 (Ed. 2.2) – Edition 2, Amendment 2 ISO/IEC 11801-1:2017, -1:2017/Cor 1:2018, -2:2017, -3:2017, -3:2017/Amd 1:2021, -3:2017/Cor 1:2018, -4:2017, -4:2017/Cor 1:2018, -5:2017, -5:2017/Cor 1:2018, -6:2017, -6:2017/Cor 1:2018 (As of September 2023, this set is current.)

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  • Weak supervision

    Weak supervision

    Weak supervision (also known as semi-supervised learning) is a paradigm in machine learning, the relevance and notability of which increased with the advent of large language models due to the large amount of data required to train them. It is characterized by using a combination of a small amount of human-labeled data (exclusively used in more expensive and time-consuming supervised learning paradigm), followed by a large amount of unlabeled data (used exclusively in unsupervised learning paradigm). In other words, the desired output values are provided only for a subset of the training data. The remaining data is unlabeled or imprecisely labeled. Intuitively, it can be seen as an exam and labeled data as sample problems that the teacher solves for the class as an aid in solving another set of problems. In the transductive setting, these unsolved problems act as exam questions. In the inductive setting, they become practice problems of the sort that will make up the exam. == Problem == The acquisition of labeled data for a learning problem often requires a skilled human agent (e.g. to transcribe an audio segment) or a physical experiment (e.g. determining the 3D structure of a protein or determining whether there is oil at a particular location). The cost associated with the labeling process thus may render large, fully labeled training sets infeasible, whereas acquisition of unlabeled data is relatively inexpensive. In such situations, semi-supervised learning can be of great practical value. Semi-supervised learning is also of theoretical interest in machine learning and as a model for human learning. == Technique == More formally, semi-supervised learning assumes a set of l {\displaystyle l} independently identically distributed examples x 1 , … , x l ∈ X {\displaystyle x_{1},\dots ,x_{l}\in X} with corresponding labels y 1 , … , y l ∈ Y {\displaystyle y_{1},\dots ,y_{l}\in Y} and u {\displaystyle u} unlabeled examples x l + 1 , … , x l + u ∈ X {\displaystyle x_{l+1},\dots ,x_{l+u}\in X} are processed. Semi-supervised learning combines this information to surpass the classification performance that can be obtained either by discarding the unlabeled data and doing supervised learning or by discarding the labels and doing unsupervised learning. Semi-supervised learning may refer to either transductive learning or inductive learning. The goal of transductive learning is to infer the correct labels for the given unlabeled data x l + 1 , … , x l + u {\displaystyle x_{l+1},\dots ,x_{l+u}} only. The goal of inductive learning is to infer the correct mapping from X {\displaystyle X} to Y {\displaystyle Y} . It is unnecessary (and, according to Vapnik's principle, imprudent) to perform transductive learning by way of inferring a classification rule over the entire input space; however, in practice, algorithms formally designed for transduction or induction are often used interchangeably. == Assumptions == In order to make any use of unlabeled data, some relationship to the underlying distribution of data must exist. Semi-supervised learning algorithms make use of at least one of the following assumptions: === Continuity / smoothness assumption === Points that are close to each other are more likely to share a label. This is also generally assumed in supervised learning and yields a preference for geometrically simple decision boundaries. In the case of semi-supervised learning, the smoothness assumption additionally yields a preference for decision boundaries in low-density regions, so few points are close to each other but in different classes. === Cluster assumption === The data tend to form discrete clusters, and points in the same cluster are more likely to share a label (although data that shares a label may spread across multiple clusters). This is a special case of the smoothness assumption and gives rise to feature learning with clustering algorithms. === Manifold assumption === The data lie approximately on a manifold of much lower dimension than the input space. In this case learning the manifold using both the labeled and unlabeled data can avoid the curse of dimensionality. Then learning can proceed using distances and densities defined on the manifold. The manifold assumption is practical when high-dimensional data are generated by some process that may be hard to model directly, but which has only a few degrees of freedom. For instance, human voice is controlled by a few vocal folds, and images of various facial expressions are controlled by a few muscles. In these cases, it is better to consider distances and smoothness in the natural space of the generating problem, rather than in the space of all possible acoustic waves or images, respectively. == History == The heuristic approach of self-training (also known as self-learning or self-labeling) is historically the oldest approach to semi-supervised learning, with examples of applications starting in the 1960s. The transductive learning framework was formally introduced by Vladimir Vapnik in the 1970s. Interest in inductive learning using generative models also began in the 1970s. A probably approximately correct learning bound for semi-supervised learning of a Gaussian mixture was demonstrated by Ratsaby and Venkatesh in 1995. == Methods == === Generative models === Generative approaches to statistical learning first seek to estimate p ( x | y ) {\displaystyle p(x|y)} , the distribution of data points belonging to each class. The probability p ( y | x ) {\displaystyle p(y|x)} that a given point x {\displaystyle x} has label y {\displaystyle y} is then proportional to p ( x | y ) p ( y ) {\displaystyle p(x|y)p(y)} by Bayes' rule. Semi-supervised learning with generative models can be viewed either as an extension of supervised learning (classification plus information about p ( x ) {\displaystyle p(x)} ) or as an extension of unsupervised learning (clustering plus some labels). Generative models assume that the distributions take some particular form p ( x | y , θ ) {\displaystyle p(x|y,\theta )} parameterized by the vector θ {\displaystyle \theta } . If these assumptions are incorrect, the unlabeled data may actually decrease the accuracy of the solution relative to what would have been obtained from labeled data alone. However, if the assumptions are correct, then the unlabeled data necessarily improves performance. The unlabeled data are distributed according to a mixture of individual-class distributions. In order to learn the mixture distribution from the unlabeled data, it must be identifiable, that is, different parameters must yield different summed distributions. Gaussian mixture distributions are identifiable and commonly used for generative models. The parameterized joint distribution can be written as p ( x , y | θ ) = p ( y | θ ) p ( x | y , θ ) {\displaystyle p(x,y|\theta )=p(y|\theta )p(x|y,\theta )} by using the chain rule. Each parameter vector θ {\displaystyle \theta } is associated with a decision function f θ ( x ) = argmax y p ( y | x , θ ) {\displaystyle f_{\theta }(x)={\underset {y}{\operatorname {argmax} }}\ p(y|x,\theta )} . The parameter is then chosen based on fit to both the labeled and unlabeled data, weighted by λ {\displaystyle \lambda } : argmax Θ ( log ⁡ p ( { x i , y i } i = 1 l | θ ) + λ log ⁡ p ( { x i } i = l + 1 l + u | θ ) ) {\displaystyle {\underset {\Theta }{\operatorname {argmax} }}\left(\log p(\{x_{i},y_{i}\}_{i=1}^{l}|\theta )+\lambda \log p(\{x_{i}\}_{i=l+1}^{l+u}|\theta )\right)} === Low-density separation === Another major class of methods attempts to place boundaries in regions with few data points (labeled or unlabeled). One of the most commonly used algorithms is the transductive support vector machine, or TSVM (which, despite its name, may be used for inductive learning as well). Whereas support vector machines for supervised learning seek a decision boundary with maximal margin over the labeled data, the goal of TSVM is a labeling of the unlabeled data such that the decision boundary has maximal margin over all of the data. In addition to the standard hinge loss ( 1 − y f ( x ) ) + {\displaystyle (1-yf(x))_{+}} for labeled data, a loss function ( 1 − | f ( x ) | ) + {\displaystyle (1-|f(x)|)_{+}} is introduced over the unlabeled data by letting y = sign ⁡ f ( x ) {\displaystyle y=\operatorname {sign} {f(x)}} . TSVM then selects f ∗ ( x ) = h ∗ ( x ) + b {\displaystyle f^{}(x)=h^{}(x)+b} from a reproducing kernel Hilbert space H {\displaystyle {\mathcal {H}}} by minimizing the regularized empirical risk: f ∗ = argmin f ( ∑ i = 1 l ( 1 − y i f ( x i ) ) + + λ 1 ‖ h ‖ H 2 + λ 2 ∑ i = l + 1 l + u ( 1 − | f ( x i ) | ) + ) {\displaystyle f^{}={\underset {f}{\operatorname {argmin} }}\left(\displaystyle \sum _{i=1}^{l}(1-y_{i}f(x_{i}))_{+}+\lambda _{1}\|h\|_{\mathcal {H}}^{2}+\lambda _{2}\sum _{i=l+1}^{l+u}(1-|f(x_{i})|)_{+}\right)} An exact solution is intractable due to the non-convex term ( 1 − | f ( x ) | ) + {\displayst

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  • Digital cinematography

    Digital cinematography

    Digital cinematography is the process of capturing (recording) a motion picture using digital image sensors rather than through film stock. As digital technology has improved in recent years, this practice has become dominant. Since the 2000s, most movies across the world have been captured as well as distributed digitally. Many vendors have brought products to market, including traditional film camera vendors like Arri and Panavision, as well as new vendors like Red, Blackmagic, Silicon Imaging, Vision Research and companies which have traditionally focused on consumer and broadcast video equipment, like Sony, GoPro, and Panasonic. As of 2023, professional 4K digital cameras were approximately equal to 35mm film in their resolution and dynamic range capacity. Some filmmakers still prefer to use film picture formats to achieve the desired results. == History == The basis for digital cameras are metal–oxide–semiconductor (MOS) image sensors. The first practical semiconductor image sensor was the charge-coupled device (CCD), based on MOS capacitor technology. Following the commercialization of CCD sensors during the late 1970s to early 1980s, the entertainment industry slowly began transitioning to digital imaging and digital video over the next two decades. The CCD was followed by the CMOS active-pixel sensor (CMOS sensor), developed in the 1990s. Beginning in the late 1980s, Sony began marketing the concept of "electronic cinematography," utilizing its analog Sony HDVS professional video cameras. The effort met with very little success. However, this led to one of the earliest high definition video shot feature movies, Julia and Julia (1987). Rainbow (1996) was the world's first film to utilize extensive digital post production techniques. Shot entirely with Sony's first Solid State Electronic Cinematography cameras and featuring over 35 minutes of digital image processing and visual effects, all post production, sound effects, editing and scoring were completed digitally. The Digital High Definition image was transferred to a 35mm negative via an electron beam recorder for theatrical release. The first digitally videoed and post produced feature was Windhorse, shot in Tibet and Nepal in 1996 on the Sony DVW-700WS Digital Betacam and the prosumer Sony DCR-VX1000. The offline editing (Avid) and the online post and color work (Roland House / da Vinci) were also all digital. The film, transferred to 35mm negative for theatrical release, won Best U.S. Feature at the Santa Barbara Film Festival in 1998. In 1997, with the introduction of HDCAM recorders and 1920 × 1080 pixel digital professional video cameras based on CCD technology, the idea, now re-branded as "digital cinematography," began to gain traction in the market. Shot and released in 1998, The Last Broadcast is believed by some to be the first feature-length video shot and edited entirely on consumer-level digital equipment. In May 1999, George Lucas challenged the supremacy of the movie-making medium of film for the first time by including footage filmed with high-definition digital cameras in Star Wars: Episode I – The Phantom Menace. The digital footage blended seamlessly with the footage shot on film and he announced later that year he would film its sequels entirely on hi-def digital video. Also in 1999, digital projectors were installed in four theaters for the showing of The Phantom Menace. In May 2000, Vidocq, which was directed by Pitof, began principal photography shot entirely using a Sony HDW-F900 camera, with the video being released in September the next year. According to the Guinness World Records, Vidocq is the first full length feature filmed in digital high resolution. In June 2000, Star Wars: Episode II – Attack of the Clones began principal photography shot entirely using a Sony HDW-F900 camera as Lucas had previously stated. The film was released in May 2002. In May 2001 Once Upon a Time in Mexico was also shot in 24 frame-per-second high-definition digital video, partially developed by George Lucas using a Sony HDW-F900 camera, following Robert Rodriguez's introduction to the camera at Lucas' Skywalker Ranch facility whilst editing the sound for Spy Kids. A lesser-known movie, Russian Ark (2002), was also shot with the same camera and was the first tapeless digital movie, recorded on HDD instead of tape. In 2009, Slumdog Millionaire became the first movie shot mainly in digital to be awarded the Academy Award for Best Cinematography. The highest-grossing movie in the history of cinema, Avatar (2009), not only was shot on digital cameras as well, but also made the main revenues at the box office no longer by film, but digital projection. Major movies shot on digital video overtook those shot on film in 2013. Since 2016 over 90% of major films were shot on digital video. As of 2017, 92% of films are shot on digital. Only 24 major films released in 2018 were shot on 35mm. Since the 2000s, most movies across the world have been captured as well as distributed digitally. Today, cameras from companies like Sony, Panasonic, JVC and Canon offer a variety of choices for shooting high-definition video. At the high-end of the market, there has been an emergence of cameras aimed specifically at the digital cinema market. These cameras from Sony, Vision Research, Arri, Blackmagic Design, Panavision, Grass Valley and Red offer resolution and dynamic range that exceeds that of traditional video cameras, which are designed for the limited needs of broadcast television. == Technology == Digital cinematography captures motion pictures digitally in a process analogous to digital photography. While there is a clear technical distinction that separates the images captured in digital cinematography from video, the term "digital cinematography" is usually applied only in cases where digital acquisition is substituted for film acquisition, such as when shooting a feature film. The term is seldom applied when digital acquisition is substituted for video acquisition, as with live broadcast television programs. === Recording === ==== Cameras ==== Professional cameras include the Sony CineAlta (F) Series, Blackmagic Cinema Camera, Red One, Arri D-20, D-21 and Alexa, Panavision Genesis, Silicon Imaging SI-2K, Thomson Viper, Vision Research Phantom, IMAX 3D camera based on two Vision Research Phantom cores, Weisscam HS-1 and HS-2, GS Vitec noX, and the Fusion Camera System. Independent micro-budget filmmakers have also pressed low-cost consumer and prosumer cameras into service for digital filmmaking. Flagship smartphones like the Apple iPhone have been used to shoot movies like Unsane (shot on the iPhone 7 Plus) and Tangerine (shot on three iPhone 5S phones) and in January 2018, Unsane's director and Oscar winner Steven Soderbergh expressed an interest in filming other productions solely with iPhones going forward. ==== Sensors ==== Digital cinematography cameras capture digital images using image sensors, either charge-coupled device (CCD) sensors or CMOS active-pixel sensors, usually in one of two arrangements. Single chip cameras designed specifically for the digital cinematography market often use a single sensor (much like digital photo cameras), with dimensions similar in size to a 16 or 35 mm film frame or even (as with the Vision 65) a 65 mm film frame. An image can be projected onto a single large sensor exactly the same way it can be projected onto a film frame, so cameras with this design can be made with PL, PV and similar mounts, in order to use the wide range of existing high-end cinematography lenses available. Their large sensors also let these cameras achieve the same shallow depth of field as 35 or 65 mm motion picture film cameras, which many cinematographers consider an essential visual tool. Codecs Professional raw video recording codecs include Blackmagic Raw, Red Raw, Arri Raw and Canon Raw. ==== Video formats ==== Unlike other video formats, which are specified in terms of vertical resolution (for example, 1080p, which is 1920×1080 pixels), digital cinema formats are usually specified in terms of horizontal resolution. As a shorthand, these resolutions are often given in "nK" notation, where n is the multiplier of 1024 such that the horizontal resolution of a corresponding full-aperture, digitized film frame is exactly 1024 n {\displaystyle 1024n} pixels. Here the "K" has a customary meaning corresponding to the binary prefix "kibi" (ki). For instance, a 2K image is 2048 pixels wide, and a 4K image is 4096 pixels wide. Vertical resolutions vary with aspect ratios though; so a 2K image with an HDTV (16:9) aspect ratio is 2048×1152 pixels, while a 2K image with a SDTV or Academy ratio (4:3) is 2048×1536 pixels, and one with a Panavision ratio (2.39:1) would be 2048×856 pixels, and so on. Due to the "nK" notation not corresponding to specific horizontal resolutions per format a 2K image lacking, for example, the typical 35mm film soundtrack space, is only 182

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  • Line splice

    Line splice

    In electrical engineering and telecommunications, a line splice is a joint directly connecting lengths of electrical cables (electrical splice) or optical fibers (optical splice). The splices are often protected by sleeves. == Splicing of copper wires == The splicing of copper wires happens in the following steps: The cores are laid one above the other at the junction. The core insulation is removed. The wires are wrapped two to three times around each other (twisting). The bare veins on a length of about 3 cm "strangle" or "twist". In some cases, the strangulation is soldered. To isolate the splice, an insulating sleeve made of paper or plastic is pushed over it. The splicing of copper wires is mainly used on paper insulated wires. LSA techniques (LSA: soldering, screwing and stripping free) are used to connect copper wires, making the copper wires faster and easier to connect. LSA techniques include: Wire connection sleeves (AVH = Adernverbindungshülsen) and other crimp connectors. The two wires to be connected are inserted into the AVH without being stripped, which is then compressed with special pliers. The about 2 cm long AVH consist of contact, pressure and insulation. For wire connection strips (AVL = Adernverbindungsleisten) several pairs of wires (10 = AVL10 or 20 = AVL20) are inserted, the strip is then closed with a lid and pressed together with a hydraulic press, which ensures the connection. == Splicing of glass fibers == Fiber-optic cables are spliced using a special arc-splicer, with installation cables connected at their ends to respective "pigtails" - short individual fibers with fiber-optic connectors at one end. The splicer precisely adjusts the light-guiding cores of the two ends of the glass fibers to be spliced. The adjustment is done fully automatically in modern devices, whereas in older models this is carried out manually by means of micrometer screws and microscope. An experienced splicer can precisely position the fiber ends within a few seconds. Subsequently, the fibers are fused together (welded) with an electric arc. Since no additional material is added, such as gas welding or soldering, this is called a "fusion splice". Depending on the quality of the splicing process, attenuation values at the splice points are achieved by 0.3 dB, with good splices also below 0.02 dB. For newer generation devices, alignment is done automatically by motors. Here one differentiates core and jacket centering. At core centering (usually single-mode fibers), the fiber cores are aligned. A possible core offset with respect to the jacket is corrected. In the jacket centering (usually in multimode fibers), the fibers are adjusted to each other by means of electronic image processing in front of the splice. When working with good equipment, the damping value is according to experience at max. 0.1 dB. Measurements are made by means of special measuring devices including optical time-domain reflectometry (OTDR). A good splice should have an attenuation of less than 0.3 dB over the entire distance. Finished fiber optic splices are housed in splice boxes. One differentiates: Fusion splice Adhesive splicing Crimp splice or NENP (no-epoxy no-polish), mechanical splice

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  • FactorDaily

    FactorDaily

    FactorDaily is an Indian digital media publication founded in 2016 by Pankaj Mishra and Jayadevan PK. Mishra was formerly an Editor at TechCrunch and the Economic Times. The digital publication was launched with an intent to produce stories on the impact of technology on life in India. == History == FactorDaily began publishing in May 2016, with daily reported stories on technology, culture and life in India. Prior to its launch, the company had raised $1 million in seed funding from Accel India, Blume Ventures, Girish Mathrubootham of Freshdesk, Vijay Shekhar Sharma of PayTm, and Jay Vijayan of Tekion. Josey Puliyenthuruthel John, formerly Managing Editor at Business Today and National Corporate Editor at Mint, later joined the company as a Consulting Editor. In January 2017, FactorDaily launched its first Podcast called The Outliers. The inaugural episode featured a conversation with Manish Sharma of Printo on his journey starting up. == Awards == The FactorDaily team won the Bengaluru Editors Lab 2017, a journalism hackathon organised by the Global Editors Network (GEN). The story titled "India has 3,800 psychiatrists for 1.2bn people. Can tech step in to manage mental health?" won the first prize in the online category of the fifth Schizophrenia Research Foundation’s (SCARF) ‘Media for Mental Health’ awards. The story titled 'The dark hand of tech that stokes sex trafficking in India', won the Stop Slavery media Awards by the Thomson Reuters Foundation for the year 2020.

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  • Cowrie (honeypot)

    Cowrie (honeypot)

    Cowrie is a medium interaction SSH and Telnet honeypot designed to log brute force attacks and shell interaction performed by an attacker. Cowrie also functions as an SSH and telnet proxy to observe attacker behavior to another system. Cowrie was developed from Kippo. == Reception == Cowrie has been referenced in published papers. The Book "Hands-On Ethical Hacking and Network Defense" includes Cowrie in a list of 5 commercial honeypots. === Prior uses === Discussing a honeypot effort called the Project Heisenberg Cloud by Rapid7, Bob Rudis, the company's chief data scientist, told eWEEK, "There are custom Rapid7-developed low- and medium-interaction honeypots used within the framework, along with open-source ones, such as Cowrie." Doug Rickert has experimented with the open-source Cowrie SSH honeypot and wrote about it on Medium. Putting up a simple honeypot isn't difficult, and there are many open-source products besides Cowrie, including the original Honeyd to MongoDB and NoSQL honeypots, to ones that emulate web servers. Some appear to be SCADA or other more advanced applications. === Best practices === Researchers at the SysAdmin, Audit, Network and Security (SANS) institute urged administrators and security researchers to run the latest version of Cowrie on a honeypot to monitor shifts in the type of passwords being scanned for and pattern of attacks on IoT devices. === Discussion and further resources === Attack Detection and Forensics Using Honeypot in an IoT Environment calls Cowrie a "medium interaction honeypot" and describes results from using it for 40 days to capture "all communicated sessions in log files." The book Advances on Data Science also devotes chapter two to "Cowrie Honeypot Dataset and Logging." ICCWS 2018 13th International Conference on Cyber Warfare and Security describes using Cowrie. On the Move to Meaningful Internet Systems: OTM 2019 Conferences includes details of using Cowrie. Splunk, a security tool that can receive information from honeypots, outlines how to set up a honeypot using the open-source Cowrie package.

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  • Deconfliction line

    Deconfliction line

    A deconfliction line is an official line of communications established between militaries who are or could be hostile, to avoid dangerous misunderstandings and miscalculations based on ignorance. The ultimate aim is to avoid accidents and conflict escalation. In the 2010s and 2020s, the US and Russia set up deconfliction lines during the Syrian civil war and Russo-Ukrainian War. They were regularly tested by military staff, and used by air traffic controllers and senior military officers. They were used to avoid midair collisions between aircraft in the same or adjacent airspace, and sometimes to give warning of airstrikes. In April 2017, Russia severed the Syrian line in retaliation for a called strike.

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  • Digital citizen

    Digital citizen

    The term digital citizen is used with different meanings. According to the definition provided by Karen Mossberger, one of the authors of Digital Citizenship: The Internet, Society, and Participation, digital citizens are "those who use the internet regularly and effectively". In this sense, a digital citizen is a person who uses information technology (IT) to engage in society, politics, and government. More recent elaborations of the concept define digital citizenship as the self-enactment of people’s role in society through the use of digital technologies, stressing the empowering and democratizing characteristics of the citizenship idea. These theories aim at taking into account the ever-increasing datafication of contemporary societies (symbolically linked to the Snowden leaks), which has called into question the meaning of “being (digital) citizens in a datafied society”. This condition is also referred to as the “algorithmic society”, characterised by the increasing datafication of social life and the pervasive presence of surveillance practices – see surveillance and surveillance capitalism, the use of artificial intelligence, and Big Data. Datafication presents crucial challenges for the very notion of citizenship, so that data collection can no longer be seen as an issue of privacy alone so that:We cannot simply assume that being a citizen online already means something (whether it is the ability to participate or the ability to stay safe) and then look for those whose conduct conforms to this meaning Instead, the idea of digital citizenship shall reflect the idea that we are no longer mere “users” of technologies since they shape our agency both as individuals and as citizens. Digital citizenship refers to the responsible and respectful use of technology to engage online, evaluate information, and protect human rights. It encompasses skills for communication, collaboration, empathy, privacy protection, and security to prevent data breaches and identity theft. == Digital citizenship in the "algorithmic society" == In the context of the algorithmic society, the question of digital citizenship "becomes one of the extents to which subjects are able to challenge, avoid or mediate their data double in this datafied society”. These reflections put the emphasis on the idea of the digital space (or cyberspace) as a political space where the respect of fundamental rights of the individual shall be granted (with reference both to the traditional ones as well as to new specific rights of the internet [see “digital constitutionalism”]) and where the agency and the identity of the individuals as citizens is at stake. This idea of digital citizenship is thought to be not only active but also performative, in the sense that “in societies that are increasingly mediated through digital technologies, digital acts become important means through which citizens create, enact and perform their role in society.” In particular, for Isin and Ruppert this points towards an active meaning of (digital) citizenship based on the idea that we constitute ourselves as digital citizen by claiming rights on the internet, either by saying or by doing something. == Types of digital participation == People who characterize themselves as digital citizens often use IT extensively—creating blogs, using social networks, and participating in online journalism. Although digital citizenship begins when any child, teen, or adult signs up for an email address, posts pictures online, uses e-commerce to buy merchandise online, and/or participates in any electronic function that is B2B or B2C, the process of becoming a digital citizen goes beyond simple internet activity. According to Thomas Humphrey Marshall, a British sociologist known for his work on social citizenship, a primary framework of citizenship comprises three different traditions: liberalism, republicanism, and ascriptive hierarchy. Within this framework, the digital citizen needs to exist in order to promote equal economic opportunities and increase political participation. In this way, digital technology helps to lower the barriers to entry for participation as a citizen within a society. They also have a comprehensive understanding of digital citizenship, which is the appropriate and responsible behavior when using technology. Since digital citizenship evaluates the quality of an individual's response to membership in a digital community, it often requires the participation of all community members, both visible and those who are less visible. A large part in being a responsible digital citizen encompasses digital literacy, etiquette, online safety, and an acknowledgement of private versus public information. The development of digital citizen participation can be divided into two main stages. The first stage is through information dissemination, which includes subcategories of its own: static information dissemination, characterized largely by citizens who use read-only websites where they take control of data from credible sources in order to formulate judgments or facts. Many of these websites where credible information may be found are provided by the government. dynamic information dissemination, which is more interactive and involves citizens as well as public servants. Both questions and answers can be communicated, and citizens have the opportunity to engage in question-and-answer dialogues through two-way communication platforms The second stage of digital citizen participation is citizen deliberation, which evaluates what type of participation and role that they play when attempting to ignite some sort of policy change. static citizen participants can play a role by engaging in online polls as well as through complaints and recommendations sent up, mainly toward the government who can create changes in policy decisions. dynamic citizen participants can deliberate amongst others on their thoughts and recommendations in town hall meetings or various media sites. One potential advantage of online participation through digital citizenship is increased social inclusion. In a report on civic engagement, citizen-powered democracy can be initiated either through information shared through the web, direct communication signals made by the state toward the public, and social media tactics from both private and public companies. In fact, it was found that the community-based nature of social media platforms allow individuals to feel more socially included and informed about political issues that peers have also been found to engage with, otherwise known as a "second-order effect." Understanding strategic marketing on social media would further explain social media customers’ participation. Two types of opportunities rise as a result, the first being the ability to lower barriers that can make exchanges much easier. In addition, they have the chance to participate in transformative disruption, giving people who have a historically lower political engagement to mobilize in a much easier and convenient fashion. Nonetheless, there are several challenges that face the presence of digital technologies in political participation. Both current as well as potential challenges can create significant risks for democratic processes. Not only is digital technology still seen as relatively ambiguous, it was also seen to have "less inclusivity in democratic life." Demographic groups differ considerably in the use of technology, and thus, one group could potentially be more represented than another as a result of digital participation. Another primary challenge consists in the ideology of a "filter bubble" effect. Alongside a tremendous spread of false information, internet users could reinforce existing prejudices and assist in polarizing disagreements in the public sphere. This can lead to misinformed voting and decisions based on exposure rather than on pure knowledge. A communication technology director, Van Dijk, stated, "Computerized information campaigns and mass public information systems have to be designed and supported in such a way that they help to narrow the gap between the 'information rich' and 'information poor' otherwise the spontaneous development of ICT will widen it." Access and equivalent amounts of knowledge behind digital technology must be equivalent in order for a fair system to put into place. Alongside a lack of evidenced support for technology that can be proven to be safe for citizens, the OECD has identified five struggles for the online engagement of citizens: Scale: To what extent can a society allow every individual's voice to be heard, but also not be lost in the mass debate? This can be extremely challenging for the government, which may not effectively know how to listen and respond to each individual contribution. Capacity: How can digital technology offer citizens more information on public policy-making? The opportunity for citizens to debate with one another is lacking for acti

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  • MIDI Show Control

    MIDI Show Control

    MIDI Show Control (MSC), is a real-time System Exclusive extension of the international Musical Instrument Digital Interface (MIDI) standard. MSC enables all types of entertainment equipment to communicate with each other through the process of show control. The MIDI Show Control protocol is a technical standard ratified by the MIDI Manufacturers Association in 1991, which allows entertainment control devices to talk with each other and with computers to perform show control functions in live and prerecorded entertainment applications. Just like musical MIDI, MSC does not transmit the actual show media - it simply transmits digital information about a multimedia performance. == How MSC works == When any cue is called by a user (typically a stage manager) and/or preprogrammed timeline in a show control software application, the show controller transmits one or more MSC messages from its 'MIDI Out' port. A typical MSC message sequence is: the user has just called a cue the cue is for lighting device 3 the cue is number 45.8 the cue is in cue list 7 MSC messages are serially transmitted in the same way as musical messages and are fully compatible with all conventional MIDI hardware; however, many modern MSC devices now use Ethernet communications for higher bandwidth and the flexibility afforded by networks. Other performance parameters are also transmitted, such as lighting desk submaster settings using MSC SET messages. All cues that a media control device is capable of playing are assigned MSC messages within the Show Controller's cue list and they are transmitted from its MIDI Out port at the appropriate show time, depending on the actions of the user and the show controller's internally timed sequences. All MSC-compatible instruments follow the MSC specification and thus transmit identical MSC messages for identical MSC events, such as the playing of a certain cue on the media controller. Since they follow a published standard, all MSC devices can communicate with and understand each other, as well as with computers that have been programmed to understand MSC messages using the MSC Command Set. All MSC compatible instruments have a built-in MIDI interface and many now follow one of the various MIDI-over-Ethernet protocols. == History == To create the MSC spec, Charlie Richmond headed the USITT MIDI Forum on their Callboard Network in 1990, which included developers and designers from the theatre sound and lighting industry from around the world. It is believed that this was the first international standard to be developed without a single physical meeting of the participants. This Forum created the MSC standard between January and September 1990. This was ratified by the MIDI Manufacturers Association (MMA) in January 1991, and the Japan MIDI Standards Committee (JMSC) later that year, becoming a part of the standard MIDI specification in August 1991. The first show to fully use the MSC specification was the Magic Kingdom Parade at Walt Disney World's Magic Kingdom in September 1991. == MIDI Show Control software ==

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  • Sunrise Calendar

    Sunrise Calendar

    Sunrise is a discontinued electronic calendar application for mobile and desktop. The service was launched in 2013 by designers Pierre Valade and Jeremy Le Van. In October 2015, Microsoft announced that they had merged the Sunrise Calendar team into the larger Microsoft Outlook team where they will work closely with the Microsoft Outlook Mobile service. == History == The first iteration of Sunrise launched in 2012 and was a daily email digest of appointments, events and birthdays. Sunrise was launched initially as an iPhone application on February 19, 2013. In June 2013, Sunrise raised $2.2 million (~$2.91 million in 2024) in venture funding from Resolute.vc, NextView Ventures, Lerer Hippeau Ventures, SV Angel, and other angel investment firms like Loïc Le Meur, Dave Morin, Fabrice Grinda. In May 2014, Sunrise launched on Android as well as on the web via a web application. In July 2014, Sunrise announced it had raised $6 million (~$7.81 million in 2024) Series A from Balderton Capital. Bernard Liautaud joined the board. On February 11, 2015, Sunrise Atelier, Inc. was acquired by Microsoft for US$100 million (~$129 million in 2024). On October 28, 2015, Microsoft announced that Sunrise would be discontinued, and its functionality merged into Outlook Mobile. Microsoft later stated that the app would permanently cease functioning on August 31, 2016, but the shutdown was delayed to September 13, 2016, to coincide with an update to Outlook Mobile that incorporates aspects of Sunrise into its calendar interface. == Features == Sunrise allowed users to connect with Google Calendar, iCloud calendar and with Exchange Server. The following third-party services featured integration with Sunrise: Foursquare, GitHub, TripIt, Asana, Evernote, Google Tasks, Trello, Songkick, and Wunderlist. As a web app, users could sign-in and use Sunrise in a web browser, with no downloads required. A native Sunrise app could also be downloaded for OS X 10.9 and later, iOS 8.0 and later (both iPhone and iPad) as well as Android phones and tablets. In May 2015, Sunrise launched Meet, a keyboard for Android and iOS that lets users select available time slots in their calendar to schedule one-to-ones.

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  • Signal-to-crosstalk ratio

    Signal-to-crosstalk ratio

    The signal-to-crosstalk ratio at a specified point in a circuit is the ratio of the power of the wanted signal to the power of the unwanted signal from another channel. The signals are adjusted in each channel so that they are of equal power at the zero transmission level point in their respective channels. The signal-to-crosstalk ratio is usually expressed in dB.

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  • Attention inequality

    Attention inequality

    Attention inequality is the inequality of distribution of attention across users on social networks, people in general, and for scientific papers. Yun Family Foundation introduced "Attention Inequality Coefficient" as a measure of inequality in attention and arguments it by the close interconnection with wealth inequality. == Relationship to economic inequality == Attention inequality is related to economic inequality since attention is an economically scarce good. The same measures and concepts as in classical economy can be applied for attention economy. The relationship develops also beyond the conceptual level—considering the AIDA process, attention is the prerequisite for real monetary income on the Internet. On data of 2018, a significant relationship between likes and comments on Facebook to donations is proven for non-profit organizations. == Attention economy == The attention economy refers to the practice of maximizing the attention users give to a product for advertising-related reasons. Attention economy remains one of the most common forms of advertising, and has been steadily increasing thanks to new technologies such as television, internet and social media. It is one of the most widely-used approaches to economy for its effectiveness for maximising the noticeability of a certain product. == Attention inequality in social media == In social media, attention inequality refers to the unequal distribution of users' attention on social media platforms. This means that instead of an equal distribution of attention, fewer sources receive a disproportionate share of attention, leaving many unnoticed. This phenomenon is possibly the result of social media algorithms, which are commonly designed to drive maximum engagement. This phenomenon is a large factor in the polarization and creation of echo-chambers. Social media algorithms tend to note content that is already performing well and display it to more users, while content that is equally engaging or well-made is not recommended to users. Posts that trigger strong emotions usually out-perform more "uncontroversial" content. When many users interact with the post, it signals the algorithm that the specific post drives engagement. The algorithm then tends to recommend that type of content to an exponential number of people, potentially outperforming "un-emotional" content. These factors, when combined, tend to create an unequal social media environment. == Attention inequality in science == According to a recent 2025 study about research inequality among scientists published in Information Processing and Management, scientific discourse is restricted to a small group of connected scientists, and is frequently not an accurate representation of the whole scientific community. Using citation-network analysis in the fields of nanoscience and chemical physics, the study claims that a group of connected scientists has a significant notability in the scientific community. The calculated connection strength between these scientists is estimated to be about 4.5, the study also says that these authors cite each other four times more often than would be predicted in a random network, whereas ordinary scientists that exist outside of this group only reach an estimated connection strength of 0.9. The study findings suggest that that scientific attention is not distributed by merit, but rather by the connectedness of the scientists involved in the research. == Extent == As data of 2008 shows, 50% of the attention is concentrated on approximately 0.2% of all hostnames, and 80% on 5% of hostnames. The Gini coefficient of attention distribution lay in 2008 at over 0.921 for such commercial domains names as ac.jp and at 0.985 for .org-domains. The Gini coefficient was measured on Twitter in 2016 for the number of followers as 0.9412, for the number of mentions as 0.9133, and for the number of retweets as 0.9034. For comparison, the world's income Gini coefficient was 0.68 in 2005 and 0.904 in 2018. More than 96% of all followers, 93% of the retweets, and 93% of all mentions are owned by 20% of Twitter. == Causes == At least for scientific papers, today's consensus states that inequality is unexplainable by variations of quality and individual talent. The Matthew effect plays a significant role in the emergence of attention inequality—those who already enjoy large amounts of attention get even more attention, and those who do not lose even more. Ranking algorithms based on relevance to the user have been found to alleviate the inequality of the number of posts across topics.

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