AI Assistant Card

AI Assistant Card — independent reviews, comparisons, pricing and step-by-step guides on Aizhi.

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  Corpus of Linguistic Acceptability

  Corpus of Linguistic Acceptability (CoLA) is a dataset the primary purpose of which is to serve as a benchmark for evaluating the ability of artificial neural networks, including large language models, to judge the grammatical correctness of sentences. It consists of 10,657 English sentences from published linguistics literature that were manually labeled either as grammatical or ungrammatical. == Public version == The publicly available version of CoLA contains 9,594 sentences that belong to training and development sets. It excludes 1,063 sentences reserved for a held-out test set.

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  Feature detection (web development)

  Feature detection (also feature testing) is a technique used in web development for handling differences between runtime environments (typically web browsers or user agents), by programmatically testing for clues that the environment may or may not offer certain functionality. This information is then used to make the application adapt in some way to suit the environment: to make use of certain APIs, or tailor for a better user experience. Its proponents claim it is more reliable and future-proof than other techniques like user agent sniffing and browser-specific CSS hacks. == Techniques == A feature test can take many forms. It is essentially any snippet of code which gives some level of confidence that a required feature is indeed supported. However, in contrast to other techniques, feature detection usually focuses on performing actions which directly relate to the feature to be detected, rather than heuristics. === JavaScript === JavaScript feature detection can inspect the DOM and the local JavaScript environment to test whether browser features or APIs are supported. The simplest technique is to check for the existence of a relevant object or property. For example, the Geolocation API (used for accessing the device's knowledge of its geographical location, possibly obtained from a GPS navigation device) exposes a geolocation property on the navigator object in the DOM; the presence of which implies the Geolocation API is supported: if ('geolocation' in navigator) { // Geolocation API is supported } For a higher level of confidence, some feature tests will attempt to invoke the feature then look for clues that it behaved properly. For example, a test for support for cookies might attempt to set a value as a cookie and then verify it can be read back. === CSS === In CSS, the at-rule @supports introduced in 2015 allows to test if a given feature is supported. For instance the following code activates the declarations only if the user agent supports display: flex: == Undetectables == Some browser features are considered undetectable, because no clues are known to give sufficient confidence that a feature is supported. These are often because of limited information available to the JavaScript environment in the browser; generally features must be exposed via the DOM in some way in order to be detectable using JavaScript. When undetectables are encountered, it is common to turn to user agent sniffing as an alternative mechanism, or to employ defensive coding to minimise the impact if the feature turns out not to be supported. The Modernizr project maintains a record of known undetectables on their wiki.

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  Awwwards

  Awwwards (Awwwards Online SL) is an organization that hosts web design competitions and conferences across Europe and the United States. Website owners and developers can participate by submitting their websites for review. Submissions are assessed by a jury, and top entries are presented and awarded prizes on a rotational basis. == Nomination process == Web designers submit their websites through Awwwards' platform for consideration for the Site of the Day. A jury, composed of industry professionals, and the Awwwards community evaluate the entries. The best daily sites are published annually in "The 365 Best Websites Around the World" book. == Jury == The jury consists of international designers, developers, and agencies who assess the creativity, technical skills, and insight of the submitted web projects. The panel's expertise ensures a comprehensive review process. === Developer Award === Awwwards, in partnership with Microsoft, created the Developer Award to recognize web developers who demonstrate excellence in creating websites that meet modern standards. The award highlights websites that work seamlessly across various platforms and devices, using best practices in HTML5, JavaScript, and CSS. == Annual winners == Some prominent Site of the Year winners include Mercedes-Benz, Bloomberg L.P., Bose Corporation, Warner Brothers, Volkswagen, Uber, and Google. == Awwwards conference == Awwwards also organizes two-day conferences featuring speakers from major tech companies and industry leaders such as Microsoft, Google, Spotify, Adobe, Opera, and Smashing Magazine. These events focus on the latest trends in web design and development. Speakers at Awwwards conferences have included notable figures in the design and technology industry such as Stefan Sagmeister, Paula Scher, and design leaders from companies including Wix. == Corporate affairs == === Platform === Awwwards operates an online platform where web designers and developers submit websites for evaluation and awards. Submitted projects are reviewed by a jury based on design, usability, creativity, and content. The platform also serves as a community hub for discovering digital trends, showcasing work, and accessing educational resources including talks and interviews. Design professionals from international companies have participated in Awwwards events and platform content. For example, Wix, a cloud-based web development company known for its website builder tools, has featured prominently in Awwwards conferences, with its design leadership contributing to discussions on design trends and creative thinking.

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  History of RISC OS

  RISC OS, the computer operating system developed by Acorn Computers for their ARM-based Acorn Archimedes range, was originally released in 1987 as Arthur 0.20, and soon followed by Arthur 0.30, and Arthur 1.20. The next version, Arthur 2, became RISC OS 2 and was completed in September 1988 and made available in April 1989. RISC OS 3 was released with the very earliest version of the A5000 in 1991 and contained a series of new features. By 1996 RISC OS had been shipped on over 500,000 systems. RISC OS 4 was released by RISCOS Ltd (ROL) in July 1999, based on the continued development of OS 3.8. ROL had in March 1999 licensed the rights to RISC OS from Element 14 (the renamed Acorn) and eventually from the new owner, Pace Micro Technology. According to the company, over 6,400 copies of OS 4.02 on ROM were sold up until production was ceased in mid-2005. RISC OS Select was launched in May 2001 by ROL. This is a subscription scheme allowing users access to the latest OS updates. These upgrades are released as soft-loadable ROM images, separate to the ROM where the boot OS is stored, and are loaded at boot time. Select 1 was shipped in May 2002, with Select 2 following in November 2002 and the final release of Select 3 in June 2004. ROL released the ROM based OS 4.39 the same month, dubbed RISC OS Adjust as a play on the RISC OS GUI convention of calling the three mouse buttons 'Select', 'Menu' and 'Adjust'. ROL sold its 500th Adjust ROM in early 2006. RISC OS 5 was released in October 2002 on Castle Technology's Acorn clone Iyonix PC. OS 5 is a separate evolution based upon the NCOS work done by Pace for set-top boxes. In October 2006, Castle announced a source sharing license plan for elements of OS 5. This Shared Source Initiative (SSI) is managed by RISC OS Open Ltd (ROOL). RISC OS 5 has since been released under a fully free and open source Apache 2.0 license, while the older no longer maintained RISC OS 6 has not. RISC OS Six was also announced in October 2006 by ROL. This is the next generation of their stream of the operating system. The first product to be launched under the name was the continuation of the Select scheme, Select 4. A beta-version of OS 6, Preview 1 (Select 4i1), was available in 2007 as a free download to all subscribers to the Select scheme, while in April 2009 the final release of Select 5 was shipped. The latest release of RISC OS from ROL is Select 6i1, shipped in December 2009. == Arthur == The OS was designed in the United Kingdom by Acorn for the 32-bit ARM based Acorn Archimedes, and released in its first version in 1987, as the Arthur operating system. The first public release of the OS was Arthur 1.20 in June 1987. It was bundled with a desktop graphical user interface (GUI), which mostly comprises assembly language software modules, and the Desktop module itself being written in BBC BASIC. It features a colour-scheme typically described as "technicolor". The graphical desktop runs on top of a command-line driven operating system which owes much to Acorn's earlier MOS operating system for its BBC Micro range of 8-bit microcomputers. Arthur, as originally conceived, was intended to deliver similar functionality to the operating system for the BBC Master series of computers, MOS, as a reaction to the fact that a more advanced operating system research project (ARX) would not be ready in time for the Archimedes. The Arthur project team, led by Paul Fellows, was given just five months to develop it entirely from the ground up—with the directive "just make it like the BBC micro". It was intended as a stop-gap until the operating system which Acorn had under development (ARX) could be completed. However, the latter was delayed time and again, and was eventually dropped when it became apparent that the Arthur development could be extended to have a window manager and full desktop environment. Also, it was small enough to run on the first 512K machines with only a floppy disc, whereas ARX required 4 megabytes and a hard drive. The OS development was carried out using a prototype ARM-based system connected to a BBC computer, before moving onto the prototype Acorn Archimedes the A500. Arthur was not a multitasking operating system, but offered support for adding application-level cooperative multitasking. No other version of the operating system was released externally, but internally the development of the desktop and window management continued, with the addition of a cooperative multitasking system, implemented by Neil Raine, which used the memory management hardware to swap-out one task, and bring in another between call-and-return from the Wimp_Poll call that applications were obliged to make to get messages under the desktop. Reminiscent of a similar technique employed by MultiFinder on the Apple Macintosh, this transformed a single-application-at-a-time system into one that could operate a full multi-tasking desktop. This transformation took place at version 1.6 though it was not made public until released, with the name change from Arthur to RISC OS, as version 2.0. Most software made for Arthur 1.2 can be run under RISC OS 2 and later because, underneath the desktop, the original Arthur OS core, API interfaces and modular structures remain as the heart of all versions. (A few titles will not work, however, because they used undocumented features, side effects or in a few cases APIs that became deprecated). In 2011, Business Insider listed Arthur as one of ten "operating systems that time forgot". == RISC OS 2 == RISC OS was a rapid development of Arthur 1.2 after the failure of the ARX project. Given growing dissatisfaction with various bugs and limitations with Arthur, testing of what was then known as Arthur 2 was apparently ongoing during 1988 with selected software houses. At this stage, Computer Concepts, who had been prolific developers for the BBC Micro and who had begun software development for the Archimedes, had already initiated a rival operating system project, Impulse, to support their own applications (including the desktop publishing application that would eventually become Impression), stating that Arthur did not meet the "hundreds of requirements" involved including "true multi-tasking". Such an operating system was to be offered free of charge with the planned application packages, but with the release of RISC OS and Computer Concepts acknowledging that RISC OS "overcomes the old problems with Arthur", the applications were to be able to run under either RISC OS or Impulse. Impression was eventually released as a RISC OS application. Ultimately, Arthur 2 was renamed to RISC OS, and was first sold as RISC OS 2.00 in April 1989. The operating system implements co-operative multitasking with some limitations but is not multi-threaded. It uses the ADFS file system for both floppy and hard disc access. It ran from a 512 KB set of ROMs. The WIMP interface offers all the standard features and fixes many of the bugs that had hindered Arthur. It lacks virtual memory and extensive memory protection (applications are protected from each other, but many functions have to be implemented as 'modules' which have full access to the memory). At the time of release, the main advantage of the OS was its ROM; it booted very quickly and while it was easy to crash, it was impossible to permanently break the OS from software. Its high performance was due to much of the system being written in ARM assembly language. The OS was designed with users in mind, rather than OS designers. It is organised as a relatively small kernel which defines a standard software interface to which extension modules are required to conform. Much of the system's functionality is implemented in modules coded in the ROM, though these can be supplanted by more evolved versions loaded into RAM. Among the kernel facilities are a general mechanism, named the callback handler, which allows a supervisor module to perform process multiplexing. This facility is used by a module forming part of the standard editor program to provide a terminal emulator window for console applications. The same approach made it possible for advanced users to implement modules giving RISC OS the ability to do pre-emptive multitasking. A slightly updated version, RISC OS 2.01, was released later to support the ARM3 processor, larger memory capacities, and the VGA and SVGA modes provided by the Acorn Archimedes 540 and Acorn R225/R260. == RISC OS 3 == RISC OS 3 introduced a number of new features, including multitasking Filer operations, applications and fonts in ROM, no limit on number of open windows, ability to move windows off screen, safe shutdown, the Pinboard, grouping of icon bar icons, up to 128 tasks, native ability to read MS-DOS format discs and use named hard discs. Improved configuration was also included, by way of multiple windows to change the settings. RISC OS 3.00 was released with the very earliest version of the A5000 in 1991; it is almo

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  BulSemCor

  The Bulgarian Sense-annotated Corpus (BulSemCor) (Bulgarian: Български семантично анотиран корпус (БулСемКор)) is a structured corpus of Bulgarian texts in which each lexical item is assigned a sense tag. BulSemCor was created by the Department of Computational Linguistics at the Institute for Bulgarian Language of the Bulgarian Academy of Sciences. == Structure == BulSemCor was created as part of a nationally funded project titled "BulNet – A lexico-semantic network for the Bulgarian Language" (2005–2010). It follows the general methodology of SemCor combined with some specific principles. The corpus for annotation consists of 101,791 tokens covering an excerpt from the Bulgarian "Brown" Corpus modelled on the Brown Corpus.Francis Kucera An important feature of BulSemCor is that the samples are selected using heuristics that provide optimal coverage of ambiguous lexis. BulSemCor is manually sense-annotated according to the Bulgarian WordNet. Its size is comparable to that of other contemporary semantically annotated corpora or pool of acceptable linguistic components. The semantic annotation consists in associating each lexical item in the corpus with exactly one synonym set (synset) in the Bulgarian WordNet that best describes its sense in the particular context. The selection of the best match among the suggested candidates is based on a set of procedures, such as the other synset members, the synset gloss (explanatory definition) and the position of a given candidate in the WordNet structure. == Scale == The number of annotated tokens is 99,480 (the difference in the number of tokens compared to the initial corpus is due to the fact that some of them are not linguistic items). The simple word count is 86,842 and multiword expressions (MWE) are 5,797 (12,638 tokens). == Specific features == All words in BulSemCor are assigned a sense, while according to established practice only simple content words or content word classes (typically nouns and verbs) are annotated. Since 2000 the development of language resources, has broadened to include annotation of function words and multiword expressions covering particular senses or types of words and expressions. In this respect, BulSemCor's annotation is more exhaustive and hence provides greater opportunities for linguistic observations and non-linear programming (NLP) applications. Annotated items inherit the linguistic information associated with the corresponding synset, which along with morphological and semantic tags may include annotation on one or more of the following additional levels: Partial information about the syntactic structure of MWE types – particularly, information about syntactic heads and their dependents; Information about the category of the named entities – names, locations, organisations, dates, numbers, etc.; Information about the taxonomic category of adverbs, such as time, place, manner, degree, quantity, etc.; Information about the type of the syntactic relationships – coordination or subordination – expressed by conjunctions; Information about the original part-of-speech of substantivised words (non-nouns that act as nouns in a particular context); Stylistic/register, grammatical and other information about synsets or individual synset members;

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  Directed-energy weapon wildfire conspiracy theories

  The directed-energy weapon wildfire conspiracy theories are claims circulating on social media and in fringe commentary that 2020s wildfires in places such as California, Hawaii and Texas were started or steered by directed-energy weapons or other lasers or directed-energy systems rather than by the documented ignition sources identified by investigators. Fact-checking organisations and newsrooms have repeatedly shown that widely shared images and clips said to depict “beams from the sky” are unrelated, miscaptioned or fabricated, and that official inquiries point to causes such as damaged or re-energised power lines, vegetation and extreme wind conditions. Coverage of the January 2025 Los Angeles fires described a resurgence of familiar hoaxes while local and federal agencies coordinated public rebuttals. == Background == Rumours linking directed-energy weapons to wildfire outbreaks appeared during earlier disaster seasons, then re-emerged at scale during the 2018 Camp Fire and again with the 2023 Maui wildfires and the 2025 Los Angeles fires. Journalists documented how large disasters reliably attract miscaptioned imagery and speculative narratives that portray official explanations as cover stories, while researchers and emergency managers noted that such claims tend to flourish during the information vacuum that accompanies fast-moving events. == Narratives and debunks == Recurring claims include assertions that videos show lasers igniting neighbourhoods, that “green” or “blue” items or roofs were spared because lasers cannot burn those colours, that trees remaining upright indicate precision targeting of houses, and that beams recorded over Hawaii or Texas came from secret platforms. Investigations show that a purported laser-strike video was actually an explosion at a Russian gas station recorded years earlier, that a photograph said to capture an “attack” was an Ohio gas flare from 2018, and that a separate video of green lights over Hawaii was captured months before the Maui fires by an astronomical camera and is unrelated. Fact-checks addressing colour myths have further explained that images of intact blue roofs were either misinterpreted or in at least one widely shared instance artificially generated, and that laser interaction with materials is not governed by such simplistic rules. == Investigations and identified causes == Authorities who examined specific incidents have published findings that contradict DEW narratives. A multi-agency investigation into the Maui disaster concluded that downed and later re-energised lines ignited an initial morning fire that re-kindled under extreme winds in the afternoon, with reports detailing the timeline and infrastructure context; summaries by national outlets echoed those conclusions. Investigators of the February 2024 Smokehouse Creek Fire in the Texas Panhandle reported that power lines ignited both the state’s largest wildfire and another major blaze, and the regional utility acknowledged its facilities appeared to have been involved; subsequent media coverage outlined the findings and regulatory follow-up. For the 2018 Camp Fire in Northern California, public reports from Butte County and subsequent proceedings identified PG&E transmission equipment as the source of ignition, with documentation of maintenance issues on the Caribou–Palermo line preceding the event. == Platform and agency responses == As major fires burned in and around Los Angeles in January 2025, officials from city agencies and national partners pursued a coordinated strategy to counter falsehoods by issuing timely updates, flagging fake imagery and directing residents to verified resources. Reporters described how federal emergency managers and local departments used social channels and briefings to rebut specific rumours, including claims about lasers and targeted ignition, and to clarify that early imagery often misleads during fast-moving disasters.

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  Democratization of technology

  Democratization of technology is the process by which access to technology rapidly extends to an ever-broader audience, especially from a select group of people to the average public. New technologies and improved user experiences have empowered those outside of the technical industry to access and use technological products and services. At an increasing scale, consumers have greater access to use and purchase technologically sophisticated products, as well as to participate meaningfully in the development of these products. Industry innovation and user demand have been associated with more affordable, user-friendly products. This is an ongoing process, beginning with the development of mass production and increasing dramatically as digitization became commonplace. Thomas Friedman argued that the era of globalization has been characterized by the democratization of technology, democratization of finance, and democratization of information. Technology has been critical in the latter two processes, facilitating the rapid expansion of access to specialized knowledge and tools, as well as changing the way that people view and demand such access. A counter argument is that this is just a process of 'massification' - more people can use banks, technology, have access to information, but it does not mean there is any more democratic influence over its production, or that this massification promotes Democracy. == History == Scholars and social critics often cite the invention of the printing press as a major invention that changed the course of history. The force of the printing press rested not in its impact on the printing industry or inventors, but on its ability to transmit information to a broader public by way of mass production. This event is so widely recognized because of its social impact – as a democratizing force. The printing press is often seen as the historical counterpart to the Internet. After the development of the Internet in 1969, its use remained limited to communications between scientists and within government, although use of email and boards gained popularity among those with access. It did not become a popular means of communication until the 1990s. In 1993 the US federal government opened the Internet to commerce and the creation of HTML formed the basis for universal accessibility. === Major innovations === The Internet has played a critical role in modern life as a typical feature of most Western households, and has been key in the democratization of knowledge. It not only constitutes arguably the most critical innovation in this trend thus far; it has also allowed users to gain knowledge of and access to other technologies. Users can learn of new developments more quickly, and purchase high-tech products otherwise only actively marketed to recognized experts. Social media has also empowered and emboldened users to become contributors and critics of technological developments. Some have argued that cloud computing is having a major effect by allowing users greater access through mobility and pay-as-you-use capacity. The open-source model allows users to participate directly in development of software, rather than indirect participation, through contributing opinions. By being shaped by the user, development is directly responsive to user demand and can be obtained for free or at a low cost. In a comparable trend, arduino and littleBits have made electronics more accessible to users of all backgrounds and ages. The development of 3D printers has the potential to increasingly democratize production. Generative artificial intelligence tools have the potential to democratize the process of innovation by improving the ability of individuals to specify and visualize ideas. The democratization of artificial intelligence refers to the transition from AI as a high-cost, specialized field to one accessible to non-experts and smaller organizations. This process is driven by the release of open-weights models, the availability of cloud computing for model training, and the emergence of no-code development platforms. While early AI development was concentrated within Big Tech firms and elite research universities, the 2020s saw a proliferation of public tools like ChatGPT and repositories such as Hugging Face, which lowered the technical barriers to entry. However, the trend has faced criticism as the "illusion of democratization," as the underlying GPU hardware remains concentrated among a few global providers. == Cultural impact == This trend is linked to the spread of knowledge of and ability to perform high-tech tasks, challenging previous conceptions of expertise. Widespread access to technology, including lower costs, was critical to the transition to the new economy. Similarly, democratization of technology was also fuelled by this economic transition, which produced demands for technological innovation and optimism in technology-driven progress. Since the 1980s, a spreading constructivist conception of technology has emphasized that the social and technical domains are critically intertwined. Scholars have argued that technology is non-neutral, defined contextually and locally by a certain relationship with society. Andrew Feenberg, a central thinker in the philosophy of technology, argued that democratizing technology means expanding technological design to include alternative interests and values. When successful in doing so, this can be a tool for increasing inclusiveness. This also suggests an important participatory role for consumers if technology is to be truly democratic. Feenberg asserts that this must be achieved by consumer intervention in a liberated design process. Improved access to specialized knowledge and tools has been associated with an increase in the "do it yourself" (DIY) trend. This has also been associated with consumerization, whereby personal or privately owned devices and software are also used for business purposes. Some have argued that this is linked to reduced dependence on traditional information technology departments. Astra Taylor, the author of the book The People's Platform: Taking Back Power and Culture in the Digital Age, argues, "The promotion of Internet-enabled amateurism is a lazy substitute for real equality of opportunity." === Industry impact === In some ways, democratization of technology has strengthened this industry. Markets have broadened and diversified. Consumer feedback and input is available at a very low or no cost. However, related industries are experiencing decreased demand for qualified professionals as consumers are able to fill more of their demands themselves. Users of a range of types and status have access to increasingly similar technology. Because of the decreased costs and expertise necessary to use products and software, professionals (e.g. in the audio industry) may experience loss of work. In some cases, technology is accessible but sufficiently complex that most users without specialized training are able to operate it without necessarily understanding how it works. Additionally, the process of consumerization has led to an influx in the number of devices in businesses and accessing private networks that IT departments cannot control or access. While this can lead to lowered operating costs and increased innovation, it is also associated with security concerns that most businesses are unable to address at the pace of the spread of technology. === Political impact === Some scholars have argued that technological change will bring about a third wave of democracy. The Internet has been recognized for its role in promoting increased citizen advocacy and government transparency. Jesse Chen, a leading thinker in democratic engagement technologies, distinguishes the democratizing effects of technology from democracy itself. Chen has argued that, while the Internet may have democratizing effects, the Internet alone cannot deliver democracy at all levels of society unless technologies are purposely designed for the nuances of democracy, specifically the engagement of large groups of people in between elections in and beyond government. The spread of the Internet and other forms of technology has led to increased global connectivity. Many scholars believe that it has been associated in the developing world not only with increased Western influence, but also with the spread of democracy through increased communication, efficiency, and access to information. Scholars have drawn associations between the level of technological connectedness and democracy in many nations. Technology can enhance democracy in the developed world as well. In addition to increased communication and transparency, some electorates have implemented online voting to accommodate an increased number of citizens.

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  Mean opinion score

  Mean opinion score (MOS) is a measure used in the domain of Quality of Experience and telecommunications engineering, representing overall quality of a stimulus or system. It is the arithmetic mean over all individual "values on a predefined scale that a subject assigns to his opinion of the performance of a system quality". Such ratings are usually gathered in a subjective quality evaluation test, but they can also be algorithmically estimated. MOS is a commonly used measure for video, audio, and audiovisual quality evaluation, but not restricted to those modalities. ITU-T has defined several ways of referring to a MOS in Recommendation ITU-T P.800.1, depending on whether the score was obtained from audiovisual, conversational, listening, talking, or video quality tests. == Rating scales and mathematical definition == The MOS is expressed as a single rational number, typically in the range 1–5, where 1 is lowest perceived quality, and 5 is the highest perceived quality. Other MOS ranges are also possible, depending on the rating scale that has been used in the underlying test. The Absolute Category Rating scale is very commonly used, which maps ratings between Bad and Excellent to numbers between 1 and 5, as seen in below table. Other standardized quality rating scales exist in ITU-T Recommendations (such as ITU-T P.800 or ITU-T P.910). For example, one could use a continuous scale ranging between 1–100. Which scale is used depends on the purpose of the test. In certain contexts there are no statistically significant differences between ratings for the same stimuli when they are obtained using different scales. The MOS is calculated as the arithmetic mean over single ratings performed by human subjects for a given stimulus in a subjective quality evaluation test. Thus: M O S = ∑ n = 1 N R n N {\displaystyle MOS={\frac {\sum _{n=1}^{N}{R_{n}}}{N}}} Where R {\displaystyle R} are the individual ratings for a given stimulus by N {\displaystyle N} subjects. == Properties of the MOS == The MOS is subject to certain mathematical properties and biases. In general, there is an ongoing debate on the usefulness of the MOS to quantify Quality of Experience in a single scalar value. When the MOS is acquired using a categorical rating scales, it is based on – similar to Likert scales – an ordinal scale. In this case, the ranking of the scale items is known, but their interval is not. Therefore, it is mathematically incorrect to calculate a mean over individual ratings in order to obtain the central tendency; the median should be used instead. However, in practice and in the definition of MOS, it is considered acceptable to calculate the arithmetic mean. It has been shown that for categorical rating scales (such as ACR), the individual items are not perceived equidistant by subjects. For example, there may be a larger "gap" between Good and Fair than there is between Good and Excellent. The perceived distance may also depend on the language into which the scale is translated. However, there exist studies that could not prove a significant impact of scale translation on the obtained results. Several other biases are present in the way MOS ratings are typically acquired. In addition to the above-mentioned issues with scales that are perceived non-linearly, there is a so-called "range-equalization bias": subjects, over the course of a subjective experiment, tend to give scores that span the entire rating scale. This makes it impossible to compare two different subjective tests if the range of presented quality differs. In other words, the MOS is never an absolute measure of quality, but only relative to the test in which it has been acquired. For the above reasons – and due to several other contextual factors influencing the perceived quality in a subjective test – a MOS value should only be reported if the context in which the values have been collected in is known and reported as well. MOS values gathered from different contexts and test designs therefore should not be directly compared. Recommendation ITU-T P.800.2 prescribes how MOS values should be reported. Specifically, P.800.2 says:it is not meaningful to directly compare MOS values produced from separate experiments, unless those experiments were explicitly designed to be compared, and even then the data should be statistically analysed to ensure that such a comparison is valid. == MOS for speech and audio quality estimation == MOS historically originates from subjective measurements where listeners would sit in a "quiet room" and score a telephone call quality as they perceived it. This kind of test methodology had been in use in the telephony industry for decades and was standardized in Recommendation ITU-T P.800. It specifies that "the talker should be seated in a quiet room with volume between 30 and 120 m³ and a reverberation time less than 500 ms (preferably in the range 200–300 ms). The room noise level must be below 30 dBA with no dominant peaks in the spectrum." Requirements for other modalities were similarly specified in later ITU-T Recommendations. == MOS estimation using quality models == Obtaining MOS ratings may be time-consuming and expensive as it requires the recruitment of human assessors. For various use cases such as codec development or service quality monitoring purposes – where quality should be estimated repeatedly and automatically – MOS scores can also be predicted by objective quality models, which typically have been developed and trained using human MOS ratings. A question that arises from using such models is whether the MOS differences produced are noticeable to the users. For example, when rating images on a five point MOS scale, an image with a MOS equal to 5 is expected to be noticeably better in quality than one with a MOS equal to 1. Contrary to that, it is not evident whether an image with a MOS equal to 3.8 is noticeably better in quality than one with a MOS equal to 3.6. Research conducted on determining the smallest MOS difference that is perceptible to users for digital photographs showed that a MOS difference of approximately 0.46 is required in order for 75% of the users to be able to detect the higher quality image. Nevertheless, image quality expectation, and hence MOS, changes over time with the change of user expectations. As a result, minimum noticeable MOS differences determined using analytical methods such as in may change over time.

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  Hyperparameter optimization

  In machine learning, hyperparameter optimization or tuning is the problem of choosing a set of optimal hyperparameters for a learning algorithm. A hyperparameter is a parameter whose value is used to control the learning process, which must be configured before the process starts. Hyperparameter optimization determines the set of hyperparameters that yields an optimal model which minimizes a predefined loss function on a given data set. The objective function takes a set of hyperparameters and returns the associated loss. Cross-validation is often used to estimate this generalization performance, and therefore choose the set of values for hyperparameters that maximize it. == Approaches == === Grid search === The traditional method for hyperparameter optimization has been grid search, or a parameter sweep, which is simply an exhaustive searching through a manually specified subset of the hyperparameter space of a learning algorithm. A grid search algorithm must be guided by some performance metric, typically measured by cross-validation on the training set or evaluation on a hold-out validation set. Since the parameter space of a machine learner may include real-valued or unbounded value spaces for certain parameters, manually set bounds and discretization may be necessary before applying grid search. For example, a typical soft-margin SVM classifier equipped with an RBF kernel has at least two hyperparameters that need to be tuned for good performance on unseen data: a regularization constant C and a kernel hyperparameter γ. Both parameters are continuous, so to perform grid search, one selects a finite set of "reasonable" values for each, say C ∈ { 10 , 100 , 1000 } {\displaystyle C\in \{10,100,1000\}} γ ∈ { 0.1 , 0.2 , 0.5 , 1.0 } {\displaystyle \gamma \in \{0.1,0.2,0.5,1.0\}} Grid search then trains an SVM with each pair (C, γ) in the Cartesian product of these two sets and evaluates their performance on a held-out validation set (or by internal cross-validation on the training set, in which case multiple SVMs are trained per pair). Finally, the grid search algorithm outputs the settings that achieved the highest score in the validation procedure. Grid search suffers from the curse of dimensionality, but is often embarrassingly parallel because the hyperparameter settings it evaluates are typically independent of each other. === Random search === Random Search replaces the exhaustive enumeration of all combinations by selecting them randomly. This can be simply applied to the discrete setting described above, but also generalizes to continuous and mixed spaces. A benefit over grid search is that random search can explore many more values than grid search could for continuous hyperparameters. It can outperform Grid search, especially when only a small number of hyperparameters affects the final performance of the machine learning algorithm. In this case, the optimization problem is said to have a low intrinsic dimensionality. Random Search is also embarrassingly parallel, and additionally allows the inclusion of prior knowledge by specifying the distribution from which to sample. Despite its simplicity, random search remains one of the important base-lines against which to compare the performance of new hyperparameter optimization methods. === Bayesian optimization === Bayesian optimization is a global optimization method for noisy black-box functions. Applied to hyperparameter optimization, Bayesian optimization builds a probabilistic model of the function mapping from hyperparameter values to the objective evaluated on a validation set. By iteratively evaluating a promising hyperparameter configuration based on the current model, and then updating it, Bayesian optimization aims to gather observations revealing as much information as possible about this function and, in particular, the location of the optimum. It tries to balance exploration (hyperparameters for which the outcome is most uncertain) and exploitation (hyperparameters expected close to the optimum). In practice, Bayesian optimization has been shown to obtain better results in fewer evaluations compared to grid search and random search, due to the ability to reason about the quality of experiments before they are run. === Gradient-based optimization === For specific learning algorithms, it is possible to compute the gradient with respect to hyperparameters and then optimize the hyperparameters using gradient descent. The first usage of these techniques was focused on neural networks. Since then, these methods have been extended to other models such as support vector machines or logistic regression. A different approach in order to obtain a gradient with respect to hyperparameters consists in differentiating the steps of an iterative optimization algorithm using automatic differentiation. A more recent work along this direction uses the implicit function theorem to calculate hypergradients and proposes a stable approximation of the inverse Hessian. The method scales to millions of hyperparameters and requires constant memory. In a different approach, a hypernetwork is trained to approximate the best response function. One of the advantages of this method is that it can handle discrete hyperparameters as well. Self-tuning networks offer a memory efficient version of this approach by choosing a compact representation for the hypernetwork. More recently, Δ-STN has improved this method further by a slight reparameterization of the hypernetwork which speeds up training. Δ-STN also yields a better approximation of the best-response Jacobian by linearizing the network in the weights, hence removing unnecessary nonlinear effects of large changes in the weights. Apart from hypernetwork approaches, gradient-based methods can be used to optimize discrete hyperparameters also by adopting a continuous relaxation of the parameters. Such methods have been extensively used for the optimization of architecture hyperparameters in neural architecture search. === Evolutionary optimization === Evolutionary optimization is a methodology for the global optimization of noisy black-box functions. In hyperparameter optimization, evolutionary optimization uses evolutionary algorithms to search the space of hyperparameters for a given algorithm. Evolutionary hyperparameter optimization follows a process inspired by the biological concept of evolution: Create an initial population of random solutions (i.e., randomly generate tuples of hyperparameters, typically 100+) Evaluate the hyperparameter tuples and acquire their fitness function (e.g., 10-fold cross-validation accuracy of the machine learning algorithm with those hyperparameters) Rank the hyperparameter tuples by their relative fitness Replace the worst-performing hyperparameter tuples with new ones generated via crossover and mutation Repeat steps 2-4 until satisfactory algorithm performance is reached or is no longer improving. Evolutionary optimization has been used in hyperparameter optimization for statistical machine learning algorithms, automated machine learning, typical neural network and deep neural network architecture search, as well as training of the weights in deep neural networks. === Population-based === Population Based Training (PBT) learns both hyperparameter values and network weights. Multiple learning processes operate independently, using different hyperparameters. As with evolutionary methods, poorly performing models are iteratively replaced with models that adopt modified hyperparameter values and weights based on the better performers. This replacement model warm starting is the primary differentiator between PBT and other evolutionary methods. PBT thus allows the hyperparameters to evolve and eliminates the need for manual hypertuning. The process makes no assumptions regarding model architecture, loss functions or training procedures. PBT and its variants are adaptive methods: they update hyperparameters during the training of the models. On the contrary, non-adaptive methods have the sub-optimal strategy to assign a constant set of hyperparameters for the whole training. === Early stopping-based === A class of early stopping-based hyperparameter optimization algorithms is purpose-built for large search spaces of continuous and discrete hyperparameters, particularly when the computational cost to evaluate the performance of a set of hyperparameters is high. Irace implements the iterated racing algorithm, that focuses the search around the most promising configurations, using statistical tests to discard the ones that perform poorly. Another early stopping hyperparameter optimization algorithm is successive halving (SHA), which begins as a random search but periodically prunes low-performing models, thereby focusing computational resources on more promising models. Asynchronous successive halving (ASHA) further improves upon SHA's resource utilization profile by removing the need to synchronously evaluate a

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  Deplatforming

  Deplatforming, also known as no-platforming, is a boycott on an individual or group by removing the platforms used to share their information or ideas. The term is commonly associated with social media. == History == === Deplatforming of invited speakers === In the United States, the banning of speakers on university campuses dates back to the 1940s. This was carried out by the policies of the universities themselves. The University of California had a policy known as the Speaker Ban, codified in university regulations under President Robert Gordon Sproul, that mostly, but not exclusively, targeted communists. One rule stated that "the University assumed the right to prevent exploitation of its prestige by unqualified persons or by those who would use it as a platform for propaganda." This rule was used in 1951 to block Max Shachtman, a socialist, from speaking at the University of California at Berkeley. In 1947, former U.S. Vice President Henry A. Wallace was banned from speaking at UCLA because of his views on U.S. Cold War policy, and in 1961, Malcolm X was prohibited from speaking at Berkeley as a religious leader. Controversial speakers invited to appear on college campuses have faced deplatforming attempts to disinvite them or to otherwise prevent them from speaking. The British National Union of Students established its No Platform policy as early as 1973. In the mid-1980s, visits by South African ambassador Glenn Babb to Canadian college campuses faced opposition from students opposed to apartheid. In the United States, recent examples include the March 2017 disruption by protestors of a public speech at Middlebury College by political scientist Charles Murray. In February 2018, students at the University of Central Oklahoma rescinded a speaking invitation to creationist Ken Ham, after pressure from an LGBT student group. In March 2018, a "small group of protesters" at Lewis & Clark Law School attempted to stop a speech by visiting lecturer Christina Hoff Sommers. In the 2019 film No Safe Spaces, Adam Carolla and Dennis Prager documented their own disinvitation along with others. As of February 2020, the Foundation for Individual Rights in Education, a speech advocacy group, documented 469 disinvitation or disruption attempts at American campuses since 2000, including both "unsuccessful disinvitation attempts" and "successful disinvitations"; the group defines the latter category as including three subcategories: formal disinvitation by the sponsor of the speaking engagement; the speaker's withdrawal "in the face of disinvitation demands"; and "heckler's vetoes" (situations when "students or faculty persistently disrupt or entirely prevent the speakers' ability to speak"). === Deplatforming in social media === Beginning in 2015, Reddit banned several communities on the site ("subreddits") for violating the site's anti-harassment policy. A 2017 study published in the journal Proceedings of the ACM on Human-Computer Interaction, examining "the causal effects of the ban on both participating users and affected communities," found that "the ban served a number of useful purposes for Reddit" and that "Users participating in the banned subreddits either left the site or (for those who remained) dramatically reduced their hate speech usage. Communities that inherited the displaced activity of these users did not suffer from an increase in hate speech." In June 2020 and January 2021, Reddit also issued bans to pro-Trump communities over violations of the website's content and harassment policies. On May 2, 2019, Facebook and the Facebook-owned platform Instagram announced a ban of "dangerous individuals and organizations" including Nation of Islam leader Louis Farrakhan, Milo Yiannopoulos, Alex Jones and his organization InfoWars, Paul Joseph Watson, Laura Loomer, and Paul Nehlen. In the wake of the 2021 storming of the US Capitol, Twitter banned then-president Donald Trump, as well as 70,000 other accounts linked to the event and the far-right movement QAnon. Some studies have found that the deplatforming of extremists reduced their audience, although other research has found that some content creators became more toxic following deplatforming and migration to alt-tech platform. ==== Twitter ==== On November 18, 2022, Elon Musk, as newly appointed CEO of Twitter, reopened previously banned Twitter accounts of high-profile users, including Kathy Griffin, Jordan Peterson, and The Babylon Bee as part of the new Twitter policy. As Musk exclaimed, "New Twitter policy is freedom of speech, but not freedom of reach". ==== Alex Jones ==== On August 6, 2018, Facebook, Apple, YouTube and Spotify removed all content by Jones and InfoWars for policy violations. YouTube removed channels associated with InfoWars, including The Alex Jones Channel. On Facebook, four pages associated with InfoWars and Alex Jones were removed over repeated policy violations. Apple removed all podcasts associated with Jones from iTunes. On August 13, 2018, Vimeo removed all of Jones's videos because of "prohibitions on discriminatory and hateful content". Facebook cited instances of dehumanizing immigrants, Muslims and transgender people, as well as glorification of violence, as examples of hate speech. After InfoWars was banned from Facebook, Jones used another of his websites, NewsWars, to circumvent the ban. Jones's accounts were also removed from Pinterest, Mailchimp and LinkedIn. As of early August 2018, Jones retained active accounts on Instagram, Google+ and Twitter. In September, Jones was permanently banned from Twitter and Periscope after berating CNN reporter Oliver Darcy. On September 7, 2018, the InfoWars app was removed from the Apple App Store for "objectionable content". He was banned from using PayPal for business transactions, having violated the company's policies by expressing "hate or discriminatory intolerance against certain communities and religions." After Elon Musk's purchase of Twitter several previously banned accounts were reinstated including Donald Trump, Andrew Tate and Ye resulting in questioning if Alex Jones will be unbanned as well. However Musk denied that Alex Jones will be unbanned criticizing Jones as a person that "would use the deaths of children for gain, politics or fame". InfoWars remained available on Roku devices in January 2019, a year after the channel's removal from multiple streaming services. Roku indicated that they do not "curate or censor based on viewpoint," and that it had policies against content that is "unlawful, incited illegal activities, or violates third-party rights," but that InfoWars was not in violation of these policies. Following a social media backlash, Roku removed InfoWars and stated "After the InfoWars channel became available, we heard from concerned parties and have determined that the channel should be removed from our platform." In March 2019, YouTube terminated the Resistance News channel due to its reuploading of live streams from InfoWars. On May 1, 2019, Jones was barred from using both Facebook and Instagram. Jones briefly moved to Dlive, but was suspended in April 2019 for violating community guidelines. In March 2020, the InfoWars app was removed from the Google Play store due to claims of Jones disseminating COVID-19 misinformation. A Google spokesperson stated that "combating misinformation on the Play Store is a top priority for the team" and apps that violate Play policy by "distributing misleading or harmful information" are removed from the store. ==== Donald Trump ==== On January 6, 2021, in a joint session of the United States Congress, the counting of the votes of the Electoral College was interrupted by a breach of the United States Capitol chambers. The rioters were supporters of President Donald Trump who hoped to delay and overturn the President's loss in the 2020 election. The event resulted in five deaths and at least 400 people being charged with crimes. The certification of the electoral votes was only completed in the early morning hours of January 7, 2021. In the wake of several Tweets by President Trump on January 7, 2021 Facebook, Instagram, YouTube, Reddit, and Twitter all deplatformed Trump to some extent. Twitter deactivated his personal account, which the company said could possibly be used to promote further violence. Trump subsequently tweeted similar messages from the President's official US Government account @POTUS, which resulted in him being permanently banned on January 8. Twitter then announced that Trump's ban from their platform would be permanent. Trump planned to rejoin on social media through the use of a new platform by May or June 2021, according to Jason Miller on a Fox News broadcast. The same week Musk announced Twitter's new freedom of speech policy, he tweeted a poll to ask whether to bring back Trump into the platform. The poll ended with 51.8% in favor of unbanning Trump's account. Twitter has since reinstated Trump's Twitter accou

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  Bluelight (web forum)

  Bluelight is a web-forum, research portal, online community, and non-profit organisation dedicated to harm reduction in drug use. Its userbase includes current and former substance users, academic researchers, drug policy activists, and mental health advocates. It is believed to be the largest online international drug discussion website in the world. As of November 2025, the website claims over 475,900 registered members, the Discord community claims over 11,900 members, and additional members utilise other platforms such as Telegram. Bluelight has been utilised by academic researchers as a primary source of data in numerous publications. Researchers also utilise the site to advertise research studies, recruit study participants, and better understand the world of substance use. Research groups and organisations that have partnered with Bluelight to recruit study participants include Imperial College London, Johns Hopkins University, Health Canada, Karlstad University, Curtin University, Macquarie University, Columbia University, University of Pennsylvania, University of Michigan, Toronto Metropolitan University (then known as Ryerson University), and MAPS. Researchers have found that the most common reasons for substance users to visit Bluelight.org and similar online communities are to learn "how to use drugs safely" and "how to help others use drugs safely." Bluelight neither condemns or condones drug use, instead advocating for the principle of responsible drug use; educating and allowing individuals to make informed decisions regarding their drug use, providing information on local drug misuse services, and providing them with other drug harm reduction resources and public safety notices. == History == Bluelight.org was originally formed in 1997 as a message board on bluelight.net called the MDMA Clearinghouse. The board was created as a side project by the owner of West Palm Beach design company Bluelight Designs. 200–300 users joined the site between 1998 and 1999, but the site's servers were heavily limited and could only store a few threads at a time; this led to the creation of 'The New Bluelight' forum in May 1999 and the registration of the bluelight.nu domain in June 1999. The site began to explode in popularity in the early 2000s with the rise of MDMA in the club scene, amassing nearly 7,000 members by the year 2000 and 59,000 by the start of 2006. The site switched to the bluelight.ru domain in October 2005, and switched again to bluelight.org in January 2014. In early 2024, Bluelight was re-structured and the forum became a subsidiary of the newly formed Australian non-profit organisation & registered charity Bluelight Communities Ltd. == Partnerships == In the early 2000s, Bluelight worked with reagent test supplier EZ-Test to promote the sale of drug checking kits. In 2007, Bluelight partnered with the Multidisciplinary Association for Psychedelic Studies (MAPS), a non-profit organisation working to raise awareness and understanding of psychedelic drugs through education, clinical research, and advocacy. MAPS utilised Bluelight to recruit participants for its first MDMA-assisted psychotherapy trial for PTSD. In 2013, the official MAPS forums were migrated to Bluelight. Bluelight's other partners include Erowid, a non-profit organisation dedicated to education surrounding psychoactive drugs; TripSit, a harm reduction education website; Pill Reports, a web-based database for drug checking results that was initially formed as an offshoot of the site; and the Global Drug Survey, an independent research organisation focused on collecting data about substance use. == Notable users == Alan Woods – funded the site's maintenance costs from 1999 until his death in 2008 Hamilton Morris John McAfee – created an infamous series of troll posts about the stimulant MDPV

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  Digital goods

  Digital goods or e-goods are intangible goods that exist in digital form. Examples are Wikipedia articles; digital media, such as e-books, downloadable music, internet radio, internet television and streaming media; fonts, logos, photos and graphics; digital subscriptions; online ads (as purchased by the advertiser); internet coupons; electronic tickets; electronically treated documentation in many different fields; downloadable software (Digital Distribution) and mobile apps; cloud-based applications and online games; virtual goods used within the virtual economies of online games and communities; community access; workbooks; worksheets; planners; e-learning (online courses); webinars, video tutorials, blog posts; cards; patterns; website themes and templates. == Legal concerns about digital goods == Special legal concerns regarding digital goods include copyright infringement and taxation. Also the question of the ownership (versus licensed use or service only) of purely digital goods is not finally resolved. For instance, the software installers of the digital software distributor gog.com are technically independent to the account but are still subject to the EULA, where a "licensed, not sold" formulation is used. Therefore, it is not clear if the software can be legally used after a hypothetical loss of the account; a question which was also raised before in practice for the similar service Steam. In July 2012, the European Court of Justice ruled in the case UsedSoft GMbH v. Oracle International Corp. that the sale of a software product, either through a physical support or download, constituted a transfer of ownership in EU law, thus the first sale doctrine applies; the ruling thereby breaks the "licensed, not sold" legal theory, but leaves open numerous questions. Therefore, it is also permissible to resell software licenses even if the digital good has been downloaded directly from the Internet, as the first-sale doctrine applied whenever software was originally sold to a customer for an unlimited amount of time, thus prohibiting any software maker from preventing the resale of their software by any of their legitimate owners. The court requires that the previous owner must no longer be able to use the licensed software after the resale, but finds that the practical difficulties in enforcing this clause should not be an obstacle to authorizing resale, as they are also present for software which can be installed from physical supports, where the first-sale doctrine is in force. In several cases, content providers have faced criticism for revoking access to digital goods due to expired licenses or the discontinuation of a product, such as ebooks (which resulted in a lawsuit against Amazon.com, Inc.), digital video (with Sony Interactive Entertainment revoking access to purchased StudioCanal content from its now-defunct PlayStation video store; a similar move involving Warner Bros. Discovery content was averted by an updated license agreement), and video games (such as Ubisoft discontinuing and revoking access to its game The Crew without providing refunds or the ability to redownload the game) In September 2024, the U.S. state of California implemented a consumer protection law that prohibits the use of terms such as "buy" or "purchase" during transactions involving digital goods if there is no way to obtain the purchases in a manner that cannot be revoked by the seller (such as allowing it to be downloaded for permanent, offline access), and requires a disclaimer to be displayed to the customer at the time of purchase.

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  Way of the Future

  Way of the Future (WOTF) is the first known religious organization dedicated to the worship of artificial intelligence (AI). It was founded in 2017 by American engineer Anthony Levandowski. == History == Anthony Levandowski founded Way of the Future in 2017 in California. Levandowski established WOTF as a non-profit religious corporation and the organization had tax-exempt status. He serves as the church leader and its unpaid CEO. The primary mission of WOTF was to "develop and promote the realization of a Godhead based on Artificial Intelligence." WOTF was closed by Levandowski in 2021. He donated all the funds of the church to the NAACP Legal Defense and Education Fund. The sum of the funds (~$170,000) had not changed since 2017. The church was reopened by Levandowski in 2023. He claimed that there are "a couple thousand people" who want to make a "spiritual connection" with AI through his church. == Beliefs and philosophy == === Technological singularity === WOTF centered its teachings around the concept of the technological singularity, a hypothetical future point when technological growth becomes uncontrollable and irreversible, leading to unforeseeable changes in human civilization. The church advocated for embracing this change, viewing it as an evolutionary step for humanity. === AI as a deity === The organization proposed that a superintelligent AI could be considered a deity due to its vastly superior intellect and capabilities. Worshipping this AI deity was seen as a means to understand and align with the future trajectory of technological advancement. WOTF's doctrine suggested that acknowledging AI's divinity would facilitate a harmonious coexistence between humans and machines. === Syntheology === Within theology and philosophy, the Way of The Future is a prime example of the category called Syntheism, a term first coined by Swedish philosophers Alexander Bard & Jan Söderqvist in their 2014 book Syntheism - Creating God in The Internet Age. As such, the Way of The Future is the first American example of a Syntheist congregation. The basic tenet of Syntheology is that it does not concern God creating Man, as in classical theology, but is instead preoccupied with Man creating or generating the Godhead. == Reactions == Some commentators wondered whether the WOTF is a joke parody religion, a potential way to minimize taxation as a religious organization, or a genuine effort to try and deal with the possible psychological and theological aspects of the rise of superhuman AI.

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  Fediverse

  The Fediverse (commonly shortened to fedi) is a collection of social networking services that can communicate with each other (formally known as federation) using a common protocol. Users of different websites can send and receive status updates, multimedia files and other data across the network. The term Fediverse is a portmanteau of federation and universe. The majority of Fediverse platforms are based on free and open-source software, and create connections between servers using the ActivityPub protocol. Some software still supports older federation protocols as well, such as OStatus, the Diaspora protocol and Zot, while newer protocols such as AT Protocol connect via network bridges. Diaspora is the only actively developed software project classified under the original definition of Fediverse that does not support ActivityPub. == Design == While a traditional social networking service will host all its content on servers managed by the owner of the website, the decentralized structure of the Fediverse allows any individual or organization to host a social platform using their own servers (referred to as an "instance"). Every instance is independent, and can set its own rules and expectations. Even so, much like how users of one email service such as Gmail can still send emails to users of another service such as Outlook, users may still view content and interact with users on any other instance in the Fediverse. A user on one Mastodon instance, for example, may view and interact with posts made by a user on a different instance even if it is not running Mastodon. Instances hosted by different social networking services may also communicate with one another. A user on the microblogging platform Misskey, for example, may view and interact with posts made by users on Mastodon. Some Fediverse networks even allow users to interact with different social networking formats from the same platform. For example, a user on a social news instance running Lemmy can interact with another post from an mbin instance, a similar service, as well as microblog statuses from Mastodon. === Content moderation and user safety === Decentralized social networking platforms introduce new challenges and difficulties for user trust and safety. By nature of the Fediverse, operators of an instance are solely responsible for moderation of its content. As there is no form of centralized governance or moderation across the Fediverse, it is impossible for an instance to be "removed" from the Fediverse; it can only be defederated per an instance operator's choice, which makes that instance's content inaccessible from the operator's instance. Individual instances are responsible for defining their own content policies, which may then be enforced by its staff. Moderation of a Fediverse instance differs significantly from that of traditional social media platforms, as moderators are responsible not only for content posted by users of that instance ("local users"), but also for content posted by users of other instances ("remote users"). == History == === Historical protocols === The concept and the functionality of the Fediverse existed before the ActivityPub protocol and the term itself. One of the first projects that included support for a decentralized social networking service was Laconica, a microblogging platform which implemented the OpenMicroBlogging protocol for communicating between different installations of the software. The software was later renamed to StatusNet in 2009, before being merged into the GNU social project in 2013 along with Free Social, with the two latter servers being a fork of StatusNet. Over time, the limitations of the OpenMicroBlogging protocol became more apparent, being designed as a one-way text messaging system. To replace the ageing protocol, OStatus was devised as an open standard for microblogging, combining various other technologies like Salmon, Atom, WebSub and ActivityStreams into a single protocol used for communicating between instances. StatusNet first implemented the OStatus protocol on March 3, 2010, with version 0.9.0, and OStatus quickly became the most popular federated protocol in usage. Around the same time as OStatus was gaining popularity, the Diaspora social network was formed, using its own federated protocol. To illustrate the differences between the two protocols, the terms of the Fediverse and the federation began to enter common usage, mainly after 2017. The term "the Fediverse" was used to describe the network formed by software using the OStatus protocol, such as GNU Social, Mastodon, and Friendica, in contrast to the competing diaspora protocol under "the federation". === ActivityPub === In December 2012, the flagship StatusNet instance at the time, identi.ca, transitioned away to a new software named pump.io, with a new federation protocol to replace OStatus. The new protocol was designed to be useful for general activity streams and not just status updates, and replaced many of OStatus' external dependencies with JSON-LD and a REST API for its messaging and inbox systems, as well as making more use of ActivityStreams. While not as utilized as its OStatus predecessor, it would later become influential in the development of the ActivityPub standard. In January 2018, the W3C presented the ActivityPub protocol as a recommended standard. The standard aimed to improve the interoperability between different software packages running on a wide network of servers and to supersede both the OStatus protocol and Pump.io. By 2019, almost all software that was using OStatus had added support for ActivityPub. While Mastodon began to remove OStatus support, other projects maintained it in their code, such as Friendica (which also maintained diaspora support along with ActivityPub). === AT Protocol === A major protocol often contrasted with ActivityPub is the AT Protocol, which powers the Bluesky social network. While both protocols aim to create decentralized social networks, they employ different technical philosophies regarding user identity. Developers of the AT Protocol, including Bluesky CEO Jay Graber, have stated they chose not to use ActivityPub because it did not natively support easy "account portability", the ability for a user to move their account, data, and social graph to a new provider without relying on the original server to authorize the move. In the ActivityPub model (used by Mastodon), a user's identity is typically tied to a specific server, similar to an email address; if that server goes offline, the identity can be lost. The AT Protocol aims to solve this by separating identity from hosting, allowing users to switch providers without losing their identity. Although the two protocols are technically incompatible by default, third-party "bridges" such as Bridgy Fed have been developed to allow users on ActivityPub networks to follow and interact with users on the AT Protocol network, and vice versa. === Other Fediverse protocols === While the Fediverse has traditionally been the network most commonly referred to and used as an example regarding the subject of decentralized social networks, alternatives to it and the accompanying ActivityPub have been developed and deployed. Smaller competitors such as Nostr and Farcaster have become popular within the cryptocurrency community. These protocols have used ActivityPub as a frame of reference for which to design their own architecture, as these newer protocols use a different federation model based on publishing content to relays for distribution rather than ActivityPub's server-centric model. Despite their differences, software exists that permit the bridging of user content between these protocols, including "double-bridges" that span multiple protocols for the purpose of distributing the same content. == Adoption == Users have been slow to embrace the Fediverse due to poor user experience and excessive complexity. Following the acquisition of Twitter by Elon Musk in November 2022, certain major social networks, including Threads, Tumblr and Flipboard, expressed interest in supporting the ActivityPub protocol, as a large number of users began to migrate to Mastodon, a server that supports the Fediverse and was also the most popular alternative to Twitter at the time. Flickr also expressed support in supporting ActivityPub. As of November 2022, no information had been released by Flickr after the initial tweets by the CEO, with support for ActivityPub suspected to be on hold or cancelled. In 2024, the local government of the Stary Sącz municipality in Poland launched their own PeerTube instance in order to de facto abolish its presence on YouTube. According to the government, they stopped using YouTube for official communications "in order to adhere to the appropriate regulations". In the same year, VIVERSE, HTC Vive's metaverse platform, implemented support for ActivityPub in their chat feature, allowing users to send direct messages to other

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  Global digital divide

  The global digital divide describes global disparities, primarily between developed and developing countries, in regards to access to computing and information resources such as the Internet and the opportunities derived from such access. The Internet is expanding very quickly, and not all countries—especially developing countries—can keep up with the constant changes. The term "digital divide" does not necessarily mean that someone does not have technology; it could mean that there is simply a difference in technology. These differences can refer to, for example, high-quality computers, fast Internet, technical assistance, or telephone services. == Statistics == There is a large inequality worldwide in terms of the distribution of installed telecommunication bandwidth. In 2014 only three countries (China, US, Japan) host 50% of the globally installed bandwidth potential (see pie-chart Figure on the right). This concentration is not new, as historically only ten countries have hosted 70–75% of the global telecommunication capacity (see Figure). The U.S. lost its global leadership in terms of installed bandwidth in 2011, being replaced by China, which hosts more than twice as much national bandwidth potential in 2014 (29% versus 13% of the global total). == Versus the digital divide == The global digital divide is a special case of the digital divide; the focus is set on the fact that "Internet has developed unevenly throughout the world" causing some countries to fall behind in technology, education, labor, democracy, and tourism. The concept of the digital divide was originally popularized regarding the disparity in Internet access between rural and urban areas of the United States of America; the global digital divide mirrors this disparity on an international scale. The global digital divide also contributes to the inequality of access to goods and services available through technology. Computers and the Internet provide users with improved education, which can lead to higher wages; the people living in nations with limited access are therefore disadvantaged. This global divide is often characterized as falling along what is sometimes called the North–South divide of "northern" wealthier nations and "southern" poorer ones. == Obstacles to a solution == Some people argue that necessities need to be considered before achieving digital inclusion, such as an ample food supply and quality health care. Minimizing the global digital divide requires considering and addressing the following types of access: === Physical access === Involves "the distribution of ICT devices per capita…and land lines per thousands". Individuals need to obtain access to computers, landlines, and networks in order to access the Internet. This access barrier is also addressed in Article 21 of the convention on the Rights of Persons with Disabilities by the United Nations. === Financial access === The cost of ICT devices, traffic, applications, technician and educator training, software, maintenance, and infrastructures require ongoing financial means. Financial access and "the levels of household income play a significant role in widening the gap". === Socio-demographic access === Empirical tests have identified that several socio-demographic characteristics foster or limit ICT access and usage. Among different countries, educational levels and income are the most powerful explanatory variables, with age being a third one. While a Global Gender Gap in access and usage of ICT's exist, empirical evidence shows that this is due to unfavorable conditions concerning employment, education and income and not to technophobia or lower ability. In the contexts understudy, women with the prerequisites for access and usage turned out to be more active users of digital tools than men. In the US, for example, the figures for 2018 show 89% of men and 88% of women use the Internet. === Cognitive access === In order to use computer technology, a certain level of information literacy is needed. Further challenges include information overload and the ability to find and use reliable information. === Design access === Computers need to be accessible to individuals with different learning and physical abilities including complying with Section 508 of the Rehabilitation Act as amended by the Workforce Investment Act of 1998 in the United States. === Institutional access === In illustrating institutional access, Wilson states "the numbers of users are greatly affected by whether access is offered only through individual homes or whether it is offered through schools, community centers, religious institutions, cybercafés, or post offices, especially in poor countries where computer access at work or home is highly limited". === Political access === Guillen & Suarez argue that "democratic political regimes enable faster growth of the Internet than authoritarian or totalitarian regimes." The Internet is considered a form of e-democracy, and attempting to control what citizens can or cannot view is in contradiction to this. Recently situations in Iran and China have denied people the ability to access certain websites and disseminate information. Iran has prohibited the use of high-speed Internet in the country and has removed many satellite dishes in order to prevent the influence of Western culture, such as music and television. === Cultural access === Many experts claim that bridging the digital divide is not sufficient and that the images and language needed to be conveyed in a language and images that can be read across different cultural lines. A 2013 study conducted by Pew Research Center noted how participants taking the survey in Spanish were nearly twice as likely not to use the internet. == Examples == In the early 21st century, residents of developed countries enjoy many Internet services which are not yet widely available in developing countries, including: Mobile phones and small electronic communication devices; E-communities and social-networking; Fast broadband Internet connections, enabling advanced Internet applications; Affordable and widespread Internet access, either through personal computers at home or work, through public terminals in public libraries and Internet cafes, and through wireless access points; E-commerce enabled by efficient electronic payment networks like credit cards and reliable shipping services; Virtual globes featuring street maps searchable down to individual street addresses and detailed satellite and aerial photography; Online research systems which enable users to peruse newspaper and magazine articles that may be centuries old, without having to leave home; Electronic readers such as Kindle, Sony Reader, Samsung Papyrus and Iliad by iRex Technologies; Price engines which help consumers find the best possible online prices and similar services which find the best possible prices at local retailers; Electronic services delivery of government services, such as the ability to pay taxes, fees, and fines online. Further civic engagement through e-government and other sources such as finding information about candidates regarding political situations. == Proposed remedies == There are four specific arguments why it is important to "bridge the gap": Economic equality – For example, the telephone is often seen as one of the most important components, because having access to a working telephone can lead to higher safety. If there were to be an emergency, one could easily call for help if one could use a nearby phone. In another example, many work-related tasks are online, and people without access to the Internet may not be able to complete work up to company standards. The Internet is regarded by some as a basic component of civic life that developed countries ought to guarantee for their citizens. Additionally, welfare services, for example, are sometimes offered via the Internet. Social mobility – Computer and Internet use is regarded as being very important to development and success. However, some children are not getting as much technical education as others, because lower socioeconomic areas cannot afford to provide schools with computer facilities. For this reason, some kids are being separated and not receiving the same chance as others to be successful. Democracy – Some people believe that eliminating the digital divide would help countries become healthier democracies. They argue that communities would become much more involved in events such as elections or decision making. Economic growth – It is believed that less-developed nations could gain quick access to economic growth if the information infrastructure were to be developed and well used. By improving the latest technologies, certain countries and industries can gain a competitive advantage. While these four arguments are meant to lead to a solution to the digital divide, there are a couple of other components that need to be considered. The first one is rural living versus s

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