AI Chatbot No Filter No Limit

AI Chatbot No Filter No Limit — independent reviews, comparisons, pricing and step-by-step guides on Aizhi.

  • H2O (software)

    H2O (software)

    H2O is an open-source, in-memory, distributed machine learning and predictive analytics platform developed by the company H2O.ai (previously 0xdata). The software uses a distributed architecture for parallel processing on standard hardware. It supports algorithms for large-scale data analysis and model deployment. H2O is primarily used by data scientists and developers for statistical modeling and data-driven decision-making. The platform is designed to handle in-memory computations across a distributed computing environment. It offers implementations for numerous statistical and machine learning algorithms, which are accessible through various programming interfaces. The software is released under the Apache License 2.0. == Functionality and features == H2O provides a suite of supervised and unsupervised machine learning algorithms. Its core functions include: Supervised learning: algorithms in the field of statistics, data mining and machine learning such as generalized linear models, random forests, gradient boosting and deep learning are implemented for classification and regression tasks. Unsupervised learning: including K-Means clustering and principal component analysis. Automated machine learning: a features designed to automate the processes of model selection, tuning, and ensemble creation. The software can ingest data from various sources, including the Hadoop Distributed File System, Amazon S3, SQL databases, as well as local file systems. It operates natively on Apache Spark clusters through Sparkling Water. Proponents claim that improved performance is achieved compared to other analysis tools. The software is distributed free of charge, under a business model based on the development of individual applications and support. == Architecture == H2O is primarily written in Java. It uses a distributed architecture that allows the platform to cluster nodes for parallel processing and in-memory storage of data and models. Users interact with the H2O platform through several primary interfaces: Programming language interfaces: APIs are provided for the R and Python programming languages, and various Apache offerings (Apache Hadoop and Spark, as well as Maven). H2O Flow: a graphical web-based interactive computational environment that functions as a notebook interface for data exploration, model building, and scripting. REST-API: allows for integration with other applications and frameworks such as Microsoft Excel or RStudio. With the H2O Machine Learning Integration Nodes, KNIME offers algorithmic workflows. While the algorithm executes, approximate results are displayed, so that users can track the progress and intervene if needed. == History, influences, and extensions == The software project was initiated by the company 0xdata, which later changed its name to H2O.ai. The three Stanford professors Stephen P. Boyd, Robert Tibshirani and Trevor Hastie form a panel that advises H2O on scientific issues. Since its inception, H2O provides open-source machine learning libraries for enterprise use. The core H2O platform is often complemented by offerings from H2O.ai, such as H2O Driverless AI. == Reception == H2O is referenced in peer-reviewed literature regarding automated machine learning (AutoML). The platform has been categorized as a "Leader" and a "Strong Performer" in industry reports by Forrester Research. H2O (the open-source platform) and the associated commercial platform Driverless AI have been recurring winners of InfoWorld's most prestigious awards, including both the Best of Open Source Software ("Bossies") and the Technology of the Year awards.

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  • Digital asset

    Digital asset

    A digital asset is anything that exists only in digital form and comes with a distinct usage right or distinct permission for use. Data that do not possess those rights are not considered assets. Digital assets include, but are not limited to: digital documents, audio content, motion pictures, and other relevant digital data currently in circulation or stored on digital appliances, such as personal computers, laptops, portable media players, tablets, data storage devices, and telecommunication devices. This encompasses any apparatus that currently exists or will exist as technology progresses to accommodate the conception of new modalities capable of carrying digital assets. This holds true regardless of the ownership of the physical device on which the digital asset is located. == Types == Types of digital assets include, but are not limited to: software, photography, logos, illustrations, animations, audiovisual media, presentations, spreadsheets, digital paintings, word documents, electronic mails, websites, and various other digital formats with their respective metadata. The number of different types of digital assets is exponentially increasing due to the rising number of devices that leverage these assets, such as smartphones, serving as conduits for digital media. In Intel's presentation at the 'Intel Developer Forum 2013,' they introduced several new types of digital assets related to medicine, education, voting, friendships, conversations, and reputation, among others. == Digital asset management system == A digital asset management (DAM) is an integrated structure that combines software, hardware, and/or other services to manage, store, ingest, organize, and retrieve digital assets. These systems enable users to find and use content when needed. == Digital asset metadata == Metadata is data about other data. Any structured information that defines a specification of any form of data is referred to as metadata. Metadata is also a claimed relationship between two entities, often used to establish connections or associations. Librarian Lorcan Dempsey says "Think of metadata as data which removes from a user (human or machine) the need to have full advance knowledge of the existence or characteristics of things of potential interest in the environment". At first, the term metadata was used for digital data exclusively, but nowadays metadata can apply to both physical and digital data. Catalogs, inventories, registers, and other similar standardized forms of organizing, managing, and retrieving resources contain metadata. Metadata can be stored and contained directly within the file it refers to or independently from it with the help of other forms of data management such as a DAM system. The more metadata is assigned to an asset the easier it gets to categorize it, especially as the amount of information grows. The asset's value rises the more metadata it has for it becomes more accessible, easier to manage, and more complex. Structured metadata can be shared with open protocols like OAI-PMH to allow further aggregation and processing. Open data sources like institutional repositories have thus been aggregated to form large datasets and academic search engines comprising tens of millions of open access works, like BASE, CORE, and Unpaywall. == Issues == Due to a lack of either legislation or legal precedent, there is limited existing governmental control and regulation surrounding digital assets in the United States and other large economies globally. Many of the control issues relating to access and transferability are maintained by individual companies. Some consequences of this include 'What is to become of the assets once their owner is deceased?' as well as can, and, if so, how, may they be inherited. This subject was broached in a bogus story about Bruce Willis allegedly looking to sue Apple as the end user agreement prevented him from bequeathing his iTunes collection to his children. Another case of this was when a soldier died on duty and the family requested access to the Yahoo! account. When Yahoo! refused to grant access, the probate judge ordered them to give the emails to the family but Yahoo! still was not required to give access. The Music Modernization Act was passed in September 2018 by the U.S. Congress to create a new music licensing system, with the aim to help songwriters get paid more.

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  • Fingerprint scanner

    Fingerprint scanner

    Fingerprint scanners are a type of biometric security device that identify an individual by identifying the structure of their fingerprints. They are used in police stations, security industries, smartphones, and other mobile devices. == Fingerprints == People have patterns of friction ridges on their fingers, these patterns are called the fingerprints. Fingerprints are uniquely detailed, durable over an individual's lifetime, and difficult to alter. Due to the unique combinations, fingerprints have become an ideal means of identification. == Types of fingerprint scanners == There are four types of fingerprint scanners: Optical scanners take a visual image of the fingerprint using a digital camera. Capacitive or CMOS scanners use capacitors and thus electric current to form an image of the fingerprint. This type of scanner tends to excel in terms of precision. Ultrasonic fingerprint scanners use high frequency sound waves to penetrate the epidermal (outer) layer of the skin. Thermal scanners sense the temperature differences on the contact surface, in between fingerprint ridges and valleys. All fingerprint scanners are susceptible to spoofing through fingerprints replicated using photographs and 3D printing. == Construction forms == Each type of fingerprint sensor can take two basic forms: the stagnant and the moving fingerprint scanner. Stagnant: The scanning module is mounted statically, and the user is required to swipe their fingers across it. This is cheaper but also less reliable than the moving form. Imaging can be less than ideal if the finger is not dragged over the scanning area at constant speed. Moving: The scanning module is mounted on a movable surface, while the user's finger can remain static. Because this layout allows the scanning module to pass the fingerprint at a constant speed, this method is generally more reliable. == Form factors == === Peripherals === Add-on fingerprint readers for PCs initially appeared in the late 1990's in the form of PCMCIA modules. Microsoft released a model in its IntelliMouse line with an integrated fingerprint reader in 2005. === Integrated readers === Laptops with built-in readers emerged around the same time as peripheral readers with devices such as NECs MC/R730F. IBM produced laptops with integrated readers starting in 2004. Apple introduced fingerprint scanners to their devices under the name Touch ID in 2013. These were initially released on the iPhone 5S, with the technology remaining exclusive to iPhones until the release of the 2016 MacBook Pro. On both laptops and smartphones, the fingerprint sensor usually uses a USB or I2C interface internally.

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  • Fediverse

    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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  • Fatsecret

    Fatsecret

    Fatsecret, commonly styled as fatsecret, is a mobile application, website and API that helps people achieve their weight loss goals and find accurate nutrition information. It also offers a weight loss clinic with coaching and medically supported programs. The platform powers global health apps. == History == Fatsecret was founded in 2006 in Melbourne, Australia by Lenny Moses and Rodney Moses. As of 2019, Lenny serves as the company's CEO. The company is known for its calorie counting and meal tracking app, and by April 2016, the company claimed to have 45 million users of its services. In August 2018, a premium version of its app was released. Since August 2009, the company has operated the Fatsecret Platform API, which allows access to its global food and nutrition database. Fatsecret reportedly had 900,000 downloads of its app in January 2020. In an analysis of several Health & Fitness app subcategories for the United States in January 2021, Fatsecret was reported to have the highest 30 day user retention rate of top Calorie Counter + Meal Planner for Weight Loss apps.

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  • Mass media use by the Islamic State

    Mass media use by the Islamic State

    The Islamic State (IS) is known for its extensive and effective use of propaganda. It uses a version of the Muslim Black Standard flag and developed an emblem which has clear symbolic meaning in the Muslim world. The Islamic State targets younger audiences, such as teenagers and young adults, since they are more vulnerable to propaganda. It is known to exploit the internet to spread its propaganda by establishing websites, such as the Al Fustat domain. Videos by the Islamic State are commonly accompanied by nasheeds (chants), notable examples being the chant Dawlat al-Islam Qamat, which came to be viewed as an unofficial anthem of the Islamic State, and Salil al-Sawarim. Academic research has emphasized the scale and volume of Islamic State media production beyond its flagship magazines. A quantitative study cited in R. Malash’s academic work documented 1,373 distinct Islamic State media products released over a six-month period between 1 August 2017 and 28 February 2018, including magazines, newsletters, reports, photographic releases, audio recordings, and other media formats. Scholars have used such datasets to illustrate the breadth and intensity of the group’s media output, particularly during periods of territorial decline, when propaganda activity remained high despite military pressure. == Traditional media == === Al-Furqan Foundation for Media Production === In January 2006, shortly after the group's rebranding as the "Islamic State of Iraq", it established the Al-Furqan Foundation for Media Production (Arabic: مؤسسة الفرقان للإنتاج الإعلامي, romanized: Muasasat al-Furqān lil'īntāj al'ilāmī), which produces CDs, DVDs, posters, pamphlets, and web-related propaganda products and official statements. It is the primary media production house of the Islamic State and responsible for production of major media releases, including the statements of the spokesmen and leaders of the group. On January 10, 2006, Al-Furqan released its very first video, titled (Arabic: زحف الأنوار, romanized: Zahf al-Anwār) It was founded by the Iraqi man Dr Wa'il al-Fayad, known as Abu Muhammad al-Furqan. He got his name "Al-Furqan" from his role in founding this media house, which was named after the 25th surah of the Quran Al-Furqan. It is the oldest media production house for the Islamic State, being founded in November 2006 to release media for the Islamic State of Iraq. The earliest release indexed by the SITE Intelligence Group is on 21 November 2006, documenting the storming of a police station in the Iraqi town of Miqdadiyah. Al-Furqan is considered to be a considerable innovation in jihadist media, with Kavkaz Center describing it as "a milestone on the path of jihad, a distinguished media that takes the great care in the management of the conflict with the crusaders and their tails and to expose the lies in the crusader's media." In October 2007, the Long War Journal reported on United States Army raids targeting Al-Furqan media cell members across Iraq, including in Mosul and Samarra. Between August 2013 and March 2014 they released the 22 part series Messages from the Land of Epic Battles. On 2 September 2014 SITE Intelligence Group discovered the beheading video called A Second Message to America, about the death of Steven Sotloff. Since then, Al-Furqan has released videos of their operations across Iraq and Syria, as well as execution videos directed to governments around the world. In April 2019, Al-Furqan released a video Interviewing Abu Bakr al-Baghdadi. Al-Furqan also produces media in the form of audio, which consists mostly of recordings of IS leaders and spokesmen giving speeches, as well as producing a single nasheed under their name called "Ya Allah Al-Jannah" (O Allah, (we ask you for) Paradise), sung by now-dead member of IS, Uqab Al-Marzuqi. === Al-I'tisam Foundation for Media Production === The Islamic State of Iraq founded a second media foundation - Al-I'tisam Media Foundation - around 2011, marked by their first video release, titled "The Conqueror of the Murtaddin: Abu Ahmad Al-Ansari". The foundation has since released a few series of videos, 50 parts of "Windows on the Land of Battles", 9 parts of "Pictures from the Land of Battles", a 9-part series quoting leaders about the establishment of the Islamic State, and other series before their last release, "Deterring the Safavids in Salah ad-Din" in 2015. Since then, there were no further releases from their behalf. === Al-Hayat Media Center === In mid-2014, IS established the Al-Hayat Media Center, which targets Western audiences and produces material in English, German, Russian, Urdu, Indonesian, Turkish, Bengali, Chinese, Bosnian, Kurdish, Uyghur, and French. When IS announced its expansion to other countries in November 2014 it established media departments for the new branches, and its media apparatus ensured that the new branches follow the same models it uses in Iraq and Syria. Then FBI Director James Comey said that IS's "propaganda is unusually slick," noting that, "They are broadcasting... in something like 23 languages". In July 2014, Al-Hayat began publishing a digital magazine called Dabiq, in a number of different languages including English. According to the magazine, its name is taken from the town of Dabiq in northern Syria, which is mentioned in a hadith about Armageddon. Al-Hayat also began publishing other digital magazines, including the Turkish language Konstantiniyye, the Ottoman word for Istanbul, the French language Dar al-Islam, and the Russian language Istok (Russian: Исток). By late 2016, these magazines had apparently all been discontinued, with Al-Hayat's material being consolidated into a new magazine called Rumiyah (Arabic for Rome). === Al-Naba === While the group's glossy, foreign-language magazines like Dabiq and Rumiyah ceased publication as the group lost territory, the weekly Arabic newsletter Al-Naba (The News) has continued to publish regularly, becoming the central pillar of the group's "media jihad" in the post-territorial phase. Recent scholarship, including studies published in 2025, suggests that Al-Naba serves a dual purpose: maintaining internal cohesion among dispersed fighters and projecting a narrative of endurance to enemies. Unlike the earlier magazines which were designed for recruitment, Al-Naba focuses on bureaucratic reporting, military statistics, and religious instruction. These are then translated and disseminated by decentralized supporter networks ("media mujahideen") to reach non-Arabic speakers. === Furat Media Center === The Al-Furat Media Center is another media center established in around 2015 to cater towards non-Arab speaking audiences. However, unlike the other organizations, the production wasn't as professional as ones made by the other media centers. Instead, they partially relied on local media departments and foreign communities of the Mujahideen to produce short-form videos. However, some professional long-form videos were also made under their behalf. As of now, the media center is the only known active branch of all the media centers of the Islamic State, after heavy losses from past campaigns against them. Their last release was "The Resolve of Muwahhidin in Russia", where videos from the Surovikino penal colony hostage crisis were edited and released. === Ajnad Foundation for Media Production === Ajnad Foundation is one of the official media wings of Islamic State which produces nasheeds and Quran recitations. It was established in January 2014 and has released more than 150 nasheeds. === Asdaa Foundation === Like the Ajnad Foundation, the Asdaa Foundation (Arabic: مؤسسة أصداء) or Asedaa Foundation produces Anasheed (Islamic chants). The foundation is the closest counterpart to Ajnad in producing Islamic State nasheeds, only difference being Ajnad is directly linked to the Islamic State while Asdaa is only classified as a "supporter organization" (munaser/munasera). The foundation had humble beginnings possibly in Yemen, where low-quality nasheeds were produced at first by 2 munshids, Abu Layth Al-Iraqi and Abu Ya'qub Al-Yamani. After that, the quality had improved a bit (possibly with new equipment and increased recognition) and eventually had its nasheeds included in the Islamic State's official media releases. One of its munshids, Abu Hafs is a renowned munshid who sings around 70 nasheeds, who as well works with Ajnad Foundation in some instances. He is currently alive, and working under Ansar Production Center (مركز إنتاج الأنصار), another Munasir foundation and Asedaa. Another Yemeni munshid, Abu Musab al-Adani, worked temporarily with Asdaa Foundation before defecting back to AQAP, from which he previously defected from. Some of their anasheed is used in IS's execution videos, a popular one is their human slaughterhouse execution video released during the time of Eid Al-Adha in 2016. The background nasheed they used was "We Came To Fill The Horizons With Terror", produced by the Asd

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  • Link-richness

    Link-richness

    Link-richness is the quality, possessed by some websites, of having many hyperlinks. Classified advertising sites like Craigslist tend to be very link-rich, sometimes with hundreds of links on their main page. They help users find the links they are looking for by grouping links into clusters. Inadequate link richness has been described as frustrating to readers, as it reduces transparency of site content from the main page. Students new to wiki collaboration were found to need guidance in how to take full advantage of the medium's potential for creating link-rich content. Link-richness in some contexts can be distracting, as when an article is surrounded by extraneous links. Indeed, it is becoming accepted as a best practice for universities to have link-rich home pages that do not rely on user categorisation and exploration of long sequences of links and are not constrained by traditional boundaries between departments. Tools are sometimes needed to make the publishing of link-rich web sites tractable, and many people may lack the technical skills, time, or inclination to engage in hand- crafting new digital document forms. A link-rich site that is low on content is sometimes referred to as a "gateway site." Link-rich portals were popular on the Web in 2000. Yahoo! and other sites featuring categories with many links were heavily used and often required fewer than three clicks to reach the content. Web designers were creating flat sites with content positioned close to the top of pages.

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  • Randomized benchmarking

    Randomized benchmarking

    Randomized benchmarking is an experimental method for measuring the average error rates of quantum computing hardware platforms. The protocol estimates the average error rates by implementing long sequences of randomly sampled quantum gate operations. Randomized benchmarking is the industry-standard protocol used by quantum hardware developers such as IBM and Google to test the performance of the quantum operations. The original theory of randomized benchmarking, proposed by Joseph Emerson and collaborators, considered the implementation of sequences of Haar-random operations, but this had several practical limitations. The now-standard protocol for randomized benchmarking (RB) relies on uniformly random Clifford operations, as proposed in 2006 by Dankert et al. as an application of the theory of unitary t-designs. In current usage randomized benchmarking sometimes refers to the broader family of generalizations of the 2005 protocol involving different random gate sets that can identify various features of the strength and type of errors affecting the elementary quantum gate operations. Randomized benchmarking protocols are an important means of verifying and validating quantum operations and are also routinely used for the optimization of quantum control procedures. == Overview == Randomized benchmarking offers several key advantages over alternative approaches to error characterization. For example, the number of experimental procedures required for full characterization of errors (called tomography) grows exponentially with the number of quantum bits (called qubits). This makes tomographic methods impractical for even small systems of just 3 or 4 qubits. In contrast, randomized benchmarking protocols are the only known approaches to error characterization that scale efficiently as number of qubits in the system increases. Thus RB can be applied in practice to characterize errors in arbitrarily large quantum processors. Additionally, in experimental quantum computing, procedures for state preparation and measurement (SPAM) are also error-prone, and thus quantum process tomography is unable to distinguish errors associated with gate operations from errors associated with SPAM. In contrast, RB protocols are robust to state-preparation and measurement errors Randomized benchmarking protocols estimate key features of the errors that affect a set of quantum operations by examining how the observed fidelity of the final quantum state decreases as the length of the random sequence increases. If the set of operations satisfies certain mathematical properties, such as comprising a sequence of twirls with unitary two-designs, then the measured decay can be shown to be an invariant exponential with a rate fixed uniquely by features of the error model. == History == Randomized benchmarking was proposed in Scalable noise estimation with random unitary operators, where it was shown that long sequences of quantum gates sampled uniformly at random from the Haar measure on the group SU(d) would lead to an exponential decay at a rate that was uniquely fixed by the error model. Emerson, Alicki and Zyczkowski also showed, under the assumption of gate-independent errors, that the measured decay rate is directly related to an important figure of merit, the average gate fidelity and independent of the choice of initial state and any errors in the initial state, as well as the specific random sequences of quantum gates. This protocol applied for arbitrary dimension d and an arbitrary number n of qubits, where d=2n. The SU(d) RB protocol had two important limitations that were overcome in a modified protocol proposed by Dankert et al., who proposed sampling the gate operations uniformly at random from any unitary two-design, such as the Clifford group. They proved that this would produce the same exponential decay rate as the random SU(d) version of the protocol proposed in Emerson et al.. This follows from the observation that a random sequence of gates is equivalent to an independent sequence of twirls under that group, as conjectured in and later proven in. This Clifford-group approach to Randomized Benchmarking is the now standard method for assessing error rates in quantum computers. A variation of this protocol was proposed by NIST in 2008 for the first experimental implementation of an RB-type for single qubit gates. However, the sampling of random gates in the NIST protocol was later proven not to reproduce any unitary two-design. The NIST RB protocol was later shown to also produce an exponential fidelity decay, albeit with a rate that depends on non-invariant features of the error model In recent years a rigorous theoretical framework has been developed for Clifford-group RB protocols to show that they work reliably under very broad experimental conditions. In 2011 and 2012, Magesan et al. proved that the exponential decay rate is fully robust to arbitrary state preparation and measurement errors (SPAM). They also proved a connection between the average gate fidelity and diamond norm metric of error that is relevant to the fault-tolerant threshold. They also provided evidence that the observed decay was exponential and related to the average gate fidelity even if the error model varied across the gate operations, so-called gate-dependent errors, which is the experimentally realistic situation. In 2018, Wallman and Dugas et al., showed that, despite concerns raised in, even under very strong gate-dependence errors the standard RB protocols produces an exponential decay at a rate that precisely measures the average gate-fidelity of the experimentally relevant errors. The results of Wallman. in particular proved that the RB error rate is so robust to gate-dependent errors models that it provides an extremely sensitive tool for detecting non-Markovian errors. This follows because under a standard RB experiment only non-Markovian errors (including time-dependent Markovian errors) can produce a statistically significant deviation from an exponential decay The standard RB protocol was first implemented for single qubit gate operations in 2012 at Yale on a superconducting qubit. A variation of this standard protocol that is only defined for single qubit operations was implemented by NIST in 2008 on a trapped ion. The first implementation of the standard RB protocol for two-qubit gates was performed in 2012 at NIST for a system of two trapped ions

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  • Artificial intelligence in education

    Artificial intelligence in education

    Artificial intelligence in education (often abbreviated as AIEd) is a subfield of educational technology that studies how to use artificial intelligence to create learning environments. Considerations in the field include data-driven decision-making, AI ethics, data privacy and AI literacy. Concerns include the potential for cheating, over-reliance, equity of access, reduced critical thinking, and the perpetuation of misinformation and bias. == History == Efforts to integrate AI into educational contexts have often followed technological advancement in the history of artificial intelligence. In the 1960s, educators and researchers began developing computer-based instruction systems, such as PLATO, developed by the University of Illinois. In the 1970s and 1980s, intelligent tutoring systems (ITS) were being adapted for classroom instruction. The International Artificial Intelligence in Education Society was founded in 1993. Coinciding with the AI boom of the 2020s, the use of large language models in the global north has been promoted and funded by venture capital and big tech. Companies creating AI services have targeted students and educational institutions as customers. Similarly, pre-AI boom educational companies have expanded their use of AI technologies. These commercial incentives for AIEd use may be related to a potential AI bubble. In the U.S., bipartisan support of AI development in K-12 education has been expressed, but specific implementations and best practices remain contentious. == Theory == AIEd applies theory from education studies, machine learning, and related fields. A 2019 review of the previous decade of studies found that most research prioritized technological design over pedagogical integration. Ouyang and Jiao (2021) propose three paradigms for AI in education, which follow roughly from least to most learner-centered and from requiring least to most technical complexity from the AI systems: AI-directed, learner-as-recipient: AIEd systems present a pre-set curriculum based on statistical patterns that do not adjust to learner's feedback. AI-supported, learner-as-collaborator: Systems that incorporate responsiveness to learner's feedback through, for example, natural language processing, wherein AI can support knowledge construction. AI-empowered, learner-as-leader: This model seeks to position AI as a supplement to human intelligence wherein learners take agency and AI provides consistent and actionable feedback. Some scholars place AI in education within a socio-technical framework. This positions AI alongside other emerging educational technologies, such as computing, the internet, and social media. The framework of Tsao, Heinrichs and Camit (2025) draws on new materialism and posthumanism, specifically Donna Haraway's concept of sympoiesis (making-with). This perspective views learning as an entanglement of human and non-human actors (students, teachers, and AI algorithms), where knowledge is co-composed in contact zones between human context and algorithmic prediction. AI agents have been trained on biased datasets, and thus continue to perpetuate societal biases. Since LLMs were created to produce human-like text, algorithmic bias can be introduced and reproduced. AI's data processing and monitoring reinforce neoliberal approaches to education rather than addressing inequalities. == Applications == Uses of generative AI chatbots in education have included assessment and feedback, machine translations, proof-reading exam question generation and copy editing, or as virtual assistants. Emotional AI in education is the study and development of systems that can detect learners' emotions or provide emotional support in learning. == Usage == === Schools and educators === Following the release of ChatGPT in November 2022, some schools and large school districts blocked access to the site and issued warnings that the use of such tools would be seen as cheating. Governmental and non-governmental organizations such as UNESCO, Article 4 of the European Union's AI Act, and the U.S. Department of Education have published reports advocating for specific AIEd approaches. National higher-education bodies have also published guidance on generative AI, including Ireland's Higher Education Authority, which issued a policy framework for higher education teaching and learning in December 2025. In 2024, UNESCO released updated global guidance for generative AI in education, emphasizing ethical use, teacher training, and data protection to ensure responsible integration of AI tools in learning environments. According to Taso (2025), policy implementation in higher education is interpreted and enacted differently by various organizations. These decentralized policies can lead to inconsistent enforcement and confusion among students regarding what constitutes acceptable use, with the burden of ethical navigation falling on individual teachers and students. AI integration in classrooms has created new forms of invisible labour for educators, who must navigate ambiguous policies, redesign assessments to be AI-resilient, and adjudicate potential academic integrity violations. The use of AI detection tools has also been criticised for creating an adversarial relationship between students and institutions, where students may be falsely accused of misconduct based on probabilistic software. AIEd advocates say that efforts should be made towards increasing global accessibility and training educators to serve underprivileged areas. === Students === Reliance on generative AI has been linked with reduced academic self-esteem and performance, and heightened learned helplessness. Algorithm errors and hallucinations are common flaws in AI agents, making them less trustworthy and reliable. According to a 2025 survey from Inside Higher Ed, 85% of higher education students use generative AI technology in some way, with 25% using AI to complete assignments for them. The most common reason cited for using AI to cheat was pressure to get high grades. 97% of students wanted some form of action from schools on the threat to academic integrity caused by AI, with the most popular options being clearer policies and more education about ethical uses of AI. In September 2025, The Atlantic published an op-ed from a high school senior arguing that the normalization of AI cheating was eroding critical thinking, academic integrity, creativity, and the shared student experience.

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  • Interference (communication)

    Interference (communication)

    In telecommunications, an interference is that which modifies a signal in a disruptive manner, as it travels along a communication channel between its source and receiver. The term is often used to refer to the addition of unwanted signals to a useful signal. Common examples include: Electromagnetic interference (EMI) Co-channel interference (CCI), also known as crosstalk Adjacent-channel interference (ACI) Intersymbol interference (ISI) Inter-carrier interference (ICI), caused by doppler shift in OFDM modulation (multitone modulation). Common-mode interference (CMI) Conducted interference Noise is a form of interference but not all interference is noise. Radio resource management aims at reducing and controlling the co-channel and adjacent-channel interference. == Interference alignment == A solution to interference problems in wireless communication networks is interference alignment, which was crystallized by Syed Ali Jafar at the University of California, Irvine. A specialized application was previously studied by Yitzhak Birk and Tomer Kol for an index coding problem in 1998. For interference management in wireless communication, interference alignment was originally introduced by Mohammad Ali Maddah-Ali, Abolfazl S. Motahari, and Amir Keyvan Khandani, at the University of Waterloo, for communication over wireless X channels. Interference alignment was eventually established as a general principle by Jafar and Viveck R. Cadambe in 2008, when they introduced "a mechanism to align an arbitrarily large number of interferers, leading to the surprising conclusion that wireless networks are not essentially interference limited." This led to the adoption of interference alignment in the design of wireless networks. Jafar explained: My research group crystallized the concept of interference alignment and showed that through interference alignment, it is possible for everyone to access half of the total bandwidth free from interference. Initially this result was shown under a number of idealized assumptions that are typical in theoretical studies. We have since continued to work on peeling off these idealizations one at a time, to bring the theory closer to practice. Along the way we have made numerous discoveries through the lens of interference alignment, which reveal new and powerful signaling schemes. According to New York University senior researcher Paul Horn: Syed Jafar revolutionized our understanding of the capacity limits of wireless networks. He demonstrated the astounding result that each user in a wireless network can access half of the spectrum without interference from other users, regardless of how many users are sharing the spectrum. This is a truly remarkable result that has a tremendous impact on both information theory and the design of wireless networks.

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  • Proximedia Group

    Proximedia Group

    Proximedia Group is a Belgian media group. == History == Proximedia Belgium was founded in 1998, by Fabrice Wuyts and Eric Glachant. The company specializes in providing websites for SMEs. The Proximedia Group SA was founded in 1999 and became the coordinating organization of Proximedia Belgium, Online, Bizbook Channel, Globule Bleu bvba, Click+, Proximedia France, Proximedia Nederland, and Proximedia Spain. The Proximedia Group has been listed at the Free Market of Euronext Brussels since 2005. In 2007, the Proximedia Group founded the Bizbook Channel. This branch specialized in creating corporate videos. In 2008, Proximedia SA took over the web agency Globule Bleu. The following year, Proximedia launched the brand BeUP. They were also elected ‘Enterprise of The Year 2009’ by Ernst & Young. Proximedia launched two new services in 2011: Videobiz and Promobook. In 2012, the Bizbook Channel was launched. Proximedia was acquired by Publicis Groupe S.A. in July 2014. == Branches == Proximedia Belgium: the oldest branch of the Proximedia Group. It makes websites and provides support for their customers. Similar branches are Proximedia France and Proximedia Nederland. Batibouw +: specialized in bringing contractors and clients together. Bizbook Channel: specialized in creating corporate videos for SMEs. Click+: offers the management of Google AdWords campaigns. This contains advertising in Google's search results. Globule Bleu: specialized in digital campaigns for larger companies or organisations. Online: an Internet Service Provider (ISP) that provides internet access, domain names, hosting of websites and data centers, email service, etc. Bizbook: an online guestbook where users can post reviews on products and services of a company. Promobook: an online service which can be used to print promotions and coupons. == Key figures == == Sale tactics and lawsuits == There are a lot of websites, forums and blogs that warn for Proximedia. This is because of the long duration of the contract, the inability to terminate the contract and the alleged aggressive approach of Proximedia and the alleged low quality of service that Proximedia offers. Also, there are a lot of lawsuits every month, some of which are customers that wish to terminate the contract, others that allege Proximedia of misguiding. List of some example lawsuits: Mitigation of contractual termination compensation on the basis of article 6:248 paragraph 2 of the Dutch Civil Code A clause on the basis of which a termination fee is claimed can be considered a penalty clause. Mitigation of the penalty based on article 6:94 of the Dutch Civil Code? Performance claim rejected; successful appeal to breach of contract; dissolution; restitution claim awarded. Agreement for IT services. Contents of the agreement. No reflex effect of the Door-to-Door Sales Act for small entrepreneurs. Implementation Act of the Consumer Rights Directive. Breach of contract? Unreasonably onerous clause? Cassation: ECLI:NL:HR:2016:996, (Partial) annulment with referral. Final judgment: ECLI:NL:GHSHE:2014:4228 Error. Reflex effect of the unfair commercial practices law? Compelling evidentiary force of written agreement. (No summary provided by court) Proximedia case. No valid defense against the claim concerning a number of monthly invoices. Article 7.1 of the agreement (containing a termination fee) is a general term in the sense of article 6:231 introductory text and under a of the Dutch Civil Code. No "reflex effect" of article 6:237 introductory text and under i of the Dutch Civil Code. Insufficiently argued why article 7.1 would be unreasonably onerous in the sense of article 6:233 of the Dutch Civil Code and that granting the claim would be unacceptable according to standards of reasonableness and fairness. Termination fee is not a penalty in the sense of article 6:91 of the Dutch Civil Code. A retailer (sole proprietorship) is approached by a representative of a company and enters into an "agreement for IT services" with a term of four years, which includes a dissolution fee of 60% of the not yet due monthly payments. The retailer is instructed to prove that, at the time of entering the agreement, the company promised him that he could terminate the agreement without any further obligations if he terminated his business. The retailer is considered to have succeeded in the burden of proof, and the company's claim for payment of the dissolution fee is rejected.

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  • Blend4Web

    Blend4Web

    Blend4Web is a free and open source framework for creating and displaying interactive 3D computer graphics in web browsers. == Overview == The Blend4Web framework leverages Blender to edit 3D scenes. Content rendering relies on WebGL, Web Audio, WebVR, and other web standards, without the use of plug-ins. It is dual-licensed. The framework is distributed under the free and open source GPLv3 and, a non-free license - with the source code being hosted on GitHub. A 3D scene can be prepared in Blender and then exported as a pair of JSON and binary files to load in a web application. It can also be exported as a single, self-contained HTML file, in which exported data, the web player GUI, and the engine itself are packed. The HTML option is considered to be the simplest way. The resulting file, which has a minimum size of 1 MB, can be embedded in a web page using a standard iframe HTML element. Blend4Web-powered web applications can be deployed on social networking websites such as Facebook. The Blend4Web toolchain consists of JavaScript libraries, the Blender add-on, and a set of tools for tweaking 3D scene parameters, debugging, and optimization. Developed by Moscow-based company Triumph in 2010, Blend4Web was publicly released on March 28, 2014. At the end of 2017, the project founders Yuri and Alex Kovelenov quit Triumph to start the development of a new WebGL framework Verge3D. In October 2019, an "Absolutely new Blend4Web" was announced, planned to make developing 3D apps easier and to add a new marketplace where people can offer their 3D models. == Features == The framework has a number of components typically found in game engines, including a positional audio system, physics engine (a fork of Bullet ported to JavaScript), animation system, and an abstraction layer for game logic programming. Up to 8 different types of animations can be assigned to a single object, including skeletal and per-vertex animation. The speed and the direction of animation (forward/backward play), as well as particle system parameters (size, initial velocity, and count), can be changed through the API. Among other supported features are: scene data dynamic loading and unloading, subsurface scattering simulation, and image-based lighting. Some out-of-box options exist for rendering extended outdoor environments, including foliage-wind interaction, water, atmosphere, and sunlight simulation. One example demonstrating these effects is "The Farm" tech demo, which also features multiple animated NPCs and the ability to walk, interact with objects and drive a vehicle in first-person mode. Being based on the cross-browser WebGL API, Blend4Web runs in the majority of web browsers, including mobile ones. There are some caveats for browsers with experimental WebGL support, such as Internet Explorer. There are also applications developed to run on Tizen-powered devices such as the Samsung Gear S2 smartwatch. Other features include: draw call batching, hidden surface determination, threaded physics simulation and ocean simulation. In version 14.09, Blend4Web introduced the possibility of adding interactivity to 3D scenes using a visual programming tool. The tool is reminiscent of the BGE's logic editor as it uses logic blocks that are placed inside Blender. It plays back animation tracks authored by an artist when the user interacts with predefined 3D objects. Since version 15.03, Blend4Web has supported attaching HTML elements (such as information windows) to 3D objects ("annotations") and copying objects in run time ("instancing"). The following post-processing effects are supported: glow, bloom, depth of field, crepuscular rays, motion blur, and screen space ambient occlusion. == Virtual reality and augmented reality == Virtual reality devices have been supported since the end of 2015. Specifically, Oculus Rift head-mounted display works over experimental WebVR API. The software also now includes preliminary support for gamepads, based on the Gamepad API. In 2017, the option to author augmented reality content was added. The system is based on the open-source tracking library ARToolKit and uses the WebRTC protocols. Starting from version 17.08, finger tracking is supported through the Leap Motion device. == Blender integration == The Blender add-on is written in Python and C and can be compiled for the Linux x86/x64, OS X x64, and MS Windows x86/x64 platforms. A Blend4Web-specific profile can be activated in the add-on settings. When switching to this profile, the Blender interface changes so that it only reveals settings relevant to Blend4Web. Blend4Web supports a set of Blender-specific features such as the node material editor (a tool for visual shader programming) and the particle system. There is basic support for Blender's non-linear animation (NLA) editor for creating simple scenarios. Blend4Web is based on Blender's real-time GLSL rendering engine, which users are recommended to use in order to enable WYSIWYG editing. == Notable uses == NASA developed an interactive web application called Experience Curiosity to celebrate the 3rd anniversary of the Curiosity rover landing on Mars. This Blend4Web-based app makes it possible to operate the rover, control its cameras and the robotic arm, and reproduce some of the prominent events of the Mars Science Laboratory mission. The application got presented at the beginning of the WebGL section at SIGGRAPH 2015. Experience Curiosity was ported to Verge3D for Blender in 2018 with several performance improvements and bug fixes. A General Motors authorized dealer in the United Arab Emirates has placed a functional Chevrolet Camaro 3D configurator on its website. Greenpeace created interactive 3D infographics to back Greenpeace's Detox campaign in Russia. Tallink featured an interactive 3D presentation of its MS Megastar vessel to allow visitors to browse details of the ship.

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  • Gas (app)

    Gas (app)

    Gas (sometimes stylized in all caps), formerly known as Melt as well as Crush, was an American anonymous social media app. Launched in August 2022, the app is oriented towards high schoolers. The app was developed by Nikita Bier, Isaiah Turner, and former Facebook engineer Dave Schatz. Gas was largely based upon the prior tbh app developed by co-founder Nikita Bier, along with Erik Hazzard, Kyle Zaragoza, and Nicolas Ducdodon in September 2017. tbh was acquired by Facebook inc. (now Meta Platforms) on October 16, 2017, and nearly a year later in July 2018 was dissolved, owing to low usage. Gas follows a similar purpose to tbh in being a social media app oriented towards high schoolers. In the app, users participate in anonymous polls regarding pre-written complimentary statements to their peers, such as "I'd say yes if (blank) asked me out on a date," "I think (blank) is the coolest kid in school," or "would make an ugly face and still look pretty." Winners of said polls receive a "flame." The name of the app is derived from this, with "gassing someone up" being Gen Z slang for complimenting someone. Users can pay a $6.99 subscription that enables "God Mode," which shows hints regarding who voted for them in a poll. Gas overtook TikTok and BeReal as the most downloaded app on the Apple App Store in October 2022 (the app is currently not available for Android). The app has over 5.1 million downloads as of early November 2022, over a million active users and 300 thousand daily downloads as of October 2022. Currently, the app is available in Canada and the majority of the United States. On January 17, 2023, Gas was acquired by Discord, however it would remain a standalone app and its developers became Discord staff members. On October 18, 2023, Discord announced that service for Gas would be permanently ending effective November 7, 2023, due to a steep decline in users. Effective November 7, the app became completely unusable. == Controversy regarding human-trafficking == Beginning in October 2022, rumors spread largely throughout TikTok and Snapchat alleged that the app was linked to human trafficking (in particular sex trafficking). According to Bier, the rumor originated with a single user review from China on October 5, and then was disseminated through TikTok accounts with "few to no US teen followers." Although largely dismissed as a hoax by experts, who cite how the app doesn't log user locations and general anonymity, the hoax became pervasive to the extent that various police departments, school systems, and local news outlets began issuing warnings regarding the app. For instance, on October 31, 2022, the police department of Piedmont, Oklahoma issued a warning to parents, encouraging them to check their children's phones, while on November 3, the Oklahoma Oktaha Public School system stated in a Facebook post that "Children are being kidnapped in other towns and this new app is thought to be the source of predators finding their location." (both statements have since been retracted by Police Chief Scott Singer and Superintendent Jerry Needham respectively). Additionally, local medial outlets such as KOCO in Oklahoma City ran stories making similar statements. The rumor had a negative impact on the app, with downloads plateauing for a two-week period in late October and with 3% of users in a single day reportedly uninstalling the app. Revenue and ratings have also reportedly dropped and the company's social media accounts have been bombarded with comments labeling them as sex-traffickers. Additionally, the four-person development team has reportedly been bombarded with various death threats as a result.

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  • Blue check

    Blue check

    A blue check is used on social media platforms, notably X (formerly known as Twitter), to indicate the authenticity of an account. Since November 2022, Twitter users whose accounts are at least 90 days old and have a verified phone number receive verification upon subscribing to X Premium or Verified Organizations; this status persists as long as the subscription remains active. When introduced in June 2009, the system provided the site's readers with a means to distinguish genuine notable account holders, such as celebrities and organizations, from impostors or parodies. Until November 2022, a blue checkmark displayed against an account name indicated that Twitter had taken steps to ensure that the account was actually owned by the person or organization whom it claimed to represent. The checkmark does not imply endorsement from Twitter, and does not mean that tweets from a verified account are necessarily accurate or truthful in any way. People with verified accounts on Twitter are often colloquially referred to as "blue checks" on social media and by reporters. In November 2022, the verification program was modified heavily by new owner Elon Musk, extending verification to any account with a verified phone number and an active subscription to an eligible X Premium (formerly Twitter Blue) plan. These changes faced criticism from users and the media, who believed that the changes would ease impersonation, and allow accounts spreading misleading information to feign credibility. In a related change, Twitter introduced additional gold and gray checkmarks, used by Verified Organizations and government-affiliated accounts, respectively. Twitter claims that the changes to verification are required to "reduce fraudulent accounts and bots". Twitter users who had been verified through the previous system were known as "legacy verified" accounts; legacy verification was deprecated in April 2023, and stripped from accounts who do not meet the new payment requirements. Musk later implied that he had been personally paying for the X Premium subscriptions of several notable celebrities. == Until November 2022 == In June 2009, after being criticized by Kanye West and sued by Tony La Russa over unauthorized accounts run by impersonators, the company launched their "Verified Accounts" program. Twitter stated that an account with a "blue tick" verification badge indicates "we've been in contact with the person or entity the account is representing and verified that it is approved". After the beta period, the company stated in their FAQ that it "proactively verifies accounts on an ongoing basis to make it easier for users to find who they're looking for" and that they "do not accept requests for verification from the general public". Originally, Twitter took on the responsibility of reaching out to celebrities and other notable people to confirm their identities in order to establish a verified account. In July 2016, Twitter announced a public application process to grant verified status to an account "if it is determined to be of public interest" and that verification "does not imply an endorsement". In 2016, the company began accepting requests for verification, but it was discontinued the same year. Twitter explained that the volume of requests for verified accounts had exceeded its ability to cope; rather, Twitter determines on its own whom to approach about verified accounts, limiting verification to accounts which are "authentic, notable, and active". In November 2020, Twitter announced a relaunch of its verification system in 2021. According to the new policy, Twitter verifies six different types of accounts; for three of them (companies, brands, and influential individuals like activists), the existence of a Wikipedia page will be one criterion for showing that the account has "Off Twitter Notability". === Controversy === On June 21, 2014, actor William Shatner raised an issue with several Engadget editorial staff and their verification status on Twitter. Besides the site's social media editor, John Colucci, Shatner also targeted several junior members of the staff for being "nobodies", unlike some of his actor colleagues who did not bear such distinction. Shatner claimed Colucci and the team were bullying him when giving a text interview to Mashable. Over a month later, Shatner continued to discuss the issue on his Tumblr page, to which Engadget replied by defending its team and discussing the controversy surrounding the social media verification. Twitter's practice and process for verifying accounts came under scrutiny again in 2017 after the company verified the account of white supremacist and far-right political activist, Jason Kessler. Many who criticized Twitter's decision to verify Kessler's account saw this as a political act on the company's behalf. In response, Twitter put its verification process on hold. The company tweeted, "Verification was meant to authenticate identity & voice but it is interpreted as an endorsement or an indicator of importance. We recognize that we have created this confusion and need to resolve it. We have paused all general verifications while we work and will report back soon." As of November 2017, Twitter continued to deny verification of Julian Assange's account following his requests. In November 2019, Dalit activists of India alleged that higher-caste people get Twitter verification easily and trended hashtags #CancelAllBlueTicksInIndia and #CasteistTwitter. Critics have said that the company's verification process is not transparent and causes digital marginalisation of already marginalised communities. Twitter India rejected the allegations, calling them "impartial" and working on a "case-by-case" policy. == Since November 2022 == On April 20, 2023, Twitter (known as X since July 2023) began removing verification status for users of public interest, causing a controversy among Twitter users. The website's system was altered, allowing any individual to receive verification for a monthly fee, an act which saw significant criticism. Following the acquisition of Twitter by Elon Musk on October 28, 2022, Musk told Twitter employees to introduce paid verification by November 7 through Twitter Blue. The Verge reported that the updated Blue subscription would cost $19.99 per month, and users would lose their verification status if they did not join within 90 days. Following backlash, Musk tweeted, in response to author Stephen King, a lowered $8 price on November 1, 2022. Twitter confirmed the new price of $7.99 per month on November 5, 2022. The new verification system began rollout on November 9, 2022, a day after the 2022 United States elections. The decision to delay its rollout was to address concerns about users potentially spreading misinformation about voting results by posing as news outlets and lawmakers. At the same time, Twitter introduced a secondary gray "Official" label on some high-profile accounts, but removed them hours after launch. Less than 48 hours later, Twitter reinstated the gray "Official" label, after multiple users were suspended for deliberately impersonating reporters and high-profile athletes like LeBron James. A viral tweet from an account purporting to be the pharmaceutical company Eli Lilly and Company caused the company's stock to fall after announcing "insulin is free now". As a result, Twitter disabled new Blue subscriptions on November 11, 2022. === Announcement === In October 2022, Casey Newton of Platformer reported that executives at Twitter began discussing the possibility of users being forced to pay for Twitter Blue in order to keep their verification status. Musk publicly announced that verification was "being revamped right now" after Newton's article; according to The Verge, Twitter planned to increase the price of Twitter Blue from US$4.99 per month to US$19.99 per month. Users would have had 90 days to subscribe or face losing their verification status, and employees were told to implement paid verification by November 9 or risk getting fired. Upon the news that Twitter Blue would cost US$19.99 per month, author Stephen King expressed displeasure towards Twitter and stated that he would leave. Musk, replying to King's tweet, proposed that the service should cost US$7.99 instead. In a separate tweet, Musk wrote that Twitter Blue subscribers would receive priority in replies, mentions, and search, fewer advertisements, and longer audio and video. Although paid verification was expected to be launched by November 7, the reintroduction of Twitter Blue was delayed until after the 2022 United States elections on November 9, according to a memo obtained by The New York Times. The announcement of paid verification resulted in several accounts facetiously impersonating Musk, such as those of comedians Kathy Griffin and Sarah Silverman, being suspended. In response, Musk announced that impersonators using Twitter Blue "will be permanently suspended". An "official

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  • Electronics

    Electronics

    Electronics is a scientific and engineering discipline that studies and applies the principles of physics to design, create, and operate devices that manipulate electrons and other electrically charged particles. It is a subfield of physics and electrical engineering which uses active devices such as transistors, diodes, and integrated circuits to control and amplify the flow of electric current and to convert it from one form to another, such as from alternating current (AC) to direct current (DC) or from analog signals to digital signals. Electronic devices have significantly influenced the development of many aspects of modern society, such as telecommunications, entertainment, education, health care, industry, and security. The main driving force behind the advancement of electronics is the semiconductor industry, which continually produces ever-more sophisticated electronic devices and circuits in response to global demand. The semiconductor industry is one of the global economy's largest and most profitable industries, with annual revenues exceeding $481 billion in 2018. The electronics industry also encompasses other branches that rely on electronic devices and systems, such as e-commerce, which generated over $29 trillion in online sales in 2017. == History and development == Karl Ferdinand Braun's development of the crystal detector, the first semiconductor device, in 1874 and the identification of the electron in 1897 by Sir Joseph John Thomson, along with the subsequent invention of the vacuum tube which could amplify and rectify small electrical signals, inaugurated the field of electronics and the electron age. Practical applications started with the invention of the diode by Ambrose Fleming and the triode by Lee De Forest in the early 1900s, which made the detection of small electrical voltages, such as radio signals from a radio antenna, practicable. Vacuum tubes (thermionic valves) were the first active electronic components which controlled current flow by influencing the flow of individual electrons, and enabled the construction of equipment that used current amplification and rectification to give us radio, television, radar, long-distance telephony and much more. The early growth of electronics was rapid, and by the 1920s, commercial radio broadcasting and telecommunications were becoming widespread and electronic amplifiers were being used in such diverse applications as long-distance telephony and the music recording industry. The next big technological step took several decades to appear, when the first working point-contact transistor was invented by John Bardeen and Walter Houser Brattain at Bell Labs in 1947. However, vacuum tubes continued to play a leading role in the field of microwave and high power transmission as well as television receivers until the middle of the 1980s. Since then, solid-state devices have all but completely taken over. Vacuum tubes are still used in some specialist applications such as high power RF amplifiers, cathode-ray tubes, specialist audio equipment, guitar amplifiers and some microwave devices. In April 1955, the IBM 608 was the first IBM product to use transistor circuits without any vacuum tubes and is believed to be the first all-transistorized calculator to be manufactured for the commercial market. The 608 contained more than 3,000 germanium transistors. Thomas J. Watson Jr. ordered all future IBM products to use transistors in their design. From that time on, transistors were almost exclusively used for computer logic circuits and peripheral devices. However, early junction transistors were relatively bulky devices that were difficult to manufacture on a mass-production basis, which limited them to a number of specialised applications. The MOSFET was invented at Bell Labs between 1955 and 1960. It was the first truly compact transistor that could be miniaturised and mass-produced for a wide range of uses. Its advantages include high scalability, affordability, low power consumption, and high density. It revolutionized the electronics industry, becoming the most widely used electronic device in the world. The MOSFET is the basic element in most modern electronic equipment. As the complexity of circuits grew, problems arose. One problem was the size of the circuit. A complex circuit like a computer was dependent on speed. If the components were large, the wires interconnecting them must be long. The electric signals took time to go through the circuit, thus slowing the computer. The invention of the integrated circuit by Jack Kilby and Robert Noyce solved this problem by making all the components and the chip out of the same block (monolith) of semiconductor material. The circuits could be made smaller, and the manufacturing process could be automated. This led to the idea of integrating all components on a single-crystal silicon wafer, which led to small-scale integration (SSI) in the early 1960s, and then medium-scale integration (MSI) in the late 1960s, followed by VLSI. In 2008, billion-transistor processors became commercially available. == Subfields == == Devices and components == An electronic component is any component, either active or passive, in an electronic system or electronic device. Components are connected together, usually by being soldered to a printed circuit board (PCB), to create an electronic circuit with a particular function. Components may be packaged singly or in more complex groups as integrated circuits. Passive electronic components are capacitors, inductors, resistors, whilst active components are such as semiconductor devices; transistors and thyristors, which control current flow at electron level. == Types of circuits == Electronic circuit functions can be divided into two function groups: analog and digital. A particular device may consist of circuitry that has either or a mix of the two types. Analog circuits are becoming less common, as many of their functions are being digitized. === Analog circuits === Analog circuits use a continuous range of voltage or current for signal processing, as opposed to the discrete levels used in digital circuits. Analog circuits were common throughout electronic devices in the early years, in devices such as radio receivers and transmitters. Analog electronic computers were valuable for solving problems with continuous variables until digital processing advanced. As semiconductor technology developed, many of the functions of analog circuits were taken over by digital circuits, and modern circuits that are entirely analog are less common; their functions being replaced by hybrid approach which, for instance, uses analog circuits at the front end of a device receiving an analog signal, and then use digital processing using microprocessor techniques thereafter. Sometimes it may be difficult to classify some circuits that have elements of both linear and non-linear operation. An example is the voltage comparator, which receives a continuous range of voltage but only outputs one of two levels, as in a digital circuit. Similarly, an overdriven transistor amplifier can take on the characteristics of a controlled switch, having essentially two levels of output. Analog circuits are still widely used for signal amplification, such as in the entertainment industry, and conditioning signals from analog sensors, such as in industrial measurement and control. === Digital circuits === Digital circuits are electric circuits based on discrete voltage levels. Digital circuits use Boolean algebra and are the basis of all digital computers and microprocessor devices. They range from simple logic gates to large integrated circuits, employing millions of such gates. Digital circuits use a binary system with two voltage levels labelled 0 and 1 to indicate logical status. Often logic 0 will be a lower voltage and referred to as Low while logic 1 is referred to as High. However, some systems use the reverse definition (0 is High) or are current based. Quite often, the logic designer may reverse these definitions from one circuit to the next as they see fit to facilitate their design. The definition of the levels as 0 or 1 is arbitrary. Ternary (with three states) logic has been studied, and some prototype computers made, but have not gained any significant practical acceptance. Universally, computers and digital signal processors are constructed with digital logic circuits using transistors such as MOSFETs in the electronic logic gates to generate binary states. Logic gates Adders Flip-flops Counters Registers Multiplexers Schmitt triggers Highly integrated devices: Memory chip Microprocessors Microcontrollers Application-specific integrated circuit (ASIC) Digital signal processor (DSP) Field-programmable gate array (FPGA) Field-programmable analog array (FPAA) System on chip (SOC) == Design == Electronic systems design deals with the multi-disciplinary design issues of complex electronic devices and systems, such as mob

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