AI Generator Quillbot

AI Generator Quillbot — independent reviews, comparisons, pricing and step-by-step guides on Aizhi.

  • Showbox.com

    Showbox.com

    Showbox is an online video streaming platform that enables users to stream and download many videos, commonly movies and TV shows, for free. == History == The company opened the platforms to users who registered from its beta in late 2015. The platform was officially launched in February 2016, enabling any visitor to sign up and create videos online. In April 2016, Showbox was featured on the Product Hunt website, coming to the top of the website's lists for that day and week with over 1400 upvotes from the Product Hunt community. Also in April 2016, Showbox partnered with YouTube's leading multi-channel networks, including Fullscreen, BroadbandTV, StyleHaul, AwesomenessTV, and BuzzMyVideos, to enable their communities of creators to access the platform. In June 2016, the company launched Showbox For Brands, a business-oriented video creation platform, enabling companies to create video content in-house and with their communities and influencers. In March 2017, the company launched Showbox Engage, a use case of its B2B product launched in 2016, enabling companies to launch user-generated content campaigns with their communities. In April 2017, Showbox and the United Nations announced a partnership around the 70th anniversary of the declaration of human rights, with an annual, ongoing global campaign in 135 languages, inviting people worldwide to create their part of the declaration in a video from anywhere around the world. In November 2017, Showbox partnered with the Ad:tech and Digital Marketing World Forum conferences (DMWF) in New York to provide their users and communities with a User Generated Content video solution. == Technology == Showbox's video creation technology includes an online green screen feature, proprietary computer vision algorithms, deep learning technology to support the automatic creation of videos in the cloud, and advanced video composition, including special effects. == Coverage and awards == In March 2015, Showbox was nominated as one of the 10 Israeli startups to take over our TV screens this year. In July 2016, Showbox won the Publicis90 award as part of Publicis' "global initiative to foster digital entrepreneurship". In March 2017, Showbox was chosen as one of The Culture Trip's 10 startups to watch for in 2017.

    Read more →
  • Key & See

    Key & See

    Key & See is a variation of the TV Key service that forms part of the open, standards-based interactive TV services platform provided by Miniweb Interactive. Key & See allows viewers to access the interactive TV content made available by broadcasters and channel owners while leaving quarter of their screen tuned to the programme they are already watching Like TV Key, Key & See can be used with interactive TV services on UK satellite TV provider Sky Digital (BSkyB) Key & See works in the same way as a TV Key but the numeric shortcut code is associated with a broadcaster and a particular TV channel or programme. Miniweb Interactive offers commercial brands and broadcasters the chance to utilise TV Key and Key & See technology as part of its interactive TV services platform

    Read more →
  • Affordable affluence

    Affordable affluence

    Affordable affluence refers to a cultural phenomenon where consumers use accessible luxury goods and lifestyles to project status and align themselves with a higher social class, without requiring substantial wealth. This concept is embodied by brands such as Aritzia and Erewhon, which position themselves as offering high-end, trendy, or health-conscious products that are relatively accessible to the average consumer. A related concept is quiet luxury, where the ultra-wealthy signal wealth through subtle means. Quiet luxury emphasizes the widening gap between the ultra-wealthy and the general public, whereas accessible affluence provides a way for the general public to indulge in the lifestyle of the ultra-wealthy. == Origin of the term == An early use of the phrase in this context in a 2023 article in The Cut called "Meet the People Working 3 Jobs to Afford Erewhon." One of the interviewees used Erewhon as an archetype of affordable affluence. It was described as “a way for regular people to position themselves adjacent to the upper class.” == Background and description == The phenomenon arises due to an individual's desire to showcase status. For years, companies have strategized how to target the average consumers by providing a product that signals an elevated social status. For instance, Aritzia partnered with celebrities and micro-influencers to make it an aspirational brand at an affordable cost. Erewhon similarly has allowed middle class consumers to subtly signal a higher degree of perceived wealth by purchasing higher priced, but still attainable items. It has allowed middle-class individuals to feel as though they are part of an exclusive culture. This phenomenon has been seen particularly with Gen Z and Millennials in the setting of financial hardships in the 2020s. Affordable affluence is an example of the lipstick effect. Because traditional status symbols such as expensive cars became relatively more unattainable, posting clips on social media that showcase affordable affluence become an alternative status symbol. Particularly with food, the perception has evolved from a necessity to a luxury. A McKinsey & Company report demonstrated that these generations place a higher importance on groceries than restaurants, travel, and beauty/fashion.

    Read more →
  • W3C Device Description Working Group

    W3C Device Description Working Group

    The W3C Device Description Working Group (DDWG), operating as part of the World Wide Web Consortium (W3C) Mobile Web Initiative (MWI), was chartered to "foster the provision and access to device descriptions that can be used in support of Web-enabled applications that provide an appropriate user experience on mobile devices." Mobile devices exhibit the greatest diversity of capabilities, and therefore present the greatest challenge to content adaptation technologies. The group published several documents, including a list of requirements for an interface to a Device Description Repository (DDR) and a standard interface meeting those requirements. The group was rechartered in 2006 to work in public towards the development of the Application Programming Interface (API) for a DDR. Early in 2007, the group launched a wiki and a blog to add to the public mailing list. The group subsequently published a formal vocabulary of core device properties, and an API called the DDR Simple API, which became a W3C Recommendation in December 2008. The group closed at the end of 2008, but with the intention of maintaining the Web pages, blog and wiki through W3C volunteer effort. == Publications == The DDWG published several W3C Working Group Notes and one W3C Recommendation. A W3C WG Note that articulates what the W3C and other organizations are doing or have already done with regard to device information. This document suggests an environment in which these technologies work together to meet the goals of content adaptation. The completed document was published on 31 October 2007. A W3C WG Note describing the ecosystem surrounding creation, maintenance and use of device descriptions. The completed document was published on 31 October 2007. A W3C WG Note describing a set of requirements for a reference repository of device descriptions. The completed document was published on 17 December 2007. A W3C WG Note describing a process to manage contributions to an initial core vocabulary, identification of key device properties, a formal initial core vocabulary and the identification of a maintainer for the core vocabulary. The details were contained in the Working Group Note describing the DDWG Core Vocabulary published on 14 April 2008. A W3C WG Note defining useful grouping and structure patterns in device descriptions. The Device Description Structures document was published as a Working Draft on 5 December 2008. The intention is that this document will be future input to other W3C groups. A W3C Recommendation defining a language-neutral programming interface to a Device Description Repository. The DDR Simple API was published on 5 December 2008. There is the possibility of future publications on the DDWG wiki describing implementations of the API in various languages, including Java, IDL, WSDL, C# etc. Much of the DDWG's material was developed in public via the DDWG Wiki and through their public mailing lists.

    Read more →
  • Natural language processing

    Natural language processing

    Natural language processing (NLP) is the processing of natural language information by a computer. NLP is a subfield of computer science and is closely associated with artificial intelligence. NLP is also related to information retrieval, knowledge representation, computational linguistics, and linguistics more broadly. Major processing tasks in an NLP system include: speech recognition, text classification, natural language understanding, and natural language generation. == History == Natural language processing has its roots in the 1950s. Already in 1950, Alan Turing published an article titled "Computing Machinery and Intelligence," which proposed what is now called the Turing test as a criterion of intelligence, though at the time that was not articulated as a problem separate from artificial intelligence. The proposed test includes a task that involves the automated interpretation and generation of natural language. === Symbolic NLP (1950s – early 1990s) === The premise of symbolic NLP is often illustrated using John Searle's Chinese room thought experiment: Given a collection of rules (e.g., a Chinese phrasebook, with questions and matching answers), the computer emulates natural language understanding (or other NLP tasks) by applying those rules to the data it confronts. 1950s: The Georgetown experiment in 1954 involved fully automatic translation of more than sixty Russian sentences into English. The authors claimed that within three or five years, machine translation would be a solved problem. However, real progress was much slower, and after the ALPAC report in 1966, which found that ten years of research had failed to fulfill the expectations, funding for machine translation was dramatically reduced. Little further research in machine translation was conducted in America (though some research continued elsewhere, such as Japan and Europe) until the late 1980s when the first statistical machine translation systems were developed. 1960s: Some notably successful natural language processing systems developed in the 1960s were SHRDLU, a natural language system working in restricted "blocks worlds" with restricted vocabularies, and ELIZA, a simulation of Rogerian psychotherapy, written by Joseph Weizenbaum between 1964 and 1966. Despite using minimal information about human thought or emotion, ELIZA was able to produce interactions that appeared human-like. When the "patient" exceeded the very small knowledge base, ELIZA might provide a generic response, for example, responding to "My head hurts" with "Why do you say your head hurts?". Ross Quillian's successful work on natural language was demonstrated with a vocabulary of only twenty words, because that was all that would fit in a computer memory at the time. 1970s: During the 1970s, many programmers began to write "conceptual ontologies", which structured real-world information into computer-understandable data. Examples are MARGIE (Schank, 1975), SAM (Cullingford, 1978), PAM (Wilensky, 1978), TaleSpin (Meehan, 1976), QUALM (Lehnert, 1977), Politics (Carbonell, 1979), and Plot Units (Lehnert 1981). During this time, the first chatterbots were written (e.g., PARRY). 1980s: The 1980s and early 1990s mark the heyday of symbolic methods in NLP. Focus areas of the time included research on rule-based parsing (e.g., the development of HPSG as a computational operationalization of generative grammar), morphology (e.g., two-level morphology), semantics (e.g., Lesk algorithm), reference (e.g., within Centering Theory) and other areas of natural language understanding (e.g., in the Rhetorical Structure Theory). Other lines of research were continued, e.g., the development of chatterbots with Racter and Jabberwacky. An important development (that eventually led to the statistical turn in the 1990s) was the rising importance of quantitative evaluation in this period. === Statistical NLP (1990s–present) === Up until the 1980s, most natural language processing systems were based on complex sets of hand-written rules. Starting in the late 1980s, however, there was a revolution in natural language processing with the introduction of machine learning algorithms for language processing. This shift was influenced by increasing computational power (see Moore's law) and a decline in the dominance of Chomskyan linguistic theories (e.g. transformational grammar), whose theoretical underpinnings discouraged the sort of corpus linguistics that underlies the machine-learning approach to language processing. 1990s: Many of the notable early successes in statistical methods in NLP occurred in the field of machine translation, due especially to work at IBM Research, such as IBM alignment models. These systems were able to take advantage of existing multilingual textual corpora that had been produced by the Parliament of Canada and the European Union as a result of laws calling for the translation of all governmental proceedings into all official languages of the corresponding systems of government. However, many systems relied on corpora that were specifically developed for the tasks they were designed to perform. This reliance has been a major limitation to their broader effectiveness and continues to affect similar systems. Consequently, significant research has focused on methods for learning effectively from limited amounts of data. 2000s: With the growth of the web, increasing amounts of raw (unannotated) language data have become available since the mid-1990s. Research has thus increasingly focused on unsupervised and semi-supervised learning algorithms. Such algorithms can learn from data that has not been hand-annotated with the desired answers or using a combination of annotated and non-annotated data. Generally, this task is much more difficult than supervised learning, and typically produces less accurate results for a given amount of input data. However, large quantities of non-annotated data are available (including, among other things, the entire content of the World Wide Web), which can often make up for the worse efficiency if the algorithm used has a low enough time complexity to be practical. 2003: word n-gram model, at the time the best statistical algorithm, is outperformed by a multi-layer perceptron (with a single hidden layer and context length of several words, trained on up to 14 million words, by Bengio et al.) 2010: Tomáš Mikolov (then a PhD student at Brno University of Technology) with co-authors applied a simple recurrent neural network with a single hidden layer to language modeling, and in the following years he went on to develop Word2vec. In the 2010s, representation learning and deep neural network-style (featuring many hidden layers) machine learning methods became widespread in natural language processing. This shift gained momentum due to results showing that such techniques can achieve state-of-the-art results in many natural language tasks, e.g., in language modeling and parsing. This is increasingly important in medicine and healthcare, where NLP helps analyze notes and text in electronic health records that would otherwise be inaccessible for study when seeking to improve care or protect patient privacy. == Approaches: Symbolic, statistical, neural networks == Symbolic approach, i.e., the hand-coding of a set of rules for manipulating symbols, coupled with a dictionary lookup, was historically the first approach used both by AI in general and by NLP in particular: such as by writing grammars or devising heuristic rules for stemming. Machine learning approaches, which include both statistical and neural networks, on the other hand, have many advantages over the symbolic approach: both statistical and neural network methods tend to focus more on the most common cases extracted from a corpus of texts, whereas the rule-based approach needs to provide rules for both rare and common cases equally. language models, produced by either statistical or neural networks methods, are more robust to both unfamiliar (e.g. containing words or structures that have not been seen before) and erroneous input (e.g. with misspelled words or words accidentally omitted) in comparison to the rule-based systems, which are also more costly to produce. the larger such a (probabilistic) language model is, the more accurate it becomes, in contrast to rule-based systems that can gain accuracy only by increasing the amount and complexity of the rules leading to intractability problems. Rule-based systems are commonly used: when the amount of training data is insufficient to successfully apply machine learning methods, e.g., for the machine translation of low-resource languages such as provided by the Apertium system, for preprocessing in NLP pipelines, e.g., tokenization, or for post-processing and transforming the output of NLP pipelines, e.g., for knowledge extraction from syntactic parses. === Statistical approach === In the late 1980s and mid-1990s, the statistical approach ended a peri

    Read more →
  • Nitro Zeus

    Nitro Zeus

    Nitro Zeus is the project name for a well funded comprehensive cyber attack plan created as a mitigation strategy after the Stuxnet malware campaign and its aftermath. Unlike Stuxnet, that was loaded onto a system after the design phase to affect its proper operation, Nitro Zeus's objectives are built into a system during the design phase unbeknownst to the system users. This built-in feature allows a more assured and effective cyber attack against the system's users. The information about its existence was raised during research and interviews carried out by Alex Gibney for his Zero Days documentary film. The proposed long term widespread infiltration of major Iranian systems would disrupt and degrade communications, power grid, and other vital systems as desired by the cyber attackers. This was to be achieved by electronic implants in Iranian computer networks. The project was seen as one pathway in alternatives to full-scale war.

    Read more →
  • Telecommunications

    Telecommunications

    Telecommunication, often used in its plural form or abbreviated as telecom, is the transmission of information over a distance using electrical or electronic means, typically through cables, radio waves, or other communication technologies. These means of transmission may be divided into communication channels for multiplexing, allowing for a single medium to transmit several concurrent communication sessions. Long-distance technologies invented during the 19th, 20th and 21st centuries generally use electric power, and include the electrical telegraph, telephone, television, and radio. Early telecommunication networks used metal wires as the medium for transmitting signals. These networks were used for telegraphy and telephony for many decades. In the first decade of the 20th century, a revolution in wireless communication began with breakthroughs including those made in radio communications by Guglielmo Marconi, who won the 1909 Nobel Prize in Physics. Other early pioneers in electrical and electronic telecommunications include co-inventors of the telegraph Charles Wheatstone and Samuel Morse, numerous inventors and developers of the telephone including Antonio Meucci, Philipp Reis, Elisha Gray and Alexander Graham Bell, inventors of radio Edwin Armstrong and Lee de Forest, as well as inventors of television like Vladimir K. Zworykin, John Logie Baird and Philo Farnsworth. Since the 1960s, the proliferation of digital technologies has meant that voice communications have gradually been supplemented by data. The physical limitations of metallic media prompted the development of optical fibre. The Internet, a technology independent of any given medium, has provided global access to services for individual users and further reduced location and time limitations on communications. == Definition == At the 1932 Plenipotentiary Telegraph Conference and the International Radiotelegraph Conference in Madrid, the two organizations merged to form the International Telecommunication Union (ITU). They defined telecommunication as "any telegraphic or telephonic communication of signs, signals, writing, facsimiles and sounds of any kind, by wire, wireless or other systems or processes of electric signaling or visual signaling (semaphores)." The definition was later reconfirmed, according to Article 1.3 of the ITU Radio Regulations, which defined it as "Any transmission, emission or reception of signs, signals, writings, images and sounds or intelligence of any nature by wire, radio, optical, or other electromagnetic systems". As such, slow communications technologies like postal mail and pneumatic tubes are excluded from the telecommunication's definition. The term telecommunication was coined in 1904 by the French engineer and novelist Édouard Estaunié, who defined it as "remote transmission of thought through electricity". Telecommunication is a compound noun formed from the Greek prefix tele- (τῆλε), meaning distant, far off, or afar, and the Latin verb communicare, meaning to share. Communication was first used as an English word in the late 14th century. It comes from Old French comunicacion (14c., Modern French communication), from Latin communicationem (nominative communication), noun of action from past participle stem of communicare, "to share, divide out; communicate, impart, inform; join, unite, participate in," literally, "to make common", from communis. == History == Many transmission media have been used for long-distance communication throughout history, from smoke signals, beacons, semaphore telegraphs, signal flags, and optical heliographs to wires and empty space made to carry electromagnetic signals. === Before the electrical and electronic era === Long-distance communication was used long before the discovery of electricity and electromagnetism enabled the invention of telecommunications. A few of the many ingenious methods for communicating over distances prior to that are described here. Homing pigeons have been used throughout history by different cultures. Pigeon post had Persian roots and was later used by the Romans to aid their military. Frontinus claimed Julius Caesar used pigeons as messengers in his conquest of Gaul. The Greeks also conveyed the names of the victors at the Olympic Games to various cities using homing pigeons. In the early 19th century, the Dutch government used the system in Java and Sumatra. And in 1849, Paul Julius Reuter started a pigeon service to fly stock prices between Aachen and Brussels, a service that operated for a year until the gap in the telegraph link was closed. In the Middle Ages, chains of beacons were commonly used on hilltops as a means of relaying a signal. Beacon chains suffered the drawback that they could only pass a single bit of information, so the meaning of the message, such as "the enemy has been sighted" had to be agreed upon in advance. One notable instance of their use was during the Spanish Armada, when a beacon chain relayed a signal from Plymouth to London. In 1792, Claude Chappe, a French engineer, built the first fixed visual telegraphy system (or semaphore line) between Lille and Paris. However semaphore suffered from the need for skilled operators and expensive towers at intervals of ten to thirty kilometres (six to nineteen miles). As a result of competition from the electrical telegraph, the last commercial line was abandoned in 1880. === Telegraph and telephone === On July 25, 1837, the first commercial electrical telegraph was demonstrated by English inventor Sir William Fothergill Cooke and English scientist Sir Charles Wheatstone. Both inventors viewed their device as "an improvement to the [existing] electromagnetic telegraph" and not as a new device. Samuel Morse independently developed a version of the electrical telegraph that he unsuccessfully demonstrated on September 2, 1837. His code was an important advance over Wheatstone's signaling method. The first transatlantic telegraph cable was successfully completed on July 27, 1866, allowing transatlantic telecommunication for the first time. After early attempts to develop a talking telegraph by Antonio Meucci and a telefon by Johann Philipp Reis, a patent for the conventional telephone was filed by Alexander Bell in February 1876 (just a few hours before Elisha Gray filed a patent caveat for a similar device). The first commercial telephone services were set up by the Bell Telephone Company in 1878 and 1879 on both sides of the Atlantic in the cities of New Haven and London. === Radio and television === In 1894, Italian inventor Guglielmo Marconi began developing wireless communication using the then-newly discovered phenomenon of radio waves, demonstrating, by 1901, that they could be transmitted across the Atlantic Ocean. This was the start of wireless telegraphy by radio. On 17 December 1902, a transmission from the Marconi station in Glace Bay, Nova Scotia, Canada, became the world's first radio message to cross the Atlantic from North America. In 1904, a commercial service was established to transmit nightly news summaries to subscribing ships, which incorporated them into their onboard newspapers. World War I accelerated the development of radio for military communications. After the war, commercial radio AM broadcasting began in the 1920s and became an important mass medium for entertainment and news. World War II again accelerated the development of radio for the wartime purposes of aircraft and land communication, radio navigation, and radar. Development of stereo FM broadcasting of radio began in the 1930s in the United States and the 1940s in the United Kingdom, displacing AM as the dominant commercial standard in the 1970s. On March 25, 1925, John Logie Baird demonstrated the transmission of moving pictures at the London department store Selfridges. Baird's device relied upon the Nipkow disk by Paul Nipkow and thus became known as the mechanical television. It formed the basis of experimental broadcasts done by the British Broadcasting Corporation beginning on 30 September 1929. === Vacuum tubes === Vacuum tubes use thermionic emission of electrons from a heated cathode for a number of fundamental electronic functions such as signal amplification and current rectification. The simplest vacuum tube, the diode invented in 1904 by John Ambrose Fleming, contains only a heated electron-emitting cathode and an anode. Electrons can only flow in one direction through the device—from the cathode to the anode. Adding one or more control grids within the tube enables the current between the cathode and anode to be controlled by the voltage on the grid or grids. These devices became a key component of electronic circuits for the first half of the 20th century and were crucial to the development of radio, television, radar, sound recording and reproduction, long-distance telephone networks, and analogue and early digital computers. While some applications had used earlier technologies such as the sp

    Read more →
  • Control communications

    Control communications

    In telecommunications, control communications is the branch of technology devoted to the design, development, and application of communications facilities used specifically for control purposes, such as for controlling (a) industrial processes, (b) movement of resources, (c) electric power generation, distribution, and utilization, (d) communications networks, and (e) transportation systems.

    Read more →
  • Example-based machine translation

    Example-based machine translation

    Example-based machine translation (EBMT) is a method of machine translation often characterized by its use of a bilingual corpus with parallel texts as its main knowledge base at run-time. It is essentially a translation by analogy and can be viewed as an implementation of a case-based reasoning approach to machine learning. == Translation by analogy == At the foundation of example-based machine translation is the idea of translation by analogy. When applied to the process of human translation, the idea that translation takes place by analogy is a rejection of the idea that people translate sentences by doing deep linguistic analysis. Instead, it is founded on the belief that people translate by first decomposing a sentence into certain phrases, then by translating these phrases, and finally by properly composing these fragments into one long sentence. Phrasal translations are translated by analogy to previous translations. The principle of translation by analogy is encoded to example-based machine translation through the example translations that are used to train such a system. Other approaches to machine translation, including statistical machine translation, also use bilingual corpora to learn the process of translation. == History == Example-based machine translation was first suggested by Makoto Nagao in 1984. He pointed out that it is especially adapted to translation between two totally different languages, such as English and Japanese. In this case, one sentence can be translated into several well-structured sentences in another language, therefore, it is no use to do the deep linguistic analysis characteristic of rule-based machine translation. == Example == Example-based machine translation systems are trained from bilingual parallel corpora containing sentence pairs like the example shown in the table above. Sentence pairs contain sentences in one language with their translations into another. The particular example shows an example of a minimal pair, meaning that the sentences vary by just one element. These sentences make it simple to learn translations of portions of a sentence. For example, an example-based machine translation system would learn three units of translation from the above example: How much is that X ? corresponds to Ano X wa ikura desu ka. red umbrella corresponds to akai kasa small camera corresponds to chiisai kamera Composing these units can be used to produce novel translations in the future. For example, if we have been trained using some text containing the sentences: President Kennedy was shot dead during the parade. and The convict escaped on July 15th., then we could translate the sentence The convict was shot dead during the parade. by substituting the appropriate parts of the sentences. == Phrasal verbs == Example-based machine translation is best suited for sub-language phenomena like phrasal verbs. Phrasal verbs have highly context-dependent meanings. They are common in English, where they comprise a verb followed by an adverb and/or a preposition, which are called the particle to the verb. Phrasal verbs produce specialized context-specific meanings that may not be derived from the meaning of the constituents. There is almost always an ambiguity during word-to-word translation from source to the target language. As an example, consider the phrasal verb "put on" and its Hindustani translation. It may be used in any of the following ways: Ram put on the lights. (Switched on) (Hindustani translation: Jalana) Ram put on a cap. (Wear) (Hindustani translation: Pahenna)

    Read more →
  • Directed-energy weapon wildfire conspiracy theories

    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.

    Read more →
  • Librem

    Librem

    Librem is a line of computers manufactured by Purism, SPC featuring free (libre) software. The laptop line is designed to protect privacy and freedom by omitting non-free (proprietary) software in their operating system and kernel, avoiding the Intel Active Management Technology, and gradually freeing and securing firmware. Librem laptops feature hardware kill switches for the microphone, webcam, Bluetooth and Wi-Fi. == Models == === Laptops === ==== Librem 13, Librem 15 and Librem 14 ==== In 2014, Purism launched a crowdfunding campaign on Crowd Supply to fund the creation and production of the Librem 15 laptop, conceived as a modern alternative to existing open-source hardware laptops, all of which used older hardware. The 15 in the name refers to its 15-inch screen size. The campaign succeeded after extending the original campaign, and the laptops were shipped to backers. In a second revision of the laptop, hardware kill switches for the camera, microphone, Wi-Fi, and Bluetooth were added. After the successful launch of the Librem 15, Purism created another campaign on Crowd Supply for a 13-inch laptop named Librem 13, which also came with hardware kill switches similar to those on the Librem 15v2. The campaign was again successful and the laptops were shipped to customers. Purism announced in December 2016 that it would start shipping from inventory rather than building to order with the new batches of Librem 15 and 13. As of January 2023, Purism has one laptop model in production, the Librem 14. ==== Comparison of laptops ==== === Librem Mini === The Librem Mini is a small form factor desktop computer, which began shipping in June 2020. === Librem 5 === On August 24, 2017, Purism began a crowdfunding campaign for the Librem 5, a smartphone aimed to run 100% free software, which would "[focus] on security by design and privacy protection by default". Purism claimed that the phone would become "the world's first ever IP-native mobile handset, using end-to-end encrypted decentralized communication." Purism cooperated with KDE and GNOME in its development of Librem 5. Security features of the Librem 5 include separation of the CPU from the baseband processor, which, according to Linux Magazine, makes the Librem 5 unique in comparison to other mobile phones. The Librem 5 also features hardware kill switches for Wi-Fi and Bluetooth communication and the phone's camera, microphone, and baseband processor. The default operating system for the Librem 5 is Purism's PureOS, a Debian derivative. The operating system uses a new user interface named Phosh, based on Wayland, wlroots, GTK and GNOME middleware. It is planned that Phosh/Plasma Mobile, Ubuntu Touch, and postmarketOS can also be installed on the phone. The release of the Librem 5 has been postponed several times. In September 2018, Purism announced that the launch date of Librem 5 would be moved from January to April 2019, because of two hardware bugs and the holiday season in Europe and North America. The Librem 5's DevKits for software developers were shipped in December 2018. The launch date was later postponed to the third quarter because of the necessity of further CPU tests. On September 24, 2019, Purism announced that the first batch of Librem 5 phones had begun shipping. The finished version of the Librem 5, known as "Evergreen", was finally shipped on November 18, 2020. === Librem Server === The Librem server is a rack mounted server, released to the public in December 2019. === Librem Key === Announced on 20 September 2018, the Librem Key is a hardware USB security token with multiple features, including integration with a tamper-evident Heads BIOS, which ensures that the Librem laptop Basic Input/Output System (BIOS) was not maliciously altered since the last laptop launch. The Librem Key also features one-time password storage with 3x HMAC-based One-time Password algorithm (HOTP) (RFC 4226) and 15 x Time-based One-time Password algorithm (TOTP) (RFC 6238) and an integrated password manager (16 entries), 40 kbit/s true random number generator, and a tamper-resistant smart card. The key supports type A USB 2.0, has dimensions of 48 x 19 x 7 mm, and weighs 6 g. == Operating system == Initially planning to preload its Librem laptops with the Trisquel operating system, Purism eventually moved off the Trisquel platform to Debian for the 2.0 release of its PureOS Linux operating system. As an alternative to PureOS, Librem laptops are purchasable with Qubes OS preinstalled. In December 2017, the Free Software Foundation added PureOS to its list of endorsed GNU/Linux distributions. == BIOS == In 2015, Purism began research to port the Librem 13 to coreboot but the effort was initially stalled. By the end of the year, a coreboot developer completed an initial port of the Librem 13 and submitted it for review. In December 2016, hardware enablement developer Youness Alaoui joined Purism and was tasked to complete the coreboot port for the original Librem 13 and prepare a port for the second revision of the device. Since summer 2017, new Librem laptops are shipped with coreboot as their standard BIOS, and updates are available for all older models. Purism calls a collection of these six components, involved in the boot process, as PureBoot: Neutralized and disabled Intel Management Engine coreboot A Trusted Platform Module (TPM) chip Heads, which has tamper-evident features to detect if the BIOS or important boot files have been modified Librem Key, Purism's USB security token Multi-factor authentication that unlocks disk encryption using the Librem Key PureBoot protects the users from various attacks like theft, BIOS malware and kernel rootkits, vulnerabilities and malicious code in the Intel Management Engine, and interdiction.

    Read more →
  • Institute of Telecommunications Professionals

    Institute of Telecommunications Professionals

    The Institute of Telecommunications Professionals (ITP) is a membership organisation for professionals in the telecommunications industry, based in the United Kingdom. The Institute was originally founded in 1906. It is now a registered company with Companies House in the United Kingdom, incorporated in 2002. Brendan O' Mahony has been the chief executive of the ITP. Lucy Woods presided over ITP for fifteen years, until 2018, when the organization named Kevin Paige chairman for five years. In 2022 the ITP appointed its new CEO, Charlotte Goodwill. In 2021, the ITP assisted a UK fibre network Vorboss in establishing its training academy. In 2023, the ITP appointed Tim Creswick, the CEO of Vorboss, as the new chair of its board of directors. The institute has an associated journal, the Journal of the Institute of Telecommunications Professionals, established in 2007 and published quarterly.

    Read more →
  • Managed private cloud

    Managed private cloud

    Managed private cloud (also known as "hosted private cloud" or "single-tenant SaaS") refers to a principle in software architecture where a single instance of the software runs on a server, serves a single client organization (tenant), and is managed by a third party. The third-party provider is responsible for providing the hardware for the server and also for preliminary maintenance. This is in contrast to multitenancy, where multiple client organizations share a single server, or an on-premises deployment, where the client organization hosts its software instance. Managed private clouds also fall under the larger umbrella of cloud computing. == Adoption == The need for private clouds arose due to enterprises requiring a dedicated service and infrastructure for their cloud computing needs, such as for business-critical operations, improved security, and better control over their resources. Managed private cloud adoption is a popular choice among organizations. It has been on the rise due to enterprises requiring a dedicated cloud environment and preferring to avoid having to deal with management, maintenance, or future upgrade costs for the associated infrastructure and services. Such operational costs are unavoidable in on-premises private cloud data centers. == Advantages and challenges of managed private cloud == A managed private cloud cuts down on upkeep costs by outsourcing infrastructure management and maintenance to the managed cloud provider. It is easier to integrate an organization's existing software, services, and applications into a dedicated cloud hosting infrastructure which can be customized to the client's needs instead of a public cloud platform, whose hardware or infrastructure/software platform cannot be individualized to each client. Customers who choose a managed private cloud deployment usually choose them because of their desire for efficient cloud deployment, but also have the need for service customization or integration only available in a single-tenant environment. This chart shows the key benefits of the different types of deployments, and shows the overlap between these cloud solutions. This chart shows key drawbacks. Since deployments are done in a single-tenant environment, it is usually cost-prohibitive for small and medium-sized businesses. While server upkeep and maintenance are handled by the service provider, including network management and security, the client is charged for all such services. It is up to the potential client to determine if a managed private cloud solution aligns with their business objectives and budget. While the service provider maintains the upkeep of servers, network, and platform infrastructure, sensitive data is typically not stored on managed private clouds as it may leave business-critical information prone to breaches via third-party attacks on the cloud service provider. Common customizations and integrations include: Active Directory Single Sign-on Learning Management Systems Video Teleconferencing == Deployment strategies and service providers == Software companies have taken a variety of strategies in the Managed Private Cloud realm. Some software organizations have provided managed private cloud options internally, such as Microsoft. Companies that offer an on-premises deployment option, by definition, enable third-party companies to market Managed Private Cloud solutions. A few managed private cloud service providers are: Adobe Connect: Adobe Connect may be purchased for on-premises deployment, multi-tenant hosted deployment, managed private cloud as ACMS, or managed by third-party managed private cloud provider ConnectSolutions. Rackspace CenturyLink Microsoft licenses for Lync, SharePoint and Exchange may be purchased for on-premises deployment, a multi-tenant hosted deployment via Office 365, or managed by third-party cloud hosting from Azaleos, ConnectSolutions and others.

    Read more →
  • Account verification

    Account verification

    Account verification is the process of verifying that a new or existing account is owned and operated by a specified real individual or organization. A number of websites, for example social media websites, offer account verification services. Verified accounts are often visually distinguished by check mark icons or badges next to the names of individuals or organizations. Account verification can enhance the quality of online services, mitigating sockpuppetry, bots, trolling, spam, vandalism, fake news, disinformation and election interference. == History == Account verification was introduced by Twitter in June 2009, initially as a feature for public figures and accounts of interest, individuals in "music, acting, fashion, government, politics, religion, journalism, media, sports, business and other key interest areas". A similar verification system was adopted by Google+ in 2011, Facebook page in October 2015 (Available in United States, Canada, United Kingdom, Australia and New Zealand) Facebook profile and Facebook page in 2018 (Available in Worldwide) Instagram in 2014, and Pinterest in 2015. On YouTube, users are able to submit a request for a verification badge once they obtain 100,000 or more subscribers. It also has an "official artist" badge for musicians and bands. In July 2016, Twitter announced that, beyond public figures, any individual would be able to apply for account verification. This was temporarily suspended in February 2018, following a backlash over the verification of one of the organisers of the far-right Unite the Right rally due to a perception that verification conveys "credibility" or "importance". In March 2018, during a live-stream on Periscope, Jack Dorsey, co-founder and CEO of Twitter, discussed the idea of allowing any individual to get a verified account. Twitter reopened account verification applications in May 2021 after revamping their account verification criteria. This time offering notability criteria for the account categories of government, companies, brands, and organizations, news organizations and journalists, entertainment, sports and activists, organizers, and other influential individuals. Instagram began allowing users to request verification in August 2018. In April 2018, Mark Zuckerberg, co-founder and CEO of Facebook, announced that purchasers of political or issue-based advertisements would be required to verify their identities and locations. He also indicated that Facebook would require individuals who manage large pages to be verified. In May 2018, Kent Walker, senior vice president of Google, announced that, in the United States, purchasers of political-leaning advertisements would need to verify their identities. In November 2022, Elon Musk included a blue verification check mark with a paid Twitter Blue monthly membership. Prior to Musk's acquisition of Twitter, Twitter offered this check mark at no charge to confirmed high profile users. On December 19, 2022, Twitter introduced two new check mark colors: gold for accounts from official businesses and organizations, and grey for accounts from governments or multilateral organizations. The type of check mark can be confirmed by visiting the profile page, then clicking or tapping on the check mark. == Techniques == === Identity verification services === Identity verification services are third-party solutions which can be used to ensure that a person provides information which is associated with the identity of a real person. Such services may verify the authenticity of identity documents such as drivers licenses or passports, called documentary verification, or may verify identity information against authoritative sources such as credit bureaus or government data, called nondocumentary verification. === Identity documents verification === The uploading of scanned or photographed identity documents is a practice in use, for example, at Facebook. According to Facebook, there are two reasons that a person would be asked to send a scan of or photograph of an ID to Facebook: to show account ownership and to confirm their name. In January 2018, Facebook purchased Confirm.io, a startup that was advancing technologies to verify the authenticity of identification documentation. === Biometric verification === === Behavioral verification === Behavioral verification is the computer-aided and automated detection and analysis of behaviors and patterns of behavior to verify accounts. Behaviors to detect include those of sockpuppets, bots, cyborgs, trolls, spammers, vandals, and sources and spreaders of fake news, disinformation and election interference. Behavioral verification processes can flag accounts as suspicious, exclude accounts from suspicion, or offer corroborating evidence for processes of account verification. === Bank account verification === Identity verification is required to establish bank accounts and other financial accounts in many jurisdictions. Verifying identity in the financial sector is often required by regulation such as Know Your Customer or Customer Identification Program. Accordingly, bank accounts can be of use as corroborating evidence when performing account verification. Bank account information can be provided when creating or verifying an account or when making a purchase. === Postal address verification === Postal address information can be provided when creating or verifying an account or when making and subsequently shipping a purchase. A hyperlink or code can be sent to a user by mail, recipients entering it on a website verifying their postal address. === Telephone number verification === A telephone number can be provided when creating or verifying an account or added to an account to obtain a set of features. During the process of verifying a telephone number, a confirmation code is sent to a phone number specified by a user, for example in an SMS message sent to a mobile phone. As the user receives the code sent, they can enter it on the website to confirm their receipt. === Email verification === An email account is often required to create an account. During this process, a confirmation hyperlink is sent in an email message to an email address specified by a person. The email recipient is instructed in the email message to navigate to the provided confirmation hyperlink if and only if they are the person creating an account. The act of navigating to the hyperlink confirms receipt of the email by the person. The added value of an email account for purposes of account verification depends upon the process of account verification performed by the specific email service provider. === Multi-factor verification === Multi-factor account verification is account verification which simultaneously utilizes a number of techniques. === Multi-party verification === The processes of account verification utilized by multiple service providers can corroborate one another. OpenID Connect includes a user information protocol which can be used to link multiple accounts, corroborating user information. == Account verification and good standing == On some services, account verification is synonymous with good standing. Twitter reserves the right to remove account verification from users' accounts at any time without notice. Reasons for removal may reflect behaviors on and off Twitter and include: promoting hate and/or violence against, or directly attacking or threatening other people on the basis of race, ethnicity, national origin, sexual orientation, gender, gender identity, religious affiliation, age, disability, or disease; supporting organizations or individuals that promote the above; inciting or engaging in the harassment of others; violence and dangerous behavior; directly or indirectly threatening or encouraging any form of physical violence against an individual or any group of people, including threatening or promoting terrorism; violent, gruesome, shocking, or disturbing imagery; self-harm, suicide; and engaging in other activity on Twitter that violates the Twitter Rules. In April 2023, Blue ticks were removed from all Twitter accounts that had not subscribed to Twitter Blue.

    Read more →
  • Texas House Bill 20

    Texas House Bill 20

    An Act Relating to censorship of or certain other interference with digital expression, including expression on social media platforms or through electronic mail messages, also known as Texas House Bill 20 (HB20), is a Texas anti-deplatforming law enacted on September 9, 2021. It prohibits large social media platforms from removing, moderating, or labeling posts made by users in the state of Texas based on their "viewpoints", unless considered illegal under federal law or otherwise falling into exempted categories. It also requires them to make various public disclosures relating to their business practices (including the impact of algorithmic and moderation decisions on the content that is delivered to users). The bill is part of a wider array of Republican-backed legislation seeking to prohibit the censorship of political speech, based on allegations that the moderation policies of large social media platforms are not politically neutral. It has been challenged in NetChoice, LLC v. Paxton, and is currently the subject of a circuit split between the Fifth Circuit, and a decision by the Eleventh Circuit that struck down a similar bill in the state of Florida. In September 2023, the U.S. Supreme Court agreed to hear NetChoice v. Paxton jointly with NetChoice v. Moody on questions of whether the Florida and Texas state laws are in compliance with the 1st Amendment. == Content == The law applies to "social media platforms" that serve users in the state of Texas, and have more than 50 million monthly active users in the United States. They are defined as any public internet website or application that allows users to "communicate with other users for the primary purpose of posting information, comments, messages, or images", excluding internet service providers, electronic mail, and services where communication features are "incidental to, directly related to, or dependent on" content that is pre-selected by the operator. In the bill, to "censor" is defined as to "block, ban, remove, deplatform, demonetize, de-boost, restrict, deny equal access or visibility to, or otherwise discriminate against" expression. The law prohibits social media platforms from "censoring on the basis of user viewpoint, user expression, or the ability of a user to receive the expression of others", or on the basis of a user's geographic location in Texas. This includes removal or labeling posts with warnings and disclaimers. Social media platforms may only censor content if it is unlawful, they are "specifically authorized" to do so by federal law, based on requests from "an organization with the purpose of preventing the sexual exploitation of children or protecting survivors of sexual abuse from ongoing harassment", or "directly incites" criminal activity or contains threats of violence against persons based on protected categories. It is disputed over whether this provision is actually enforceable, as it may be preempted by Section 230 of the Communications Decency Act (which states that the operators of interactive computer services are not responsible for the actions of their users). Social media platforms must make public disclosures regarding the algorithmic techniques and moderation polices that are used to determine the content provided to users, must publish a compliant acceptable use policy (AUP), and must publish a biannual transparency report containing specific details on all actions made by the service regarding the moderation of users and content. The law also prohibits email providers from "intentionally imped[ing] the transmission of another person's electronic mail message based on the content." == Legislative history == Texas Governor Greg Abbott signed the bill into law on September 9, 2021. Democrat-proposed amendments excluding Holocaust denial, terrorism content, and vaccine misinformation from the bill were rejected. Following a suit by the industry groups Computer & Communications Industry Association (CCIA) and NetChoice, NetChoice, LLC v. Paxton, the bill was blocked by U.S. District Judge Robert Pitman in December 2021, on First Amendment grounds. Texas appealed to the United States Court of Appeals for the Fifth Circuit. Judges Edith Jones, Andrew Oldham, and Leslie H. Southwick, lifted the injunction on May 11, 2022, but the decision was appealed to the Supreme Court which suspended the bill pending a full review in the Fifth Circuit. On September 16, 2022, the Fifth Circuit reversed the injunction, allowing the bill to take effect; Judge Oldham stated that the bill "chills censorship" and "does not chill speech", and accused the plaintiffs of "attempt[ing] to extract a freewheeling censorship right from the Constitution's free speech guarantee. The Platforms are not newspapers. Their censorship is not speech." Southwick dissented, stating that "we are in a new arena, a very extensive one, for speakers and for those who would moderate their speech. None of the precedents fit seamlessly." The CCIA and NetChoice requested a stay on the ruling and that the case be taken to the Supreme Court, arguing that the reversal conflicts with an Eleventh Circuit decision in NetChoice v. Moody which struck down a similar anti-moderation bill imposed by the state of Florida. On October 12, 2022, the Fifth Circuit granted the stay.

    Read more →