AI App Just Like Chatgpt

AI App Just Like Chatgpt — independent reviews, comparisons, pricing and step-by-step guides on Aizhi.

Event store

An event store is a type of database optimized for storage of events. Conceptually, an event store records only the events affecting an entity, dossier, or policy, and the state of the entity at any point in its history can be reconstructed by replaying its contributing events in sequential order. Events (and their corresponding data) are the only "real" facts that should be stored in the database. All other objects can be derived from these events, meaning they are instantiated in memory by runtime code as needed (e.g. for showing in a user interface). In theory, any object that aggregates over recorded event data is not stored in the database. Instead these objects are built 'on the fly', by traversing the event history. When the aggregated object instance is no longer needed, it can simply be discarded (released from memory). == Example with insurance policies == For example, the event store concept of a database can be applied to insurance policies or pension dossiers. In these policies or dossiers the instantiation of each object that make up the dossier or policy (the person, partner(s), employments, etc.) can be derived and can be instantiated in memory based on the real world events. == Double timeline == A crucial part of an event store database is that each event has a double timeline: This enables event stores to correct errors of events that have been entered into the event store database before. The two dates are: Valid date is the date at which the event has become valid. Transaction date is the date at which the event is entered into the database. == Error correction == Another crucial part of an event store database is that events that are stored are not allowed to be changed. Once stored, also erroneous events are not changed anymore. The only way to change (or better: correct) these events is to instantiate a new event with the new values and using the double timeline. A correcting event would have the new values of the original event, with an event data of that corrected event, but a different transaction date. This mechanism ensures reproducibility at each moment in the time, even in the time period before the correction has taken place. It also allows to reproduce situations based on erroneous events (if required). == Advantages and disadvantages == One advantage of the event store concept is that handling the effects of back dated events (events that take effect before previous events and that may even invalidate them) is much easier. An event store will simplify the code in that rolling back erroneous situations and rolling up the new, correct situations is not needed anymore. Disadvantage may be that the code needs to re-instantiate all objects in memory based on the events each time a service call is received for a specific dossier or policy. == Compared to regular databases == In regular databases, handling backdated events to correct previous, erroneous events can be painful as it often results in rolling back all previous, erroneous transactions and objects and rolling up the new, correct transactions and objects. In an event store, only the new event (and its corresponding facts) are stored. The code will then redetermine the transactions and objects based on the new facts in memory.
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Cringe culture

Cringe culture () is an Internet phenomenon and neologism characterized by the mockery and ridicule of content, behaviors, or expressions deemed embarrassing or awkward. The term cringe evolved semantically from describing personal secondhand embarrassment to becoming a dismissive label applied to various forms of online expression and fan behavior. The phenomenon emerged in the early 2000s as a response to awkward online content but gradually transformed into a cultural force that impacted fan communities, creative expression, and social media behavior. Cringe culture gained particular prominence through online platforms like Reddit and 4chan, and has been observed to cause the decline of various fandoms when they become labeled as cringe. Cringe culture has extended beyond Internet communities into academic and professional settings. Educators have noticed increased self-consciousness among students about displaying effort in their work (known as tryharding). By the early 2020s, a cultural pushback against cringe culture began to emerge, with public figures and celebrities advocating for authentic self-expression and rejecting the fear of being perceived as "trying too hard". == Origin == The term cringe underwent semantic change from its original usage describing an involuntary physical response, then to embarrassment. The term gained popularity in online forums during the early 2000s, when public self-humiliation online was a relatively novel phenomenon. Early cringe culture drew much of its content from YouTube. According to Kaitlyn Tiffany of The Atlantic, the majority of cringe stemmed from people who did not seem to understand that anyone in the world could see their videos. The phenomenon initially focused on empathy and secondhand embarrassment, with viewers relating to the awkward situations they witnessed. Popular early examples of cringe include the 2002 viral video Star Wars Kid and "My Video for Briona for Our 7 Month", in which a man winks, licks his lips, and makes romantic declarations to his partner. Early cringe culture encompassed multiple styles, including self-deprecating, playful, and hostile forms. On /b/ (4chan's "random" board), early cringe discussions targeted groups like Tumblr users, social justice warriors, fangirls, and furries, while also being used to describe "normies" who lacked sufficient knowledge of Internet culture to understand its ironic humor. In July 2012, Reddit user Michael Dombkowski took over the dormant r/cringe subreddit after watching a KENS5 segment about teen werewolves. Dombkowski created RSS feeds to alert him whenever someone mentioned cringe anywhere on Reddit, then encouraged users to visit his subreddit. The subreddit collected 10,000 monthly pageviews in its first month, which grew to 941,000 by September 2012 and 5 million the following month. According to The Daily Dot, Dombkowski had intended the subreddit to elicit empathy from viewers rather than to mock its subjects. On November 9, 2012, Dombkowski banned all images from r/cringe and created r/cringepics as a spinoff subreddit for image-based content. The community initially opposed this decision, as users worried that it would fragment the community. In a few months, r/cringepics overtook r/cringe in traffic and subscribers. By 2014, the combined subreddits amassed over 500,000 subscribers and more than 30 million monthly pageviews. In a March 2013 company AMA ("Ask Me Anything"), Reddit's general manager Erik Martin stated that he hates "r/cringepics and anything cringe related and the whole idea." == Impact == Cringe culture has impacted various fandoms. Screen Rant dubbed the phenomenon in which a fandom abruptly dissipates when suddenly deemed cringe (due to the actions of individuals within the fandom or the fandom being re-evaluated as a whole) as the "My Hero Academia Effect". My Hero Academia initially enjoyed popularity in 2020 during the COVID-19 pandemic, but the resurfacing of embarrassing TikTok videos of convention-goers in 2020 caused the My Hero Academia fandom to be deemed cringy, and thus was abandoned by many anime fans. Similarly, the fandom of the Homestuck webcomic, which ran from 2009 to 2016, faced scrutiny when cosplayers filled bathtubs with Sharpies to achieve gray skin coloring (emulating the design of the Homestuck characters), which led to property damage at hotels and convention bans. Many fans subsequently abandoned the fandom, and as a result, according to Screen Rant, the Homestuck fandom was almost non-existent by 2024. It is worth noting that as of September 27, 2025 animation studio SpindleHorse, also responsible for the popular animated show Hazbin Hotel (another common recipient of Cringe Culture discussion) has released a Homestuck animated pilot episode on YouTube. Other fandoms that were deemed cringy include the Stranger Things and Hazbin Hotel fandoms. Isobel Heal of Varsity described being "far too insecure as a teen to even consider listening to songs inspired by My Little Pony or Five Nights at Freddy's regardless of how catchy they were," but found that attending a Living Tombstone concert allowed her to overcome these inhibitions. She wrote that everyone in the crowd was "completely unafraid to engage in the silliness of the entire night," which allowed her to "let my guard down and enjoy the evening without fear of feeling 'cringe.'" Heal described her experience of singing along to tracks like "Discord", a My Little Pony–themed song, provided what she described as healing "the wounds of the younger me" and represented a form of reclaiming interests that had been suppressed due to social pressure and bullying. == Reactions == New York University professor Ocean Vuong observed that students increasingly hesitate to reveal effort behind their creative work. Vuong stated that students often say "I want to be a good writer, but it's a bit cringe" and perform cynicism because it can be misread as intelligence. In May 2022, Taylor Swift addressed cringe culture in her commencement speech at New York University: she advised graduates to "learn to live alongside cringe" and that "cringe is unavoidable over a lifetime." Other celebrities have made public speeches fighting against the perceived notion that "tryharding" is cringe. In his 31st Screen Actors Guild Awards acceptance speech, Timothée Chalamet emphasized his pursuit of greatness and the effort he invested in his roles, which diverged from typical humble acceptance speeches. In her 67th Annual Grammy Awards acceptance speech, rapper Doechii also stressed her dedication and hard work. According to The Daily Dot, X users called Chalamet and Doechii's speeches "refreshing" and decried those who embrace cringe culture as "miserable losers". In 2023, Critical Role dungeon master Matthew Mercer spoke against cringe culture at New York Comic Con: "We live in an odd time of 'cringe culture' where anything that's honest can be called cringe. And I don't agree with that." Mercer argued that much of what is dismissed as cringe consists of "people being their authentic self." In October 2025, actress and singer Ariana Grande discussed her experience with cringe culture in an interview on the podcast Shut Up Evan. She described the phenomenon as "unfair", stating that people should be allowed to express passion and happiness without judgement. She further explained that in the wake of her leading role in the 2024 film Wicked there were those who perceived the behavior of her and costar Cynthia Erivo during the film's press tour as "inauthentic" and therefore cringe. == Analysis == In 2021, Steven Dashiell wrote in the journal Studies in Popular Culture that cringe culture functions as a mechanism for social boundaries within the My Little Pony: Friendship Is Magic fandom, and that cringe culture operates not only between different communities but also within fandoms themselves. In his analysis, Dashiell examined a Reddit thread where a brony (an adult fan of My Little Pony: Friendship Is Magic) expressed embarrassment about other bronies. The thread received over 400 comments in which participants engaged in what Dashiell termed other-izing: distancing themselves from behaviors they deemed cringeworthy. Rather than defending the criticized bronies, commenters consistently used the term cringe to describe their reactions to certain fan behaviors while distinguishing themselves from the so-called "deviant brony" to normalize their own participation in the fandom. A February 2024 Hinge report revealed that more than half of Generation Z worries about cringe while dating and are 50 percent more likely than millennials to delay responding to avoid seeming overeager.
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CSS HTML Validator

CSS HTML Validator (previously named CSE HTML Validator) is an HTML editor and CSS editor for Microsoft Windows (and Linux and other Unix-like operating systems when used with Wine) that helps web developers create syntactically correct and accessible HTML/HTML5, XHTML, and CSS documents by locating errors, potential problems like browser compatibility issues, and common mistakes. It is also able to check links, check spelling, suggest improvements, alert developers to deprecated, obsolete, or proprietary tags, attributes, and CSS properties, and find issues that can affect search engine optimization. CSS HTML Validator is developed, marketed, and sold by AI Internet Solutions LLC located in the United States. The first version of CSS HTML Validator was released in 1997 for Windows 95. The current version is 2026/v26.02 (as of January 9, 2026) and is for Windows 10 and above, including Windows 11. A native macOS and Linux command-line console tool (called htmlval) became available with version 23. There are currently three main editions of CSS HTML Validator — Pro/Professional, Home/Standard, and Lite. The Enterprise edition was discontinued in 2025/v25. While the application is generally a commercial product (except for the Lite edition), a free version of the Home edition is available for personal/educational, non-commercial use. A free limited version of the htmlval command-line console tool for macOS and Linux is also available. == Features == CSS HTML Validator includes an HTML editor, validator for HTML, XHTML, htmx, polyglot markup, CSS, PHP and JavaScript (using JSLint or JSHint), link checker (to find dead and broken links), spell checker, accessibility checker, and search engine optimization (SEO) checker. An integrated web browser allows developers to browse the web while the pages are automatically validated. Because documents are checked locally and not uploaded over the Internet to a server in order to be checked, validations are performed relatively quickly, and security and privacy are increased. A custom scripting language called TNPL, included in the Pro and Enterprise editions, can be used to customize validations by adding, eliminating, or changing validator messages. TNPL can also be used to integrate customized validation checks to meet the unique requirements of an individual or entity. A Batch Wizard tool, included in the Pro and Enterprise editions, can check entire Web sites, parts of Web sites, or a list of local web documents. The Batch Wizard generates reports in standard HTML or XML format. The reports can be viewed using a normal web browser. The accessibility checker includes support for Section 508 Amendment to the Rehabilitation Act of 1973 and Web Content Accessibility Guidelines (both WCAG 1.0 and WCAG 2.0/2.1/2.2). Using a version of HTML Tidy with HTML5 support and the Pretty Print & Fix Tool, CSS HTML Validator can automatically fix some common problems with HTML and XHTML documents. However, some problems cannot be fixed (or fixed correctly) with automated tools and require manual review and repair. == Version history == Validation of polyglot markup was added in version 12, and mobile development support (for HTML and CSS) was added in version 14 and improved in version 15. Version 15 added built-in syntax checking for JSON and HTML5 cache manifest files. Version 16 added JavaScript linting using JSHint, a static code analysis tool for checking JavaScript, but also continues to support JSLint. Version 17 added support for the Accelerated Mobile Pages Project, which is a type of HTML optimized for mobile web browsing, and support for live DOM validation using Google Chrome CSS HTML Validator 2018/v18 renames the software from CSE HTML Validator to CSS HTML Validator and includes updated HTML5 and CSS support. Version 18 also added a new "By Message" report in the Batch Wizard and dropped support for Windows Vista and below. CSS HTML Validator 2019/v19 includes updated HTML and CSS support, adds WCAG 2.1 support, improves support when running under Wine (software), and is a native 64-bit application (previously releases were 32-bit). CSS HTML Validator 2020/v20, first released in January 2020, includes HTML, CSS, accessibility, and other updates, including improved support for the Accelerated Mobile Pages Project. Also, beginning with version 20, the Standard edition was renamed to the Home edition. CSS HTML Validator 2021/v21, first released in January 2021, includes further HTML, CSS, accessibility, and other updates. CSS HTML Validator 2022/v22, released in January 2022, includes improvements and updates to keep the program up-to-date, a new Microsoft Edge WebView2 rendering engine for the integrated web browser, and three new dark themes. Later updates to version 22 added support for checking JSON Lines and NDJSON documents. CSS HTML Validator 2023/v23, released in January 2023, includes more improvements and updates to keep the program up-to-date. The new release also introduced new command-line macOS and Linux ports of the core validation engine, called htmlval for Mac and Linux. Official support for Windows 7, 8, and 8.1 was dropped in the 2023/v23 version. CSS HTML Validator 2024/v24, released in January 2024, includes updates and improvements. It also adds support for htmx. CSS HTML Validator 2025/v25, released in December 2024, includes further updates and improvements for 2025. Version 25 discontinues the Enterprise edition, moving Enterprise functionality to the Pro edition. CSS HTML Validator 2026/v26, released in January 2026, includes updated support for HTML and CSS. An online edition based on CSS HTML Validator Pro that can check documents via file upload, URL, or snippets (direct text input) was discontinued May 2017 in favor of the desktop version for Microsoft Windows. == Purpose of validation == The purpose of validation and computerized checking of HTML, XHTML, and CSS documents is to help make sure that the documents are syntactically correct and problem-free. Checked HTML, XHTML, and CSS documents are more likely to: be more accessible for people with disabilities (such as blindness), as well as all users in general render faster (user agents don't have to "figure out" and decipher bad syntax) render as intended and with fewer problems on a variety of user agents, including mobile devices cause browsers and user agents to build a more consistent Document Object Model, which is important for CSS and JavaScript be forward-compatible with future versions of user agents and browsers ("future-proof") be compatible with current and future HTML, XHTML, and CSS specifications cause fewer problems for visitors and web indexing not contain dead, broken, or rotting links While automated checking tools are helpful for website development and continued maintenance, they cannot guarantee that a document will display (render) and behave as intended in all browsers. Developers should always test documents in a variety of browsers (including mobile browsers) to locate problems that cannot be detected with a computerized checking tool. == Differences from other HTML validators == CSS HTML Validator is an offline desktop app for Microsoft Windows and a native macOS and Linux command-line console tool that does not require an Internet connection. The offline nature of CSS HTML Validator is in contrast to online web-based services. CSS HTML Validator primarily works offline (except for link checking when it must go online), which has speed and privacy benefits compared to web-based solutions and services like the W3C Markup Validation Service. However, the user must keep the software updated unlike web-based solutions which are typically kept updated by the solution provider. CSS HTML Validator checks HTML/XHTML syntax, CSS, links, spelling, accessibility, JavaScript, SEO, and PHP with one pass, while DTD-based validators are more limited and cannot check HTML5. CSS HTML Validator includes a built-in scripting language (called TNPL) which allows for a high degree of customization via scripting and "user functions". This allows developers to add custom (specialized) validation checks and messages. CSS HTML Validator includes a DTD-based validator which can optionally be used for checking DTD-based versions of HTML (versions prior to HTML5), however one of CSS HTML Validator's primary differences is that its custom validation engine can perform more checks on a document than a DTD-based validator can. This is because DTD-based validators are limited to checking only what can be specified in a Document Type Definition. == Integration == CSS HTML Validator integrates with other third-party software like those listed below. This allows validation using CSS HTML Validator from within the third-party program. EmEditor - includes a special Lite edition build of CSS HTML Validator for built-in checking of HTML and CSS Blumentals Software - several Blumentals software products integrate with CSS H
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Creative work

A creative work is a manifestation of creative effort in the world through a creative process involving one or more individuals. The term includes fine artwork (sculpture, paintings, drawing, sketching, performance art), dance, writing (literature), filmmaking, and musical composition. The term is frequently used in the context of copyright. It is an important concept in both philosophy and law. Creative works require a creative mindset and are not typically rendered in an arbitrary fashion, although works may demonstrate (i.e., have in common) a degree of arbitrariness, such that it is improbable that two people would independently create the same work. At its base, creative work involves two main steps – having an idea, and then turning that idea into a substantive form or process. Typically, the creative process results in work that has some aesthetic value, identified as a creative expression. Naturally, this expression generally invokes external stimuli (e.g., influences and experiences) which a person draws on because they view the source as creative or inspirational; the degree to which this is reflected may be used in determinations of the derivativeness of the created work. Alternatively, the creator may draw on imagination, and their references may be clouded even to them, for the nature of imagination is as yet not fully understood philosophically, and the level of necessary self-examination of an artist's internal processing is a challenge for even those most self-aware of their minds and mental processes. == Legal definition == === United Kingdom === For the purpose of section 221(2)(c) of the Income Tax (Trading and Other Income) Act 2005, the expression "creative works" means: (a) literary, dramatic, musical or artistic works, or (b) designs,created by the taxpayer personally or, if the qualifying trade, profession or vocation is carried on in partnership, by one or more of the partners personally.
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Oculus Quill

Quill is a painting and animation software for virtual reality. It runs on Microsoft Windows with Oculus Rift headsets. It is used to create 3D paintings and animated cartoons. Quill was released on November 29, 2016, on the Oculus Store. Theater Elsewhere(formerly Quill Theater), an application for viewing creations made in Quill, was later made available following the release of the Oculus Quest. In September 2021, Facebook, now known as Meta Platforms, and the owner of Oculus, sold Quill to its original creator, who continues to develop and support the app. == Development == Quill was originally developed by Oculus Story Studio as an internal tool for the creative needs of the studio's project Dear Angelica directed by Saschka Unseld along with its art-director Wesley Allsbrook. == Controls == The software works on Oculus Rift utilizing its 6DoF motion controllers. Users can paint in 3D space using their hands naturally, and animate those paintings with keyframes. They can also capture videos and photos of their creations. == Reception == Dear Angelica, a VR story fully painted in Quill, was nominated for an Emmy Award in 2017.
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Enterprise social software

Enterprise social software (also known as or regarded as a major component of Enterprise 2.0), comprises social software as used in "enterprise" (business/commercial) contexts. It includes social and networked modifications to corporate intranets and other classic software platforms used by large companies to organize their communication. In contrast to traditional enterprise software, which imposes structure prior to use, enterprise social software tends to encourage use prior to providing structure. Carl Frappaolo and Dan Keldsen defined Enterprise 2.0 in a report written for Association for Information and Image Management (AIIM) as "a system of web-based technologies that provide rapid and agile collaboration, information sharing, emergence and integration capabilities in the extended enterprise". == Applications == === Functionality === Social software for an enterprise must (according to Andrew McAfee, Associate Professor, Harvard Business School) have the following functionality to work well: Search: allowing users to search for other users or content Links: grouping similar users or content together Authoring: including blogs and wikis Tags: allowing users to tag content Extensions: recommendations of users; or content based on profile Signals: allowing people to subscribe to users or content with RSS feeds McAfee recommends installing easy-to-use software which does not impose any rigid structure on users. He envisages an informal roll-out, but on a common platform to enable future collaboration between areas. He also recommends strong and visible managerial support to achieve this. In 2007 Dion Hinchcliffe expanded the list above by adding the following four functions: Freeform function: no barriers to authorship (meaning free from a learning curve or from restrictions) Network-oriented function, requiring web-addressable content in all cases Social function: stressing transparency (to access), diversity (in content and community members) and openness (to structure) Emergence function: requiring the provision of approaches that detect and leverage the collective wisdom of the community Enterprise search differs from a typical web search in its focus on "use within an organization by employees seeking information held internally, in a variety of formats and locations, including databases, document management systems, and other repositories". === Criticism === There has been recent criticism that the adaptation of the social paradigm (e.g. openness and altruistic behavior) does not always work well for the enterprise setting, which led some authors to question the proper functioning of enterprise social software. The findings from a novel study suggests that free and non-anonymous sharing of trusted information (beyond marketing or product information) is significantly influenced by concerns from business users.
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Hype (marketing)

Hype in marketing is a strategy of using extreme publicity. Hype as a modern marketing strategy is closely associated with social media. Marketing through hype often uses artificial scarcity to induce demand. Consumers of hyped products often participate as a form of conspicuous consumption to signify characteristics about themselves. Hype allows brands to promote their image above the actual quality of the product. Streetwear brands have collaborated with luxury fashion to justify charging premium prices for their goods. As an example, fashion label Vetements used social media channels to promote a limited-edition hoodie which sold 500 units in hours, recording sales of €445,000. When hype marketing is used to drive demand for limited-edition goods, consumers sometimes attempt resell those good on secondary markets for a profit (comparable to ticket scalping). The resale market is a $24 billion industry. == Method == Luxury brands may release products as a collaborate with ready-made garment brands as a way to build hype. Collaborations have been used by some luxury brands to circumvent fast fashion brands copying their designs. NYU Professor Adam Alter says that for an established brand to create a scarcity frenzy, they need to release a limited number of different products, frequently. Hype is often built via Pop-up retail. Comme des Garçons was one of the first to use this strategy, leasing a short-term vacant shop solved the storage problems of releasing product for quick sale. Hype campaigns also rely on influencer marketing, where brands enlist creators whose parasocial relationships with their followers help convert audience attention into demand for limited releases. == In popular culture == The term 'hypebeast' has been coined to define consumers vulnerable to hype marketing. The origins of the term come from the Hong Kong-based company Hypebeast. The behaviours of the hypebeast define hype marketing; the purchase of popular goods they can't afford to impress others. Hype also manifests itself in queues with brands often retailing hyped products through pop-up stores. Many luxury brands release hyped products via their online shop. This has led to the creation of companies that allow consumers to use bots to guarantee or improve their chances of purchasing a limited-edition product.
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Frictionless sharing

Frictionless sharing refers to the transparent or automatic dissemination of user activity across social media platforms, typically without requiring explicit action from the user each time content is shared. The concept gained prominence in 2011 after Mark Zuckerberg announced a series of new features for Facebook at the F8 developers conference, framing the changes as enabling “real-time serendipity in a friction-less experience.” == History and concept == Before 2011, the term “frictionless sharing” was occasionally used in academic and technical contexts to describe sharing of resources with minimal effort, such as through social bookmarking or Creative Commons licensing to reduce barriers to reuse of research data. The concept took on a broader cultural meaning when Facebook introduced its Timeline interface and new “social apps” in 2011. These features enabled third-party applications to automatically publish user activity to the platform—effectively shifting sharing from a deliberate act to a passive process. For example, integrating music streaming service Spotify meant that any song a user listened to could automatically appear in a Facebook “Ticker,” allowing friends to see the activity and click through to play the song themselves. == Zuckerberg’s vision == Zuckerberg articulated a vision of a Web in which sharing occurs by default rather than by choice: “You read, you watch, you listen, you buy—and everyone you know will hear all about it on Facebook.” This “frictionless” model assumes ongoing consent after an initial opt-in. Once users connect an app to their profile, any future activity with that app may be automatically shared. This shift from intentional posting to ambient sharing represented a significant evolution in how personal data is distributed online. == Criticism and debate == Many commentators and users have raised concerns about frictionless sharing. While some criticism centers on online privacy, others focus on how automatic updates can flood news feeds and erode the social value of sharing. Critics argue that when sharing becomes automatic, it dilutes the personal curation that makes social media exchanges meaningful. According to Slate, this approach risks “killing taste,” because users typically choose to share only select content they find worth highlighting, rather than everything they consume. AL.com similarly observed that the frictionless model encourages over-sharing, overwhelming both users and their networks with minor or trivial activities. For example, integrating multiple platforms—such as Twitter, Foursquare, Pinterest, Spotify, and others—can create an incessant stream of updates that some users may find intrusive or irritating. This can lead to what critics describe as “narcissistic” or noisy timelines, potentially undermining the “social” nature of social media. == Business model and data implications == For Facebook, frictionless sharing offers clear business advantages. More frequent and detailed sharing provides valuable data that can be used to refine targeted advertising and personalize content delivery. The model also encourages users to spend more time on the platform, reinforcing its position as a central hub of online social activity. Other technology companies have experimented with similar approaches. Google has introduced forms of cross-platform integration that facilitate automatic activity sharing, though with a more explicit opt-in structure compared to Facebook. This approach has been described as “friction with consent,” allowing users to manually enable or disable integrations on a per-service basis.
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Vegas Pro

Vegas Pro (formerly known as Sony Vegas) is a professional video editing software package for non-linear editing (NLE), designed to run on the Microsoft Windows operating system. The first release of Vegas Beta was on June 11, 1999. Vegas was originally developed as a non-linear audio editing application. Version 2.0 would split the program into audio and video editing variants, with the former being dropped by version 4.0, making the video offering the only variant available to consumers. Vegas Pro features real-time multi-track video and audio editing on unlimited tracks, resolution-independent video sequencing, complex effects, compositing tools, 24-bit/192 kHz audio support, VST and DirectX plug-in effect support, and Dolby Digital surround sound mixing. The software was originally published by Sonic Foundry until May 2003, when Sony purchased Sonic Foundry and formed Sony Creative Software. On May 24, 2016, Sony announced that Vegas was sold to MAGIX, which formed VEGAS Creative Software, to continue support and development of the software. As of the end of March 2026, it was publicly announced that Boris FX had taken ownership of Vegas Pro. Each release of Vegas is sold standalone; however, upgrade discounts are sometimes provided. == Features == Vegas does not require any specialized hardware to run properly, allowing it to operate on any Windows computer that meets the system requirements. == History == Vegas 1.0 was released after a brief public beta by Sonic Foundry on July 23, 1999 at the NAMM Show in Nashville, Tennessee as an audio-only tool with a particular focus on re-scaling and resampling audio. It supported formats like DivX and Real Networks RealSystem G2 file formats. Martin Walker from Sound on Sound described working in Vegas 1.0 as a "very pleasurable experience, especially since so many functions are highly intuitive" though also criticizing some features as hard to figure out due to the lack of a central help file. Later, on June 12, 2000, Vegas Video and Audio 2.0 (also referred to as just Vegas 2.0) was released, with its beta releasing earlier that year on April 10. This was the first version of Vegas to include video-editing tools and was also the first to have a low-cost "LE" version alongside the regular release. The LE releases would continue through version 3.0 of Vegas but would be discontinued by the release of Vegas 4.0. Vegas 3.0 was released the next year on December 3, and added new video effects, features for ease-of-use with DV, and support for editing Windows Media files. Vegas 4.0 was released on 6 February 2003 and added application scripting, advanced color correction, 5.1 surround sound mixing, and Steinberg ASIO support. This was the last release under the Sonic Foundry name after it sold much of its software suite, including Sound Forge and Acid Pro, to Sony Pictures Digital for $18 million later in 2003. Under Sony's ownership, Vegas 5.0 was released on April 19, 2004, bringing 3D track motion, compositing, reversing, envelope automation, etc. 7.0 also added an improved video preview, enhanced layout management, improved snapping, and more customization. With the release of 8.0, Sony opted to go back to the original "Vegas Pro" branding that the first version released with. It added the ability to burn Blu-ray and DVD optical media, support for 32-bit floating point audio, support for tempo-based audio effects, and more. It also moved the timeline to the bottom of the window by default with the option of moving it back to the top if the user wished to. Sony was also experimenting with 64-bit at this time and ported Vegas Pro 8.0 to 64-bit systems under the name "Vegas Pro 8.1". Vegas Pro 9.0 added support for 4K resolution and pro camcorder formats like Red and XDCAM EX. In 2009, Sony Creative Software purchased the Velvetmatter Radiance suite of video FX plug-ins which were included in Sony Vegas Pro 9.0. As a result, they were no longer available as a separate product from Velvetmatter. Vegas Pro 10 was released in 2010 with stereoscopic 3D editing, image stabilization, OpenFX plugin support, real-time audio event effects, and a few UI changes. This was the last release to include support for Windows XP. Vegas Pro 11 was released the next year on 17 October, with GPGPU video acceleration, enhanced text tools, enhanced stereoscopic/3D features, RAW photo support, and new event synchronization mechanisms. In addition, Vegas Pro 11 comes pre-loaded with "NewBlue" Titler Pro, a 2D and 3D titling plug-in. Vegas Pro 12 would add two new configurations: Vegas Pro 12 Edit, for "Professional Video and Audio Production"; and Vegas Pro 12 Suite, for "Professional Editing, Disc Authoring, and Visual Effects Design". Vegas Pro 13 would be the last version released with Sony branding after the acquisition of much of Sony Creative Software's library by Magix. After they acquired Vegas, Magix released version 14 on September 20, 2016. It featured advanced 4K upscaling as well as many bug fixes, a higher video velocity limit, RED camera support, and a variety of other features. This was also the last version to have the light theme enabled by default. Released on August 28, 2017, Vegas Pro 15 features major UI changes that claim to bring usability improvements and customization. It was the first version of VEGAS Pro to have a dark theme; it also allows more efficient editing speeds, including adding new shortcuts to speed the video editing process. Vegas Pro 15 includes support for Intel Quick Sync Video (QSV) and other technologies, as well as various other features. It introduced a new VEGAS Pro icon as a V. Vegas Pro 16 has some new features including file backup, motion tracking, improved video stabilization, 360° editing and HDR support. Magix has continued to improve Vegas through version 21 with support for reading Matroska files, a more detailed render dialogue, live streaming, VST3 support, a VST 32-bit bridge, and a selective Paste Event Attributes menu. Magix would later release a subscription model for using Vegas named "Vegas Pro 365" on January 17, 2018, although the perpetual licence is still an option for customers. This version includes cloud-based speech synthesis among other features not included in the mainline Vegas release. == Version history == Each release of Vegas is sold standalone, however upgrade discounts are sometimes provided. === Vegas Beta === Sonic Foundry introduced a sneak preview version of Vegas Pro on June 11, 1999. It is called a "Multitrack Media Editing System". === Vegas 1.0 === Released on July 23, 1999 at the NAMM Show in Nashville, Tennessee, Vegas was an audio-only tool with a particular focus on rescaling and resampling audio. It supported formats like DivX and Real Networks RealSystem G2 file formats. Version 1.0 is the final Vegas release to include Windows 95 support. === Vegas Video beta (Vegas 2.0 beta) === Released on April 10, 2000, this was the first version of Vegas to include video-editing tools. === Vegas Video (Vegas 2.0) === Released on June 12, 2000. Version 2.0 is the final Vegas Video release to include Windows NT 4.0 support. === Vegas Video 3.0 === Released on December 3, 2001. This release added: New Video Effects – Lens Flare, Light Rays, Film FX, Color Curves, Mirror, Remap, Deform, Convolution, Linear Blur, Black Restore, Levels, Unsharp Mask, Color Grading, and Timecode Burn filter. Batch Capture with Automatic Scene Detection – Captures DV with automatic scene detection, batch capture, tape logging, still image capture and thumbnail previews. Red Book Audio CD Mastering with CD Architect (TM) Technology – Used for burning Red Book audio CD masters directly from the Vegas timeline with ISRC, UPC, and PQ list support. New Sonic Foundry DV Codec – Introduces a DV codec developed by Sonic Foundry that offers artifact-free compositing and DV chromakeying. DV Print-to-Tape from the Timeline – Prints projects to DV cameras and decks from the Vegas timeline. Windows Media (TM) File Editing – Creates and edits Windows Media (TM) files. New MPEG Encoding Tools – Used for producing MPEG-2 files for DVD productions. Dynamic RAM Previewing – Temporary RAM/render-free previews for analysis and tweaking of complex video FX without rendering. VideoCD and Data CD Burning – Burning projects directly to VideoCD for playback on most DVD players or data CDs for playback computers' CD-ROMs. === Vegas 4.0 === Released on February 6, 2003. This release added: Advanced Color Correction Tools Searchable Media Pool Bins Vectorscope, Histogram, Parade and Waveform Monitoring Application Scripting Improved Ripple Editing Motion Blur and Super-Sampling Envelopes 5.1 Surround Mixing Dolby® Digital AC-3 Encoding certified and tested by Dolby Laboratories DirectX® Audio Plug-In Effects Automation ASIO Driver Support Windows Media™ 9 Support, including Surround Encoding DVD Authoring with AC-3 File Import Capabilities Integration with DVD Architect via Chap
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Hardware compatibility list

A hardware compatibility list (HCL) is a list of computer hardware (typically including many types of peripheral devices) that is compatible with a particular operating system or device management software. The list contains both whole computer systems and specific hardware elements including motherboards, sound cards, and video cards. In today's world, there is a vast amount of computer hardware in circulation, and many operating systems too. A hardware compatibility list is a database of hardware models and their compatibility with a certain operating system. HCLs can be centrally controlled (one person or team keeps the list of hardware maintained) or user-driven (users submit reviews on hardware they have used). There are many HCLs. Usually, each operating system will have an official HCL on its website.
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Artificial Intelligence for Digital Response

Artificial Intelligence for Digital Response (AIDR) is a free and open source platform to filter and classify social media messages related to emergencies, disasters, and humanitarian crises. It has been developed by the Qatar Computing Research Institute and awarded the Grand Prize for the 2015 Open Source Software World Challenge. Muhammad Imran stated that he and his team "have developed novel computational techniques and technologies, which can help gain insightful and actionable information from online sources to enable rapid decision-making" - according to him the system "combines human intelligence with machine learning techniques, to solve many real-world challenges during mass emergencies and health issues". == How to use == It can be used by logging in with ones Twitter credentials and by collecting tweets by specifying keywords or hashtags, like #ChileEarthquake, and possibly a geographical region as well. == Use == It has been deployed in conjunction with UNICEF in Zambia to classify short messages related to AIDS/HIV received through the U-Report platform. AIDR was used for the first time during the 2010 Pakistan floods. The first real test of AIDR took place during the 2014 Iquique earthquake in Chile. == Related talks and events == Muhammad Imran delivered a keynote talk on the science behind the AIDR system at the International Conference on Information Systems for Crisis Response And Management (ISCRAM). Abdelkader Lattab and Ji Lucas also presented the system at the 2016 QCRI-IBM Data Science Connect event.
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IAmAnas

#IAmAnas (I Am Anas) is a Twitter hashtag and social media campaign that started in 2015. Users tweeted to express support for the undercover investigative works of Ghanaian journalist Anas Aremeyaw Anas. The campaign restarted in 2018 when the Ghanaian MP and financier of the New Patriotic Party, Kennedy Agyapong, announced his intention to reveal the identity of Anas following the journalist's exposé of corruption at the Ghana Football Association. Anas maintains that "being anonymous has always been his secret weapon." Pictures purported to be of Anas were first released by a TV station owned by Agyapong, and were quickly picked up by other media houses. At least one person, a Dutch-Brazilian model, has claimed ownership of one picture that was released, and has threatened legal action against Agyapong for possibly putting his life in danger. In response to Agyapong, social media users retweeted photos of themselves, random people, or even comic images of entities that resemble the trademark covered face of Anas. When the hashtag first began in 2015, along with other popular uses of the journalist's name, Elizabeth Ohene wrote an article about Ghanaians use of humour in response to dealing with the expose of government corruption. "I do not know when these words will make it into Wikipedia or the Oxford English Dictionary but for the moment you can take it from me that: To go undercover is to anas, to make secret recordings is to anas-anas, to wear disguises is to do an anas, to be caught in the act is to be anased. To have someone exposed taking bribes is to have that person being given the full Anas Aremeyaw Anas."
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Symbolic regression

Symbolic regression (SR) is a type of regression analysis that searches the space of mathematical expressions to find the model that best fits a given dataset, both in terms of accuracy and simplicity. No particular model is provided as a starting point for symbolic regression. Instead, initial expressions are formed by randomly combining mathematical building blocks such as mathematical operators, analytic functions, constants, and state variables. Usually, a subset of these primitives will be specified by the person operating it, but that's not a requirement of the technique. The symbolic regression problem for mathematical functions has been tackled with a variety of methods, including recombining equations most commonly using genetic programming, as well as more recent methods utilizing Bayesian methods and neural networks. Another non-classical alternative method to SR is called Universal Functions Originator (UFO), which has a different mechanism, search-space, and building strategy. Further methods such as Exact Learning attempt to transform the fitting problem into a moments problem in a natural function space, usually built around generalizations of the Meijer-G function. By not requiring a priori specification of a model, symbolic regression isn't affected by human bias, or unknown gaps in domain knowledge. It attempts to uncover the intrinsic relationships of the dataset, by letting the patterns in the data itself reveal the appropriate models, rather than imposing a model structure that is deemed mathematically tractable from a human perspective. The fitness function that drives the evolution of the models takes into account not only error metrics (to ensure the models accurately predict the data), but also special complexity measures, thus ensuring that the resulting models reveal the data's underlying structure in a way that's understandable from a human perspective. This facilitates reasoning and favors the odds of getting insights about the data-generating system, as well as improving generalisability and extrapolation behaviour by preventing overfitting. Accuracy and simplicity may be left as two separate objectives of the regression—in which case the optimum solutions form a Pareto front—or they may be combined into a single objective by means of a model selection principle such as minimum description length. It has been proven that symbolic regression is an NP-hard problem. Nevertheless, if the sought-for equation is not too complex it is possible to solve the symbolic regression problem exactly by generating every possible function (built from some predefined set of operators) and evaluating them on the dataset in question. == Difference from classical regression == While conventional regression techniques seek to optimize the parameters for a pre-specified model structure, symbolic regression avoids imposing prior assumptions, and instead infers the model from the data. In other words, it attempts to discover both model structures and model parameters. This approach has the disadvantage of having a much larger space to search, because not only the search space in symbolic regression is infinite, but there are an infinite number of models which will perfectly fit a finite data set (provided that the model complexity isn't artificially limited). This means that it will possibly take a symbolic regression algorithm longer to find an appropriate model and parametrization, than traditional regression techniques. This can be attenuated by limiting the set of building blocks provided to the algorithm, based on existing knowledge of the system that produced the data; but in the end, using symbolic regression is a decision that has to be balanced with how much is known about the underlying system. Nevertheless, this characteristic of symbolic regression also has advantages: because the evolutionary algorithm requires diversity in order to effectively explore the search space, the result is likely to be a selection of high-scoring models (and their corresponding set of parameters). Examining this collection could provide better insight into the underlying process, and allows the user to identify an approximation that better fits their needs in terms of accuracy and simplicity. == Benchmarking == === SRBench === In 2021, SRBench was proposed as a large benchmark for symbolic regression. In its inception, SRBench featured 14 symbolic regression methods, 7 other ML methods, and 252 datasets from PMLB. The benchmark intends to be a living project: it encourages the submission of improvements, new datasets, and new methods, to keep track of the state of the art in SR. === SRBench Competition 2022 === In 2022, SRBench announced the competition Interpretable Symbolic Regression for Data Science, which was held at the GECCO conference in Boston, MA. The competition pitted nine leading symbolic regression algorithms against each other on a novel set of data problems and considered different evaluation criteria. The competition was organized in two tracks, a synthetic track and a real-world data track. ==== Synthetic Track ==== In the synthetic track, methods were compared according to five properties: re-discovery of exact expressions; feature selection; resistance to local optima; extrapolation; and sensitivity to noise. Rankings of the methods were: QLattice PySR (Python Symbolic Regression) uDSR (Deep Symbolic Optimization) ==== Real-world Track ==== In the real-world track, methods were trained to build interpretable predictive models for 14-day forecast counts of COVID-19 cases, hospitalizations, and deaths in New York State. These models were reviewed by a subject expert and assigned trust ratings and evaluated for accuracy and simplicity. The ranking of the methods was: uDSR (Deep Symbolic Optimization) QLattice geneticengine (Genetic Engine) == Non-standard methods == Most symbolic regression algorithms prevent combinatorial explosion by implementing evolutionary algorithms that iteratively improve the best-fit expression over many generations. Recently, researchers have proposed algorithms utilizing other tactics in AI. Silviu-Marian Udrescu and Max Tegmark developed the "AI Feynman" algorithm, which attempts symbolic regression by training a neural network to represent the mystery function, then runs tests against the neural network to attempt to break up the problem into smaller parts. For example, if f ( x 1 , . . . , x i , x i + 1 , . . . , x n ) = g ( x 1 , . . . , x i ) + h ( x i + 1 , . . . , x n ) {\displaystyle f(x_{1},...,x_{i},x_{i+1},...,x_{n})=g(x_{1},...,x_{i})+h(x_{i+1},...,x_{n})} , tests against the neural network can recognize the separation and proceed to solve for g {\displaystyle g} and h {\displaystyle h} separately and with different variables as inputs. This is an example of divide and conquer, which reduces the size of the problem to be more manageable. AI Feynman also transforms the inputs and outputs of the mystery function in order to produce a new function which can be solved with other techniques, and performs dimensional analysis to reduce the number of independent variables involved. The algorithm was able to "discover" 100 equations from The Feynman Lectures on Physics, while a leading software using evolutionary algorithms, Eureqa, solved only 71. AI Feynman, in contrast to classic symbolic regression methods, requires a very large dataset in order to first train the neural network and is naturally biased towards equations that are common in elementary physics.
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Personal media

Personal media are media of communication which are used by an individual rather than by a corporation or institution. They are generally contrasted with mass media which are produced by teams of people and broadcast to a general population. In other words, personal media allow individuals, as opposed to corporate entities, to contribute knowledge and opinion to the public. The term dates from the 1980s. New technologies such as social media and self-publishing are creating a variety of modes for modern media. Marika Lüders suggests a two-dimensional model for classifying such media with one dimension being the degree of interaction between the senders and receivers; and the other dimension being the level of institutionalisation and professionalism. Katherine Nashleanas links the concept of personal media to the notion of 'control' by an individual as opposed to a centralised authority. She argues that although personal media including the fax have been available to the general public since the 1960s, more recent technologies such as the smartphone confer greater control over content production and distribution to their users.
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Errored second

In telecommunications and data communication systems, an errored second is an interval of a second during which any error whatsoever has occurred, regardless of whether that error was a single bit error or a complete loss of communication for that entire second. The type of error is not important for the purpose of counting errored seconds. In communication systems with very low uncorrected bit error rates, such as modern fiber-optic transmission systems, or systems with higher low-level error rates that are corrected using large amounts of forward error correction, errored seconds are often a better measure of the effective user-visible error rate than the raw bit error rate. For many modern packet-switched communication systems, even a single uncorrected bit error is enough to cause the loss of a data packet by causing its CRC check to fail; whether that packet loss was caused by a single bit error or a hundred-bit-long error burst is irrelevant. For systems using large amounts of forward error correction, the reverse applies; a single low-level bit error will almost never occur, since any small errors will almost always be corrected, but any error sufficiently large to cause the forward error correction to fail will almost always result in a large burst error. More specialist and precise definitions of errored seconds exist in standards such as the T1 and DS1 transport systems.
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