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  Video editing software

  Video editing software or a video editor is software used for performing the post-production video editing of digital video sequences on a non-linear editing system (NLE). It has replaced traditional flatbed celluloid film editing tools and analog video tape editing machines. Video editing software serves a lot of purposes, such as filmmaking, audio commentary, and general editing of video content. In NLE software, the user manipulates sections of video, images, and audio on a sequence. These clips can be trimmed, cut, and manipulated in many different ways. When editing is finished, the user exports the sequence as a video file. == Components == === Timeline === NLE software is typically based on a timeline interface where sections moving image video recordings, known as clips, are laid out in sequence and played back. The NLE offers a range of tools for trimming, splicing, cutting, and arranging clips across the timeline. Another kind of clip is a text clip, used to add text to a video, such as title screens or movie credits. Audio clips can additionally be mixed together, such as mixing a soundtrack with multiple sound effects. Typically, the timeline is divided into multiple rows on the y-axis for different clips playing simultaneously, whereas the x-axis represents the run time of the video. Effects such as transitions can be performed on each clip, such as a crossfade effect going from one scene to another. === Exporting === Since video editors represent a project with a file format specific to the program, one needs to export the video file in order to publish it. Once a project is complete, the editor can then export to movies in a variety of formats in a context that may range from broadcast tape formats to compressed video files for web publishing (such as on an online video platform or personal website), optical media, or saved to mobile devices. To facilitate editing, source video typically has a higher resolution than the desired output. Therefore, higher resolution video needs to be downscaled during exporting, or after exporting in a process known as transsizing. === Visual effects === As digital video editing advanced, visual effects became possible, and is part of the standard toolkit, usually found in prosumer and professional grade software. A common ability is to do compositing techniques such as chroma keying or luma keying, among others, which allow different objects to look as if they are in the same scene. A different kind of visual effects is motion capture. Software such as Blender can perform motion capture to make animated objects follow an actor's movements. === Additional features === Most professional video editors are able to do color grading, which is to manipulate visual attributes of a video such as contrast to enhance output, and improve emotional impact. Some video editors such as iMovie include stock footage available for use. == Hardware requirements == As video editing puts great demands on storage and graphics performance, especially at high resolutions such as 4K, and for videos with many visual effects, powerful hardware is often required. It is not uncommon for a computer built for video editing to have a lot of drive capacity, and a powerful graphics processing unit, which optimally has hardware accelerated video encoding. Having sufficient disk space is important since videos can take up large amounts of storage, depending on the resolution and compression format used. Each minute of a Full HD (1080p) video at 30 fps takes up 60MB of space. When visual effects are used, a server farm can be employed to speed up the rendering process. == Examples == Video editing software can be divided into consumer grade, which focuses on ease-of-use, along with professional grade software, which focuses on feature availability, and advanced editing techniques. The typical use case for the former is to edit personal videos on the go, when more advanced editing is not required. === Consumer grade === Photos (Apple) Google Photos YouTube Create === Prosumer grade === ==== Proprietary software ==== iMovie CyberLink PowerDirector === Professional grade === ==== Proprietary software ==== Final Cut Pro Adobe Premiere Pro DaVinci Resolve Vegas Pro Lightworks Camtasia Media Composer ==== Free and open source software ==== Avidemux Blender Cinelerra Flowblade Kdenlive OpenShot Shotcut While most video editing software has been separate from the operating systems, some operating systems have had a video editor installed by default, such as Windows Movie Maker in Windows XP, or as a component of the default photo viewer, such as the Photos app on iOS. Some social media platforms, such as TikTok and Instagram may include a rudimentary video editor to trim clips.

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  SIP (software)

  SIP is an open source software tool used to connect computer programs or libraries written in C or C++ with the scripting language Python. It is an alternative to SWIG. SIP was originally developed in 1998 for PyQt — the Python bindings for the Qt GUI toolkit — but is suitable for generating bindings for any C or C++ library. == Concept == SIP takes a set of specification (.sip) files describing the API and generates the required C++ code. This is then compiled to produce the Python extension modules. A .sip file is essentially the class header file with some things removed (because SIP does not include a full C++ parser) and some things added (because C++ does not always provide enough information about how the API works). For PyQt v4 I use an internal tool (written using PyQt of course) called metasip. This is sort of an IDE for SIP. It uses GCC-XML to parse the latest header files and saves the relevant data, as XML, in a metasip project. metasip then does the equivalent of a diff against the previous version of the API and flags up any changes that need to be looked at. Those changes are then made through the GUI and ticked off the TODO list. Generating the .sip files is just a button click. In my subversion repository, PyQt v4 is basically just a 20M XML file. Updating PyQt v4 for a minor release of Qt v4 is about half an hours work. In terms of how the generated code works then I don't think it's very different from how any other bindings generator works. Python has a very good C API for writing extension modules - it's one of the reasons why so many 3rd party tools have Python bindings. For every C++ class, the SIP generated code creates a corresponding Python class implemented in C. == Notable applications that use SIP == PyQt, a python port of the application framework and widget toolkit Qt QGIS, a free and open-source cross-platform desktop geographic information system (GIS) QtiPlot, a computer program to analyze and visualize scientific data calibre (software), a free and open-source cross-platform e-book manager Veusz, a free and open-source cross-platform program to visualize scientific data

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  Lingua Libre

  Lingua Libre is an online collaborative project and tool by the Wikimédia France association, which aims to build a collaborative, multilingual, audiovisual speech corpus under a free license. It mostly consists of a rapid recording online service which allows the user to chain hundreds of recordings. Contributors have produced content in 310+ languages. == Description == Lingua Libre enables the recording of words, phrases or sentences of any language, oral (audio recording) or signed (video recording). Words are presented to the speaker in the form of a list, created on the spot, in advance, or by reusing an existing Wikimedia category. The speaker simply reads the word displayed on the screen, and the software moves on to the next word when it detects a silence after the read word. This principle, borrowed from the open source software Shtooka recorder with the help of its creator, Nicolas Vion, makes it possible to record several hundreds of words per hour. The recordings are then uploaded automatically from the web client to the Wikimedia Commons media library. In spring 2021, Lingua Libre was offline due to a fire in Strasbourg, but no audio recordings were lost. === Use of the recordings === The recordings can be consulted either on Lingua Libre or on Commons. They are mainly used on other Wikimedia projects, for example to illustrate entries on Wiktionaries or proper nouns in Wikipedia articles. The re-use of the recordings in a language teaching context is envisaged. Language learners can freely download pronunciations and use them on GoldenDict, a popular dictionary software. Thus, audio recordings can be used as “Pronunciation Dictionaries” on GoldenDict without needing internet connection. The recordings are also reused in Natural Language Processing projects, for example to drive Mozilla's DeepSpeech speech recognition engines. == Versions == Lingua Libre was initiated on January 23, 2015 and has had three successive versions: === Lingua Libre v.1 (2016) === As part of the Languages of France project, which aims to document and promote the regional languages of France on Wikimedia and Internet projects in general, the conception of Lingua Libre started in November 2015, partly funded by the DGLFLF (General Delegation for the French language and the languages of France). The first version of the project was launched in August 2016. Only suitable for audio recording, Lingua Libre was shown during a workshop on Occitan language in December 2016, and then presented to the online Wikimedia community and at international events in 2017. === Lingua Libre v.2 (2018) === A complete rebuilding was launched at the end of 2017. The new version of Lingua Libre is based on MediaWiki, uses Wikibase and OAuth to better integrate into the Wikimedia environment. The interface is translated via Translatewiki.net so that the project can be used by a large number of communities. The new version of the site was ready in June 2018 and opened to the public in August 2018. === Lingua Libre v.2.2 (2020) === In 2020, important changes were made to the platform; a new look was developed especially for the site, the .org domain replaced the .fr domain used until then, and added support for sign languages through video recording. == Statistics == In the first two years of the project's launch, approximately 10,000 recordings were made. The transition to v.2 was accompanied by a sharp increase in the contributions. The number of recordings multiplied by 10 in less than a year, exceeding the 100,000 threshold in May 2019. These recordings were made by 127 speakers in almost 50 languages. By September 2020, the platform had more than 300,000 recordings in 90 languages with more than 350 speakers. The 500,000 recordings milestone was reached in June 2021, thanks to 540 speakers of 120 languages.

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  IgHome

  igHome is a customizable start page introduced in 2012 as an alternative to iGoogle, the personal web portal launched by Google in May 2005. Just like iGoogle, igHome offers users the possibility to build a start page containing a central search box and a number of gadgets. igHome mimics the user interface of iGoogle. Registered igHome users can create multiple tabs and import RSS feeds.

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  Embodied agent

  In artificial intelligence, an embodied agent, also sometimes referred to as an interface agent, is an intelligent agent that interacts with the environment through a physical body within that environment. Agents that are represented graphically with a body, for example a human or a cartoon animal, are also called embodied agents, although they have only virtual, not physical, embodiment. A branch of artificial intelligence focuses on empowering such agents to interact autonomously with human beings and the environment. Mobile robots are one example of physically embodied agents; Ananova and Microsoft Agent are examples of graphically embodied agents. Embodied conversational agents are embodied agents (usually with a graphical front-end as opposed to a robotic body) that are capable of engaging in conversation with one another and with humans employing the same verbal and nonverbal means that humans do (such as gesture, facial expression, and so forth). == Embodied conversational agents == Embodied conversational agents are a form of intelligent user interface. Graphically embodied agents aim to unite gesture, facial expression and speech to enable face-to-face communication with users, providing a powerful means of human-computer interaction. == Advantages == Face-to-face communication allows communication protocols that give a much richer communication channel than other means of communicating. It enables pragmatic communication acts such as conversational turn-taking, facial expression of emotions, information structure and emphasis, visualization and iconic gestures, and orientation in a three-dimensional environment. This communication takes place through both verbal and non-verbal channels such as gaze, gesture, spoken intonation and body posture. Research has found that users prefer a non-verbal visual indication of an embodied system's internal state to a verbal indication, demonstrating the value of additional non-verbal communication channels. As well as this, the face-to-face communication involved in interacting with an embodied agent can be conducted alongside another task without distracting the human participants, instead improving the enjoyment of such an interaction. Furthermore, the use of an embodied presentation agent results in improved recall of the presented information. Embodied agents also provide a social dimension to the interaction. Humans willingly ascribe social awareness to computers, and thus interaction with embodied agents follows social conventions, similar to human to human interactions. This social interaction both raises the believably and perceived trustworthiness of agents, and increases the user's engagement with the system. Rickenberg and Reeves found that the presence of an embodied agent on a website increased the level of user trust in that website, but also increased users' anxiety and affected their performance, as if they were being watched by a real human. Another effect of the social aspect of agents is that presentations given by an embodied agent are perceived as being more entertaining and less difficult than similar presentations given without an agent. Research shows that perceived enjoyment, followed by perceived usefulness and ease of use, is the major factor influencing user adoption of embodied agents. A study in January 2004 by Byron Reeves at Stanford demonstrated how digital characters could "enhance online experiences" through explaining how virtual characters essentially add a sense of familiarity to the user experience and make it more approachable. This increase in likability in turn helps make the products better, which benefits both the end users and those creating the product. === Applications === The rich style of communication that characterizes human conversation makes conversational interaction with embodied conversational agents ideal for many non-traditional interaction tasks. A familiar application of graphically embodied agents is computer games; embodied agents are ideal for this setting because the richer communication style makes interacting with the agent enjoyable. Embodied conversational agents have also been used in virtual training environments, portable personal navigation guides, interactive fiction and storytelling systems, interactive online characters and automated presenters and commentators. Major virtual assistants like Siri, Amazon Alexa and Google Assistant do not come with any visual embodied representation, which is believed to limit the sense of human presence by users. The U.S. Department of Defense utilizes a software agent called SGT STAR on U.S. Army-run Web sites and Web applications for site navigation, recruitment and propaganda purposes. Sgt. Star is run by the Army Marketing and Research Group, a division operated directly from The Pentagon. Sgt. Star is based upon the ActiveSentry technology developed by Next IT, a Washington-based information technology services company. Other such bots in the Sgt. Star "family" are utilized by the Federal Bureau of Investigation and the Central Intelligence Agency for intelligence gathering purposes.

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  Google Gadgets

  Google Gadgets are dynamic web content that can be embedded on a web page. They can be added to and interact strongly with Google's iGoogle personalized home page (discontinued in November 2013, although iGoogle Gadgets still work on other websites) and the Google Desktop (discontinued in September 2011) application, as well as Google Wave (also no longer supported by Google) and Google Sites. Webmasters can add and customize a gadget to their own business or personal web site, a process called "syndication". Gadgets are developed by Google and third-party developers using the Google Gadgets API, using basic web technologies such as XML and JavaScript. == Multi-user persistent - Wave Gadgets == With the advent of Google Wave (now Apache Wave), gadgets became able to have persistent storage and multi-user capabilities and better state management. Gadgets using Google Wave in this way were simply known as 'Wave Gadgets'. For instance, a game written using a Google Gadget could use Google Wave technology to record a list of users and high scores without having to worry about how to permanently store the scores on a hosted server. The use of Google Wave would give the gadget multi-user and permanent storage capabilities. For example, scores could be stored in a Google Wave hosted permanently by Google at no cost to the user. As of early 2013, Google Gadgets were deprecated in Google Spreadsheets. Shortly after, they were removed from all spreadsheets. == Technology == Google Gadgets are written in XML and can have HTML and JavaScript components, and were able to use Google Wave. Here is an example of a Hello World program written using Google Gadget technology. Google Gadgets API is a Google API which allows developers to create Google Gadgets easily.

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  List of .NET libraries and frameworks

  This article contains a list of libraries that can be used in .NET languages. These languages require .NET Framework, Mono, or .NET, which provide a basis for software development, platform independence, language interoperability and extensive framework libraries. Standard Libraries (including the Base Class Library) are not included in this article. == Introduction == Apps created with .NET Framework or .NET run in a software environment known as the Common Language Runtime (CLR), an application virtual machine that provides services such as security, memory management, and exception handling. The framework includes a large class library called Framework Class Library (FCL). Thanks to the hosting virtual machine, different languages that are compliant with the .NET Common Language Infrastructure (CLI) can operate on the same kind of data structures. These languages can therefore use the FCL and other .NET libraries that are also written in one of the CLI compliant languages. When the source code of such languages are compiled, the compiler generates platform-independent code in the Common Intermediate Language (CIL, also referred to as bytecode), which is stored in CLI assemblies. When a .NET app runs, the just-in-time compiler (JIT) turns the CIL code into platform-specific machine code. To improve performance, .NET Framework also comes with the Native Image Generator (NGEN), which performs ahead-of-time compilation to machine code. This architecture provides language interoperability. Each language can use code written in other languages. Calls from one language to another are exactly the same as would be within a single programming language. If a library is written in one CLI language, it can be used in other CLI languages. Moreover, apps that consist only of pure .NET assemblies, can be transferred to any platform that contains an implementation of CLI and run on that platform. For example, apps written using .NET can run on Windows, macOS, and various versions of Linux. .NET apps or their libraries, however, may depend on native platform features, e.g. COM. As such, platform independence of .NET apps depends on the ability to transfer necessary native libraries to target platforms. In 2019, the Windows Forms and Windows Presentation Foundation portions of .NET Framework were made open source. === .NET implementations === There are four primary .NET implementations that are actively developed and maintained: .NET Framework: The original .NET implementation that has existed since 2002. While not yet discontinued, Microsoft does not plan on releasing its next major version, 5.0. Mono: A cross-platform implementation of .NET Framework by Ximian, introduced in 2004. It is free and open-source. It is now developed by Xamarin, a subsidiary of Microsoft. Universal Windows Platform (UWP): An implementation of .NET used for building UWP apps. It's designed to unify development for different targeted types of devices, including PCs, tablets, phablets, phones, and the Xbox. .NET: A cross-platform re-implementation of .NET Framework, introduced in 2016 and initially called .NET Core. It is free and open-source. .NET superseded .NET Framework with the release of .NET 5. Each implementation of .NET includes the following components: One or more runtime environments, e.g. Common Language Runtime (CLR) for .NET Framework and CoreCLR for .NET A class library The .NET Standard is a set of common APIs that are implemented in the Base Class Library of any .NET implementation. The class library of each implementation must implement the .NET Standard, but may also implement additional APIs. Traditionally, .NET apps targeted a certain version of a .NET implementation, e.g. .NET Framework 4.6. Starting with the .NET Standard, an app can target a version of the .NET Standard and then it could be used (without recompiling) by any implementation that supports that level of the standard. This enables portability across different .NET implementations. The following table lists the .NET implementations that adhere to the .NET Standard and the version number at which each implementation became compliant with a given version of .NET Standard. For example, according to this table, .NET Core 3.0 was the first version of .NET Core that adhered to .NET Standard 2.1. This means that any version of .NET Core bigger than 3.0 (e.g. .NET Core 3.1) also adheres to .NET Standard 2.1. == Web frameworks == === ASP.NET === First released in 2002, ASP.NET is an open-source server-side web application framework designed for web development to produce dynamic web pages. It is the successor to Microsoft's Active Server Pages (ASP) technology, built on the Common Language Runtime (CLR). === ASP.NET Core === ASP.NET was completely rewritten in 2016 as a modular web framework, together with other frameworks like Entity Framework. The re-written framework uses the new open-source .NET Compiler Platform (also known by its codename "Roslyn") and is cross platform. The programming models ASP.NET MVC, ASP.NET Web API, and ASP.NET Web Pages (a model using only Razor pages) were merged into a unified MVC 6. === Blazor === Blazor is a free and open-source web framework that enables developers to create Single-page Web apps using C# and HTML in ASP.NET Razor pages ("components"). Blazor is part of the ASP.NET Core framework. Blazor Server apps are hosted on a web server, while Blazor WebAssembly apps are downloaded to the client's web browser before running. In addition, a Blazor Hybrid framework is available with server-based and client-based application components. == Numerical libraries == === Open-source numerical libraries === ==== AForge.NET ==== This is a computer vision and artificial intelligence library. It implements a number of genetic, fuzzy logic and machine learning algorithms with several architectures of artificial neural networks with corresponding training algorithms. ==== ALGLIB ==== This is a cross-platform open source numerical analysis and data processing library. It consists of algorithm collections written in different programming languages (C++, C#, FreePascal, Delphi, VBA) and has dual licensing – commercial and GPL. ==== Math.NET Numerics ==== This library aims to provide methods and algorithms for numerical computations in science, engineering and everyday use. Covered topics include special functions, linear algebra, probability models, random numbers, interpolation, integral transforms and more. MIT/X11 license. ==== Meta.Numerics ==== This is a library for advanced scientific computation in the .NET Framework. ==== ML.NET ==== This is a free software machine learning library. The preview release of ML.NET included transforms for feature engineering like n-gram creation, and learners to handle binary classification, multi-class classification, and regression tasks. Additional ML tasks like anomaly detection and recommendation systems have since been added, and other approaches like deep learning will be included in future versions. === Proprietary numerical libraries === ==== ILNumerics.Net ==== This is a high performance, typesafe numerical array set of classes and functions for general math, FFT and linear algebra. The library, developed for .NET/Mono, aims to provide 32- and 64-bit script-like syntax in C#, 2D & 3D plot controls, and efficient memory management. It is released under GPLv3 or commercial license. ==== Measurement Studio ==== This is an integrated suite of UI controls and class libraries for use in developing test and measurement applications. The analysis class libraries provide various digital signal processing, signal filtering, signal generation, peak detection, and other general mathematical functionality. ==== NMath ==== This is a numerical component library for the .NET platform developed by CenterSpace Software. It includes signal processing (FFT) classes, a linear algebra (LAPACK & BLAS) framework, and a statistics package. == 3D graphics == === Open-source 3D graphics === ==== Open Toolkit (OpenTK) ==== This is a low-level C# binding for OpenGL, OpenGL ES and OpenAL. It runs on Windows, Linux, Mac OS X, BSD, Android and iOS. It can be used standalone or integrated into a GUI. ==== Windows Presentation Foundation (WPF) ==== This is a graphical subsystem for rendering user interfaces, developed by Microsoft. It also contains a 3D rendering engine. In addition, interactive 2D content can be overlaid on 3D surfaces natively. It only runs on Windows operating systems. === Proprietary 3D graphics === ==== Unity ==== This is a cross-platform game engine developed by Unity Technologies and used to develop video games for PC, consoles, mobile devices and websites. == Image processing == === AForge.NET === This is a computer vision and artificial intelligence library. It implements a number of image processing algorithms and filters. It is released under the LGPLv3 and partly GPLv3 license. Majority of the library is written in C# and th

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  Python (programming language)

  Python is a high-level, general-purpose programming language that emphasizes code readability, simplicity, and ease-of-writing with the use of significant indentation, "plain English" naming, an extensive ("batteries-included") standard library, and garbage collection. Python supports multiple programming paradigms but with an emphasis on object-oriented programming and dynamic typing. Guido van Rossum began working on Python in the late 1980s as a successor to the ABC programming language. Python 3.0, released in 2008, was a major revision and not completely backward-compatible with earlier versions. Beginning with Python 3.5, capabilities and keywords for typing were added to the language, allowing optional static typing. As of 2026, the Python Software Foundation supports Python 3.10, 3.11, 3.12, 3.13, and 3.14, following the project's annual release cycle and five-year support policy. Python 3.15 is currently in the alpha development phase, and the stable release is expected to launch in October 2026. Earlier versions in the 3.x series have reached end-of-life and no longer receive security updates. Python has gained extensive use in the machine learning community. It is widely taught as an introductory programming language. Since 2003, Python has consistently ranked among the top ten most popular programming languages in the TIOBE Programming Community Index, which ranks programming languages based on searches across 24 platforms. == History == Python was conceived in the late 1980s by Guido van Rossum at Centrum Wiskunde & Informatica (CWI) in the Netherlands. It was designed as a successor to the ABC programming language, which was inspired by SETL, capable of exception handling and interfacing with the Amoeba operating system. Python implementation began in December 1989. Van Rossum first released it in 1991 as Python 0.9.0. Van Rossum assumed sole responsibility for the project, as the lead developer, until 12 July 2018, when he announced his "permanent vacation" from responsibilities as Python's "benevolent dictator for life" (BDFL); this title was bestowed on him by the Python community to reflect his long-term commitment as the project's chief decision-maker. (He has since come out of retirement and is self-titled "BDFL-emeritus".) In January 2019, active Python core developers elected a five-member Steering Council to lead the project. The name Python derives from the British comedy series Monty Python's Flying Circus. (See § Naming.) Python 2.0 was released on 16 October 2000, featuring many new features such as list comprehensions, cycle-detecting garbage collection, reference counting, and Unicode support. Python 2.7's end-of-life was initially set for 2015, and then postponed to 2020 out of concern that a large body of existing code could not easily be forward-ported to Python 3. It no longer receives security patches or updates. While Python 2.7 and older versions are officially unsupported, a different unofficial Python implementation, PyPy, continues to support Python 2, i.e., "2.7.18+" (plus 3.11), with the plus signifying (at least some) "backported security updates". Python 3.0 was released on 3 December 2008, and was a major revision and not completely backward-compatible with earlier versions, with some new semantics and changed syntax. Python 2.7.18, released in 2020, was the last release of Python 2. Several releases in the Python 3.x series have added new syntax to the language, and made a few (considered very minor) backward-incompatible changes. As of May 2026, Python 3.14.5 is the latest stable release. All older 3.x versions had a security update down to Python 3.9.24 then again with 3.9.25, the final version in 3.9 series. Python 3.10 is, since November 2025, the oldest supported branch. Python 3.15 has an alpha released, and Android has an official downloadable executable available for Python 3.14. Releases receive two years of full support followed by three years of security support. == Design philosophy and features == Python is a multi-paradigm programming language. Object-oriented programming and structured programming are fully supported, and many of their features support functional programming and aspect-oriented programming – including metaprogramming and metaobjects. Many other paradigms are supported via extensions, including design by contract and logic programming. Python is often referred to as a 'glue language' because it is purposely designed to be able to integrate components written in other languages. Python uses dynamic typing and a combination of reference counting and a cycle-detecting garbage collector for memory management. It uses dynamic name resolution (late binding), which binds method and variable names during program execution. Python's design offers some support for functional programming in the "Lisp tradition". It has filter, map, and reduce functions; list comprehensions, dictionaries, sets, and generator expressions. The standard library has two modules (itertools and functools) that implement functional tools borrowed from Haskell and Standard ML. Python's core philosophy is summarized in the Zen of Python (PEP 20) written by Tim Peters, which includes aphorisms such as these: Explicit is better than implicit. Simple is better than complex. Readability counts. Special cases aren't special enough to break the rules. Although practicality beats purity, errors should never pass silently, unless explicitly silenced. There should be one-- and preferably only one --obvious way to do it. However, Python has received criticism for violating these principles and adding unnecessary language bloat. Responses to these criticisms note that the Zen of Python is a guideline rather than a rule. The addition of some new features had been controversial: Guido van Rossum resigned as Benevolent Dictator for Life after conflict about adding the assignment expression operator in Python 3.8. Nevertheless, rather than building all functionality into its core, Python was designed to be highly extensible through modules. This compact modularity has made it particularly popular as a means of adding programmable interfaces to existing applications. Van Rossum's vision of a small core language with a large standard library and an easily extensible interpreter stemmed from his frustrations with ABC, which represented the opposite approach. Python claims to strive for a simpler, less-cluttered syntax and grammar, while giving developers a choice in their coding methodology. Python lacks do .. while loops, which Rossum considered harmful. In contrast to Perl's motto "there is more than one way to do it", Python advocates an approach where "there should be one – and preferably only one – obvious way to do it". In practice, however, Python provides many ways to achieve a given goal. There are at least three ways to format a string literal, with no certainty as to which one a programmer should use. Alex Martelli is a Fellow at the Python Software Foundation and Python book author; he wrote that "To describe something as 'clever' is not considered a compliment in the Python culture." Python's developers typically prioritize readability over performance. For example, they reject patches to non-critical parts of the CPython reference implementation that would offer increases in speed that do not justify the cost of clarity and readability. Execution speed can be improved by moving speed-critical functions to extension modules written in languages such as C, or by using a just-in-time compiler like PyPy. Also, it is possible to transpile to other languages. However, this approach either fails to achieve the expected speed-up, since Python is a very dynamic language, or only a restricted subset of Python is compiled (with potential minor semantic changes). Python is meant to be a fun language to use. This goal is reflected in the name – a tribute to the British comedy group Monty Python – and in playful approaches to some tutorials and reference materials. For instance, some code examples use the terms "spam" and "eggs" (in reference to a Monty Python sketch), rather than the typical terms "foo" and "bar". A common neologism in the Python community is pythonic, which has a broad range of meanings related to program style: Pythonic code may use Python idioms well; be natural or show fluency in the language; or conform with Python's minimalist philosophy and emphasis on readability. === Enhancement Proposals === Python Enhancement Proposals are a design document for either providing information to the Python community, or proposal for new feature in Python. PEPs are intented to explain new processes in Python, provide naming conventions or document the processes in the language. PEPs are overseen by Python Steering Council. There are 3 kinds of PEPs, with those are being standards track PEP, Informational PEP and Process PEPs which has their own unique meanings. They were firstly introduced in 2000, in

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  Neural network Gaussian process

  A Neural Network Gaussian Process (NNGP) is a Gaussian process (GP) obtained as the limit of a certain type of sequence of neural networks. Specifically, a wide variety of network architectures converges to a GP in the infinitely wide limit, in the sense of distribution. The concept constitutes an intensional definition, i.e., a NNGP is just a GP, but distinguished by how it is obtained. == Motivation == Bayesian networks are a modeling tool for assigning probabilities to events, and thereby characterizing the uncertainty in a model's predictions. Deep learning and artificial neural networks are approaches used in machine learning to build computational models which learn from training examples. Bayesian neural networks merge these fields. They are a type of neural network whose parameters and predictions are both probabilistic. While standard neural networks often assign high confidence even to incorrect predictions, Bayesian neural networks can more accurately evaluate how likely their predictions are to be correct. Computation in artificial neural networks is usually organized into sequential layers of artificial neurons. The number of neurons in a layer is called the layer width. When we consider a sequence of Bayesian neural networks with increasingly wide layers (see figure), they converge in distribution to a NNGP. This large width limit is of practical interest, since the networks often improve as layers get wider. And the process may give a closed form way to evaluate networks. NNGPs also appears in several other contexts: It describes the distribution over predictions made by wide non-Bayesian artificial neural networks after random initialization of their parameters, but before training; it appears as a term in neural tangent kernel prediction equations; it is used in deep information propagation to characterize whether hyperparameters and architectures will be trainable. It is related to other large width limits of neural networks. === Scope === The first correspondence result had been established in the 1995 PhD thesis of Radford M. Neal, then supervised by Geoffrey Hinton at University of Toronto. Neal cites David J. C. MacKay as inspiration, who worked in Bayesian learning. Today the correspondence is proven for: Single hidden layer Bayesian neural networks; deep fully connected networks as the number of units per layer is taken to infinity; convolutional neural networks as the number of channels is taken to infinity; transformer networks as the number of attention heads is taken to infinity; recurrent networks as the number of units is taken to infinity. In fact, this NNGP correspondence holds for almost any architecture: Generally, if an architecture can be expressed solely via matrix multiplication and coordinatewise nonlinearities (i.e., a tensor program), then it has an infinite-width GP. This in particular includes all feedforward or recurrent neural networks composed of multilayer perceptron, recurrent neural networks (e.g., LSTMs, GRUs), (nD or graph) convolution, pooling, skip connection, attention, batch normalization, and/or layer normalization. === Illustration === Every setting of a neural network's parameters θ {\displaystyle \theta } corresponds to a specific function computed by the neural network. A prior distribution p ( θ ) {\displaystyle p(\theta )} over neural network parameters therefore corresponds to a prior distribution over functions computed by the network. As neural networks are made infinitely wide, this distribution over functions converges to a Gaussian process for many architectures. The notation used in this section is the same as the notation used below to derive the correspondence between NNGPs and fully connected networks, and more details can be found there. The figure to the right plots the one-dimensional outputs z L ( ⋅ ; θ ) {\displaystyle z^{L}(\cdot ;\theta )} of a neural network for two inputs x {\displaystyle x} and x ∗ {\displaystyle x^{}} against each other. The black dots show the function computed by the neural network on these inputs for random draws of the parameters from p ( θ ) {\displaystyle p(\theta )} . The red lines are iso-probability contours for the joint distribution over network outputs z L ( x ; θ ) {\displaystyle z^{L}(x;\theta )} and z L ( x ∗ ; θ ) {\displaystyle z^{L}(x^{};\theta )} induced by p ( θ ) {\displaystyle p(\theta )} . This is the distribution in function space corresponding to the distribution p ( θ ) {\displaystyle p(\theta )} in parameter space, and the black dots are samples from this distribution. For infinitely wide neural networks, since the distribution over functions computed by the neural network is a Gaussian process, the joint distribution over network outputs is a multivariate Gaussian for any finite set of network inputs. == Discussion == === Infinitely wide fully connected network === This section expands on the correspondence between infinitely wide neural networks and Gaussian processes for the specific case of a fully connected architecture. It provides a proof sketch outlining why the correspondence holds, and introduces the specific functional form of the NNGP for fully connected networks. The proof sketch closely follows the approach by Novak and coauthors. ==== Network architecture specification ==== Consider a fully connected artificial neural network with inputs x {\displaystyle x} , parameters θ {\displaystyle \theta } consisting of weights W l {\displaystyle W^{l}} and biases b l {\displaystyle b^{l}} for each layer l {\displaystyle l} in the network, pre-activations (pre-nonlinearity) z l {\displaystyle z^{l}} , activations (post-nonlinearity) y l {\displaystyle y^{l}} , pointwise nonlinearity ϕ ( ⋅ ) {\displaystyle \phi (\cdot )} , and layer widths n l {\displaystyle n^{l}} . For simplicity, the width n L + 1 {\displaystyle n^{L+1}} of the readout vector z L {\displaystyle z^{L}} is taken to be 1. The parameters of this network have a prior distribution p ( θ ) {\displaystyle p(\theta )} , which consists of an isotropic Gaussian for each weight and bias, with the variance of the weights scaled inversely with layer width. This network is illustrated in the figure to the right, and described by the following set of equations: x ≡ input y l ( x ) = { x l = 0 ϕ ( z l − 1 ( x ) ) l > 0 z i l ( x ) = ∑ j W i j l y j l ( x ) + b i l W i j l ∼ N ( 0 , σ w 2 n l ) b i l ∼ N ( 0 , σ b 2 ) ϕ ( ⋅ ) ≡ nonlinearity y l ( x ) , z l − 1 ( x ) ∈ R n l × 1 n L + 1 = 1 θ = { W 0 , b 0 , … , W L , b L } {\displaystyle {\begin{aligned}x&\equiv {\text{input}}\\y^{l}(x)&=\left\{{\begin{array}{lcl}x&&l=0\\\phi \left(z^{l-1}(x)\right)&&l>0\end{array}}\right.\\z_{i}^{l}(x)&=\sum _{j}W_{ij}^{l}y_{j}^{l}(x)+b_{i}^{l}\\W_{ij}^{l}&\sim {\mathcal {N}}\left(0,{\frac {\sigma _{w}^{2}}{n^{l}}}\right)\\b_{i}^{l}&\sim {\mathcal {N}}\left(0,\sigma _{b}^{2}\right)\\\phi (\cdot )&\equiv {\text{nonlinearity}}\\y^{l}(x),z^{l-1}(x)&\in \mathbb {R} ^{n^{l}\times 1}\\n^{L+1}&=1\\\theta &=\left\{W^{0},b^{0},\dots ,W^{L},b^{L}\right\}\end{aligned}}} ==== ==== z l | y l {\displaystyle z^{l}|y^{l}} is a Gaussian process We first observe that the pre-activations z l {\displaystyle z^{l}} are described by a Gaussian process conditioned on the preceding activations y l {\displaystyle y^{l}} . This result holds even at finite width. Each pre-activation z i l {\displaystyle z_{i}^{l}} is a weighted sum of Gaussian random variables, corresponding to the weights W i j l {\displaystyle W_{ij}^{l}} and biases b i l {\displaystyle b_{i}^{l}} , where the coefficients for each of those Gaussian variables are the preceding activations y j l {\displaystyle y_{j}^{l}} . Because they are a weighted sum of zero-mean Gaussians, the z i l {\displaystyle z_{i}^{l}} are themselves zero-mean Gaussians (conditioned on the coefficients y j l {\displaystyle y_{j}^{l}} ). Since the z l {\displaystyle z^{l}} are jointly Gaussian for any set of y l {\displaystyle y^{l}} , they are described by a Gaussian process conditioned on the preceding activations y l {\displaystyle y^{l}} . The covariance or kernel of this Gaussian process depends on the weight and bias variances σ w 2 {\displaystyle \sigma _{w}^{2}} and σ b 2 {\displaystyle \sigma _{b}^{2}} , as well as the second moment matrix K l {\displaystyle K^{l}} of the preceding activations y l {\displaystyle y^{l}} , z i l ∣ y l ∼ G P ( 0 , σ w 2 K l + σ b 2 ) K l ( x , x ′ ) = 1 n l ∑ i y i l ( x ) y i l ( x ′ ) {\displaystyle {\begin{aligned}z_{i}^{l}\mid y^{l}&\sim {\mathcal {GP}}\left(0,\sigma _{w}^{2}K^{l}+\sigma _{b}^{2}\right)\\K^{l}(x,x')&={\frac {1}{n^{l}}}\sum _{i}y_{i}^{l}(x)y_{i}^{l}(x')\end{aligned}}} The effect of the weight scale σ w 2 {\displaystyle \sigma _{w}^{2}} is to rescale the contribution to the covariance matrix from K l {\displaystyle K^{l}} , while the bias is shared for all inputs, and so σ b 2 {\displaystyle \sigma _{b}^{2}} makes the z i l {\displaystyle z_{i}^{l}} for different datapoints more similar and

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  Likewise, Inc.

  Likewise, Inc., is an American technology startup company which provides a social networking service for finding and saving content recommendations for movies, TV shows, books, and podcasts. A team of ex-Microsoft employees founded Likewise in October 2017 with financial investment from Microsoft co-founder Bill Gates. The company is led by CEO Ian Morris and as of 2020 had a team of about 35 employees. Its headquarters operates in Bellevue, Washington. As of July 2020, 1 million users had joined the platform. == History == === Ideation (October 2017) === In 2017, former Microsoft Communications Chief Larry Cohen came up with the idea for Likewise in Bill Gates’ private office, Gates Ventures. Cohen currently serves as Gates Ventures’ CEO and managing partner. Cohen collaborated with colleagues Michael Dix and Ian Morris to co-found what would become Likewise, with Morris as its CEO. Gates funded the company's early development. The company developed its platform in stealth mode before launching publicly in October 2018. === Release (October 2018) === Likewise officially released its platform in the US and Canada on October 3, 2018. === Growth (2020 COVID-19 pandemic) === Likewise experienced accelerated growth alongside the COVID-19 pandemic. From March 2020 to July 2020, the platform's monthly active users tripled in numbers. The company reached one million users in July 2020. == Applications == === Mobile === Likewise is available as a mobile app for the Android and iOS mobile operating systems. Users receive recommendations from the Likewise algorithm, people they follow, and the Likewise editorial team. === Likewise TV === In October 2019, the company launched its Apple TV app called Likewise TV. The television app organizes shows across streaming services under one watchlist. On July 20, 2020, Likewise TV expanded to Android TV and Amazon Fire TV users.

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  Protocol engineering

  Protocol engineering is the application of systematic methods to the development of communication protocols. It uses many of the principles of software engineering, but it is specific to the development of distributed systems. == History == When the first experimental and commercial computer networks were developed in the 1970s, the concept of protocols was not yet well developed. These were the first distributed systems. In the context of the newly adopted layered protocol architecture (see OSI model), the definition of the protocol of a specific layer should be such that any entity implementing that specification in one computer would be compatible with any other computer containing an entity implementing the same specification, and their interactions should be such that the desired communication service would be obtained. On the other hand, the protocol specification should be abstract enough to allow different choices for the implementation on different computers. It was recognized that a precise specification of the expected service provided by the given layer was important. It is important for the verification of the protocol, which should demonstrate that the communication service is provided if both protocol entities implement the protocol specification correctly. This principle was later followed during the standardization of the OSI protocol stack, in particular for the transport layer. It was also recognized that some kind of formalized protocol specification would be useful for the verification of the protocol and for developing implementations, as well as test cases for checking the conformance of an implementation against the specification. While initially mainly finite-state machine were used as (simplified) models of a protocol entity, in the 1980s three formal specification languages were standardized, two by ISO and one by ITU. The latter, called SDL, was later used in industry and has been merged with UML state machines. == Principles == The following are the most important principles for the development of protocols: Layered architecture: A protocol layer at the level n consists of two (or more) entities that have a service interface through which the service of the layer is provided to the users of the protocol, and which uses the service provided by a local entity of level (n-1). The service specification of a layer describes, in an abstract and global view, the behavior of the layer as visible at the service interfaces of the layer. The protocol specification defines the requirements that should be satisfied by each entity implementation. Protocol verification consists of showing that two (or more) entities satisfying the protocol specification will provide at their service interfaces the specified service of that layer. The (verified) protocol specification is used mainly for the following two activities: The development of an entity implementation. Note that the abstract properties of the service interface are defined by the service specification (and also used by the protocol specification), but the detailed nature of the interface can be chosen during the implementation process, separately for each entity. Test suite development for conformance testing. Protocol conformance testing checks that a given entity implementation conforms to the protocol specification. The conformance test cases are developed based on the protocol specification and are applicable to all entity implementations. Therefore standard conformance test suites have been developed for certain protocol standards. == Methods and tools == Tools for the activities of protocol verification, entity implementation and test suite development can be developed when the protocol specification is written in a formalized language which can be understood by the tool. As mentioned, formal specification languages have been proposed for protocol specification, and the first methods and tools where based on finite-state machine models. Reachability analysis was proposed to understand all possible behaviors of a distributed system, which is essential for protocol verification. This was later complemented with model checking. However, finite-state descriptions are not powerful enough to describe constraints between message parameters and the local variables in the entities. Such constraints can be described by the standardized formal specification languages mentioned above, for which powerful tools have been developed. It is in the field of protocol engineering that model-based development was used very early. These methods and tools have later been used for software engineering as well as hardware design, especially for distributed and real-time systems. On the other hand, many methods and tools developed in the more general context of software engineering can also be used of the development of protocols, for instance model checking for protocol verification, and agile methods for entity implementations. == Constructive methods for protocol design == Most protocols are designed by human intuition and discussions during the standardization process. However, some methods have been proposed for using constructive methods possibly supported by tools to automatically derive protocols that satisfy certain properties. The following are a few examples: Semi-automatic protocol synthesis: The user defines all message sending actions of the entities, and the tool derives all necessary reception actions (even if several messages are in transit). Synchronizing protocol: The state transitions of one protocol entity are given by the user, and the method derives the behavior of the other entity such that it remains in states that correspond to the former entity. Protocol derived from service specification: The service specification is given by the user and the method derives a suitable protocol for all entities. Protocol for control applications: The specification of one entity (called the plant - which must be controlled) is given, and the method derives a specification of the other entity such that certain fail states of the plant are never reached and certain given properties of the plant's service interactions are satisfied. This is a case of supervisory control. == Books == Ming T. Liu, Protocol Engineering, Advances in Computers, Volume 29, 1989, Pages 79–195. G.J. Holzmann, Design and Validation of Computer Protocols, Prentice Hall, 1991. H. König, Protocol Engineering, Springer, 2012. M. Popovic, Communication Protocol Engineering, CRC Press, 2nd Ed. 2018. P. Venkataram, S.S. Manvi, B.S. Babu, Communication Protocol Engineering, 2014.

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  Yahoo Groups

  Yahoo! Groups was a free-to-use system of electronic mailing lists offered by Yahoo!. Prior to February 2020, Yahoo! Groups was one of the world's largest collections of online discussion boards. It allowed members to subscribe to various groups, read subscribed discussions online, view and share photos, files and bookmarks within a group, access a group calendar, create polls for group members, and receive email notifications of new discussion topics. Some groups were simply announcement boards, to which only the group moderators could post, while others were discussion forums. Depending on each group's settings, membership could be open to everyone or only to invited or approved people. On February 1, 2020, Yahoo! removed online access to discussions and all other features except simple membership management, essentially turning all groups into mailing lists, and on October 13, 2020, it announced that Yahoo Groups would shut down completely on December 15, 2020. == History == In 1998 Yahoo! Clubs was launched as an extension of services developed by Yahoo! Messenger. In August 2000 Yahoo acquired eGroups.com. Yahoo! Groups was launched in early 2001 as an integration of technology from eGroups.com and community groups from both eGroups.com and Yahoo! Clubs. In 2001 Yahoo! deleted adult groups from its search directory, making it very difficult to locate Yahoo! groups with adult content. The Groups Updates Email feature was introduced in 2010. It summarized, in a single email, all the updates that occurred every twenty-four hours in all groups. In September 2010, a major facelift was rolled out, making Yahoo! Groups look very similar to Facebook. In December, Yahoo! Groups Japan emailed its users and posted a notice on its homepage, to announce that its service, which commenced in February 2004, would be closing on May 28, 2014. In October 2019, Yahoo! announced that all content that had been posted to Yahoo! Groups will be deleted on December 14, 2019; that date was later amended to January 31, 2020. Yahoo! announced that adding new content would be blocked on October 28, 2019. Once the content was deleted, users of Yahoo! Groups were only able to browse the group directory, request invitations and, if members of a group, send messages to that group. On October 13, 2020, Yahoo! announced they would be shutting down Yahoo! Groups on December 15, 2020. The site was closed down a few days after the advertised date, displaying a message that the service was officially shut down. This message stopped appearing at the end of January 2021 and the Yahoo! Groups web address began redirecting to the main Yahoo! page. === Criticism and controversy === On August 31, 2010, Yahoo! Groups started rolling out a major software change, which was denounced by a large number of users. The re-model was completely abandoned on January 12, 2011. == Site statistics == In August 2008, Yahoo! Group staff reported that there were 113 million users, and nine million Groups using 22 languages. In July 2010, the web analytics website Quantcast reported around 915 thousand unique visitors daily to the Yahoo! Groups website (US). In January 2011, that number had increased to 933 thousand unique visitors daily. The number did not include Yahoo! Group members who accessed the Groups site via email. In September 2010, at its "Product Runway" event, Yahoo! told reporters that Yahoo! Groups had 115 million group members and that there were 10 million Yahoo! groups. == Archives ==

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  Lessac Technologies

  Lessac Technologies, Inc. (LTI) is an American firm which develops voice synthesis software, licenses technology and sells synthesized novels as MP3 files. The firm currently has seven patents granted and three more pending for its automated methods of converting digital text into human-sounding speech, more accurately recognizing human speech and outputting the text representing the words and phrases of said speech, along with recognizing the speaker's emotional state. The LTI technology is partly based on the work of the late Arthur Lessac, a Professor of Theater at the State University of New York and the creator of Lessac Kinesensic Training, and LTI has licensed exclusive rights to exploit Arthur Lessac's copyrighted works in the fields of speech synthesis and speech recognition. Based on the view that music is speech and speech is music, Lessac's work and books focused on body and speech energies and how they go together. Arthur Lessac's textual annotation system, which was originally developed to assist actors, singers, and orators in marking up scripts to prepare for performance, is adapted in LTI's speech synthesis system as the basic representation of the speech to be synthesized (Lessemes), in contrast to many other systems which use a phonetic representation. LTI's software has two major components: (1) a linguistic front-end that converts plain text to a sequence of prosodic and phonosensory graphic symbols (Lessemes) based on Arthur Lessac's annotation system, which specify the speech units to be synthesized; (2) a signal-processing back-end that takes the Lessemes as acoustic data and produces human-sounding synthesized speech as output, using unit selection and concatenation. LTI's text-to-speech system came in second in the world-wide Blizzard Challenge 2011 and 2012. The first-place team in 2011 also employed LTI's "front-end" technology, but with its own back-end. The Blizzard Challenge, conducted by the Language Technologies Institute of Carnegie Mellon University, was devised as a way to evaluate speech synthesis techniques by having different research groups build voices from the same voice-actor recordings, and comparing the results through listening tests. LTI was founded in 2000 by H. Donald Wilson (chairman), a lawyer, LexisNexis entrepreneur and business associate of Arthur Lessac; and Gary A. Marple (chief inventor), after Marple suggested that Arthur Lessac's kinesensic voice training might be applicable to computational linguistics. After Wilson's death in 2006, his nephew John Reichenbach became the firm's CEO.

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  Wix.com

  Wix.com Ltd. (Hebrew: וויקס.קום, romanized: wix.com) or simply Wix is an Israeli software company, publicly listed in the US, that provides cloud-based web development services. It offers tools for creating HTML5 websites for desktop and mobile platforms using online drag-and-drop editing. Along with its headquarters and other offices in Israel, Wix also has offices in Brazil, Canada, Germany, India, Ireland, Japan, Lithuania, Poland, the Netherlands, the United States, Ukraine, and Singapore. Users can add applications for social media, e-commerce, online marketing, contact forms, e-mail marketing, and community forums to their websites. The Wix website builder is built on a freemium business model, earning its revenues through premium upgrades. According to the W3Techs technology survey website, Wix was used by 2.5% of websites as of September 2023; at the end of May 2025, it was 3.8%. == History == === Corporate affairs === Wix was founded in 2006 by Israeli developers Avishai Abrahami, Nadav Abrahami, and Giora Kaplan. With its main offices in Tel Aviv, Wix was backed by investors Insight Venture Partners, Mangrove Capital Partners, Bessemer Venture Partners, DAG Ventures, and Benchmark Capital. By April 2010, Wix had 3.5 million users and raised US$10 million in Series C funding provided by Benchmark Capital and existing investors Bessemer Venture Partners and Mangrove Capital Partners. In March 2011, Wix had 8.5 million users and raised US$40 million in Series D funding, bringing its total funding to that date to US$61 million. By August 2013, the Wix platform had more than 34 million registered users. On 5 November 2013, Wix had an initial public offering on NASDAQ, raising about US$127 million for the company and some share holders. In 2016, Mark Tluszcz became the chair of the board of directors. In 2020, Wix's revenue increased to $989 million, a 30% rise year-on-year, primarily due to the shift of businesses online during the coronavirus pandemic. The company added over 31 million new registered users in 2020, reaching a total of 196.7 million by year's end. Wix added approximately 1 million net new premium subscriptions in 2020, surpassing $1 billion in annual collections for the first time. By the end of the year, there were 5.5 million premium subscriptions, a 22% increase compared to the end of 2019. As of its most recent reporting in June 2024, Wix has over 260 million users worldwide. === Product development === ==== 2000s ==== Wix entered an open beta phase in 2007 using a platform based on Adobe Flash. ==== 2010s ==== In June 2011, Wix launched the Facebook store module, making its first step into social commerce. In March 2012, Wix launched a new HTML5 site builder, replacing the Adobe Flash technology. In October 2012, Wix launched an app market for users to sell applications built with the company's automated web development technology. In August 2014, Wix launched Wix Hotels, a booking system for hotels, bed and breakfasts, and vacation rentals that use Wix websites. In June 2016, Wix introduced Wix ADI (Artificial Design Intelligence), a platform that uses artificial intelligence to design websites. ==== 2020s ==== In 2020, Wix launched an additional CMS, EditorX, which included additional CSS features to the original builder. In July 2023, Wix announced that it would be building on its ADI technology to create an AI powered website generator In October 2023, Wix launched the Wix Studio website builder. Co-founder and CEO, Avishai Abrahami described the platform as a “product for agencies”. In March 2024, the AI web builder, which uses a chatbot to help users create content was launched to the public. In March 2025, the digital publisher CNET has identified Wix as the "Best overall website builder overall." In August 2025, Wix announced it would launch banking services—including checking accounts and loans for small businesses—via a partnership with Israeli fintech Unit Finance, as it sought to diversify amid what it described as threats to its core website-building business from artificial intelligence. In January 2026, Wix launched Wix Harmony. Wix harmony is an AI website builder that uses agentic technology, generative design and vibe coding—with manual editing features for additional control. In May 2026, Wix announced layoffs affecting approximately 1,000 employees, or 20% of its workforce. CEO Avishai Abrahami cited two factors: the need to restructure around artificial intelligence and the appreciation of the Israeli shekel against the US dollar, which increased the cost of its Israel-based workforce relative to its dollar-denominated revenue. === Acquisitions === In April 2014, Wix announced the acquisition of Appixia, an Israeli startup for creating native mobile commerce (mCommerce) apps. In October 2014, Wix announced its acquisition of OpenRest, a developer of online ordering systems for restaurants. In April 2015, Wix acquired Moment.me, a mobile website builder for events and marketing tools for social lead generation. On 23 February 2017, Wix acquired the online art community DeviantArt for US$36 million. In January 2017, the company acquired Flok, a provider of customer loyalty programs tools. In February 2020, Wix acquired Inkfrog for eBay sellers, a web design company that provides customized business management software for eBay sellers. On 2 March 2021, Wix acquired SpeedETab, a Miami-based restaurant online technology provider. In May 2021, Wix acquired Rise.ai, a gift card and customer re-engagement package for online brands. A month later, Wix acquired Modalyst, a marketplace and drop-shipping platform. In May 2025, Wix acquired Hour One, a startup specializing in AI-powered video creation tools, to enhance its generative AI capabilities. In June 2025, the company acquired Base44, owned by independent entrepreneur Maor Shlomo, with the intention of integrating Base44's artificial intelligence capabilities and conversational interface into Wix's website and app building platform. == Description == Wix uses a freemium business model. Users can create websites for free then must purchase premium packages to connect their sites to their own domains, remove Wix ads, access the form builder, add e-commerce capabilities, or buy extra data storage and bandwidth. Wix provides customizable website templates and a drag-and-drop HTML5 website builder that includes apps, graphics, image galleries, fonts, vectors, animations, and other options. Users also may opt to create their web sites from scratch. In October 2013, Wix introduced a mobile editor for mobile viewing customization. Wix App Market offers both free and subscription-based applications, with a revenue split of 80% for the developer and 20% for Wix. Customers can integrate third-party applications into their own web sites, such as photograph feeds, blogging, music playlists, online community, e-mail marketing, and file management. Custom JavaScript code can be inserted into Wix webpages using the Velo API. == Controversies == === Use of WordPress code === In October 2016, there was a controversy over Wix's use of WordPress's GPL-licensed code. In response, Avishai Abrahami, Wix's CEO, published a response describing which open-source code was used and how Wix says it collaborates with the open-source community. However, it was subsequently noted that collaboration with the open-source community was not sufficient under the terms of the GPL license, which requires any code built on GPL-licensed code to be released under the same license. === Censorship === On 31 May 2021, 2021 Hong Kong Charter, a Wix-hosted website run by exiled Hong Kong activists, was shut down at the request of the Hong Kong Police. This was the first known case of Hong Kong's National Security Law being used to censor content on an overseas website. Wix later apologized for "mistakenly removing the website" and reinstated the website after it had been down for four days. In October 2023, Wix fired an employee in Dublin, Ireland, for having made social media posts critical of Israel. This incident led to criticism of Wix from members of the Oireachtas (the Irish parliament) and from the head of the Irish government, Taoiseach Leo Varadkar, who said it was "not okay to dismiss somebody because of their political views". Deputy head of government, Tánaiste Micheál Martin, also condemned their dismissal, stating "we tolerate debate with freedom of speech, freedom of opinion, and people have different opinions on these issues." The dismissed employee, Courtney Carey, successfully sued the company for unfair dismissal. Wix did not contest the charge, admitting liability. === Outreach abroad === In October 2023, The Irish Times reported that an Israeli advertising agency advised Wix staff how they can tailor posts for "outreach abroad". This included advice for Wix employees to “show Westernity” in social media posts supporting Israel, stating that “unlike the Gazans,

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  DevOps toolchain

  A DevOps toolchain is a set or combination of tools that aid in the delivery, development, and management of software applications throughout the systems development life cycle, as coordinated by an organization that uses DevOps practices. Generally, DevOps tools fit into one or more activities, which supports specific DevOps initiatives: Plan, Create, Verify, Package, Release, Configure, Monitor, and Version Control. == Toolchains == In software, a toolchain is the set of programming tools that is used to perform a complex software development task or to create a software product, which is typically another computer program or a set of related programs. In general, the tools forming a toolchain are executed consecutively so the output or resulting environment state of each tool becomes the input or starting environment for the next one, but the term is also used when referring to a set of related tools that are not necessarily executed consecutively. As DevOps is a set of practices that emphasizes the collaboration and communication of both software developers and other information technology (IT) professionals, while automating the process of software delivery and infrastructure changes, its implementation can include the definition of the series of tools used at various stages of the lifecycle; because DevOps is a cultural shift and collaboration between development and operations, there is no one product that can be considered a single DevOps tool. Instead a collection of tools, potentially from a variety of vendors, are used in one or more stages of the lifecycle. == Stages of DevOps == === Plan === Plan consists of two elements: "define" and "plan". This activity refers to the business value and application requirements. Specifically "Plan" activities include: Production metrics, objects and feedback Requirements Business metrics Update release metrics Release plan, timing and business case Security policy and requirement A combination of the IT personnel will be involved in these activities: business application owners, software development, software architects, continual release management, security officers and the organization responsible for managing the production of IT infrastructure. === Create === Create consists of the building, coding, and configuring of the software development process. The specific activities are: Design of the software and configuration Coding including code quality and performance Software build and build performance Release candidate Tools and vendors in this category often overlap with other categories. Because DevOps is about breaking down silos, this is reflective in the activities and product solutions. === Verify === Verify is directly associated with ensuring the quality of the software release; activities designed to ensure code quality is maintained and the highest quality is deployed to production. The main activities in this are: Acceptance testing Regression testing Security and vulnerability analysis Performance Configuration testing Solutions for verify-related activities generally fall under four main categories: Test automation, Static analysis, Test Lab, and Security. === Package === Package refers to the activities involved once the release is ready for deployment, often also referred to as staging or Preproduction / "preprod". This often includes tasks and activities such as: Approval/preapprovals Package configuration Triggered releases Release staging and holding === Release === Release related activities include schedule, orchestration, provisioning and deploying software into production and targeted environment. The specific Release activities include: Release coordination Deploying and promoting applications Fallbacks and recovery Scheduled/timed releases Solutions that cover this aspect of the toolchain include application release automation, deployment automation and release management. === Configure === Configure activities fall under the operation side of DevOps. Once software is deployed, there may be additional IT infrastructure provisioning and configuration activities required. Specific activities including: Infrastructure storage, database and network provisioning and configuring Application provision and configuration. The main types of solutions that facilitate these activities are continuous configuration automation, configuration management, and infrastructure as code tools. === Monitor === Monitoring is an important link in a DevOps toolchain. It allows IT organization to identify specific issues of specific releases and to understand the impact on end-users. A summary of Monitor related activities are: Performance of IT infrastructure End-user response and experience Production metrics and statistics Information from monitoring activities often impacts Plan activities required for changes and for new release cycles. === Version Control === Version Control is an important link in a DevOps toolchain and a component of software configuration management. Version Control is the management of changes to documents, computer programs, large web sites, and other collections of information. A summary of Version Control related activities are: Non-linear development Distributed development Compatibility with existent systems and protocols Toolkit-based design Information from Version Control often supports Release activities required for changes and for new release cycles.

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