AI Code Vulnerability Scanner

AI Code Vulnerability Scanner — independent reviews, comparisons, pricing and step-by-step guides on Aizhi.

AUTINDEX

AUTINDEX is a commercial text mining software package based on sophisticated linguistics. AUTINDEX, resulting from research in information extraction, is a product of the Institute of Applied Information Sciences (IAI) which is a non-profit institute that has been researching and developing language technology since its foundation in 1985. IAI is an institute affiliated to Saarland University in Saarbrücken, Germany. AUTINDEX is the result of a number of research projects funded by the EU (Project BINDEX), by Deutsche Forschungsgemeinschaft and the German Ministry for Economy. Amongst the latter there are the projects LinSearch, and WISSMER, see also the reference to IAI-Website. The basic functionality of AUTINDEX is the extraction of key words from a document to represent the semantics of the document. Ideally the system is integrated with a thesaurus that defines the standardised terms to be used for key word assignment. AUTINDEX is used in library applications (e.g. integrated in dandelon.com) as well as in high quality (expert) information systems, and in document management and content management environments. Together with AUTINDEX a number of additional software comes along such as an integration with Apache Solr / Lucene to provide a complete information retrieval environment, a classification and categorisation system on the basis of a machine learning software that assigns domains to the document, and a system for searching with semantically similar terms that are collected in so called tag clouds.
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Mike Little

Mike Little (born 12 May 1962) is an English web developer and writer. He is the co-founder of the free and open source web publishing software WordPress. == Biography == Mike Little was born in Manchester, England in 1962 to a Nigerian father, who was a mathematics lecturer and musician, and an English mother who worked as a primary school teacher. Little was placed into foster care when he was four months of age, and was later adopted by the same family. He grew up on a council estate in Brinnington, Stockport, and was educated at Stockport School. In 2003, Little and Matt Mullenweg started working on a project in which they built on b2/cafelog and later named it WordPress, releasing the first version on 27 May 2003. Little states that, despite not being invited to join his co-founder's for-profit business Automattic, he and Mullenweg remain on good terms. He clarified: "I don’t want it to sound like he cheated me out of something or ripped me off in some way. He didn’t." In June 2013, Little was awarded the SAScon's "Outstanding Contribution to Digital" award for his part in co-founding and developing WordPress. Little has been described as "modest" and living in "virtual anonymity". He has one daughter. He identifies as a follower of Stoicism and a humanist, and in 2021, he became a patron of charity Humanists UK.
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Raseef22

Raseef22 (Arabic: رصيف22) is a liberal Arabic media network founded in 2013 based in Beirut, Lebanon. It publishes content in Arabic and English from different Arab states and describes itself as an independent media platform. International Media Support mentions Raseef22 along with HuffPost Arabic and Al Jazeera as one of the biggest Pan-Arab online platforms. == Name == The Arabic word raseef (رَصِيف) means platform or pavement, and the number 22 refers to the number of states in the Arab League. == History == Kareem Sakka co-founded Raseef22 in the aftermath of the Arab Spring, which he cites as a source of inspiration. In an article in The Washington Post, he wrote that Raseef22 was created as a "digital space for those eager to know what was going on around them." Raseef22 was one of the 500 websites censored in Egypt in late 2017 after it published an article on Egyptian security agencies' vies to influence the media. After the site was blocked in Egypt, it was targeted in a cyber attack that took it offline in locations around the world. Jamal Khashoggi wrote for Raseef22 regularly. One of his notable articles was "Notes on the Freedom of the Arabs from Oslo, Norway," published June 5, 2018. The site was blocked in Saudi Arabia December 2018 when the Saudi Ministry of Communications and Information Technology ordered its censorship due to its "unprecedented response to the assassination of Jamal Khashoggi in Istanbul." This decision might have also been related to Raseef22's coverage of Saudi-Israeli relations and interviews with activists later imprisoned or placed under house arrest coverage In 2019 the Association of LGBT Journalists (AJL) in Paris gave Raseef22 a golden foreign press award for its six-month series of articles on gender and sexuality issues. == Readership == According to its publisher in 2019, the news agency counted 12 million readers annually from 22 Arab nations. Of the readership, he wrote that it "believes in the talent and promise of the Arab mind and sees the ugliness of tyranny, patriarchy, misogyny and the futility of proxy rulers and wars." Al-Quds Al-Arabi described Raseef22 as "oriented to the youth."
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Digital media service

A digital media service (DMS) is an online service provider that sells access to digital library of content such as films, software, games, images, literature, etc. While no transfer of property is made, a nearly perfect duplicate of the data (song movie, etc.) is made on a customer's computer. Content is either primarily hosted on a dedicated server, which is owned by the service provider, or it is hosted primarily on the hard drives of its customers using a P2P protocol with, perhaps, a dedicated server to supplement. == History == One example of the older business model is the iTunes Store, which still markets and prices data as individual retail products. There are no examples of the latter business model in operation yet, but one is currently in development by Global Gaming Factory X and expected to begin operation some time after they acquire The Pirate Bay domain on August 27, 2009. A key difference between the two models is that the model which relies on its customer base for offering their bandwidth for other customers to access customer hosted data can operate at significantly lower costs than a company that seeks to limit data access to a per-download fee in order to supplement the cost of using its own hosting and bandwidth. The P2P model holds the potential for companies to offer unlimited access to the largest data library in the history of the internet to its customers for a reasonably low membership rate that is relevant to the cost of operation. While the market is virtually untouched, the P2P supplemented model will need entrepreneurs who are able to overcome a series of challenges in order to compete with the older business model as well as that which is offered for free (and often against the wishes of copyright holders) by hundreds of P2P communities on the internet. These challenges include, but are not limited to: Offering better data quality, speed, convenience and ease of use, protocol, sense of security, indexing and search organization, site up time, data library size, customer support, advertising, artist/copyright holder incentives and compensation, incentives and compensation for customers hosting data and providing bandwidth, guaranteed seeding (available access to indexed data at all times), than competitors.
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Gallery software

Gallery software is software that helps the user publish or share photos, pictures, videos or other digital media. Most galleries are located on Web servers, where users are allowed to register and publish their pictures. Gallery software usually features automatic image resizing, allows digital media be categorized into sets, and allows comments. == Types == Early digital media publishing and sharing was done with imageboards. The boards are by topics, sometimes called "chan". Each discussion in a "chan" are started with a piece of digital media, and follow-up discussions can contain another piece too. Software works in this way: Futallaby, Danbooru. Traditionally, galleries are managed. An administrator maintains a set of or hierarchy of albums. The users can upload their digital media in one of the existing albums defined by an administrator, or create their own albums. The users with sufficient permission can re-categorise the digital media others uploaded. Often, the site's administrator can define which album the users are allowed to categorise their media into, or delete other user's content. Examples are open source galleries Coppermine, Gallery Project. There are decentralised gallery software that does not have an administrator for managing contents. Pinterest, Flickr and DeviantArt has been successful with this model. Open source gallery software MediaGoblin works in this way. Each user can create their own "collections", to categorise theirs or other users' media. However users cannot put media into other user's collections. Each user's category is separate. There is no centralised theme or hierarchy for the media.
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Directed-energy weapon wildfire conspiracy theories

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

A group (often termed as a community, e-group or club) is a feature in many social networking services which allows users to create, post, comment to and read from their own interest- and niche-specific forums, often within the realm of virtual communities. Groups, which may allow for open or closed access, invitation and/or joining by other users outside the group, are formed to provide mini-networks within the larger, more diverse social network service. Much like electronic mailing lists, they are also owned and maintained by owners, moderators, or managers, who can edit posts to discussion threads and regulate member behavior within the group. However, unlike traditional Internet forums and mailing lists, groups in social networking services allow owners and moderators alike to share account credentials between groups without having to log in to every group. == History == The rise of the World Wide Web resulted in an expansion of the varieties of methods for communication on the Internet, much of which was limited in the 1980s to discussion in newsgroups, BBS and chat rooms. While the initial rise of web-based mass communication took place in the form of early Internet forums in the mid-1990s, a few services such as MSN Groups, Yahoo! Groups and eGroups pioneered the combination of web-based mailing list archives with user profiles; by 2000, such services doubled as full-fledged mailing lists and Internet forums, allowing users to create an extremely large variety of discussion and networking mediums with comparatively sparse thresholds of complexity. Further features included chat rooms (often Java-based), image and video galleries, and group calendars. The second spurt of bullecalbel networking, one which was less dependent upon mailing list-related features and more upon Internet forum features, began in the early- to mid-2000s in the form of such services as LiveJournal, Friendster, MySpace and Facebook. These services continued the evolution of the web-based e-group as a discussion and organization medium. In the late 2000s, services such as Yammer and Micromobs further advanced e-group communication by taking advantage of microblog-style activity streams. == In virtual worlds == In Second Life, groups are centered less around discussion forums (as such, an asynchronous conferencing feature is not built into the Second Life network as of 2009) and common interest, and are more centered on maintenance of a particular geographic location inside the network. Such groups are often created by the owners of areas such as buildings, plots of land or whole islands in order to cater to the most frequent visitors and patrons of the regions. With the limited asynchronous messaging capability of Second Life, groups are also a means of mass-emailing announcements pertinent to the group, but are not completely capable of hosting discussion or deliberation of such announcement messages. == The importance of online social networking groups == Before people expanded their social life to the internet, they had small circles. These included the networks gained from rural areas or villages, such as family, friends and neighbors, and community groups such as churches. These networks represented a social safety net to support individuals. Since we have moved a huge part of our social life to the internet, online social networking groups have become a way to maintain a structure in social life. Online networking is made up by clusters of people, bounding themselves together on the World Wide Web. To be able to sort out the many different clusters we belong to we use online groups to helps us arrange and make sense of all our contacts. This sense-making is rooted within us, we sort and put people into compartments or sort by categories to make sense and try to understand our relationships to the people around us. Online social networking groups therefore enables us to do the same thing online. Online social networks have a huge impact on people’s lives. Since the social network revolution has offered people with more loose ties and diversity in their relationships, it creates both stress and opportunities. Furthermore, the Internet revolution has transformed the contact point from a household to the individual. In addition, people are in constant communication with each other due to the mobile revolution. All in all, the mentioned revolutions created a new social operating system: "networked individualism". The way that people currently connect, communicate and exchange information can be described as a form of operating system because of the similarities between the structure of computer systems and the networked individualism that has taken form in society. These structures consist of unwritten rules, norms, constraints and opportunities which are apparent for those who are part of a specific network. == Concerns == There is some research claiming that fake news is infiltrating online social networking. A recent study claimed that people exposed to fake news generally revert to their original opinion even after finding out the information they were given was false.
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Digital backlot

A digital backlot or virtual backlot is a motion-picture set that is neither a genuine location nor a constructed studio; the shooting takes place entirely on a stage with a blank background (often a greenscreen) that will later on project an artificial environment put in during post-production. Digital backlots are mainly used for genres such as science fiction, where building a real set would be too expensive or outright impossible. == Notable films == Among the first films to introduce the technique was Mini Moni the Movie by Shinji Higuchi in 2002, predated by Rest In Peace by Stolpskott Film (2000). Others include: === Released === Rest in Peace (Sweden, 2000) – Shot entirely with green-screen. Some sections fully CGI. Casshern (Japan, 2004) – Shot on celluloid. A few practical set pieces used. Able Edwards (United States, 2004) – Shot digitally on Canon XL1 cameras. Immortal (France, 2004) – Shot on celluloid. Also showed CGI characters interacting with live actors. Sky Captain and the World of Tomorrow (United States, 2004) – Shot digitally on Sony CineAlta cameras. Sin City (United States, 2005) – Shot digitally on CineAlta cameras. Three practical sets used. MirrorMask (United States/United Kingdom, 2005) – Shot on celluloid. 80% of film uses digital backlot. Some practical set pieces used. The Cabinet of Dr. Caligari (United States, 2005) – Shot digitally. 300 (United States, 2007) – Shot on celluloid. Two practical sets used. Speed Racer (United States, 2008) – Directed by the Wachowskis. Three practical sets used. The Spirit (United States, 2008) – Director Frank Miller shot the film with the same techniques he and Robert Rodriguez used on Sin City. Avatar (United States, 2009) – Directed by James Cameron. Two practical sets used. Goemon (Japan, 2009) – The second film from Casshern helmer Kazuaki Kiriya. Alice in Wonderland (United States, 2010) – Directed by Tim Burton. Practical sets used. Sin City: A Dame to Kill For (United States 2014) – Co-directed by Robert Rodriguez and Frank Miller. Sequel to Sin City. === Upcoming === Tribes of October
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Photometric stereo

Photometric stereo is a technique in computer vision for estimating the surface normals of objects by observing that object under different lighting conditions (photometry). It is based on the fact that the amount of light reflected by a surface is dependent on the orientation of the surface in relation to the light source and the observer. By measuring the amount of light reflected into a camera, the space of possible surface orientations is limited. Given enough light sources from different angles, the surface orientation may be constrained to a single orientation or even overconstrained. The technique was originally introduced by Woodham in 1980. The special case where the data is a single image is known as shape from shading, and was analyzed by B. K. P. Horn in 1989. Photometric stereo has since been generalized to many other situations, including extended light sources and non-Lambertian surface finishes. Current research aims to make the method work in the presence of projected shadows, highlights, and non-uniform lighting. Photometric stereo is widely used in various fields, including archaeology, cultural heritage conservation, and quality control. It is now integrated into widely used open-source software, such as Meshroom. == Basic method == Under Woodham's original assumptions — Lambertian reflectance, known point-like distant light sources, and uniform albedo — the problem can be solved by inverting the linear equation I = L ⋅ n {\displaystyle I=L\cdot n} , where I {\displaystyle I} is a (known) vector of m {\displaystyle m} observed intensities, n {\displaystyle n} is the (unknown) surface normal, and L {\displaystyle L} is a (known) 3 × m {\displaystyle 3\times m} matrix of normalized light directions. This model can easily be extended to surfaces with non-uniform albedo, while keeping the problem linear. Taking an albedo reflectivity of k {\displaystyle k} , the formula for the reflected light intensity becomes I = k ( L ⋅ n ) . {\displaystyle I=k(L\cdot n).} If L {\displaystyle L} is square (there are exactly 3 lights) and non-singular, it can be inverted, giving L − 1 I = k n . {\displaystyle L^{-1}I=kn.} Since the normal vector is known to have length 1, k {\displaystyle k} must be the length of the vector k n {\displaystyle kn} , and n {\displaystyle n} is the normalised direction of that vector. If L {\displaystyle L} is not square (there are more than 3 lights), a generalisation of the inverse can be obtained using the Moore–Penrose pseudoinverse, by simply multiplying both sides with L T {\displaystyle L^{T}} , giving L T I = L T k ( L ⋅ n ) , {\displaystyle L^{T}I=L^{T}k(L\cdot n),} ( L T L ) − 1 L T I = k n , {\displaystyle (L^{T}L)^{-1}L^{T}I=kn,} after which the normal vector and albedo can be solved as described above. == Non-Lambertian surfaces == The classical photometric stereo problem concerns itself only with Lambertian surfaces, with perfectly diffuse reflection. This is unrealistic for many types of materials, especially metals, glass and smooth plastics, and will lead to aberrations in the resulting normal vectors. Many methods have been developed to lift this assumption. In this section, a few of these are listed. === Specular reflections === Historically, in computer graphics, the commonly used model to render surfaces started with Lambertian surfaces and progressed first to include simple specular reflections. Computer vision followed a similar course with photometric stereo. Specular reflections were among the first deviations from the Lambertian model. These are a few adaptations that have been developed. Many techniques ultimately rely on modelling the reflectance function of the surface, that is, how much light is reflected in each direction. This reflectance function has to be invertible. The reflected light intensities towards the camera is measured, and the inverse reflectance function is fit onto the measured intensities, resulting in a unique solution for the normal vector. === General BRDFs and beyond === According to the Bidirectional reflectance distribution function (BRDF) model, a surface may distribute the amount of light it receives in any outward direction. This is the most general known model for opaque surfaces. Some techniques have been developed to model (almost) general BRDFs. In practice, all of these require many light sources to obtain reliable data. These are methods in which surfaces with general BRDFs can be measured. Determine the explicit BRDF prior to scanning. To do this, a different surface is required that has the same or a very similar BRDF, of which the actual geometry (or at least the normal vectors for many points on the surface) is already known. The lights are then individually shone upon the known surface, and the amount of reflection into the camera is measured. Using this information, a look-up table can be created that maps reflected intensities for each light source to a list of possible normal vectors. This puts constraints on the possible normal vectors the surface may have, and reduces the photometric stereo problem to an interpolation between measurements. Typical known surfaces to calibrate the look-up table with are spheres for their wide variety of surface orientations. Restricting the BRDF to be symmetrical. If the BRDF is symmetrical, the direction of the light can be restricted to a cone about the direction to the camera. Which cone this is depends on the BRDF itself, the normal vector of the surface, and the measured intensity. Given enough measured intensities and the resulting light directions, these cones can be approximated and therefore the normal vectors of the surface. Some progress has been made towards modelling an even more general surfaces, such as Spatially Varying Bidirectional Distribution Functions (SVBRDF), Bidirectional surface scattering reflectance distribution functions (BSSRDF), and accounting for interreflections. However, such methods are still fairly restrictive in photometric stereo. Better results have been achieved with structured light. == Uncalibrated photometric stereo == Uncalibrated Photometric Stereo is an approach in photometric stereo that aims to reconstruct the 3D shape of an object from images captured under unknown lighting conditions. Unlike classical methods, which often assume controlled or known lighting setups, this approach removes these constraints, making it adaptable to diverse and real-world environments. The advent of deep learning has revolutionized universal PS by replacing handcrafted assumptions with data-driven models. Recent approaches leverage Transformer-based architectures and multi-scale encoder–decoder networks to directly estimate surface normals from input images. Uncalibrated Photometric Stereo is inherently an ill-posed problem, as it attempts to recover 3D shape and lighting conditions simultaneously from images alone. This leads to fundamental ambiguities in the reconstruction process, which manifest as systematic errors in the recovered geometry, including global distortions in the object's overall shape, and misinterpretation of surface orientation, where concave regions may appear convex and vice versa. To address the challenges of uncalibrated photometric stereo, hybrid methods have emerged that combine multi-view stereo and photometric stereo. These approaches leverage the strengths of both techniques, including geometric reliability and resolution.
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Distributed operating system

A distributed operating system is system software over a collection of independent software, networked, communicating, and physically separate computational nodes. They handle jobs which are serviced by multiple CPUs. Each individual node holds a specific software subset of the global aggregate operating system. Each subset is a composite of two distinct service provisioners. The first is a ubiquitous minimal kernel, or microkernel, that directly controls that node's hardware. Second is a higher-level collection of system management components that coordinate the node's individual and collaborative activities. These components abstract microkernel functions and support user applications. The microkernel and the management components collection work together. They support the system's goal of integrating multiple resources and processing functionality into an efficient and stable system. This seamless integration of individual nodes into a global system is referred to as transparency, or single system image; describing the illusion provided to users of the global system's appearance as a single computational entity. == Description == A distributed OS provides the essential services and functionality required of an OS but adds attributes and particular configurations to allow it to support additional requirements such as increased scale and availability. To a user, a distributed OS works in a manner similar to a single-node, monolithic operating system. That is, although it consists of multiple nodes, it appears to users and applications as a single-node. Separating minimal system-level functionality from additional user-level modular services provides a "separation of mechanism and policy". Mechanism and policy can be simply interpreted as "what something is done" versus "how something is done," respectively. This separation increases flexibility and scalability. == Overview == === The kernel === At each locale (typically a node), the kernel provides a minimally complete set of node-level utilities necessary for operating a node's underlying hardware and resources. These mechanisms include allocation, management, and disposition of a node's resources, processes, communication, and input/output management support functions. Within the kernel, the communications sub-system is of foremost importance for a distributed OS. In a distributed OS, the kernel often supports a minimal set of functions, including low-level address space management, thread management, and inter-process communication (IPC). A kernel of this design is referred to as a microkernel. Its modular nature enhances reliability and security, essential features for a distributed OS. === System management === System management components are software processes that define the node's policies. These components are the part of the OS outside the kernel. These components provide higher-level communication, process and resource management, reliability, performance and security. The components match the functions of a single-entity system, adding the transparency required in a distributed environment. The distributed nature of the OS requires additional services to support a node's responsibilities to the global system. In addition, the system management components accept the "defensive" responsibilities of reliability, availability, and persistence. These responsibilities can conflict with each other. A consistent approach, balanced perspective, and a deep understanding of the overall system can assist in identifying diminishing returns. Separation of policy and mechanism mitigates such conflicts. === Working together as an operating system === The architecture and design of a distributed operating system must realize both individual node and global system goals. Architecture and design must be approached in a manner consistent with separating policy and mechanism. In doing so, a distributed operating system attempts to provide an efficient and reliable distributed computing framework allowing for an absolute minimal user awareness of the underlying command and control efforts. The multi-level collaboration between a kernel and the system management components, and in turn between the distinct nodes in a distributed operating system is the functional challenge of the distributed operating system. This is the point in the system that must maintain a perfect harmony of purpose, and simultaneously maintain a complete disconnect of intent from implementation. This challenge is the distributed operating system's opportunity to produce the foundation and framework for a reliable, efficient, available, robust, extensible, and scalable system. However, this opportunity comes at a very high cost in complexity. === The price of complexity === In a distributed operating system, the exceptional degree of inherent complexity could easily render the entire system an anathema to any user. As such, the logical price of realizing a distributed operation system must be calculated in terms of overcoming vast amounts of complexity in many areas, and on many levels. This calculation includes the depth, breadth, and range of design investment and architectural planning required in achieving even the most modest implementation. These design and development considerations are critical and unforgiving. For instance, a deep understanding of a distributed operating system's overall architectural and design detail is required at an exceptionally early point. An exhausting array of design considerations are inherent in the development of a distributed operating system. Each of these design considerations can potentially affect many of the others to a significant degree. This leads to a massive effort in balanced approach, in terms of the individual design considerations, and many of their permutations. As an aid in this effort, most rely on documented experience and research in distributed computing power. == History == Research and experimentation efforts began in earnest in the 1970s and continued through the 1990s, with focused interest peaking in the late 1980s. A number of distributed operating systems were introduced during this period; however, very few of these implementations achieved even modest commercial success. Fundamental and pioneering implementations of primitive distributed operating system component concepts date to the early 1950s. Some of these individual steps were not focused directly on distributed computing, and at the time, many may not have realized their important impact. These pioneering efforts laid important groundwork, and inspired continued research in areas related to distributed computing. In the mid-1970s, research produced important advances in distributed computing. These breakthroughs provided a solid, stable foundation for efforts that continued through the 1990s. The accelerating proliferation of multi-processor and multi-core processor systems research led to a resurgence of the distributed OS concept. === The DYSEAC === One of the first efforts was the DYSEAC, a general-purpose synchronous computer. In one of the earliest publications of the Association for Computing Machinery, in April 1954, a researcher at the National Bureau of Standards – now the National Institute of Standards and Technology (NIST) – presented a detailed specification of the DYSEAC. The introduction focused upon the requirements of the intended applications, including flexible communications, but also mentioned other computers: Finally, the external devices could even include other full-scale computers employing the same digital language as the DYSEAC. For example, the SEAC or other computers similar to it could be harnessed to the DYSEAC and by use of coordinated programs could be made to work together in mutual cooperation on a common task… Consequently[,] the computer can be used to coordinate the diverse activities of all the external devices into an effective ensemble operation. The specification discussed the architecture of multi-computer systems, preferring peer-to-peer rather than master-slave. Each member of such an interconnected group of separate computers is free at any time to initiate and dispatch special control orders to any of its partners in the system. As a consequence, the supervisory control over the common task may initially be loosely distributed throughout the system and then temporarily concentrated in one computer, or even passed rapidly from one machine to the other as the need arises. …the various interruption facilities which have been described are based on mutual cooperation between the computer and the external devices subsidiary to it, and do not reflect merely a simple master-slave relationship. This is one of the earliest examples of a computer with distributed control. The Dept. of the Army reports certified it reliable and that it passed all acceptance tests in April 1954. It was completed and delivered on time, in May 1954. This was a "portable comput
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Prix Ars Electronica

The Prix Ars Electronica is one of the best known and longest running yearly prizes in the field of electronic and interactive art, computer animation, digital culture and music. It has been awarded since 1987 by Ars Electronica (Linz, Austria). In 2005, the Golden Nica, the highest prize, was awarded in six categories: "Computer Animation/Visual Effects," "Digital Musics," "Interactive Art," "Net Vision," "Digital Communities" and the "u19" award for "freestyle computing." Each Golden Nica came with a prize of €10,000, apart from the u19 category, where the prize was €5,000. In each category, there are also Awards of Distinction and Honorary Mentions. The Golden Nica trophy is a replica of the Greek Nike of Samothrace. It is a handmade gold-plated wooden statuette that is approximately 35 cm high with a wingspan of about 20 cm. "Prix Ars Electronica" is a phrase composed of French, Latin and Spanish words, loosely translated as "Electronic Arts Prize." == Golden Nica winners == === Computer animation / film / vfx === The "Computer Graphics" category (1987–1994) was open to different kinds of computer images. The "Computer Animation" (1987–1997) was replaced by the current "Computer Animation/Visual Effects" category in 1998. ==== Computer Graphics ==== 1987 – Figur10 by Brian Reffin Smith, UK 1988 – The Battle by David Sherwin, US 1989 – Gramophone by Tamás Waliczky, HU 1990 – P-411-A by Manfred Mohr, Germany 1991 – Having encountered Eve for the second time, Adam begins to speak by Bill Woodard, US 1992 – RD Texture Buttons by Michael Kass and Andrew Witkin, US 1993 – Founders Series by Michael Tolson, US 1994 – Jellylife / Jellycycle / Jelly Locomotion by Michael Joaquin Grey, US ==== Computer Animation ==== 1987 – Luxo Jr. by John Lasseter, US 1988 – Red's Dream by John Lasseter, US 1989 – Broken Heart by Joan Staveley, US 1990 – Footprint by Mario Sasso and Nicola Sani, IT 1991 – Panspermia by Karl Sims, US 1992 – Liquid Selves / Primordial Dance by Karl Sims, US 1993 – Lakmé by Pascal Roulin, BE 1994 – Jurassic Park by Dennis Muren, Mark Dippé and Steve Williams, US/CA Distinction: Quarxs by Maurice Benayoun, FR Distinction: K.O. Kid by Marc Caro, FR 1995 – God's Little Monkey by David Atherton and Bob Sabiston, US 1996 – Toy Story by John Lasseter, Lee Unkrich and Ralph Eggleston, US 1997 – Dragonheart by Scott Squires, Industrial Light & Magic (ILM), US ==== Computer Animation/Visual Effects ==== 1998 – The Sitter by Liang-Yuan Wang, TW Titanic by Robert Legato and Digital Domain, US 1999 – Bunny by Chris Wedge, US What Dreams May Come by Mass Illusions, POP, Digital Domain, Vincent Ward, Stephen Simon and Barnet Bain, US 2000 – Maly Milos by Jakub Pistecky, CA Maaz by Christian Volckman, FR 2001 – Le Processus by Xavier de l’Hermuzičre and Philippe Grammaticopoulos, FR 2002 – Monsters, Inc. by Andrew Stanton, Lee Unkrich, Pete Docter and David Silverman, US 2003 – Tim Tom by Romain Segaud and Cristel Pougeoise, FR 2004 – Ryan by Chris Landreth, US. Distinction: Parenthèse from Francois Blondeau, Thibault Deloof, Jérémie Droulers, Christophe Stampe, France Distinction: Birthday Boy from Sejong Park, Australia 2005 – Fallen Art by Tomek Baginski, Poland. Distinction: The Incredibles from Pixar Distinction: City Paradise by Gaëlle Denis (UK), Passion Pictures (FR) 2006 – 458nm by Jan Bitzer, Ilija Brunck, Tom Weber, Filmakademie Baden-Württemberg, Germany. Distinction: Kein platz Für Gerold by Daniel Nocke / Studio Film Bilder, Germany Distinction: Negadon, the monster from Mars, by Jun Awazu, Japan 2007 – Codehunters by Ben Hibon, (UK) 2008 – Madame Tutli-Putli by Chris Lavis, Maciek Szczerbowski. (Directors), Jason Walker (Special Visual Effects), National Film Board of Canada 2009 – HA'Aki by Iriz Pääbo, National Film Board of Canada 2010 – Nuit Blanche by Arev Manoukian (Director), Marc-André Gray (Visual Effects Artist), National Film Board of Canada 2011 – Metachaos by Alessandro Bavari (IT) 2012 – Rear Window Loop by Jeff Desom (LU) Distinction: Caldera by Evan Viera/Orchid Animation (US) Distinction: Rise of the Planet of the Apes by Weta Digital (NZ)/Twentieth Century Fox 2013 – Forms by Quayola (IT), Memo Akten (TR) Distinction: Duku Spacemarines by La Mécanique du Plastique (FR) Distinction: Oh Willy… by Emma De Swaef (BE), Marc James Roels (BE) / Beast Animation 2014 – Walking City by Universal Everything (UK) 2015 – Temps Mort by Alex Verhaest (BE)[1] Distinction: Bär by Pascal Floerks (DE) Distinction: The Reflection of Power by Mihai Grecu (RO/HU) === Digital Music === This category is for those making electronic music and sound art through digital means. From 1987 to 1998 the category was known as "Computer music." Two Golden Nicas were awarded in 1987, and none in 1990. There was no Computer Music category in 1991. 1987 – Peter Gabriel and Jean-Claude Risset 1988 – Denis Smalley 1989 – Kaija Saariaho 1990 – None 1991 – Category omitted 1992 – Alejandro Viñao 1993 – Bernard Parmegiani 1994 – Ludger Brümmer Distinction: Jonathan Impett 1995 – Trevor Wishart 1996 – Robert Normandeau 1997 – Matt Heckert 1998 – Peter Bosch and Simone Simons (joint award) 1999 – Come to Daddy by Aphex Twin (Richard D. James) and Chris Cunningham (joint award) Distinction: Birthdays by Ikue Mori (JP) Distinction: Mego (label), Hotel Paral.lel by Christian Fennesz, Seven Tons For Free by Peter Rehberg (a.k.a. Pita) 2000 – 20' to 2000 by Carsten Nicolai Distinction: Minidisc by Gescom Distinction: Outside the Circle of Fire by Chris Watson 2001 – Matrix by Ryoji Ikeda 2002 – Man'yo Wounded 2001 by Yasunao Tone 2003 – Ami Yoshida, Sachiko M and Utah Kawasaki (joint award) 2004 – Banlieue du Vide by Thomas Köner 2005 – TEO! A Sonic Sculpture by Maryanne Amacher 2006 – L'île ré-sonante by Éliane Radigue 2007 – Reverse-Simulation Music by Mashiro Miwa 2008 – Reactable by Sergi Jordà (ES), Martin Kaltenbrunner (AT), Günter Geiger (AT) and Marcos Alonso (ES) 2009 – Speeds of Time versions 1 and 2 by Bill Fontana (US) 2010 – rheo: 5 horizons by Ryoichi Kurokawa (JP) 2011 – Energy Field by Jana Winderen (NO) 2012 – "Crystal Sounds of a Synchrotron" by Jo Thomas (GB) 2013 – frequencies (a) by Nicolas Bernier (CA) Distinction: SjQ++ by SjQ++ (JP) Distinction: Borderlands Granular by Chris Carlson (US) 2015 – Chijikinkutsu by Nelo Akamatsu (JP) Distinction: Drumming is an elastic concept by Josef Klammer (AT) Distinction: Under Way by Douglas Henderson (DE) 2017 – Not Your World Music: Noise In South East Asia by Cedrik Fermont (CD/BE/DE), Dimitri della Faille (BE/CA) Distinction: Gamelan Wizard by Lucas Abela (AU), Wukir Suryadi (ID) und Rully Shabara (ID) Distinction: Corpus Nil by Marco Donnarumma (DE/IT) === Hybrid art === 2007 – Symbiotica 2008 – Pollstream – Nuage Vert by Helen Evans (FR/UK) and Heiko Hansen (FR/DE) HeHe 2009 – Natural History of the Enigma by Eduardo Kac (US) 2010 – Ear on Arm by Stelarc (AU) 2011 – May the Horse Live in me by Art Orienté Objet (FR) 2012 – Bacterial radio by Joe Davis (US) Distinction: Free Universal Construction Kit (F.U.C.K.) by Golan Levin and Shawn Sims 2013 – Cosmopolitan Chicken Project, Koen Vanmechelen (BE) 2015 – Plantas Autofotosintéticas, Gilberto Esparza (MX) 2017 – K-9_topology, Maja Smrekar (SI) === [the next idea] voestalpine Art and Technology Grant === 2009 – Open_Sailing by Open_Sailing Crew led by Cesar Harada. 2010 – Hostage by [Frederik De Wilde]. 2011 – Choke Point Project by P2P Foundation (NL). 2012 – qaul.net – tools for the next revolution by Christoph Wachter & Mathias Jud 2013 – Hyperform by Marcelo Coelho (BR), Skylar Tibbits (US), Natan Linder (IL), Yoav Reaches (IL) Honorary Mentions: GravityLight by Martin Riddiford (GB), Jim Reeves (GB) 2014 – BlindMaps by Markus Schmeiduch, Andrew Spitz and Ruben van der Vleuten 2015 – SOYA C(O)U(L)TURE by XXLab (ID) – Irene Agrivina Widyaningrum, Asa Rahmana, Ratna Djuwita, Eka Jayani Ayuningtias, Atinna Rizqiana === Interactive Art === Prizes in the category of interactive art have been awarded since 1990. This category applies to many categories of works, including installations and performances, characterized by audience participation, virtual reality, multimedia and telecommunication. 1990 – Videoplace installation by Myron Krueger 1991 – Think About the People Now project by Paul Sermon 1992 – Home of the Brain installation by Monika Fleischmann and Wolfgang Strauss 1993 – Simulationsraum-Mosaik mobiler Datenklänge (smdk) installation by Knowbotic Research 1994 – A-Volve environment by Christa Sommerer and Laurent Mignonneau 1995 – the concept of Hypertext, attributed to Tim Berners-Lee 1996 – Global Interior Project installation by Masaki Fujihata 1997 – Music Plays Images X Images Play Music concert by Ryuichi Sakamoto and Toshio Iwai 1998 – World Skin, a Photo Safari in the Land of War installation by Jean-Baptiste Barrière and Maurice Benayoun 1999 – Difference Engine #3 by construct and Lynn Hershman 2000 – Vectorial Elevati
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WebGL

WebGL (short for Web Graphics Library) is a JavaScript API for rendering interactive 2D and 3D graphics within any compatible web browser without the use of plug-ins. WebGL is fully integrated with other web standards, allowing GPU-accelerated usage of physics, image processing, and effects in the HTML canvas. WebGL elements can be mixed with other HTML elements and composited with other parts of the page or page background. WebGL programs consist of control code written in JavaScript, and shader code written in OpenGL ES Shading Language (GLSL ES, sometimes referred to as ESSL), a language similar to C or C++. WebGL code is executed on a computer's GPU. WebGL is designed and maintained by the non-profit Khronos Group. On February 9, 2022, Khronos Group announced WebGL 2.0 support from all major browsers. From 2024, a new graphics API, WebGPU, is being developed to supersede WebGL. WebGPU provides extended capabilities, a more modern interface, and direct GPU access, which is useful for demanding graphics as well as AI applications. == Design == WebGL 1.0 is based on OpenGL ES 2.0 and provides an API for 3D graphics. It uses the HTML5 canvas element and is accessed using Document Object Model (DOM) interfaces. WebGL 2.0 is based on OpenGL ES 3.0. It guarantees the availability of many optional extensions of WebGL 1.0, and exposes new APIs. Automatic memory management is provided implicitly by JavaScript. Like OpenGL ES 2.0, WebGL lacks the fixed-function APIs introduced in OpenGL 1.0 and deprecated in OpenGL 3.0. This functionality, if required, has to be implemented by the developer using shader code and JavaScript. Shaders in WebGL are written in GLSL and passed to the WebGL API as text strings. The WebGL implementation compiles these strings to GPU code. This code is executed for each vertex sent through the API and for each pixel rasterized to the screen. == History == WebGL evolved out of the Canvas 3D experiments started by Vladimir Vukićević at Mozilla. Vukićević first demonstrated a Canvas 3D prototype in 2006. By the end of 2007, both Mozilla and Opera had made their own separate implementations. In early 2009, the non-profit technology consortium Khronos Group started the WebGL Working Group, with initial participation from Apple, Google, Mozilla, Opera, and others. Version 1.0 of the WebGL specification was released March 2011. An early application of WebGL was Zygote Body. In November 2012 Autodesk announced that they ported most of their applications to the cloud running on local WebGL clients. These applications included Autodesk Fusion and AutoCAD. Development of the WebGL 2 specification started in 2013 and finished in January 2017. The specification is based on OpenGL ES 3.0. First implementations are in Firefox 51, Chrome 56 and Opera 43. == Implementations == === Almost Native Graphics Layer Engine === Almost Native Graphics Layer Engine (ANGLE) is an open source graphic engine which implements WebGL 1.0 (2.0 which closely conforms to ES 3.0) and OpenGL ES 2.0 and 3.0 standards. It is a default backend for both Google Chrome and Mozilla Firefox on Windows platforms and works by translating WebGL and OpenGL calls to available platform-specific APIs. ANGLE currently provides access to OpenGL ES 2.0 and 3.0 to desktop OpenGL, OpenGL ES, Direct3D 9, and Direct3D 11 APIs. ″[Google] Chrome uses ANGLE for all graphics rendering on Windows, including the accelerated Canvas2D implementation and the Native Client sandbox environment.″ == Software == WebGL is widely supported by modern browsers. However, its availability depends on other factors, too, like whether the GPU supports it. The official WebGL website offers a simple test page. More detailed information (like what renderer the browser uses, and what extensions are available) can be found at third-party websites. === Desktop browsers === Source: Google Chrome – WebGL 1.0 has been enabled on all platforms that have a capable graphics card with updated drivers since version 9, released in February 2011. By default on Windows, Chrome uses the ANGLE (Almost Native Graphics Layer Engine) renderer to translate OpenGL ES to Direct X 9.0c or 11.0, which have better driver support. However, on Linux and Mac OS X, the default renderer is OpenGL. It is also possible to force OpenGL as the renderer on Windows. Since September 2013, Chrome also has a newer Direct3D 11 renderer, which requires a newer graphics card. Chrome 56+ supports WebGL 2.0. Firefox – WebGL 1.0 has been enabled on all platforms that have a capable graphics card with updated drivers since version 4.0. Since 2013 Firefox also uses DirectX on the Windows platform via ANGLE. Firefox 51+ supports WebGL 2.0. Safari – Safari 6.0 and newer versions installed on OS X Mountain Lion, Mac OS X Lion and Safari 5.1 on Mac OS X Snow Leopard implemented support for WebGL 1.0, which was disabled by default before Safari 8.0. Safari version 12 (available in MacOS Mojave) has available support for WebGL 2.0 as an "Experimental" feature. Safari 15 enables WebGL 2.0 for all users. Opera – WebGL 1.0 has been implemented in Opera 11 and 12, but was disabled by default in 2014. Opera 43+ supports WebGL 2.0. Internet Explorer – WebGL 1.0 is partially supported in Internet Explorer 11. Internet Explorer initially failed most of the official WebGL conformance tests, but Microsoft later released several updates. The latest 0.94 WebGL engine currently passes ≈97% of Khronos tests. WebGL support can also be manually added to earlier versions of Internet Explorer using third-party plugins such as IEWebGL. Microsoft Edge – For Microsoft Edge Legacy, the initial stable release supports WebGL version 0.95 (context name: "experimental-webgl") with an open source GLSL to HLSL transpiler. Version 10240+ supports WebGL 1.0 as prefixed. Latest Chromium-based Edge supports WebGL 2.0. === Mobile browsers === Google Chrome – WebGL 1.0 is supported on Android as of Chrome 25. WebGL 2.0 is supported on Android as of Chrome 58. Chrome is used for the Android system webview as of Android 5. Firefox for mobile – WebGL 1.0 is available for Android devices since Firefox 4. Safari on iOS – WebGL 1.0 is available for mobile Safari in iOS 8. WebGL 2.0 is available for mobile Safari in iOS 15. Microsoft Edge – Prefixed WebGL 1.0 was available on Windows 10 Mobile.. Latest Chromium-based Edge supports WebGL 2.0. Opera Mobile – Opera Mobile 12 supports WebGL 1.0 (on Android only). Sailfish OS – WebGL 1.0 is supported in the default Sailfish browser. Tizen – WebGL 1.0 is supported == Tools and ecosystem == === Utilities === The low-level nature of the WebGL API, which provides little on its own to quickly create desirable 3D graphics, motivated the creation of higher-level libraries that abstract common operations (e.g. loading scene graphs and 3D objects in certain formats; applying linear transformations to shaders or view frustums). Some such libraries were ported to JavaScript from other languages. Examples of libraries that provide high-level features include A-Frame (VR), BabylonJS, PlayCanvas, three.js, OSG.JS, Google’s model-viewer and CopperLicht. Web3D also made a project called X3DOM to make X3D and VRML content run on WebGL. === Games === There has been an emergence of 2D and 3D game engines for WebGL, such as Unreal Engine 4 and Unity. The Stage3D/Flash-based Away3D high-level library also has a port to WebGL via TypeScript. A more light-weight utility library that provides just the vector and matrix math utilities for shaders is sylvester.js. It is sometimes used in conjunction with a WebGL specific extension called glUtils.js. There are also some 2D libraries built atop WebGL, like Cocos2d-x or Pixi.js, which were implemented this way for performance reasons in a move that parallels what happened with the Starling Framework over Stage3D in the Flash world. The WebGL-based 2D libraries fall back to HTML5 canvas when WebGL is not available. Removing the rendering bottleneck by giving almost direct access to the GPU has exposed performance limitations in the JavaScript implementations. Some were addressed by asm.js and WebAssembly (similarly, the introduction of Stage3D exposed performance problems within ActionScript, which were addressed by projects like CrossBridge). === Content creation === As with any other graphics API, creating content for WebGL scenes requires using a 3D content creation tool and exporting the scene to a format that is readable by the viewer or helper library. Desktop 3D authoring software such as Blender, Autodesk Maya or SimLab Composer can be used for this purpose. In particular, Blend4Web allows a WebGL scene to be authored entirely in Blender and exported to a browser with a single click, even as a standalone web page. There are also some WebGL-specific software such as CopperCube and the online WebGL-based editor Clara.io. Online platforms such as Sketchfab and Clara.io allow users to directly upload their 3D models
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Machine learning

Machine learning (ML) is a field of study in artificial intelligence concerned with the development and study of statistical algorithms that can learn from data and generalize to unseen data, and thus perform tasks without being explicitly programmed. Advances in the field of deep learning have allowed neural networks, a class of statistical algorithms, to surpass many previous machine learning approaches in performance. Statistics and mathematical optimisation methods compose the foundations of machine learning. Data mining is a related field of study, focusing on exploratory data analysis (EDA) through unsupervised learning. From a theoretical viewpoint, probably approximately correct learning provides a mathematical and statistical framework for describing machine learning. Most traditional machine learning and deep learning algorithms can be described as empirical risk minimisation under this framework. == History == The term machine learning was coined in 1959 by Arthur Samuel, an IBM employee and pioneer in the field of computer gaming and artificial intelligence. The synonym self-teaching computers was also used during this time period. The earliest machine learning program was introduced in the 1950s, when Samuel invented a computer program that calculated the chance of winning in checkers for each side, but the history of machine learning is rooted in decades of efforts to study human cognitive processes. In 1949, Canadian psychologist Donald Hebb published the book The Organization of Behavior, in which he introduced a theoretical neural structure formed by certain interactions among nerve cells. The Hebbian theory of neuron interaction set the groundwork for how many machine learning algorithms work, with connected artificial neurons changing the strength of their connections based on data. Other researchers who have studied human cognitive systems contributed to the modern machine learning technologies as well, including Walter Pitts and Warren McCulloch, who proposed the first mathematical model of neural networks including algorithms that mirror human thought processes. By the early 1960s, an experimental "learning machine" with punched tape memory, called Cybertron, had been developed by Raytheon Company to analyse sonar signals, electrocardiograms, and speech patterns using rudimentary reinforcement learning. It was repetitively "trained" by a human operator/teacher to recognise patterns and equipped with a "goof" button to cause it to reevaluate incorrect decisions. A representative book on research into machine learning during the 1960s was Nils Nilsson's book "Learning Machines", dealing mostly with machine learning for pattern classification. Interest related to pattern recognition continued into the 1970s, as described by Duda and Hart in 1973. In 1981, a report was given on using teaching strategies so that an artificial neural network learns to recognise 40 characters (26 letters, 10 digits, and 4 special symbols) from a computer terminal. Tom M. Mitchell provided a widely quoted, more formal definition of the algorithms studied in the machine learning field: "A computer program is said to learn from experience E with respect to some class of tasks T and performance measure P if its performance at tasks in T, as measured by P, improves with experience E." This definition of the tasks in which machine learning is concerned is fundamentally operational rather than defining the field in cognitive terms. This follows Alan Turing's proposal in his paper "Computing Machinery and Intelligence", in which the question, "Can machines think?", is replaced by asking whether machines can convincingly imitate a human in its responses to human-posed questions. In 2014 Ian Goodfellow and others introduced generative adversarial networks (GANs) which could produce realistic synthetic data. By 2016 AlphaGo had won against top human players in Go using reinforcement learning techniques. == Relationships to other fields == === Artificial intelligence === As a scientific endeavour, machine learning grew out of the quest for artificial intelligence (AI). In the early days of AI as an academic discipline, some researchers were interested in having machines learn from data. They attempted to approach the problem with various symbolic methods, as well as what were then termed "neural networks"; these were mostly perceptrons and other models that were later found to be reinventions of the generalised linear models of statistics. Probabilistic reasoning was also employed, especially in automated medical diagnosis. However, an increasing emphasis on the logical, knowledge-based approach caused a rift between AI and machine learning. Probabilistic systems were plagued by theoretical and practical problems of data acquisition and representation. By 1980, expert systems had come to dominate AI, and statistics was out of favour. Work on symbolic/knowledge-based learning continued within AI, leading to inductive logic programming (ILP), but the more statistical line of research was now outside the field of AI proper, in pattern recognition and information retrieval. Neural network research was abandoned by AI and computer science around the same time. This subfield, termed "connectionism", was continued by researchers from other disciplines, including John Hopfield, David Rumelhart, and Geoffrey Hinton. Their main success came in the mid-1980s with the reinvention of backpropagation. Machine learning (ML), reorganised and recognised as its own field, started to flourish in the 1990s. The field changed its goal from achieving artificial intelligence to tackling solvable problems of a practical nature. It shifted focus away from the symbolic approaches it had inherited from AI, and toward methods and models borrowed from statistics, fuzzy logic, and probability theory. === Data compression === === Data mining === Machine learning and data mining often employ the same methods and overlap significantly, but while machine learning focuses on prediction based on known properties learned from the training data, data mining focuses on the discovery of previously unknown properties in the data (this is the analysis step of knowledge discovery in databases). Data mining uses many machine learning methods, but with different goals; on the other hand, machine learning also employs data mining methods as "unsupervised learning" or as a preprocessing step to improve learner accuracy. Much of the confusion between these two research communities comes from the basic assumptions they work with: in machine learning, performance is usually evaluated with respect to the ability to reproduce known knowledge, while in knowledge discovery and data mining (KDD) the key task is the discovery of previously unknown knowledge. Evaluated with respect to known knowledge, an uninformed (unsupervised) method will easily be outperformed by other supervised methods, while in a typical KDD task, supervised methods cannot be used due to the unavailability of training data. Machine learning also has intimate ties to optimization: Many learning problems are formulated as minimisation of some loss function on a training set of examples. Loss functions express the discrepancy between the predictions of the model being trained and the actual problem instances (for example, in classification, one wants to assign a label to instances, and models are trained to correctly predict the preassigned labels of a set of examples). === Generalization === Characterizing the generalisation of various learning algorithms is an active topic of current research, especially for deep learning algorithms. === Statistics === Machine learning and statistics are closely related fields in terms of methods, but distinct in their principal goal: statistics draws population inferences from a sample, while machine learning finds generalisable predictive patterns. Conventional statistical analyses require the a priori selection of a model most suitable for the study data set. In addition, only significant or theoretically relevant variables based on previous experience are included for analysis. In contrast, machine learning is not built on a pre-structured model; rather, the data shape the model by detecting underlying patterns. The more variables (input) used to train the model, the more accurate the ultimate model will be. Leo Breiman distinguished two statistical modelling paradigms: the data model and the algorithmic model, wherein "algorithmic model" means more or less the machine learning algorithms like Random forest. Some statisticians have adopted methods from machine learning, producing the field of statistical learning. === Statistical physics === Analytical and computational techniques derived from deep-rooted physics of disordered systems can be extended to large-scale problems, including machine learning, e.g., to analyse the weight space of deep neural networks. Statistical physics is thus
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Kimchi (software)

Kimchi is a web management tool to manage Kernel-based Virtual Machine (KVM) infrastructure. Developed with HTML5, Kimchi is developed to intuitively manage KVM guests, create storage pools, manage network interfaces (bridges, VLANs, NAT), and perform other related tasks. The name is an extended acronym for KVM infrastructure management. It is an Apache-licensed project hosted on GitHub, and incubated by oVirt.org.
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Social media use by the Islamic State

The Islamic State is widely known for its posting of disturbing content, such as beheading videos, on the internet. This propaganda is disseminated through websites and many social media platforms such as Twitter, Facebook, Telegram, and YouTube. By utilizing social media, the organization has garnered a strong following and successfully recruited tens of thousands of followers from around the world. In response to its successful use of social media, many websites and social media platforms have banned accounts and removed content promoting the Islamic State from their platforms. == Background == The Islamic State is a Jihadist militant group and a former unrecognised proto-state. The group sophisticatedly utilizes social media as a tool for spreading its message and for international recruitment. == Target audience == IS targets a variety of different groups both in the Middle East and Western Countries. There are a wide variety of motives for why fighters may be prompted to join IS. Researchers from Quantum cite nine attributes characteristic of a fighter looking to join IS: status seeking, identity seeking, revenge, redemption, thrill, ideology, justice, and death. The standard IS recruit, both from the Middle East and Western countries, is relatively young. The average age of IS fighters is around 26 years old, with 86% of recruits being male. Middle Eastern recruits come from economically disadvantaged backgrounds in Northern Iraq. Recent destruction in the Iraq War and Syrian Civil War has created hatred of Western Powers in the region. By 2025, researchers identified a significant shift toward targeting minors and adolescents, a phenomenon dubbed the "Alt-Jihad." This younger demographic is targeted not through theological arguments, but through a "victimhood-revenge" narrative that blends extremist ideology with pop-culture aesthetics in gaming environments like Roblox and Minecraft. In 2024 alone, 42 minors were arrested in Europe for involvement in IS-related plotting or propaganda. Western recruits are often second or third-generation immigrants. Computer scientists Zeeshan ul-hassan Usmani also found that the majority of the Western recruits do not feel "at home" in their home country. As a result, these fighters often have desires to go abroad and escape conditions in their home country. In addition to recruitment, IS's social media presence is also meant to intimidate and spread terror around the world. IS's posting of beheadings and other execution videos primarily target the Western world. == Content and messages == IS produces propaganda videos that range from video executions to full-length documentaries. The videos have a high production quality and incorporate montages, slow motion scenes, and are often accompanied by a short dialogue. IS has a dedicated team of over 100 media insurgents dedicated to recording these videos. While the group previously relied on glossy magazines like Dabiq, post-territorial strategies have shifted focus to the weekly newsletter Al-Naba. Unlike previous publications designed for recruitment, Al-Naba serves as a "central pillar" of the group's media strategy, focusing on bureaucratic reporting and military statistics to project a narrative of endurance and maintain internal cohesion among dispersed fighters. The IS executions typically consist of beheadings or mass shootings in retaliation to western intervention in IS territory. The particular videos that IS often post include executions of "enemies of the Caliphate," which often consist of westerners or Jordanian nationals. Most infamously, an executioner nicknamed Jihadi John was seen in many of these videos prior to his death in 2015. Jihadi John is notorious for executing many US, UK, and Japanese citizens such as Steven Sotloff, David Haines, and Alan Henning. In many of the videos and materials produced by IS, there is the theme of inclusion and brotherhood. Additionally, the videos also focus on three main messages: Convey narrative of global war and ultimate victory Radicalize populations globally Encourage international lone state actor and small cell attacks in support of IS These messages can be seen throughout all content produced by the Islamic State such as war documentaries, execution videos, and Rumiyah (magazine). == Social media usage == From 2013 to 2014, the organization primarily used mainstream platforms such as Twitter, Facebook, and YouTube. In 2014, these large social media platforms removed IS content. Since then, IS has chosen to utilize social media platforms that either protect their content or allow for content to quickly be reposted. These platforms of choice are Telegram, Justpaste.it, and Surespot, until the latter's shutdown in 2022. By 2025, the group had further diversified into decentralized platforms like Rocket.Chat and TamTam to evade moderation. IS also implements marketing initiatives like “Jihadist Follow Friday,” which encourages users to follow new IS-related accounts each Friday. This specific hashtag mirrors commonly used hashtags such as #motivation monday or #throwbackthursday. To augment their online presence and popularity, the organization encourages their followers to use a plethora of Arabic hashtags, which translate to #theFridayofSupportingISIS, and #CalamityWillBefalltheUS. This allows them to gain followers each week while promoting their community and message on a weekly basis. === Twitter === During 2014, there were an estimated 46,000 to 90,000 Twitter accounts that advocated for IS or were run by supporters of the group. In 2015, Twitter reported that it banned 125,000 IS sympathetic accounts. In 2016, it published an update of 325,000 deleted accounts. Though many accounts have been suspended, IS supporters often create new accounts. Twitter defines those who recreate accounts as “resurgents” and explains that these are often difficult accounts to remove completely, since they tend to pop back up in alternate forms. It is estimated that approximately 20% of all IS affiliated Twitter accounts can be traced back to fake accounts created by the same user. Many of these accounts are traced back to the “Baqiya family,” which is an online network of thousands of IS followers. Many of these accounts are active during important IS military victories. During the IS march on Mosul, there were about 42,000 tweets on Twitter supporting the invasion. === Telegram === During 2014, IS became very active on Telegram after many major social media platforms banned IS content and sympathetic accounts. Telegram is an encrypted messaging application. The platform by nature is created as an end-to-end user encryption platform. Further, it also has special features such as the self-destruct timer which erase all evidence and messages. The app has a user data protection policy because violating this policy could potentially damage the app’s brand of customer privacy. Government agencies have been unable to break Telegram's encryption technology. On Telegram, IS often uses the hashtag #KhilafahNews to attract their users. Telegram is used by IS to plan social media campaigns on alternate platforms. The organization also uses Telegram as an anchor platform to connect with their user base when their other accounts are banned on Twitter and Facebook. On 28 February 2016 a video was uploaded threatening to expose the najaasah and shoot the hesitates. Produced by Ibn-Altayb and distributed by Al-Hayat, the video shows footage of Bruxelles attacks and the victims. In July 2017, Telegram came under scrutiny from the media and news media outlets. It has been documented that IS gunmen have used this app to maintain contact with IS leaders in Raqqa days before terror attacks in Turkey, Berlin, and St. Petersburg. Despite concerns from Western media, there has been little to no action taken against IS accounts on Telegram. In April 2019 a video was uploaded in which they urged lone wolves to attempt to attack during the Holy Week in Sevilla and Málaga. In Sevilla, a jihadist who intended to perform a lone wolf attack was arrested. === TikTok === In October 2019, it was reported that IS recruitment content was discovered on TikTok. Approximately two dozen accounts were subsequently shut down in response. By 2025, TikTok had evolved into a "low-threshold" gateway for extremist recruitment, characterized by researchers as part of a "Virtual Caliphate Complex." Nearly 93 unofficial IS support groups, known as "feeder groups," were found to be repackaging official IS content into short-form videos with pink hearts, catchy music, and internet memes to evade detection and appeal to the "TikTok generation." This content often promotes a "victimhood-revenge" narrative rather than complex theology, specifically designed to radicalize minors. === Justpaste.it === Justpaste.it, an anonymous photo and text sharing website, has also been utilized heavily. With the option to lock images, the website allows anonymous
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