AI Assistant Unfiltered

AI Assistant Unfiltered — independent reviews, comparisons, pricing and step-by-step guides on Aizhi.

  • Text-to-image personalization

    Text-to-image personalization

    Text-to-Image personalization is a task in deep learning for computer graphics that augments pre-trained text-to-image generative models. In this task, a generative model that was trained on large-scale data (usually a foundation model), is adapted such that it can generate images of novel, user-provided concepts. These concepts are typically unseen during training, and may represent specific objects (such as the user's pet) or more abstract categories (new artistic style or object relations). Text-to-Image personalization methods typically bind the novel (personal) concept to new words in the vocabulary of the model. These words can then be used in future prompts to invoke the concept for subject-driven generation, inpainting, style transfer and even to correct biases in the model. To do so, models either optimize word-embeddings, fine-tune the generative model itself, or employ a mixture of both approaches. == Technology == Text-to-Image personalization was first proposed during August 2022 by two concurrent works, Textual Inversion and DreamBooth. In both cases, a user provides a few images (typically 3–5) of a concept, like their own dog, together with a coarse descriptor of the concept class (like the word "dog"). The model then learns to represent the subject through a reconstruction based objective, where prompts referring to the subject are expected to reconstruct images from the training set. In Textual Inversion, the personalized concepts are introduced into the text-to-image model by adding new words to the vocabulary of the model. Typical text-to-image models represent words (and sometimes parts-of-words) as tokens, or indices in a predefined dictionary. During generation, an input prompt is converted into such tokens, each of which is converted into a ‘word-embedding’: a continuous vector representation which is learned for each token as part of the model's training. Textual Inversion proposes to optimize a new word-embedding vector for representing the novel concept. This new embedding vector can then be assigned to a user-chosen string, and invoked whenever the user's prompt contains this string. In DreamBooth, rather than optimizing a new word vector, the full generative model itself is fine-tuned. The user first selects an existing token, typically one which rarely appears in prompts. The subject itself is then represented by a string containing this token, followed by a coarse descriptor of the subject's class. A prompt describing the subject will then take the form: "A photo of " (e.g. "a photo of sks cat" when learning to represent a specific cat). The text-to-image model is then tuned so that prompts of this form will generate images of the subject. == Textual Inversion == The key idea in Textual Inversion is to add a new term to the vocabulary of the diffusion model that corresponds to the new (personalized) concept. Textual Inversion operates by inverting the concepts into new pseudo-words within the textual embedding space of a pre-trained text-to-image model. These pseudo-words can be injected into new scenes using simple natural language descriptions, allowing for simple and intuitive modifications. The method allows a user to leverage multi-modal information — using a text-driven interface for ease of editing, but providing visual cues when approaching the limits of natural language. The resulting model is extremely light-weight per concept: only 1K long, but succeeds to encode detailed visual properties of the concept. == Extensions == Several approaches were proposed to refine and improve over the original methods. These include the following. Low-rank Adaptation (LoRA) - an adapter-based technique for efficient finetuning of models. In the case of text-to-image models, LoRA is typically used to modify the cross-attention layers of a diffusion model. Perfusion - a low rank update method that also locks the activations of the key matrix in the diffusion model's cross attention layers to the concept's coarse class. Extended Textual Inversion - a technique that learns an individual word embedding for each layer in the diffusion model's denoising network. Encoder-based methods that use another neural network to quickly personalize a model == Challenges and limitations == Text-to-image personalization methods must contend with several challenges. At their core is the goal of achieving high-fidelity to the personal concept while maintaining high alignment between novel prompts containing the subject, and the generated images (typically referred to as ‘editability’). Another challenge that personalization methods must contend with is memory requirements. Initial implementations of personalization methods required more than 20 Gigabytes of GPU memory, and more recent approaches have reported requirements of more than 40 Gigabytes. However, optimizations such as Flash Attention have since reduced this requirement considerably. Approaches that tune the entire generative model may also create checkpoints that are several gigabytes in size, making it difficult to share or store many models. Embedding based approaches require only a few kilobytes, but typically struggle to preserve identity while maintaining editability. More recent approaches have proposed hybrid tuning goals which optimize both an embedding and a subset of network weights. These can reduce storage requirements to as little as 100 Kilobytes while achieving quality comparable to full tuning methods. Finally, optimization processes can be lengthy, requiring several minutes of tuning for each novel concept. Encoder and quick-tuning methods aim to reduce this to seconds or less.

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  • The Morning After (web series)

    The Morning After (web series)

    The Morning After is a Hulu original web series that premiered on January 17, 2011, and ended April 24, 2014. It was produced by Hulu and Jace Hall's HDFilms, streaming Monday through Friday. The show originally featured Brian Kimmet and Ginger Gonzaga as hosts. Later shows used a rotation of hosts including Alison Haislip, Dave Holmes, Damien Fahey, Bradley Hasemeyer, Haley Mancini, Paul Nyhart, and Rachel Perry. The series advertises itself as "a smart, daily shot of pop culture to help Hulu users stay up to date" and typically highlights notable moments from television shows and current news in an entertaining fashion. In keeping with its focus on pop culture, The Morning After will sometimes stream an episode featuring past pop culture titled "From the Archives," such as its April Fools' Day episode. == History == While not the first original series to appear exclusively on Hulu, The Morning After is the company's first self-branded production. It was preceded by If I Can Dream, a reality series co-produced with 19 Entertainment and created by Simon Fuller. Hulu originated the idea in house, based on user feedback and observations from discussion boards hosted by the website. The concept was modeled after The Big Show with Olbermann and Patrick. The company sought out a production partner and ultimately chose Jace Hall and his team at HDFilms to executive produce. Initial stream of the series was held on January 17, 2011, and featured coverage of Piers Morgan, the Golden Globes, and The Bachelor. Senior VP of Content and Distribution Andy Forssell made the announcement for the show the same day. The show aired its last episode April 24, 2014. == Format == A typical episode usually begins with a cold open shared by the varying hosts listing the highlights to be covered. The topics focus on TV and Pop Culture Highlights from the previous night, with the intention of helping Hulu users digest hours of content in a matter of moments. The show has the hosts trade humorous remarks regarding the news and each other, taking turns reviewing the night's TV and injecting their own personality. The Morning After was named as an honoree by the Webbys on April 10, 2012, in the variety section of its online video category.

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  • HtmlUnit

    HtmlUnit

    HtmlUnit is a headless web browser written in Java. It allows high-level manipulation of websites from other Java code, including filling and submitting forms and clicking hyperlinks. It also provides access to the structure and the details within received web pages. HtmlUnit emulates parts of browser behaviour including the lower-level aspects of TCP/IP and HTTP. A sequence such as getPage(url), getLinkWith("Click here"), click() allows a user to navigate through hypertext and obtain web pages that include HTML, JavaScript, Ajax and cookies. This headless browser can deal with HTTPS security, basic HTTP authentication, automatic page redirection and other HTTP headers. It allows Java test code to examine returned pages either as text, an XML DOM, or as collections of forms, tables, and links. The goal is to simulate real browsers; namely Chrome, Firefox and Edge. The most common use of HtmlUnit is test automation of web pages, but sometimes it can be used for web scraping, or downloading website content. == Benefits == Provides high-level API, taking away lower-level details away from the user. Compared to other WebDriver implementations, HtmlUnitDriver is the fastest to implement. It can be configured to simulate a specific browser. == Drawbacks == Element layout and rendering can not be tested. The JavaScript support is not complete, which is one of the areas of ongoing enhancements. == Used technologies == W3C DOM HTTP connection, using Apache HttpComponents JavaScript, using forked Rhino HTML Parsing, NekoHTML CSS: using CSS Parser XPath support, using Xalan == Libraries using HtmlUnit == Selenium WebDriver Spring MVC Test Framework Google Web Toolkit tests WebTest Wetator

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  • Fear of missing out

    Fear of missing out

    Fear of missing out (FOMO) is the feeling of apprehension that one is either not in the know about or missing out on information, events, experiences, or life decisions that could make one's life better. FOMO is also associated with a fear of regret, which may lead to concerns that one might miss an opportunity for social interaction, a novel experience, a memorable event, profitable investment, or the comfort of loved ones. It is characterized by a desire to stay continually connected with what others are doing, and can be described as the fear that deciding not to participate is the wrong choice. FOMO could result from not knowing about a conversation, missing a TV show, not attending a wedding or party, or hearing that others have discovered a new restaurant. In recent years, FOMO has been attributed to a number of negative psychological and behavioral symptoms. FOMO has increased in recent times due to advancements in technology. Social networking sites create many opportunities for FOMO. While it provides opportunities for social engagement, it offers a view into an endless stream of activities in which a person is not involved. Further, a common tendency is to post about positive experiences (such as a great restaurant) rather than negative ones (such as a bad first date). Psychological dependence on social media can lead to FOMO or even pathological Internet use. FOMO is also present in video games, investing, and business marketing. The increasing popularity of the phrase has led to related linguistic and cultural variants. FOMO is associated with worsening depression and anxiety, and a lowered quality of life. FOMO can also affect businesses. Hype and trends can lead business leaders to invest based on perceptions of what others are doing, rather than their own business strategy. This is also the idea of the bandwagon effect, where one individual may see another person or people do something and they begin to think it must be important because everyone is doing it. They might not even understand the meaning behind it, and they may not totally agree with it. Nevertheless, they are still going to participate because they don't want to be left out. == History == Patrick J. McGinnis coined the term FOMO and popularized it in a 2004 op-ed titled "Social Theory at HBS: McGinnis' Two FOs" in The Harbus, the magazine of Harvard Business School, where he was then a student. The article also referred to another related condition, Fear of a Better Option (FOBO), and the role of these two fears in the school's social life. Currently the term has been used as a hashtag on social media and has been mentioned in hundreds of news articles, from online sources like Salon.com to print papers like The New York Times. === Earlier forms === The phrase "fear of missing out" is a common English phrase, especially in the form "fear of missing out on (something)". The term "fear of missing out" (but not the term FOMO) was used earlier in the academic business literature by marketing strategist Dan Herman, who used it in presentations in the late 1990s, and included the phrase in a 2000 paper about "short-term brands", where a motivation for trying these brands is "ambition to exhaust all possibilities and the fear of missing out on something". Herman also believes the concept has evolved to become more wide spread through mobile phone usage, texting, and social media and has helped flesh out the concept of the fear of missing out to the masses. Before the Internet, a related phenomenon, "keeping up with the Joneses", was widely experienced. FOMO generalized and intensified this experience because so much more of people's lives became publicly documented and easily accessed. == Symptoms == === Psychological === Fear of missing out has been associated with a deficit in psychological needs. Self-determination theory contends that an individual's psychological satisfaction in their competence, autonomy, and relatedness consists of three basic psychological needs for human beings. Test subjects with lower levels of basic psychological satisfaction reported a higher level of FOMO. FOMO has also been linked to negative psychological effects in overall mood and general life satisfaction. A study performed on college campuses found that experiencing FOMO on a certain day led to a higher fatigue on that day specifically. Experiencing FOMO continuously throughout the semester also can lead to higher stress levels among students. An individual with an expectation to experience the fear of missing out can also develop a lower level of self-esteem. A study by JWTIntelligence suggests that FOMO can influence the formation of long-term goals and self-perceptions. In this study, around half of the respondents stated that they are overwhelmed by the amount of information needed to stay up-to-date, and that it is impossible to not miss out on something. The process of relative deprivation creates FOMO and dissatisfaction. It reduces psychological well-being. FOMO led to negative social and emotional experiences, such as boredom and loneliness. A 2013 study found that it negatively impacts mood and life satisfaction, reduces self-esteem, and affects mindfulness. Four in ten young people reported FOMO sometimes or often. FOMO was found to be negatively correlated with age, and men were more likely than women to report it. People who experience higher levels of FOMO tend to have a stronger desire for high social status, are more competitive with others of the same gender, and are more interested in short-term relationships. Studies have found that experiencing fear of missing out has been linked to anxiety or depression. === Behavioral === The fear of missing out stems from a feeling of missing social connections or information. This absent feeling is then followed by a need or drive to interact socially to boost connections. The fear of missing out not only leads to negative psychological effects but also has been shown to increase negative behavioral patterns. In aims of maintaining social connections, negative habits are formed or heightened. A 2019 University of Glasgow study surveyed 467 adolescents, and found that the respondents felt societal pressure to always be available. According to John M. Grohol, founder and Editor-in-Chief of Psych Central, FOMO may lead to a constant search for new connections with others, abandoning current connections to do so. The fear of missing out derived from digital connection has been positively correlated with bad technology habits especially in youth. These negative habits included increased screen time, checking social media during school, or texting while driving. Social media use in the presence of others can be referred to as phubbing, the habit of snubbing a physically present person in favour of a mobile phone. Multiple studies have also identified a negative correlation between the hours of sleep and the scale at which individuals experience fear of missing out. A lack of sleep in college students experiencing FOMO can be attributed to the number of social interactions that occur late at night on campuses. == Settings == === Social media === Fear of missing out has a positive correlation with higher levels of social media usage. Social media connects individuals and showcases the lives of others at their peak. This gives people the fear of missing out when they feel like others on social media are taking part in positive life experiences that they personally are not also experiencing. This fear of missing out related to social media has symptoms including anxiety, loneliness, and a feeling of inadequacy compared to others. Self-esteem plays a key role in the levels a person feels when experiencing the fear of missing out, as their self worth is influenced by people they observe on social media. There are two types of anxiety; one related to genetics that is permanent, and one that is temporary. The temporary state of anxiety is the one that is more relevant to the fear of missing out, and is directly related to the individual looking at social media sites for a short period of time. This anxiety is caused by a loss of feeling of belonging through the concept of social exclusion. FOMO-sufferers may increasingly seek access to others' social lives, and consume an escalating amount of real-time information. A survey in 2012 indicated that 83% of respondents said that there is information overload in regards that there is too much to watch and read. Constant information that is available to people through social media causes the fear of missing out as people feel worse about themselves for not staying up to date with relevant information. Social media shows just exactly what people are missing out on in real time including events like parties, opportunities, and other events leading for people to fear missing out on other related future events. Another survey indicates that almost 40% of people from ages 12 through 67 i

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  • Distribution management system

    Distribution management system

    A distribution management system (DMS) is a collection of applications designed to monitor and control the electric power distribution networks efficiently and reliably. It acts as a decision support system to assist the control room and field operating personnel with the monitoring and control of the electric distribution system. Improving the reliability and quality of service in terms of reducing power outages, minimizing outage time, maintaining acceptable frequency and voltage levels are the key deliverables of a DMS. Given the complexity of distribution grids, such systems may involve communication and coordination across multiple components. For example, the control of active loads may require a complex chain of communication through different components as described in US patent 11747849B2 In recent years, utilization of electrical energy increased exponentially and customer requirement and quality definitions of power were changed enormously. As electric energy became an essential part of daily life, its optimal usage and reliability became important. Real-time network view and dynamic decisions have become instrumental for optimizing resources and managing demands, leading to the need for distribution management systems in large-scale electrical networks. == Overview == Most distribution utilities have been comprehensively using IT solutions through their Outage Management System (OMS) that makes use of other systems like Customer Information System (CIS), Geographical Information System (GIS) and Interactive Voice Response System (IVRS). An outage management system has a network component/connectivity model of the distribution system. By combining the locations of outage calls from customers with knowledge of the locations of the protection devices (such as circuit breakers) on the network, a rule engine is used to predict the locations of outages. Based on this, restoration activities are charted out and the crew is dispatched for the same. In parallel with this, distribution utilities began to roll out Supervisory Control and Data Acquisition (SCADA) systems, initially only at their higher voltage substations. Over time, use of SCADA has progressively extended downwards to sites at lower voltage levels. DMSs access real-time data and provide all information on a single console at the control centre in an integrated manner. Their development varied across different geographic territories. In the US, for example, DMSs typically grew by taking Outage Management Systems to the next level, automating the complete sequences and providing an end to end, integrated view of the entire distribution spectrum. In the UK, by contrast, the much denser and more meshed network topologies, combined with stronger Health & Safety regulation, had led to early centralisation of high-voltage switching operations, initially using paper records and schematic diagrams printed onto large wallboards which were 'dressed' with magnetic symbols to show the current running states. There, DMSs grew initially from SCADA systems as these were expanded to allow these centralised control and safety management procedures to be managed electronically. These DMSs required even more detailed component/connectivity models and schematics than those needed by early OMSs as every possible isolation and earthing point on the networks had to be included. In territories such as the UK, therefore, the network component/connectivity models were usually developed in the DMS first, whereas in the USA these were generally built in the GIS. The typical data flow in a DMS has the SCADA system, the Information Storage & Retrieval (ISR) system, Communication (COM) Servers, Front-End Processors (FEPs) & Field Remote Terminal Units (FRTUs). == Why DMS? == Reduce the duration of outages Improve the speed and accuracy of outage predictions. Reduce crew patrol and drive times through improved outage locating. Improve the operational efficiency Determine the crew resources necessary to achieve restoration objectives. Effectively utilize resources between operating regions. Determine when best to schedule mutual aid crews. Increased customer satisfaction A DMS incorporates IVR and other mobile technologies, through which there is an improved outage communications for customer calls. Provide customers with more accurate estimated restoration times. Improve service reliability by tracking all customers affected by an outage, determining electrical configurations of every device on every feeder, and compiling details about each restoration process. == DMS Functions == In order to support proper decision making and O&M activities, DMS solutions should support the following functions: Network visualization & support tools Applications for Analytical & Remedial Action Utility Planning Tools System Protection Schemes The various sub functions of the same, carried out by the DMS are listed below:- === Network Connectivity Analysis (NCA) === Distribution network usually covers over a large area and catering power to different customers at different voltage levels. So locating required sources and loads on a larger GIS/Operator interface is often very difficult. Panning & zooming provided with normal SCADA system GUI does not cover the exact operational requirement. Network connectivity analysis is an operator specific functionality which helps the operator to identify or locate the preferred network or component very easily. NCA does the required analyses and provides display of the feed point of various network loads. Based on the status of all the switching devices such as circuit breaker (CB), Ring Main Unit (RMU) and/or isolators that affect the topology of the network modeled, the prevailing network topology is determined. The NCA further assists the operator to know operating state of the distribution network indicating radial mode, loops and parallels in the network. === Switching Schedule & Safety Management === In territories such as the UK a core function of a DMS has always been to support safe switching and work on the networks. Control engineers prepare switching schedules to isolate and make safe a section of network before work is carried out, and the DMS validates these schedules using its network model. Switching schedules can combine telecontrolled and manual (on-site) switching operations. When the required section has been made safe, the DMS allows a Permit To Work (PTW) document to be issued. After its cancellation when the work has been finished, the switching schedule then facilitates restoration of the normal running arrangements. Switching components can also be tagged to reflect any Operational Restrictions that are in force. The network component/connectivity model, and associated diagrams, must always be kept absolutely up to date. The switching schedule facility therefore also allows 'patches' to the network model to be applied to the live version at the appropriate stage(s) of the jobs. The term 'patch' is derived from the method previously used to maintain the wallboard diagrams. === State Estimation (SE) === The state estimator is an integral part of the overall monitoring and control systems for transmission networks. It is mainly aimed at providing a reliable estimate of the system voltages. This information from the state estimator flows to control centers and database servers across the network. The variables of interest are indicative of parameters like margins to operating limits, health of equipment and required operator action. State estimators allow the calculation of these variables of interest with high confidence despite the facts that the measurements may be corrupted by noise, or could be missing or inaccurate. Even though we may not be able to directly observe the state, it can be inferred from a scan of measurements which are assumed to be synchronized. The algorithms need to allow for the fact that presence of noise might skew the measurements. In a typical power system, the State is quasi-static. The time constants are sufficiently fast so that system dynamics decay away quickly (with respect to measurement frequency). The system appears to be progressing through a sequence of static states that are driven by various parameters like changes in load profile. The inputs of the state estimator can be given to various applications like Load Flow Analysis, Contingency Analysis, and other applications. === Load Flow Applications (LFA) === Load flow study is an important tool involving numerical analysis applied to a power system. The load flow study usually uses simplified notations like a single-line diagram and focuses on various forms of AC power rather than voltage and current. It analyzes the power systems in normal steady-state operation. The goal of a power flow study is to obtain complete voltage angle and magnitude information for each bus in a power system for specified load and generator real power and voltage conditions. Once this

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  • WebGL

    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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  • Hashtag

    Hashtag

    A hashtag is a metadata tag operator that is prefaced by the hash symbol, #. On social media, hashtags are used on microblogging and photo-sharing services–especially Twitter and Tumblr–as a form of user-generated tagging that enables cross-referencing of content by topic or theme. For example, a search within Instagram for the hashtag #flowers returns all posts that have been tagged with that term. After the initial hash symbol, a hashtag may include letters, numerals or other punctuation. The use of hashtags was first proposed by American blogger and product consultant Chris Messina in a 2007 tweet. Messina made no attempt to patent the use because he felt that "they were born of the internet, and owned by no one". Hashtags became entrenched in the culture of Twitter and soon emerged across Instagram, Facebook, and YouTube. In June 2014, hashtag was added to the Oxford English Dictionary as "a word or phrase with the symbol # in front of it, used on social media websites and apps so that you can search for all messages with the same subject". == Origin and acceptance == The number sign or hash symbol, #, has long been used in information technology to highlight specific pieces of text. In 1970, the number sign was used to denote immediate address mode in the assembly language of the PDP-11 when placed next to a symbol or a number, and around 1973, '#' was introduced in the C programming language to indicate special keywords that the C preprocessor had to process first. The pound sign was adopted for use within IRC (Internet Relay Chat) networks around 1988 to label groups and topics. Channels or topics that are available across an entire IRC network are prefixed with a hash symbol # (as opposed to those local to a server, which uses an ampersand '&'). The use of the pound sign in IRC inspired Chris Messina to propose a similar system on Twitter to tag topics of interest on the microblogging network. He proposed the usage of hashtags on Twitter: How do you feel about using # (pound) for groups. As in #barcamp [msg]? According to Messina, he suggested use of the hashtag to make it easy for lay users without specialized knowledge of search protocols to find specific relevant content. Therefore, the hashtag "was created organically by Twitter users as a way to categorize messages". The first published use of the term "hash tag" was in a blog post "Hash Tags = Twitter Groupings" by Stowe Boyd, on August 26, 2007, according to lexicographer Ben Zimmer, chair of the American Dialect Society's New Words Committee. Messina's suggestion to use the hashtag was not immediately adopted by Twitter, but the convention gained popular acceptance when hashtags were used in tweets relating to the 2007 San Diego forest fires in Southern California. The hashtag gained international acceptance during the 2009–2010 Iranian election protests; Twitter users used both English- and Persian-language hashtags in communications during the events. Hashtags have since played critical roles in recent social movements such as #jesuischarlie, #BLM, and #MeToo. Beginning July 2, 2009, Twitter began to hyperlink all hashtags in tweets to Twitter search results for the hashtagged word (and for the standard spelling of commonly misspelled words). In 2010, Twitter introduced "Trending Topics" on the Twitter front page, displaying hashtags that are rapidly becoming popular, and the significance of trending hashtags has become so great that the company makes significant efforts to foil attempts to spam the trending list. During the 2010 World Cup, Twitter explicitly encouraged the use of hashtags with the temporary deployment of "hashflags", which replaced hashtags of three-letter country codes with their respective national flags. Other platforms such as YouTube and Gawker Media followed in officially supporting hashtags, and real-time search aggregators such as Google Real-Time Search began supporting hashtags. == Format == A hashtag must begin with a hash (#) character followed by other characters, and is terminated by a space or the end of the line. Some platforms may require the # to be preceded with a space. Most or all platforms that support hashtags permit the inclusion of letters (without diacritics), numerals, and underscores. Other characters may be supported on a platform-by-platform basis. Some characters, such as "&", are generally not supported as they may already serve other search functions. Hashtags are not case sensitive (a search for "#hashtag" will match "#HashTag" as well), but the use of embedded capitals (i.e., CamelCase) increases legibility and improves accessibility. Languages that do not use word dividers handle hashtags differently. In China, microblogs Sina Weibo and Tencent Weibo use a double-hashtag-delimited #HashName# format, since the lack of spacing between Chinese characters necessitates a closing tag. Twitter uses a different syntax for Chinese characters and orthographies with similar spacing conventions: the hashtag contains unspaced characters, separated from preceding and following text by spaces (e.g., '我 #爱 你' instead of '我#爱你') or by zero-width non-joiner characters before and after the hashtagged element, to retain a linguistically natural appearance (displaying as unspaced '我‌#爱‌你', but with invisible non-joiners delimiting the hashtag). === Etiquette and regulation === Some communities may limit, officially or unofficially, the number of hashtags permitted on a single post. Misuse of hashtags can lead to account suspensions. Twitter warns that adding hashtags to unrelated tweets, or repeated use of the same hashtag without adding to a conversation can filter an account from search results, or suspend the account. Individual platforms may deactivate certain hashtags either for being too generic to be useful, such as #photography on Instagram, or due to their use to facilitate illegal activities. === Alternate formats === In 2009, StockTwits began using ticker symbols preceded by the dollar sign (e.g., $XRX). In July 2012, Twitter began supporting the tag convention and dubbed it the "cashtag". The convention has extended to national currencies, and Cash App has implemented the cashtag to mark usernames. == Function == Hashtags are particularly useful in unmoderated forums that lack a formal ontological organization. Hashtags help users find content similar interest. Hashtags are neither registered nor controlled by any one user or group of users. They do not contain any set definitions, meaning that a single hashtag can be used for any number of purposes, and that the accepted meaning of a hashtag can change with time. Hashtags intended for discussion of a particular event tend to use an obscure wording to avoid being caught up with generic conversations on similar subjects, such as a cake festival using #cakefestival rather than simply #cake. However, this can also make it difficult for topics to become "trending topics" because people often use different spelling or words to refer to the same topic. For topics to trend, there must be a consensus, whether silent or stated, that the hashtag refers to that specific topic. Hashtags may be used informally to express context around a given message, with no intent to categorize the message for later searching, sharing, or other reasons. Hashtags may thus serve as a reflexive meta-commentary. This can help express contextual cues or offer more depth to the information or message that appears with the hashtag. "My arms are getting darker by the minute. #toomuchfaketan". AnoHashtags can also be used to express personal feelings and emotions. ther function of the hashtag can be used to express personal feelings and emotions. For example, with "It's Monday!! #excited #sarcasm" in which the adjectives are directly indicating the emotions of the speaker. Verbal use of the word hashtag is sometimes used in informal conversations. Use may be humorous, such as "I'm hashtag confused!" By August 2012, use of a hand gesture, sometimes called the "finger hashtag", in which the index and middle finger both hands are extended and arranged perpendicularly to form the hash, was documented. === Co-optation by other industries === Companies, businesses, and advocacy organizations have taken advantage of hashtag-based discussions for promotion of their products, services or campaigns. In the early 2010s, some television broadcasters began to employ hashtags related to programs in digital on-screen graphics, to encourage viewers to participate in a backchannel of discussion via social media prior to, during, or after the program. Television commercials have sometimes contained hashtags for similar purposes. The increased usage of hashtags as brand promotion devices has been compared to the promotion of branded "keywords" by AOL in the late 1990s and early 2000s, as such keywords were also promoted at the end of television commercials and series episodes. Organized real-world events have used hashta

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  • GeForce RTX 50 series

    GeForce RTX 50 series

    The GeForce RTX 50 series of consumer graphics cards is the successor of Nvidia's GeForce 40 series. Announced at CES 2025, it debuted with the release of the RTX 5070, RTX 5080 and RTX 5090 in January 2025. It is based on Nvidia's Blackwell architecture featuring Nvidia RTX's fourth-generation RT cores for hardware-accelerated real-time ray tracing, and fifth-generation deep learning–focused Tensor Cores. The GPUs are manufactured by TSMC on a custom 4N process node. == Background == In March 2024, Nvidia announced the Blackwell architecture for its datacenter products. Like Ampere, the architecture is shared by consumer and datacenter products rather than having distinct architectures released simultaneously like Ada Lovelace for consumers and Hopper for datacenter. At the Game Awards in December 2024, a cinematic trailer for The Witcher IV was shown that had been pre-rendered on an "unannounced Nvidia GeForce RTX GPU". This was assumed to be an upcoming GeForce RTX 50 series GPU. Following the RTX 50 series announcement, Nvidia confirmed that the trailer was "pre-rendered in Unreal Engine 5 on a GeForce RTX 5090". Later in the same month, it was reported that Nvidia had begun stockpiling GeForce RTX 50 series units in U.S. warehouses due to a threatened 10% import tariff and 60% tariff on Chinese imports that Donald Trump promised in his re-election campaign. === Announcement === On January 6, 2025, the GeForce RTX 50 series was officially announced for desktop and mobile devices during Nvidia's CES keynote in Las Vegas. The pricing announcement was met with surprise as the RTX 5080 at $999 was the same price that the RTX 4080 Super released at a year earlier despite the anticipated price increases. Nvidia CEO Jensen Huang falsely claimed that the RTX 5070 could reach "RTX 4090 performance at $549", a figure that relies on the use of DLSS 4 upscaling and Multi Frame generation, and is not an indication of raw performance. == Features == === Blackwell architecture === The GeForce RTX 50 series is powered by the Blackwell microarchitecture, which continues Ada Lovelace's emphasis on high graphics frequencies and large L2 caches. The Blackwell architecture introduces Nvidia RTX's fourth-generation RT cores for hardware-accelerated real-time ray tracing and fifth-generation Tensor Cores for AI compute and performing floating-point calculations. === GDDR7 === RTX 50 series GPUs are the first consumer GPUs to feature GDDR7 video memory for greater memory bandwidth over the same bus width compared to the GDDR6 and GDDR6X memory used in the GeForce 40 series. RTX 50 series desktop GPUs use GDDR7 modules from Samsung due to them being available for validation earlier than modules from SK Hynix and Micron. === 12V-2×6 connector === The GeForce RTX 50 series uses the 16-pin 12V-2×6 connector, which is a revision of the 12VHPWR connector featured on the GeForce 40 series. There were problems with the 12VHPWR connector melting on some RTX 4090 GPUs due to the connector not being fully seated and connector design flaws that did not implement a high enough safety and error tolerance. The 12V-2×6 connector revision, published by PCI-SIG in July 2023, addressed this by shortening the four sense pins so the connector will not push any power if it has not been fully seated. The 12VHPWR design would still draw up to 150W of power even if the sense pins were not making full contact. 12V-2×6 is backwards compatible with existing 12VHPWR cables and adapters. Nvidia has mandated to its AIB partners that the 16-pin 12V-2×6 connector be used on all RTX 50 series designs. With the GeForce 40 series, the 12VHPWR connector was only mandated on higher power cards such as the RTX 4070 Super, RTX 4070 Ti, RTX 4070 Ti Super, RTX 4080, RTX 4080 Super and RTX 4090 while RTX 4060, RTX 4060 Ti and RTX 4070 AIB designs had the option of using 8-pin PCIe connectors. The 600W-capable 12VHPWR connector would not have been necessary on sub-200W cards. === DLSS 4 === The fourth generation of Deep Learning Super Sampling (DLSS) was unveiled alongside the RTX 50 series. DLSS 4 upscaling uses a new vision transformer-based model for enhanced image quality with reduced ghosting and greater image stability in motion compared to the previous convolutional neural network (CNN) model. DLSS 4 also allows a greater number of frames to be generated and interpolated based on a single traditionally rendered frame. This form of frame generation called Multi Frame Generation is exclusive to the RTX 50 series while the GeForce 40 series is limited to one interpolated frame per traditionally rendered frame. Nvidia claims that DLSS 4's frame generation model uses 30% less video memory with the example of Warhammer 40,000: Darktide using 400 MB less memory at 4K resolution with frame generation enabled. Nvidia claims that 75 titles will integrate DLSS 4 Multi Frame Generation at launch, including Alan Wake 2, Cyberpunk 2077, Indiana Jones and the Great Circle, and Star Wars Outlaws. === Media Engine and I/O === The RTX 50 series includes DisplayPort 2.1b UHBR20 (80Gbps) with higher display output data rates to support high resolution and high refresh rate displays. The GeForce 40 series received criticism for only including DisplayPort 1.4a (32Gbps) while the competing Radeon RX 7000 series included DisplayPort 2.1 UHBR13.5 (54Gbps). At CES 2025, VESA announced a collaboration with Nvidia on the new DP80LL ("low loss") UHBR20 active cable standard. DP80LL allows for 80Gbps DisplayPort 2.1 cables up to 3 meters long as passive DP80 cables are limited in length due to signal integrity concerns. The RTX 50 series introduces the ninth-generation NVENC encoder and sixth-generation NVDEC video decoder. For the first time in a consumer GeForce GPU, encoding and decoding video in the 4:2:2 color format for professional-grade higher color depth is supported. == List of GPUs == === Desktop === GeForce RTX 50 series desktop GPUs are the second consumer GPUs to utilize a PCIe 5.0 interface and the first to feature GDDR7 video memory (except for the entry level RTX 5050 that still uses GDDR6). They are fabricated by TSMC using a custom 5 nm process dubbed 4N. === Mobile === Laptops featuring GeForce RTX 50 series laptop GPUs were shown at CES 2025. Laptops with RTX 50 series GPUs were paired with Intel's Arrow Lake-HX and AMD's Strix Point and Fire Range CPUs. Nvidia claims that Blackwell architecture's new Max-Q features can increase battery life by up to 40% over GeForce 40 series laptops. For example, Advanced Power Gating saves power by turning off areas of the GPU that are unused and the paired GDDR7 memory can run in an "ultra" low-voltage state. Initial RTX 50 series laptops will become available in March 2025 starting at $1,299. == Controversies == === 12V-2x6 power connector issue === The 12V-2x6 connector used by multiple 5090 cards faces criticism due to a design flaw that can potentially cause the connector to melt. The flaw primarily affect Nvidia's own RTX 5090 FE and RTX 5080 FE cards and are similar to the failures seen on the RTX 40 series but models by third party OEMs have been affected as well. === Availability and pricing === The releases of the RTX 5090, 5080 and 5070 Ti were marked by severe availability issues and pricing well above MSRP. Pricing became an issue again at the end of 2025 due to an ongoing memory supply shortage. Nvidia has been rumored to cut production of 16GB VRAM cards, affecting the availability of the RTX 5060 Ti 16GB and RTX 5070 Ti SKUs. === 32-bit support removal for CUDA, OpenCL, and GPU PhysX === Support for 32-bit OpenCL, and CUDA applications (and as a result 32-bit GPU-accelerated PhysX), was dropped for the GeForce RTX 50 series, which resulted in several applications encountering performance issues with GPU PhysX options or not being able to run at all, causing negative reactions from numerous gaming communities. On December 4, 2025, with the release of driver version 591.44, 32-bit GPU-accelerated PhysX support was restored for certain games. Support for more games was promised in the future. === Incomplete dies and missing ROPs === The dies of certain RTX 5090/5090D, 5080, and 5070 Ti cards were missing eight render output units (ROPs), resulting in slower graphics while pure compute and AI workloads are unaffected. Nvidia claimed that less than 0.5% of cards are affected and that the "production anomaly" has been rectified. === Black screen issues === Some RTX 5080 and 5090 users reported an issue where the system would boot into a black screen after installing Nvidia drivers. Nvidia confirmed the issue and said that a new driver update would fix it for people who hadn't received a VBIOS update yet. Released on February 27, 2025 Nvidia drivers version 572.60 claim to have fixed the issue. Nvidia has since released multiple hotfix and Game Ready drivers that contain additional fixes for the issue. === Windows driver branch quality and stabilit

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  • ObjectVision

    ObjectVision

    ObjectVision was a forms-based programming language and environment for Windows 3.x developed by Borland. The latest version, 2.1, was released in 1992. An ObjectVision application is composed by forms designed in a graphic way that contains objects and events to provide interactivity. Forms are connected together with logic in the form of decision trees. ObjectVision applications also can interact with databases using multiple engines, like Paradox and dBase. A finished project is saved as an OVD file, that is executed by an interpreted runtime that can be freely distributed. ObjectVision was not used broadly except in some niche segments, but the visual programming ideas were the basis for Borland Delphi.

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  • Web performance

    Web performance

    Web performance refers to the speed in which web pages are downloaded and displayed on the user's web browser. Web performance optimization (WPO), or website optimization is the field of knowledge about increasing web performance. Faster website download speeds have been shown to increase visitor retention and loyalty and user satisfaction, especially for users with slow internet connections and those on mobile devices. Web performance also leads to less data travelling across the web, which in turn lowers a website's power consumption and environmental impact. Some aspects which can affect the speed of page load include browser/server cache, image optimization, and encryption (for example SSL), which can affect the time it takes for pages to render. The performance of the web page can be improved through techniques such as multi-layered cache, light weight design of presentation layer components and asynchronous communication with server side components. == History == In the first decade or so of the web's existence, web performance improvement was focused mainly on optimizing website code and pushing hardware limitations. According to the 2002 book Web Performance Tuning by Patrick Killelea, some of the early techniques used were to use simple servlets or CGI, increase server memory, and look for packet loss and retransmission. Although these principles now comprise much of the optimized foundation of internet applications, they differ from current optimization theory in that there was much less of an attempt to improve the browser display speed. Steve Souders coined the term "web performance optimization" in 2004. At that time Souders made several predictions regarding the impact that WPO as an "emerging industry" would bring to the web, such as websites being fast by default, consolidation, web standards for performance, environmental impacts of optimization, and speed as a differentiator. One major point that Souders made in 2007 is that at least 80% of the time that it takes to download and view a website is controlled by the front-end structure. This lag time can be decreased through awareness of typical browser behavior, as well as of how HTTP works. == Optimization techniques == Web performance optimization improves user experience (UX) when visiting a website and therefore is highly desired by web designers and web developers. They employ several techniques that streamline web optimization tasks to decrease web page load times. This process is known as front end optimization (FEO) or content optimization. FEO concentrates on reducing file sizes and "minimizing the number of requests needed for a given page to load." In addition to the techniques listed below, the use of a content delivery network—a group of proxy servers spread across various locations around the globe—is an efficient delivery system that chooses a server for a specific user based on network proximity. Typically the server with the quickest response time is selected. The following techniques are commonly used web optimization tasks and are widely used by web developers: Web browsers open separate Transmission Control Protocol (TCP) connections for each Hypertext Transfer Protocol (HTTP) request submitted when downloading a web page. These requests total the number of page elements required for download. However, a browser is limited to opening only a certain number of simultaneous connections to a single host. To prevent bottlenecks, the number of individual page elements are reduced using resource consolidation whereby smaller files (such as images) are bundled together into one file. This reduces HTTP requests and the number of "round trips" required to load a web page. Web pages are constructed from code files such JavaScript and Hypertext Markup Language (HTML). As web pages grow in complexity, so do their code files and subsequently their load times. File compression can reduce code files by about 40 percent, thereby improving site responsiveness. Web Caching Optimization reduces server load, bandwidth usage and latency. CDNs use dedicated web caching software to store copies of documents passing through their system. Many website platforms, such as SiteGround, IONOS, Wix, and Hostinger, rely on global CDNs and caching technologies to deliver faster page loads across different geographical regions. Subsequent requests from the cache may be fulfilled should certain conditions apply. Web caches are located on either the client side (forward position) or web-server side (reverse position) of a CDN. Web browsers are also able to store content for re-use through the HTTP cache or web cache. Requests web browsers make are typically routed to the HTTP cache to validate if a cached response may be used to fulfill a request. If such a match is made, the response is fulfilled from the cache. This can be helpful for reducing network latency and costs associated with data-transfer. The HTTP cache is configured using request and response headers. Code minification distinguishes discrepancies between codes written by web developers and how network elements interpret code. Minification removes comments and extra spaces as well as crunch variable names in order to minimize code, decreasing files sizes by as much as 60%. In addition to caching and compression, lossy compression techniques (similar to those used with audio files) remove non-essential header information and lower original image quality on many high resolution images. These changes, such as pixel complexity or color gradations, are transparent to the end-user and do not noticeably affect perception of the image. Another technique is the replacement of raster graphics with resolution-independent vector graphics. Vector substitution is best suited for simple geometric images. Lazy loading of images and video reduces initial page load time, initial page weight, and system resource usage, all of which have positive impacts on website performance. It is used to defer initialization of an object right until the point at which it is needed. The browser loads the images in a page or post when they are needed such as when the user scrolls down the page and not all images at once, which is the default behavior, and naturally, takes more time. == HTTP/1.x and HTTP/2 == Since web browsers use multiple TCP connections for parallel user requests, congestion and browser monopolization of network resources may occur. Because HTTP/1 requests come with associated overhead, web performance is impacted by limited bandwidth and increased usage. Compared to HTTP/1, HTTP/2 is binary instead of textual is fully multiplexed instead of ordered and blocked can therefore use one connection for parallelism uses header compression to reduce overhead allows servers to "push" responses proactively into client caches Instead of a website's hosting server, CDNs are used in tandem with HTTP/2 in order to better serve the end-user with web resources such as images, JavaScript files and Cascading Style Sheet (CSS) files since a CDN's location is usually in closer proximity to the end-user. == Metrics == In recent years, several metrics have been introduced that help developers measure various aspects of the performance of their websites. In 2019, Google introduced metrics such as Time to First Byte (TTFB), First Contentful Paint (FCP), First Paint (FP), First Input Delay (FID), Cumulative Layout Shift (CLS) and Largest Contentful Paint (LCP) allow for website owner to gain insights into issues that might hurt the performance of their websites making it seem sluggish or slow to the user. Other metrics including Request Count (number of requests required to load a page), DOMContentLoaded (time when HTML document is completely loaded and parsed excluding CSS style sheets, images, etc.), Above The Fold Time (content that is visible without scrolling), Round Trip Time, number of Render Blocking Resources (such as scripts, stylesheets), Onload Time, Connection Time, Total Page Size help provide an accurate picture of latencies and slowdowns occurring at the networking level which might slow down a site. Modules to measure metrics such as TTFB, FCP, LCP, FP etc are provided with major frontend JavaScript libraries such as React, NuxtJS and Vue. Google publishes a library, the core-web-vitals library that allows for easy measurement of these metrics in frontend applications. In addition to this, Google also provides the Lighthouse, a Chrome dev-tools component and PageSpeed Insight a site that allows developers to measure and compare the performance of their website with Google's recommended minimums and maximums. In addition to this, tools such as the Network Monitor by Mozilla Firefox help provide insight into network-level slowdowns that might occur during transmission of data.

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  • Dynamic web page

    Dynamic web page

    A dynamic web page is a web page constructed at runtime (during software execution), as opposed to a static web page, delivered as it is stored. A server-side dynamic web page is a web page whose construction is controlled by an application server processing server-side scripts. In server-side scripting, parameters determine how the assembly of every new web page proceeds, and including the setting up of more client-side processing. A client-side dynamic web page processes the web page using JavaScript running in the browser as it loads. JavaScript can interact with the page via Document Object Model (DOM), to query page state and modify it. Even though a web page can be dynamic on the client-side, it can still be hosted on a static hosting service such as GitHub Pages or Amazon S3 as long as there is not any server-side code included. A dynamic web page is then reloaded by the user or by a computer program to change some variable content. The updating information could come from the server, or from changes made to that page's DOM. This may or may not truncate the browsing history or create a saved version to go back to, but a dynamic web page update using AJAX technologies will neither create a page to go back to, nor truncate the web browsing history forward of the displayed page. Using AJAX, the end user gets one dynamic page managed as a single page in the web browser while the actual web content rendered on that page can vary. The AJAX engine sits only on the browser requesting parts of its DOM, the DOM, for its client, from an application server. A particular application server could offer a standardized REST style interface to offer services to the web application. DHTML is the umbrella term for technologies and methods used to create web pages that are not static web pages, though it has fallen out of common use since the popularization of AJAX, a term which is now itself rarely used. Client-side-scripting, server-side scripting, or a combination of these make for the dynamic web experience in a browser. == Basic concepts == Classical hypertext navigation, with HTML or XHTML alone, provides "static" content, meaning that the user requests a web page and simply views the page and the information on that page. However, a web page can also provide a "live", "dynamic", or "interactive" user experience. Content (text, images, form fields, etc.) on a web page can change, in response to different contexts or conditions. There are two ways to create this kind of effect: Using client-side scripting to change interface behaviors within a specific web page, in response to mouse or keyboard actions, data received from a web API, websocket or at specified timing events. In this case the dynamic behavior occurs within the presentation. Using server-side scripting to change the supplied page source code between pages, adjusting the sequence or reload of the web pages or web content supplied to the browser. Server responses may be determined by such conditions as data in a posted HTML form, parameters in the URL, the type of browser being used, the passage of time, or a database or server state. Web pages that use client-side scripting must use presentation technology broadly called rich interfaced pages. Client-side scripting languages like JavaScript or ActionScript, used for Dynamic HTML (DHTML) and Flash technologies respectively, are frequently used to orchestrate media types (sound, animations, changing text, etc.) of the presentation. The scripting also allows use of remote scripting, a technique by which the DHTML page requests additional information from a server, using a hidden Frame, XMLHttpRequests, or a web service. It is also possible to use a web framework to create a web API, which the client, via the use of JavaScript, uses to obtain data and alter its appearance or behavior dynamically depending on the data. Web pages that use server-side scripting are often created with the help of server-side languages such as PHP, Perl, ASP, JSP, ColdFusion and other languages. These server-side languages typically use the Common Gateway Interface (CGI) to produce dynamic web pages. These kinds of pages can also use, on the client-side, the first kind (DHTML, etc.). == History == It is difficult to be precise about "dynamic web page beginnings" or chronology because the precise concept makes sense only after the "widespread development of web pages". HTTP has existed since 1989, HTML, publicly standardized since 1996. The web browser's rise in popularity started with Mosaic in 1993. Between 1995 and 1996, multiple dynamic web products were introduced to the market, including Coldfusion, WebObjects, PHP, and Active Server Pages. The introduction of JavaScript (then known as LiveScript) enabled the production of client-side dynamic web pages, with JavaScript code executed in the client's browser. The letter "J" in the term AJAX originally indicated the use of JavaScript, as well as XML. With the rise of server side JavaScript processing, for example, Node.js, originally developed in 2009, JavaScript is also used to dynamically create pages on the server that are sent fully formed to clients. MediaWiki, the content management system that powers Wikipedia, is an example for an originally server-side dynamic web page, interacted with through form submissions and URL parameters. Throughout time, progressively enhancing extensions such as the visual editor have also added elements that are dynamic on the client side, while the original dynamic server-side elements such as the classic edit form remain available to be fallen back on (graceful degradation) in case of error or incompatibility. == Server-side scripting == A program running on a web server is used to generate the web content on various web pages, manage user sessions, and control workflow. Server responses may be determined by such conditions as data in a posted HTML form, parameters in the URL, the type of browser being used, the passage of time, or a database or server state. Such web pages are often created with the help of server-side languages such as ASP, ColdFusion, Java, JavaScript, Perl, PHP, Ruby, Python, and other languages, by a support server that can run on the same hardware as the web server. These server-side languages often use the Common Gateway Interface (CGI) to produce dynamic web pages. Two notable exceptions are ASP.NET, and JSP, which reuse CGI concepts in their APIs but actually dispatch all web requests into a shared virtual machine. The server-side languages are used to embed tags or markers within the source file of the web page on the web server. When a user on a client computer requests that web page, the web server interprets these tags or markers to perform actions on the server. For example, the server may be instructed to insert information from a database or information such as the current date. Dynamic web pages are often cached when there are few or no changes expected and the page is anticipated to receive considerable amount of web traffic that would wastefully strain the server and slow down page loading if it had to generate the pages on the fly for each request. == Client-side scripting == Client-side scripting is changing interface behaviors within a specific web page in response to input device actions, or at specified timing events. In this case, the dynamic behavior occurs within the presentation. The client-side content is generated on the user's local computer system. Such web pages use presentation technology called rich interfaced pages. Client-side scripting languages like JavaScript or ActionScript, used for Dynamic HTML (DHTML) and Flash technologies respectively, are frequently used to orchestrate media types (sound, animations, changing text, etc.) of the presentation. Client-side scripting also allows the use of remote scripting, a technique by which the DHTML page requests additional information from a server, using a hidden frame, XMLHttpRequests, or a Web service. The first public use of JavaScript was in 1995, when the language was implemented in Netscape Navigator 2, standardized as ECMAScript two years later. Example The client-side content is generated on the client's computer. The web browser retrieves a page from the server, then processes the code embedded in the page (typically written in JavaScript) and displays the retrieved page's content to the user. The innerHTML property (or write command) can illustrate the client-side dynamic page generation: two distinct pages, A and B, can be regenerated (by an "event response dynamic") as document.innerHTML = A and document.innerHTML = B; or "on load dynamic" by document.write(A) and document.write(B). == Combination technologies == All of the client and server components that collectively build a dynamic web page are called a web application. Web applications manage user interactions, state, security, and performance. Ajax uses a combination of both client-side script

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  • UCSD Pascal

    UCSD Pascal

    UCSD Pascal is a Pascal programming language system that runs on the UCSD p-System, a portable, highly machine-independent operating system. UCSD Pascal was first released in 1977. It was developed at the University of California, San Diego (UCSD). == The p-System == In 1977, the University of California, San Diego (UCSD) Institute for Information Systems developed UCSD Pascal to provide students with a common environment that could run on any of the then available microcomputers as well as campus DEC PDP-11 minicomputers. The operating system became known as UCSD p-System. There were three operating systems that IBM offered for its original IBM PC: the UCSD p-System, CP/M-86, and IBM PC DOS. Vendor SofTech Microsystems emphasized p-System's application portability, with virtual machines for 20 CPUs as of the IBM PC's release. It predicted that users would be able to use applications they purchased on future computers running p-System; advertisements called it "the Universal Operating System". PC Magazine denounced UCSD p-System on the IBM PC, stating in a review of Context MBA, written in the language, that it "simply does not produce good code". The p-System did not sell very well for the IBM PC, because of a lack of applications and because it was more expensive than the other choices. Previously, IBM had offered the UCSD p-System as an option for IBM Displaywriter, an 8086-based dedicated word processing machine. (The Displaywriter's native operating system had been developed completely internally and was not opened for end-user programming.) Notable extensions to standard Pascal include separately compilable Units and a String type. Some intrinsics were provided to accelerate string processing (e.g. scanning in an array for a particular search pattern); other language extensions were provided to allow the UCSD p-System to be self-compiling and self-hosted. UCSD Pascal was based on a p-code machine architecture. Its contribution to these early virtual machines was to extend p-code away from its roots as a compiler intermediate language into a full execution environment. The UCSD Pascal p-Machine was optimized for the new small microcomputers with addressing restricted to 16-bit (only 64 KB of memory). James Gosling cites UCSD Pascal as a key influence (along with the Smalltalk virtual machine) on the design of the Java virtual machine. UCSD p-System achieved machine independence by defining a virtual machine, called the p-Machine (or pseudo-machine, which many users began to call the "Pascal-machine" like the OS—although UCSD documentation always used "pseudo-machine") with its own instruction set called p-code (or pseudo-code). Urs Ammann, a student of Niklaus Wirth, originally presented a p-code in his PhD thesis, from which the UCSD implementation was derived, the Zurich Pascal-P implementation. The UCSD implementation changed the Zurich implementation to be "byte oriented". The UCSD p-code was optimized for execution of the Pascal programming language. Each hardware platform then only needed a p-code interpreter program written for it to port the entire p-System and all the tools to run on it. Later versions also included additional languages that compiled to the p-code base. For example, Apple Computer offered a Fortran Compiler (written by Silicon Valley Software, Sunnyvale California) producing p-code that ran on the Apple version of the p-system. Later, TeleSoft (also located in San Diego) offered an early Ada development environment that used p-code and was therefore able to run on a number of hardware platforms including the Motorola 68000, the System/370, and the Pascal MicroEngine. UCSD p-System shares some concepts with the later Java platform. Both use a virtual machine to hide operating system and hardware differences, and both use programs written to that virtual machine to provide cross-platform support. Likewise both systems allow the virtual machine to be used either as the complete operating system of the target computer or to run in a "box" under another operating system. The UCSD Pascal compiler was distributed as part of a portable operating system, the p-System. == History == UCSD p-System began around 1974 as the idea of UCSD's Kenneth Bowles, who believed that the number of new computing platforms coming out at the time would make it difficult for new programming languages to gain acceptance. He based UCSD Pascal on the Pascal-P2 release of the portable compiler from Zurich. He was particularly interested in Pascal as a language to teach programming. UCSD introduced two features that were important improvements on the original Pascal: variable length strings, and "units" of independently compiled code (an idea included into the then-evolving Ada (programming language)). Niklaus Wirth credits the p-System, and UCSD Pascal in particular, with popularizing Pascal. It was not until the release of Turbo Pascal that UCSD's version started to slip from first place among Pascal users. The Pascal dialect of UCSD Pascal came from the subset of Pascal implemented in Pascal-P2, which was not designed to be a full implementation of the language, but rather "the minimum subset that would self-compile", to fit its function as a bootstrap kit for Pascal compilers. UCSD added strings from BASIC, and several other implementation dependent features. Although UCSD Pascal later obtained many of the other features of the full Pascal language, the Pascal-P2 subset persisted in other dialects, notably Borland Pascal, which copied much of the UCSD dialect. == Versions == There were four versions of UCSD p-code engine, each with several revisions of the p-System and UCSD Pascal. A revision of the p-code engine (i.e., the p-Machine) meant a change to the p-code language, and therefore compiled code is not portable between different p-Machine versions. Each revision was represented with a leading Roman Numeral, while operating system revisions were enumerated as the "dot" number following the p-code Roman Numeral. For example, II.3 represented the third revision of the p-System running on the second revision of the p-Machine. === Version I === Original version, never officially distributed outside of the University of California, San Diego. However, the Pascal sources for both Versions I.3 and I.5 were freely exchanged between interested users. Specifically, the patch revision I.5a was known to be one of the most stable. === Version II === Widely distributed, available on many early microcomputers. Numerous versions included Apple II ultimately Apple Pascal, DEC PDP-11, Intel 8080, Zilog Z80, and MOS 6502 based machines, Motorola 68000 and the IBM PC (Version II on the PC was restricted to one 64K code segment and one 64K stack/heap data segment; Version IV removed the code segment limit but cost a lot more). Project members from this era include Dr Kenneth L Bowles, Mark Allen, Richard Gleaves, Richard Kaufmann, Pete Lawrence, Joel McCormack, Mark Overgaard, Keith Shillington, Roger Sumner, and John Van Zandt. === Version III === Custom version written for Western Digital to run on their Pascal MicroEngine microcomputer. Included support for parallel processes for the first time. === Version IV === Commercial version, developed and sold by SofTech. Based on Version II; did not include changes from Version III. Did not sell well due to combination of their pricing structure, performance problems due to p-code interpreter, and competition with native operating systems (on top of which it often ran). After SofTech dropped the product, it was picked up by Pecan Systems, a relatively small company formed of p-System users and fans. Sales revived somewhat, due mostly to Pecan's reasonable pricing structure, but the p-System and UCSD Pascal gradually lost the market to native operating systems and compilers. Available for the TI-99/4A equipped with p-code card, Commodore CBM 8096, Sage II/IV, HP 9000, and BBC Micro with 6502 second processor. == Further use == The Corvus Systems computer used UCSD Pascal for all its user software. The "innovative concept" of the Constellation OS was to run Pascal (interpretively or compiled) and include all common software in the manual, so users could modify as needed.

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  • SAP BTP

    SAP BTP

    SAP Business Technology Platform (SAP BTP) is a platform as a service developed by SAP SE that offers a suite of services including database and data management, AI, analytics, application development, automation and integration all running on one unified platform. == Overview == SAP BTP is made up of four components: Application development and automation: to create applications or extend existing applications. Data and analytics: to access and analyze data across SAP and third-party systems using multi-cloud architecture. Integration: to integrate and connect applications and data. Artificial Intelligence (AI): to access large language models (LLMs) to develop AI. == History == SAP BTP was introduced as part of the SAP strategy to unify its portfolio and cloud offerings under a single platform. The platform was evolved from earlier initiatives such as SAP Cloud Platform and now serves as the central hub for cloud, data, analytics, integration and AI technologies. Initially unveiled as "SAP NetWeaver Cloud" belonging to the SAP HANA Cloud portfolio on October 16, 2012 the cloud platform was reintroduced with the new name "SAP HANA Cloud Platform" on May 13, 2013 as the foundation for SAP cloud products, including the SAP BusinessObjects Cloud. Adoption of the SAP HANA Cloud Platform in 2015 stood at over 4000 customers and 500 partners. In 2016, SAP and Apple Inc. partnered to develop mobile applications on iOS using cloud-based software development kits (SDKs) for the SAP Cloud Platform. On February 27, 2017, SAP HANA Cloud Platform was renamed "SAP Cloud Platform" at the Mobile World Congress. On January 18, 2021, the name "SAP Cloud Platform" was retired from the SAP product portfolio to support SAP BTP. As of October 2024, SAP states that SAP BTP is used by more than 27,000 customers and more than 2,800 partners. Recently, SAP Business One has worked on improving the functionalities of BTP to cater for the demands of digital transformation. The platform offers comprehensive services in AI, application development, automation, integration, data management, and analytics.

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  • New media

    New media

    New media are communication technologies that enable or enhance interaction between users, as well as interaction between users and content. In the middle of the 1990s, the phrase "new media" became widely used as part of a sales pitch for the influx of interactive CD-ROMs for entertainment and education. The new media technologies, sometimes known as Web 2.0, include a wide range of web-related communication tools such as blogs, wikis, online social networking, virtual worlds, and other social media platforms. The phrase "new media" refers to computational media that share material online and through computers. New media inspire new ways of thinking about older media. Media do not replace one another in a clear, linear succession, instead evolving in a more complicated network of interconnected feedback loops . What is different about new media is how they specifically refashion traditional media and how older media refashion themselves to meet the challenges of new media. Unless they contain technologies that enable digital generative or interactive processes, broadcast television programs, non-interactive news websites, feature films, magazines, and books are not considered to be new media. The term "new media" stands in contrast to old media, which dominated the media landscape as a form of mass media for many years. == History == In the 1950s, connections between computing and radical art began to grow stronger. It was not until the 1980s that Alan Kay and his co-workers at Xerox PARC began to give the computability of a personal computer to the individual, rather than have a big organization be in charge of this. In the late 1980s and early 1990s, however, we seem to witness a different kind of parallel relationship between social changes and computer design. Although causally unrelated, conceptually, it makes sense that the Cold War and the design of the Web took place at exactly the same time. Writers and philosophers such as Marshall McLuhan were instrumental in the development of media theory during this period which is now famous declaration in Understanding Media: The Extensions of Man, that "the medium is the message" drew attention to the too often ignored influence media and technology themselves, rather than their "content," have on humans' experience of the world and on society broadly. Until the 1980s, media relied primarily upon print and analog broadcast models such as television and radio. The last twenty-five years have seen the rapid transformation into media which are predicated upon the use of digital technologies such as the Internet and video games. However, these examples are only a small representation of new media. The use of digital computers has transformed the remaining 'old' media, as suggested by the advent of digital television and online publications. Even traditional media forms such as the printing press have been transformed through the application of technologies by using of image manipulation software like Adobe Photoshop and desktop publishing tools. Andrew L. Shapiro argues that the "emergence of new, digital technologies signals a potentially radical shift of who is in control of information, experience and resources". W. Russell Neuman suggests that whilst the "new media" have technical capabilities to pull in one direction, economic and social forces pull back in the opposite direction. According to Neuman, "We are witnessing the evolution of a universal interconnected network of audio, video, and electronic text communications that will blur the distinction between interpersonal and mass communication; and between public and private communication". Neuman argues that new media will: Alter the meaning of geographic distance. Allow for a huge increase in the volume of communication. Provide the possibility of increasing the speed of communication. Provide opportunities for interactive communication. Allow forms of communication that were previously separate to overlap and interconnect. Consequently, it has been the contention of scholars such as Douglas Kellner and James Bohman that new media and particularly the Internet will provide the potential for a democratic postmodern public sphere, in which citizens can participate in well informed, non-hierarchical debate pertaining to their social structures. Contradicting these positive appraisals of the potential social impacts of new media are scholars such as Edward S. Herman and Robert McChesney who have suggested that the transition to new media has seen a handful of powerful transnational telecommunications corporations who achieve a level of global influence which was hitherto unimaginable. Scholars have highlighted both the positive and negative potential and actual implications of new media technologies, suggesting that some of the early work in new media studies was guilty of technologicaldeterminism – whereby the effects of media were determined by the technologies themselves, rather than by tracing the complex social networks that governed the development, funding, implementation, and future evolution of any technology. Based on the argument that people have a limited amount of time to spend on the consumption of different media, displacement theory argue that the viewership or readership of one particular outlet leads to the reduction in the amount of time spent by the individual on another. The introduction of new media, such as the internet, therefore reduces the amount of time individuals would spend on existing "old" media, which could ultimately lead to the end of such traditional media. == Definition == Although, there are several ways that new media may be described, Lev Manovich, in an introduction to The New Media Reader, defines new media by using eight propositions: New media versus cyberculture – Cyberculture is the various social phenomena that are associated with the Internet and network communications (blogs, online multi-player gaming), whereas new media is concerned more with cultural objects and paradigms (digital to analog television, smartphones). New media as computer technology used as a distribution platform – New media are the cultural objects which use digital computer technology for distribution and exhibition. e.g. (at least for now) Internet, Web sites, computer multimedia, Blu-ray disks etc. The problem with this is that the definition must be revised every few years. The term "new media" will not be "new" anymore, as most forms of culture will be distributed through computers. New media as digital data controlled by software – The language of new media is based on the assumption that, in fact, all cultural objects that rely on digital representation and computer-based delivery do share a number of common qualities. New media is reduced to digital data that can be manipulated by software as any other data. Now media operations can create several versions of the same object. An example is an image stored as matrix data which can be manipulated and altered according to the additional algorithms implemented, such as color inversion, gray-scaling, sharpening, rasterizing, etc. New media as the mix between existing cultural conventions and the conventions of software – New media today can be understood as the mix between older cultural conventions for data representation, access, and manipulation and newer conventions of data representation, access, and manipulation. The "old" data are representations of visual reality and human experience, and the "new" data is numerical data. The computer is kept out of the key "creative" decisions, and is delegated to the position of a technician. e.g. In film, software is used in some areas of production, in others are created using computer animation. New media as the aesthetics that accompanies the early stage of every new modern media and communication technology – While ideological tropes indeed seem to be reappearing rather regularly, many aesthetic strategies may reappear two or three times ... In order for this approach to be truly useful it would be insufficient to simply name the strategies and tropes and to record the moments of their appearance; instead, we would have to develop a much more comprehensive analysis which would correlate the history of technology with social, political, and economical histories or the modern period. New media as faster execution of algorithms previously executed manually or through other technologies – Computers are a huge speed-up of what were previously manual techniques. e.g. calculators. Dramatically speeding up the execution makes possible previously non-existent representational technique. This also makes possible of many new forms of media art such as interactive multimedia and video games. On one level, a modern digital computer is just a faster calculator, we should not ignore its other identity: that of a cybernetic control device. New media as the encoding of modernist avant-garde; new media as metamedia – Manovi

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  • Algorithmic curation

    Algorithmic curation

    Algorithm curation is the selection of online media by technologies such as recommender systems and personalized search. Curation entails the selective sharing of online content and recommendations based on inferred interests. Curation algorithms implement different filter approaches, such as collaborative filtering and content-based filtering. Examples include search engine and social media products such as the Twitter feed, Facebook's News Feed, and Google Personalized Search. == History == === Early algorithmic curation === Online platforms use newsfeed algorithms to determine what content to present to each user. The volume of content published on social media platforms created a need for automated filtering, as manual review of all available content by users is not feasible. These systems function as a form of gatekeeper, shaping which new material users are exposed to and influencing knowledge, attention, and political exposure. ==== Information overload ==== Early ranking algorithms addressed information overload by surfacing the most recent or most popular posts. Later systems shifted toward ranking content based on predicted engagement, aiming to increase the time users spend on a platform. Research has found that these engagement-oriented systems can increase the spread of misinformation and contribute to political polarization as a side effect of optimising for user interaction. ==== How algorithm changes users' feeds over time ==== Algorithmic curation has been found to increase source diversity in some respects while simultaneously reducing the number of external links presented to users, which limits exposure to off-platform content. Research using agent-based modelling has examined how user behaviour, information quality, and algorithmic design interact with one another over time. === Emergence of AI === Platforms increasingly shifted from rule-based ranking systems toward machine-learning and AI-driven approaches, which allow feeds to be personalised at a larger scale and with greater responsiveness to user behaviour. For example, X (formerly Twitter) moved away from a chronological feed toward an AI-powered ranking system that personalises content for each user. These systems are capable of making ranking decisions across volumes of content and user interactions that would not be practical to handle manually. == Approach == === Filter types === ==== Collaborative filtering ==== Collaborative filtering (CF) methods create recommendations based on a person's usage patterns. CF predicts a person's preference for an item by matching their interests with those of users who have similar interests. This process allows for the sharing of ratings between users with similar profiles. CF is based on patterns of human behaviour rather than machine analysis of content itself. Users of CF systems rate items they have interacted with, and these ratings form a profile of interests. The CF system then matches that user with others who have similar profiles, and uses their ratings to generate recommendations. Collaborative filtering can be applied across various content types including text, images, music, and financial products, and can account for complex attributes such as taste and quality that are difficult to represent explicitly. ==== Content-based filtering ==== Content-based filtering (CBF) builds a user profile to represent the types of items a user has engaged with, based on keywords and attributes used to describe those items. Recommendations are generated by presenting items similar to those the user has previously engaged with or is currently viewing. The CBF method creates a profile for each item based on discrete attributes and features, and then constructs a content-based user profile using a weighted vector of those features derived from items the user has rated, purchased, or interacted with. The weights represent the relative importance of each feature, and can be computed using techniques such as Bayesian classifiers, cluster analysis, decision trees, and artificial neural networks, with the goal of estimating the probability that a user will engage with a suggested item. One application of content-based filtering is Pandora Radio, where users provide an artist, genre, or composer to generate a station, and the system surfaces music with similar attributes. == Technology == === Recommender system === Recommender systems rank and suggest content to users based on a combination of implicit and explicit user input. Implicit signals include time spent viewing or engaging with a specific item. Explicit signals include actions such as liking posts, saving store pages, reading news articles, or sharing content. === Personalized search === Personalized search aims to retrieve results most relevant to the user by incorporating contextual factors beyond the explicit query, such as past queries, browsing history, and inferred interests. Social media platforms such as X (formerly Twitter) and Bluesky generate recommendations based on similar users and the content those users interact with. Personalized search may also allow users to explicitly filter results by blocking content containing certain phrases or hashtags. For first-time users without prior history, personalized search may draw on content-based filtering to establish an initial context. Similar processes are used by search engines and retail platforms to tailor results and product recommendations to individual users. == AI contribution == Artificial intelligence contributes to algorithmic curation through machine-learning models capable of processing large volumes of data. Techniques such as deep learning and reinforcement learning allow curation algorithms to model user preferences with greater granularity alongside established filtering approaches. This enables platforms to adjust content rankings rapidly in response to user behaviour. In social media and streaming contexts, AI-driven systems arrange feeds according to predicted relevance, with the outputs shaped by patterns present in the training data. == Social media and potential impact == === Echo chambers === Social media algorithms, such as those used by X (formerly Twitter), recommend content that the system predicts a user will engage with positively. Content from accounts with differing perspectives is less likely to be surfaced, which may reduce source and topic diversity and contribute to the formation of echo chambers. For example, Facebook's news feed is designed to surface content aligned with users' prior engagement, which may reinforce existing views. This dynamic may contribute to filter bubbles, in which users are seldom exposed to content outside their existing interests. Users may further narrow their feeds by actively blocking certain content or accounts. === Over-representation === A pattern observed across social media platforms is the concentration of algorithmic visibility among a small subset of users. Content from the most active users, those with the largest followings, or those generating the most engagement tends to be surfaced more frequently, meaning a small number of accounts can account for a disproportionate share of what appears in other users' feeds.

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