AI Content Understanding

AI Content Understanding — independent reviews, comparisons, pricing and step-by-step guides on Aizhi.

  • DeepRoute.ai

    DeepRoute.ai

    DeepRoute.ai (Chinese: 元戎启行) is a Chinese autonomous driving company founded in 2019 and headquartered in Shenzhen, China. The company develops full-stack self-driving solutions including perception, decision-making, and control systems. == History == DeepRoute.ai was founded in February 2019 in Shenzhen, China, by Zhou Guang (周光), who serves as the company's CEO. In September 2019, the company collaborated with Dongfeng for a live-streamed autonomous driving demonstration. In October 2019, during the 7th Military World Games, DeepRoute.ai conducted Robotaxi demonstration operations. In November 2019, it obtained an intelligent connected vehicle road test permit for public roads in Shenzhen. In October 2020, DeepRoute.ai signed an "Autonomous Driving Leadership Project" with Dongfeng to build one of China's largest autonomous fleets. In August 2020, DeepRoute.ai announced its partnership with Cao Cao Mobility, a Geely-backed ride-hailing company, to test Robotaxis in Hangzhou for daily operations, planning to provide Robotaxis during the 2022 Asian Games. In September 2021, DeepRoute.ai secured US$300 million in a Series B funding round led by Alibaba. In December 2021, the company unveiled its DeepRoute-Driver 2.0, an L4-level autonomous driving solution comprising five solid-state lidar sensors, eight cameras, a proprietary computing system and an optional millimeter-wave radar. with a production cost of under US$10,000. In June 2022, it partnered with Deppon Express to provide autonomous light truck freight transfer services. In March 2023, the company launched its high-precision map-free intelligent driving solution, DeepRoute-Driver 3.0. In November 2024, Great Wall Motor announced a $100 million Series C funding round for Deeproute. With this, Deeproute has completed five rounds of financing, raising a cumulative total of over $500 million. Its shareholders include Fosun RZ Capital, Yunqi Partners, Alibaba, Vision Plus Capital, and Dongfeng, among others. In the same month, Deeproute.ai emphasised that they were in "deep cooperation" with Nvidia and spoke on being part of the first batch of companies in China to get a hold of Nvidia's newer Thor chip for cars which will be used in a new system released next year. This new system will help manage more complex driving scenarios through visual cues. == Products == === VLA Model === VLA Model is a Vision–language–action model designed for autonomous driving systems. It integrates visual perception, semantic understanding, and action decision-making into a unified framework, aiming to enhance the safety and adaptability of advanced driver-assistance systems (ADAS) in complex road environments. The model was officially launched on August 26, 2025, as the core of DeepRoute.ai's DeepRoute IO 2.0 platform. The VLA model is characterized by its "visual-language-action" architecture, which incorporates a chain-of-thought (CoT) reasoning capability inspired by large language models. This design is intended to address the "black box" limitations of traditional end-to-end autonomous driving systems by enabling the model to analyze information, infer causality, and make decisions in a more transparent and interpretable manner. === Appliance === The company has partnered with several automakers including Dongfeng Motor Corporation and Geely to develop and test autonomous vehicles.

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  • Vue.js

    Vue.js

    Vue.js (commonly referred to as Vue; pronounced "view") is an open-source model–view–viewmodel front end JavaScript framework for building user interfaces and single-page applications. It was created by Evan You and is maintained by him and the rest of the active core team members. == Overview == Vue.js features an incrementally adaptable architecture that focuses on declarative rendering and component composition. The core library is focused on the view layer only. Advanced features required for complex applications such as routing, state management and build tooling are offered via officially maintained supporting libraries and packages. Vue.js allows for extending HTML with HTML attributes called directives. The directives offer functionality to HTML applications, and come as either built-in or user defined directives. == History == Vue was created by Evan You after working for Google using AngularJS in several projects. He later summed up his thought process: "I figured, what if I could just extract the part that I really liked about Angular and build something really lightweight." The first source code commit to the project was dated July 2013, at which time it was originally named "Seed". Vue was first publicly announced the following February, in 2014. Version names are often derived from manga and anime series, with the first letters arranged in alphabetical order. === Versions === When a new major is released i.e. v3.y.z, the last minor i.e. 2.x.y will become a LTS release for 18 months (bug fixes and security patches) and for the following 18 months will be in maintenance mode (security patches only). Vue 3 was officially released in September 2020. According to the State of Vue.js Report 2025, 96% of surveyed developers reported having used Vue 3.x. However, 35% also indicated that they used Vue 2.7.x in the past year, reflecting continued reliance on Vue 2 despite its end of support. The report also noted that more than a quarter of respondents encountered challenges when migrating from Vue 2 to Vue 3. === State management evolution === 2015 - Vuex introduced as official state management solution 2021 - Pinia development begins as Vuex 5 experiment 2022 - Pinia becomes officially recommended for new projects 2023 - Vue team announces Vuex maintenance mode transition According to the State of Vue.js Report 2025, the Vue's core team recommendation is reflected in developer adoption–over 80% of surveyed developers reported using Pinia while Vuex still had 38.4% usage, indicating ongoing reliance on the older library. == Features == === Components === Vue components extend basic HTML elements to encapsulate reusable code. At a high level, components are custom elements to which the Vue's compiler attaches behavior. In Vue, a component is essentially a Vue instance with pre-defined options. The code snippet below contains an example of a Vue component. The component presents a button and prints the number of times the button is clicked: === Templates === Vue uses an HTML-based template syntax that allows binding the rendered DOM to the underlying Vue instance's data. All Vue templates are valid HTML that can be parsed by specification-compliant browsers and HTML parsers. Vue compiles the templates into virtual DOM render functions. A virtual Document Object Model (or "DOM") allows Vue to render components in its memory before updating the browser. Combined with the reactivity system, Vue can calculate the minimal number of components to re-render and apply the minimal amount of DOM manipulations when the app state changes. Vue users can use template syntax or choose to directly write render functions using hyperscript either through function calls or JSX. Render functions allow applications to be built from software components. === Reactivity === Vue features a reactivity system that uses plain JavaScript objects and optimized re-rendering. Each component keeps track of its reactive dependencies during its render, so the system knows precisely when to re-render, and which components to re-render. === Transitions === Vue provides a variety of ways to apply transition effects when items are inserted, updated, or removed from the DOM. This includes tools to: Automatically apply classes for CSS transitions and animations Integrate third-party CSS animation libraries, such as Animate.css Use JavaScript to directly manipulate the DOM during transition hooks Integrate third-party JavaScript animation libraries, such as Velocity.js When an element wrapped in a transition component is inserted or removed, this is what happens: Vue will automatically sniff whether the target element has CSS transitions or animations applied. If it does, CSS transition classes will be added/removed at appropriate timings. If the transition component provided JavaScript hooks, these hooks will be called at appropriate timings. If no CSS transitions/animations are detected and no JavaScript hooks are provided, the DOM operations for insertion and/or removal will be executed immediately on next frame. === Routing === A traditional disadvantage of single-page applications (SPAs) is the inability to share links to the exact "sub" page within a specific web page. Because SPAs serve their users only one URL-based response from the server (it typically serves index.html or index.vue), bookmarking certain screens or sharing links to specific sections is normally difficult if not impossible. To solve this problem, many client-side routers delimit their dynamic URLs with a "hashbang" (#!), e.g. page.com/#!/. However, with HTML5 most modern browsers support routing without hashbangs. Vue provides an interface to change what is displayed on the page based on the current URL path – regardless of how it was changed (whether by emailed link, refresh, or in-page links). Additionally, using a front-end router allows for the intentional transition of the browser path when certain browser events (i.e. clicks) occur on buttons or links. Vue itself doesn't come with front-end hashed routing. But the open-source "vue-router" package provides an API to update the application's URL, supports the back button (navigating history), and email password resets or email verification links with authentication URL parameters. It supports mapping nested routes to nested components and offers fine-grained transition control. With Vue, developers are already composing applications with small building blocks building larger components. With vue-router added to the mix, components must merely be mapped to the routes they belong to, and parent/root routes must indicate where children should render. The code above: Sets a front-end route at websitename.com/user/. Which will render in the User component defined in (const User...) Allows the User component to pass in the particular id of the user which was typed into the URL using the $route object's params key: $route.params.id. This template (varying by the params passed into the router) will be rendered into inside the DOM's div#app. The finally generated HTML for someone typing in: websitename.com/user/1 will be: == Ecosystem == The core library comes with tools and libraries both developed by the core team and contributors. === Official tooling === Devtools – Browser devtools extension for debugging Vue.js applications Vite – Standard Tooling for rapid Vue.js development Vue Loader – a webpack loader that allows the writing of Vue components in a format called Single-File Components (SFCs) Vue.js Plugins Collection - Collection of almost 100 plugins and ecosystem libraries across various categories. === Official libraries === Vue Router – The official router, suitable for building SPAs Pinia – The official state management solution === Video courses === Vue School – Expert-led courses on Vue.js and its ecosystem. === State management libraries === Pinia – Official state management solution with modular architecture Vuex – Legacy state management library, now in maintenance mode VueUse – Collection of 200+ composition utilities including state management helpers === Community & Core Teams Resources === The State of Vue.js Report - A comprehensive publication about Vue.js created since 2017 by Monterail, Vue & Nuxt Official Partner. Each edition includes unique data from developer survey, key ecosystem trends and case studies. The latest 5th edition released in March 2025 was co-created with Evan You and Vue&Nuxt Core Teams. Although the Vue.js Ecosystem is generally very well-developed, developers point to some ecosystem gaps as one of the most important thing missing (as of March 2025 Developer Survey in the State of Vue.js Report 2025). 22% of respondents mentioned the lack of robust, official component libraries like MUI or Radix, and the need for better testing utilities. There was also demand for more modular, enterprise-ready solutions for dashboards, e-commerce, and animation libraries similar to Fr

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  • Outline of web design and web development

    Outline of web design and web development

    The following outline is provided as an overview of and topical guide to web design and web development, two very related fields: Web design – field that encompasses many different skills and disciplines in the production and maintenance of websites. The different areas of web design include web graphic design; interface design; authoring, including standardized code and proprietary software; user experience design; and search engine optimization. Often many individuals will work in teams covering different aspects of the design process, although some designers will cover them all. The term web design is normally used to describe the design process relating to the front-end (client side) design of a website including writing markup. Web design partially overlaps web engineering in the broader scope of web development. Web designers are expected to have an awareness of usability and if their role involves creating markup then they are also expected to be up to date with web accessibility guidelines. Web development – work involved in developing a web site for the Internet (World Wide Web) or an intranet (a private network). Web development can range from developing a simple single static page of plain text to complex web-based internet applications (web apps), electronic businesses, and social network services. A more comprehensive list of tasks to which web development commonly refers, may include web engineering, web design, web content development, client liaison, client-side/server-side scripting, web server and network security configuration, and e-commerce development. Among web professionals, "web development" usually refers to the main non-design aspects of building web sites: writing markup and coding. Web development may use content management systems (CMS) to make content changes easier and available with basic technical skills. For larger organizations and businesses, web development teams can consist of hundreds of people (web developers) and follow standard methods like Agile methodologies while developing websites. Smaller organizations may only require a single permanent or contracting developer, or secondary assignment to related job positions such as a graphic designer or information systems technician. Web development may be a collaborative effort between departments rather than the domain of a designated department. There are three kinds of web developer specialization: front-end developer, back-end developer, and full-stack developer. Front-end developers are responsible for behaviour and visuals that run in the user browser, back-end developers deal with the servers and full-stack developers are responsible for both. Currently, the demand for React and Node.JS developers are very high all over the world. == Web design == Graphic design Typography Page layout User experience design (UX design) User interface design (UI design) Web Design techniques Responsive web design (RWD) Adaptive web design (AWD) Progressive enhancement Tableless web design Software Adobe Photoshop Adobe Illustrator Adobe XD Figma Sketch (software) Affinity Designer Inkscape == Web development == Front-end web development – the practice of converting data to a graphical interface, through the use of HTML, CSS, and JavaScript, so that users can view and interact with that data. HyperText Markup Language (HTML) (.html) Cascading Style Sheets (CSS) (.css) CSS framework JavaScript (.js) Package managers for JavaScript npm (originally short for Node Package Manager) Server-side scripting (also known as "Server-side (web) development" or "Back-end (web) development") ASP (.asp) ASP.NET Web Forms (.aspx) ASP.NET Web Pages (.cshtml, .vbhtml) ColdFusion Markup Language (.cfm) Go (.go) Google Apps Script (.gs) Hack (.php) Haskell (.hs) (example: Yesod) Java (.jsp) via JavaServer Pages JavaScript or TypeScript using Server-side JavaScript (.ssjs, .js, .ts) (example: Node.js) Lasso (.lasso) Lua (.lp .op .lua) Node.js (.node) Parser (.p) Perl via the CGI.pm module (.cgi, .ipl, .pl) PHP (.php, .php3, .php4, .phtml) Progress WebSpeed (.r,.w) Python (.py) (examples: Pyramid, Flask, Django) R (.rhtml) – (example: rApache) React (.jsx, .tsx) Ruby (.rb, .rbw) (example: Ruby on Rails) SMX (.smx) Tcl (.tcl) Full stack web development – involves both front-end and back-end (server-side) development Web framework Types of framework architectures Model–view–controller Three-tier architecture Software Atom IntelliJ IDEA Sublime Text Visual Studio Code

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  • W3C Device Description Working Group

    W3C Device Description Working Group

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

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  • Sorenson Squeeze

    Sorenson Squeeze

    Sorenson Squeeze was a software video encoding tool used to compress and convert video and audio files on Mac OS X or Windows operating systems. It was sold as a standalone tool and has also long been bundled with Avid Media Composer. == History == Sorenson Squeeze was first announced on July 17, 2001, as the first variable bit rate (VBR) compression application for Mac OS X, and was released on October 29 of that same year. By March 2002, Sorenson Squeeze became available for Windows OS. Sorenson Squeeze was originally released as a tool for encoding videos for the Web and QuickTime playback but began adding new codecs as more versions were released. The software was discontinued by Sorenson in January 2019, and correspondingly was no longer offered as part of Avid Media Composer. == Features == Squeeze included a number of features to improve video & audio quality. Features included: GPU accelerated H.264 encoding, adaptive bitrate encoding, HD encoding and Dolby certified AC3 Audio. Intelligent encoding presets available in Squeeze included: x265 (H.265) MainConcept H.264 and MainConcept H.264 CUDA. Adaptive bitrate encoding allows for optimal bitrate and error resilience based on network conditions, resulting in a dynamic adjustment of the video bitstream being delivered. It encoded to multiple formats including QuickTime, Windows Media, Flash Video, Silverlight, WebM & WMV. It uses multiple codecs, including the Sorenson codecs SV3 Pro and Spark, H.265, H.264, H.263, VP6, VC1, MPEG2, and many others. Squeeze operates on the Apple Macintosh and Microsoft Windows operating systems. Squeeze offers native plugins to Avid, Apple Final Cut Pro and Adobe Premiere (CS4, CS5) NLEs. Each copy of Squeeze included the Dolby Certified AC3 Consumer encoder. Squeeze also included a simplified review and approval process, which allows the user to automatically send secure, password protected videos for immediate review. Instant feedback is received via Web or mobile. == Versions == Sorenson Squeeze was released on October 29, 2001. Sorenson Squeeze for Macromedia Flash MX was released on March 14, 2002. Sorenson Squeeze 3 for MPEG-4 was released in January 2003. Sorenson Squeeze 3 Compression Suite was released in January 2003. Sorenson Squeeze 5 was released on March 31, 2008. Sorenson Squeeze was updated to version 5.1 on May 11, 2009. Sorenson Squeeze 6 was released on November 3, 2009. Sorenson Squeeze 7 was released January 25, 2011. Sorenson Squeeze 11 was released August 27, 2016. == Awards == Streaming Media magazine Readers’ Choice Award for Encoding Software for 2007, 2008, 2009 and 2010. 2008 Vanguard Award from Digital Content Producer magazine == Squeeze 7 system requirements == Windows Pentium IV-based computer or greater Windows XP, Vista or 7 32- and 64-bit compatible (including AVID 64-bit update); Faster performance on 64-bit systems 512 MB RAM 120 MB available hard drive space QuickTime 7.2 or later DirectX 9.0b or later Macintosh Intel-based processor Mac OS 10.4 or later 32- and 64-bit compatible; Faster performance on 64-bit systems 512 MB RAM 120 MB available hard drive space QuickTime 7.2 or later

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  • Amplified conference

    Amplified conference

    An amplified conference is a conference or similar event in which the talks and discussions at the conference are 'amplified' through use of networked technologies in order to extend the reach of the conference deliberations. The term was originally coined by Lorcan Dempsey in a blog post. The term is now widely used within the academic and research community with Wankel proposing the following definition: The extension of a physical event (or a series of events) through the use of social media tools for expanding access to (aspects of) the event beyond physical and temporal bounds. Such amplification takes place in the context of intent to make the most of the intellectual content, discussion, networking, and discovery initiated by the event through the process of sharing with co-attendees, colleagues, friends and wider informed publics. A paper by Haider and others illustrates how amplified conferences are becoming mainstream in a discussion on "how social media have been employed as part of the project, particularly around event amplification". As described by Guy in the Ariadne ejournal the term is not a prescriptive one, but rather describes a pattern of behaviors which initially took place at IT and Web-oriented conferences once WiFi networks started to become available at conference venues and delegates started to bring with them networked devices such as laptops and, more recently, PDAs and mobile phones. == Different Approaches to 'Amplification' of Conferences == There are a number of ways in which conferences can be amplified through use of networked technologies: Amplification of the audiences' voice: Prior to the availability of real time chat technologies at events (whether use of IRC, Twitter, instant messaging clients, etc.) it was only feasible to discuss talks with immediate neighbours, and even then this may be considered rude. Amplification of the speaker's talk: The availability of video and audio-conferencing technologies make it possible for a speaker to be heard by an audience which isn't physically present at the conference. Although use of video technologies has been available to support conferences for some time, this has normally been expensive and require use of dedicated video-conferencing technologies. However the availability of lightweight desktop tools make it much easier to deploy such technologies, without even, requiring the involvement of conference organisers. Amplification across time: Video and audio technologies can also be used to allow a speaker's talk to be made available after the event, with use of podcasting or videocasting technologies allowing the talks to be easily syndicated to mobile devices as well as accessed on desktop computers. Amplification of the speaker's slides: The popularity of global repository services for slides, such as SlideShare, enable the slides used by a speaker to be more easily found, embedded on other Web sites and commented upon, in ways that were not possible when the slides, if made available at all, were only available on a conference Web site. Amplification of feedback to the speaker: Micro-blogging technologies, such as Twitter, are being used not only as a discussion channel for conference participants but also as a way of providing real-time feedback to a speaker during a talk. We are also now seeing dedicated microblogging technologies, such as Coveritlive and Scribblelive, being developed which aim to provide more sophisticated 'back channels' for use at conferences. Amplification of a conference's collective memory: The popularity of digital cameras and the photographic capabilities of many mobile phones is leading to many photographs being taken at conferences. With such photographs often being uploaded to popular photographic sharing services, such as Flickr, and such collections being made more easy to discover through agreed use of tags, we are seeing amplification of the memories of an event though the sharing of such resources. The ability of such photographic resources to be 'mashed up' with, say, accompanying music, can similarly help to enrich such collective experiences. Amplification of the learning: The ability to be able to follow links to resources and discuss the points made by a speaker during a talk can enrich the learning which takes place at an event, as described by Shabajee's article on "'Hot' or Not? Welcome to real-time peer review" published in the Times Higher Education Supplement in May 2003. Long term amplification of conference outputs: The availability in a digital format of conference resources, including 'official' resources such as slides, video and audio recordings, etc. which have been made by the conference organisers with the approval of speakers, together with more nebulous resources such as archives of conference back channels, and photographs and unofficial recordings taken at the event may help to provide a more authentic record of an event, which could potentially provide a valuable historical record. The amplification of conferences can be viewed as an example of how new technologies are altering standard practice. By using these techniques a different type of interaction is created at the conference itself, but also the boundaries around the conference can be seen as permeable, with remote participants engaging in discussion. An amplified conference also provides a considerably altered archive compared with a 'traditional' one. For the latter, the printed proceedings will be the main record, but for an amplified event this record is distributed across many media and takes in a wider range of content types, including the papers, videos of the presentations (for example on YouTube), the slides (e.g. on Slideshare), photos of the event (Flickr), interaction between participants (Twitter), reflections and comments (blogs), etc. The amplified conference represents an example of changing practice in digital scholarship.

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  • Influencer speak

    Influencer speak

    Influencer speak is a speech pattern commonly associated with English-speaking digital content creators, particularly on platforms such as TikTok. This style is characterized by linguistic features such as uptalk, where intonation rises at the end of declarative sentences, and vocal fry, a low, creaky vibration in speech. These features are often used to engage audiences. == Characteristics == Influencer speak is commonly associated with: Uptalk – a rising intonation at the end of statements Vocal fry – a creaky sound often occurring at the end of sentences Use of filler words and slang – contributes to a conversational tone that resonates with audiences == Origins == The origins of "influencer speak" are linked to the "Valley Girl" accent, which became prominent in the 1980s. This earlier style included features such as uptalk and vocal fry, which have been adapted for digital platforms. Linguists have noted that these patterns are often led by young women, who are recognized as linguistic innovators in sociolinguistic research. == Sociolinguistic significance == "Influencer speak" is used to maintain audience engagement. Features such as uptalk help speakers retain the "conversational floor," ensuring continuous attention from listeners. A study conducted by UCLA researchers has shown that creators adjust their speech styles based on the platform and audience. For example, a comedic tone may be emphasized on TikTok, while a more professional tone may be used on platforms such as LinkedIn or YouTube.

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  • Deplatforming

    Deplatforming

    Deplatforming, also known as no-platforming, is a boycott on an individual or group by removing the platforms used to share their information or ideas. The term is commonly associated with social media. == History == === Deplatforming of invited speakers === In the United States, the banning of speakers on university campuses dates back to the 1940s. This was carried out by the policies of the universities themselves. The University of California had a policy known as the Speaker Ban, codified in university regulations under President Robert Gordon Sproul, that mostly, but not exclusively, targeted communists. One rule stated that "the University assumed the right to prevent exploitation of its prestige by unqualified persons or by those who would use it as a platform for propaganda." This rule was used in 1951 to block Max Shachtman, a socialist, from speaking at the University of California at Berkeley. In 1947, former U.S. Vice President Henry A. Wallace was banned from speaking at UCLA because of his views on U.S. Cold War policy, and in 1961, Malcolm X was prohibited from speaking at Berkeley as a religious leader. Controversial speakers invited to appear on college campuses have faced deplatforming attempts to disinvite them or to otherwise prevent them from speaking. The British National Union of Students established its No Platform policy as early as 1973. In the mid-1980s, visits by South African ambassador Glenn Babb to Canadian college campuses faced opposition from students opposed to apartheid. In the United States, recent examples include the March 2017 disruption by protestors of a public speech at Middlebury College by political scientist Charles Murray. In February 2018, students at the University of Central Oklahoma rescinded a speaking invitation to creationist Ken Ham, after pressure from an LGBT student group. In March 2018, a "small group of protesters" at Lewis & Clark Law School attempted to stop a speech by visiting lecturer Christina Hoff Sommers. In the 2019 film No Safe Spaces, Adam Carolla and Dennis Prager documented their own disinvitation along with others. As of February 2020, the Foundation for Individual Rights in Education, a speech advocacy group, documented 469 disinvitation or disruption attempts at American campuses since 2000, including both "unsuccessful disinvitation attempts" and "successful disinvitations"; the group defines the latter category as including three subcategories: formal disinvitation by the sponsor of the speaking engagement; the speaker's withdrawal "in the face of disinvitation demands"; and "heckler's vetoes" (situations when "students or faculty persistently disrupt or entirely prevent the speakers' ability to speak"). === Deplatforming in social media === Beginning in 2015, Reddit banned several communities on the site ("subreddits") for violating the site's anti-harassment policy. A 2017 study published in the journal Proceedings of the ACM on Human-Computer Interaction, examining "the causal effects of the ban on both participating users and affected communities," found that "the ban served a number of useful purposes for Reddit" and that "Users participating in the banned subreddits either left the site or (for those who remained) dramatically reduced their hate speech usage. Communities that inherited the displaced activity of these users did not suffer from an increase in hate speech." In June 2020 and January 2021, Reddit also issued bans to pro-Trump communities over violations of the website's content and harassment policies. On May 2, 2019, Facebook and the Facebook-owned platform Instagram announced a ban of "dangerous individuals and organizations" including Nation of Islam leader Louis Farrakhan, Milo Yiannopoulos, Alex Jones and his organization InfoWars, Paul Joseph Watson, Laura Loomer, and Paul Nehlen. In the wake of the 2021 storming of the US Capitol, Twitter banned then-president Donald Trump, as well as 70,000 other accounts linked to the event and the far-right movement QAnon. Some studies have found that the deplatforming of extremists reduced their audience, although other research has found that some content creators became more toxic following deplatforming and migration to alt-tech platform. ==== Twitter ==== On November 18, 2022, Elon Musk, as newly appointed CEO of Twitter, reopened previously banned Twitter accounts of high-profile users, including Kathy Griffin, Jordan Peterson, and The Babylon Bee as part of the new Twitter policy. As Musk exclaimed, "New Twitter policy is freedom of speech, but not freedom of reach". ==== Alex Jones ==== On August 6, 2018, Facebook, Apple, YouTube and Spotify removed all content by Jones and InfoWars for policy violations. YouTube removed channels associated with InfoWars, including The Alex Jones Channel. On Facebook, four pages associated with InfoWars and Alex Jones were removed over repeated policy violations. Apple removed all podcasts associated with Jones from iTunes. On August 13, 2018, Vimeo removed all of Jones's videos because of "prohibitions on discriminatory and hateful content". Facebook cited instances of dehumanizing immigrants, Muslims and transgender people, as well as glorification of violence, as examples of hate speech. After InfoWars was banned from Facebook, Jones used another of his websites, NewsWars, to circumvent the ban. Jones's accounts were also removed from Pinterest, Mailchimp and LinkedIn. As of early August 2018, Jones retained active accounts on Instagram, Google+ and Twitter. In September, Jones was permanently banned from Twitter and Periscope after berating CNN reporter Oliver Darcy. On September 7, 2018, the InfoWars app was removed from the Apple App Store for "objectionable content". He was banned from using PayPal for business transactions, having violated the company's policies by expressing "hate or discriminatory intolerance against certain communities and religions." After Elon Musk's purchase of Twitter several previously banned accounts were reinstated including Donald Trump, Andrew Tate and Ye resulting in questioning if Alex Jones will be unbanned as well. However Musk denied that Alex Jones will be unbanned criticizing Jones as a person that "would use the deaths of children for gain, politics or fame". InfoWars remained available on Roku devices in January 2019, a year after the channel's removal from multiple streaming services. Roku indicated that they do not "curate or censor based on viewpoint," and that it had policies against content that is "unlawful, incited illegal activities, or violates third-party rights," but that InfoWars was not in violation of these policies. Following a social media backlash, Roku removed InfoWars and stated "After the InfoWars channel became available, we heard from concerned parties and have determined that the channel should be removed from our platform." In March 2019, YouTube terminated the Resistance News channel due to its reuploading of live streams from InfoWars. On May 1, 2019, Jones was barred from using both Facebook and Instagram. Jones briefly moved to Dlive, but was suspended in April 2019 for violating community guidelines. In March 2020, the InfoWars app was removed from the Google Play store due to claims of Jones disseminating COVID-19 misinformation. A Google spokesperson stated that "combating misinformation on the Play Store is a top priority for the team" and apps that violate Play policy by "distributing misleading or harmful information" are removed from the store. ==== Donald Trump ==== On January 6, 2021, in a joint session of the United States Congress, the counting of the votes of the Electoral College was interrupted by a breach of the United States Capitol chambers. The rioters were supporters of President Donald Trump who hoped to delay and overturn the President's loss in the 2020 election. The event resulted in five deaths and at least 400 people being charged with crimes. The certification of the electoral votes was only completed in the early morning hours of January 7, 2021. In the wake of several Tweets by President Trump on January 7, 2021 Facebook, Instagram, YouTube, Reddit, and Twitter all deplatformed Trump to some extent. Twitter deactivated his personal account, which the company said could possibly be used to promote further violence. Trump subsequently tweeted similar messages from the President's official US Government account @POTUS, which resulted in him being permanently banned on January 8. Twitter then announced that Trump's ban from their platform would be permanent. Trump planned to rejoin on social media through the use of a new platform by May or June 2021, according to Jason Miller on a Fox News broadcast. The same week Musk announced Twitter's new freedom of speech policy, he tweeted a poll to ask whether to bring back Trump into the platform. The poll ended with 51.8% in favor of unbanning Trump's account. Twitter has since reinstated Trump's Twitter accou

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  • List of publications in data science

    List of publications in data science

    This is a list of publications in data science, generally organized by order of use in a data analysis workflow. See the list of publications in statistics for more research-based and fundamental publications; while this list is more applied, business oriented, and cross-disciplinary. General article inclusion criteria are: Papers from notable practitioners or notable professors, either with a Wikipedia page or reference to their notability Common knowledge all data professionals should know, with references validating this claim Highly cited applied statistics and machine learning publications Discussion-facilitating papers on the field of data science as a whole (for example, the Attention Is All You Need paper is arguably a landmark paper that can be added here, but it is specific to generative artificial intelligence, not for all practitioners of data) Some reasons why a particular publication might be regarded as important: Topic creator – A publication that created a new topic Breakthrough – A publication that changed scientific knowledge significantly Influence – A publication which has significantly influenced the world or has had a massive impact on the teaching of data science. When possible, a reference is used to validate the inclusion of the publication in this list. == History == Statistical Modeling: The Two Cultures (with comments and a rejoinder by the author) Author: Leo Breiman Publication data: Online version: https://projecteuclid.org/journals/statistical-science/volume-16/issue-3/Statistical-Modeling--The-Two-Cultures-with-comments-and-a/10.1214/ss/1009213726.pdf Description: Describes two cultures of statistics, one using a parsimonious and generative stochastic model, while the other is an algorithmic model with no known mechanism for how the data is generated. Breiman argues that while statistics has traditionally favored using the stochastic model, there is value in expanding the methods that statisticians can use to study phenomenon. Importance: Influence on the philosophies of statisticians right before the increased use of machine learning and deep learning methods. In a 20-year retrospective on this article, "Breiman's words are perhaps more relevant than ever". Notable statisticians at the time wrote opinion pieces about the publication. Although overall critical of the publication, David Cox writes that the publication "contains enough truth and exposes enough weaknesses to be thought-provoking." Bradley Efron commented that this publication is a "stimulating paper". Emanuel Parzen also comments about this publication that "Breiman alerts us to systematic blunders (leading to wrong conclusions) that have been committed applying current statistical practice of data modeling". Data Scientist: The Sexiest Job of the 21st Century Author: Thomas H. Davenport and DJ Patil Publication data: Online version: hbr.org/2022/07/is-data-scientist-still-the-sexiest-job-of-the-21st-century Description: Describes the new role at companies that is coined "Data scientist", what they do, how an organization might recruit one to their organization, and how to work with one effectively. Importance: This publication has been an influence on the data community as mentioned near the time it was published in 2012 by institutions like IEEE Spectrum, but also mentioned nearly a decade later asking the same question the title poses. In a retrospective response to their own publication 10 years earlier, authors Davenport and Patil have reflected that the role of a data scientist has "become better institutionalized, the scope of the job has been redefined, the technology it relies on has made huge strides, and the importance of non-technical expertise, such as ethics and change management, has grown". 50 Years of Data Science Author: David Donoho Publication data: Online version: https://www.tandfonline.com/doi/full/10.1080/10618600.2017.1384734 Description: Retrospective discussion paper on the history and origins of data science, with a number of commentary from notable statisticians. Importance: This has been described as "the first in the field to present such a comprehensive and in-depth survey and overview", and helps to define the field that has many definitions. The Composable Data Management System Manifesto Author: Pedro Pedreira, Orri Erling, Konstantinos Karanasos, Scott Schneider, Wes McKinney, Satya R Valluri, Mohamed Zait, Jacques Nadeau Publication data: Online version: https://www.vldb.org/pvldb/vol16/p2679-pedreira.pdf Description: The vision paper advocating for a paradigm shift in how data management systems are designed using standard, composable, interoperable tools rather than siloed software tools. Importance: A paradigm shifting view on how future data science software tools should be designed for more efficient workflows, the principles of which "will be especially crucial for addressing fragmentation, improving interoperability, and promoting user-centricity as data ecosystems grow increasingly complex". == Data collection and organization == Tidy Data Author: Hadley Wickham Publication data: Online version: https://www.jstatsoft.org/article/view/v059i10/ https://vita.had.co.nz/papers/tidy-data.pdf Description: Describes a framework for data cleaning that is summarized in the quote, "each variable is a column, each observation is a row, and each type of observational unit is a table". This allows a standard data structure for which data analysis tools can be consistently built around. Importance: Cited over 1,500 times, this effort for tidy data has been described by David Donoho as having "more impact on today's practice of data analysis than many highly regarded theoretical statistics articles". In the context of data visualization, this publication is said to support "efficient exploration and prototyping because variables can be assigned different roles in the plot without modifying anything about the original dataset". Data Organization in Spreadsheets Author: Karl W. Broman and Kara H. Woo Publication data: Online version: https://www.tandfonline.com/doi/full/10.1080/00031305.2017.1375989 Description: This article offers practical recommendations for organizing data in spreadsheets, like Microsoft Excel and Google Sheets, to reduce errors and lower the barrier for later analyses due to limitations in spreadsheets or quirks in the software. Importance: Influences teaching both data and non-data practitioners to create more analysis-friendly spreadsheets, and has been described to outline "spreadsheet best practices". == Data visualizations == Quantitative Graphics in Statistics: A Brief History Author: James R. Beniger and Dorothy L. Robyn Publication data: Online version: https://www.jstor.org/stable/2683467 Description: Outlines history and evolution of quantitative graphics in statistics, going through spatial organization (17th and 18th centuries), discrete comparison (18th and 19th centuries), continuous distribution (19th century), and multivariate distribution and correlation (late 19th and 20th centuries). Importance: Helps put into perspective for learning data practitioners the recency of graphics that are used. A later publication "Graphical Methods in Statistics" by Stephen Fienberg in 1979 writes that his publication "owes much to the work of Beniger and Robyn". == Practice == Data Science for Business Author: Foster Provost and Tom Fawcett Publication data: Online version: N/A Description: Broadly outlines principles of data science and data-analytic thinking for businesses. Importance: Cited over 3,000 times, it is "highly recommended for students" but also it is also recommended due to its "relevance to senior management leaders who want to build and lead a team of data scientists and implement data science in solving complex business problems". == Tooling == Hidden Technical Debt in Machine Learning Systems Author: D. Sculley, Gary Holy, Daniel Golovin, Eugene Davydov, Todd Phillips, Dietmar Ebner, Vinay Chaudhary, Michael Young, Jean-François Crespo, Dan Dennison Publication data: Online version: https://proceedings.neurips.cc/paper_files/paper/2015/file/86df7dcfd896fcaf2674f757a2463eba-Paper.pdf Description: This paper argues that it is "dangerous to think of [complex machine learning] quick wins as coming for free" and overviews risk factors to account for when implementing a machine learning system. Importance: All authors worked for Google, article is cited over 2,000 times, and helped practitioners thinking about quickly implementing a machine learning tool without understanding the long-term maintenance of the tool. A few useful things to know about machine learning Author: Pedro Domingos Publication data: Online version: https://dl.acm.org/doi/10.1145/2347736.2347755 https://homes.cs.washington.edu/~pedrod/papers/cacm12.pdf Description: The purpose of this paper is to distill inaccessible "folk knowledge" to effectively implement machine learning projects because "machin

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  • Web syndication

    Web syndication

    Web syndication is making content available from one website to other sites. Most commonly, websites are made available to provide either summaries or full renditions of a website's recently added content. The term may also describe other kinds of content licensing for reuse. Contemporary web syndicates include: MSN, Excite, and Yahoo! News. == Motivation == For the subscribing sites, syndication is an effective way of adding greater depth and immediacy of information to their pages, making them more attractive to users. For the provider site, syndication increases exposure. This generates new traffic for the provider site—making syndication an easy and relatively cheap, or even free, form of advertisement. Content syndication has become an effective strategy for link building, as search engine optimization has become an increasingly important topic among website owners and online marketers. Links embedded within the syndicated content are typically optimized around anchor terms that will point an optimized link back to the website that the content author is trying to promote. These links tell the algorithms of the search engines that the website being linked to is an authority for the keyword that is being used as the anchor text. However the rollout of Google Panda's algorithm may not reflect this authority in its SERP rankings based on quality scores generated by the sites linking to the authority. The prevalence of web syndication is also of note to online marketers, since web surfers are becoming increasingly wary of providing personal information for marketing materials (such as signing up for a newsletter) and expect the ability to subscribe to a feed instead. Although the format could be anything transported over HTTP, such as HTML or JavaScript, it is more commonly XML. Web syndication formats include RSS, Atom, and JSON Feed. == History == Syndication first arose in earlier media such as print, radio, and television, allowing content creators to reach a wider audience. In the case of radio, the United States Federal government proposed a syndicate in 1924 so that the country's executives could quickly and efficiently reach the entire population. In the case of television, it is often said that "Syndication is where the real money is." Additionally, syndication accounts for the bulk of TV programming. One predecessor of web syndication is the Meta Content Framework (MCF), developed in 1996 by Ramanathan V. Guha and others in Apple Computer's Advanced Technology Group. Today, millions of online publishers, including newspapers, commercial websites, and blogs, distribute their news headlines, product offers, and blog postings in the news feed. == As a commercial model == Conventional syndication businesses such as Reuters and Associated Press thrive on the internet by offering their content to media partners on a subscription basis, using business models established in earlier media forms. Commercial web syndication can be categorized in three ways: by business models by types of content by methods for selecting distribution partners Commercial web syndication involves partnerships between content producers and distribution outlets. There are different structures of partnership agreements. One such structure is licensing content, in which distribution partners pay a fee to the content creators for the right to publish the content. Another structure is ad-supported content, in which publishers share revenues derived from advertising on syndicated content with that content's producer. A third structure is free, or barter syndication, in which no currency changes hands between publishers and content producers. This requires the content producers to generate revenue from another source, such as embedded advertising or subscriptions. Alternatively, they could distribute content without remuneration. Typically, those who create and distribute content free are promotional entities, vanity publishers, or government entities. Types of content syndicated include RSS or Atom Feeds and full content. With RSS feeds, headlines, summaries, and sometimes a modified version of the original full content is displayed on users' feed readers. With full content, the entire content—which might be text, audio, video, applications/widgets, or user-generated content—appears unaltered on the publisher's site. There are two methods for selecting distribution partners. The content creator can hand-pick syndication partners based on specific criteria, such as the size or quality of their audiences. Alternatively, the content creator can allow publisher sites or users to opt into carrying the content through an automated system. Some of these automated "content marketplace" systems involve careful screening of potential publishers by the content creator to ensure that the material does not end up in an inappropriate environment. Just as syndication is a source of profit for TV producers and radio producers, it also functions to maximize profit for Internet content producers. As the Internet has increased in size it has become increasingly difficult for content producers to aggregate a sufficiently large audience to support the creation of high-quality content. Syndication enables content creators to amortize the cost of producing content by licensing it across multiple publishers or by maximizing the distribution of advertising-supported content. A potential drawback for content creators, however, is that they can lose control over the presentation of their content when they syndicate it to other parties. Distribution partners benefit by receiving content either at a discounted price, or free. One potential drawback for publishers, however, is that because the content is duplicated at other publisher sites, they cannot have an "exclusive" on the content. For users, the fact that syndication enables the production and maintenance of content allows them to find and consume content on the Internet. One potential drawback for them is that they may run into duplicate content, which could be an annoyance. == E-commerce == Web syndication has been used to distribute product content such as feature descriptions, images, and specifications. As manufacturers are regarded as authorities and most sales are not achieved on manufacturer websites, manufacturers allow retailers or dealers to publish the information on their sites. Through syndication, manufacturers may pass relevant information to channel partners. Such web syndication has been shown to increase sales. Web syndication has also been found effective as a search engine optimization technique.

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  • Telecommunications device for the deaf

    Telecommunications device for the deaf

    A telecommunications device for the deaf (TDD) is a teleprinter, an electronic device for text communication over a telephone line, that is designed for use by persons with hearing or speech difficulties. Other names for the device include teletypewriter (TTY), textphone (common in Europe), and minicom (United Kingdom). The typical TDD is a device about the size of a typewriter or laptop computer with a QWERTY keyboard and small screen that uses an LED, LCD, or VFD screen to display typed text electronically. In addition, TDDs commonly have a small spool of paper on which text is also printed – old versions of the device had only a printer and no screen. The text is transmitted live, via a telephone line, to a compatible device, i.e. one that uses a similar communication protocol. Special telephone services have been developed to carry the TDD functionality even further. In certain countries, there are systems in place so that a deaf person can communicate with a hearing person on an ordinary voice phone using a human relay operator. There are also "carry-over" services, enabling people who can hear but cannot speak ("hearing carry-over", a.k.a. "HCO"), or people who cannot hear but are able to speak ("voice carry-over", a.k.a. "VCO") to use the telephone. The term TDD is sometimes discouraged because people who are deaf are increasingly using mainstream devices and technologies to carry out most of their communication. The devices described here were developed for use on the partially-analog Public Switched Telephone Network (PSTN). They do not work well on the new internet protocol (IP) networks. Thus as society increasingly moves toward IP based telecommunication, the telecommunication devices used by people who are deaf will not be TDDs. In the US and Canada, the devices are referred to as TTYs. Teletype Corporation, of Skokie, Illinois, made page printers for text, notably for news wire services and telegrams, but these used standards different from those for deaf communication, and although in quite widespread use, were technically incompatible. Furthermore, these were sometimes referred to by the "TTY" initialism, short for "Teletype". When computers had keyboard input mechanisms and page printer output, before CRT terminals came into use, Teletypes were the most widely used devices. They were called "console typewriters". (Telex used similar equipment, but was a separate international communication network.) == History == === APCOM acoustic coupler or MODEM device === The TDD concept was developed by James C. Marsters (1924–2009), a dentist and private airplane pilot who became deaf as an infant because of scarlet fever, and Robert Weitbrecht, a deaf physicist. In 1964, Marsters, Weitbrecht and Andrew Saks, an electrical engineer and grandson of the founder of the Saks Fifth Avenue department store chain, founded APCOM (Applied Communications Corp.), located in the San Francisco Bay area, to develop the acoustic coupler, or modem; their first product was named the PhoneType. APCOM collected old teleprinter machines (TTYs) from the Department of Defense and junkyards. Acoustic couplers were cabled to TTYs enabling the AT&T standard Model 500 telephone to couple, or fit, into the rubber cups on the coupler, thus allowing the device to transmit and receive a unique sequence of tones generated by the different corresponding TTY keys. The entire configuration of teleprinter machine, acoustic coupler, and telephone set became known as the TTY. Weitbrecht invented the acoustic coupler modem in 1964. The actual mechanism for TTY communications was accomplished electro-mechanically through frequency-shift keying (FSK) allowing only half-duplex communication, where only one person at a time can transmit. === Paul Taylor TTY device === During the late 1960s, Paul Taylor combined Western Union Teletype machines with modems to create teletypewriters, known as TTYs. He distributed these early, non-portable devices to the homes of many in the deaf community in St. Louis, Missouri. He worked with others to establish a local telephone wake-up service. In the early 1970s, these small successes in St. Louis evolved into the nation's first local telephone relay system for the deaf. === Micon Industries MCM device === In 1973, the Manual Communications Module (MCM), which was the world's first electronic portable TTY allowing two-way telecommunications, premiered at the California Association of the Deaf convention in Sacramento, California. The battery-powered MCM was invented and designed by a deaf news anchor and interpreter, Kit Patrick Corson, in conjunction with Michael Cannon and physicist Art Ogawa. It was manufactured by Michael Cannon's company, Micon Industries, and initially marketed by Kit Corson's company, Silent Communications. In order to be compatible with the existing TTY network, the MCM was designed around the five-bit Baudot code established by the older TTY machines instead of the ASCII code used by computers. The MCM was an instant success with the deaf community despite the drawback of a $599 cost. Within six months there were more MCMs in use by the deaf and hard of hearing than TTY machines. After a year Micon took over the marketing of the MCM and subsequently concluded a deal with Pacific Bell (who coined the term "TDD") to purchase MCMs and rent them to deaf telephone subscribers for $30 per month. After Micon formed an alliance with APCOM, Michael Cannon (Micon), Paul Conover (Micon), and Andrea Saks (APCOM) successfully petitioned the California Public Utilities Commission (CPUC), resulting in a tariff that paid for TTY devices to be distributed free of cost to deaf persons. Micon produced over 1,000 MCMs per month, resulting in approximately 50,000 MCMs being disseminated into the deaf community. Before he left Micon in 1980, Michael Cannon developed several computer compatible variations of the MCM and a portable, battery operated printing TTY, but they were never as popular as the original MCM. Newer model TTYs could communicate with selectable codes that allow communications at a higher bit rate on those models similarly equipped. However, the lack of true computer interface functionality spelled the demise of the original TTY and its clones. During the mid-1970s, other so-called portable telephone devices were being cloned by other companies, and this was the time period when the term "TDD" began being used largely by those outside the deaf community. === Text messaging and the Def-Tone System (DTS) === This relay system became known commonly as the Def-Tone System (DTS) because the tones representing letters of the alphabet were eventually carried in tones outside the range of human hearing. Today, this is commonly called multi-tap because you press a number 1, 2 or 3 times to get a corresponding letter. In 1994 Joseph Alan Poirier, a college student-worker, recommended using the system to send texts to forklifts to improve delivery of parts to the assembly line at GM Powertrain in Toledo, Ohio, and sending a text to pagers. He recommended taking pagers to alphanumeric displays incorporating the same system in discussions with the pager supplier for Outback Steakhouse and having relays put in the forklifts to ping alert messages to the pagers used in that system. He called it text messaging, coining the phrase. It is theorized that when Toyota forklift was allegedly hired by GM for this work, one of the subcontractors, Kyocera, utilized the work for the Toyota forklift company to create text messaging for cell phones. === Marsters Award === In 2009, AT&T received the James C. Marsters Promotion Award from TDI (formerly Telecommunications for the Deaf, Inc.) for its efforts to increase accessibility to communication for people with disabilities. The award holds some irony; it was AT&T that, in the 1960s, resisted efforts to implement TTY technology, claiming it would damage its communication equipment. In 1968, the Federal Communications Commission struck down AT&T's policy and forced it to offer TTY access to its network. == Protocols == There are many different standards for TDDs and textphones. === Original 5-bit Baudot code === The original standard used by TTYs is a variant of the Baudot code. The maximum speed of this protocol is 10 characters per second. This is a half-duplex protocol, which means that only one person at a time may transmit characters. If both try to transmit at the same time, the characters will be garbled on the other end. This protocol is commonly used in the United States. This is a variant of the Baudot code, implemented as 5-bits per character transmitted asynchronously using frequency-shift key-modulation at either 45.5 or 50 baud, 1 start bit, 5 data bits, and 1.5 stop bits. Details of the protocol implementation are available in TIA-825-A and also in T-REC V.18 Annex A "5-bit operational mode". === Turbo Code === The UltraTec company implements another protocol known as Enh

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  • Comparison of JavaScript-based web frameworks

    Comparison of JavaScript-based web frameworks

    This is a comparison of web frameworks for front-end web development that are reliant on JavaScript code for their behavior. == General information == == High-level framework comparison == JavaScript-based web application frameworks, such as React and Vue, provide extensive capabilities but come with associated trade-offs. These frameworks often extend or enhance features available through native web technologies, such as routing, component-based development, and state management. While native web standards, including Web Components, modern JavaScript APIs like Fetch and ES Modules, and browser capabilities like Shadow DOM, have advanced significantly, frameworks remain widely used for their ability to enhance developer productivity, offer structured patterns for large-scale applications, simplify handling edge cases, and provide tools for performance optimization. Frameworks can introduce abstraction layers that may contribute to performance overhead, larger bundle sizes, and increased complexity. Modern frameworks, such as React 18 and Vue 3, address these challenges with features like concurrent rendering, tree-shaking, and selective hydration. While these advancements improve rendering efficiency and resource management, their benefits depend on the specific application and implementation context. Lightweight frameworks, such as Svelte and Preact, take different architectural approaches, with Svelte eliminating the virtual DOM entirely in favor of compiling components to efficient JavaScript code, and Preact offering a minimal, compatible alternative to React. Framework choice depends on an application’s requirements, including the team’s expertise, performance goals, and development priorities. A newer category of web frameworks, including enhance.dev, Astro, and Fresh, leverages native web standards while minimizing abstractions and development tooling. These solutions emphasize progressive enhancement, server-side rendering, and optimizing performance. Astro renders static HTML by default while hydrating only interactive parts. Fresh focuses on server-side rendering with zero runtime overhead. Enhance.dev prioritizes progressive enhancement patterns using Web Components. While these tools reduce reliance on client-side JavaScript by shifting logic to build-time or server-side execution, they still use JavaScript where necessary for interactivity. This approach makes them particularly suitable for performance-critical and content-focused applications. == Features == == Browser support ==

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  • Comparison of machine learning software

    Comparison of machine learning software

    The following tables are a comparison of machine learning software such as software frameworks, libraries, and computer programs used for machine learning. == Machine learning software == == Other comparisons == == Machine learning helper libraries and platforms == Apache OpenNLP — natural language processing toolkit CUDA — GPU computing platform used to accelerate machine learning and deep learning workloads Horovod — distributed training framework for deep learning Hugging Face Transformers — library of pretrained transformer models built on other machine learning frameworks Kubeflow — machine learning platform for Kubernetes Mallet — toolkit for natural language processing and text analysis NumPy — numerical computing library used in machine learning OpenCV — computer vision library with machine learning functions ONNX — open format for representing machine learning models pandas — data analysis and data preparation library used in machine learning PlaidML — tensor compiler and backend for machine learning frameworks Polars — Dataframe library used for machine learning data preparation and analysis PyArrow — columnar data library used in machine learning data processing ROOT (TMVA) — data analysis framework with machine learning tools SciPy — scientific computing and optimization library used in machine learning == Online development environments for machine learning == Google Colab — hosted Jupyter Notebook environment commonly used for machine learning and deep learning JupyterLab — notebook-based development environment for machine learning and data science Jupyter Notebook — interactive notebook environment used for machine learning and data science Kaggle — online data science and machine learning platform

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  • Hardware compatibility list

    Hardware compatibility list

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

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  • Filter (social media)

    Filter (social media)

    Filters are digital image effects often used on social media. They initially simulated the effects of camera filters, and they have since developed with facial recognition technology and computer-generated augmented reality. Social media filters—especially beauty filters—are often used to alter the appearance of selfies taken on smartphones or other similar devices. While filters are commonly associated with beauty enhancement and feature alterations, there is a wide range of filters that have different functions. From adjusting photo tones to using face animations and interactive elements, users have access to a range of tools. These filters allow users to enhance photos and allow room for creative expression and fun interactions with digital content. == History == Beauty filters originate from Purikura ("print club"), a type of Japanese photographic arcade game machine conceived in 1994 by Sasaki Miho, a female employee at Atlus, and released in 1995 by Atlus and Sega primarily for female visitors at Japanese arcades. They allowed the manipulation of digital selfie photos with kawaii beauty filters similar to later Snapchat filters. Purikura filters included beautifying the image, cat whiskers, bunny ears, writing text, scribbling graffiti, selecting backdrops, borders, insertable decorations, icons, hair extensions, twinkling diamond tiaras, tenderized light effects, and predesigned decorative margins. To capitalize on the Purikura phenomenon in Japan during the late 1990s, Japanese mobile phones began including a front-facing camera, starting with the Kyocera Visual Phone VP‑210 in 1999. The Sanyo SCP-5300 released in 2002 was the first camera phone with filter effects, such as illumination, white‑balance control, sepia, black and white, and negative colors. Purikura-like beauty filters later appeared in smartphone apps such as Instagram and Snapchat in the 2010s. In 2010, Apple introduced the iPhone 4—the first iPhone model with a front-facing camera. It gave rise to a dramatic increase in selfies, which could be touched up with more flattering lighting effects with applications such as Instagram. The American photographer Cole Rise was involved in the creation of the original filters for Instagram around 2010, designing several of them himself, including Sierra, Mayfair, Sutro, Amaro, and Willow. However, the technology for virtual lens filters was invented and patented by Patrick Levy-Rosenthal in 2007. The patent received 100 citations, including Facebook, Nvidia, Microsoft, Samsung, and Snap. In September, 2011, the Instagram 2.0 update for the application introduced "live filters," which allowed the user to preview the effect of the filter while shooting with the application's camera. #NoFilter, a hashtag label to describe an image that had not been filtered, became popular around 2013. An update in 2014 allowed users to adjust the intensity of the filters as well as fine-tune other aspects of the image, features that had been available for years on applications such as VSCO and Litely. In 2014, Snapchat started releasing sponsored filters to monetize the participatory use of the application. In September 2015, Snapchat acquired Looksery and released a feature called "lenses," animated filters using facial recognition technology. Some of the early lenses available on Snapchat at the time were Heart Eyes, Terminator, Puke Rainbows, Old, Scary, Rage Face, Heart Avalanche. The Coachella filter released April 2016 was a popular early augmented reality filter. In April 2017, Facebook released the Camera Effects Platform, which is the first augmented reality platform that allows developers to create their own filters and effects on Facebook's Camera. In December 2017, Snapchat also launched their Lens Studio augmented reality developer tool that allows users and advertisers to do the same on the Snapchat application. In April 2022,TikTok joined the two, and launched their own augmented reality developer platform called Effect house. In February 2023, Effect House gave opened up the access to generative AI tools that allowed creators to change facial features in real time. In November 2023, TikTok released a feature where users no longer needed Effect House to create their own filters, as they are now able to create their own effects on the TikTok application. In August 2024, Meta announced that it would be removing third-party filter effects from its family of apps by January 14, 2025. The AR development software Meta Spark AR will also be retired at the same time; it was at one point the "world's largest mobile AR platform". Brand and creator effects represent the vast majority of filters available on Meta platforms, with over 2 million third-party filters available as of 2021. == Beauty filter == A beauty filter is a filter applied to still photographs, or to video in real time, to enhance the physical attractiveness of the subject. Typical effects of such filters include smoothing skin texture and modifying the proportions of facial features, for example enlarging the eyes or narrowing the nose. Filters may be included as a built-in feature of social media apps such as Instagram or Snapchat, or implemented through standalone applications such as Facetune. In 2020, the "Perfect Skin" filter for Snapchat and Instagram which was created by Brazilian augmented reality developer Brenno Faustino gained more than 36 million impressions in the first 24 hours of its release. In 2021, TikTok users pointed out how the default front-facing camera on the platform automatically applied the retouch and other feature-altering filters. Users noted that these filters slimmed down faces, smoothed skin, whitened teeth, and altered facial features such as nose and eye size, without the option to disable this feature through settings. In March 2023, the "Bold Glamour" filter was released on TikTok and instantly went viral with over 18 million videos created within its first week. This filter subtly enhances the user's facial features seamlessly, giving the illusion of fuller eyebrows, taller cheekbones, enhanced eye make up, a smaller nose, plumper lips, and clearer skin, giving off a natural yet distinct effect. As of May 2024, the filter has been used in over 220 million videos and has become a pivotal moment for beauty filters on digital platforms. Critics have raised concerns that the widespread use of such filters on social media may lead to negative body image, particularly among girls. Though Meta's intention of removing third-party filters will likely see all beauty filters removed, academics feel that the damage of beautifying filters is already done. === Background === The manipulation of photos to enhance attractiveness has long been possible using software such as Adobe Photoshop and, before that, analogue techniques such as airbrushing. However, such tools required considerable technical and artistic skill, and so their use was mostly limited to professional contexts, such as magazines or advertisements. By contrast, filters work in an automated fashion through the use of complex algorithms, requiring little or no input from the user. This ease of use, in combination with the increase in processing power of smartphones, and the rise of social media and selfie culture, have led to photographic manipulation occurring on a much wider scale than ever before. One of the earliest examples of a content-aware digital photographic filter is red-eye reduction. === Effects === Typical changes applied by beauty filters include: Smoothing skin texture; minimizing fine lines and blemishes Erasing under-eye bags Erasing naso-labial lines ("laugh lines") Application of virtual makeup, such as lipstick or eyeshadow Slimming the face; erasing double chins Enlarging the eyes Whitening teeth Narrowing the nose Increasing fullness of the lips Beauty filters most frequently target the face, though in some cases they may affect other body parts. For example, the app "Retouch Me" was reported to have a feature which allows users to superimpose visible abdominal muscles (a "six pack") onto photos featuring the subject's bare stomach. === Reception and psychological effects === Some commentators have expressed concern that beauty filters may create unrealistic beauty standards, particularly among girls, and contribute to rates of body dysmorphic disorder. A correlation has been established between negative body image and the use of beautifying filters, though the direction of causation is unknown. The inability to discern whether a particular image has been filtered is thought to exacerbate their negative psychological effects. Policymakers have advocated for social networks to disclose the use of filters; TikTok, Instagram, and Snapchat all label filtered photos and videos with the name of the filter applied. It has also been noted that beauty filters on social media tend to highlight Eurocentric features, like lighter eyes, a smaller nose, and flushed ch

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