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  • The Triple Revolution

    The Triple Revolution

    "The Triple Revolution" was an open memorandum sent to U.S. President Lyndon B. Johnson and other government figures on March 22, 1964. It concerned three megatrends of the time: increasing use of automation, the nuclear arms race, and advancements in human rights. Drafted under the auspices of the Center for the Study of Democratic Institutions, it was signed by an array of noted social activists, professors, and technologists who identified themselves as the Ad Hoc Committee on the Triple Revolution. The chief initiator of the proposal was W. H. "Ping" Ferry, at that time a vice-president of CSDI, basing it in large part on the ideas of the futurist Robert Theobald. == Overview == The statement identified three revolutions underway in the world: the cybernation revolution of increasing automation; the weaponry revolution of mutually assured destruction; and the human rights revolution. It discussed primarily the cybernation revolution. The committee claimed that machines would usher in "a system of almost unlimited productive capacity" while continually reducing the number of manual laborers needed, and increasing the skill needed to work, thereby producing increasing levels of unemployment. It proposed that the government should ease this transformation through large-scale public works, low-cost housing, public transit, electrical power development, income redistribution, union representation for the unemployed, and government restraint on technology deployment. == Legacy == Martin Luther King Jr.'s final Sunday sermon, delivered six days before his April 1968 assassination, explicitly references the thesis of "The Triple Revolution": There can be no gainsaying of the fact that a great revolution is taking place in the world today. In a sense it is a triple revolution: that is, a technological revolution, with the impact of automation and cybernation; then there is a revolution in weaponry, with the emergence of atomic and nuclear weapons of warfare; then there is a human rights revolution, with the freedom explosion that is taking place all over the world. Yes, we do live in a period where changes are taking place. And there is still the voice crying through the vista of time saying, "Behold, I make all things new; former things are passed away." In Harlan Ellison's 1967 anthology Dangerous Visions, Philip José Farmer's story "Riders of the Purple Wage" uses the Triple Revolution document as the premise of a future society, in which the "purple wage" of the title is a guaranteed income dole on which most of the population lives. At the 1968 World Science Fiction Convention in San Francisco, Farmer delivered a lengthy Guest of Honor speech in which he called for the founding of a grassroots activist organization called REAP which would work for implementation of the Ad Hoc Committee's recommendations. Looking back on the proposal in his 2008 book, Daniel Bell wrote: "the cybernetic revolution quickly proved to be illusory. There were no spectacular jumps in productivity. ... Cybernation had proved to be one more instance of the penchant for overdramatizing a momentary innovation and blowing it up far out of proportion to its actuality. ... The image of a completely automated production economy—with an endless capacity to turn out goods—was simply a social-science fiction of the early 1960s. Paradoxically, the vision of Utopia was suddenly replaced by the spectre of Doomsday. In place of the early-sixties theme of endless plenty, the picture by the end of the decade was one of a fragile planet of limited resources whose finite stocks were being rapidly depleted, and whose wastes from soaring industrial production were polluting the air and waters." In his 2015 book Rise of the Robots, Martin Ford claims The Triple Revolution's predictions of steady decline in future employment were not wrong, but rather premature. He cites "Seven Deadly Trends" that began in the 1970s-1980s and by the mid-2010s appeared set to continue: Stagnation in real wages Decline in labor's share of national income in many countries (breakdown of Bowley's law), while corporate profits increased Declining labor force participation Diminishing job creation, lengthening jobless recoveries, and soaring long-term unemployment Rising inequality Declining incomes, and underemployment for recent college graduates Polarization and part-time jobs (middle-class jobs are disappearing, to be replaced by a small number of high-paying jobs and large number of low-paying jobs) According to Ford, the 1960s were part of what in retrospect seems like a golden age for labor in the United States, when productivity and wages rose together in near lockstep, and unemployment was low. But after about 1980, wages began stagnating while productivity continued to rise. Labor's share of the economic output began to decline. Ford describes the role that automation and information technology play in these trends, and how new technologies including narrow AI threaten to destroy jobs faster than displaced workers can be retrained for new jobs, before automation takes the new jobs as well. This includes many job categories, such as in transportation, that were never threatened by automation before. According to a 2013 study, about 47% of US jobs are susceptible to automation. == Signatories ==

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  • Nanonetwork

    Nanonetwork

    A nanonetwork or nanoscale network is a set of interconnected nanomachines (devices a few hundred nanometers or a few micrometers at most in size) which are able to perform only very simple tasks such as computing, data storing, sensing and actuation. Nanonetworks are expected to expand the capabilities of single nanomachines both in terms of complexity and range of operation by allowing them to coordinate, share and fuse information. Nanonetworks enable new applications of nanotechnology in the biomedical field, environmental research, military technology and industrial and consumer goods applications. Nanoscale communication is defined in IEEE P1906.1. == Communication approaches == Classical communication paradigms need to be revised for the nanoscale. The two main alternatives for communication in the nanoscale are based either on electromagnetic communication or on molecular communication. === Electromagnetic === This is defined as the transmission and reception of electromagnetic radiation from components based on novel nanomaterials. Recent advancements in carbon and molecular electronics have opened the door to a new generation of electronic nanoscale components such as nanobatteries, nanoscale energy harvesting systems, nano-memories, logical circuitry in the nanoscale and even nano-antennas. From a communication perspective, the unique properties observed in nanomaterials will decide on the specific bandwidths for emission of electromagnetic radiation, the time lag of the emission, or the magnitude of the emitted power for a given input energy, amongst others. For the time being, two main alternatives for electromagnetic communication in the nanoscale have been envisioned. First, it has been experimentally demonstrated that is possible to receive and demodulate an electromagnetic wave by means of a nanoradio, i.e., an electromechanically resonating carbon nanotube which is able to decode an amplitude or frequency modulated wave. Second, graphene-based nano-antennas have been analyzed as potential electromagnetic radiators in the terahertz band. === Molecular === Molecular communication is defined as the transmission and reception of information by means of molecules. The different molecular communication techniques can be classified according to the type of molecule propagation in walkaway-based, flow-based or diffusion-based communication. In walkway-based molecular communication, the molecules propagate through pre-defined pathways by using carrier substances, such as molecular motors. This type of molecular communication can also be achieved by using E. coli bacteria as chemotaxis. In flow-based molecular communication, the molecules propagate through diffusion in a fluidic medium whose flow and turbulence are guided and predictable. The hormonal communication through blood streams inside the human body is an example of this type of propagation. The flow-based propagation can also be realized by using carrier entities whose motion can be constrained on the average along specific paths, despite showing a random component. A good example of this case is given by pheromonal long range molecular communications. In diffusion-based molecular communication, the molecules propagate through spontaneous diffusion in a fluidic medium. In this case, the molecules can be subject solely to the laws of diffusion or can also be affected by non-predictable turbulence present in the fluidic medium. Pheromonal communication, when pheromones are released into a fluidic medium, such as air or water, is an example of diffusion-based architecture. Other examples of this kind of transport include calcium signaling among cells, as well as quorum sensing among bacteria. Based on the macroscopic theory of ideal (free) diffusion the impulse response of a unicast molecular communication channel was reported in a paper that identified that the impulse response of the ideal diffusion based molecular communication channel experiences temporal spreading. Such temporal spreading has a deep impact in the performance of the system, for example in creating the intersymbol interference (ISI) at the receiving nanomachine. In order to detect the concentration-encoded molecular signal two detection methods named sampling-based detection (SD) and energy-based detection (ED) have been proposed. While the SD approach is based on the concentration amplitude of only one sample taken at a suitable time instant during the symbol duration, the ED approach is based on the total accumulated number of molecules received during the entire symbol duration. In order to reduce the impact of ISI a controlled pulse-width based molecular communication scheme has been analysed. The work presented in showed that it is possible to realize multilevel amplitude modulation based on ideal diffusion. A comprehensive study of pulse-based binary and sinus-based, concentration-encoded molecular communication system have also been investigated.

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  • List of UPnP AV media servers and clients

    List of UPnP AV media servers and clients

    This is a list of UPnP AV media servers and client application or hard appliances. == UPnP AV media servers == === Software === === Cross-platform === Allonis myServer, a multi-faceted media player/organizer with a DLNA/UPnP server, controller, and renderer, including conversion. Runs on Microsoft Windows. Supports most all HTML5 devices as remote controls. Asset UPnP (DLNA compatible) from Illustrate. An audio specific UPnP/DLNA server for Windows, QNAP, macOS and Linux. Features audio WAVE/LPCM transcoding from a range of audio codecs, ReplayGain and playlists. FreeMi UPnP Media Server, very simple server, historically used to stream to the STB Freebox, based on .net/mono. Home Media Server, a free media server/player/controller for Windows, Linux, macOS, individual device settings, transcoding, external and internal subtitles, restricted device access to folders, uploading files, Internet-Radio, Internet-Television, Digital Video Broadcasting (DVB), DMR-control and "Play To", Music (Visualization), Photo (Slideshow), support for 3D-subtitles, support for BitTorrent files, Web-navigation with HTML5 player, Digital Media Renderer (DMR) emulation for AirPlay and Google Cast devices. Jellyfin, a free and open-source suite of multimedia applications designed to organize, manage, and share digital media files to networked devices. JRiver Media Center, a multi-faceted media player/organizer with a DLNA/UPnP server, controller, and renderer, including conversion. Supports Microsoft Windows, macOS and Linux. Kodi (previously XBMC), a cross platform open source software media-player/media center for Android, Apple TV, Linux, macOS and Windows. LimboMedia, a free cross platform home- and UPnP/DLNA mediaserver with android app and WebM transcoding for browser playback (build with java and FFmpeg). MinimServer, a Java-based highly configurable uPnP/DNLA music server with additional consideration given to Classical Music, supports transcoding with MinimStreamer, supports Microsoft Windows, macOS, Linux, and various NAS devices. Neutron Music Player, acts as a cross platform UPnP/DLNA Media Renderer server available for Android, iOS, BlackBerry 10 & PlayBook platforms. Supports gapless playback and has possibility to output rendered audio further to the high-resolution internal DAC or external USB DAC or another UPnP/DLNA Media Renderer with all supported DSP effects applied. Plex, a cross-platform and closed source software media player and entertainment hub for digital media, available for macOS, Microsoft Windows, Linux, as well as mobile clients for iOS (including Apple TV (2nd generation) onwards), Android, Windows Phone, and many devices such as Xbox. Supports on-the-fly transcoding of video and music. PonoMusic World. Based on the JRiver Media Center software, includes similar features along with a store for purchasing HD audio tracks. PS3 Media Server, a free cross platform Java based UPnP DLNA server especially good for AVC and other current HD media codecs with on-the-fly transcoding. Serviio, is available with a free and a pro license. It can stream media files (music, video or images) to renderer devices (e.g. a TV set, Blu-ray player, games console or mobile phone) on a local area network. TVMOBiLi, a cross platform, high performance UPnP/DLNA Media Server for Windows, macOS and Linux. TwonkyMedia server, a cross-platform multimedia server and entertainment hub for digital media, available for Android, Apple TV, iOS, Linux, macOS, Microsoft Windows, Windows Phone, and Xbox 360. Universal Media Server, a free (open source) DLNA-compliant UPnP Media Server for Windows, macOS and Linux (originally based on the PS3 Media Server). It is able to stream videos, audio and images to any DLNA-capable device. It contains more features than most paid UPnP/DLNA Media Servers. It streams to many devices including TVs (Samsung, Sony, Panasonic, LG, Philips and more.), PS3, Xbox(One/360), smartphones, Blu-ray players and more. vGet Cast, a simple, cross platform (Chrome App) DLNA server and controller for single, local video files. Vuze, an open-source Java-based BitTorrent client which contains MediaServer plugin. Wild Media Server, a media server/player/controller for Windows, Linux, macOS, individual device settings, transcoding, external and internal subtitles, restricted device access to folders, uploading files, Internet-Radio, Internet-Television, Digital Video Broadcasting (DVB), DMR-control and "Play To", Music (Visualization), Photo (Slideshow), support for 3D-subtitles, support for BitTorrent files, Web-navigation with HTML5 player, Digital Media Renderer (DMR) emulation for AirPlay and Google Cast devices. === Android === BubbleUPnP Android UPnP/DLNA server, player, controller and renderer CastLab Android UPnP/DLNA server. Pixel Media Server, Android UPnP/DLNA Media Server. Supports all popular Video and Audio files. It also support external subtitle file (SRT) Plato is an Android UPnP client app that can play videos and audio. Toaster Cast Android UPnP/DLNA server, controller and renderer vGet, Android App that can play videos embedded in websites on DLNA renderers. Media Cast UPnP, Android UPnP client app that can play videos/Audio. Media Server Pro is a DLNA server that allows individual file selections for sharing. Slick UPnP A minimal and intuitive open-source Android UPnP client app that can play video/audio. (It is not DMS) YAACC Open source UPnP controller, renderer and server app === Linux === === Microsoft Windows === Sundtek Streamingserver a native Windows TV Server providing DVB, ATSC and ISDB-T via UPnP/DLNA, it also supports streaming media files (it only supports TV devices from Sundtek). Stream What You Hear, a Windows application that streams the sound of your computer (i.e.: “what you hear”) to UPnP/DLNA device such as TVs, amps, network receivers, game consoles, etc... TVersity Media Server, a Windows application that streams multimedia content from a personal computer to UPnP, DLNA and mobile devices (Chromecast is also supported). It was the first media server to offer real-time transcoding (back in 2005). TVersity Screen Server, a Windows application that mirrors the screen of a personal computer to UPnP, DLNA and mobile devices. DVBViewer, a Windows application, mainly for TV/Radio recording/playback, but with the ability to stream live TV/radio as well as multimedia files via UPnP/DLNA. DivX, a Windows application, mainly for video encoding into DivX format, but has the ability to stream multimedia files via DLNA. foobar2000, a freeware audio player for Windows. Highly customizable, audio only. Download of dlna-extension from the developers' webpage necessary. Home Media Center, a free and open source media server compatible with DLNA. Includes web interface for streaming content to web browser (Android, iOS, ...), subtitles integration and Windows desktop streaming. This server is easy to use. KooRaRoo Media, a commercial DLNA media server and organizer for Windows. Includes on-the-fly transcoding, per-file and per-folder parental controls, powerful organizing features with dynamic playlists, Internet radio streaming, "Play To" functionality and remote device control, burned-in and external subtitles, extensive format support including RAW photo formats. Streams all files to all devices. Media Go, media player and tagger MediaMonkey, a free media player/tagger/editor with an UPnP/DLNA client and server for Microsoft Windows MusicBee, an audio player, supports UPnP via a plugin. Mezzmo, a commercial software package. Mezzmo streams music, movies, photos and subtitles to the UPnP and DLNA-enabled devices. It automatically finds and organizes music, movies and photos, imports multimedia files from iPad, iPhone, iPod, Audio CDs, iTunes, Windows Media Player and WinAmp. DLNA server supports all popular media file formats with real time transcoding to meet the device specifications. PlayOn, a commercial UPnP/DLNA media server for Windows, includes a transcoder for streaming web video. TVble, a cloud connected (Rotten tomatoes/TMDB etc.), Torrent streaming, DLNA enabled media server. Allows single file or playlist downloads. Windows Media Connect from Microsoft, a free UPnP AV MediaServer and control point (server and client) for Microsoft Windows WMC version 2.0 can be installed for usage with Windows Media Player 10 for Windows XP WMC version 3.0 can be installed for usage with Windows Media Player 11 for Windows XP WMC version 4.0 comes pre-installed on Windows Vista with its Windows Media Player 11 WMC can also refer to Windows Media Center. From the Windows Media Center entry in Wikipedia: In May 2015, Microsoft announced that Windows Media Center would be discontinued on Windows 10, and that it would be uninstalled when upgrading; but stated that those upgrading from a version of Windows that included the Media Center application would receive the paid Windows DVD Player app to maintain DVD playback functio

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  • InteLex Past Masters

    InteLex Past Masters

    InteLex Past Masters is a collection of full-text web-based scholarly editions of classic works in the humanities. InteLex Corporation was founded in 1989 by its current chief executive officer, Mark Rooks, to produce electronic versions of the works of the great philosophers, based on existing scholarly editions. The company is located in Charlottesville, Virginia. Its databases are marketed to academic institutions, with pricing based on the individual collections purchased. Content is provided in XML and searchable image format and is accessed through the InteLex Corporation website. In addition to philosophy, subject coverage includes religious studies, English literature, women's writing, social science, and history of science. InteLex databases are found in institutions in over 65 countries around the world.

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  • Rabbit r1

    Rabbit r1

    The Rabbit r1 is an artificial intelligence personal assistant device developed by the American technology startup Rabbit Inc and co-designed by Teenage Engineering. It was announced at the 2024 Consumer Electronics Show as a handheld device intended to perform digital tasks through voice commands, touch interaction, and web-based AI agents. The r1 was marketed around Rabbit's concept of a "large action model" (LAM), which the company described as software able to operate websites and services on behalf of users. The device runs rabbitOS, an operating system based on the Android Open Source Project. Its services have included AI search, image recognition, voice interaction, music playback, rideshare and food-ordering integrations, and later experimental web-agent features such as LAM Playground and teach mode. Initial reviews were largely negative, with reviewers criticizing the device's limited functionality, bugs, and unclear advantages over a smartphone. Critics also questioned Rabbit's claims after the r1 software was shown to run on an Android phone. Rabbit continued to issue software updates after launch, including rabbitOS 2 in September 2025, which introduced a redesigned card-based interface, gesture navigation, and a "creations" feature for generating small software tools and experiences on the device. Rabbit Inc was founded by Jesse Lyu Cheng. == Hardware == Display: A 2.88-inch touchscreen for interactive user input. Input: push-to-talk button to activate voice commands; scroll wheel; Gyroscope; Magnetometer; Accelerometer; GPS. Camera: 8 MP single camera, with a resolution of 3264x2448, allowing for the connected external AI to use computer vision. Audio: Equipped with a speaker and dual microphones for audio interaction. Connectivity: Supports Wi-Fi and cellular connections via a SIM card slot to access internet services. Processor: Runs on a 2.3GHz MediaTek Helio P35 processor. Memory: Contains 4GB of RAM for operational tasks. Storage: Offers 128GB of internal storage for data. Ports: Utilizes a USB-C port for charging and data connections. == Software == The Rabbit r1 runs rabbitOS, which is based on the Android Open Source Project (AOSP), specifically Android 13. Rabbit founder Jesse Lyu described rabbitOS as a "very bespoke AOSP" after reports that the r1's software could be run on a conventional Android phone. Rabbit described the r1 as using a large action model (LAM), a type of AI agent intended to perform tasks across software interfaces rather than only answer questions. At launch, the device supported a limited set of services, including AI search, vision features, music playback, and some third-party integrations. Perplexity.ai was one of the AI services used to answer user queries. In 2024, Rabbit released several software updates that added features and attempted to address early criticism of the device. In July 2024, the company launched "beta rabbit", an advanced search and conversation mode for more complex queries. In October 2024, it released LAM Playground, a web-based agent feature intended to let the r1 operate websites on behalf of users. Reviewers found the feature experimental; Android Authority reported that it could perform some navigation tasks but struggled with CAPTCHAs, loops, and unintended behavior. In November 2024, Rabbit introduced a beta "teach mode", which allowed users to demonstrate web-based tasks in the Rabbithole web portal and later ask the r1 to repeat them. The company described teach mode as experimental, and The Verge noted that Rabbit warned users that results could be unpredictable and that CAPTCHA-protected sites could cause problems. Rabbit released rabbitOS 2 in September 2025. The update redesigned the interface around a card-based layout, added additional touchscreen gestures, and introduced "creations", a feature that lets users generate simple software tools, games, and interfaces through natural-language prompts. Coverage of the update described it as a major software overhaul rather than new hardware. == Reception == === Funding === Rabbit raised $20 million in funding from Khosla Ventures, Synergis Capital and Kakao Investment in October 2023. The company announced an additional $10 million in funding in December 2023. === Sales === Following its announcement at the 2024 Consumer Electronics Show, 130,000 units were sold. On August 13, 2024, Rabbit announced that sales of r1 had expanded to the entire European Union (except Malta) and United Kingdom. On August 21, 2024, sales of r1 expanded to Singapore. === Reviews === The r1 was met with strong criticism immediately after Rabbit began shipping the device. Some reviews questioned what the device was able to do that a smartphone could not, while comparing it to the similar Humane Ai Pin. YouTuber Marques Brownlee called the device "barely reviewable". Android Authority's Mishaal Rahman managed to install Rabbit r1's software on a Pixel 6a smartphone, after a tipster shared an APK file. The Verge echoed the claims made by Rahman. In response, Lyu published statements confirming its use of Android, but denying that the r1 is an Android app. Mashable called its Vision features impressive, but said that "these praise-worthy features are overshadowed by buggy performance". Ars Technica wrote a blog post claiming "the company is blocking access from bootleg APKs". TechCrunch gave a slightly more positive review, calling the device a "fun peep at a possible future", but could not "advise anyone to buy one now." Shortly after the launch of r1, Rabbit began a weekly cadence of software updates to address much of the criticism from the early reviews, including "battery and GPS performance, time zone selection, and more". Digital Trends said the Magic Camera feature "takes the most mundane, ordinary, and badly composed photos and makes something fun and eye-catching from them." Mashable said the "beta rabbit" feature "makes Rabbit R1 more conversational and intelligent". Later coverage noted that Rabbit continued to update the r1 after its poorly received launch. The Verge reported in September 2024 that about 5,000 of roughly 100,000 purchasers were using the device at any given moment, citing Lyu, and described the product as having launched before it was ready. In 2025, coverage of rabbitOS 2 described the update as an attempt to reset the device's software experience after the criticism of its original release. == Controversies == === GAMA project === Rabbit Inc has garnered attention due to allegations surrounding its funding and the company's past projects. The company came under scrutiny when Stephen Findeisen, known as Coffeezilla on YouTube, published a video in May 2024, alleging that Rabbit Incorporation was "built on a scam". Rabbit Incorporation, initially named Cyber Manufacturing Co, rebranded just two months before launching the Rabbit R1. The company, under its former name, raised $6 million in November 2021 for a project called GAMA, described as a "Next Generation NFT Project." Jesse Lyu, the CEO of Rabbit Incorporation, referred to GAMA as a "fun little project." Coffeezilla, who investigates influencer scams, highlighted old Clubhouse recordings of Jesse Lyu discussing the GAMA project. In these recordings, Lyu emphasized the substantial funding behind GAMA and its potential to be a revolutionary, carbon-negative cryptocurrency. Coffeezilla questioned the whereabouts of the funds raised for GAMA, estimating that approximately $1 million in refunds to investors remained unresolved. He suggested that the rebranding to Rabbit Incorporation and the shift to developing the Rabbit R1 were attempts to divert from the GAMA project's issues. In response to Coffeezilla's inquiries, Rabbit Incorporation stated that the $6 million raised was used for the GAMA project. The company said that NFTs cannot be refunded unless the owner agrees to "burn" them on the blockchain. Rabbit Incorporation also said that the GAMA project was open-sourced and returned to the community, aligning with community feedback. They also mentioned that efforts to buy back NFTs were made to counteract malicious trading and maintain market stability. === Security === In June 2024, Engadget reported that the Rabbitude team, a community reverse engineering project, had gained access to the r1's codebase revealing that r1's software contained several hardcoded API keys in its code for ElevenLabs, Microsoft Azure, Yelp, and Google Maps, potentially allowing unauthorized access to r1 responses, including those containing the users' personal information. For a short time, Rabbit immediately began revoking and rotating those secrets and confirmed that the code was leaked by an employee who had "been terminated and remains under investigation". In July 2024, the company revealed that all user chats and device pairing data were logged on the r1 with no ability to delete them. This meant that lost or stolen devices could be used to extract user

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  • Packingham v. North Carolina

    Packingham v. North Carolina

    Packingham v. North Carolina, 582 U.S. 98 (2017), is a case in which the Supreme Court of the United States held that a North Carolina statute that prohibited registered sex offenders from using social media websites was unconstitutional because it violated the First Amendment to the U.S. Constitution, which protects freedom of speech. In 2010, Lester Gerard Packingham, a registered sex offender, posted on Facebook under a pseudonym to comment favorably on a recent traffic court experience. Police then identified Packingham and charged him with violating North Carolina's law. Packingham moved to dismiss the charges, arguing that the state's law violated the First Amendment. The trial court dismissed this motion and ultimately convicted Packingham. A state appellate court initially reversed the trial court, holding that the law did violate the First Amendment, but the North Carolina Supreme Court, the state's highest court, disagreed and reinstated the conviction. In June 2017, the U.S. Supreme Court unanimously reversed the North Carolina Supreme Court's judgment. In the majority opinion authored by Justice Anthony Kennedy, the Court held that social media—defined broadly to include Facebook, Amazon.com, The Washington Post, and WebMD, among many others—is a "protected space" under the First Amendment for lawful speech. The Court offered that North Carolina could protect children through less restrictive means, such as prohibiting "conduct that often presages a sexual crime, like contacting a minor or using a website to gather information about a minor". == Background == === North Carolina statute === In 2008, the state of North Carolina passed a law that made it a felony for a registered sex offender "to access a commercial social networking Web site where the sex offender knows that the site permits minor children to become members or to create or maintain personal Web pages". The law defined a "commercial social networking Web site" using four criteria. Specifically, the website must: be "operated by a person who derives revenue from membership fees, advertising, or other sources related to the operation of the Web site". facilitate "the social introduction between two or more persons for the purposes of friendship, meeting other persons, or information exchanges". allow "users to create Web pages or personal profiles that contain information such as the name or nickname of the user, photographs placed on the personal Web page by the user, other personal information about the user, and links to other personal Web pages on the commercial social networking Web site of friends or associates of the user that may be accessed by other users or visitors to the Web site". provide "users or visitors... mechanisms to communicate with other users, such as a message board, chat room, electronic mail, or instant messenger". The law exempted websites that "Provid[e] only one of the following discrete services: photo-sharing, electronic mail, instant messenger, or chat room or message board platform", as well as websites that have as their primary purpose "the facilitation of commercial transactions involving goods or services between [their] members or visitors". === Facts of the case === In 2002, Lester Gerard Packingham was convicted of taking "indecent liberties with a child", a felony that required him to register as a sex offender. A North Carolina court sentenced him to 10–12 months in prison with 24 months of supervised release. He was given no other special instructions on his behavior outside of prison other than to "remain away from" the minor. In 2010, after a state court dismissed a traffic ticket against Packingham, he submitted a post on Facebook under the name "J. R. Gerrard", stating: "Man God is Good! How about I got so much favor they dismissed the ticket before court even started? No fine, no court cost, no nothing spent. . . . . .Praise be to GOD, WOW! Thanks JESUS!" The Durham Police Department identified Packingham as the author of the post after cross-checking the time of the post with recently dismissed traffic tickets, and a grand jury indicted him for violating the North Carolina statute. === Lower court proceedings === Initially, Packingham moved to dismiss his indictment, arguing that it violated the First Amendment. A North Carolina Superior Court judge denied this motion, and he was convicted of violating the North Carolina social media law. Packingham appealed his conviction to the North Carolina Court of Appeals, which reversed the trial court's decision in 2013. Applying intermediate scrutiny, the court of appeals determined that North Carolina's law violated the First Amendment because it was too broad, applying to all registered sex offenders regardless of whether the offender had committed a crime involving a minor or whether the offender was a continuing threat to minors. The appeals court also stated that the law had been defined broadly enough to prohibit a registered sex offender from conducting a wide array of Internet activity, such as "conducting a 'Google' search, purchasing items on Amazon.com, or accessing a plethora of Web sites unrelated to online communication with minors". In 2015, the North Carolina Supreme Court, the state's highest court, reversed the court of appeals, holding that the law was "constitutional in all respects". The North Carolina Supreme Court found that the statute was a "limitation on conduct" and did not impede any free speech. The state had a vested interest in “forestalling the illicit lurking and contact of minors” by registered sex offenders and potential future victims, and upheld Packingham's conviction. == Supreme Court ruling == Packingham filed a petition for a writ of certiorari with the Supreme Court of the United States. The federal government also filed a brief recommending that the Supreme Court grant certiorari, arguing that the North Carolina Supreme Court incorrectly decided the case in favor of the state. The U.S. Supreme Court granted certiorari in October 2016. Amicus briefs in support of Packingham were filed by the libertarian Cato Institute and the American Civil Liberties Union. The North Carolina Supreme Court filed a brief supporting its prior decision, urging the importance of protecting minors from being stalked online. === Oral argument === The oral argument took place in February 2017. Packingham’s lawyer, David T. Goldberg, argued that the law banned “vast swaths of First Amendment activity”, went too far in restricting which Internet sites could be accessed, and forbade use of the Internet in general. The law targeted speech on some of the platforms that Americans use most often, Goldberg noted, and that under the law Packingham could not even use Twitter to read the myriad messages discussing his own case. He further noted that the law imposes punishment without regard to whether the offender actually did anything wrong. North Carolina’s senior deputy Attorney General, Robert C. Montgomery, argued for the state, and claimed that communication through social media sites is a “crucial channel”. Justice Sonia Sotomayor asked Montgomery to provide evidence as to the claim that by giving Packingham Internet privileges, he would commit another crime. Justice Stephen Breyer added that “It seems to be well-settled law that the state can’t (bar usage) unless there is a 'clear and present danger'." === Opinion of the Court === In June 2017 the Supreme Court delivered a judgment in favor of Packingham, unanimously voting to reverse the state court's ruling. Justice Anthony Kennedy authored the decision, joined by Justice Ginsburg, Justice Breyer, Justice Sotomayor, and Justice Kagan. Kennedy explained the decision: "A fundamental principle of the First Amendment is that all persons have access to places where they can speak and listen, and then, after reflection, speak and listen once more." He continued that "By prohibiting sex offenders from using those websites, North Carolina with one broad stroke bars access to what for many are the principal sources for knowing current events, checking ads for employment, speaking and listening in the modern public square, and otherwise exploring the vast realms of human thought and knowledge." Citing Ashcroft v. Free Speech Coalition as a precedent, Kennedy also wrote: "It is well established that, as a general rule, the Government 'may not suppress lawful speech as the means to suppress unlawful speech'." === Concurring opinion === Justice Samuel Alito wrote an opinion concurring in the judgment, joined by John Roberts and Clarence Thomas. While Alito agreed that the state statute at issue violated the First Amendment, he noted that there are reasonable scenarios for which legal bans for sex offenders can be placed, such as for sites targeted at teenagers. Justice Gorsuch took no part in the decision of the case. == Impact == Packingham v. North Carolina was one of the first U.S. Supreme Court cases to ana

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  • FactorDaily

    FactorDaily

    FactorDaily is an Indian digital media publication founded in 2016 by Pankaj Mishra and Jayadevan PK. Mishra was formerly an Editor at TechCrunch and the Economic Times. The digital publication was launched with an intent to produce stories on the impact of technology on life in India. == History == FactorDaily began publishing in May 2016, with daily reported stories on technology, culture and life in India. Prior to its launch, the company had raised $1 million in seed funding from Accel India, Blume Ventures, Girish Mathrubootham of Freshdesk, Vijay Shekhar Sharma of PayTm, and Jay Vijayan of Tekion. Josey Puliyenthuruthel John, formerly Managing Editor at Business Today and National Corporate Editor at Mint, later joined the company as a Consulting Editor. In January 2017, FactorDaily launched its first Podcast called The Outliers. The inaugural episode featured a conversation with Manish Sharma of Printo on his journey starting up. == Awards == The FactorDaily team won the Bengaluru Editors Lab 2017, a journalism hackathon organised by the Global Editors Network (GEN). The story titled "India has 3,800 psychiatrists for 1.2bn people. Can tech step in to manage mental health?" won the first prize in the online category of the fifth Schizophrenia Research Foundation’s (SCARF) ‘Media for Mental Health’ awards. The story titled 'The dark hand of tech that stokes sex trafficking in India', won the Stop Slavery media Awards by the Thomson Reuters Foundation for the year 2020.

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  • Digital first

    Digital first

    Digital first is a communication theory that publishers should release content into new media channels in preference to old media. The premise behind the theory is that after the advent of Internet, most established media organizations continued to give priority to traditional media. Over time, those organizations faced a choice to either publish first in digital media or traditional media. A "digital first" decision occurs when a publisher chooses to distribute information online in preference to or at the expense of traditional media like print publishing. Many employers and employees find it challenging to imagine using digital first practices. Distributing content digital first introduces new practices, including a need to manage the data which tracks readership. Many paper print publishers feel intimidated by the idea of publishing content online before publishing it in paper media. Comedian John Oliver in the show Last Week Tonight criticized digital first practices as a cause of lower standards in journalism. == Digital-First Transformation in Business and Education == The classical perspective of an information system is that it represents and reflects physical reality. However, it is increasingly evident that digital technologies not only represent reality but also actively shape it, as, in many instances, the digital version is created first, and the physical version follows. Gradually, digital infrastructures are integrated in people's work and life, shaping a digital environment through technologies such as 5G, sensors, and blockchain. The Digital First Framework, developed by Professor Youngjin Yoo, is a conceptual approach that helps the physical companies in the integration of digital technologies into the core of product and service design. The shift from traditional cars, where the physical vehicle precedes its digital representation on Google maps, to autonomous vehicles, where the digital representation (the blue dot) is created first, emphasizes the digital-first mindset in the design and operation of systems. In today's business environment, it's critical for organizations to embrace a digital-first strategy. Companies built on digital platforms will significantly diverge from traditional, hierarchical business structures that typically focus on a single product or market. These digitally-centered enterprises will offer products and services that are tailored to individual requirements, utilizing algorithms to assess needs based on specific situations, and relying on external partners to provide these solutions. This highlights the need to transform traditional R&D practices. It's essential for R&D teams to move beyond their laboratories and immerse themselves in the environments of their users. Understanding the context of use is fundamental to creating a relevant platform. As an illustration, the concept of Digital-first, as defined by Rohm et al. (2019), involves the integration of digital projects within educational courses, exemplified by institutions like M-School. The program adopts a programmatic approach, where successive courses progressively build upon one another, adopting an all-encompassing perspective that regards all aspects of marketing as inherently digital. Students actively participate in real-world projects, including campaigns for community improvement, and are tasked with generating content for diverse platforms. Through hands-on collaboration with live clients and the utilization of tools such as Google AdWords and Facebook Advertising, students acquire practical experience in the realms of digital marketing and analytics. == vBook == A vBook is an eBook that is digital first media with embedded video, images, graphs, tables, text, and other media.

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  • Pandorabots

    Pandorabots

    Pandorabots, Inc. is an artificial intelligence company that runs a web service for building and deploying chatbots. Pandorabots implements and supports development of the Artificial Intelligence Markup Language and makes portions of its code accessible for free. The Pandorabots Platform is "one of the oldest and largest chatbot hosting services in the world", allowing creation of virtual agents to hold human-like text or voice chats with consumers. The platform is written in Allegro Common LISP. == Use Cases == Common use cases include advertising, virtual assistance, e-learning, entertainment and education. The platform has also been used by academics and universities use the platform for teaching and research.

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  • Amino (app)

    Amino (app)

    Amino was a social media application originally developed by Narvii, Inc. It was originally created by Yin Wang and Ben Anderson in 2010, and then launched as an app in 2012. Amino was acquired by MediaLab AI Inc in January 2021, and the founders are no longer associated with the application. The platform ceased all operations in December 2025. == History == In 2010, Wang and Anderson came up with the idea for a convention-like community while attending an anime convention in Boston, Massachusetts. Later that year, they would release two apps revolving around K-pop and photography that allowed fans of those subjects to chat freely. That same year, Amino was officially released. === Shutdown === In early December 2025, the Amino platform abruptly stopped all operations. Users worldwide lost access to the mobile application and website, with server requests returning connection time-out errors. Parent company MediaLab AI has issued no official statement regarding the cause to date, or declared any possible cause behind it. === Final Message === According to Shawn, a member of Amino support, Amino has ceased operations as of December 19th. The message that was sent out from Shawn reads: "Hey there, Thanks for your message. Amino has ceased operations. As of December 19th, we no longer retain personal data relating to you. Accordingly, we are unable to provide a copy of your data. Kind regards, - Amino Support" This message was sent on January 4th, 2026. This was the final support message sent from the Amino Support mail. == Growth == Amino received 1.65 million dollars of seed funding in 2014, primarily from Union Ventures. Some additional seed investors include Google Ventures, SV Angel, Box Group, and other interested parties. By July 2014, Amino's apps were downloaded 500,000 times. Though only having 15 communities at that time, Amino eventually grew to have 41 communities in September 2015. Amino's apps had been downloaded 13 million times by July 2016. Fandoms had migrated from websites like Facebook and Reddit to Amino, partly because of the app's mobile-native experience. Before 2016, when a user wanted to join a new Amino, they had to download another app for the Amino they wanted to join, with each apps name beginning with "Amino for:". In 2016, Amino Apps launched a centralized portal that hosted every Amino community in one app, meaning users no longer had to download multiple apps. In July of the same year, ACM, an app that allowed users to create their own communities, was launched. This resulted in the number of communities on Amino skyrocketing to over 2.5 million as of June 2018. == Features == The main feature of Amino was communities dedicated to a certain topic that users could join. Users could also chat with other members of a community in three ways: text, voice, or screening room, which allowed users to watch videos together while voice chatting. Other features include polls, blog posts, image posts, wiki entries, stories, and quizzes. In some cases, posts that were very well-made and had been noticed by a community's administration would end up receiving a feature, making it appear on the front page along with other featured content. In 2018, a premium membership option called Amino+ was added. Amino+ comes with additional features such as exclusive stickers, the ability to make stickers, custom chat bubbles, high resolution images, and other perks. Membership can now only be purchased with money. Amino coins can be purchased or earned through enabling ads, watching ad videos, completing activities on the Offer Wall, and playing Lucky Draw when checking in, but are of little use due to the users not being able to buy Amino+ by amino coins anymore. Members can give and receive coins through props. In 2019, Amino introduced six original short-form animated series, labelled "Amino Originals," produced by independent artists from across the internet. ATJ's "Little Red," a re-imagining of Little Red Riding Hood, premiered on November 15, 2019. "Little Red" was joined by five other shows in late December. Sophie Feher's "The Reef," a comedy featuring an aspiring marine biologist meeting a merman, premiered on December 27 alongside "Princely," an LGBT fairy tale created by Matt Bruneau-Richardson of Tiny Siren Animation. "Spaced Out," an alien abduction comedy by Michael Jae, and YouTuber Alex Clark's "Wyndvania II" premiered on December 28. Mysie Pereira's fairy tale "Turned to Stone" and Marcin Pawlowski's "Stranded" premiered on December 29, 2019. == Administration == On each community, there are two types of staff members, these being ‘Leader’ and ‘Curator.’ Leaders are higher rank than curators. Curators are usually the ones who feature posts, or post important announcements for users to see. Curators are able to disable a post or public chat, delete comments or chat threads, manage featured content, manage posts in topic categories, and approve Wiki entries. Leaders have more power than curators. In addition to curator powers, leaders can submit a community to be listed, change the Amino's features, change navigation, alter the community appearance, change the Amino's privacy settings, manage the Amino's join requests, send invites, appoint or demote Curators, strike or ban members, manage flagged content, change users' custom titles, manage topics and wiki categories, and create broadcasts (notifications sent for posts). One leader will have the status of agent. An agent is the primary leader of a community; the person who created the community is automatically agent. An agent has the ability to delete their community as long as it is not too large or too active. An agent can appoint and remove both leaders and curators. Agent status can be transferred voluntarily to another leader, curator, or community member. If an agent is inactive, Team Amino may assist in transferring agent status. == Apps == === Amino Community Manager === Otherwise known as ACM, this application is what users use to create and manage their own community in Amino. This app allows moderators to customize a community's theme, icon, and categories. ACM also allows moderation to customize community descriptions, pick leaders, change language settings, create a tagline for the community, change the home page lay out, alter the side navigation menu, and more. Unlisted communities are able to change their community's title and Amino ID, but this is not an option once a community is listed. A leader can use ACM to submit a request for their community to be listed on the explore page, after which the community will be reviewed by Team Amino for approval. Communities can be deleted on ACM, but only by the agent of that community. == Guidelines == Amino has a set of guidelines that all communities must comply with. Amino does not allow harassment or hate, spam or self-promotion (including promotion of one's own Amino community), sexual/NSFW content, self harm, real graphic/gross content (fictional content is generally acceptable), unsafe/illegal content, or content that violates copyright. Communities are allowed to have additional rules so long as they do not violate Amino's rules. In addition to Amino's rules, users are required to be at least 13 years of age in the U.S. and 16 years of age in European Union countries. While sexual imagery is not allowed in any community and text based sexual content is not allowed in public areas, some private communities are allowed to discuss sexual themes. However, they are not exempt from Amino's rules on NSFW content. If guidelines are broken, a leader may disable content or impose a warning, strike, or ban, depending on the severity of the infringement. A warning is a message informing the user that they have violated a guideline and may face further punishment unless they change their behaviour. A strike will put the user in read-only mode for up to 24 hours; this mode prevents the user from posting, chatting, or interacting with posts in that community. A ban removes the user from the community. Team Amino can separately issue users with strikes or bans across the entire platform. == Controversies == In 2017, organizations in Argentina for the protection of minors reported inappropriate material on the app, ranging from pornography to material promoting suicide to underage users. In 2019, Abilene police in Texas released a statement that sexual predators were using Amino chat rooms to approach minors. In 2020, authorities from the Christian County in the state of Kentucky alerted parents about possible sexual predators on Amino. In 2025, the British Police identified Amino as one of several platforms used by a child exploitation network that had previously extorted minors in different countries in Europe and North America. Several families reported to the National Society for the Prevention of Cruelty to Children that pedophiles were using the app for the purpose of sexual role-playing with minors, c

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  • Cringe culture

    Cringe culture

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

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  • Randomized benchmarking

    Randomized benchmarking

    Randomized benchmarking is an experimental method for measuring the average error rates of quantum computing hardware platforms. The protocol estimates the average error rates by implementing long sequences of randomly sampled quantum gate operations. Randomized benchmarking is the industry-standard protocol used by quantum hardware developers such as IBM and Google to test the performance of the quantum operations. The original theory of randomized benchmarking, proposed by Joseph Emerson and collaborators, considered the implementation of sequences of Haar-random operations, but this had several practical limitations. The now-standard protocol for randomized benchmarking (RB) relies on uniformly random Clifford operations, as proposed in 2006 by Dankert et al. as an application of the theory of unitary t-designs. In current usage randomized benchmarking sometimes refers to the broader family of generalizations of the 2005 protocol involving different random gate sets that can identify various features of the strength and type of errors affecting the elementary quantum gate operations. Randomized benchmarking protocols are an important means of verifying and validating quantum operations and are also routinely used for the optimization of quantum control procedures. == Overview == Randomized benchmarking offers several key advantages over alternative approaches to error characterization. For example, the number of experimental procedures required for full characterization of errors (called tomography) grows exponentially with the number of quantum bits (called qubits). This makes tomographic methods impractical for even small systems of just 3 or 4 qubits. In contrast, randomized benchmarking protocols are the only known approaches to error characterization that scale efficiently as number of qubits in the system increases. Thus RB can be applied in practice to characterize errors in arbitrarily large quantum processors. Additionally, in experimental quantum computing, procedures for state preparation and measurement (SPAM) are also error-prone, and thus quantum process tomography is unable to distinguish errors associated with gate operations from errors associated with SPAM. In contrast, RB protocols are robust to state-preparation and measurement errors Randomized benchmarking protocols estimate key features of the errors that affect a set of quantum operations by examining how the observed fidelity of the final quantum state decreases as the length of the random sequence increases. If the set of operations satisfies certain mathematical properties, such as comprising a sequence of twirls with unitary two-designs, then the measured decay can be shown to be an invariant exponential with a rate fixed uniquely by features of the error model. == History == Randomized benchmarking was proposed in Scalable noise estimation with random unitary operators, where it was shown that long sequences of quantum gates sampled uniformly at random from the Haar measure on the group SU(d) would lead to an exponential decay at a rate that was uniquely fixed by the error model. Emerson, Alicki and Zyczkowski also showed, under the assumption of gate-independent errors, that the measured decay rate is directly related to an important figure of merit, the average gate fidelity and independent of the choice of initial state and any errors in the initial state, as well as the specific random sequences of quantum gates. This protocol applied for arbitrary dimension d and an arbitrary number n of qubits, where d=2n. The SU(d) RB protocol had two important limitations that were overcome in a modified protocol proposed by Dankert et al., who proposed sampling the gate operations uniformly at random from any unitary two-design, such as the Clifford group. They proved that this would produce the same exponential decay rate as the random SU(d) version of the protocol proposed in Emerson et al.. This follows from the observation that a random sequence of gates is equivalent to an independent sequence of twirls under that group, as conjectured in and later proven in. This Clifford-group approach to Randomized Benchmarking is the now standard method for assessing error rates in quantum computers. A variation of this protocol was proposed by NIST in 2008 for the first experimental implementation of an RB-type for single qubit gates. However, the sampling of random gates in the NIST protocol was later proven not to reproduce any unitary two-design. The NIST RB protocol was later shown to also produce an exponential fidelity decay, albeit with a rate that depends on non-invariant features of the error model In recent years a rigorous theoretical framework has been developed for Clifford-group RB protocols to show that they work reliably under very broad experimental conditions. In 2011 and 2012, Magesan et al. proved that the exponential decay rate is fully robust to arbitrary state preparation and measurement errors (SPAM). They also proved a connection between the average gate fidelity and diamond norm metric of error that is relevant to the fault-tolerant threshold. They also provided evidence that the observed decay was exponential and related to the average gate fidelity even if the error model varied across the gate operations, so-called gate-dependent errors, which is the experimentally realistic situation. In 2018, Wallman and Dugas et al., showed that, despite concerns raised in, even under very strong gate-dependence errors the standard RB protocols produces an exponential decay at a rate that precisely measures the average gate-fidelity of the experimentally relevant errors. The results of Wallman. in particular proved that the RB error rate is so robust to gate-dependent errors models that it provides an extremely sensitive tool for detecting non-Markovian errors. This follows because under a standard RB experiment only non-Markovian errors (including time-dependent Markovian errors) can produce a statistically significant deviation from an exponential decay The standard RB protocol was first implemented for single qubit gate operations in 2012 at Yale on a superconducting qubit. A variation of this standard protocol that is only defined for single qubit operations was implemented by NIST in 2008 on a trapped ion. The first implementation of the standard RB protocol for two-qubit gates was performed in 2012 at NIST for a system of two trapped ions

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  • ShowDocument

    ShowDocument

    ShowDocument is an online web application that allows multiple users to conduct web meetings, upload, share and review documents from remote locations. The service was developed by the HBR Labs company, established in 2007. == Features == Users can collaborate on and review documents in real time, with annotations and text being visible to all users and accessible for co-editing. The idea of every user being able to annotate can cause conflicts within the sessions, and so main navigation options are under the "presenter"'s control - which can be given to a different user as well. An earlier version of the application, by contrast, had allowed all users to navigate and edit at once, causing the system to drop all incomplete edits. It is possible to draw and write on a virtual whiteboard, and to stream a YouTube video to a group in full synchronization. A feature also exists for co-browsing of Google Maps. Entering an open session in the application can be done with a given code number, or by receiving a link through an Email message. Different file formats can be uploaded and saved either online or offline, such as PDF. A PDF file's text cannot be edited - text is edited through the separate text editor. Although the platform contains a text chat, it is not intended to replace instant messaging software, as there are no extensive messaging features. The application has a paid and free version, with the free version having a few limitations: audio and video options are disabled, number of participants is limited and sessions are time-limited. == Development == ShowDocument was first developed in 2007. On September 8, 2009, HBR labs released a new update which included features such as secure online document storage and mobile device support.

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  • DBOS

    DBOS

    DBOS (Formerly Database-Oriented Operating System, now just DBOS) is an open source durable workflow execution software library written for the Python, TypeScript, Java, and Go programming languages. DBOS arose from a joint open source project from MIT and Stanford, after a discussion between Michael Stonebraker and Matei Zaharia on how to scale and improve scheduling and performance of millions of Apache Spark tasks. Today it is a commercial company that offers an open source system to add durable computing to any software, built on concepts derived from the joint research project. == History == === 2020: Academic R&D Project === DBOS originated in 2020 as a joint open source project between MIT, Stanford, and Carnegie Mellon. The project explored the idea of operating system services built atop a distributed database - a database-oriented operating system meant to simplify and improve the scalability, security and resilience of large-scale distributed applications. The basic concept was to run a multi-node multi-core, transactional, highly-available distributed database, such as VoltDB, as the only application for a microkernel, and then to implement scheduling, messaging, file systems and other operating system services on top of the database. The architectural philosophy is described by this quote from the abstract of their initial preprint: All operating system state should be represented uniformly as database tables, and operations on this state should be made via queries from otherwise stateless tasks. This design makes it easy to scale and evolve the OS without whole-system refactoring, inspect and debug system state, upgrade components without downtime, manage decisions using machine learning, and implement sophisticated security features. A prototype was built with competitive performance to existing systems. ==

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  • Algorithmic radicalization

    Algorithmic radicalization

    Algorithmic radicalization is the concept that recommender algorithms on popular social media sites, such as YouTube and Facebook, drive users toward progressively more extreme content over time, leading to the development of radicalized extremist political views. Algorithms meticulously record user interactions, encompassing likes, dislikes and the duration of time watching content, with the objective of generating an endless stream of media designed to sustain user engagement. The phenomenon of echo chamber channels has been demonstrated to exacerbate the polarization of consumers, primarily through the reinforcement of media preferences and the validation of one's existing beliefs. Algorithmic radicalization remains a controversial phenomenon as it is often not in the best interest of social media companies to remove echo chamber channels. To what extent recommender algorithms are actually responsible for radicalization remains disputed. Studies have found contradictory results regarding the promotion of extremist content by algorithms. == Social media echo chambers and filter bubbles == Social media platforms learn the interests and likes of the user to modify their experiences in their feed to keep them engaged and scrolling, known as a filter bubble. An echo chamber is formed when users come across beliefs that magnify or reinforce their thoughts and form a group of like-minded users in a closed system. Echo chambers spread information without any opposing beliefs and can possibly lead to confirmation bias. According to group polarization theory, an echo chamber can potentially lead users and groups towards more extreme radicalized positions. According to the National Library of Medicine, "Users online tend to prefer information adhering to their worldviews, ignore dissenting information, and form polarized groups around shared narratives. Furthermore, when polarization is high, misinformation quickly proliferates." == By site == === Facebook === Facebook's algorithm focuses on recommending content that makes the user want to interact. They rank content by prioritizing popular posts by friends, viral content, and sometimes divisive content. Each feed is personalized to the user's specific interests which can sometimes lead users towards an echo chamber of troublesome content. Users can find their list of interests the algorithm uses by going to the "Your ad Preferences" page. According to a Pew Research study, 74% of Facebook users did not know that list existed until they were directed towards that page in the study. It is also relatively common for Facebook to assign political labels to their users. In recent years, Facebook has started using artificial intelligence to change the content users see in their feed and what is recommended to them. A document known as The Facebook Files has revealed that their AI system prioritizes user engagement over everything else. The Facebook Files has also demonstrated that controlling the AI systems has proven difficult to handle. In an August 2019 internal memo leaked in 2021, Facebook has admitted that "the mechanics of our platforms are not neutral", concluding that in order to reach maximum profits, optimization for engagement is necessary. In order to increase engagement, algorithms have found that hate, misinformation, and politics are instrumental for app activity. As referenced in the memo, "The more incendiary the material, the more it keeps users engaged, the more it is boosted by the algorithm." According to a 2018 study, "false rumors spread faster and wider than true information... They found falsehoods are 70% more likely to be retweeted on Twitter than the truth, and reach their first 1,500 people six times faster. This effect is more pronounced with political news than other categories." === YouTube === YouTube has been around since 2005 and has more than 2.5 billion monthly users. YouTube discovery content systems focus on the user's personal activity (watched, favorites, likes) to direct them to recommended content. YouTube's algorithm is accountable for roughly 70% of users' recommended videos and what drives people to watch certain content. According to a 2022 study by the Mozilla Foundation, users have little power to keep unsolicited videos out of their suggested recommended content. This includes videos about hate speech, livestreams, etc. YouTube has been identified as an influential platform for spreading radicalized content. Al-Qaeda and similar extremist groups have been linked to using YouTube for recruitment videos and engaging with international media outlets. In a research study published by the American Behavioral Scientist Journal, they researched "whether it is possible to identify a set of attributes that may help explain part of the YouTube algorithm's decision-making process". The results of the study showed that YouTube's algorithm recommendations for extremism content factor into the presence of radical keywords in a video's title. In February 2023, in the case of Gonzalez v. Google, the question at hand is whether or not Google, the parent company of YouTube, is protected from lawsuits claiming that the site's algorithms aided terrorists in recommending ISIS videos to users. Section 230 is known to generally protect online platforms from civil liability for the content posted by its users. Multiple studies have found little to no evidence to suggest that YouTube's algorithms direct attention towards far-right content to those not already engaged with it. === TikTok === TikTok is a platform that recommends videos to a user's 'For You Page' (FYP), making every users' page different. With the nature of the algorithm behind the app, TikTok's FYP has been linked to showing more explicit and radical videos over time based on users' previous interactions on the app. Since TikTok's inception, the app has been scrutinized for misinformation and hate speech as those forms of media usually generate more interactions to the algorithm. Various extremist groups, including jihadist organizations, have utilized TikTok to disseminate propaganda, recruit followers, and incite violence. The platform's algorithm, which recommends content based on user engagement, can expose users to extremist content that aligns with their interests or interactions. As of 2022, TikTok's head of US Security has put out a statement that "81,518,334 videos were removed globally between April – June for violating our Community Guidelines or Terms of Service" to cut back on hate speech, harassment, and misinformation. Studies have noted instances where individuals were radicalized through content encountered on TikTok. For example, in early 2023, Austrian authorities thwarted a plot against an LGBTQ+ pride parade that involved two teenagers and a 20-year-old who were inspired by jihadist content on TikTok. The youngest suspect, 14 years old, had been exposed to videos created by Islamist influencers glorifying jihad. These videos led him to further engagement with similar content, eventually resulting in his involvement in planning an attack. Another case involved the arrest of several teenagers in Vienna, Austria, in 2024, who were planning to carry out a terrorist attack at a Taylor Swift concert. The investigation revealed that some of the suspects had been radicalized online, with TikTok being one of the platforms used to disseminate extremist content that influenced their beliefs and actions. == Self-radicalization == The U.S. Department of Justice defines 'Lone-wolf' (self) terrorism as "someone who acts alone in a terrorist attack without the help or encouragement of a government or a terrorist organization". Through social media outlets on the internet, 'Lone-wolf' terrorism has been on the rise, being linked to algorithmic radicalization. Through echo-chambers on the internet, viewpoints typically seen as radical were accepted and quickly adopted by other extremists. These viewpoints are encouraged by forums, group chats, and social media to reinforce their beliefs. == References in media == === The Social Dilemma === The Social Dilemma is a 2020 docudrama about how algorithms behind social media enables addiction, while possessing abilities to manipulate people's views, emotions, and behavior to spread conspiracy theories and disinformation. The film repeatedly uses buzz words such as 'echo chambers' and 'fake news' to prove psychological manipulation on social media, therefore leading to political manipulation. In the film, Ben falls deeper into a social media addiction as the algorithm found that his social media page has a 62.3% chance of long-term engagement. This leads into more videos on the recommended feed for Ben and he eventually becomes more immersed into propaganda and conspiracy theories, becoming more polarized with each video. == Proposed solutions == === United States: Weakening Section 230 protections === In the Communications Decency Act, Section 230 states t

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