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  TinEye

  TinEye is a reverse image search engine developed and offered by Idée, Inc., a company based in Toronto, Ontario, Canada. It was the first image search engine on the web to use image identification technology rather than keywords, metadata or watermarks. TinEye allows users to search not using keywords but with images. Upon submitting an image, TinEye creates a "unique and compact digital signature or fingerprint" of the image and matches it with other indexed images. This procedure is able to match even heavily edited versions of the submitted image, but will not usually return similar images in the results. == History == Idée, Inc. was founded by Leila Boujnane and Paul Bloore in 1999. Idée launched the service on May 6, 2008 and went into open beta in August that year. While computer vision and image identification research projects began as early as the 1980s, the company claims that TinEye is the first web-based image search engine to use image identification technology. The service was created with copyright owners and brand marketers as the intended user base, to look up unauthorized use and track where the brands are showing up respectively. In June 2014, TinEye claimed to have indexed more than five billion images for comparisons. However, this is a relatively small proportion of the total number of images available on the World Wide Web. As of September 2025, TinEye's search results claim to have over 77.6 billion images indexed for comparison. == Technology == A user uploads an image to the search engine (the upload size is limited to 20 MB) or provides a URL for an image or for a page containing the image. The search engine will look up other usage of the image in the internet, including modified images based upon that image, and report the date and time at which they were posted. TinEye does not recognize outlines of objects or perform facial recognition, but recognizes the entire image, and some altered versions of that image. This includes smaller, larger, and cropped versions of the image. TinEye has shown itself capable of retrieving different images from its database of the same subject, such as famous landmarks. TinEye is capable of searching for images in JPEG, PNG, WebP, GIF, BMP and TIFF format. Results generated from TinEye include the total number of matches in their database, a preview image, and the URL to each match. TinEye can sort results by best match, most changed, biggest image, newest, and oldest. User registration is optional and offers storage of the user's previous queries. Other features include embeddable widgets and bookmarklets. TinEye has also released their commercial API. == Usage == TinEye's ability to search the web for specific images (and modifications of those images) makes it a potential tool for the copyright holders of visual works to locate infringements on their copyright. It also creates a possible avenue for people who are looking to make use of imagery under orphan works to find the copyright holders of that imagery. Being that orphan works can be defined as "copyrighted works whose owners are difficult or impossible to identify and/or locate," the use of TinEye could potentially remove the orphan work status from online images that can be found in its database. === Fact-checking === It has been recommended by fact-checkers as a useful resource in attempts to verify the origin of images. As of 2019, TinEye specialized in copyright violations and finding exact versions of images online.

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  Paperless society

  A paperless society is a society in which paper communication (written documents, email, letters, etc.) is replaced by electronic communication and storage. The concept was first introduced by Frederick Wilfrid Lancaster in 1978. Furthermore, libraries would no longer be needed to handle printed documents. "Librarians will, in time, become information specialists in a deinstitutionalized setting". Lancaster also stated that both computers and libraries will not always give us the information that other people and living life will. == Literature == Brodman, E. (1979). Review of Toward Paperless Information Systems. Bulletin of the Medical Library Association, 67(4), 437–439. Buckland, M. K. (1980). Review of Toward Paperless Information Systems. Journal of Academic Librarianship, 5(6), 349. Grosch, A. (1979). Review of Toward Paperless Information Systems. College & Research Libraries, 40(1), 88–89. Kohl, D. F. (2004). From the editor . . . The paperless society . . . Not quite yet. Journal of Academic Librarianship, 30(3), 177–178. Lancaster, F. W. (1978a). Toward paperless information systems. New York: Academic Press. Lancaster, F. W. (1980b). The future of the librarian lies outside of the library. Catholic Library World, 51, 388–391. Lancaster, F. W. (1982a). Libraries and librarians in an age of electronics. Arlington, VA: Information Resources Press. Lancaster, F. W. (1982b). The evolving paperless society and its implications for libraries. International Forum on Information and Documentation, 7(4), 3–10. Lancaster, F. W. (1983). Future librarianship: Preparing for an unconventional career. Wilson Library Bulletin, 57, 747–753. Lancaster, F. W. (1985). The paperless society revisited. American Libraries, 16, 553–555. Lancaster, F. W. (1993). Libraries and the future: Essays on the library in the twenty-first century. New York: Haworth Press. Lancaster, F. W. (1999). Second thoughts on the paperless society. Library Journal, 124(15), 48– 50. Lancaster, F. W., & Smith, L. C. (1980c). On-Line systems in the communication process: Projections. Journal of the American Society for Information Science, 31(3), 193–200. Miall, D. S. (2001). The library versus the Internet: Literary studies under siege? Proceedings of the Modern Language Association, 116(5), 1405–1414. Salton, G. (1979). Review of Toward Paperless Information Systems. Journal of Documentation, 35(3), 250–252. Sellen, A. J., & Harper, R. H. R. (2003). The myth of the paperless office. Cambridge, MA: MIT Press. Stevens, N. D. (2006). The fully electronic academic library. College & Research Libraries, 67(1),5–14. Young, Arthur P. (2008).Aftermath of a Prediction: F. W. Lancaster and the Paperless Society LIBRARY TRENDS, 56(4),(“The Evaluation and Transformation of Information Systems: Essays Honoring the Legacy of F. W. Lancaster,” edited by Lorraine J. Haricombe and Keith Russell), pp. 843–858.

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  Are We Dating The Same Guy?

  Are We Dating The Same Guy?, also abbreviated AWDTSG is a series of over 200 individual Facebook groups where women share dating profiles of men they matched with on dating networks to seek the opinion of other women who may have dated the same man in the past. The first group was created by Paola Sanchez and aimed at women living in the New York City environs. The groups have over 3.5 million members as of January 2024. The group's function is to post screenshots of a man's dating profile to that city's designated Facebook group, after which the poster asks "any tea?". Other users in the group will then share information about the man and share warnings. The groups are moderated by volunteers, and have been described as a feminist group. The groups have rules saying that personal information such as addresses must not be included in the Facebook posts. Users attempting to join the group are also examined to prevent fake profiles. The group is mainly for straight women. According to Vice, the men being posted about have no way to defend against accusations made about them, and on the other hand, posters cannot prove their stories unless backed up by others. Often times, members post pictures alongside personal information such as names, which may infringe on subjects' legal right to privacy. Lawyers have said these issues can lead to defamation lawsuits, and members can make false allegations and create fabricated stories. If members tell a man that he's been talked about on the group, the "snitch" will be banned and be "exposed to the whole group". == History == The first Are We Dating The Same Guy group was created by Paola Sanchez. The first group was created in March 2022 in New York City. A male counterpart, named "Are We Dating the Same Girl NYC" was created for New York, with mostly the same guidelines and rules to the original. When the original Are We Dating The Same Guy group found it, they denounced the new group. == Operations == Administrators are told not to respond to men asking to have posts about them removed, and to not remove said posts. The people being posted about have reported being questioned by their employers about things they have not done. Members of the groups sometimes criticise the physical appearance of the men being posted about. According to the Evening Standard, the groups "frequent[ly] mock" the appearance or dating profiles of the men who are posted about, despite being against the rules. For this behaviour, women are sometimes kicked out, or the group is disciplined en masse by admins. The groups have rules against hate towards men, but the rules can be difficult to enforce in large groups, with some having over 100,000 members. Some men have also been able to join the groups without being noticed. == Reception == In October 2023, Sera Bozza of Body+Soul wrote that consistently using Are We Dating The Same Guy can "affect your real-world view". She wrote that "A few stories of cheating may persuade you to believe that all men are unfaithful". Some lawyers and commentators have expressed concern that the groups fail to acknowledge the legal right to privacy and users can create false allegations and fabricated stories, and cyberbully men without them being able to defend themselves. This may lead to civil lawsuits against the author for defamation, harassment, and other related privacy torts. Netsafe, an online safety organisation in New Zealand, advises users of a similar group to familiarise themselves with the Harmful Digital Communications Act to ensure that posts do not lead to "harmful consequences". The Independent reported that men who have been posted on the dating groups have felt violated, and that even if reviewed positively by potentially thousands of strangers, the men being discussed about may have their reputation slightly decreased due to the association with being on the groups. The Independent also reported that some men believe that the groups are created to spread lies or mock them. Mashable reported that the growth of AWDTSG in recent years has led to the rise of a small industry of online reputation and content removal services, as increasing numbers of men seek assistance. A co-founder of Maximatic Media, one such agency offering these removal services, stated that many of the men contacting the firm do so in a state of panic after learning that allegations about them have circulated among tens of thousands of participants without their knowledge. Mashable similarly reported that the growing visibility of AWDTSG and similar platforms has contributed to what commentators describe as a "public trial" dynamic, where subjective accounts about dating behavior are interpreted as factual assessments and can influence a person's reputation among large audiences within their locale. The Oklahoman reported that anonymous, unverified claims in these groups have led some men to experience social and dating repercussions, although legal analysts argue that the benefits of community-based safety networks still outweigh these concerns in modern, app based dating environments. UTV/ITV News reportedly spoke to a man who was posted who alleged he attempted suicide, was clinically dead for three minutes, and spent three weeks in a psychiatric hospital as a result of the posts made about him. Many other men have talked about malicious false claims made about them. Self-described men’s rights activists have taken a dislike to these groups and have gotten multiple North American groups shut down by running campaigns, threatening lawsuits, and mass Facebook reporting. They also have Reddit communities dedicated to getting rid of such groups. Women who have posted in the groups have felt that they have put their safety at risk, with some having been confronted by the men they posted about. The group has been noted for exposing men who use dating apps while already in a relationship, misrepresent their ages, or repeatedly stand up the women they meet through apps, among other bad dating behaviors. For example, some members of the group had matched on a dating site with a man who had, several years prior, killed a stranger while having a mental break. After this information came to light, members of the group were warned. The group has also been noted to be complimentary of some men. == Lawsuits == In 2023, a 41-year-old man sued the administrators of the London group for $35,000 under defamation, alleging that the group "called names, accused of sending lewd photos and of being a bad parent". In January 2024 a man sued Meta, the owner of Facebook, along with Patreon, GoFundMe, and the AWDTSG website, as well as almost 30 group members due to alleged defamation, emotional distress, and invasion of privacy. Claiming that the groups violate anti-doxxing laws and do not fact check, seeking $75,000 in damages. He claims that the group shared fake images of him sending women texts containing harassment, his name and photo. His attorneys claim that if the images were real, they would fall under free speech in the First Amendment. By February, groups had raised $80,000. The Washington Post said that this case caused AWDTSG to "explode into public view". The case was dismissed in 2025 by the United States District Court for the Northern District of Illinois. On May 15, 2026, the United States Court of Appeals for the Seventh Circuit declined to renew the case in D'Ambrosio v. Meta Platforms Inc., et al. The plaintiff and his attorneys, Marc Trent and Aaron Walner of Trent Law Firm, were sanctioned "for frivolously appealing the dismissal of the claims," "misrepresentations of law," in connection with falsified citations included in the plaintiff's brief, and " disputing at oral argument without any evidentiary basis that [the plaintiff] client sent the text message she attributed to him." == By country == === Australia === In Australia, there are groups for multiple cities including Sydney, Melbourne, Adelaide, Perth, Brisbane and Rockhampton with many having several thousand members. The Sydney group has 30,000 members. In March 2023, the Adelaide version of the group, which had 7,000 members, was shut down. In 2024, groups titled "Sis, Are We Dating The Same Guy" stopped accepting new posts after an admin was sued for defamation and had to pay over AU$20,000 in legal fees. The case was settled out of court. The administrator announcing these closures cited a 2021 defamation High Court case involving detainee Dylan Voller, which led to the High Court saying that owners of Facebook groups can be held liable for defamatory comments, even if they did not know the comments had been made. === Canada === In 2023, a group was started for Ottawa. The founder previously was in a relationship full of "cheating and lies", which prompted her to creating the Facebook community. In 2023, the group for Vancouver and British Columbia was shut down after concerns about men being unable to protect themselves against fa

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  Telecommunications

  Telecommunication, often used in its plural form or abbreviated as telecom, is the transmission of information over a distance using electrical or electronic means, typically through cables, radio waves, or other communication technologies. These means of transmission may be divided into communication channels for multiplexing, allowing for a single medium to transmit several concurrent communication sessions. Long-distance technologies invented during the 19th, 20th and 21st centuries generally use electric power, and include the electrical telegraph, telephone, television, and radio. Early telecommunication networks used metal wires as the medium for transmitting signals. These networks were used for telegraphy and telephony for many decades. In the first decade of the 20th century, a revolution in wireless communication began with breakthroughs including those made in radio communications by Guglielmo Marconi, who won the 1909 Nobel Prize in Physics. Other early pioneers in electrical and electronic telecommunications include co-inventors of the telegraph Charles Wheatstone and Samuel Morse, numerous inventors and developers of the telephone including Antonio Meucci, Philipp Reis, Elisha Gray and Alexander Graham Bell, inventors of radio Edwin Armstrong and Lee de Forest, as well as inventors of television like Vladimir K. Zworykin, John Logie Baird and Philo Farnsworth. Since the 1960s, the proliferation of digital technologies has meant that voice communications have gradually been supplemented by data. The physical limitations of metallic media prompted the development of optical fibre. The Internet, a technology independent of any given medium, has provided global access to services for individual users and further reduced location and time limitations on communications. == Definition == At the 1932 Plenipotentiary Telegraph Conference and the International Radiotelegraph Conference in Madrid, the two organizations merged to form the International Telecommunication Union (ITU). They defined telecommunication as "any telegraphic or telephonic communication of signs, signals, writing, facsimiles and sounds of any kind, by wire, wireless or other systems or processes of electric signaling or visual signaling (semaphores)." The definition was later reconfirmed, according to Article 1.3 of the ITU Radio Regulations, which defined it as "Any transmission, emission or reception of signs, signals, writings, images and sounds or intelligence of any nature by wire, radio, optical, or other electromagnetic systems". As such, slow communications technologies like postal mail and pneumatic tubes are excluded from the telecommunication's definition. The term telecommunication was coined in 1904 by the French engineer and novelist Édouard Estaunié, who defined it as "remote transmission of thought through electricity". Telecommunication is a compound noun formed from the Greek prefix tele- (τῆλε), meaning distant, far off, or afar, and the Latin verb communicare, meaning to share. Communication was first used as an English word in the late 14th century. It comes from Old French comunicacion (14c., Modern French communication), from Latin communicationem (nominative communication), noun of action from past participle stem of communicare, "to share, divide out; communicate, impart, inform; join, unite, participate in," literally, "to make common", from communis. == History == Many transmission media have been used for long-distance communication throughout history, from smoke signals, beacons, semaphore telegraphs, signal flags, and optical heliographs to wires and empty space made to carry electromagnetic signals. === Before the electrical and electronic era === Long-distance communication was used long before the discovery of electricity and electromagnetism enabled the invention of telecommunications. A few of the many ingenious methods for communicating over distances prior to that are described here. Homing pigeons have been used throughout history by different cultures. Pigeon post had Persian roots and was later used by the Romans to aid their military. Frontinus claimed Julius Caesar used pigeons as messengers in his conquest of Gaul. The Greeks also conveyed the names of the victors at the Olympic Games to various cities using homing pigeons. In the early 19th century, the Dutch government used the system in Java and Sumatra. And in 1849, Paul Julius Reuter started a pigeon service to fly stock prices between Aachen and Brussels, a service that operated for a year until the gap in the telegraph link was closed. In the Middle Ages, chains of beacons were commonly used on hilltops as a means of relaying a signal. Beacon chains suffered the drawback that they could only pass a single bit of information, so the meaning of the message, such as "the enemy has been sighted" had to be agreed upon in advance. One notable instance of their use was during the Spanish Armada, when a beacon chain relayed a signal from Plymouth to London. In 1792, Claude Chappe, a French engineer, built the first fixed visual telegraphy system (or semaphore line) between Lille and Paris. However semaphore suffered from the need for skilled operators and expensive towers at intervals of ten to thirty kilometres (six to nineteen miles). As a result of competition from the electrical telegraph, the last commercial line was abandoned in 1880. === Telegraph and telephone === On July 25, 1837, the first commercial electrical telegraph was demonstrated by English inventor Sir William Fothergill Cooke and English scientist Sir Charles Wheatstone. Both inventors viewed their device as "an improvement to the [existing] electromagnetic telegraph" and not as a new device. Samuel Morse independently developed a version of the electrical telegraph that he unsuccessfully demonstrated on September 2, 1837. His code was an important advance over Wheatstone's signaling method. The first transatlantic telegraph cable was successfully completed on July 27, 1866, allowing transatlantic telecommunication for the first time. After early attempts to develop a talking telegraph by Antonio Meucci and a telefon by Johann Philipp Reis, a patent for the conventional telephone was filed by Alexander Bell in February 1876 (just a few hours before Elisha Gray filed a patent caveat for a similar device). The first commercial telephone services were set up by the Bell Telephone Company in 1878 and 1879 on both sides of the Atlantic in the cities of New Haven and London. === Radio and television === In 1894, Italian inventor Guglielmo Marconi began developing wireless communication using the then-newly discovered phenomenon of radio waves, demonstrating, by 1901, that they could be transmitted across the Atlantic Ocean. This was the start of wireless telegraphy by radio. On 17 December 1902, a transmission from the Marconi station in Glace Bay, Nova Scotia, Canada, became the world's first radio message to cross the Atlantic from North America. In 1904, a commercial service was established to transmit nightly news summaries to subscribing ships, which incorporated them into their onboard newspapers. World War I accelerated the development of radio for military communications. After the war, commercial radio AM broadcasting began in the 1920s and became an important mass medium for entertainment and news. World War II again accelerated the development of radio for the wartime purposes of aircraft and land communication, radio navigation, and radar. Development of stereo FM broadcasting of radio began in the 1930s in the United States and the 1940s in the United Kingdom, displacing AM as the dominant commercial standard in the 1970s. On March 25, 1925, John Logie Baird demonstrated the transmission of moving pictures at the London department store Selfridges. Baird's device relied upon the Nipkow disk by Paul Nipkow and thus became known as the mechanical television. It formed the basis of experimental broadcasts done by the British Broadcasting Corporation beginning on 30 September 1929. === Vacuum tubes === Vacuum tubes use thermionic emission of electrons from a heated cathode for a number of fundamental electronic functions such as signal amplification and current rectification. The simplest vacuum tube, the diode invented in 1904 by John Ambrose Fleming, contains only a heated electron-emitting cathode and an anode. Electrons can only flow in one direction through the device—from the cathode to the anode. Adding one or more control grids within the tube enables the current between the cathode and anode to be controlled by the voltage on the grid or grids. These devices became a key component of electronic circuits for the first half of the 20th century and were crucial to the development of radio, television, radar, sound recording and reproduction, long-distance telephone networks, and analogue and early digital computers. While some applications had used earlier technologies such as the sp

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  Accelerated Linear Algebra

  XLA (Accelerated Linear Algebra) is an open-source compiler for machine learning developed by the OpenXLA project. XLA is designed to improve the performance of machine learning models by optimizing the computation graphs at a lower level, making it particularly useful for large-scale computations and high-performance machine learning models. Key features of XLA include: Compilation of Computation Graphs: Compiles computation graphs into efficient machine code. Optimization Techniques: Applies operation fusion, memory optimization, and other techniques. Hardware Support: Optimizes models for various hardware, including CPUs, GPUs, and NPUs. Improved Model Execution Time: Aims to reduce machine learning models' execution time for both training and inference. Seamless Integration: Can be used with existing machine learning code with minimal changes. XLA represents a significant step in optimizing machine learning models, providing developers with tools to enhance computational efficiency and performance. == OpenXLA Project == OpenXLA Project is an open-source machine learning compiler and infrastructure initiative intended to provide a common set of tools for compiling and deploying machine learning models across different frameworks and hardware platforms. It provides a modular compilation stack that can be used by major deep learning frameworks like JAX, PyTorch, and TensorFlow. The project focuses on supplying shared components for optimization, portability, and execution across CPUs, GPUs, and specialized accelerators. Its design emphasizes interoperability between frameworks and a standardized set of representations for model computation. == Components == The OpenXLA ecosystem includes several core components: XLA – A deep learning compiler that optimizes computational graphs for multiple hardware targets. PJRT – A runtime interface that allows different back-ends to connect to XLA through a consistent API. StableHLO – A high-level operator set intended to serve as a stable, portable representation for ML models across compilers and frameworks. Shardy – An MLIR-based system for describing and transforming models that run in distributed or multi-device environments. Additional profiling, testing, and integration tools maintained under the OpenXLA organization. == Users and adopters == Several machine learning frameworks can use or interoperate with OpenXLA components, including JAX, TensorFlow, and parts of the PyTorch ecosystem. The project is developed with participation from multiple hardware and software organizations that contribute back-end integrations, testing, or specifications for their devices. This includes Alibaba, Amazon Web Services, AMD, Anyscale, Apple, Arm, Cerebras, Google, Graphcore, Hugging Face, Intel, Meta, NVIDIA and SiFive. == Supported target devices == x86-64 ARM64 NVIDIA GPU AMD GPU Intel GPU Apple GPU Google TPU AWS Trainium, Inferentia Cerebras Graphcore IPU == Governance == OpenXLA is developed as a community project with its work carried out in public repositories, discussion forums, and design meetings. Some components, such as StableHLO, began with stewardship from specific organizations and have outlined plans for more formal and distributed governance models as the project matures. == History == The project was announced in 2022 as an effort to coordinate development of ML compiler technologies across major AI companies, notably: Alibaba, Amazon Web Services, AMD, Anyscale, Apple, Arm, Cerebras, Google, Graphcore, Hugging Face, Intel, Meta, NVIDIA and SiFive.. It consolidated the XLA compiler, introduced StableHLO as a portable operator set, and created a unified structure for additional tools. Development continues within multiple repositories under the OpenXLA umbrella. It was founded by Eugene Burmako, James Rubin, Magnus Hyttsten, Mehdi Amini, Navid Khajouei, and Thea Lamkin from Google's Machine Learning organization.

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  MX1 Ltd

  MX1 was a global media services provider founded in July 2016 from a merger between digital media services companies, RR Media and SES Platform Services, and a wholly owned subsidiary of global satellite owner and operator, SES. In September 2019, MX1 was merged into the SES Video division and the MX1 brand dropped. Broadcast and streamed content management, playout, distribution, and monetisation services from both MX1 and SES Video are now provided under the SES name. Before merger with SES, MX1 claimed to manage more than 5 million media assets and every day to distribute more than 3,600 TV channels, manage the playout of over 525 channels, distribute content to more than 120 subscription VOD platforms, and deliver over 8,400 hours of online video streaming and more than 620 hours of premium sports and live events. == Services == MX1 video and media services are provided through a single hybrid, cloud and on-premises solution, called MX1 360, which enables video and media solutions including content and metadata management, archiving, localisation solutions, channel playout, VOD, online video (OTT) and content distribution. Services provided by MX1 include: === Content aggregation === Acquisition of content via satellite, fibre or IP with satellite downlinking services (for encryption, re-encryption and re-muxing into different platforms), fibre reception from any location, and IP reception via the public Internet. Live sports, news and entertainment production (including in-studio, outside broadcasting, and SNG) with mobile live streaming and video contribution. === Content management === Digital mastering including scanning, conversion, restoration, quality control and localisation/versioning. Content archiving including secure, cloud and on-premises digital storage, and disaster recovery services. Metadata packaging and platform validation to enhance content discovery, searchability and cataloguing. Playout preparation and delivery to any format. === Channel origination and playout === Managed TV channel origination in SD, HD and UHD including 3D graphics, and video and audio effects, using cloud-based solution accessible from any location, with live content insertion and operation, and 24/7 monitoring. === Online video/VOD services === Content preparation and management for online video, VOD, live streaming services and Online video platforms using an ultra-high capacity content delivery network, including subscriber management, apps, DRM, social media, advertising tools, monetisation tools, metadata management, and analytics. === Content delivery === Delivery in all video formats over hybrid distribution network of satellite (using over 150 platforms), fibre (60 digital media hubs worldwide) and the Internet with complete downlink/uplink turnaround services and OTT content delivery. == Locations == MX1 has 16 offices worldwide, the most recent opened in March 2017 in Seoul, South Korea, as well as media centres in UK (London), US (Hawley, PA), Israel (Emeq Ha'Ela), Romania (Bucharest) and at the headquarters in Unterföhring near Munich, Germany. In the early part of 2017, significant upgrades were made to MX1's US media centre in Hawley, Pennsylvania, including expanding its capabilities for US based and global content aggregation, management and delivery to support US broadcasters and content providers. == History == RRsat was founded in Israel by David Rivel, an electronics, computers and communications engineer in 1981 as a communications provider, and in 2014 changed its name to RR Media to reflect its expanding global service offering. In 2015, RR Media acquired Eastern Space Systems (ESS), a Romanian provider of content management and content distribution services and satellite transmission services provider, SatLink Communications. Digital Playout Centre GmbH (DPC) was founded in 1996 by German media company, Kirch to provide playout, multiplexing, satellite uplinks and other broadcast services to Kirch's Premiere pay-TV platform (now Sky Deutschland) and other private and public German broadcasters. In 2005, SES Astra (a subsidiary of SES Global, now SES) bought 100% of DPC from Premiere and the company renamed ASTRA Platform Services GmbH (APS). In 2012, to reflect the company's expanding worldwide reach, the name was changed to SES Platform Services. In February 2016, it was announced that SES Platform Services had agreed, subject to regulatory approvals, to purchase RR Media. The acquisition was completed in July 2016, with the merged company renamed MX1 and headed by Avi Cohen, the former CEO of RR Media. In October 2017, Cohen was replaced as CEO by Wilfred Urner, the former CEO of SES Platform Services, CEO of SES subsidiary, HD+ and Head of Media Platforms and Product Development, SES Video.

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  Over-the-top media services in India

  As per Govt of India, there are currently about 57 providers of over-the-top media services (OTT) in India, which distribute streaming media or video on demand over the Internet. == History and growth == The first dependent Indian OTT platform was BIGFlix, launched by Reliance Entertainment in 2008. In 2010 Digivive launched India's first OTT mobile app called nexGTv, which provides access to both live TV and on–demand content. nexGTV was the first app to live–stream Indian Premier League matches on smart phones and did so during 2013 and 2014. The livestream of the IPL since 2015, when rights were won, played an important role in the growth of another OTT platform, Hotstar (now JioHotstar) in India. OTT Platforms gained significant momentum in India when both DittoTV (Zee) and Sony Liv were launched in the Indian market around 2013. Following the initial push of Regional OTT platforms like Aha, Hoichoi, Sun NXT, Planet Marathi, Chaupal & MX Player. The Indian OTT industry saw rapid transformation with the entry of global OTT companies such as Netflix and Amazon Prime Video into the Indian market in 2016. Replacement of this competition with global enterprises caused local rivals to innovate in both region and hyper-regional content. === Hotstar === Hotstar (now JioHotstar) is the most subscribed–to OTT platform in India, owned by JioStar as of February 2025, with around 500 million active users and over 650 million downloads. According to Hotstar's India Watch Report 2018, 96% of watch time on Hotstar comes from videos longer than 20 minutes, while one–third of Hotstar subscribers watch television shows. In 2019, Hotstar began investing ₹120 crore in generating original content such as "Hotstar Specials." 80% of the viewership on Hotstar comes from drama, movies and sports programs. Hotstar has the exclusive streaming rights of IPL in India. === Netflix === American streaming service Netflix entered India in January 2016. In April 2017, it was registered as a limited liability partnership (LLP) and started commissioning content. It earned a net profit of ₹2020,000 (₹2.02 million) for fiscal year 2017. In fiscal year 2018, Netflix earned revenues of ₹580 million. According to Morgan Stanley Research, Netflix had the highest average watch time of more than 120 minutes but viewer counts of around 20 million in July 2018. As of 2018, Netflix has six million subscribers, of which 5–6% are paid members. India was not affected by Netflix's July 2018 increase in subscription rates for the US and Latin America. Netflix has stated its intent to invest ₹600 crore in the production of Indian original programming. In late 2018, Netflix bought 150,000 square feet (14,000 m2) of office space in Bandra–Kurla Complex (BKC) in Mumbai as their head office. As of December 2018, Netflix has more than 40 employees in India. === Other OTT providers === Sun NXT is an Indian video on demand service run by Sun TV Network. It was launched in June 2017, streaming in the Tamil language and six other languages. The platform has more than 4,000 Tamil movies and 200 Tamil shows, as well as regional movies and shows. Sun NXT also streams a large library of its own Sun TV shows and movies. Amazon Prime Video was launched in 2016. The platform has 2,300 titles available including 2,000 movies and about 400 shows. It has announced that it will invest ₹20 billion in creating original content in India. Besides English, Prime Video is available in six Indian languages as of December 2018. Amazon India launched Amazon Prime Music in February 2018. Eros Now, an OTT platform launched by Eros International, has the most content among the OTT providers in India, including over 12,000 films, 100,000 music tracks and albums, and 100 TV shows. Eros Now was named the Best OTT Platform of the Year 2019 at the British Asian Media Awards. It has 211.5 million registered users and 36.2 million paying subscribers as of September 2020. In February 2020, Aha OTT platform was launched, broadcasting exclusively Telugu content. In 2021, Planet Marathi became the first OTT platform dedicated to Marathi content in India, including web-series, films, music, theater, fiction and non-fiction reality shows. It is available for both Android and iOS mobile devices along with Android TV and Amazon Fire TV devices. Bollywood actress Madhuri Dixit helped launch the platform. With rising interest for Korean dramas, Rakuten Viki saw its biggest jump of web traffic from India in 2020 due to the COVID-19 lockdown, which led to ad localization on the platform. The OTT market in fiscal year 2020 was estimated to be worth $1.7 billion. === SonyLIV and ZEE5 === In December 2021, Sony and Zee announced their merger, and announced plans to merge their OTT platforms. The merger was called off. === OTT services launched as Amazon Prime video channels === The list is by alphabetical order, not by rank or popularity. == Content regulation == Due to the absence of any rules and regulation regarding OTT content, many OTT providers were accused of showing nudity, vulgarity and obscenity and hurting Hindu religious sentiments in their shows. Series which were the focus of controversy include Four More Shots Please!, Tandav, Paatal Lok, Sacred Games, Mirzapur Lust stories franchise, Rana Naidu. Thank You for Coming, and Annapoorani (2023). According to media reports, between 2018 and 2024, some OTT platforms emerged which started showing porn in the form of web series. Both the Supreme Court and Delhi High Court say that OTT regulation is necessary. === OTT regulation === On 25 Feb 2021, Indian govt introduced self-regulation rules for OTT platforms to stop obscene content and abusive language. On 19 March 2023, I&B minister Anurag Thakur said that self regulation does not mean that OTT should show obscenity and nudity. On 15 April 2023, I&B Secretary Apurva Chandra has said because of the government's soft-touch regulations on OTT industry have led to the creation of content that is undesirable and vulgar. On 26 April 2023, MIB India said that if nudity and obscenity is seen on any OTT platform, strict action will be taken against it. On 16 May 2023, Don't show obscene content, parliamentary panel told to Netflix and Amazon Prime Video. On 20 June 2023, the government told Netflix, Disney+ Hotstar and all other streaming services that their content should be independently reviewed for obscenity and violence before being shown online. On 27 June 2023, DPCGC took punitive action against Ullu for streaming obscene content and asked them to remove all their explicit shows or remove all adult scenes within 15 days. On 18 July 2023, Anarug Thakur said in a meeting with all OTT stakeholders that demeaning Indian culture will not be tolerated. OTT can't show vulgarity and nudity in the garb of 'creative expression'.The cited sources do not mention vulgarity - they say this was about demeaning Indian culture/society. On 22 August 2023, Indian government assured that it will bring rules and regulation to regulate vulgar and obscene content on social media and OTT platforms. On 10 November 2023, MIB India introduces the 'Broadcasting Service Regulation Bill', which included Programme code with Content Evaluation Committee(CEC) for every OTT platforms. Currently public consultation is ongoing till 15 January 2024. The draft bill mandates that all OTT streaming platforms can only broadcast those web series or content, which will be duly certified by Content Evaluation Committee(CEC). On 14 March 2024, the Ministry of Information and Broadcasting banned over 18 OTT apps from Google play store and suspended all of their 57 social media accounts, as well as closed nineteen streaming websites. The banned platforms were MoodX, Prime Play, Hunters, Besharams, Rabbit movies, Voovi, Fugi, Mojflix, Chikooflix, Nuefliks, Xtramood, NeonX VIP, X Prime, Tri Flicks, Uncut Adda, Dreams Films, Hot Shots VIP, and Yessma. On 25 July 2025, the Ministry of Information and Broadcasting banned from 25 OTT apps from Google play store and suspended all of their 40 social media accounts, as well as 26 closed streaming websites. The banned platforms were include ALTT, Ullu, Big Shots App, Desiflix, Boomex, NeonX VIP, Navarasa Lite, Gulab App, Kangan App, Bull App, ShowHit, Jalva App, Wow Entertainment, Look Entertainment, Hitprime, Fugi, Feneo, ShowX, Sol Talkies, Adda TV, HotX VIP, Hulchul App, MoodX, Triflicks, and Mojflix. On 24 February 2026, the Ministry of Information and Broadcasting banned from 5 OTT apps from Google play store and suspended all of their 5 social media accounts, as well as 5 closed streaming websites. The banned platforms were include Feel App, Digi Movieplex, Jugnu App, MoodX VIP, and Koyal Playpro. === Legal action === Currently OTT is regulated under the IT Rules 2021, which clearly stated that 'No content that is prohibited by law at the time being force can be Publishing or transmitted'. MIB has continuously taking action

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  Solid-state electronics

  Solid-state electronics are semiconductor electronics: electronic equipment that use semiconductor devices such as transistors, diodes and integrated circuits (ICs). The term is also used as an adjective for devices in which semiconductor electronics that have no moving parts replace devices with moving parts, such as the solid-state relay, in which transistor switches are used in place of a moving-arm electromechanical relay, or the solid-state drive (SSD), a type of semiconductor memory used in computers to replace hard disk drives, which store data on rotating disks. == History == The term solid-state became popular at the beginning of the semiconductor era in the 1960s to distinguish this new technology. A semiconductor device works by controlling an electric current consisting of electrons or holes moving within a solid crystalline piece of semiconducting material such as silicon, while the thermionic vacuum tubes it replaced worked by controlling a current of electrons or ions in a vacuum within a sealed tube. Although the first solid-state electronic device was the cat's whisker detector, a crude semiconductor diode invented around 1904, solid-state electronics started with the invention of the transistor in 1947. Before that, all electronic equipment used vacuum tubes, because vacuum tubes were the only electronic components that could amplify—an essential capability in all electronics. The transistor, which was invented by John Bardeen and Walter Houser Brattain while working under William Shockley at Bell Laboratories in 1947, could also amplify, and replaced vacuum tubes. The first transistor hi-fi system was developed by engineers at GE and demonstrated at the University of Philadelphia in 1955. In terms of commercial production, The Fisher TR-1 was the first "all transistor" preamplifier, which became available mid-1956. In 1961, a company named Transis-tronics released a solid-state amplifier, the TEC S-15. The replacement of bulky, fragile, energy-hungry vacuum tubes by transistors in the 1960s and 1970s created a revolution not just in technology but in people's habits, making possible the first truly portable consumer electronics such as the transistor radio, cassette tape player, walkie-talkie and quartz watch, as well as the first practical computers and mobile phones. Other examples of solid state electronic devices are the microprocessor chip, LED lamp, solar cell, charge coupled device (CCD) image sensor used in cameras, and semiconductor laser. Also during the 1960s and 1970s, television set manufacturers switched from vacuum tubes to semiconductors, and advertised sets as "100% solid state" even though the cathode-ray tube (CRT) was still a vacuum tube. It meant only the chassis was 100% solid-state, not including the CRT. Early advertisements spelled out this distinction, but later advertisements assumed the audience had already been educated about it and shortened it to just "100% solid state". LED displays can be said to be truly 100% solid-state.

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  ShowScoop

  ShowScoop is a website and mobile app platform on which users can rate and review artists, concerts, and music festivals that they have seen/attended. The reviews and ratings are designed to be informative of how well such performances are live. This helps concert-goers decide which live music events they want to attend. == History == ShowScoop was founded in August 2012 by Micah Smurthwaite and is based out of San Diego, CA. In February 2013, ShowScoop launched its mobile app at the SF Music Tech Summit. The application is currently available on the iPhone, with plans to expand into the Android market in the future. == Services == ShowScoop uses crowdsourcing to provide accurate ratings of live concert experiences. In addition to viewing ratings, users are encouraged to rate and review concerts they have attended. The ShowScoop database includes nearly one million artists and over 2.5 million live music events. ShowScoop users can rate artists on four aspects of the performance: stage presence, crowd interaction, sound quality, and visual effects. The rating system uses an ascending scale from one to five in each of the aspects, with five being the highest score. In addition to the quantitative ratings, ShowScoop users are also free to write qualitative reviews in a provided comment section. This allows users to explain their ratings and add further insight or opinion. ShowScoop incorporates several facets of social media into its services. Users can create a user profile to share limited personal information and store their ratings and reviews. Users are also given the option of sharing their evaluations with their social networks on Facebook and Twitter. Users can "like" reviews, follow artists, and follow other ShowScoop users. The mobile app allows users to take photos, apply filters, and share the final image in conjunction with reviews and through Instagram. == Road Crew == ShowScoop's "Road Crew" is a group made up of top contributors within the ShowScoop community. The Road Crew assists in curating artist pages, assuring information quality and accuracy. In return, members of the Road Crew are given incentives, including free tickets to concerts and personal invitations to exclusive shows. Applicants to the Road Crew are judged on the number and quality of their reviews, the photos and videos they have posted, and their general engagement with the ShowScoop community in following and liking users and reviews.

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  RR Media

  RR Media was a NASDAQ listed provider of global digital media services to the broadcast industry and content owners. Its services can be divided into four main groups: global content distribution network (satellite, fiber and the internet); content management & playout; sports, news & live events; and online video services. The company was rebranded to RR Media from RRsat in September 2014. In February 2016, it was announced that, subject to regulatory approvals, RR Media was to be acquired by SES, based in Betzdorf, Luxembourg, and merged with SES subsidiary company, SES Platform Services a media services provider for television broadcasters, production companies and platform operators, based in Unterföhring near Munich, Germany. In July 2016, the merged company was named MX1. == Digital media services == Global content distribution services RR Media's global distribution network uses a combination of satellite, fiber and the internet. The network includes satellite downlink and uplink; fiber connectivity to digital media hubs; connectivity to TV service providers; and internet-based content delivery. RR Media's network delivers live television channels, streaming media and Video on demand (VOD) content in all formats including Standard-definition television (SD), High-definition television (HD), 4K resolution (4K) & 3D television (3D). End-to-end content management & playout services RR Media manages, prepares and plays out content from its media centers. Services include: content preparation (digitization, localization, conversion, ingest, multiple formatting, editing, restoration); content management (digital asset management, media ingest and library, streamlined workflows, metadata curation, Video on demand (VOD) delivery) and playout, channel creation, playlist management, advertising insertion/management, graphics, titles & overlay, live events operations). RR Media also creates branded or white label product television channels using live and archived materials. Sports, news & live events RR Media delivers live sports and event content for sports rights holders, broadcasters and news channels. Services include: live production (Outside broadcasting vans, Satellite news gathering (SNG), studios), global live distribution, sports content preparation and content management, playout and origination.RR Media provides downlink, uplink, simultaneous translation, turnaround and live production services for sports events like football, basketball, tennis and golf, news and entertainment channels. Online video services RR Media converts existing and archive content into programs, channels and other digital assets, and converges broadcast and internet delivery. Services include converged media (preparing content for broadcast or online use) Content Management Systems (CMS), VOD services, branded platforms, multi-screen delivery, web video portals and viewer measurement tools (using digital analytics). == Media centers == RR Media's media centers are based in Hawley, PA (USA), Emeq Ha’Ela (Israel) Bucharest (Romania), with another facility opened in London, (UK) in June 2015. An additional facility in Miami, FL United States was announced in April 2016. The centers provide RR Media's services, including content preparation, management, online video, live content and distribution, and 24/7 service and support. == Awards == In November 2014, RR Media won the award for Achievement in Legacy Content at the 2014 TVB Europe awards in London, in recognition for its work with British Pathe and the restoration for YouTube. In February 2014, the World Teleport Association named Avi Cohen, CEO of RR Media (formerly RRsat), as its 2014 Teleport Executive of the Year. In 2009, the World Teleport Association awarded RR Media (then RRsat) the Independent Teleport Operator of the Year award for excellence. == History == RR Media (as RRsat) was established in 1981 as a communications provider. The company was founded by David Rivel, an electronics, computers and communications engineer. Rivel is CEO of the company for 31 years and from 2012 a Member of RR Media's board of directors. Under management of Rivel RRsat Communications Network Ltd. went public on 2006-11-01 - NASDAQ:RRST In 2014, the Company rebranded from RRsat Global Communications Network to RR Media. The rebrand was launched at the International Broadcasting Convention (IBC) Show in Amsterdam. In 2015, RR Media announced its NASDAQ stock ticker symbol change to RRM. == Acquisitions == In April 2015, RR Media acquired Eastern Space Systems (ESS) in Romania, a privately held provider of content management and content distribution services and related consulting services. In June 2015, RR Media acquired Satlink Communications as part of strategy to increase scale and expand its global content distribution network and content management footprint, strengthening its customer mix and leverage media industry expertise.

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  Vacuum tube characteristics

  Vacuum tube characteristics (also called tube curves, valve characteristics or valve curves) describes the electrical relationships between electrode voltages and currents in a vacuum tube. These relationships are commonly presented as characteristic curves in tube manuals and engineering references. The curves typically show plate current versus plate voltage for several fixed control-grid voltages, showing how current varies with electrode potentials under controlled conditions. Designers use them to select operating points, determine voltage gain, estimate output power, and construct graphical load-line analyses. The use of characteristic curves as an engineering tool for analyzing vacuum-tube operation was established in the 1910s, notably in work by Edwin Howard Armstrong. Examples of such curves appear in early tube manuals and textbooks and form the basis of classical vacuum-tube circuit design. Different types of vacuum tubes are characterized using plots appropriate to their electrode structure and intended use. Two-electrode devices such as diodes are described primarily by the relation between plate voltage and plate current. Amplifying tubes containing control grids, such as triodes, tetrodes, pentodes, and beam tetrodes, are represented by families of curves measured for different grid voltages. From these families additional parameters such as amplification factor (μ), transconductance (gm), and plate resistance (rp) may be obtained. Although these plots are used primarily for circuit design, their shapes arise from the underlying physics of electron flow in vacuum tubes. The physical principles responsible for the observed characteristics are discussed in later sections. == 3/2 power law == In high-vacuum thermionic diodes operating under normal conditions, plate current increases nonlinearly with plate voltage. Over the space-charge-limited region, the current is well approximated by the three-halves power relation I p = P ⋅ V p 3 / 2 {\displaystyle I_{p}=P\cdot V_{p}^{3/2}} where P {\displaystyle P} is the perveance of the tube. Perveance is determined primarily by electrode geometry, including cathode area and cathode-to-plate spacing. It provides a practical measure of current-producing capability and is often used in tube manuals in place of a complete family of plate-characteristic curves. == Signal diode characterization == For small-signal diodes, tube manuals typically publish a single static anode characteristic showing anode current (Ia) as a function of anode voltage (Va), measured with the heater operating at its rated voltage. Because the diode contains no control grid, only one such I–V curve is required. The low-voltage portion of the curve is particularly important in detector service, where the nonlinear curvature of the current–voltage relation allows a small alternating signal to produce a net direct-current output, resulting in rectification. In addition to the static characteristic, tube manuals specify heater ratings, maximum plate voltage, permissible average current, and interelectrode capacitance. These parameters define the allowable operating region and high-frequency behavior. Another typical data sheet for a diode is for the Philips EB91 double diode. This book includes curves of the diode response in use as a detector. The output voltage is non-zero for an input voltage of 0 due to the Edison effect. == Rectifier characterization == Vacuum-tube rectifiers intended for power-supply service are specified differently from signal diodes. Their data emphasize heater requirements, peak inverse voltage, maximum peak plate current, permissible DC output current for various filter configurations, and regulation characteristics. Rectifier tubes exhibit nonlinear voltage drop that increases with current. For limited operating ranges this behavior may be represented by an equivalent or effective series resistance corresponding to the local slope of the plate characteristic (dynamic plate resistance, dV/dI). Diode voltages can be determied by use of a graphical aide. In capacitor-input supplies, conduction occurs in pulses near the peaks of the AC waveform, producing peak currents substantially greater than the average DC load current. Data sheets therefore specify maximum peak plate current and permissible filter capacitance in addition to average DC ratings. Under varying load conditions, the supply voltage changes in accordance with the rectifier's nonlinear characteristic and effective impedance. == Triode characterization == === Early use === The systematic use of characteristic curves to explain and quantify vacuum-tube amplification was introduced by Edwin Howard Armstrong in 1914. Using measured plate voltage-current curves, Armstrong demonstrated the mechanism of triode amplification and clarified the operation of grid-leak detection. ==== Plate and transfer characteristics ==== Triode data sheets present families of plate characteristics showing plate current I p {\displaystyle I_{p}} as a function of plate voltage E p {\displaystyle E_{p}} for several fixed grid voltages E g {\displaystyle E_{g}} . From these curves the operating point, voltage gain, and load-line behavior may be determined graphically. In normal operation, plate current depends on both grid and plate voltage. Classical analysis shows that the characteristics for different grid voltages are similar in form and differ primarily by horizontal displacement. In triodes, plate current may be approximated by I p = k ( E g + E p μ ) 3 / 2 {\displaystyle I_{p}=k\left(E_{g}+{\frac {E_{p}}{\mu }}\right)^{3/2}} where E g {\displaystyle E_{g}} is the grid voltage, E p {\displaystyle E_{p}} the plate voltage, μ {\displaystyle \mu } the amplification factor, and k {\displaystyle k} a constant determined by the tube geometry.. The amplification factor μ represents the relative effectiveness of grid voltage compared with plate voltage in controlling current. It is fundamentally determined by structural dimensions, particularly grid-to-cathode spacing relative to plate-to-cathode spacing. ==== Small-signal parameters ==== Triodes are commonly characterized by three interrelated small-signal parameters: Amplification factor ( μ {\displaystyle \mu } ) — the change in plate voltage divided by the change in grid voltage at constant plate current: μ = ( ∂ E p ∂ E g ) I p {\displaystyle \mu =\left({\frac {\partial E_{p}}{\partial E_{g}}}\right)_{I_{p}}} Transconductance ( g m {\displaystyle g_{m}} ) — the change in plate current divided by the change in grid voltage at constant plate voltage: g m = ( ∂ I p ∂ E g ) E p {\displaystyle g_{m}=\left({\frac {\partial I_{p}}{\partial E_{g}}}\right)_{E_{p}}} Plate resistance ( r p {\displaystyle r_{p}} ) — the change in plate voltage divided by the change in plate current at constant grid voltage: r p = ( ∂ E p ∂ I p ) E g {\displaystyle r_{p}=\left({\frac {\partial E_{p}}{\partial I_{p}}}\right)_{E_{g}}} These parameters are related by μ = g m r p {\displaystyle \mu =g_{m}r_{p}} as shown in classical tube theory treatments. These parameters are obtained either from slopes of the characteristic curves or from tabulated operating-point data. ==== Comparison of ECC81, ECC82, and ECC83 ==== The ECC81, ECC82, and ECC83 (also known respectively as 12AT7, 12AU7, and 12AX7) are closely related dual triodes widely used in small-signal amplifier stages. Although similar in construction and envelope size, they differ significantly in electrical parameters due to differences in electrode spacing and grid structure. (Data representative of manufacturer specifications.) The ECC83 exhibits high μ {\displaystyle \mu } and high plate resistance, producing large voltage gain but relatively low current drive capability. The ECC82 has lower μ {\displaystyle \mu } and lower plate resistance, allowing greater current delivery and reduced voltage gain. The ECC81 occupies an intermediate position with comparatively high transconductance and moderate amplification factor. These differences arise primarily from variations in grid pitch, cathode area, and electrode spacing, which determine perveance and amplification factor. Although the external envelope is similar, the internal geometry governs the characteristic curves and small-signal parameters. == Tetrode (screen-grid) characterization == The screen-grid tube (tetrode) was developed primarily to reduce the electrostatic coupling between plate and control grid that limited gain and stability in radio-frequency triode amplifiers. In triodes, the grid–plate capacitance provides feedback from plate to grid, restricting obtainable gain and often requiring neutralization circuits such as those used in neutrodyne receivers. By inserting a positively biased screen grid between control grid and plate, this capacitive coupling is greatly reduced, permitting higher stable gain at radio frequencies. The screen grid, also known as the shield grid or grid 2 (to distinguish it from t

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  Hashtag

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

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  Adversarial machine learning

  Adversarial machine learning is the study of the attacks on machine learning algorithms, and of the defenses against such attacks. Machine learning techniques are mostly designed to work on specific problem sets, under the assumption that the training and test data are generated from the same statistical distribution (IID). However, this assumption is often violated in practical high-stake applications, where users may intentionally supply fabricated data that violates the statistical assumption. Most common attacks in adversarial machine learning include evasion attacks, data poisoning attacks, Byzantine attacks and model extraction. == History == At the MIT Spam Conference in January 2004, John Graham-Cumming showed that a machine-learning spam filter could be used to defeat another machine-learning spam filter by automatically learning which words to add to a spam email to get the email classified as not spam. In 2004, Nilesh Dalvi and others noted that linear classifiers used in spam filters could be defeated by simple "evasion attacks" as spammers inserted "good words" into their spam emails. (Around 2007, some spammers added random noise to fuzz words within "image spam" in order to defeat OCR-based filters.) In 2006, Marco Barreno and others published "Can Machine Learning Be Secure?", outlining a broad taxonomy of attacks. As late as 2013 many researchers continued to hope that non-linear classifiers (such as support vector machines and neural networks) might be robust to adversaries, until Battista Biggio and others demonstrated the first gradient-based attacks on such machine-learning models (2012–2013). In 2012, deep neural networks began to dominate computer vision problems; starting in 2014, Christian Szegedy and others demonstrated that deep neural networks could be fooled by adversaries, again using a gradient-based attack to craft adversarial perturbations. Further work would show that adversarial attacks are harder to produce in uncontrolled environments, due to the different environmental constraints that cancel out the effect of noise. For example, any small rotation or slight illumination on an adversarial image can destroy the adversariality. In addition, researchers such as Google Brain's Nick Frosst point out that it is much easier to make self-driving cars miss stop signs by physically removing the sign itself, rather than creating adversarial examples. Frosst also believes that the adversarial machine learning community incorrectly assumes models trained on a certain data distribution will also perform well on a completely different data distribution. He suggests that a new approach to machine learning should be explored, and is currently working on a unique neural network that has characteristics more similar to human perception than state-of-the-art approaches. While adversarial machine learning continues to be heavily rooted in academia, large tech companies such as Google, Microsoft, and IBM have begun curating documentation and open source code bases to allow others to concretely assess the robustness of machine learning models and minimize the risk of adversarial attacks. === Examples === Examples include attacks in spam filtering, where spam messages are obfuscated through the misspelling of "bad" words or the insertion of "good" words; attacks in computer security, such as obfuscating malware code within network packets or modifying the characteristics of a network flow to mislead intrusion detection; attacks in biometric recognition where fake biometric traits may be exploited to impersonate a legitimate user; or to compromise users' template galleries that adapt to updated traits over time. Researchers showed that by changing only one-pixel it was possible to fool deep learning algorithms. Others 3-D printed a toy turtle with a texture engineered to make Google's object detection AI classify it as a rifle regardless of the angle from which the turtle was viewed. Creating the turtle required only low-cost commercially available 3-D printing technology. A machine-tweaked image of a dog was shown to look like a cat to both computers and humans. A 2019 study reported that humans can guess how machines will classify adversarial images. Researchers discovered methods for perturbing the appearance of a stop sign such that an autonomous vehicle classified it as a merge or speed limit sign. A data poisoning filter called Nightshade was released in 2023 by researchers at the University of Chicago. It was created for use by visual artists to put on their artwork to corrupt the data set of text-to-image models, which usually scrape their data from the internet without the consent of the image creator. McAfee attacked Tesla's former Mobileye system, fooling it into driving 50 mph over the speed limit, simply by adding a two-inch strip of black tape to a speed limit sign. Adversarial patterns on glasses or clothing designed to deceive facial-recognition systems or license-plate readers, have led to a niche industry of "stealth streetwear". An adversarial attack on a neural network can allow an attacker to inject algorithms into the target system. Researchers can also create adversarial audio inputs to disguise commands to intelligent assistants in benign-seeming audio; a parallel literature explores human perception of such stimuli. Clustering algorithms are used in security applications. Malware and computer virus analysis aims to identify malware families, and to generate specific detection signatures. In the context of malware detection, researchers have proposed methods for adversarial malware generation that automatically craft binaries to evade learning-based detectors while preserving malicious functionality. Optimization-based attacks such as GAMMA use genetic algorithms to inject benign content (for example, padding or new PE sections) into Windows executables, framing evasion as a constrained optimization problem that balances misclassification success with the size of the injected payload and showing transferability to commercial antivirus products. Complementary work uses generative adversarial networks (GANs) to learn feature-space perturbations that cause malware to be classified as benign; Mal-LSGAN, for instance, replaces the standard GAN loss with a least-squares objective and modified activation functions to improve training stability and produce adversarial malware examples that substantially reduce true positive rates across multiple detectors. == Challenges in applying machine learning to security == Researchers have observed that the constraints under which machine-learning techniques function in the security domain are different from those of common benchmark domains. Security data may change over time, include mislabeled samples, or reflect adversarial behavior, which complicates evaluation and reproducibility. === Data collection issues === Security datasets vary across formats, including binaries, network traces, and log files. Studies have reported that the process of converting these sources into features can introduce bias or inconsistencies. In addition, time-based leakage can occur when related malware samples are not properly separated across training and testing splits, which may lead to overly optimistic results. === Labeling and ground truth challenges === Malware labels are often unstable because different antivirus engines may classify the same sample in conflicting ways. Ceschin et al. note that families may be renamed or reorganized over time, causing further discrepancies in ground truth and reducing the reliability of benchmarks. === Concept drift === Because malware creators continuously adapt their techniques, the statistical properties of malicious samples also change. This form of concept drift has been widely documented and may reduce model performance unless systems are updated regularly or incorporate mechanisms for incremental learning. === Feature robustness === Researchers differentiate between features that can be easily manipulated and those that are more resistant to modification. For example, simple static attributes, such as header fields, may be altered by attackers, while structural features, such as control-flow graphs, are generally more stable but computationally expensive to extract. === Class imbalance === In realistic deployment environments, the proportion of malicious samples can be extremely low, ranging from 0.01% to 2% of total data. This unbalanced distribution causes models to develop a bias towards the majority class, achieving high accuracy but failing to identify malicious samples. Prior approaches to this problem have included both data-level solutions and sequence-specific models. Methods like n-gram and Long Short-Term Memory (LSTM) networks can model sequential data, but their performance has been shown to decline significantly when malware samples are realistically proportioned in the training set, demonstrating the limitations in

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  Digital divide

  Digital divide is inequitable access to and use of digital technology, encompassing four interrelated dimensions: motivational, material, skills, and usage access. The digital divide worsens inequality in access to information and resources. According to 2026 data from the U.S. Census Bureau, a significant 'digital divide' persists, with over 15.7 million Americans lacking access to high-speed broadband. Students from low-income households often face limited access to reliable internet and digital devices, which negatively affects their educational opportunities. In the Information Age, people without access to the Internet and other technology are at a disadvantage, for they are less able to connect with others, find and apply for jobs, shop, and learn. People living in poverty, in insecure housing or who are homeless, elderly people, and those living in rural communities may have limited access to the Internet; in contrast, urban middle class people have easy access to the Internet. Another divide is between producers and consumers of Internet content, which could be a result of educational disparities. While social media use varies across age groups, a US 2010 study reported no racial divide. == History == The historical roots of the digital divide in the United States refer to the increasing gap that occurred during the early modern period between those who could and could not access the real time forms of calculation, decision-making, and visualization offered via written and printed media. "Over time, focus has shifted from binary access to differentiated use, where quality and purpose of engagement vary across socio-economic groups." Within this context, ethical discussions regarding the relationship between education and the free distribution of information were raised by thinkers such as Immanuel Kant, Jean Jacques Rousseau, and Mary Wollstonecraft (1712–1778). The latter advocated that governments should intervene to ensure that any society's economic benefits should be fairly and meaningfully distributed. Amid the Industrial Revolution in Great Britain, Rousseau's idea helped to justify poor laws that created a safety net for those who were harmed by new forms of production. Later, when telegraph and postal systems evolved, many used Rousseau's ideas to argue for full access to those services, even if it meant subsidizing hard-to-serve citizens. Thus, "universal services" referred to innovations in regulation and taxation that would allow phone services such as AT&T in the United States to serve hard-to-serve rural users. In 1996, as telecommunications companies merged with Internet companies, the Federal Communications Commission adopted Telecommunications Act of 1996 to consider regulatory strategies and taxation policies to close the digital divide. Though the term "digital divide" was coined among consumer groups that sought to tax and regulate information and communications technology (ICeT) companies to close the digital divide, the topic soon moved onto a global stage. The focus was the World Trade Organization which passed the Telecommunications Services Act, which resisted regulation of ICT companies so that they would be required to serve hard-to-serve individuals and communities. In 1999, to assuage anti-globalization forces, the WTO hosted the "Financial Solutions to Digital Divide" in Seattle, US, co-organized by Craig Warren Smith of Digital Divide Institute and Bill Gates Sr. the chairman of the Bill and Melinda Gates Foundation. It catalyzed a full-scale global movement to close the digital divide, which quickly spread to all sectors of the global economy. In 2000, US president Bill Clinton mentioned the term in the State of the Union Address. Since the early 2000s, the international community has transitioned from a focus on domestic infrastructure to a global, multi-dimensional framework for digital equity. This shift was formalized through the World Summit on the Information Society (WSIS) in Geneva (2003) and Tunis (2005), where the International Telecommunication Union (ITU) established a roadmap for bridging the Global North-South disparity as part of the Sustainable Development Goals. Academic and policy discourse has since evolved to distinguish between the first-level divide (physical access), the second-level divide (digital literacy), and the third-level divide (the ability to translate technology use into socio-economic capital). By the 2020s, critical reflections on national development emphasized that the divide is fundamentally a socio-institutional gap. Research by Tiwari, Kostenko, and Yekhanurov (2025) identifies four pillars for achieving national digital maturity which are digital governance capacity, institutional design to prevent adverse digital incorporation, infrastructure resilience, and citizen capability. This modern era is characterized by the pursuit of meaningful connectivity, a standard that requires internet access to be not only available but affordable, high-speed, and supportive of active content creation. === During the COVID-19 pandemic === At the outset of the COVID-19 pandemic, governments worldwide issued stay-at-home orders that imposed lockdowns, quarantines, restrictions, and closures. The resulting interruptions to schooling, public services, and business operations drove nearly half of the world's population into seeking alternative methods to live while in isolation. These methods included telemedicine, virtual classrooms, online shopping, technology-based social interactions and working remotely, all of which require access to high-speed or broadband internet access and digital technologies. A Pew Research Centre study reports that 90% of Americans describe the use of the Internet as "essential" during the pandemic. The accelerated use of digital technologies created a landscape where the ability, or lack thereof, to access digital spaces became a crucial factor in everyday life. According to the Pew Research Center, 59% of children from lower-income families were likely to face digital obstacles in completing school assignments. These obstacles included the use of a cellphone to complete homework, having to use public Wi-Fi because of unreliable internet service in the home and lack of access to a computer in the home. This difficulty, titled the homework gap, affects more than 30% of K-12 students living below the poverty threshold, and disproportionally affects American Indian/Alaska Native, Black, and Hispanic students. These types of interruptions or privilege gaps in education exemplify problems in the systemic marginalization of historically oppressed individuals in primary education. The pandemic exposed inequity causing discrepancies in learning. "Large-scale events such as COVID-19 intensify both access and skills gaps, underlining the need for resilient digital inclusion policies. Studies during COVID-19 reveal first-level (access) and second-level (skills) divides, with underserved students struggling with reliable internet, devices, and platform navigation ” A lack of "tech readiness", that is, confident and independent use of devices, was reported among the US elderly population; with more than 50% reporting an inadequate knowledge of devices and more than one-third reporting a lack of confidence. "Older adults often face skills and confidence barriers, illustrating later-stage divides in van Dijk’s model." Moreover, according to a UN research paper, similar results can be found across various Asian countries, with those aged over 74, reporting less confident or inconsistent use of digital devices. This aspect of the digital divide and the elderly occurred during the pandemic as healthcare providers increasingly relied upon telemedicine to manage chronic and acute health conditions. == Aspects == There are various definitions of the digital divide, all with slightly different emphasis, which is evidenced by related concepts like digital inclusion, digital participation, digital skills, media literacy, and digital accessibility.“Van Dijk’s model identifies sequential barriers—motivational, material, skills, and usage—that must be addressed to bridge the divide.” === Infrastructure === The infrastructure by which individuals, households, businesses, and communities connect to the Internet addresses the physical mediums that people use to connect to the Internet such as desktop computers, laptops, basic mobile phones or smartphones, MP3 players, gaming consoles, electronic book readers, and tablets. Traditionally, the nature of the divide has been measured in terms of the existing numbers of subscriptions and digital devices. Given the increasing number of such devices, some have concluded that the digital divide among individuals has increasingly been closing as the result of a natural and almost automatic process. Others point to persistent lower levels of connectivity among women, racial and ethnic minorities, people with lower incomes, rura

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  Cultural technology

  Cultural technology (Korean: 문화기술; Hanja: 文化技術; RR: munhwagisul) is a system used by South Korean talent agencies to promote K-pop culture throughout the world as part of the Korean Wave. The system was developed by Lee Soo-man, founder of talent agency and record company SM Entertainment. == History == === Coinage === During a speech at the Stanford Graduate School of Business in 2011, Lee said he coined the term "cultural technology" as a system about fourteen years prior, when S.M. Entertainment decided to promote its K-pop artists to all of Asia. In the late 1990s, Lee and his colleagues created a manual on cultural technology, which specified the steps needed to popularize K-pop artists outside South Korea. "The manual, which all S.M. employees are instructed to learn, explains when to bring in foreign composers, producers, and choreographers; what chord progressions to use in what country; the precise color of eyeshadow a performer should wear in a particular country; the exact hand gestures he or she should make; and the camera angles to be used in the videos (a three-hundred-and-sixty-degree group shot to open the video, followed by a montage of individual closeups)," according to The New Yorker. The term "cultural technology," apart from Lee's systemized definition, can be traced back to the lectures of Michael White, an Australian social worker, educator, and therapeutic theorist and his works Narrative Means to Therapeutic Ends (1990) and Maps of Narrative Practice (2007). Its usage may also date further back to French philosopher Michel Foucault (1977). South Korean computer scientist Kwangyun Wohn said he coined the term "culture technology" in 1994. Cultural technology has also been one of six technology initiatives of the South Korean government since 2001. In regards to cultural technology, the Korean Wave is considered one of the most successful outcomes of government support of exporting Korean entertainment products. === The Four Core Stages === The cultural technology system originally employed by SM Entertainment since the 1990s existed in four stages: Casting, Training, Producing, and Marketing/Managing. Each of these four stages were curated to help spread the Hallyu wave through the development of its artists, and are present in the strategies of many other South Korean talent agencies when creating, debuting, and marketing groups. ==== Casting ==== While the majority of K-pop idols are from South Korea, some are from Japan, China, or Thailand. Many of Korea's entertainment companies, such as SM's Global Auditions, Bighit's Hit It auditions, and YG's Next Generation, host worldwide auditions. Scouting and streetcasting are also common, with members like BTS's Jin recruited for their looks or other surface reasons. Sometimes, casting agents go to dance schools to recruit the top dancers to be trained further at the entertainment company. ==== Training ==== Idols train extensively before debut. They receive training in dance, vocal activities, presentation, and other areas that will benefit them in the industry. Oftentimes, this training will last for years at a time, and trainees are in the proverbial dungeon. Before debut, idols and groups attempt to gain fans through pre-debut activities. SM Entertainment has a system in place called SM Rookies, which is a pre-debut team that hosts concerts and releases videos that strengthen the fanbase of the group even before their first single is released. Other forms of pre-debut activities include featuring in other, more seasoned idols' videos—like Nu'est in Orange Caramel or Exo in Girls' Generation-TTS Twinkle or BTS in Jo Kwon. One particular method of pre-debut training is coupled with casting in production shows, like Sixteen and Produce 101, in which members for a final group are selected and trained. ==== Producing ==== The production of music is integral in culture technology. For cultural technology, production of music helps create differentiated content to set trends in the K-pop world—trends that vary from music to also costume, choreography, and music videos. SM in particular focuses heavily on the expansion globally. Some companies also outsource production to more internationally famed parties, like Cube Entertainment's partnership with Skrillex for 4minute's Act. 7. ==== Marketing/Managing ==== In the marketing and management stage, talent agencies seek to broaden their reach. Often, idols have potential for being actors and actresses in dramas, or perhaps hosts/permanent members of variety shows like Kim Hee-chul in Knowing Bros. This so-called omnidirectional marketing lineup ranges over lifestyle and seeks to reach many aspects of living, like music, TV, drama, entertainment, sports, and fashion. This is also where older groups find new life, like Super Junior. Companies are not complacent but experiment constantly to develop the best marketing for the best management system. Marketing also aspires to branch out to international audiences, sometimes via the implementation of variety shows. Despite being primarily in Korean, these variety shows are accessible to all due to the simplistic, easily understood nature of shows—game-oriented shows like Run BTS! or consistently subbed shows like Weekly Idol are popular in showing the fun-loving side of idols. == Evolution into New Culture Technology == In February 2016, SM hosted a press conference discussing the future of SM and its cultural technology. Lee Soo-man announced the implementation of New Culture Technology, an SM-specific system. While SM's cultural technology in the past relied on local, Korean artists like Rain and BoA, the updated model tries to embed more and more foreign singers from strategic markets into larger girl or boy bands. These imported singers are then used to promote their acts back in their respective home countries. New Culture Technology is five projects—SM Station, EDM, Digital Platforms, Rookies Entertainment, and MCN—and one experimental group, NCT. It is a convergence and expansion of SM's four core culture technologies developed and deals heavily with interaction and the desire to innovate through communication. === SM Station === SM announced their intention of creating a new song every week for 52 weeks. Through this constant output of music, they intend to stray away from conventional forms of music and show active movement in digital music market and physical album market through freely and continuously releasing music. Additionally, this SM Station will feature collaborations between artists, producers, composers, and company brands outside the SM label. The name of SM Station is both derived from the radio station and the metaphorical train station. === NCT === Neo Culture Technology (NCT) introduced the idea of "Interactive". SM company tried to connect the targeting market, customers and artist, in order to lead the K-pop culture. NCT (Neo Culture Technology) is the new artist group formed by SM that embodies the concepts of cultural technology. With the seemingly limitless combinations and groups, SM aspires to make the whole world a stage for NCT. Since 2023, there are six NCT groups, who debuted on the digital song sales: NCT U, NCT 127, NCT Dream, WayV, NCT DoJaeJung, and NCT Wish. As of October 2023, the group consists of 25 members: Johnny, Taeyong, Yuta, Kun, Doyoung, Ten, Jaehyun, Winwin, Jungwoo, Mark, Xiaojun, Hendery, Renjun, Jeno, Haechan, Jaemin, Yangyang, Chenle, Jisung, Sion, Riku, Yushi, Daeyoung, Ryo, and Sakuya. ScreaM Records ScreaM Records has been released by SM Entertainment as an EDM label since 2016 for "SM TOWN: New Culture Technology". ScreaM Records is made for "performances made to be enjoyed". It collaborates with inside and outside Korean well-known EDM DJs. ScreaM Records has first launched collaborated song "Wave" E-Mart's home electronics store, Electro Mart. "Our goal is to provide opportunities to producers who have yet to be discovered and produce world famous DJs from the Asian scene." a ScreaM Records representative said. == Three stages of globalization == According to Lee, there are three stages necessary to popularize Korean culture outside South Korea: exporting the product, collaborating with international companies to expand the product's presence abroad, and finally creating a joint venture with international companies. As part of their joint ventures with international companies, South Korean talent agencies may hire foreign composers, producers, and choreographers to ensure K-pop songs feel "local" to foreign countries.

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