AI Chat Free Online

AI Chat Free Online — independent reviews, comparisons, pricing and step-by-step guides on Aizhi.

• 

  BabyCenter

  BabyCenter is an online media company based in San Francisco, New York City, Chicago, and Los Angeles that provides information on conception, pregnancy, birth, and early childhood development for parents and expecting parents. BabyCenter operates 8 country and region specific properties including websites, apps, emails, print publications, and an online community where parents can connect on a variety of topics. The visitors of website and the users of the app can sign up for free weekly email newsletters that guide them through pregnancy and their child's development. In addition to publishing detailed, medically reviewed information about pregnancy and parenting, BabyCenter, under its Mission Motherhood initiative, ran numerous social programs and has participated in public health initiatives in partnership with hospitals, healthcare agencies, nonprofits, NGOs, and government agencies to provide pregnancy and parenting advice. It also annually publishes the most popular baby names. BabyCenter LLC is part of the Everyday Health Group, a division of Ziff Davis. == History == BabyCenter was founded in October 1997 by Stanford University MBA graduates Matt Glickman and Mark Selcow, who recognized a need for information about pregnancy and parenting on the internet. BabyCenter was initially funded through $13.5 million in startup capital funding from venture capital firms, including Bessemer Venture Partners, Intel, and Trinity Ventures. The funds were used to open the BabyCenter Store in October 1998. In the early years of its operation, BabyCenter offered multiple resources and services for parents, including a website that provided medically reviewed information and guidance to new and expectant parents on such topics as fertility, labor, and childcare; a weekly email for pregnant women tailored to their week of pregnancy (based on their pregnancy due date); and community groups and chat rooms for pregnant couples and parents to discuss pregnancy and child-rearing strategies. The site grew quickly, and by early 1999 had 175 employees and an annual revenue of $35 million. In April of that year, the two founders sold BabyCenter to another website, eToys.com, for $190 million in stock. Twenty-three months later, in 2001, shortly before declaring bankruptcy, eToys sold the site to Johnson & Johnson for $10 million. During the eToys ownership, BabyCenter launched its first international E-commerce site in the UK during the spring of 2000. Starting in 2005, BabyCenter launched an expansion plan, extending its global network to Australia, Canada and other countries, staffing each outpost with local editors. In 2007, BabyCenter debuted a Mandarin-language site in China, initiated operations in India, launched a Spanish language website, and introduced its first mobile site. BabyCenter released My Pregnancy Today, its first mobile app, to Apple's App Store in August 2010 and to the Android market in April 2011. The app provided daily information, nutrition tips, advice relevant to the user's week of pregnancy, and 3-D animated videos showcasing a baby's development in utero. The My Pregnancy app was joined by a My Baby Today app in October 2011. In 2015, BabyCenter released Mom Feed, its first mobile app for parents of toddlers and older children (ages 1 to 8). Mom Feed offered personalized, stage-based information as well as content from the BabyCenter Community and Blog in a real-time stream. In 2016, BabyCenter launched its web-based Baby Names Finder. In 2018, Mom Feed was discontinued and BabyCenter replaced that experience with a separate Child Health content area on its website. Also in 2018, BabyCenter launched its mobile baby name generator, the Baby Names app, which, like the web-based Baby Names Finder, leverages data from hundreds of thousands of parents that culminates in its annual most popular Baby Names Report. In 2019, Johnson & Johnson sold Baby Center to Everyday Health Group, a division of New York-based parent company of Ziff Davis, Inc. Neither side disclosed terms of the deal. == Popular research == BabyCenter's most popular baby names is released annually and often cited by the media. In March 2024, BabyCenter did a review of the app Temu and said that the website has found products that have been recalled, could be counterfeit or circumvent U.S. safety standards and features that are important in preventing issues like choking. In 2025, BabyCenter released a report about the cost of raising a newborn baby in the first year. == Content and products == === Websites === BabyCenter has 8 country and region-specific websites around the world, including sites for the United States, Canada, Australia, Brazil, India, Germany, the United Kingdom, and Latin America. Users can find parenting and pregnancy advice in seven languages: English, Spanish, Portuguese, Arabic, French, German, and Hindi BabyCenter content for each country- or region-specific site is written by an editorial team based in that country or region. Medical and health content for each site is reviewed by a medical advisory board based there and adheres to that country or region's medical standards. For example, the U.S. site works with and follows the recommendations of such U.S. medical authorities as the American Academy of Pediatrics, the American Congress of Obstetrics & Gynecology and the Society for Maternal-Fetal Medicine. BabyCenter regularly conducts research and provides thought leadership on pregnancy and parenting topics, popularly cited by major media outlets including The Wall Street Journal, Forbes, The Washington Post, BuzzFeed, Insider, MarketWatch, Axios. === Community, blogs and social === From its earliest days, BabyCenter has had a community area that allows people to join a group of parents with children born in the same month, known as a Birth Club. BabyCenter launched a blog called Momformation in 2007. Eventually, the name was changed to BabyCenter Blog. In April 2021, the BabyCenter Community was identified in a research article within the journal PLOS Computational Biology as facilitating "unobstructed communication" between parents, which avoids the "strong echo chamber phenomena" that can foster and perpetuate vaccine misinformation. === My Pregnancy and Baby Today App === The app is available in six languages, although not all features are supported for every market. Initially the apps only featured pregnancy articles that could be found on the BabyCenter website, but over the years the feature set has expanded to include a growing list of app-specific tools such as weekly fetal development information, a kick tracker, a birth plan worksheet, a contraction timer, a baby growth tracker, a photo journal for pregnant women to record their pregnancy bellies, and a photo journal for documenting a baby's first year. === Mission Motherhood™ === BabyCenter was a cofounder of the Mobile Alliance for Maternal Action (MAMA), a public-private partnership between USAID, Johnson & Johnson, the UN Foundation, and BabyCenter from 2011 to-to 2015. The MAMA program sparked the creation of MomConnect, an initiative of the South African Department of Health for which BabyCenter developed SMS messages with health information about pregnancy and a child's first year of life. BabyCenter helped develop similar messages for mMitra, a voice messaging program in India. A research article in the Maternal and Child Health Journal stated the mMitra program offered strong evidence "that tailored mobile phone voice messages can improve key infant care knowledge and practices that lead to improved infant health outcomes in low-resource settings. BabyCenter's Mission Motherhood Messages were available to qualifying organizations on the BabyCenter website. BabyCenter contributed websites for Free Basics. These websites featured age and stage-based pregnancy and baby articles targeted to low-income, lower-education women who would not otherwise have access to health information. Content developed for this program was also used to support a UNICEF SMS program during the 2016 Zika outbreak. == Awards and recognition == In 1998, BabyCenter won a Webby Award for Best Home Site. Since then, it has been nominated for a Webby Award 19 times and won either a Webby or a People's Choice Webby Award 12 times – including a People's Voice win in 2021 for Lifestyle websites and mobile sites. In 2002, it won Service Journalism award from Online Journalism Awards (OJA). In 2015, BabyCenter won five Digital Health Awards for content about autism in children. In 2016, BabyCenter won seven Digital Health Awards: four for videos about the aches and pains of pregnancy, baby sleep, and the walking milestone in child development; two for articles about baby sleep training and sleep apnea in babies; and one for the BabyCenter mobile app My Pregnancy & Baby Today. In 2021, Forbes Health chose My Pregnancy & Baby Today as the best pregnancy app of 2021, and Women's Health identified it

  Read more →
• 

  Algorithmic amplification

  Algorithmic amplification is the process by which automated ranking and recommendation systems on digital platforms increase the visibility of certain content beyond its initial audience. Major platforms including Facebook, YouTube, TikTok, and X (formerly Twitter) use such systems to determine what appears in users' feeds and search results. The term is used in research on social media and digital media regulation to describe how platform design choices influence the distribution of online information. Unlike chronological feeds, algorithmic systems evaluate content using signals such as engagement rates, viewing duration, and predicted relevance to individual users. Content that performs strongly on these metrics may be promoted to progressively larger audiences through feeds, search rankings, or autoplay systems. The process is distinct from content moderation, which involves removing, labelling, or restricting content under platform rules, although the two can interact in practice. The concept is closely connected to the attention economy. Research has linked algorithmic amplification to the spread of misinformation and the circulation of political content, as well as to effects on young users' mental health. The scale and direction of those effects remain debated, in part because independent researchers have limited access to the internal workings of platform recommendation systems. Governments in the European Union, United Kingdom, United States, and China have pursued differing regulatory approaches to recommendation algorithms. The EU's Digital Services Act and the UK's Online Safety Act 2023 impose obligations on large platforms related to recommendation system transparency and risk, while China became the first country to enact binding legislation specifically targeting such systems. Internal documents and whistleblower testimony reported by the BBC in 2026 described how competitive pressure between Meta and TikTok led to trade-offs between engagement and user safety in the design of their recommendation systems. == Terminology == The term algorithmic amplification is used in media studies, platform governance scholarship and regulatory literature to describe how automated systems influence the distribution of content beyond what organic user sharing alone would produce. It is distinct from viral spread, which refers primarily to user-driven sharing behaviour, and from algorithmic bias, which describes systematic errors or unfairness in algorithmic outputs. The related term algorithmic curation is used for the broader process of selecting and ordering content, of which amplification is one possible outcome. The phrase also appears in regulatory and legislative discussion of recommendation systems. The European Union's Digital Services Act (DSA) identifies recommendation systems as a potential source of systemic risk, and the term appears frequently in academic and policy commentary on the regulation. In the United States, proposals including the Filter Bubble Transparency Act and the Kids Online Safety Act (KOSA) have used it to frame requirements around recommendation system transparency. In the United Kingdom, the House of Commons Science, Innovation and Technology Committee used the term in a 2025 report on how recommendation algorithms contributed to the spread of misinformation during the 2024 Southport riots. A Joint Declaration on AI and Freedom of Expression adopted in October 2025 by four international freedom of expression mandate holders, including the UN Special Rapporteur on Freedom of Opinion and Expression and the OSCE Representative on Freedom of the Media, stated that recommender systems and other AI-powered curation tools exert "a large hidden influence and gatekeeper role" over what information people access and consume. == Background == Early internet platforms typically displayed content in reverse-chronological order or through keyword-based search systems. Although the term is most often applied to social media, the underlying logic predates social media itself. A 2021 overview traced the origins of modern recommendation systems to the early 1990s, when they were first used experimentally for personal email and information filtering. The 1992 Tapestry mail system and the 1994 GroupLens news filtering system were early milestones before recommendation systems spread into e-commerce and other online services. As user bases and content volumes grew during the 2000s, major platforms including Google, YouTube, and Facebook developed machine-learning systems to personalise content delivery and prioritise material predicted to generate engagement. Facebook introduced its News Feed in 2006, which gradually shifted from chronological presentation towards algorithmically ranked content. YouTube altered its recommendation system in 2012 to prioritise watch time rather than clicks, a change the platform said was prompted by concerns that click-based metrics encouraged misleading thumbnails and low-quality videos. TikTok, launched internationally in 2018, adopted a model in which its primary content surface, the For You feed, is driven almost entirely by algorithmic recommendation rather than by a user's social graph. An internal document obtained by The New York Times in 2021 showed that the platform's algorithm optimised for retention and time spent, using signals such as watch duration, replays, likes, and comments to score and rank videos. Algorithmic recommendation also became central to platforms outside social media. Spotify's personalised features, including Discover Weekly, Release Radar, and Home recommendations, use behavioural signals and inferred "taste profiles" to surface tracks and artists beyond a listener's existing library. An ethnographic study of music curators at streaming platforms described this blend of algorithmic and human editorial selection as an "algo-torial" model of gatekeeping. Amazon adopted item-based collaborative filtering for product recommendations in 1998, and its recommendation engine has been described as one of the earliest large-scale deployments of recommendation technology in e-commerce. The same dynamics operate on adult content platforms. Law professor Amy Adler has argued that from 2007 onwards the pornography industry migrated to algorithm-driven streaming platforms, most of which are controlled by a single near-monopoly company, Aylo (formerly MindGeek). These platforms use algorithmic search engines, suggestions, rigid categorisation of content, and AI-driven search term optimisation in ways that produce the same distorting effects found on mainstream speech platforms, including filter bubbles, feedback loops, and the tendency of algorithmic recommendations to alter individual preferences. == Mechanisms == Recommendation systems commonly combine collaborative filtering, which predicts a user's preferences from the behaviour of similar users, with machine-learning models that predict which content a user is likely to engage with from their prior activity. In a common two-stage design, a platform first generates a set of candidate items from a large content pool and then ranks them using a scoring model with objectives such as predicted engagement or user satisfaction. Small changes in ranking criteria can shift exposure at scale, particularly when applied repeatedly across multiple browsing sessions. These systems typically rely on signals including engagement rates, viewing duration, click-through rates, and network relationships between users. Modern recommendation pipelines continuously update predictions as new behavioural data arrives, allowing platforms to adjust rankings in near real time. Users' revealed preferences, expressed through behaviour such as clicks and viewing time, do not always align with their stated preferences, expressed through explicit feedback such as surveys or content controls. Popularity signals can create feedback dynamics in which early engagement increases the likelihood that content will be shown to additional users. Experimental research on online cultural markets has demonstrated how such feedback processes can produce unequal visibility outcomes even when initial differences in content quality are small. == Beneficial and public-interest uses == Recommendation systems can help users navigate large volumes of content by surfacing material predicted to match their interests or needs, which can improve discoverability on platforms with large content libraries. In public health communication, platforms can help health authorities distribute timely information at scale, though the same recommendation systems also risk amplifying misinformation alongside official guidance. Sociologist Zeynep Tufekci has argued that the shift from independent blogs to large centralised platforms transferred gatekeeping power from traditional media to corporate algorithms. In the case of the Egyptian uprising of 2011, she noted that ordinary users

  Read more →
• 

  Infone

  Infone was a service launched by Metro One Telecommunications in 2003. The service was discontinued effective December 14, 2005. == How it worked == Infone included directory assistance and other services via a toll-free phone number. A user could call 888-411-1111 to request directory assistance, directions, traffic information, movie times, call completion, dinner reservation assistance and other services. Infone provided a number of innovative 411 'concierge'-like services, including movie listings from a live operator, and offered a feature where they could provide information from a linked Microsoft Outlook calendar when set up in advance. For a period of time they advertised heavily on U.S. television, featuring ads with then Governor of Minnesota Jesse Ventura, emphasizing their use of all U.S. based operators. The price offered was $0.89 per call up to 15 minutes (for use when the operator connects you to the requested number, as well as for additional information requests afterwards), with $0.05 for each additional minute, making Infone also a competitively priced long-distance service. New users received 5–10 free calls. Infone identified a registered user (along with billing information; the service was only payable by credit card) by caller ID (numbers were registered on signing up) and by an advanced voiceprint recognition system (VPRS) from SpeechWorks that identified the user when the user called from an unregistered telephone number (or no caller ID) through the use of a personal phrase spoken by the user (e.g., "Hello Infone!") after the welcome tone.

  Read more →
• 

  Mini-STX

  Mini-STX (mSTX, Mini Socket Technology EXtended, originally "Intel 5x5") is a computer motherboard form factor that was released by Intel in 2015 (as "Intel 5x5"). These motherboards measure 147mm by 140mm (5.8" x 5.5"), making them larger than "4x4" NUC (102x102mm / 4.01" x 4.01" inches) and Nano-ITX (120x120mm / 4.7" x 4.7") boards, but notably smaller than the more common Mini-ITX (170x170mm / 6.7" x 6.7") boards. Unlike these standards, which use a square shape, the Mini-STX form factor is 7mm longer from front-to-rear, making it slightly rectangular. == Mini-STX design elements == The Mini-STX design suggests (but does not require) support for: Socketed processors (e.g. LGA or PGA CPUs) Onboard power regulation circuitry, enabling direct DC power input IO ports embedded on the front and rear of the motherboard (akin to NUC, but unlike typical motherboards which often use headers instead to connect built-in ports on enclosures) == Adoption by manufacturers == This motherboard form factor is still not in particularly common use with consumer-PC manufacturers, although there are a few offerings: ASRock offers both DeskMini kits (that use mini-STX boards) and standalone motherboards, Asus offer VivoMini kits (that use mini-STX boards) and standalone motherboards, Gigabyte offers a few motherboards, and industrial PC suppliers (e.g. Kontron, Iesy, ASRock Industrial) also provide some options for mini-STX equipment. == Derivatives == ASRock developed a derivative of mini-STX, dubbed micro-STX, for their 'DeskMini GTX/RX' small form-factor PCs and industrial motherboards. Micro-STX adds an MXM slot which allows the use of special PCI Express expansion cards, including graphics or machine learning accelerators, but increases the width of the board to be extended two inches, resulting in measurements of 147 x 188 mm (5.8" x 7.4")

  Read more →
• 

  Networked Help Desk

  Networked Help Desk is an open standard initiative to provide a common API for sharing customer support tickets between separate instances of issue tracking, bug tracking, customer relationship management (CRM) and project management systems to improve customer service and reduce vendor lock-in. The initiative was created by Zendesk in June 2011 in collaboration with eight other founding member organizations including Atlassian, New Relic, OTRS, Pivotal Tracker, ServiceNow and SugarCRM. The first integration, between Zendesk and Atlassian's issue tracking product, Jira, was announced at the 2011 Atlassian Summit. By August 2011, 34 member companies had joined the initiative. A year after launching, over 50 organizations had joined. Within Zendesk instances this feature is branded as ticket sharing. == Basis == Support tools are generally built around a common paradigm that begins with a customer making a request or an incident report, these create a ticket. Each ticket has a progress status and is updated with annotations and attachments. These annotations and attachments may be visible to the customer (public), or only visible to analysts (private). Customers are notified of progress made on their ticket until it is complete. If the people necessary to complete a ticket are using separate support tools, additional overhead is introduced in maintaining the relevant information in the ticket in each tool while notifying the customer of progress made by each group in completing their ticket. For example, if a customer support issue is caused by a software bug and reported to a help desk using one system, and then the fix is documented by the developers in another, and analyzed in a customer relationship management tool, keeping the records in each system up-to-date and notifying the customer manually using a swivel chair approach is unnecessarily time-consuming and error-prone. If information is not transferred correctly, a customer may have to re-explain their problem each time their ticket is transferred. For systems with the Networked Help Desk API implemented, it is possible for several different applications related to a customer's support experience to synchronize data in one uniquely identified shared ticket. While many applications in these domains have implemented APIs that allow data to be imported, exported and modified, Network Help Desk provide a common standard for customer support information to automatically synchronize between several systems. Once implemented, two systems can quickly share tickets with just a configuration change as they both understand the same interface. Communication between two instances on a specific ticket occurs in three steps, an invitation agreement, sharing of ticket data and continued synchronization of tickets. The standard allows for "full delegation" (analysts in both systems each make public and private comments and synchronize status) as well as "partial delegation" where the instance receiving the ticket can only make private comments and status changes are not synchronized. Tickets may be shared with multiple instances. == Implementation list ==

  Read more →
• 

  Digital asset

  A digital asset is anything that exists only in digital form and comes with a distinct usage right or distinct permission for use. Data that do not possess those rights are not considered assets. Digital assets include, but are not limited to: digital documents, audio content, motion pictures, and other relevant digital data currently in circulation or stored on digital appliances, such as personal computers, laptops, portable media players, tablets, data storage devices, and telecommunication devices. This encompasses any apparatus that currently exists or will exist as technology progresses to accommodate the conception of new modalities capable of carrying digital assets. This holds true regardless of the ownership of the physical device on which the digital asset is located. == Types == Types of digital assets include, but are not limited to: software, photography, logos, illustrations, animations, audiovisual media, presentations, spreadsheets, digital paintings, word documents, electronic mails, websites, and various other digital formats with their respective metadata. The number of different types of digital assets is exponentially increasing due to the rising number of devices that leverage these assets, such as smartphones, serving as conduits for digital media. In Intel's presentation at the 'Intel Developer Forum 2013,' they introduced several new types of digital assets related to medicine, education, voting, friendships, conversations, and reputation, among others. == Digital asset management system == A digital asset management (DAM) is an integrated structure that combines software, hardware, and/or other services to manage, store, ingest, organize, and retrieve digital assets. These systems enable users to find and use content when needed. == Digital asset metadata == Metadata is data about other data. Any structured information that defines a specification of any form of data is referred to as metadata. Metadata is also a claimed relationship between two entities, often used to establish connections or associations. Librarian Lorcan Dempsey says "Think of metadata as data which removes from a user (human or machine) the need to have full advance knowledge of the existence or characteristics of things of potential interest in the environment". At first, the term metadata was used for digital data exclusively, but nowadays metadata can apply to both physical and digital data. Catalogs, inventories, registers, and other similar standardized forms of organizing, managing, and retrieving resources contain metadata. Metadata can be stored and contained directly within the file it refers to or independently from it with the help of other forms of data management such as a DAM system. The more metadata is assigned to an asset the easier it gets to categorize it, especially as the amount of information grows. The asset's value rises the more metadata it has for it becomes more accessible, easier to manage, and more complex. Structured metadata can be shared with open protocols like OAI-PMH to allow further aggregation and processing. Open data sources like institutional repositories have thus been aggregated to form large datasets and academic search engines comprising tens of millions of open access works, like BASE, CORE, and Unpaywall. == Issues == Due to a lack of either legislation or legal precedent, there is limited existing governmental control and regulation surrounding digital assets in the United States and other large economies globally. Many of the control issues relating to access and transferability are maintained by individual companies. Some consequences of this include 'What is to become of the assets once their owner is deceased?' as well as can, and, if so, how, may they be inherited. This subject was broached in a bogus story about Bruce Willis allegedly looking to sue Apple as the end user agreement prevented him from bequeathing his iTunes collection to his children. Another case of this was when a soldier died on duty and the family requested access to the Yahoo! account. When Yahoo! refused to grant access, the probate judge ordered them to give the emails to the family but Yahoo! still was not required to give access. The Music Modernization Act was passed in September 2018 by the U.S. Congress to create a new music licensing system, with the aim to help songwriters get paid more.

  Read more →
• 

  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.

  Read more →
• 

  AMiner (database)

  AMiner (formerly ArnetMiner) is a free online service used to index, search, and mine big scientific data. == Overview == AMiner (ArnetMiner) is designed to search and perform data mining operations against academic publications on the Internet, using social network analysis to identify connections between researchers, conferences, and publications. This allows it to provide services such as expert finding, geographic search, trend analysis, reviewer recommendation, association search, course search, academic performance evaluation, and topic modeling. AMiner was created as a research project in social influence analysis, social network ranking, and social network extraction. A number of peer-reviewed papers have been published arising from the development of the system. It has been in operation for more than three years, and has indexed 130,000,000 researchers and more than 265 million publications. The research was funded by the Chinese National High-tech R&D Program and the National Science Foundation of China. AMiner is commonly used in academia to identify relationships between and draw statistical correlations about research and researchers. It has attracted more than 10 million independent IP accesses from 220 countries and regions. The product has been used in Elsevier's SciVerse platform, and academic conferences such as SIGKDD, ICDM, PKDD, WSDM. == Operation == AMiner automatically extracts the researcher profile from the web. It collects and identifies the relevant pages, then uses a unified approach to extract data from the identified documents. It also extracts publications from online digital libraries using heuristic rules. It integrates the extracted researchers’ profiles and the extracted publications. It employs the researcher name as the identifier. A probabilistic framework has been proposed to deal with the name ambiguity problem in the integration. The integrated data is stored into a researcher network knowledge base (RNKB). The principal other product in the area are Google Scholar, Elsevier's Scirus, and the open source project CiteSeer. == History == It was initiated and created by professor Jie Tang from Tsinghua University, China. It was first launched in March 2006. The following provide a list of updates in the past years: March 2006, Version 0.1, Functions include researcher profiling, expert search, conference search, and publication search. The system was developed in Perl; August 2006, Version 1.0, The system was re-implemented in Java; July 2007, Version 2.0, New functions include researcher interest mining, association search, survey paper finding (unavailable now); April 2008, Version 3.0, New functions include query understanding, new GUI, and search log analysis; November 2008, Version 4.0, New functions include graph search, topic modeling, NSF/NSFC funding information extraction; April 2009, Version 5.0, New functions include Profile edition, open API service, Bole search, course search (unavailable now); December 2009, Version 6.0, New functions include academic performance evaluation, user feedback, conference analysis; May 2010, Version 7.0, New functions include name disambiguation, paper-reviewer recommendation, ArnetPage creation; March 2012, Version II, renamed as AMiner, rewrote all the codes and redesign the GUI. New functions include: geographic search, ArnetAPP platform. June 2014, Version II, renamed as AMiner, rewrote all the codes and redesign the GUI. New functions include: geographic search, ArnetAPP platform. December 2015, a completely new version got online. May 2017, professional version got online. April 2018, New functions include Trend Analysis, a deep learning based Name Disambiguation == Resources == AMiner published several datasets for academic research purpose, including Open Academic Graph, DBLP+citation (a data set augmenting citations into the DBLP data from Digital Bibliography & Library Project), Name Disambiguation, Social Tie Analysis. For more available datasets and source codes for research, please refer to.

  Read more →
• 

  Jais (language model)

  Jais is an open-source large language model launched in August 2023. Developed as a collaboration between Emirati AI company G42, the Mohamed bin Zayed University of Artificial Intelligence (MBZUAI), and US-based Cerebras Systems, Jais was designed to produce high-quality Arabic text and was also trained on English data. The model's creation was motivated by the underrepresentation of the Arabic language in the field of generative artificial intelligence. It aims to provide a more culturally and linguistically accurate model for the world's 400 million Arabic speakers. Its name is a reference to Jebel Jais, the highest mountain in the UAE. == Background and development == Jais was developed in response to the limited availability of advanced generative artificial intelligence models for the Arabic language, despite it being spoken by over 400 million people. Existing models were often trained on limited or low-quality Arabic web content, resulting in poor performance. The project represents a significant investment by the United Arab Emirates in the field of AI as part of its national strategy. The model was created through a partnership between Inception (now Core42), a subsidiary of the Abu Dhabi-based AI company G42; the Mohamed bin Zayed University of Artificial Intelligence (MBZUAI); and Cerebras Systems, a US company specializing in AI hardware. The model is named after Jebel Jais, the highest peak in the UAE. == Training == The initial version of Jais released in August 2023 had 13 billion parameters. In November 2023, Core42 released Jais 30B, an improved version with 30 billion parameters. Both models were trained on a subset of the Cerebras Condor Galaxy 1 supercomputer. The training dataset consisted of a mix of Arabic, English, and computer code. According to Timothy Baldwin, a professor of natural language processing at MBZUAI, training the model on a diverse Arabic dataset allows it to switch between dialects. == Features == Jais is designed to generate text in both English and Arabic. The project has also released instruction-tuned "Chat" variants for both the 13B and 30B models, which are specifically optimized for conversational applications. Additional functionality for working with images, graphs, and tabular data is planned for future releases.

  Read more →
• 

  Cardiovascular health awareness in Nepal

  Cardiovascular health awareness in Nepal has improved in recent times. It has emerged as a cost-effective tool for prevention of heart disease in recent years. == Background == Cardiovascular diseases in Nepal is responsible for maximum number of deaths and rapid urbanization possess extra threat in this situation emphasizing need for widespread awareness campaigns. Efforts to enhance cardiovascular health awareness among the general public, particularly through social media platforms, have proven pivotal in motivating individuals to adopt healthier lifestyle choices and improve heart health in Nepal in recent years. These awareness initiatives, often organized on special occasions such as World Heart Day of World Heart Federation, World Hypertension Day, and World Health Day of World Health Organization, have garnered active participation from the public, reflecting a growing interest in health-related information. Notably, various hospitals, organizations, and health professionals actively contribute to cardiovascular health awareness in Nepal. The prevalence of heart health-related content on social media platforms indicates a substantial dissemination of information. The engagement of a large number of followers underscores the audience's keen interest in health matters, evident in the significant engagement on various social media accounts and pages. During an event of cardiovascular health awareness a Guinness World Record was achieved on World Heart Day 2023. A Facebook live awareness programme on heart health prevention attracted 11,212 viewers during the 30-minute presentation and was awarded the "Most viewers for a cardiovascular health awareness live stream on Facebook" by Guinness World Record signifying depth of public involvement and importance of social media use in health awareness. In 2014, a 11-day heart camp was conducted in Nepal to raise awareness . In 2015, a is a heart health education program " Mission to Save Heart" was conducted to empower health professionals to manage heart attacks and reduce heart disease deaths.

  Read more →
• 

  Media Block

  A Media Block or Integrated Media Block (IMB) is a component in a digital cinema projection system. Its purpose is to convert the Digital Cinema Package (DCP) content into data that ultimately produces picture and sound in a theater in compliance with DCI anti-piracy encryption requirements. == Terminology == DCI specification allows for two different security system architectures. In the first the Media Block is outside of the projector. This design is simply referred to as a "Media Block" and is typically a device attached directly to the motherboard of a Digital Cinema server. The media block is usually connected to the projector by dual-link SDI cables. Such media block is limited to processing 2K output, downscaling 4K DCPs if necessary. The second architecture describes an "Integrated Media Block". This refers to a device attached and integrated directly into the projector, which receives image data from the server, usually via a cat6 Ethernet connection. They can process 2K and 4K output. Some hardware implementations integrate the entire server on a single board and are able to work both as a MB as well as an IMB. == Security features == All security functions are contained within a Secure Processing Block (SPB), a tamper-proof physical device. Upon ingestion into a DCP server, Key Delivery Messages (KDM) are stored on flash memory in the media block or IMB. A KDM is written to enable the playback of a specific DCP during a specific time window and on a specific media block or IMB, identified by its serial number during the authoring process. Media blocks and IMBs also contain a secure clock that is set in the factory cannot be altered by the end user, which the DCP servers to which they are attached use to determine showtimes. The secure clock prevents theaters from showing encrypted movies outside the times authorized by the KDM (e.g. after it has expired) by simply changing the date and time in the server's BIOS. Media blocks and IMBs also typically include anti-tamper devices, designed to self-destruct the unit if unauthorized modification of its hardware, software or secure clock is attempted.

  Read more →
• 

  Key & See

  Key & See is a variation of the TV Key service that forms part of the open, standards-based interactive TV services platform provided by Miniweb Interactive. Key & See allows viewers to access the interactive TV content made available by broadcasters and channel owners while leaving quarter of their screen tuned to the programme they are already watching Like TV Key, Key & See can be used with interactive TV services on UK satellite TV provider Sky Digital (BSkyB) Key & See works in the same way as a TV Key but the numeric shortcut code is associated with a broadcaster and a particular TV channel or programme. Miniweb Interactive offers commercial brands and broadcasters the chance to utilise TV Key and Key & See technology as part of its interactive TV services platform

  Read more →
• 

  Lost Art-Database

  The Lost Art-Datenbank is an online database published by the German Lost Art Foundation (Deutsches Zentrum Kulturgutverluste. It contains information on cultural objects looted from Jewish collectors or transferred due to Nazi persecution during the Nazi era. Until 2015, it was managed by the Koordinierungsstelle für Kulturgutverluste (Magdeburg Coordination Office). == Creation == Following the Washington Conference of 1998, and the commitments to provide more transparency regarding looted art, Germany launched the Lost Art Database in 2000 order to help Holocaust victims and their families track down artworks that had been looted from them or lost due to Nazi persecution. == Functionality == The Lost Art Database lists art and books and other cultural objects that were lost, seized, stolen or forceably sold during the Nazi era. The database is divided into search requests from victims' families, heirs or institutions and "found" reports from cultural institutions on items with unresolved provenance gaps from the Nazi periods. The section on reports of finds lists objects that are known to have been unlawfully seized or relocated as a result of the war. In addition, reports are published here on cultural objects for which an uncertain or incomplete provenance may indicate a possible unlawful seizure or war-related relocation. The publication of reports in the Lost Art Internet Database is carried out on behalf of and with the consent of the reporting persons and institutions. The responsibility for the content of the reports lies with these legal or natural persons. There have been controversies over which items should be included in the database. Lost Art is based on the Washington Principles adopted in 1998, which Germany has committed itself to implementing (Joint Declaration, 1999). The Lost Art Database is considered a key resource in the search for looted art and the victims of persecution. Every item in the Lost Art Database has an identifier, known as a Lost Art ID. Proveana is the linked research database. == Other lost art databases == Other countries have launched databases to help identify Nazi looted art. Each database has its own area of focus. The German Lost Art Database allows families or heirs to submit information. Other countries have databases that focus on looted artworks that have not been found or artworks that were repatriated to the national authorities after the defeat of the Nazis but were never returned to their original owners. Other databases have been created for stolen antiquities, looted art from colonial era, art stolen from Syria, Iraq, Ukraine, or from museums or collectors.

  Read more →
• 

  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.

  Read more →
• 

  Acquisition of DirecTV by AT&T

  AT&T Inc. announced an agreement with the DirecTV Group on May 18, 2014, to acquire the company for $48.5 billion in a joint cash-stock transaction and assumed debts of $18.6 billion for a total offer of $67.1 billion. Due to stalling growth in the wireless sector, AT&T began diversifying into mass media to expand its consumer offerings. After regulatory agencies approved the purchase on July 24, 2015, AT&T briefly became the largest Pay-TV provider. DirecTV was brought under AT&T's communication segment and DirecTV Now was launched on November 30, 2016, as an alternative to cord-cutting. In the years following the purchase, DirecTV lost millions of subscribers across its satellite and streaming services and by 2019, calls grew for AT&T to divest itself off the business. Initially, AT&T rejected these calls and defended the acquisition, but by February 2021, it reached a deal with TPG Inc. to transfer ownership of DirecTV. Under the terms of the agreement, AT&T would retain a 70% majority stake in DirecTV but would no longer oversee its daily operations. The deal was finalized by August 2, 2021, with AT&T receiving $7.1 billion. By July 3, 2025, AT&T sold its majority stake to TPG, ending any ties of involvement. == Background and Development == === AT&T's history === The company to bear the name "AT&T" was founded on March 3, 1885, as American Telephone and Telegraph Company (or AT&T Corporation) by Theodore Newton Vail as a long-distance subsidiary of the Bell Telephone Company. By December 1899, the Bell Telephone's assets were transferred to AT&T, with the latter gaining control of the Bell System, a regional network of local telecom companies. Theodore Vail became AT&T's President in 1907 and under his leadership, AT&T gained a monopoly over the telephone sector in the United States. This near century dominance earned AT&T the nickname of "Ma Bell." In 1974, the U.S. Department of Justice sued AT&T on accounts of antitrust violations. AT&T challenged the lawsuit, but in 1982, it reached a settlement with the DOJ to break apart its Bell System monopoly into seven regional companies. On January 1, 1984, the Bell System came to an end and led to a reshaped telecom industry. One of these regional companies, Southwestern Bell, emerged as the smallest, but after the passage of the 1996 Telecom Act, deregulated telecom rules allowed SBC to become a major telecom company. AT&T briefly became the largest cable and broadband company by the end of the 20th Century, but later deconsolidated to exit those industries. In 2005, SBC acquired its former parent, AT&T, and took on its branding as AT&T Inc, while retaining its previous business history. The newly reincorporated AT&T acquired BellSouth in 2006 and reconstituted much of its former Bell System. === DirecTV's history === == Acquisition Timeline == == Managing DirecTV == == Divestment and Spinoff ==

  Read more →