AI Data Warehouse

AI Data Warehouse — independent reviews, comparisons, pricing and step-by-step guides on Aizhi.

  • Artificial Linguistic Internet Computer Entity

    Artificial Linguistic Internet Computer Entity

    A.L.I.C.E. (Artificial Linguistic Internet Computer Entity), also referred to as Alicebot, or simply Alice, is a natural language processing chatbot—a program that engages in a conversation with a human by applying some heuristical pattern matching rules to the human's input. It was inspired by Joseph Weizenbaum's classical ELIZA program. It is one of the strongest programs of its type and has won the Loebner Prize, awarded to accomplished humanoid, talking robots, three times (in 2000, 2001, and 2004). The program is unable to pass the Turing test, as even the casual user will often expose its mechanistic aspects in short conversations. Alice was originally composed by Richard Wallace; it "came to life" on November 23, 1995. The program was rewritten in Java beginning in 1998. The current incarnation of the Java implementation is Program D. The program uses an XML Schema called AIML (Artificial Intelligence Markup Language) for specifying the heuristic conversation rules. Alice code has been reported to be available as open source. The AIML source is available from ALICE A.I. Foundation on Google Code and from the GitHub account of Richard Wallace. These AIML files can be run using an AIML interpreter like Program O or Program AB. == In popular culture == Spike Jonze has cited ALICE as the inspiration for his academy award-winning film Her, in which a human falls in love with a chatbot. In a New Yorker article titled “Can Humans Fall in Love with Bots?” Jonze said “that the idea originated from a program he tried about a decade ago called the ALICE bot, which engages in friendly conversation.” The Los Angeles Times reported:Though the film’s premise evokes comparisons to Siri, Jonze said he actually had the idea well before the Apple digital assistant came along, after using a program called Alicebot about ten years ago. As geek nostalgists will recall, that intriguing if at times crude software (it flunked the industry-standard Turing Test) would attempt to engage users in everyday chatter based on a database of prior conversations. Jonze liked it, and decided to apply a film genre to it. “I thought about that idea, and what if you had a real relationship with it?” Jonze told reporters. “And I used that as a way to write a relationship movie and a love story.”

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  • Photonically Optimized Embedded Microprocessors

    Photonically Optimized Embedded Microprocessors

    The Photonically Optimized Embedded Microprocessors (POEM) is DARPA program. It should demonstrate photonic technologies that can be integrated within embedded microprocessors and enable energy-efficient high-capacity communications between the microprocessor and DRAM. For realizing POEM technology CMOS and DRAM-compatible photonic links should operate at high bit-rates with very low power dissipation. == Current research == Currently research in this field is at University of Colorado, Berkley University, and Nanophotonic Systems Laboratory ( Ultra-Efficient CMOS-Compatible Grating Coupler Design).

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  • Algorithmic amplification

    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

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  • Extremely online

    Extremely online

    An extremely online (often capitalized), terminally online, or chronically online person is someone who is closely engaged with Internet culture. People said to be extremely online often believe that online posts are very important. Events and phenomena can themselves be extremely online; while often used as a descriptive term, the phenomenon of extreme online usage has been described as "both a reformation of the delivery of ideas – shared through words and videos and memes and GIFs and copypasta – and the ideas themselves". Here, "online" is used to describe "a way of doing things, not [simply] the place they are done". == Criteria == While the term was in use as early as 2014, it gained popularity over the latter half of the 2010s in conjunction with the increasing prevalence and notability of Internet phenomena in all areas of life. Extremely online people, according to The Daily Dot, are interested in topics "no normal, healthy person could possibly care about", and have been analogized to "pop culture fandoms, just without the pop". Extremely online phenomena such as fan culture and reaction GIFs have been described as "swallowing democracy" by journalists such as Amanda Hess in The New York Times, who claimed that a "great convergence between politics and culture, values and aesthetics, citizenship and commercialism" had become "a dominant mode of experiencing politics". Vulture – formerly the pop culture section of New York magazine, now a stand-alone website – has a section for articles tagged "extremely online". == Historical background == In the 2010s, many categories and labels came into wide use from media outlets to describe Internet-mediated cultural trends, such as the alt-right, the dirtbag left, and doomerism. These ideological categories are often defined by their close association with online discourse. For example, the term "alt-right" was added to the Associated Press' stylebook in 2016 to describe the "digital presence" of far-right ideologies, the dirtbag left refers to a group of "underemployed and overly online millennials" who "have no time for the pieties of traditional political discourse", and the doomer's "blackpilled despair" is combined with spending "too much time on message boards in high school" to produce an eclectic "anti-socialism". Extreme onlineness transcends ideological boundaries. For example, right-wing figures like Alex Jones and Laura Loomer have been described as "extremely online", but so have those on the left like Alexandria Ocasio-Cortez and fans of the Chapo Trap House podcast. Extremely online phenomena can range from acts of offline violence (such as the 2019 Christchurch shootings) to "[going] on NPR to explain the anti-capitalist irony inherent in kids eating Tide Pods". United States President Donald Trump's posts on social media have been frequently cited as extremely online, during both his presidency and his 2020 presidential campaign; Vox claimed his approach to re-election veered into being "Too Online", and Reason questioned whether the final presidential debate was "incomprehensible to normies". While individual people are often given the description, being extremely online has also been posited as an overall cultural phenomenon, applying to trends like lifestyle movements suffixed with "-wave" and "-core" based heavily on Internet media, as well as an increasing expectation for digital social researchers to have an "online presence" to advance in their careers. == Participants and media coverage == One example of a phenomenon considered to be extremely online is the "wife guy" (a guy who posts about his wife); despite being a "stupid online thing" which spent several years as a piece of Internet slang, in 2019 it became the subject of five articles in leading U.S. media outlets. Like many extremely online phrases and phenomena, the "wife guy" has been attributed in part to the in-character Twitter account dril. The account frequently parodies how people behave on the Internet, and has been widely cited as influential on online culture. In one tweet, his character refuses to stop using the Internet, even when someone shouts outside his house that he should log off. Many of dril's other coinages have become ubiquitous parts of Internet slang. Throughout the 2010s, posters such as dril inspired commonly used terms like "corncobbing" (referring to someone losing an argument and failing to admit it); while originally a piece of obscure Internet slang used on sites like Twitter, use of the term (and controversy over its misinterpretation) became a subject of reporting from traditional publications, with some noting that keeping up with the rapid turnover of inside jokes, memes, and quotes online required daily attention to avoid embarrassment. Twitch has been described as "talk radio for the extremely online". Another example of an event cited as extremely online is No Nut November. Increasingly, researchers are expected to have more of an online presence, to advance in their careers, as networking and portfolios continue to transition to the digital world. In November 2020, an article in The Washington Post criticized the filter bubble theory of online discourse on the basis that it "overgeneralized" based on a "small subset of extremely online people". The 2021 storming of the United States Capitol was described as extremely online, with "pro-Trump internet personalities", such as Baked Alaska, and fans livestreaming and taking selfies. People who have been described as extremely online include Chrissy Teigen, Jon Ossoff, and Andrew Yang. In contrast, Joe Biden has been cited as the antithesis of extremely online—The New York Times wrote in 2019 that he had "zero meme energy".

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  • Comparison of video editing software

    Comparison of video editing software

    This is a comparison of non-linear video editing software applications. See also a more complete list of video editing software. == General information == This table gives basic general information about the different editors: === Active === === Discontinued / Inactive === ==== Definition ==== professional: used for full length Hollywood movies; professional (small): mainly used for paid commercials, short films or podcasts/YouTube channels; prosumer: Mainly targeting private use, anything that can do more than just trimming a film; basic: trimming a film; == System requirements == This table lists the operating systems that different editors can run on without emulation, as well as other system requirements. Note that minimum system requirements are listed; some features (like High Definition support) may be unavailable with these specifications. "Unix" includes the similar Linux, BSD and Unix-like operating systems. == High definition/High resolution import == The table below indicates the ability of each program to import various High Definition video or High resolution video formats for editing. == Feature set == == Output options == Please note that recording to Blu-ray does not imply 1080@50p/60p . Most only support up to 1080i 25/30 frames per second recording. Also not all formats can be output.

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  • TheFWA

    TheFWA

    FWA (Favourite Website Awards) is an international award platform that honors and rewards web designers, developers and agencies around the world for excellence within the field of web design and development. The FWA was founded in May 2000 by Rob Ford. In November 2012, The FWA was the most visited website award program in the history of the internet, with over 170 millions site visits. == Jury == The FWA jury is composed of more than 500 web professionals (200 women + 200 men) from 35 countries. == Awards granted == FWA of the Day (FOTD) : Every day, the FWA jury selects the best project, FWA of the Month (FOTM): Every month, the FWA jury selects the best project, People's Choice Award (PCA) : Every year, a public vote selects the people's favourite project, FWA of the Year (FOTY) : Every year, the FWA jury selects the best project. == Hall Of Fame == The FWA Hall of Fame was established in May 2007 (to celebrate the seventh anniversary of the FWA), as a recognition of web's greatest individuals and companies.

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  • NexDock

    NexDock

    NexDock is a series of lapdock devices (containing a laptop screen, keyboard, trackpad, and battery connected to a phone or other device) sold by Nex Computer LLC. The product can be used with mobile desktop environments, including Samsung DeX and the former Windows Continuum. Critical reception for the series has been mixed, with reviewers praising the concept's utility for mobile productivity while noting hardware limitations and its niche appeal. == History == The first NexDock was introduced in 2016 through a successful Indiegogo campaign. Its development coincided with interest in smartphone-powered desktop interfaces, and it was marketed as a companion for Windows 10 Mobile's Continuum feature. Subsequent models, often launched via Kickstarter, added features like higher-resolution displays, touchscreens, and convertible hinges to adapt to the growing capabilities of smartphones. == Models == === NexDock (Original, 2016) === The first model featured a 14.1-inch 1366x768 display and connected primarily via a mini HDMI port. === NexDock 2 (2019) === This model introduced a 13.3-inch 1080p IPS display and a USB-C port, improvements aimed at better supporting platforms like Samsung DeX. === NexDock Touch (2020) === A touchscreen was added to the 13.3-inch display, allowing for more direct interaction with the connected device's operating system. === NexDock 360 (2021) === This version incorporated a 360-degree hinge, allowing the device to be used in laptop, tablet, tent, or stand modes. === NexDock Wireless (2023) === Wireless display connectivity was the key feature of this model, offering a cable-free connection to compatible phones and computers. === NexDock XL (2023) === The screen size was increased to 15.6 inches. It retained the 360-degree hinge and also offered a version with wireless charging for a connected phone. == Reception == Reviews of NexDock products have been mixed, generally praising the concept while pointing out execution flaws. The devices are often lauded for their utility with Samsung DeX, turning a high-end Samsung phone into a viable portable workstation. A review of the NexDock 2 from ZDNet concluded it was a "great companion for the modern road warrior," and Digital Trends called the original a "no-brainer shell" for expanding a phone's capability. However, reviewers have consistently highlighted hardware limitations. In its review of the NexDock Touch, TechRadar stated that while it was a "compelling package for a very specific niche," the "trackpad and keyboard are a bit of a letdown and the screen could be brighter." This sentiment was echoed in other reviews, with criticism often aimed at the trackpad's performance and feel. A review of the NexDock 2 from Android Authority described the experience as being "janky at times," concluding that the device "delivers on its promise — sort of." A common point across many reviews is that the overall performance is entirely dependent on the power of the connected phone, and the experience is often best suited for light productivity tasks rather than replacing a dedicated laptop.

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  • Friending and following

    Friending and following

    Friending is the act of adding someone to a list of "friends" on a social networking service. The notion does not necessarily involve the concept of friendship. It is also distinct from the idea of a "fan"—as employed on the WWW sites of businesses, bands, artists, and others—since it is more than a one-way relationship. A "fan" only receives things. A "friend" can communicate back to the person friending. The act of "friending" someone usually grants that person special privileges (on the service) with respect to oneself. On Facebook, for example, one's "friends" have the privilege of viewing and posting to one's "timeline". Following is a similar concept on other social network services, such as Twitter and Instagram, where a person (follower) chooses to add content from a person or page to their newsfeed. Unlike friending, following is not necessarily mutual, and a person can unfollow (stop following) or block another user at any time without affecting that user's following status. The first scholarly definition and examination of friending and defriending (the act of removing someone from one's friend list, also called unfriending) was David Fono and Kate Raynes-Goldie's "Hyperfriendship and beyond: Friends and Social Norms on LiveJournal" from 2005, which identified the use of the term as both a noun and a verb by users of early social network site and blogging platform LiveJournal, which was originally launched in 1999. == Friend/follower count, friend collecting, and multiple accounts == The addition of people to a friend list without regard to whether one actually is their friend is sometimes known as friend whoring. Matt Jones of Dopplr went so far as to coin the expression "friending considered harmful" to describe the problem of focusing upon the friending of more and more people at the expense of actually making any use of a social network. Friend collecting is the adding of hundreds or thousands of friends/followers, a not uncommon order of magnitude on some social sites. As a result, many teen users feel pressured to heavily curate their posts, posting only carefully posed and edited photographs with well-thought-out captions. Some Instagram users will create a second account, known as a Finsta (short for "Fake Instagram"). A Finsta is typically private, and the owner only allows close friends to follow it. Since the follower count is kept down, the posts can be more candid and silly in nature. Users may also create multiple accounts based on their interests. Someone with a personal social media account might be a photographer and maintain a separate account for that. There is risk associated with following large numbers of people: scholars say that social anxiety could be an effect of managing a large social media network, as users can feel jealous and have a "fear of missing out". == Unfriending and unfollowing == Unfriending is the act of removing someone from a friends list. On Facebook, this means the action is unilateral, meaning, the friendship is terminated on both sides. The act of unfriending is often used when one user was flirting and made the other uncomfortable. Unfollowing is a little different. When a user unfollows someone on Instagram or Twitter, it continues a one-sided relationship. Often, the unfollowed user doesn't realize they were unfollowed, so they continue the following. == Social network friending and friendship == There are distinct groups of "friends" that one can friend on a social networking service. The notion of a social network friend does not necessarily embody the concept of friendship. Although terminology has not yet evolved to distinguish the different types of social networking friends, they can be broken into the following three categories. friends who are actually known These are people that may be one's friends or family in real life, with whom one has regular interaction either on-line or off-line. organizational friends These are companies and other organizations who maintain a "friending" relationship as a contacts list. complete strangers These are social networking "friends" with whom one has no relationship at all. Within these categories "friends" can be made up of strong ties, weak existing ties, weak latent ties, and parasocial ties. Strong ties can be made up of close family members and friends where self-disclosure, intimacy and frequent content occur. Weak existing ties can be made up of acquaintances, co-workers and distance relatives with whom the user has inconsistent contact. Weak latent ties can be made up of people within a similar geographical location or profession that can be used as a potential future bridge to other connections. Parasocial ties can be made up of celebrities, public figures and media personas. Human nature is to reciprocate a friending, marking someone as a friend who has marked oneself as a friend. This is a social norm for social networking services. However, this leads to mixing up who is an actual friend, and who is a contact. Tagging someone as a "contact" who has marked one as a "friend" can be perceived as impolite. Other concerns about this issue are treated in Sherry Turkle's Alone Together which analyses many behavioral dynamics in social media friendships. Turkle defines herself as "cautiously optimistic", but expresses concern that distance communications may undermine genuine face-to-face spoken discourses, lessening people's expectations of one another. One social networking service, FriendFeed, allows one to friend someone as a "fake" friend. The person "fake" friended receives the usual notifications for friending, but that person's updates are not received. Gavin Bell, author of Building Social Web Applications, describes this mechanism as "ludicrous". Results from a 2007 survey the Center for the Digital Future stated that only 23% of internet users have at least one virtual friend whom they have only met online. Ideally the number of virtual friends is directly proportional to the use of the Internet, but the same survey showed 20% of heavy-users (more than 3 hours/day) who claimed an average of 8.7% online friends, reported at least one relationship that started virtually and migrated to in-person contact. This results and other concerning issues are included in the book Networked: The New Social Operating System co-written by Lee Rainie and Barry Wellman in 2012. == Ethical considerations == The act of "friending" someone on a social networking service has particular ethical implications for judges in the United States. Judicial codes of conducts in the various states generally incorporate some form of provision that judges should avoid even the appearance of impropriety. Whether this regulates and even prohibits judges "friending" attorneys that appear before them, and law enforcement personnel, has been the subject of some analysis by the judicial ethics panels of the various states. They haven't all agreed on the guidance that they have given to judges: The New York state Judicial Ethics committee in 2009 simply advised judges to employ caution, noting that the issue of "friending" someone on a social networking service is a publicly observable act that has little difference from other public behavior concerns judges already face. The Florida Judicial Ethics Advisory committee in 2009 noted that, judges being normal human beings, it was unavoidable for judges to form friendships without the responsibilities of their job. It prohibited judges from friending any attorneys that appeared before them, whilst allowing friending of those who do not, on the grounds that it may give the appearance to the general public (even if the substance is otherwise) that those attorneys who are friended hold special sway with the judge. A minority opinion of the committee asserted that there is a substantive difference between "friending" on a social networking service and actual friendship, and that the general public, being aware of the norms of social networking services, was capable of drawing this distinction and would not reasonably conclude either a special degree of influence or a violation of the code of judicial conduct. This minority opinion was outnumbered twice in 2009, both in the Judicial Ethics Advisory and in the Florida Supreme Court Judicial Ethics Advisory committee. The South Carolina judicial conduct committee in 2009 permitted judges to friend attorneys and law enforcement personnel, with the proviso that no judicial business should be conducted upon nor discussed via the social networking service. "... a judge should not become isolated from the community in which the judge lives.", the committee stated. The Kentucky Judicial Ethics committee in 2010 took the same position as the minority opinion in Florida. It urged judges to exercise caution, but recognized that the act of friending "does not, in and of itself, indicate the degree or intensity of a judge's relationship with the person who is the 'friend'

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  • Google Vids

    Google Vids

    Google Vids (not to be confused with Google Video) is an online timeline-based video editing application included as part of the Google Workspace suite. It is designed to help users create informational videos for work-related purposes. The app uses Google's Gemini technology to enable users to create video storyboards manually or with AI assistance using simple prompts. Features include uploading media, choosing stock videos, images, background music, and a voiceover feature with script generation using AI. The app is currently in testing with select Google Workspace Labs users. Like Kapwing and Capcut, Google Vids is primarily for creating work-related content like sales training, onboarding videos, vendor outreach, and project updates. It offers various styles and templates, collaborative features, and is not limited to videos without the short integration at the moment. Google Vids was announced on April 9, 2024. In September 2025, Google began to roll out a basic version of the application to Google Workspace users.

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  • Fear of missing out

    Fear of missing out

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

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  • Cloud9 (service provider)

    Cloud9 (service provider)

    Cloud9 is a mobile network operator focussed on providing mobile subscriptions over the air to programmable SIM cards, SoftSIMs and eSIMs. Their service is used in both smartphones and IoT devices. The company is privately held with headquarters in the United Kingdom. == History == Cloud9, originally owned by Wire9 Telecom Plc, funded and established by investor and telecom specialist, Lee Jones, before being sold for an undisclosed sum by Jones to billionaire Romain Zaleski. It established in the UK, Gibraltar, and Isle of Man as a domestic Mobile Network Operator. Cloud9 obtained spectrum licenses in the Isle of Man in 2007 and Gibraltar in 2010. Around 2011, Cloud9 decided to focus on supplying global SIM cards to save roaming charges. The Gibraltar spectrum licence was sold to another company. The business relocated its core network to Telehouse in London and became a subsidiary of BlueMango Technologies Ltd. Later the company was acquired by Wireless Logic Ltd. In 2013, Cloud9 acquired the IPR of Zynetix Ltd. Through this acquisition, the company achieved sales as an MVNE. In 2014, the company was voted as a Red Herring Top 100 Europe finalist. == Features == Cloud9 has shipped several million 'Travel SIMs'; all SIM cards have been branded with the logo of these resellers. Additionally, the company provides the digital signatures ('profiles' or 'IMSIs') that provide a SIM card with the ability to register with a network and function. These can be provisioned over the air to dynamic SIM cards such as programmable removable UICCs, SoftSIMs and eSIMs. They are members of the GSM Association and are involved in the GSMA remote SIM provisioning standard for eSIMs that will be released soon. The Cloud9 core network also supports 4G (HSS/PDG). Its Mobile Country Code is 234 and its Mobile Network Code is 18. TADIG code is GBRC9. The company has been allocated the following UK number ranges by Ofcom: 4478722, 4477000, 4474409, 4479782, 4479783 and 4475588 The core network is hosted on Cloud9 servers at Telehouse near Canary Wharf in London. Additional components are hosted in Amazon Web Services facilities around the world in order to minimise latency and provide scalability.

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  • Communications system

    Communications system

    A communications system is a collection of individual telecommunications networks systems, relay stations, tributary stations, and terminal equipment usually capable of interconnection and interoperation to form an integrated whole. Communication systems allow the transfer of information from one place to another or from one device to another through a specified channel or medium. The components of a communications system serve a common purpose, are technically compatible, use common procedures, respond to controls, and operate in union. In the structure of a communication system, the transmitter first converts the data received from the source into a light signal and transmits it through the medium to the destination of the receiver. The receiver connected at the receiving end converts it to digital data, maintaining certain protocols e.g. FTP, ISP assigned protocols etc. Telecommunications is a method of communication (e.g., for sports broadcasting, mass media, journalism, etc.). Communication is the act of conveying intended meanings from one entity or group to another through the use of mutually understood signs and semiotic rules. == Types == === By media === An optical communication system is any form of communications system that uses light as the transmission medium. Equipment consists of a transmitter, which encodes a message into an optical signal, a communication channel, which carries the signal to its destination, and a receiver, which reproduces the message from the received optical signal. Fiber-optic communication systems transmit information from one place to another by sending light through an optical fiber. The light forms a carrier signal that is modulated to carry information. A radio communication system is composed of several communications subsystems that give exterior communications capabilities. A radio communication system comprises a transmitting conductor in which electrical oscillations or currents are produced and which is arranged to cause such currents or oscillations to be propagated through the free space medium from one point to another remote therefrom and a receiving conductor at such distant point adapted to be excited by the oscillations or currents propagated from the transmitter. Power-line communication systems operate by impressing a modulated carrier signal on power wires. Different types of power-line communications use different frequency bands, depending on the signal transmission characteristics of the power wiring used. Since the power wiring system was originally intended for transmission of AC power, the power wire circuits have only a limited ability to carry higher frequencies. The propagation problem is a limiting factor for each type of power line communications. === By technology === A duplex communication system is a system composed of two connected parties or devices which can communicate with one another in both directions. The term duplex is used when describing communication between two parties or devices. Duplex systems are employed in nearly all communications networks, either to allow for a communication "two-way street" between two connected parties or to provide a "reverse path" for the monitoring and remote adjustment of equipment in the field. An antenna is basically a small length of a conductor that is used to radiate or receive electromagnetic waves. It acts as a conversion device. At the transmitting end it converts high frequency current into electromagnetic waves. At the receiving end it transforms electromagnetic waves into electrical signals that is fed into the input of the receiver. several types of antenna are used in communication. Examples of communications subsystems include the Defense Communications System (DCS). === Examples: by technology === Telephone Mobile phone Tablet computer Television Telegraph Edison Telegraph TV cable Computer === By application area === The term transmission system is used in the telecommunications industry to emphasize the intermediate media, protocols, and equipment in the circuit, rather than particular end-user applications. A tactical communications system is a communications system that (a) is used within, or in direct support of tactical forces (b) is designed to meet the requirements of changing tactical situations and varying environmental conditions, (c) provides securable communications, such as voice, data, and video, among mobile users to facilitate command and control within, and in support of, tactical forces, and (d) usually requires extremely short installation times, usually on the order of hours, in order to meet the requirements of frequent relocation. An Emergency communication system is any system (typically computer based) that is organized for the primary purpose of supporting the two way communication of emergency messages between both individuals and groups of individuals. These systems are commonly designed to integrate the cross-communication of messages between are variety of communication technologies. An Automatic call distributor (ACD) is a communication system that automatically queues, assigns and connects callers to handlers. This is used often in customer service (such as for product or service complaints), ordering by telephone (such as in a ticket office), or coordination services (such as in air traffic control). A Voice Communication Control System (VCCS) is essentially an ACD with characteristics that make it more adapted to use in critical situations (no waiting for dial tone, or lengthy recorded announcements, radio and telephone lines equally easily connected to, individual lines immediately accessible etc..) == Key components == =

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  • Sentence embedding

    Sentence embedding

    In natural language processing, a sentence embedding is a representation of a sentence as a vector of numbers which encodes meaningful semantic information. State of the art embeddings are based on the learned hidden layer representation of dedicated sentence transformer models. BERT pioneered an approach involving the use of a dedicated [CLS] token prepended to the beginning of each sentence inputted into the model; the final hidden state vector of this token encodes information about the sentence and can be fine-tuned for use in sentence classification tasks. In practice however, BERT's sentence embedding with the [CLS] token achieves poor performance, often worse than simply averaging non-contextual word embeddings. SBERT later achieved superior sentence embedding performance by fine tuning BERT's [CLS] token embeddings through the usage of a siamese neural network architecture on the SNLI dataset. Other approaches are loosely based on the idea of distributional semantics applied to sentences. Skip-Thought trains an encoder-decoder structure for the task of neighboring sentences predictions; this has been shown to achieve worse performance than approaches such as InferSent or SBERT. An alternative direction is to aggregate word embeddings, such as those returned by Word2vec, into sentence embeddings. The most straightforward approach is to simply compute the average of word vectors, known as continuous bag-of-words (CBOW). However, more elaborate solutions based on word vector quantization have also been proposed. One such approach is the vector of locally aggregated word embeddings (VLAWE), which demonstrated performance improvements in downstream text classification tasks. == Applications == In recent years, sentence embedding has seen a growing level of interest due to its applications in natural language queryable knowledge bases through the usage of vector indexing for semantic search. LangChain for instance utilizes sentence transformers for purposes of indexing documents. In particular, an indexing is generated by generating embeddings for chunks of documents and storing (document chunk, embedding) tuples. Then given a query in natural language, the embedding for the query can be generated. A top k similarity search algorithm is then used between the query embedding and the document chunk embeddings to retrieve the most relevant document chunks as context information for question answering tasks. This approach is also known formally as retrieval-augmented generation. Though not as predominant as BERTScore, sentence embeddings are commonly used for sentence similarity evaluation which sees common use for the task of optimizing a Large language model's generation parameters is often performed via comparing candidate sentences against reference sentences. By using the cosine-similarity of the sentence embeddings of candidate and reference sentences as the evaluation function, a grid-search algorithm can be utilized to automate hyperparameter optimization. == Evaluation == A way of testing sentence encodings is to apply them on Sentences Involving Compositional Knowledge (SICK) corpus for both entailment (SICK-E) and relatedness (SICK-R). In the best results are obtained using a BiLSTM network trained on the Stanford Natural Language Inference (SNLI) Corpus. The Pearson correlation coefficient for SICK-R is 0.885 and the result for SICK-E is 86.3. A slight improvement over previous scores is presented in: SICK-R: 0.888 and SICK-E: 87.8 using a concatenation of bidirectional Gated recurrent unit.

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  • International Teletraffic Congress

    International Teletraffic Congress

    The International Teletraffic Congress (ITC) is the first international conference in networking science and practice. It was created in 1955 by Arne Jensen to initially cater to the emerging need to understand and model traffic in telephone networks using stochastic methodologies, and to bring together researchers with these considerations as a common theme. Up through World War II, teletraffic research was done mainly by engineers and mathematicians working in telephone companies. Most of their work was published in local or company journals. In 1955, however, the field acquired a formal, international, institutional structure, with the organization of the first International Teletraffic Congress (ITC). Over the years, it has broaden its scope to address a wide spectrum ranging from the mathematical theory of traffic processes, stochastic system modelling and analysis, traffic and performance measurements, network management, traffic engineering to network capacity planning and cost optimization, including network economics and reliability for various types of networks. ITC served as a forum for all theoretical fundamentals and engineering practices for large-scale deployment and operation of telecommunications networks. Since its inception, ITC witnessed the evolution of communications and networking: the influence of computer science on telecommunication, the advent of the Internet and the massive deployment of mobile communications and optics, the appearance of peer-to-peer networking and social networks, the ever increasing speed and flexibility of new communication technologies, networks, user devices, and applications, and the ever changing operation challenges arising from this development. ITC documented this evolution with contemporary measurement studies, performance analyses of new technologies, recommendations for provisioning and configuration, and greatly contributed to the methodological toolbox of network scientists. Today, with its conferences, specialist seminars, regional seminars, training courses and publications, the ITC aims at a worldwide forum for all questions related to network and service performance, management, and assessment, both present and futuristic. The notion of traffic is broadly used to encompass data traffic from the MAC layer all the way to application traffic in the application layer. The scope of ITC is thus ranging all issues embedding operations, design, planning, economics and performance analysis of current and emerging communication networks and services, to be addressed by applying a variety of tools from different fields, such as Stochastic Processes, Information theory, Control theory, Signal and Processing, Game theory and optimization techniques, Statistical methodologies and Artificial Intelligence techniques. The target audience of such issues is experts from research organizations, universities, equipment vendors and suppliers, network operators, service providers, system integrators and international technical organizations, guaranteeing a well-balanced contribution from theory, application, and practice. The general goal remains to bring researchers and practitioners together toward operational understanding of all types of current and future networks. The ITC is ruled by the International Advisory Council (IAC) which gathers a number of technical experts, from universities and the research arms of key corporations in the industry, from countries having a strong tradition in teletraffic development. The IAC responsibilities are to disseminate information on teletraffic which is of interest for the whole community and: to select the locations of Plenary Congresses and to ensure their high-level technical programme to support Specialist Seminars on specific topics of current interest to promote Regional Seminars for the dissemination of teletraffic concepts in developing countries to facilitate the liaison activity with the ITU through participation in the standardization process and in the Development Programme The technical program and the organization of each ITC event remains within the responsibilities of the hosting country, but with significant IAC support to guarantee that the event is consistent with the quality standards established during the previous congresses. The ITC Plenary Congresses were scheduled tri-annually from 1955 until 1995 when the interval became bi-annual to account for the ever-accelerating development of network technologies, products and services and the associated dramatic increases in network demands. Similarly, to better cover the impact of dramatic changes undergoing in the field of computer and communication systems, networks and usage, it has been decided to hold the Plenary Congress on an annual basis from 2009. == Content == Teletraffic science is the traditional term for all theoretical fundamentals and engineering practices to describe data flows in telecommunication networks, the performance of the usage of network resources, procedures for sizing of resources and engineering the networks for given traffic load and quality of service requirements. For more than 50 years of the 20th century, traffic or teletraffic has been identified primarily with telephone networks. With the huge development of computers, stored program control of network nodes and computer communication, the traditional teletraffic science field naturally extended to computer networks, mobile and wireless/optical networks, and for a wide spectrum of new applications. The convergence between the voice network, the Internet, the television and mobility raised new questions that request new models and tools to be developed. In addition, the development of community networks, home networking, multiple access networking technologies, and the advent of pervasive and ambient communications dictates new challenges to be addressed. Today, ITC addresses the emerging paradigms such as an increasing diversity of distributed applications and services over various media like mobile/optical networks, enabling new markets and economy. ITC has steered the evolutions in communications since its creation in 1955 and remains at the forefront of innovation regarding modeling and performance. The scientific roots of communications traffic are based on the theory of probability and stochastic processes, modelling and performance evaluation. Modelling is the key for the mathematical description and quantitative performance analysis. Traffic flows are described by stochastic processes with complex dependencies which have to be validated by traffic measurements. Modelling also includes operational properties of resource control reflected by service strategies such as queueing disciplines, admission control, and routing. The results of such performance analyses are used for resource dimensioning (sizing), resource management, and network optimization while providing targeted Quality of Service. Teletraffic science is closely related to methods of operation research (queueing theory, optimization, forecasting) and computational sciences (simulation technology distributed systems). In this context, ITC represents a wide community of researchers and practitioners and is regularly organizing events like Congresses, Specialist Seminars and Workshops in order to discuss the latest changes in the modelling, design and performance of communication systems, networks and services. === The evolution of technologies of the 20th century === ITC has been witnessing the change of communication and networking technologies which are reflected in the proceedings and programs of the congresses. The specialist seminars and the motto of the congresses thereby reflect the hot topics of that time and the evolution. Selected topics of the 70's, 80's and 90's were 1998: Traffic Issues related to Multimedia and Nomadic Communications 1995: Traffic Modeling and Measurement in Broadband and Mobile Communications 1990: Broadband Technologies: Architectures, Applications, Control and Performance 1986: ISDN Traffic Issues 1984: Fundamentals of Teletraffic Theory 1977: Modeling of SPC Exchanges and Data Networks === Recent topics in the 21st century === With the rise of the Internet, new networking paradigms and technologies but also new challenges emerged: 2020: Teletraffic in the era of beyond-5G and AI 2019: Networked Systems and Services 2018: Teletraffic in the Smart World 2017: Ubiquitous, software-based, and sustainable networks and services 2016: Digital Connected World 2015: Traffic, Performance and Big Data 2014: Towards a Sustainable World 2013: Energy Efficient and Green Networking 2010: Multimedia Applications - Traffic, Performance and QoE 2009: Network Virtualization - Concepts and Performance 2008: Future Internet Design and Experimental Facilities 2008: Quality of Experience 2002: Internet Traffic Engineering and Traffic Management == Arne Jensen Lifetime Achievement Awards == The Arne Jensen Lifetime A

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  • Locative media

    Locative media

    Locative media or location-based media (LBM) is a virtual medium of communication functionally bound to a location. The physical implementation of locative media, however, is not bound to the same location to which the content refers. Location-based media delivers multimedia and other content directly to the user of a mobile device dependent upon their location. Location information determined by means such as mobile phone tracking and other emerging real-time locating system technologies like Wi-Fi or RFID can be used to customize media content presented on the device. Locative media are digital media applied to real places and thus triggering real social interactions. While mobile technologies such as the Global Positioning System (GPS), laptop computers and mobile phones enable locative media, they are not the goal for the development of projects in this field. == Description == Media content is managed and organized externally of the device on a standard desktop, laptop, server, or cloud computing system. The device then downloads this formatted content with GPS or other RTLS coordinate-based triggers applied to each media sequence. As the location-aware device enters the selected area, centralized services trigger the assigned media, designed to be of optimal relevance to the user and their surroundings. Use of locative technologies "includes a range of experimental uses of geo-technologies including location-based games, artistic critique of surveillance technologies, experiential mapping, and spatial annotation." Location based media allows for the enhancement of any given environment offering explanation, analysis and detailed commentary on what the user is looking at through a combination of video, audio, images and text. The location-aware device can deliver interpretation of cities, parklands, heritage sites, sporting events or any other environment where location based media is required. The content production and pre-production are integral to the overall experience that is created and must have been performed with ultimate consideration of the location and the users position within that location. The media offers a depth to the environment beyond that which is immediately apparent, allowing revelations about background, history and current topical feeds. == Locative, ubiquitous and pervasive computing == The term 'locative media' was coined by Karlis Kalnins. Locative media is closely related to augmented reality (reality overlaid with virtual reality) and pervasive computing (computers everywhere, as in ubiquitous computing). Whereas augmented reality strives for technical solutions, and pervasive computing is interested in embedded computers, locative media concentrates on social interaction with a place and with technology. Many locative media projects have a social, critical or personal (memory) background. While strictly spoken, any kind of link to additional information set up in space (together with the information that a specific place supplies) would make up location-dependent media, the term locative media is strictly bound to technical projects. Locative media works on locations and yet many of its applications are still location-independent in a technical sense. As in the case of digital media, where the medium itself is not digital but the content is digital, in locative media the medium itself might not be location-oriented, whereas the content is location-oriented. Japanese mobile phone culture embraces location-dependent information and context-awareness. It is projected that in the near future locative media will develop to a significant factor in everyday life. == Enabling technologies == Locative media projects use technology such as Global Positioning System (GPS), laptop computers, the mobile phone, Geographic Information System (GIS), and web map services such as Mapbox, OpenStreetMap, and Google Maps among others. Whereas GPS allows for the accurate detection of a specific location, mobile computers allow interactive media to be linked to this place. The GIS supplies arbitrary information about the geological, strategic or economic situation of a location. Web maps like Google Maps give a visual representation of a specific place. Another important new technology that links digital data to a specific place is radio-frequency identification (RFID), a successor to barcodes like Semacode. Research that contributes to the field of locative media happens in fields such as pervasive computing, context awareness and mobile technology. The technological background of locative media is sometimes referred to as "location-aware computing". == Creative representation == Place is often seen as central to creativity; in fact, "for some—regional artists, citizen journalists and environmental organizations for example—a sense of place is a particularly important aspect of representation, and the starting point of conversations." Locative media can propel such conversations in its function as a "poetic form of data visualization," as its output often traces how people move in, and by proxy, make sense of, urban environments. Given the dynamism and hybridity of cities and the networks which comprise them, locative media extends the internet landscape to physical environments where people forge social relations and actions which can be "mobile, plural, differentiated, adventurous, innovative, but also estranged, alienated, impersonalized." Moreover, in using locative technologies, users can expand how they communicate and assert themselves in their environment and, in doing so, explore this continuum of urban interactions. Furthermore, users can assume a more active role in constructing the environments they are situated in accordingly. In turn, artists have been intrigued with locative media as a means of "user-led mapping, social networking and artistic interventions in which the fabric of the urban environment and the contours of the earth become a 'canvas.'" Such projects demystify how resident behaviors in a given city contribute to the culture and sense of personality that cities are often perceived to take on. Design scholars Anne Galloway and Matthew Ward state that "various online lists of pervasive computing and locative media projects draw out the breadth of current classification schema: everything from mobile games, place-based storytelling, spatial annotation and networked performances to device-specific applications." A prominent use of locative media is in locative art. A sub-category of interactive art or new media art, locative art explores the relationships between the real world and the virtual or between people, places or objects in the real world. == Examples == Notable locative media projects include Bio Mapping by Christian Nold in 2004, locative art projects such as the SpacePlace ZKM/ZKMax bluecasting and participatory urban media access in Munich in 2005 and Britglyph by Alfie Dennen in 2009, and location-based games such as AR Quake by the Wearable Computer Lab at the University of South Australia and Can You See Me Now? in 2001 by Blast Theory in collaboration with the Mixed Reality Lab at the University of Nottingham. In 2005, the Silicon Valley–based collaborators of C5 first exhibited the C5 Landscape Initiative, a suite of four GPS inspired projects that investigate perception of landscape in light of locative media. In William Gibson's 2007 novel Spook Country, locative art is one of the main themes and set pieces in the story. Narrative projects which engage with locative media are sometimes referred to as Location-Aware Fiction, as explored in "Data and Narrative: Location Aware Fiction" a 2003 essay by Kate Armstrong. This location-aware fiction is also known as locative literature, where locative stories and poems can be experienced via digital portals, apps, QR codes and e-books, as well as via analogue forms such as labelling tape, Scrabble tiles, fridge magnets or Post-It notes, and these are forms often used by the writer and artist Matt Blackwood. The Transborder Immigrant Tool by the Electronic Disturbance Theater is a locative media project aimed at providing life saving directions to water for people trying to cross the US / Mexico border. The project attracted global media attention in 2009 and 2010. Articles included a Los Angeles Times cover story focusing on Ricardo Dominguez and an AP story interviewing Micha Cárdenas and Brett Stalbaum. The articles focused on concerns over the legality of the project and the ensuing investigations of the group, which are still underway. The Transborder Immigrant Tool has recently been included in a number of major exhibitions including Here, Not There at the Museum of Contemporary Art San Diego and the 2010 California Biennial at the Orange County Museum of Art. Invisible Threads by Stephanie Rothenberg and Jeff Crouse is a locative media project aimed at creating embodied awareness of sweatshops and just-in-time production t

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