AI Face Paint

AI Face Paint — independent reviews, comparisons, pricing and step-by-step guides on Aizhi.

Lessac Technologies

Lessac Technologies, Inc. (LTI) is an American firm which develops voice synthesis software, licenses technology and sells synthesized novels as MP3 files. The firm currently has seven patents granted and three more pending for its automated methods of converting digital text into human-sounding speech, more accurately recognizing human speech and outputting the text representing the words and phrases of said speech, along with recognizing the speaker's emotional state. The LTI technology is partly based on the work of the late Arthur Lessac, a Professor of Theater at the State University of New York and the creator of Lessac Kinesensic Training, and LTI has licensed exclusive rights to exploit Arthur Lessac's copyrighted works in the fields of speech synthesis and speech recognition. Based on the view that music is speech and speech is music, Lessac's work and books focused on body and speech energies and how they go together. Arthur Lessac's textual annotation system, which was originally developed to assist actors, singers, and orators in marking up scripts to prepare for performance, is adapted in LTI's speech synthesis system as the basic representation of the speech to be synthesized (Lessemes), in contrast to many other systems which use a phonetic representation. LTI's software has two major components: (1) a linguistic front-end that converts plain text to a sequence of prosodic and phonosensory graphic symbols (Lessemes) based on Arthur Lessac's annotation system, which specify the speech units to be synthesized; (2) a signal-processing back-end that takes the Lessemes as acoustic data and produces human-sounding synthesized speech as output, using unit selection and concatenation. LTI's text-to-speech system came in second in the world-wide Blizzard Challenge 2011 and 2012. The first-place team in 2011 also employed LTI's "front-end" technology, but with its own back-end. The Blizzard Challenge, conducted by the Language Technologies Institute of Carnegie Mellon University, was devised as a way to evaluate speech synthesis techniques by having different research groups build voices from the same voice-actor recordings, and comparing the results through listening tests. LTI was founded in 2000 by H. Donald Wilson (chairman), a lawyer, LexisNexis entrepreneur and business associate of Arthur Lessac; and Gary A. Marple (chief inventor), after Marple suggested that Arthur Lessac's kinesensic voice training might be applicable to computational linguistics. After Wilson's death in 2006, his nephew John Reichenbach became the firm's CEO.
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Telecommunications device for the deaf

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

Algorithm curation is the selection of online media by technologies such as recommender systems and personalized search. Curation entails the selective sharing of online content and recommendations based on inferred interests. Curation algorithms implement different filter approaches, such as collaborative filtering and content-based filtering. Examples include search engine and social media products such as the Twitter feed, Facebook's News Feed, and Google Personalized Search. == History == === Early algorithmic curation === Online platforms use newsfeed algorithms to determine what content to present to each user. The volume of content published on social media platforms created a need for automated filtering, as manual review of all available content by users is not feasible. These systems function as a form of gatekeeper, shaping which new material users are exposed to and influencing knowledge, attention, and political exposure. ==== Information overload ==== Early ranking algorithms addressed information overload by surfacing the most recent or most popular posts. Later systems shifted toward ranking content based on predicted engagement, aiming to increase the time users spend on a platform. Research has found that these engagement-oriented systems can increase the spread of misinformation and contribute to political polarization as a side effect of optimising for user interaction. ==== How algorithm changes users' feeds over time ==== Algorithmic curation has been found to increase source diversity in some respects while simultaneously reducing the number of external links presented to users, which limits exposure to off-platform content. Research using agent-based modelling has examined how user behaviour, information quality, and algorithmic design interact with one another over time. === Emergence of AI === Platforms increasingly shifted from rule-based ranking systems toward machine-learning and AI-driven approaches, which allow feeds to be personalised at a larger scale and with greater responsiveness to user behaviour. For example, X (formerly Twitter) moved away from a chronological feed toward an AI-powered ranking system that personalises content for each user. These systems are capable of making ranking decisions across volumes of content and user interactions that would not be practical to handle manually. == Approach == === Filter types === ==== Collaborative filtering ==== Collaborative filtering (CF) methods create recommendations based on a person's usage patterns. CF predicts a person's preference for an item by matching their interests with those of users who have similar interests. This process allows for the sharing of ratings between users with similar profiles. CF is based on patterns of human behaviour rather than machine analysis of content itself. Users of CF systems rate items they have interacted with, and these ratings form a profile of interests. The CF system then matches that user with others who have similar profiles, and uses their ratings to generate recommendations. Collaborative filtering can be applied across various content types including text, images, music, and financial products, and can account for complex attributes such as taste and quality that are difficult to represent explicitly. ==== Content-based filtering ==== Content-based filtering (CBF) builds a user profile to represent the types of items a user has engaged with, based on keywords and attributes used to describe those items. Recommendations are generated by presenting items similar to those the user has previously engaged with or is currently viewing. The CBF method creates a profile for each item based on discrete attributes and features, and then constructs a content-based user profile using a weighted vector of those features derived from items the user has rated, purchased, or interacted with. The weights represent the relative importance of each feature, and can be computed using techniques such as Bayesian classifiers, cluster analysis, decision trees, and artificial neural networks, with the goal of estimating the probability that a user will engage with a suggested item. One application of content-based filtering is Pandora Radio, where users provide an artist, genre, or composer to generate a station, and the system surfaces music with similar attributes. == Technology == === Recommender system === Recommender systems rank and suggest content to users based on a combination of implicit and explicit user input. Implicit signals include time spent viewing or engaging with a specific item. Explicit signals include actions such as liking posts, saving store pages, reading news articles, or sharing content. === Personalized search === Personalized search aims to retrieve results most relevant to the user by incorporating contextual factors beyond the explicit query, such as past queries, browsing history, and inferred interests. Social media platforms such as X (formerly Twitter) and Bluesky generate recommendations based on similar users and the content those users interact with. Personalized search may also allow users to explicitly filter results by blocking content containing certain phrases or hashtags. For first-time users without prior history, personalized search may draw on content-based filtering to establish an initial context. Similar processes are used by search engines and retail platforms to tailor results and product recommendations to individual users. == AI contribution == Artificial intelligence contributes to algorithmic curation through machine-learning models capable of processing large volumes of data. Techniques such as deep learning and reinforcement learning allow curation algorithms to model user preferences with greater granularity alongside established filtering approaches. This enables platforms to adjust content rankings rapidly in response to user behaviour. In social media and streaming contexts, AI-driven systems arrange feeds according to predicted relevance, with the outputs shaped by patterns present in the training data. == Social media and potential impact == === Echo chambers === Social media algorithms, such as those used by X (formerly Twitter), recommend content that the system predicts a user will engage with positively. Content from accounts with differing perspectives is less likely to be surfaced, which may reduce source and topic diversity and contribute to the formation of echo chambers. For example, Facebook's news feed is designed to surface content aligned with users' prior engagement, which may reinforce existing views. This dynamic may contribute to filter bubbles, in which users are seldom exposed to content outside their existing interests. Users may further narrow their feeds by actively blocking certain content or accounts. === Over-representation === A pattern observed across social media platforms is the concentration of algorithmic visibility among a small subset of users. Content from the most active users, those with the largest followings, or those generating the most engagement tends to be surfaced more frequently, meaning a small number of accounts can account for a disproportionate share of what appears in other users' feeds.
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Supercomputer operating system

A supercomputer operating system is an operating system intended for supercomputers. Since the end of the 20th century, supercomputer operating systems have undergone major transformations, as fundamental changes have occurred in supercomputer architecture. While early operating systems were custom tailored to each supercomputer to gain speed, the trend has been moving away from in-house operating systems and toward some form of Linux, with it running all the supercomputers on the TOP500 list in November 2017. In 2021, top 10 computers run for instance Red Hat Enterprise Linux (RHEL), or some variant of it or other Linux distribution e.g. Ubuntu. Given that modern massively parallel supercomputers typically separate computations from other services by using multiple types of nodes, they usually run different operating systems on different nodes, e.g., using a small and efficient lightweight kernel such as Compute Node Kernel (CNK) or Compute Node Linux (CNL) on compute nodes, but a larger system such as a Linux distribution on server and input/output (I/O) nodes. While in a traditional multi-user computer system job scheduling is in effect a tasking problem for processing and peripheral resources, in a massively parallel system, the job management system needs to manage the allocation of both computational and communication resources, as well as gracefully dealing with inevitable hardware failures when tens of thousands of processors are present. Although most modern supercomputers use the Linux operating system, each manufacturer has made its own specific changes to the Linux distribution they use, and no industry standard exists, partly because the differences in hardware architectures require changes to optimize the operating system to each hardware design. == Context and overview == In the early days of supercomputing, the basic architectural concepts were evolving rapidly, and system software had to follow hardware innovations that usually took rapid turns. In the early systems, operating systems were custom tailored to each supercomputer to gain speed, yet in the rush to develop them, serious software quality challenges surfaced and in many cases the cost and complexity of system software development became as much an issue as that of hardware. In the 1980s the cost for software development at Cray came to equal what they spent on hardware and that trend was partly responsible for a move away from the in-house operating systems to the adaptation of generic software. The first wave in operating system changes came in the mid-1980s, as vendor specific operating systems were abandoned in favor of Unix. Despite early skepticism, this transition proved successful. By the early 1990s, major changes were occurring in supercomputing system software. By this time, the growing use of Unix had begun to change the way system software was viewed. The use of a high level language (C) to implement the operating system, and the reliance on standardized interfaces was in contrast to the assembly language oriented approaches of the past. As hardware vendors adapted Unix to their systems, new and useful features were added to Unix, e.g., fast file systems and tunable process schedulers. However, all the companies that adapted Unix made unique changes to it, rather than collaborating on an industry standard to create "Unix for supercomputers". This was partly because differences in their architectures required these changes to optimize Unix to each architecture. As general purpose operating systems became stable, supercomputers began to borrow and adapt critical system code from them, and relied on the rich set of secondary functions that came with them. However, at the same time the size of the code for general purpose operating systems was growing rapidly. By the time Unix-based code had reached 500,000 lines long, its maintenance and use was a challenge. This resulted in the move to use microkernels which used a minimal set of the operating system functions. Systems such as Mach at Carnegie Mellon University and ChorusOS at INRIA were examples of early microkernels. The separation of the operating system into separate components became necessary as supercomputers developed different types of nodes, e.g., compute nodes versus I/O nodes. Thus modern supercomputers usually run different operating systems on different nodes, e.g., using a small and efficient lightweight kernel such as CNK or CNL on compute nodes, but a larger system such as a Linux-derivative on server and I/O nodes. == Early systems == The CDC 6600, generally considered the first supercomputer in the world, ran the Chippewa Operating System, which was then deployed on various other CDC 6000 series computers. The Chippewa was a rather simple job control oriented system derived from the earlier CDC 3000, but it influenced the later KRONOS and SCOPE systems. The first Cray-1 was delivered to the Los Alamos Lab with no operating system, or any other software. Los Alamos developed the application software for it, and the operating system. The main timesharing system for the Cray 1, the Cray Time Sharing System (CTSS), was then developed at the Livermore Labs as a direct descendant of the Livermore Time Sharing System (LTSS) for the CDC 6600 operating system from twenty years earlier. In developing supercomputers, rising software costs soon became dominant, as evidenced by the 1980s cost for software development at Cray growing to equal their cost for hardware. That trend was partly responsible for a move away from the in-house Cray Operating System to UNICOS system based on Unix. In 1985, the Cray-2 was the first system to ship with the UNICOS operating system. Around the same time, the EOS operating system was developed by ETA Systems for use in their ETA10 supercomputers. Written in Cybil, a Pascal-like language from Control Data Corporation, EOS highlighted the stability problems in developing stable operating systems for supercomputers and eventually a Unix-like system was offered on the same machine. The lessons learned from developing ETA system software included the high level of risk associated with developing a new supercomputer operating system, and the advantages of using Unix with its large extant base of system software libraries. By the middle 1990s, despite the extant investment in older operating systems, the trend was toward the use of Unix-based systems, which also facilitated the use of interactive graphical user interfaces (GUIs) for scientific computing across multiple platforms. The move toward a commodity OS had opponents, who cited the fast pace and focus of Linux development as a major obstacle against adoption. As one author wrote "Linux will likely catch up, but we have large-scale systems now". Nevertheless, that trend continued to gain momentum and by 2005, virtually all supercomputers used some Unix-like OS. These variants of Unix included IBM AIX, the open source Linux system, and other adaptations such as UNICOS from Cray. By the end of the 20th century, Linux was estimated to command the highest share of the supercomputing pie. == Modern approaches == The IBM Blue Gene supercomputer uses the CNK operating system on the compute nodes, but uses a modified Linux-based kernel called I/O Node Kernel (INK) on the I/O nodes. CNK is a lightweight kernel that runs on each node and supports a single application running for a single user on that node. For the sake of efficient operation, the design of CNK was kept simple and minimal, with physical memory being statically mapped and the CNK neither needing nor providing scheduling or context switching. CNK does not even implement file I/O on the compute node, but delegates that to dedicated I/O nodes. However, given that on the Blue Gene multiple compute nodes share a single I/O node, the I/O node operating system does require multi-tasking, hence the selection of the Linux-based operating system. While in traditional multi-user computer systems and early supercomputers, job scheduling was in effect a task scheduling problem for processing and peripheral resources, in a massively parallel system, the job management system needs to manage the allocation of both computational and communication resources. It is essential to tune task scheduling, and the operating system, in different configurations of a supercomputer. A typical parallel job scheduler has a master scheduler which instructs some number of slave schedulers to launch, monitor, and control parallel jobs, and periodically receives reports from them about the status of job progress. Some, but not all supercomputer schedulers attempt to maintain locality of job execution. The PBS Pro scheduler used on the Cray XT3 and Cray XT4 systems does not attempt to optimize locality on its three-dimensional torus interconnect, but simply uses the first available processor. On the other hand, IBM's scheduler on the Blue Gene supercomputers aims to exploit locality a
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Bitstrips

Bitstrips, Inc. was a Canadian media and technology company based in Toronto, founded in 2007 by Jacob Blackstock, David Kennedy, Shahan Panth, Dorian Baldwin, and Jesse Brown. The company created and offered a web application, Bitstrips.com, which allowed users to create comic strips using personalized avatars, and preset templates and poses. Brown and Blackstock explained that the service was meant to enable self-expression without the need to have artistic skills. Bitstrips was first presented in 2008 at South by Southwest in Austin, Texas, and the service later piloted and launched a version designed for use as educational software. The service achieved increasing prominence following the launch of versions for Facebook and mobile platforms. In 2014, Bitstrips launched a spin-off app known as Bitmoji, which allows users to create personalized stickers for use in instant messaging. In July 2016, Snapchat Inc. announced that it had acquired the company; the Bitstrips comic service was shut down, but Bitmoji remains operational, and has subsequently been given greater prominence within Snapchat's overall platform. == History == Bitstrips was co-developed by Toronto-based comic artist Jacob Blackstock and his high school friend, journalist Jesse Brown. The service was originally envisioned as a means to allow anyone to create their own comic strip without needing artistic skills. Brown explained that "it's so difficult and time-consuming to tell a story in comic book form, drawing the same characters again and again in these tiny little panels, and just the amount of craftsmanship required. And even if you can do it well, which I never could, it takes years to make a story." Brown stated that the service would be "groundwork for a whole new way to communicate", and went as far as describing the service as being a "YouTube for comics". Blackstock explained that the concept of Bitstrips was influenced by his own use of comics as a form of socialization; a student, Blackstock and his friends drew comics featuring each other and shared them during classes. He felt that Bitstrips was a "medium for self-expression", stating that "It's not just about you making the comics, but since you and your friends star in these comics, it's like you're the medium. The visual nature of comics just speaks so much louder than text." The service was publicly unveiled at South by Southwest in 2008. In 2009, the service introduced a version oriented towards the educational market, Bitstrips for Schools, which was initially piloted at a number of schools in Ontario. The service was praised by educators for being engaging to students, especially within language classes. Brown noted that students were using the service to create comics outside of class as well, stating that it was "so gratifying and shocking what people do with your tool to make their own stories in ways that you never would have anticipated. Some of them are just brilliant." In December 2012, Bitstrips launched a version for Facebook; by July 2013, Bitstrips had 10 million unique users on Facebook, having created over 50 million comics. In October 2013, Bitstrips launched a mobile app; in two months, Bitstrips became a top-downloaded app in 40 countries, and over 30 million avatars had been created with it. In November 2013, Bitstrips secured a round of funding from Horizons Ventures and Li Ka-shing. In October 2014, Bitstrips launched Bitmoji, a spin-off app that allows users to create stickers featuring Bitstrips characters in various templates. In July 2016, following unconfirmed reports earlier in the year, Snapchat Inc. announced that it had acquired Bitstrips. The company's staff continue to operate out of Toronto, but the original Bitstrips comic service was shut down in favour of focusing exclusively on Bitmoji, leaving many Bitstrips users to call for a reboot of the comic service.
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Hyperscale computing

In computing, hyperscale is the ability of an architecture to scale appropriately as increased demand is added to the system. This typically involves the ability to seamlessly provide and add computing, memory, networking, and storage resources to a given node or set of nodes that make up a larger computing, distributed computing, or grid computing environment. Hyperscale computing is necessary in order to build a robust and scalable cloud, big data, map reduce, or distributed storage system and is often associated with the infrastructure required to run large distributed sites such as Google, Facebook, Twitter, Amazon, Microsoft, IBM Cloud, Oracle Cloud, or Cloudflare. Companies like Ericsson, AMD, and Intel provide hyperscale infrastructure kits for IT service providers. Companies like Scaleway, Switch, Alibaba, IBM, QTS, Neysa, Digital Realty Trust, Equinix, Oracle, Meta, Amazon Web Services, SAP, Microsoft, Google, and Cloudflare build data centers for hyperscale computing. Such companies are sometimes called "hyperscalers". They are recognized for their massive scale in cloud computing and data management, operating in environments that require extensive infrastructure to accommodate large-scale data processing and storage.
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Fingerprint scanner

Fingerprint scanners are a type of biometric security device that identify an individual by identifying the structure of their fingerprints. They are used in police stations, security industries, smartphones, and other mobile devices. == Fingerprints == People have patterns of friction ridges on their fingers, these patterns are called the fingerprints. Fingerprints are uniquely detailed, durable over an individual's lifetime, and difficult to alter. Due to the unique combinations, fingerprints have become an ideal means of identification. == Types of fingerprint scanners == There are four types of fingerprint scanners: Optical scanners take a visual image of the fingerprint using a digital camera. Capacitive or CMOS scanners use capacitors and thus electric current to form an image of the fingerprint. This type of scanner tends to excel in terms of precision. Ultrasonic fingerprint scanners use high frequency sound waves to penetrate the epidermal (outer) layer of the skin. Thermal scanners sense the temperature differences on the contact surface, in between fingerprint ridges and valleys. All fingerprint scanners are susceptible to spoofing through fingerprints replicated using photographs and 3D printing. == Construction forms == Each type of fingerprint sensor can take two basic forms: the stagnant and the moving fingerprint scanner. Stagnant: The scanning module is mounted statically, and the user is required to swipe their fingers across it. This is cheaper but also less reliable than the moving form. Imaging can be less than ideal if the finger is not dragged over the scanning area at constant speed. Moving: The scanning module is mounted on a movable surface, while the user's finger can remain static. Because this layout allows the scanning module to pass the fingerprint at a constant speed, this method is generally more reliable. == Form factors == === Peripherals === Add-on fingerprint readers for PCs initially appeared in the late 1990's in the form of PCMCIA modules. Microsoft released a model in its IntelliMouse line with an integrated fingerprint reader in 2005. === Integrated readers === Laptops with built-in readers emerged around the same time as peripheral readers with devices such as NECs MC/R730F. IBM produced laptops with integrated readers starting in 2004. Apple introduced fingerprint scanners to their devices under the name Touch ID in 2013. These were initially released on the iPhone 5S, with the technology remaining exclusive to iPhones until the release of the 2016 MacBook Pro. On both laptops and smartphones, the fingerprint sensor usually uses a USB or I2C interface internally.
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Event cinema

Event cinema sometimes called alternative content cinema or livecasts refers to the use of movie theaters to display a varied range of live and recorded entertainment excluding traditional films, such as sport, opera, musicals, ballet, music, one-off TV specials, current affairs, comedy and religious services. == History and development == Event Cinema was set up at the start of the century with rock concerts by Bon Jovi (2001), David Bowie (2003), and Robbie Williams (2005) bringing non-film audiences into cinemas that had newly installed digital equipment. The Metropolitan Opera in New York through their partnership with Fathom Events is acknowledged as the trailblazer in this area, aggressively seeking out new markets and setting high standards for live broadcasts via satellite. Emulated by other opera houses worldwide such as the Royal Opera House following a close second, Glyndebourne, La Scala and the Sydney Opera House the genre of opera within the 'Event Cinema' industry has been a huge success, and has brought new, younger audiences into cash-strapped opera houses depended on state funding and wealthy benefactors for the first time - an unforeseen and happy consequence of digitisation. Ballet and theater have also been very successful, as have rock concerts, both live and recorded. The UK's National Theatre has been a huge success here with their season of live broadcasts under the banner 'NT Live', featuring big name casts such as Helen Mirren, whose recent turn as Queen Elizabeth II in The Audience was a sell out everywhere. (This was in partnership with another West End theatre and the NT are keen to help other theatres maximise their potential through live broadcasts). The Globe and the Royal Shakespeare Company are also producing work for live broadcast and recorded exhibition. As digitisation of cinemas matures, the Event Cinema industry is growing. The strongest territory is the US, followed by the UK and mainland European territories. Latin America is also a very strong market. Recent additions include Pompeii Live, a unique exhibition by the UK's British Museum, featuring celebrities and curators taking the audience on a live tour around the recreated set of Pompeii within the museum itself, and they are also exploring the schools market for the first time, following the live broadcast on June 18 with a daytime broadcast aimed at UK schools for the first time. If successful this will no doubt prove a model for future museums to emulate. An added incentive for exhibitors is the ability to show alternative content, i.e. alternative to mainstream, studio-driven content, such as live special events, sports, pre-show advertising and other digital or video content. In industry terms this has become known as 'Alternative Content', but has recently become known more widely as 'Event Cinema'. === Expanding markets === Some low-budget films that would normally not have a theatrical release because of distribution costs might be shown in smaller engagements than the typical large release studio pictures. The cost of duplicating a digital "print" is very low, so adding more theaters to a release has a small additional cost to the distributor. Movies that start with a small release could scale to a much larger release quickly if they were sufficiently successful, opening up the possibility that smaller movies could achieve box office success previously out of their reach. ==== Technical specifications ==== Event Cinema is also finding a market in 3rd world countries in which the higher costs and quality of DCI equipment are not yet affordable, as crucially there are no DCI specifications for Alternative Content as there is in mainstream [studio] content. This has led to an explosion in the variety of content on offer, but a lack of standardisation has led to questionable quality at times. As the industry matures, this lack of regulation is expected to change and there are moves afoot to introduce codes of practice and technical specifications. Recorded content complements mainstream studio content by maximising the 'downtime' that plagues the cinema industry, where screens worldwide spend a large proportion of their time in darkness and cinemas empty. Some cinema chains have targeted pensioners in particular, offering free tea and coffee for afternoon matinees of recorded opera, for example. Digital Cinema Packages (DCPs) have been useful to cinemas not yet equipped with satellite broadcasting capability and has enabled exhibitors to build their Event Cinema audience, which is not generally the 18-24 demographic that multiplexes are targeting. ==== New Audiences ==== Event Cinema has seen a return of an older, affluent audience, previously turned off by the multiplex experience, and cinemas are starting to capitalise on this by offering waiter-serviced, high class finger food and alcoholic beverages, complete with bars and restaurants, a world away from the traditional popcorn/soft drink model; art house cinemas are increasingly marketing themselves as 'destination' venues for an evening's entertainment, somewhere to spend an entire evening, rather than just a couple of hours. As exhibition admissions have plateau'd in recent years due to the explosion in VOD, tablet and mobile content technology, this new revenue stream has been a surprise and welcome addition to the cinema industry, though the US studios have been cautious in embracing the change as yet. The thrill of Live broadcasts means they are generally regarded as more popular than recorded events, but there are exceptions; artists with a loyal cult or teenage following tend to do particularly well in this area, as concert films featuring artists such as the Grateful Dead, Pearl Jam, JLS, Led Zeppelin and the Rolling Stones have shown. ==== The Future ==== As more and more distributors are emerging, offering an increasingly broad range of content to cinemas worldwide, the landscape itself is shifting: screen advertising companies, technical providers, and exhibitors themselves are reinventing themselves as Alternative Content or Event Cinema distributors, and the industry is witnessing a re-evaluation of business models and practices worldwide. Predictions are that this industry could be work in excess of US$1bn by 2015. An illustration of the growth of this industry is the news the establishment of a European trade association promoting the industry to the general public and supporting those involved in it and the Event Cinema Association.
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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 ==
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DBOS

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

Nitro Zeus is the project name for a well funded comprehensive cyber attack plan created as a mitigation strategy after the Stuxnet malware campaign and its aftermath. Unlike Stuxnet, that was loaded onto a system after the design phase to affect its proper operation, Nitro Zeus's objectives are built into a system during the design phase unbeknownst to the system users. This built-in feature allows a more assured and effective cyber attack against the system's users. The information about its existence was raised during research and interviews carried out by Alex Gibney for his Zero Days documentary film. The proposed long term widespread infiltration of major Iranian systems would disrupt and degrade communications, power grid, and other vital systems as desired by the cyber attackers. This was to be achieved by electronic implants in Iranian computer networks. The project was seen as one pathway in alternatives to full-scale war.
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Data plan

A data plan is a subscription plan from a cellular or other mobile service provider to provide internet data and connectivity. == Formatting == Data plans are usually created by a contract between the telecommunications carrier and the user of their service. This contract outlines a maximum amount of usable data, usually highlighted in either megabytes or gigabytes, allotted per month for the user. In most cases companies will allow a user to surpass the amount of data allowed in the contract, however, will have to pay a per-gigabyte fee, ranging anywhere from five to fifteen U.S. dollars. === Popularization of unlimited plans === Unlimited data plans have seen a large increase in usage by consumers since their initial introduction by U.S. network T-Mobile. These plans, instead of setting an overall maximum for the user, have an amount set-up that, when surpassed, will slow the speed of the network for that user. Unlimited plans typically cost significantly more than the traditional shared data plans, which is a major reason that carriers have set large boundaries and fees. The limits imposed on unlimited plans are designed to fight against attempts to misuse the network, such as a DDoS attack, but are more commonly reasoned as a method to increase the number of people that can use one tower simultaneously. === Data speed changes === When a network is near reaching peak capacity data speeds may be slowed down by carriers as part of most major telecom contracts. This, as stated previously, allows for more people to be utilizing one tower, reducing needed capital for the company. Since speed changes are allowed at the company's will, the user has no official guarantee of speed on most major networks. === Costs brought upon by additional data === In many cases both the user and carrier have to incur additional costs when a user utilizes more of a given data package, which has helped in the proliferation of data caps and other forms of shared data plans. Most of the charges that the carrier has to incur for additional data usage is partially or fully given to the user of the network. ==== Users ==== Users are required to pay flat-rate additional fees that occur when they go above the amount of data given to them in their contract, utility, or prepaid plan. The cost per gigabyte of this fee is usually higher than what the contract itself offers, which discourages users from over-utilizing data and incurring a charge for the carrier. Certain contracts, which do not offer paying additional fees for an increase in data, may result in a shutdown of service, or in extremely rare cases, termination of the service as a whole. ==== Carriers ==== Carriers incur costs for additional data usage, as it limits the number of customers, and associated contracts, that they can handle on one network. Creating more cell phone towers in a given area would be costly, and largely useless until particular spikes in traffic. When the peak usable amount of one tower is reached, it may cause negative public relations towards the reliability of the corporation as a whole.
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Line Drawing System-1

LDS-1 (Line Drawing System-1) was a calligraphic (vector, rather than raster) display processor and display device created by Evans & Sutherland in 1969. This model was known as the first graphics device with a graphics processing unit. == Features == It was controlled by a variety of host computers. Straight lines were smoothly rendered in real-time animation. General principles of operation were similar to the systems used today: 4x4 transformation matrices, 1x4 vertices. Possible uses included flight simulation (in the product brochure there are screenshots of landing on a carrier), scientific imaging and GIS systems. == History == The first LDS-1 was shipped to the customer (BBN) in August 1969. Only a few of these systems were ever built. One was used by the Los Angeles Times as their first typesetting/layout computer. One went to NASA Ames Research Center for Human Factors Research. Another was bought by the Port Authority of New York to develop a tugboat pilot trainer for navigation in the harbor. The MIT Dynamic Modeling had one, and there was a program for viewing an ongoing game of Maze War.
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WEA Manufacturing

WEA Manufacturing was the record, tape, and compact disc manufacturing arm of WEA International Inc. from 1978 to 2003, when it was sold and merged into Cinram International, a previous competitor. The last owner when the plant closed was Technicolor. == History == WEA Manufacturing Inc. was created in 1978–1979 when Warner Communications Inc. purchased two of its longtime suppliers: the record pressing plants Specialty Records Corporation (Olyphant, Pennsylvania) and Allied Record Company (Los Angeles). The company was headquartered in Olyphant, where the original plant was replaced in late 1981 by a new facility which retained the name Specialty Records Corporation. The Specialty Records Corporation name was dropped in 1996 in favor of WEA Manufacturing. The company invested in CD manufacturing in 1986, matching a $247,000 contribution by economic development corporation Ben Franklin Technology Partners to develop and implement new processes of manufacturing audio CDs and CD-ROMs. BFTP assembled a team of experts in physics, electrical engineering, and thin film technology from the University of Scranton and Lehigh University to carry out the research and development. The Olyphant plant and another plant in Alsdorf, Germany, were expanded to support CD pressing that year, with the Olyphant facility's production commencing first in September 1986. WEA Manufacturing grew to become one of the largest manufacturers of recorded media in the world. The company began manufacturing Laserdiscs in July 1991. The company's DVD division, Warner Advanced Media Operations (WAMO), helped design the high-density format used in DVDs, and manufactured some of the first DVDs in the late 1990s. The company was sold to Cinram International in October 2003 and no longer exists under the name WEA Manufacturing, but the Olyphant plant continued to operate under its new ownership. In 2005, the company was Lackawanna County's largest employer, with over 2,300 people working at the Olyphant plant. Cinram closed the former Allied plant in 2006, while Technicolor (which purchased Cinram's assets in 2015) closed the Olyphant plant in 2018. == Patents == WEA Manufacturing held U.S. patents related to compact disc manufacture: Print scanner, (1993). Interference of converging spherical waves with application to the design of light-readable information-recording media and systems for reading such media, (2004). Method of manufacturing a composite disc structure and apparatus for performing the method, (2005). Methods and apparatus for reducing the shrinkage of an optical disc's clamp area and the resulting optical disc, (2005). == Litigation == In 1990, WEA Manufacturing was sued by a Canadian firm, Optical Recording Co. (ORC), for alleged infringement of two 1971 patents related to glass mastering equipment which was used by Time Warner and WEA Manufacturing in the manufacture of approximately 450 million CDs. ORC contended that unlike five other major CD manufacturers in the U.S., Time Warner had refused to license the technology from ORC. In 1992, a jury assessed damages of 6 cents per disc, plus $4–5 million in interest.
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Fifth Estate

The Fifth Estate is a socio-cultural reference to groupings of outlier viewpoints in contemporary society, and is most associated with bloggers, journalists publishing in non-mainstream media outlets, and online social networks. The "Fifth" Estate extends the sequence of the three classical estates (clergy (first), nobility (second), commoners (third)) and the preceding Fourth Estate, essentially the common press. The use of "fifth estate" dates to the 1960s counterculture, and in particular the influential Fifth Estate, an underground newspaper first published in Detroit in 1965. Web-based technologies have enhanced the scope and power of the Fifth Estate far beyond the modest and boutique conditions of its beginnings. Nimmo and Combs asserted in 1992 that political pundits constitute a Fifth Estate. Media researcher Stephen D. Cooper argued in 2006 that bloggers are the Fifth Estate. In 2009, William Dutton argued that the Fifth Estate is not just the blogging community, nor an extension of the media, but "networked individuals" enabled by the Internet, e.g. social media, in ways that can hold the other estates accountable.
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