AI Headshot Apk

AI Headshot Apk — independent reviews, comparisons, pricing and step-by-step guides on Aizhi.

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  Pose (computer vision)

  In the fields of computing and computer vision, pose (or spatial pose) represents the position and the orientation of an object, each usually in three dimensions. Poses are often stored internally as transformation matrices. The term “pose” is largely synonymous with the term “transform”, but a transform may often include scale, whereas pose does not. In computer vision, the pose of an object is often estimated from camera input by the process of pose estimation. This information can then be used, for example, to allow a robot to manipulate an object or to avoid moving into the object based on its perceived position and orientation in the environment. Other applications include skeletal action recognition. == Pose estimation == The specific task of determining the pose of an object in an image (or stereo images, image sequence) is referred to as pose estimation. Pose estimation problems can be solved in different ways depending on the image sensor configuration, and choice of methodology. Three classes of methodologies can be distinguished: Analytic or geometric methods: Given that the image sensor (camera) is calibrated and the mapping from 3D points in the scene and 2D points in the image is known. If also the geometry of the object is known, it means that the projected image of the object on the camera image is a well-known function of the object's pose. Once a set of control points on the object, typically corners or other feature points, has been identified, it is then possible to solve the pose transformation from a set of equations which relate the 3D coordinates of the points with their 2D image coordinates. Algorithms that determine the pose of a point cloud with respect to another point cloud are known as point set registration algorithms, if the correspondences between points are not already known. Genetic algorithm methods: If the pose of an object does not have to be computed in real-time a genetic algorithm may be used. This approach is robust especially when the images are not perfectly calibrated. In this particular case, the pose represent the genetic representation and the error between the projection of the object control points with the image is the fitness function. Learning-based methods: These methods use artificial learning-based system which learn the mapping from 2D image features to pose transformation. In short, this means that a sufficiently large set of images of the object, in different poses, must be presented to the system during a learning phase. Once the learning phase is completed, the system should be able to present an estimate of the object's pose given an image of the object. == Camera pose ==

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  Account verification

  Account verification is the process of verifying that a new or existing account is owned and operated by a specified real individual or organization. A number of websites, for example social media websites, offer account verification services. Verified accounts are often visually distinguished by check mark icons or badges next to the names of individuals or organizations. Account verification can enhance the quality of online services, mitigating sockpuppetry, bots, trolling, spam, vandalism, fake news, disinformation and election interference. == History == Account verification was introduced by Twitter in June 2009, initially as a feature for public figures and accounts of interest, individuals in "music, acting, fashion, government, politics, religion, journalism, media, sports, business and other key interest areas". A similar verification system was adopted by Google+ in 2011, Facebook page in October 2015 (Available in United States, Canada, United Kingdom, Australia and New Zealand) Facebook profile and Facebook page in 2018 (Available in Worldwide) Instagram in 2014, and Pinterest in 2015. On YouTube, users are able to submit a request for a verification badge once they obtain 100,000 or more subscribers. It also has an "official artist" badge for musicians and bands. In July 2016, Twitter announced that, beyond public figures, any individual would be able to apply for account verification. This was temporarily suspended in February 2018, following a backlash over the verification of one of the organisers of the far-right Unite the Right rally due to a perception that verification conveys "credibility" or "importance". In March 2018, during a live-stream on Periscope, Jack Dorsey, co-founder and CEO of Twitter, discussed the idea of allowing any individual to get a verified account. Twitter reopened account verification applications in May 2021 after revamping their account verification criteria. This time offering notability criteria for the account categories of government, companies, brands, and organizations, news organizations and journalists, entertainment, sports and activists, organizers, and other influential individuals. Instagram began allowing users to request verification in August 2018. In April 2018, Mark Zuckerberg, co-founder and CEO of Facebook, announced that purchasers of political or issue-based advertisements would be required to verify their identities and locations. He also indicated that Facebook would require individuals who manage large pages to be verified. In May 2018, Kent Walker, senior vice president of Google, announced that, in the United States, purchasers of political-leaning advertisements would need to verify their identities. In November 2022, Elon Musk included a blue verification check mark with a paid Twitter Blue monthly membership. Prior to Musk's acquisition of Twitter, Twitter offered this check mark at no charge to confirmed high profile users. On December 19, 2022, Twitter introduced two new check mark colors: gold for accounts from official businesses and organizations, and grey for accounts from governments or multilateral organizations. The type of check mark can be confirmed by visiting the profile page, then clicking or tapping on the check mark. == Techniques == === Identity verification services === Identity verification services are third-party solutions which can be used to ensure that a person provides information which is associated with the identity of a real person. Such services may verify the authenticity of identity documents such as drivers licenses or passports, called documentary verification, or may verify identity information against authoritative sources such as credit bureaus or government data, called nondocumentary verification. === Identity documents verification === The uploading of scanned or photographed identity documents is a practice in use, for example, at Facebook. According to Facebook, there are two reasons that a person would be asked to send a scan of or photograph of an ID to Facebook: to show account ownership and to confirm their name. In January 2018, Facebook purchased Confirm.io, a startup that was advancing technologies to verify the authenticity of identification documentation. === Biometric verification === === Behavioral verification === Behavioral verification is the computer-aided and automated detection and analysis of behaviors and patterns of behavior to verify accounts. Behaviors to detect include those of sockpuppets, bots, cyborgs, trolls, spammers, vandals, and sources and spreaders of fake news, disinformation and election interference. Behavioral verification processes can flag accounts as suspicious, exclude accounts from suspicion, or offer corroborating evidence for processes of account verification. === Bank account verification === Identity verification is required to establish bank accounts and other financial accounts in many jurisdictions. Verifying identity in the financial sector is often required by regulation such as Know Your Customer or Customer Identification Program. Accordingly, bank accounts can be of use as corroborating evidence when performing account verification. Bank account information can be provided when creating or verifying an account or when making a purchase. === Postal address verification === Postal address information can be provided when creating or verifying an account or when making and subsequently shipping a purchase. A hyperlink or code can be sent to a user by mail, recipients entering it on a website verifying their postal address. === Telephone number verification === A telephone number can be provided when creating or verifying an account or added to an account to obtain a set of features. During the process of verifying a telephone number, a confirmation code is sent to a phone number specified by a user, for example in an SMS message sent to a mobile phone. As the user receives the code sent, they can enter it on the website to confirm their receipt. === Email verification === An email account is often required to create an account. During this process, a confirmation hyperlink is sent in an email message to an email address specified by a person. The email recipient is instructed in the email message to navigate to the provided confirmation hyperlink if and only if they are the person creating an account. The act of navigating to the hyperlink confirms receipt of the email by the person. The added value of an email account for purposes of account verification depends upon the process of account verification performed by the specific email service provider. === Multi-factor verification === Multi-factor account verification is account verification which simultaneously utilizes a number of techniques. === Multi-party verification === The processes of account verification utilized by multiple service providers can corroborate one another. OpenID Connect includes a user information protocol which can be used to link multiple accounts, corroborating user information. == Account verification and good standing == On some services, account verification is synonymous with good standing. Twitter reserves the right to remove account verification from users' accounts at any time without notice. Reasons for removal may reflect behaviors on and off Twitter and include: promoting hate and/or violence against, or directly attacking or threatening other people on the basis of race, ethnicity, national origin, sexual orientation, gender, gender identity, religious affiliation, age, disability, or disease; supporting organizations or individuals that promote the above; inciting or engaging in the harassment of others; violence and dangerous behavior; directly or indirectly threatening or encouraging any form of physical violence against an individual or any group of people, including threatening or promoting terrorism; violent, gruesome, shocking, or disturbing imagery; self-harm, suicide; and engaging in other activity on Twitter that violates the Twitter Rules. In April 2023, Blue ticks were removed from all Twitter accounts that had not subscribed to Twitter Blue.

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  JQuery

  jQuery is a JavaScript library designed to simplify HTML DOM tree traversal and manipulation, as well as event handling, CSS animations, and Ajax. It is free, open-source software using the permissive MIT License. As of August 2022, jQuery is used by 77% of the 10 million most popular websites. Web analysis indicates that it is the most widely deployed JavaScript library by a large margin, having at least three to four times more usage than any other JavaScript library. jQuery's syntax is designed to make it easier to navigate a document, select DOM elements, create animations, handle events, and develop Ajax applications. jQuery also provides capabilities for developers to create plug-ins on top of the JavaScript library. This enables developers to create abstractions for low-level interaction and animation, advanced effects and high-level, theme-able widgets. The modular approach to the jQuery library allows the creation of powerful dynamic web pages and Web applications. The set of jQuery core features—DOM element selections, traversal, and manipulation—enabled by its selector engine (named "Sizzle" from v1.3), created a new "programming style", fusing algorithms and DOM data structures. This style influenced the architecture of other JavaScript frameworks like YUI v3 and Dojo, later stimulating the creation of the standard Selectors API. Microsoft and Nokia bundle jQuery on their platforms. Microsoft includes it with Visual Studio for use within Microsoft's ASP.NET AJAX and ASP.NET MVC frameworks while Nokia has integrated it into the Web Run-Time widget development platform. == Overview == jQuery, at its core, is a Document Object Model (DOM) manipulation library. The DOM is a tree-structure representation of all the elements of a Web page. jQuery simplifies the syntax for finding, selecting, and manipulating these DOM elements. For example, jQuery can be used for finding an element in the document with a certain property (e.g. all elements with the h1 tag), changing one or more of its attributes (e.g. color, visibility), or making it respond to an event (e.g. a mouse click). jQuery also provides a paradigm for event handling that goes beyond basic DOM element selection and manipulation. The event assignment and the event callback function definition are done in a single step in a single location in the code. jQuery also aims to incorporate other highly used JavaScript functionality (e.g. fade ins and fade outs when hiding elements, animations by manipulating CSS properties). The principles of developing with jQuery are: Separation of JavaScript and HTML: The jQuery library provides simple syntax for adding event handlers to the DOM using JavaScript, rather than adding HTML event attributes to call JavaScript functions. Thus, it encourages developers to completely separate JavaScript code from HTML markup. Brevity and clarity: jQuery promotes brevity and clarity with features like "chainable" functions and shorthand function names. Elimination of cross-browser incompatibilities: The JavaScript engines of different browsers differ slightly so JavaScript code that works for one browser may not work for another. Like other JavaScript toolkits, jQuery handles all these cross-browser inconsistencies and provides a consistent interface that works across different browsers. Extensibility: New events, elements, and methods can be easily added and then reused as a plugin. == History == jQuery was originally created in January 2006 at BarCamp NYC by John Resig, influenced by Dean Edwards' earlier cssQuery library. It is currently maintained by a team of developers led by Timmy Willison (with the jQuery selector engine, Sizzle, being led by Richard Gibson). jQuery was originally licensed under the CC BY-SA 2.5, and relicensed to the MIT License in 2006. At the end of 2006, it was dual-licensed under GPL and MIT licenses. As this led to some confusion, in 2012 the GPL was dropped and is now only licensed under the MIT license. === Popularity === In 2015, jQuery was used on 62.7% of the top 1 million websites (according to BuiltWith), and 17% of all Internet websites. In 2017, jQuery was used on 69.2% of the top 1 million websites (according to Libscore). In 2018, jQuery was used on 78% of the top 1 million websites. In 2019, jQuery was used on 80% of the top 1 million websites (according to BuiltWith), and 74.1% of the top 10 million (per W3Techs). In 2021, jQuery was used on 77.8% of the top 10 million websites (according to W3Techs). == Features == jQuery includes the following features: DOM element selections using the multi-browser open source selector engine Sizzle, a spin-off of the jQuery project DOM manipulation based on CSS selectors that uses elements' names and attributes, such as id and class, as criteria to select nodes in the DOM Events Effects and animations Ajax Deferred and Promise objects to control asynchronous processing JSON parsing Extensibility through plug-ins Utilities, such as feature detection Compatibility methods that are natively available in modern browsers, but need fallbacks for old browsers, such as jQuery.inArray() and jQuery.each(). Cross-browser support === Browser support === jQuery 3.0 and newer supports "current−1 versions" (meaning the current stable version of the browser and the version that preceded it) of Firefox (and ESR), Chrome, Safari, and Edge as well as Internet Explorer 9 and newer. On mobile it supports iOS 7 and newer, and Android 4.0 and newer. == Distribution == The jQuery library is typically distributed as a single JavaScript file that defines all its interfaces, including DOM, Events, and Ajax functions. It can be included within a Web page by linking to a local copy or by linking to one of the many copies available from public servers. jQuery has a content delivery network (CDN) hosted by MaxCDN. Google in Google Hosted Libraries service and Microsoft host the library as well. Example of linking a copy of the library locally (from the same server that hosts the Web page): Example of linking a copy of the library from jQuery's public CDN: == Interface == === Functions === jQuery provides two kinds of functions, static utility functions and jQuery object methods. Each has its own usage style. Both are accessed through jQuery's main identifier: jQuery. This identifier has an alias named $. All functions can be accessed through either of these two names. ==== jQuery methods ==== The jQuery function is a factory for creating a jQuery object that represents one or more DOM nodes. jQuery objects have methods to manipulate these nodes. These methods (sometimes called commands), are chainable as each method also returns a jQuery object. Access to and manipulation of multiple DOM nodes in jQuery typically begins with calling the $ function with a CSS selector string. This returns a jQuery object referencing all the matching elements in the HTML page. $("div.test"), for example, returns a jQuery object with all the div elements that have the class test. This node set can be manipulated by calling methods on the returned jQuery object. ==== Static utilities ==== These are utility functions and do not directly act upon a jQuery object. They are accessed as static methods on the jQuery or $ identifier. For example, $.ajax() is a static method. === No-conflict mode === jQuery provides a $.noConflict() function, which relinquishes control of the $ name. This is useful if jQuery is used on a Web page also linking another library that demands the $ symbol as its identifier. In no-conflict mode, developers can use jQuery as a replacement for $ without losing functionality. === Typical start-point === Typically, jQuery is used by putting initialization code and event handling functions in $(handler). This is triggered by jQuery when the browser has finished constructing the DOM for the current Web page. or Historically, $(document).ready(callback) has been the de facto idiom for running code after the DOM is ready. However, since jQuery 3.0, developers are encouraged to use the much shorter $(handler) signature instead. === Chaining === jQuery object methods typically also return a jQuery object, which enables the use of method chains: This line finds all div elements with class attribute test , then registers an event handler on each element for the "click" event, then adds the class attribute foo to each element. Certain jQuery object methods retrieve specific values (instead of modifying a state). An example of this is the val() method, which returns the current value of a text input element. In these cases, a statement such as $('#user-email').val() cannot be used for chaining as the return value does not reference a jQuery object. === Creating new DOM elements === Besides accessing existing DOM nodes through jQuery, it is also possible to create new DOM nodes, if the string passed as the argument to $() factory looks like HTML. For example, the below code finds an HTML select element, and cr

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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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  Dhammin

  Dhammin (Arabic: ضمّن) is a political platform that manages candidates' electoral campaigns for the National Assembly, Municipal Council or Cooperative Society councils of Kuwait. The platform was founded by Abdullah Al-Salloum and it is, according to news reports and interviews, the first within the field to apply distributed-systems' methodologies.

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  Web API

  A web API is an application programming interface (API) for either a web server or a web browser. As a web development concept, it can be related to a web application's client side (including any web frameworks being used). A server-side web API consists of one or more publicly exposed endpoints to a defined request–response message system, typically expressed in JSON or XML by means of an HTTP-based web server. A server API (SAPI) is not considered a server-side web API, unless it is publicly accessible by a remote web application. == Client side == A client-side web API is a programmatic interface to extend functionality within a web browser or other HTTP client. Originally these were most commonly in the form of native plug-in browser extensions however most newer ones target standardized JavaScript bindings. The Mozilla Foundation created their WebAPI specification which is designed to help replace native mobile applications with HTML5 applications. Google created their Native Client architecture which is designed to help replace insecure native plug-ins with secure native sandboxed extensions and applications. They have also made this portable by employing a modified LLVM AOT compiler. == Server side == A server-side web API consists of one or more publicly exposed endpoints to a defined request–response message system, typically expressed in JSON or XML. The web API is exposed most commonly by means of an HTTP-based web server. Mashups are web applications which combine the use of multiple server-side web APIs. Webhooks are server-side web APIs that take input as a Uniform Resource Identifier (URI) that is designed to be used like a remote named pipe or a type of callback such that the server acts as a client to dereference the provided URI and trigger an event on another server which handles this event thus providing a type of peer-to-peer IPC. === Endpoints === Endpoints are important aspects of interacting with server-side web APIs, as they specify where resources can be accessed by third-party software. Usually the access is via a URI to which HTTP requests are posted, and from which the response is thus expected. Web APIs may be public or private, the latter of which requires an access token. Endpoints need to be static, otherwise the correct functioning of software that interacts with them cannot be guaranteed. If the location of a resource changes (and with it the endpoint) then previously written software will break, as the required resource can no longer be found at the same place. As API providers still want to update their web APIs, many have introduced a versioning system in the URI that points to an endpoint. === Resources versus services === Web 2.0 Web APIs often use machine-based interactions such as REST and SOAP. RESTful web APIs use HTTP methods to access resources via URL-encoded parameters, and use JSON or XML to transmit data. By contrast, SOAP protocols are standardized by the W3C and mandate the use of XML as the payload format, typically over HTTP. Furthermore, SOAP-based Web APIs use XML validation to ensure structural message integrity, by leveraging the XML schemas provisioned with WSDL documents. A WSDL document accurately defines the XML messages and transport bindings of a Web service. === Documentation === Server-side web APIs are interfaces for the outside world to interact with the business logic. For many companies this internal business logic and the intellectual property associated with it are what distinguishes them from other companies, and potentially what gives them a competitive edge. They do not want this information to be exposed. However, in order to provide a web API of high quality, there needs to be a sufficient level of documentation. One API provider that not only provides documentation, but also links to it in its error messages is Twilio. However, there are now directories of popular documented server-side web APIs. === Growth and impact === The number of available web APIs has grown consistently over the past years, as businesses realize the growth opportunities associated with running an open platform, that any developer can interact with. ProgrammableWeb tracks over 24000 Web APIs that were available in 2022, up from 105 in 2005. Web APIs have become ubiquitous. There are few major software applications/services that do not offer some form of web API. One of the most common forms of interacting with these web APIs is via embedding external resources, such as tweets, Facebook comments, YouTube videos, etc. In fact there are very successful companies, such as Disqus, whose main service is to provide embeddable tools, such as a feature-rich comment system. Any website of the TOP 100 Alexa Internet ranked websites uses APIs and/or provides its own APIs, which is a very distinct indicator for the prodigious scale and impact of web APIs as a whole. As the number of available web APIs has grown, open source tools have been developed to provide more sophisticated search and discovery. APIs.json provides a machine-readable description of an API and its operations, and the related project APIs.io offers a searchable public listing of APIs based on the APIs.json metadata format. === Business === ==== Commercial ==== Many companies and organizations rely heavily on their Web API infrastructure to serve their core business clients. In 2014 Netflix received around 5 billion API requests, most of them within their private API. ==== Governmental ==== Many governments collect a lot of data, and some governments are now opening up access to this data. The interfaces through which this data is typically made accessible are web APIs. Web APIs allow for data, such as "budget, public works, crime, legal, and other agency data" to be accessed by any developer in a convenient manner. == Example == An example of a popular web API is the Astronomy Picture of the Day API operated by the American space agency NASA. It is a server-side API used to retrieve photographs of space or other images of interest to astronomers, and metadata about the images. According to the API documentation, the API has one endpoint: https://api.nasa.gov/planetary/apod The documentation states that this endpoint accepts GET requests. It requires one piece of information from the user, an API key, and accepts several other optional pieces of information. Such pieces of information are known as parameters. The parameters for this API are written in a format known as a query string, which is separated by a question mark character (?) from the endpoint. An ampersand (&) separates the parameters in the query string from each other. Together, the endpoint and the query string form a URL that determines how the API will respond. This URL is also known as a query or an API call. In the below example, two parameters are transmitted (or passed) to the API via the query string. The first is the required API key and the second is an optional parameter — the date of the photograph requested. https://api.nasa.gov/planetary/apod?api_key=DEMO_KEY&date=1996-12-03 Visiting the above URL in a web browser will initiate a GET request, calling the API and showing the user a result, known as a return value or as a return. This API returns JSON, a type of data format intended to be understood by computers, but which is somewhat easy for a human to read as well. In this case, the JSON contains information about a photograph of a white dwarf star: The above API return has been reformatted so that names of JSON data items, known as keys, appear at the start of each line. The last of these keys, named url, indicates a URL which points to a photograph: https://apod.nasa.gov/apod/image/9612/ngc2440_hst2.jpg Following the above URL, a web browser user would see this photo: Although this API can be called by an end user with a web browser (as in this example) it is intended to be called automatically by software or by computer programmers while writing software. JSON is intended to be parsed by a computer program, which would extract the URL of the photograph and the other metadata. The resulting photo could be embedded in a website, automatically sent via text message, or used for any other purpose envisioned by a software developer.

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  Digital edition

  A digital edition is an online magazine or online newspaper delivered in electronic form which is formatted identically to the print version. Digital editions are often called digital facsimiles to underline the likeness to the print version. Digital editions have the benefit of reduced cost to the publisher and reader by avoiding the time and the expense to print and deliver paper edition. This format is considered more environmentally friendly due to the reduction of paper and energy use. These editions also often feature interactive elements such as hyperlinks both within the publication itself and to other internet resources, search option and bookmarking, and can also incorporate multimedia such as video or animation to enhance articles themselves or for advertisement purposes. Some delivery methods also include animation and sound effects that replicate turning of the page to further enhance the experience of their print counterparts. Magazine publishers have traditionally relied on two revenue sources: selling ads and selling magazines. Additionally some publishers are using other electronic publication methods such as RSS to reach out to readers and inform them when new digital editions are available. Current technologies are generally either reader-based, requiring a download of an application and subsequent download of each edition, or browser-based, often using Macromedia Flash, requiring no application download (such as Adobe Acrobat). Some application-based readers allow users to access editions while not connected to internet. Dedicated hardware such as the Amazon Kindle and the iPad is also available for reading digital editions of select books, popular national magazines such as Time, The Atlantic, and Forbes and popular national newspapers such as the New York Times, Wall Street Journal, and Washington Post. Archives of print newspapers, in some cases dating hundreds of years back, are being digitized and made available online. Google is indexing existing digital archives produced by the newspapers themselves or by third parties. Newspaper and magazine archival began with microform film formats solving the problem of efficiently storing and preserving. This format, however, lacked accessibility. Many libraries, especially state libraries in the United States are archiving their collections digitally and converting existing microfilm to digital format. The Library of Congress provides project planning assistance and the National Endowment for the Humanities procures funding through grants from its National Digital Newspaper Program. Digital magazines, ezines, e-editions and emags are sometimes referred to as digital editions, however some of these formats are published only in digital format unlike digital editions which replicate a printed edition as well. == Digital magazines == Digital-replica magazines number in thousands—consumer and business publications, house magazines for associations, institutions and corporations – and conversion from print to digital was still increasing as of 2009. A 2008 report funded by digital-replica technology providers and auditing agencies counted 1,786 digital-replica editions having more than 7 million circulation among business-to-business publications, of which 230 editions were audited The same report counted 1,470 digital-replica editions of consumer magazines having 5.5 million digital circulation, of which 240 editions were audited. These authors estimated that by year end of 2009 there would be 8,000 digital magazines, having a combined distribution of more than 30 million people. Surveys have shown that, while not all subscribers prefer a digital edition, some do because of the environmental benefit and also because digital magazines are searchable and may easily be passed along or linked to. One such survey funded by a digital publisher reported on inputs from more than 30,000 subscribers to business, consumer and other digital magazines. == Digital magazine business models == === Reduced printing and distribution costs === The publishers' choice to save by moving some or all subscribers from print to digital is widely accepted. Oracle magazine, which has 176,000 of its 516,000 subscribers receiving digital according to its June 2009 BPA circulation statement, is said to be the most widely circulated digital edition of a business-to-business publication. Publishers who do this need to choose whether to make some issues all-digital, move some subscribers to digital edition, add some digital-only subscribers, or send all subscribers the digital edition. === Paid subscription revenue === In 2009, a major consumer magazine, PC Magazine, went all-digital, charging an annual subscription fee for its digital-replica edition. Many consumer magazines and newspapers are already available in eReader formats that are sold through booksellers. === Sponsorship and advertising revenue === Digital editions often carry special "front cover" advertising, or advertising on the email message alerting the subscriber of the digital edition. Publishers also produce special digital-only inserts and rich-media ads or advertorials. === Designed-for-digital issues === Another approach is to fully replace printed issues with digital ones, or to use digital editions for extra issues that would otherwise have to be printed.

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  Optical recording

  The history of optical recording can be divided into a few number of distinct major contributions. The pioneers of optical recording worked mostly independently, and their solutions to the many technical challenges have very distinctive features, such as reflective disc (Compaan and Kramer) transparent disc (Gregg) floppy disc (Russell) rigid disc (Compaan and Kramer) focused laser beam for read-out through transparent substrate (Compaan and Kramer). == Gregg 1958 == Laserdisc technology, using a transparent disc, was invented by David Paul Gregg in 1958 (and patented in 1970 and 1990). By 1969 Philips had developed a videodisc in reflective mode, which has great advantages over the transparent mode. MCA and Philips decided to join their efforts. They first publicly demonstrated the videodisc in 1972. Laserdisc was first available on the market, in Atlanta, on December 15, 1978, two years after the VHS VCR and four years before the CD, which is based on Laserdisc technology. Philips produced the players and MCA produced the discs. The Philips/MCA cooperation was not successful, and discontinued after a few years. Several of the scientists responsible for the early research (John Winslow, Richard Wilkinson and Ray Dakin) founded Optical Disc Corporation (now ODC Nimbus). == Russell 1965 == While working at Pacific Northwest National Laboratory, James Russell invented an optical storage system for digital audio and video, patenting the concept in 1970. The earliest patents by Russell, US 3,501,586, and 3,795,902 were filed in 1966, and 1969. respectively. He built prototypes, and the first was operating in 1973. Russell had found a way to record digital information onto a photosensitive plate in tiny dark spots, each spot one micrometre from centre to centre, with a laser that wrote the binary patterns. Russell's first optical disc was distinctly different from the eventual compact disc product: the disc in the player was not read by laser light. A key characteristic of Russell's invention is that a laser is not used for the reading the disc, instead the entire disc or oblong sheet to be read is illuminated by a large playback light source at the back of the transparent foil. As a result, the information density is relatively low. By 1985, Russell held over 25 patents to various technologies related to optical recording and playback. Russell's intellectual property was purchased by Optical Recording Corporation (ORC) in Toronto in 1985, and this firm notified a number of CD manufacturers that their CD technology was based on patents held by ORC. In 1987, ORC signed an agreement with Sony whereby Sony paid for licensing of the technology. Further licenses followed from Philips and others. Warner Communications did not sign, and was sued by ORC. In 1992, the large CD manufacturer, now called Time Warner, was ordered to pay ORC US$30 million in patent violations. In the 1970 patent, the spot diameter was around 10 micrometres. Thus, the areal information density was around a factor hundred less than that of the CD as later developed. Russell continued to refine the concept throughout the 1970s. Philips and Sony, however, were able to put far greater resources into the parallel development of the concept, arriving at a smaller and more sophisticated product in just a few years. Russell's various partners and ventures failed to produce a single consumer product. == Korpel 1968 == Adrianus Korpel worked for the Zenith Electronics Corporation, when he developed very early optical videodisc systems, including holographic storage. == Kramer and Compaan 1969 == The Philips development of the videodisc technology began in 1969 with efforts by Dutch physicists Klaas Compaan and Piet Kramer to record video images in holographic form on disc. Their prototype Laserdisc shown in 1972 used a laser beam in reflective mode to read a track of pits using an FM video signal. Together with MCA, Philips brought the optical videodisk to market in 1978. The cooperation between Philips and MCA did not last long, and discontinued after a few years. == Immink and Doi 1979 == The Compact Disc (CD), which is based on MCA/Philips Laserdisc technology, was developed by a taskforce of Sony and Philips in 1979–1980. Toshi Doi and Kees Schouhamer Immink created the digital technologies that turned the analog Laserdisc into a high-density low-cost digital audio disc. The CD, available on the market since October 1982, remains the standard physical medium for sale of commercial audio recordings Standard CDs have a diameter of 120 mm and can hold up to 80 minutes of audio (700 MB of data). The Mini CD has various diameters ranging from 60 to 80 mm; they are sometimes used for CD singles or device drivers, storing up to 24 minutes of audio. The technology was later adapted and expanded to include data storage CD-ROM, write-once audio and data storage CD-R, rewritable media CD-RW, Super Audio CD (SACD), Video Compact Discs (VCD), Super Video Compact Discs (SVCD), PhotoCD, PictureCD, CD-i, and Enhanced CD. CD-ROMs and CD-Rs remain widely used technologies in the computer industry. The CD and its extensions have been extremely successful: in 2004, worldwide sales of CD audio, CD-ROM, and CD-R reached about 30 billion discs. By 2007, 200 billion CDs had been sold worldwide.

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  Pulse-coupled networks

  Pulse-coupled networks or pulse-coupled neural networks (PCNNs) are neural models proposed by modeling a cat's visual cortex, and developed for high-performance biomimetic image processing. In 1989, Eckhorn introduced a neural model to emulate the mechanism of cat's visual cortex. The Eckhorn model provided a simple and effective tool for studying small mammal’s visual cortex, and was soon recognized as having significant application potential in image processing. In 1994, Johnson adapted the Eckhorn model to an image processing algorithm, calling this algorithm a pulse-coupled neural network. The basic property of the Eckhorn's linking-field model (LFM) is the coupling term. LFM is a modulation of the primary input by a biased offset factor driven by the linking input. These drive a threshold variable that decays from an initial high value. When the threshold drops below zero it is reset to a high value and the process starts over. This is different than the standard integrate-and-fire neural model, which accumulates the input until it passes an upper limit and effectively "shorts out" to cause the pulse. LFM uses this difference to sustain pulse bursts, something the standard model does not do on a single neuron level. It is valuable to understand, however, that a detailed analysis of the standard model must include a shunting term, due to the floating voltages level in the dendritic compartment(s), and in turn this causes an elegant multiple modulation effect that enables a true higher-order network (HON). A PCNN is a two-dimensional neural network. Each neuron in the network corresponds to one pixel in an input image, receiving its corresponding pixel's color information (e.g. intensity) as an external stimulus. Each neuron also connects with its neighboring neurons, receiving local stimuli from them. The external and local stimuli are combined in an internal activation system, which accumulates the stimuli until it exceeds a dynamic threshold, resulting in a pulse output. Through iterative computation, PCNN neurons produce temporal series of pulse outputs. The temporal series of pulse outputs contain information of input images and can be used for various image processing applications, such as image segmentation and feature generation. Compared with conventional image processing means, PCNNs have several significant merits, including robustness against noise, independence of geometric variations in input patterns, capability of bridging minor intensity variations in input patterns, etc. A simplified PCNN called a spiking cortical model was developed in 2009. == Applications == PCNNs are useful for image processing, as discussed in a book by Thomas Lindblad and Jason M. Kinser. PCNNs have been used in a variety of image processing applications, including: image segmentation, pattern recognition, feature generation, face extraction, motion detection, region growing, image denoising and image enhancement Multidimensional pulse image processing of chemical structure data using PCNN has been discussed by Kinser, et al. They have also been applied to an all pairs shortest path problem.

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  KKday

  KKday is an online travel e-commerce platform focused on connecting independent travelers with authentic, curated local experiences, tours, activities, and attraction tickets. == History == KKday was founded in 2014 in Taipei, Taiwan, by CEO Ming Chen, who previously started and led both Star Travel and Ezfly to IPO. In March of 2016, the company raised US$4.5 million in a Series A round led by AppWorks Ventures with participation by 91Capital. The raise allowed KKday to open offices and expand into Hong Kong, Japan, South Korea and Singapore by 2016. By the end of 2016, KKday offered over 6,000 travel experiences across 53 countries and 174 cities, marking early international expansion with its official launch in Singapore in October 2016, accompanied by promotional campaigns to attract regional users. Expansion into Malaysia, Thailand, Vietnam and the Philippines continued throughout 2017 and into 2018, with the company opening offices in Indonesia and mainland China. KKday rapidly expanded its inventory, reaching over 10,000 experiences in more than 500 cities across 80 countries by 2018, with key markets in Taiwan, Hong Kong, and South Korea. In February 2018, KKday raised $10.5 million in a funding round led by Japanese travel giant H.I.S., allowing integration with larger travel networks and further global growth. Forbes reports that by the end of 2018, the company operated in 11 countries and regions, employed around 400 staff, and recorded over 4 million weekly website views with more than 1 million app downloads. A combination of a Japanese and South Korean trade dispute, along with the Covid-19 pandemic in 2020, lead KKday to pivot quickly toward domestic staycations and local experiences while initially raising $70m in their Series C which, was later extended to $95m. The Series C funds were partially used to accelerate and expand Rezio. Launched in 2019, Rezio is KKday's B2B SaaS booking management platform for travel providers, allowing them to track inventory, manage reservations and sell tickets. FineDayClub was launched in 2020 by KKday as a personalized luxury subscription travel service to cater to high end clients. KKday’s CFO, Jenny Tsai pivoted to lead KKday’s new venture. KKday was able to successfully navigate and adapt to travel patterns during the Covid-19 pandemic by reducing user acquisition costs by two thirds and focusing on domestic travel experiences to drive bookings and revenue. KKday was particularly successful in Vietnam, with bookings increased by 2,000% through 2022 and the company's travel operator platform Rezio, onboarding over 1,200 operators inside the country. In 2021, KKday acquired Activity Japan, a domestic focused travel company, founded by Kimiharu Obuchi in 2014. The successful acquisition, a key factor in KKday’s rapid expansion in the Japanese market, was facilitated by H.I.S., a common early investor in both platforms. In 2023 KKday inked a partnership with Rail Europe to create an all-in-one platform for 150 rail lines over 33 European countries with the intent of increasing ridership across Europe. In late 2024, KKday completed its Series D at $70M, bringing the total amount of capital raised to over $250M. The funds are to be earmarked for continued global expansion, artificial intelligence integration and enhanced partnerships, similar to the partnership with Tablelog, which now allows users to book restaurant reservations at 42,000 restaurants in Japan through the platform. == Platform == KKDay is an e-commerce online travel agency operating in 92 countries with over 350,000 travel experiences available for booking. The company started with focus on authentic local travel experiences in the Asian Pacific market and has expanded to a more global focus. KKday connects travelers with travel services and experiences such as attraction tickets, theme parks, cultural experiences, and seasonal events. KKday has positioned itself as an all-in-one travel super app with booking for hotels, rental cars, flights, sim cards, rail passes, dining and tickets. === Rezio === Rezio is a cloud-based SaaS booking management platform developed by KKday specifically for tour operators, activity providers, and attractions in the travel industry. It serves as an all-in-one system designed to help these businesses digitize their operations, particularly those previously relying on offline processes. Features include a mobile app for on-the-go order management, customer information checks, and voucher scanning, as well as channel management, analytics for customer data, and integrations with multiple OTAs and payment providers. Unlike KKday, which is an OTA marketplace for consumer exposure (with commissions), Rezio focuses on backend operations for suppliers, allowing brand independence, operational efficiency, and direct customer relationships while optionally connecting to OTAs like KKday. Rezio supports over 5,000 merchants, 30,000 experiences, and 10 million travelers worldwide, with a strong presence in Asia. One of the brands successful implementations was at the Nikko Toshogu Shrine where Rezio was implemented to help with long lines and wait times due to over-tourism. The shrine was able to implement the inventory management features to allow online booking and cashless payments onsite. === FineDayClub === FineDayClub is a membership-based travel concierge service launched in late 2020 by KKday. It is aimed at families, and organizations seeking customized travel experiences. It offers one-on-one advisory services. === ActivityJapan === ActivityJapan is a Japanese comprehensive online travel site that specializes in authentic Japanese travel experiences. It was purchased by KKday in 2021 but continues to operate independently.

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  Hardware-based encryption

  Hardware-based encryption is the use of computer hardware to assist software, or sometimes replace software, in the process of data encryption. Typically, this is implemented as part of the processor's instruction set. For example, the AES encryption algorithm (a modern cipher) can be implemented using the AES instruction set on the ubiquitous x86 architecture. Such instructions also exist on the ARM architecture. However, more unusual systems exist where the cryptography module is separate from the central processor, instead being implemented as a coprocessor, in particular a secure cryptoprocessor or cryptographic accelerator, of which an example is the IBM 4758, or its successor, the IBM 4764. Hardware implementations can be faster and less prone to exploitation than traditional software implementations, and furthermore can be protected against tampering. == History == Prior to the use of computer hardware, cryptography could be performed through various mechanical or electro-mechanical means. An early example is the Scytale used by the Spartans. The Enigma machine was an electro-mechanical system cipher machine notably used by the Germans in World War II. After World War II, purely electronic systems were developed. In 1987 the ABYSS (A Basic Yorktown Security System) project was initiated. The aim of this project was to protect against software piracy. However, the application of computers to cryptography in general dates back to the 1940s and Bletchley Park, where the Colossus computer was used to break the encryption used by German High Command during World War II. The use of computers to encrypt, however, came later. In particular, until the development of the integrated circuit, of which the first was produced in 1960, computers were impractical for encryption, since, in comparison to the portable form factor of the Enigma machine, computers of the era took the space of an entire building. It was only with the development of the microcomputer that computer encryption became feasible, outside of niche applications. The development of the World Wide Web lead to the need for consumers to have access to encryption, as online shopping became prevalent. The key concerns for consumers were security and speed. This led to the eventual inclusion of the key algorithms into processors as a way of both increasing speed and security. == Implementations == === In the instruction set === ==== x86 ==== The X86 architecture, as a CISC (Complex Instruction Set Computer) Architecture, typically implements complex algorithms in hardware. Cryptographic algorithms are no exception. The x86 architecture implements significant components of the AES (Advanced Encryption Standard) algorithm, which can be used by the NSA for Top Secret information. The architecture also includes support for the SHA Hashing Algorithms through the Intel SHA extensions. Whereas AES is a cipher, which is useful for encrypting documents, hashing is used for verification, such as of passwords (see PBKDF2). ==== ARM ==== ARM processors can optionally support Security Extensions. Although ARM is a RISC (Reduced Instruction Set Computer) architecture, there are several optional extensions specified by ARM Holdings. === As a coprocessor === IBM 4758 – The predecessor to the IBM 4764. This includes its own specialised processor, memory and a Random Number Generator. IBM 4764 and IBM 4765, identical except for the connection used. The former uses PCI-X, while the latter uses PCI-e. Both are peripheral devices that plug into the motherboard. === Proliferation === Advanced Micro Devices (AMD) processors are also x86 devices, and have supported the AES instructions since the 2011 Bulldozer processor iteration. Due to the existence of encryption instructions on modern processors provided by both Intel and AMD, the instructions are present on most modern computers. They also exist on many tablets and smartphones due to their implementation in ARM processors. == Advantages == Implementing cryptography in hardware means that part of the processor is dedicated to the task. This can lead to a large increase in speed. In particular, modern processor architectures that support pipelining can often perform other instructions concurrently with the execution of the encryption instruction. Furthermore, hardware can have methods of protecting data from software. Consequently, even if the operating system is compromised, the data may still be secure (see Software Guard Extensions). == Disadvantages == If, however, the hardware implementation is compromised, major issues arise. Malicious software can retrieve the data from the (supposedly) secure hardware – a large class of method used is the timing attack. This is far more problematic to solve than a software bug, even within the operating system. Microsoft regularly deals with security issues through Windows Update. Similarly, regular security updates are released for Mac OS X and Linux, as well as mobile operating systems like iOS, Android, and Windows Phone. However, hardware is a different issue. Sometimes, the issue will be fixable through updates to the processor's microcode (a low level type of software). However, other issues may only be resolvable through replacing the hardware, or a workaround in the operating system which mitigates the performance benefit of the hardware implementation, such as in the Spectre exploit.

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  Awwwards

  Awwwards (Awwwards Online SL) is an organization that hosts web design competitions and conferences across Europe and the United States. Website owners and developers can participate by submitting their websites for review. Submissions are assessed by a jury, and top entries are presented and awarded prizes on a rotational basis. == Nomination process == Web designers submit their websites through Awwwards' platform for consideration for the Site of the Day. A jury, composed of industry professionals, and the Awwwards community evaluate the entries. The best daily sites are published annually in "The 365 Best Websites Around the World" book. == Jury == The jury consists of international designers, developers, and agencies who assess the creativity, technical skills, and insight of the submitted web projects. The panel's expertise ensures a comprehensive review process. === Developer Award === Awwwards, in partnership with Microsoft, created the Developer Award to recognize web developers who demonstrate excellence in creating websites that meet modern standards. The award highlights websites that work seamlessly across various platforms and devices, using best practices in HTML5, JavaScript, and CSS. == Annual winners == Some prominent Site of the Year winners include Mercedes-Benz, Bloomberg L.P., Bose Corporation, Warner Brothers, Volkswagen, Uber, and Google. == Awwwards conference == Awwwards also organizes two-day conferences featuring speakers from major tech companies and industry leaders such as Microsoft, Google, Spotify, Adobe, Opera, and Smashing Magazine. These events focus on the latest trends in web design and development. Speakers at Awwwards conferences have included notable figures in the design and technology industry such as Stefan Sagmeister, Paula Scher, and design leaders from companies including Wix. == Corporate affairs == === Platform === Awwwards operates an online platform where web designers and developers submit websites for evaluation and awards. Submitted projects are reviewed by a jury based on design, usability, creativity, and content. The platform also serves as a community hub for discovering digital trends, showcasing work, and accessing educational resources including talks and interviews. Design professionals from international companies have participated in Awwwards events and platform content. For example, Wix, a cloud-based web development company known for its website builder tools, has featured prominently in Awwwards conferences, with its design leadership contributing to discussions on design trends and creative thinking.

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  Gemini Enterprise Agent Platform

  Gemini Enterprise Agent Platform (formerly known as Vertex AI) is a managed machine learning (ML) and artificial intelligence (AI) platform developed by Google Cloud. It provides a unified environment for building, training, deploying, and scaling ML models and generative AI applications. The platform integrates tools for the full ML lifecycle, including data preparation, model training, evaluation, deployment, and monitoring, under a single API and user interface. Vertex AI was announced at Google I/O and released as a generally available product on May 18, 2021. At launch, Google described Vertex AI as unifying its AutoML offerings with its prior Cloud AI Platform capabilities, and as adding operational features intended to help teams move models from experimentation into production use. On April 22, 2026, Google announced Gemini Enterprise Agent Platform as the replacement evolution of Vertex AI. == History == Google Cloud announced the general availability of Vertex AI on May 18, 2021, at the Google I/O developer conference. The platform was designed to consolidate Google Cloud's previously separate ML offerings, including AutoML and the legacy AI Platform, into a single system. At launch, Google claimed that Vertex AI required roughly 80% fewer lines of code to train a model compared to competing platforms. In June 2023, Google made generative AI support in Vertex AI generally available, giving developers access to foundation models including PaLM 2, Imagen, and Codey through the platform's Model Garden and the newly launched Generative AI Studio. At the time of this launch, Model Garden included over 60 models from Google and its partners. In August 2023, at the Google Cloud Next conference, Google announced further updates to Vertex AI, including the addition of third-party models such as Claude 2 from Anthropic and Llama 2 from Meta to the Model Garden, as well as new tools called Vertex AI Extensions for connecting models to APIs for real-time data retrieval. At the same event, Vertex AI Search and Conversation were made generally available, providing enterprise search and chatbot capabilities powered by foundation models. In April 2024, at Google Cloud Next, the company introduced Vertex AI Agent Builder, a no-code tool for creating AI-powered conversational agents built on top of Gemini large language models. This brought together the existing Vertex AI Search and Conversation products with new developer tools for building generative AI experiences. == Features == === Model training === Vertex AI supports both AutoML, which enables code-free model training on tabular, image, text, or video data, and custom training, which gives users full control over the ML framework, training code, and hyperparameter tuning. The platform provides serverless training as well as dedicated training clusters with GPU and TPU accelerators. Vertex AI Vizier handles automatic hyperparameter tuning, and Vertex AI Experiments allows comparison and tracking of training runs. === Model Garden === The Vertex AI Model Garden is a curated catalog of over 200 enterprise-ready models, including Google's own foundation models (such as Gemini, Imagen, and Veo), third-party models (such as Anthropic's Claude and Mistral AI models), and popular open-source models (such as Llama and Gemma). Models are accessible as fully managed model-as-a-service APIs. === Pipelines (workflow orchestration) === Vertex AI Pipelines provides managed orchestration of ML workflows and supports pipelines built with the Kubeflow Pipelines SDK, among other options described in Google Cloud documentation. === Vertex AI Studio === Vertex AI Studio provides tools for prompt design, testing, and model management, allowing developers to prototype and build generative AI applications using natural language, code, images, or video. === Agent Builder and Agent Engine === Vertex AI Agent Builder is a suite of products for building, deploying, and governing AI agents in production environments. It supports development with the open-source Agent Development Kit (ADK) and other frameworks. Vertex AI Agent Engine provides the underlying infrastructure for deploying and scaling agents, with support for enterprise security features including HIPAA compliance, customer-managed encryption keys (CMEK), and VPC Service Controls. === Generative AI tooling and model access === Google markets Vertex AI as providing access to Google foundation models (including the Gemini family) and developer tools such as Vertex AI Studio, along with a model catalog that includes Google and selected open source models (marketed as "Model Garden"). Google has also offered products within Vertex AI aimed at building generative search and conversational applications, including offerings named "Vertex AI Search" and "Vertex AI Conversation" as reported in 2023 coverage of platform updates. === MLOps tools === The platform includes a range of MLOps capabilities: Vertex AI Pipelines for orchestrating and automating ML workflows as reusable pipelines. Vertex AI Feature Store for serving, sharing, and reusing ML features across projects. Vertex AI Model Registry for storing, versioning, and managing trained models. Vertex AI Model Monitoring for detecting training-serving skew and inference drift in deployed models. Vertex Explainable AI for interpreting model predictions. Vertex AI Workbench for managed JupyterLab notebook environments integrated with Google Cloud Storage and BigQuery. == Industry recognition == Google was named a Leader for the fifth consecutive year in the 2024 Gartner Magic Quadrant for Cloud AI Developer Services, a recognition that encompasses Vertex AI and its related offerings. Google was also recognized as a Leader in the 2024 Gartner Magic Quadrant for Data Science and Machine Learning Platforms and was named a Leader in the Forrester Wave for AI/ML Platforms, Q3 2024. In October 2025, Google was also named a Leader in the 2025 IDC (International Data Corporation) MarketScape for Worldwide GenAI Life-Cycle Foundation Model Software. == Pricing == Vertex AI uses a pay-as-you-go pricing model, with costs determined by the specific services consumed, including model training, prediction serving, and data storage. For generative AI tasks, pricing is based on a per-token model, with rates varying depending on the specific model used and whether tokens are input or output. Google offers a free tier for new users, which includes limited custom training hours and online prediction usage, along with an introductory US$300 in Google Cloud credits valid for 90 days. == Adoption == In the year following its 2021 launch, Google reported that usage of Vertex AI and BigQuery had driven 2.5 times more machine learning predictions compared to the prior year, and that active customers of Vertex AI Workbench had grown 25-fold over a six-month period. Early enterprise adopters included Ford, Wayfair, and Seagate, among others. Wayfair reported that it was able to run large model training jobs 5 to 10 times faster using the platform.

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  Battleboarding

  Battleboarding, also known as versus debating and "who would win" debating, is an activity that involves discussing and debating around hypothetical fights between individuals; most popularly, fictional characters. These debates are often held in forums, blogs, sites and wikis, known as versus sites or battle boards. Netizens who engage in battleboarding online are often called "battleboarders". The earliest iterations of battleboarding first appeared in various online boards and forums, though its origins can be traced back to magazines, television shows, and comic book letter columns. Eventually, the online activity grew, becoming one of the most popular internet activities today, and spawning many online communities dedicated solely for battleboarding. It soon evolved into its own subculture, and even went on to inspire other media. == History == === Origins === Before the advent of the internet, articles about hypothetical fights were published in magazines. These articles range from topics like sports, comics and anime, such as Black Belt Magazine issue May 1997 which discussed about a hypothetical match between Muhammad Ali and Bruce Lee, and Wizard Magazine #133 which discussed about various hypothetical fights between American comic characters against Japanese anime characters. During that time, many comic book publishers also conceptualized and published "versus" storylines like Batman Versus Predator and Justice League/Avengers. Many films also capitalized on the concept of characters from different franchises fighting each other, such as Frankenstein Meets the Wolf Man (1934), King Kong vs. Godzilla (1962), Freddy vs Jason (2003), and Alien vs. Predator (2004). Another inspiration behind battleboarding were television shows and documentaries whose premise involved hypothetical fights concerning a variety of subjects like zoology, paleontology, and military history. These include shows such as Animal Face-Off (which pitted animals against each other), Deadliest Warrior (which pitted historical warriors, oftentimes from different time periods, against each other), and Jurassic Fight Club (which was about analyzing cases where different types of dinosaurs fought one another). Death Battle, a web series about pitting characters against each other that began in 2010, is a similar show that soon inspired many battleboarding communities and fandoms. Death Battle, as with many other battleboarding series and websites before it, utilised "calcs", which are mathematical equations that try to calculate how strong a character or weapon is. Other popular web series about the subject include Super Power Beat Down and Grudge Match. === Forums and sites === Many internet forums about movies, comics, anime, and video games often held discussions about hypothetical fights between characters from these media. These discussions would be the first iteration of online battleboarding. A notable early battleboarding website was stardestroyer.net (founded 1998), created by Michael Wong. The website focuses in large part on match-ups between the Star Wars and Star Trek franchises, and also includes a forum covering this as well as other more general battleboarding topics, usually related to science fiction and space opera. In addition to the forums, several webpages written by the administrators and contributors were embedded on the site. These attempted to mathematically quantify the capabilities of Star Wars technology and prove their superiority to their Star Trek equivalents, such as Wong's "Star Wars vs Star Trek: Technology Overview" and Brian Young's "Turbolaser Commentaries." stardestroyer.net had a notable impact on early battleboarding culture and also influenced official products. Curtis Saxton, author of several officially-licensed Star Wars technical reference books, thanked Wong, Young, and several other stardestroyer.net contributors by name in the acknowledgements section of Star Wars: Attack of the Clones Incredible Cross-Sections (2002), referring to them as "prominent among the hundreds of people contributing to constructive debates about Star Wars technicalities over the years, resulting in the consensus of conceptual and physical foundations applied in these pages." Saxton's books in the Incredible Cross-Sections series contain specific numbers about the capabilities of Star Wars ships original to these publications and not used in any other official sources. In an interview conducted by TheForce.Net, Saxton claimed to have been offered the job of writing reference books by a DK employee familiar with his "Star Wars Technical Commentaries" webpage (1995–2001), where Saxton attempted to calculate the firepower, speed, and durability of Star Wars spaceships using his background as an astrophysics student. One of the oldest and longest-running battleboarding forum is Comic Vine's "battle forum", whose first post was in 2007. Comic Vine also has one of the largest impacts on battleboarding, creating many common rules and terminologies such as "bloodlusted", "morals are off", "speed equalized", and many others. Another long-running battle forum is a subreddit called r/whowouldwin, where redditors can post and debate fights about real or fictional individuals. Verdicts of these match-ups are often chosen by using evidences of a character's power, weakness, or feat, such as movie clips, comic book panel scans, and excerpts from related literature; all of which are posted and categorized in a separate subreddit called r/respectthreads. Other influential battle forums include Fanverse, where users can post their own calcs about a character's power level. The popularity of battle forums inspired the creation of websites dedicated only for battleboarding. These include The Outskirts Battle Dome, a website that popularized the use of "power levels" in battleboarding; the aforementioned stardestroyer.net; and Space Battles, a website whose forums and threads are filled with posts about hypothetical fights between characters as well as other related topics. Another influential battleboarding site is the now defunct Fact Pile, and its sister site, FactPileTopia. Fact Pile is one of the first battleboarding site that actually listed down and documented winners of their match-ups. The site closed down in 2016 along with its forum, wikia, and YouTube channel. Besides these, blogs about battleboarding were also created, such as dreager1.com. === Wikis === Nowadays, the most popular battleboarding communities can be seen in Fandom, with two of the oldest and most popular being Deadliest Fiction and VS Battles Wiki. Deadliest Fiction is a Deadliest Warrior-inspired fanon created in July 2010 by a group of historians, academics, and pop culture enthusiasts. Being one of the most influential and accurate battleboarding sites around, Deadliest Fiction allows users to create hypothetical match-ups in the form of blogs, where other users can vote and debate around who will win in the comment section. Once a verdict is reached, the site allows the user to create a simulated fanfiction of how the fight would happen. The same year in October, a similar battleboarding site named VS Battles Wiki was created. In the VS Battles Wiki, users can create profiles and power levels of characters, post match-ups in its threads and forums, and list down the winners and losers of these threads in said character profiles. The wiki is considered the most active wiki battleboarding site today, with over 1 million visitors per month. However, throughout the years, the VS Battles Wiki has had its share of controversies, such as alleged inaccuracies in its profiles. There have also been websites and fanfiction wikis inspired by the battleboarding internet show Death Battle. These include the long-running G1 Death Battle Fan Blog, r/deathbattlematchups, and the popular Death Battle Fanon Wiki and DBX Fanon Wiki. Death Battle also released its own dice and card game, complete with rules and effects taken from battleboarding. == Subculture == In its rise in popularity, battleboarding has given birth to a unique online subculture with its own rules, activities, and terminologies. Several of these influences have become present in other online communities and popular media. Some of the common slang and terminologies used in battleboarding subculture includes: Battle Field Removal: Often abbreviated to "BFR", this is a rule that a fight can end if one character is taken out of a battlefield. This rule is used for characters who have the powers to teleport or transport enemies without actually killing them. Battle Royale: A term originating from Comic Vine in which multiple characters are pitted against each other. The name is probably derived from the film Battle Royale or the video game genre of the same name. Bloodlusted: A hypothetical situation wherein the characters are pitted against each other while in a furious, berserker-like state. Calc: These are calculations battl

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  Packard Bell Statesman

  The Packard Bell Statesman was an economy line of notebook-sized laptops introduced in 1993 by Packard Bell. They were slower in performance and lacked features compared to most competitor products, but they were lower in price. It was created in a collaboration between Packard Bell and Zenith Data Systems. The Statesman series was essentially a rebrand of Zenith Data Systems Z-Star 433 series, with the only notable difference of the logo in the middle and text on the front bezel. == History == In June 1993 Zenith Data Systems announced an alliance with Packard Bell. Zenith acquired about 20% of Packard Bell and they would both now work together to design and build PC's. Zenith would also provide Packard Bell with private-label versions of their portable PC's. The Packard Bell Statesman was a rebrand of the Zenith Z-Star notebook computer series. While the Statesman was being advertised by Packard Bell, the Z-Star series was also still being sold by Zenith. The Statesman was first introduced on October 4, 1993. Prices started at $1,500 for a monochrome or color DSTN model with a 33 MHz Cyrix Cx486SLC, 4 MB of RAM, 200 MB hard disk drive, internal 1.44 MB floppy disk drive, and MS-DOS 6.0 with Windows 3.1 for the included software. A "J mouse" pointing device was included, similar to the TrackPoint. The Statesman was expected to begin shipping within the next few weeks. == Specifications == === Hardware === CPU The first two models, the 200M and 200C, used the Cyrix Cx486SLC. This was Cyrix's first processor, which was a 386SX pin-compatible chip with on-board L1 cache and 486 instructions, being known as a "hybrid chip". The processor was clocked at 33 MHz and had 1 KB of L1 cache. It was a 16-bit processor and was pin compatible with the Intel 80386SX. On the bottom of the unit, the motherboard had an empty socket for a Cyrix FasMath co-processor, which could improve floating-point math performance. The 200M and 200C plus models had a Cyrix Cx486SLC2 clocked at 50 MHz, which was 50% faster than the original 486SLC. The SLC2 similarly had 1 KB of on-board cache and was pin compatible with the previous model. Graphics & Display For video all models used three versions of the Chips & Technologies 655xx, the CT65520, 65525, and 65530. The 65520 was first introduced in early 1992 as the first controller with Super VGA resolution. It supported resolutions up to 1024x768 in 16 colors or shades of gray. If in 800x600 resolution, it can display up to 256 colors. All 3 chips were the same, with the CT65525 identifying as a CT65530. The CT65530 had an ability of 5V and 3.3V mixed operation and linear video memory addressing. All models used a 9.5in 800x600 resolution DSTN LCD. The 200M and 200M Plus had a monochrome display, while the 200C and 200C Plus had a color display. Audio All models had only basic audio available, with just a piezo speaker soldered onto the motherboard and no sound controller. Memory Standard RAM included was 4-8 MB of EDO RAM. The RAM was on a proprietary SIPP package that could only be upgraded to 12 MB maximum if the user had compatible modules. Storage For storage all models used a hard drive with a size of 100 or 200 MB, and all models had an internal 1.44 MB floppy disk drive located on the side of the unit. The maximum capacity hard drive compatible if the user wanted to upgrade was 500 MB.Ports & Expansion For ports all models had 1x serial, 1x parallel, 1x VGA output, and 1x PS/2 keyboard/mouse input. For expansion all models only had one PCMCIA type II slot. Keyboard & Mouse All models used a small-scale keyboard with control keys. One interesting feature of the keyboard is that the J key also acted as a mouse, working similar to IBM's ThinkPad TrackPoint. On some models additional keys such as S, D, F, G and space let you do other mouse actions such as right click, left click, double click, and middle mouse click. === Software === The series shipped with MS-DOS and Windows 3.1 as the included operating system. == Model Comparison == Statesman 200M — The first Statesman model, it came with a DSTN monochrome screen, and a Nickel-cadmium battery pack which could last up to 4 hours. It weighed 7.4 lb and was $1500. Statesman 200C — The second Statesman model, it was the same as the 200M with the only notable differences of a DSTN color display rather than monochrome and a slightly decreased battery life of about 3 hours. It cost $700 more than the 200M at $2200. Statesman 200M/200C Plus — The 200M/200C Plus were both identical to their previous base models, with the only difference of them having a Cx486SLC2 running at 50 MHz. In 1994 it cost around $2,295 for the 200C plus with 4 MB of ram, with 8 MB costing an extra $400. == Reception == The Statesman received fair reception, with most reviewers giving positivity for the low price and high battery life, but mainly criticizing the performance and screen quality of the model line. A review by PC World writer Rex Farrance and Owen Linderholm said the 200M had a good price, being only $1500, and a good battery life which lasted about 4 hours. In benchmarks however, the 200M performed "noticeably below the average". It was noted that the 200M's worst feature was its monochrome display, being "cloudy and a bit dim for our tastes". The J mouse was considered a decent choice, and was said to be "highly usable" after some practice. The 200M was listed as number 3 on PC World's top 20 budget PC list. PC World also reviewed the 200C, saying the color display is only a "marginal, although an improvement on the monochrome version". The 200C placed 9 on the PC World top 20 budget PC list. Compute! Magazine reviewed the 200C Plus in September 1994 stating it "lagged far behind the others, especially the DXs, but then speed isn't everything". It was given pros for low cost and good display, but criticized for its low performance, not having a trackball, and poor external monitor support.

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