AI Chatbot Questionnaire

AI Chatbot Questionnaire — independent reviews, comparisons, pricing and step-by-step guides on Aizhi.

  • Artificial psychology

    Artificial psychology

    Artificial psychology (AP) has had multiple meanings dating back to 19th century, with recent usage related to artificial intelligence (AI).Artificial psychology is a theoretical field related to artificial intelligence, cognitive science, and psychology, which explores how advanced AI systems may develop human-like decision-making processes. In 1999, Zhiliang Wang and Lun Xie presented a theory of artificial psychology based on artificial intelligence. They analyze human psychology using information science research methods and artificial intelligence research to probe deeper into the human mind. == Main Theory == Dan Curtis (b. 1963) proposed AP is a theoretical discipline. The theory considers the situation when an artificial intelligence approaches the level of complexity where the intelligence meets two conditions: Condition I A: Makes all of its decisions autonomously B: Is capable of making decisions based on information that is New Abstract Incomplete C: The artificial intelligence is capable of reprogramming itself based on the new data, allowing it to evolve. D: And is capable of resolving its own programming conflicts, even in the presence of incomplete data. This means that the intelligence autonomously makes value-based decisions, referring to values that the intelligence has created for itself. Condition II All four criteria are met in situations that are not part of the original operating program When both conditions are met, then, according to this theory, the possibility exists that the intelligence will reach irrational conclusions based on real or created information. At this point, the criteria are met for intervention which will not necessarily be resolved by simple re-coding of processes due to extraordinarily complex nature of the codebase itself; but rather a discussion with the intelligence in a format which more closely resembles classical (human) psychology. If the intelligence cannot be reprogrammed by directly inputting new code, but requires the intelligence to reprogram itself through a process of analysis and decision based on information provided by a human, in order for it to overcome behavior which is inconsistent with the machines purpose or ability to function normally, then artificial psychology is by definition, what is required. The level of complexity that is required before these thresholds are met is currently a subject of extensive debate. The theory of artificial psychology does not address the specifics of what those levels may be, but only that the level is sufficiently complex that the intelligence cannot simply be recoded by a software developer, and therefore dysfunctionality must be addressed through the same processes that humans must go through to address their own dysfunctionalities. Along the same lines, artificial psychology does not address the question of whether or not the intelligence is conscious. As of 2022, the level of artificial intelligence does not approach any threshold where any of the theories or principles of artificial psychology can even be tested, and therefore, artificial psychology remains a largely theoretical discipline. Even at a theoretical level, artificial psychology remains an advanced stage of artificial intelligence.

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  • Webby Awards

    Webby Awards

    The Webby Awards (colloquially referred to as the Webbys) are awards for excellence on the Internet presented annually by the International Academy of Digital Arts and Sciences, a judging body composed of over three thousand industry experts and technology innovators. Categories include websites, advertising and media, online film and video, mobile sites and apps, and social. Two winners are selected in each category, one by members of The International Academy of Digital Arts and Sciences, and one by the public who cast their votes during Webby People's Voice voting. Each winner presents a five-word acceptance speech, a trademark of the annual awards show. In its early years, the award was hailed as the "Internet's highest honor" and was associated with the phrase "The Oscars of the Internet." == History == In its early years, the organization was one of several vying to be the premiere internet awards show. Both shows would compare themselves to the Oscars, as did media outlets such as The New York Times to Canada's Globe & Mail. The winners of the First Annual Webby Awards in 1995 were presented by John Brancato and Michael Ferris, writers for Columbia Pictures. It was held at the Hollywood Roosevelt Hotel. The televised Webby Awards were sponsored by the Academy of Web Design and Cool Site of the Day. The first Webby Awards were produced by Kay Dangaard at the Hollywood Roosevelt Hotel as a nod to the first site of the Academy of Motion Picture Arts and Sciences (Oscars). That first year, they were called "Webbie" Awards. The first "Site of the Year" winner was the pioneer webisodic serial The Spot. The modern Webby Awards were co-founded by Tiffany Shlain, a filmmaker, when she was hired by The Web Magazine to re-establish them, and were first held in San Francisco in 1997. They quickly became known for its requirement that winners give their acceptance speeches in five words. After this, the awards became more successful than the magazine and IDG closed the publication. Shlain and co-founder Maya Draisin Farrah continued to run The Webby Awards until 2004. The International Academy of Digital Arts and Sciences, which selects the winners of The Webby Awards, was established in 1998 by co-founders Tiffany Shlain, Spencer Ante and Maya Draisin. Members of the Academy include Kevin Spacey, Grimes, Questlove, Internet inventor Vint Cerf, Instagram's Head of Fashion Partnerships Eva Chen, comedian Jimmy Kimmel, Twitter founder Biz Stone, Vice Media co-founder and CEO Shane Smith, Tumblr's David Karp, Director of Harvard's Berkman Klein Center for Internet & Society Susan P. Crawford, Refinery29's Executive Creative Director Piera Gelardi, and CEO and co-founder of Gimlet Media Alex Blumberg. The Webby Awards is owned and operated by the Webby Media Group, a division of Recognition Media, which also owns and produces the Lovie Awards in Europe and Netted by the Webbys, a daily email publication launched in 2009. David-Michel Davies, CEO of Webby Media Group, current Executive Director of the Webby Awards and co-founder of Internet Week New York, was named Executive Director of the Webby Awards in 2005. In 2009, the 13th Annual Webby Awards received nearly 10,000 entries from all 50 US states and over 60 countries. That same year, more than 500,000 votes were cast in The Webby People's Voice Awards. In 2012, the 16th Annual Webby awards received 1.5 million votes from more than 200 countries for the People's Voice awards. In 2015, the 19th Annual Webby Awards received nearly 13,000 entries from all 50 U.S. states and over 60 countries worldwide. == Nomination process == The 2000 awards began the transition to nominee submissions. Previously, nominees had been selected by an internal committee. As early as 2017, organizations wanting to nominate themselves were charged $395 for a single entry. An "ad campaign entry" would cost $595. By 2024, those fees had risen to $495 and $675, respectively. Executive Academy Members with category-specific expertise evaluate the shortlisted entries based on the appropriate Website, Advertising & Media, Online Film & Video, Mobile Sites & Apps, and Social category criteria, and cast ballots to determine Webby Honorees, Nominees and Webby Winners. Deloitte provides vote tabulation consulting for the Webby Awards. In addition to the award given in each category by the International Academy of Digital Arts and Sciences, another winner is selected in each category as determined by the general public during People's Voice voting. Winners of both the Academy-selected and People's Voice-selected awards are invited to the Webbys. == Awards granted == The Webby Awards are presented in over a hundred categories among all four types of entries. A website can be entered in multiple categories and receive multiple awards. In each category, two awards are handed out: a Webby Award selected by The International Academy of Digital Arts and Sciences, and a People's Voice Award selected by the general public. == Ceremony == Between 2005 and 2019, the Webby Awards were presented in New York City. Many of the ceremony hosts are comedians and comedic actors. Comedian Rob Corddry hosted the ceremony from 2005 to 2007. Seth Meyers of Saturday Night Live hosted in 2008 and 2009, B.J. Novak of the sitcom The Office in 2010, and Lisa Kudrow in 2011. Comedian, actor, and writer Patton Oswalt hosted from 2012 to 2014. Comedian Hannibal Buress hosted in 2015. The Webbys are famous for limiting recipients to five-word speeches, which are often humorous, although some exceed the limit. In 2005 when accepting his Lifetime Achievement Award, former Vice President Al Gore's speech was "Please don't recount this vote." He was introduced by Vint Cerf who used the same format to state, "We all invented the Internet." In 2013, the creator of the Graphics Interchange Format (GIF), Steve Wilhite, accepted his Webby and delivered his now famous five-word speech, "It's pronounced 'Jif' not 'Gif'." == Criticism == The Webbys have been criticized for their pay-to-enter and pay-to-attend policy (winners and nominees also have to pay to attend the award ceremony), and thus for not taking most websites into consideration before distributing their awards. Gawker, its Valleywag column, and others, have called the awards a scam, with Valleywag saying, "...somewhere along the way, the organizers figured out that this goofy charade could be milked for profit." In response, Webby Awards executive director David-Michel Davies told the Wall Street Journal that entry fees "provide the best and most sustainable model for ensuring that our judging process remains consistent and rigorous and is not dependent on things like sponsorships that can fluctuate from year to year." == Anthem Awards == In 2021, the Webby organization started a new line of awards, the Anthem Awards, to honor the purpose and mission-driven work of people, companies and organizations worldwide. The finalists and winners are selected by the International Academy of Digital Arts and Sciences.

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  • Information Age

    Information Age

    The Information Age is a historical period that began in the mid-20th century. It is characterized by a rapid shift from traditional industries, as established during the Industrial Revolution, to an economy centered on information technology. The onset of the Information Age has been linked to the development of the transistor in 1947. Advances in computer miniaturization, internet communication, and semiconductor technology enabled the rapid expansion of digital systems and global information networks. The Information Age transformed industries such as education, healthcare, finance, entertainment, and communication through digital infrastructure and connected technologies. The rise of smartphones and cloud-based services further accelerated global internet accessibility and digital interaction. == Digital applications and mobile technology == The expansion of Android and iOS ecosystems during the 21st century contributed to the widespread use of utility applications and mobile productivity tools. Applications related to calculations, scheduling, digital organization, and educational support became increasingly common on smartphones and tablets. Mobile utility software demonstrates how modern digital platforms support accessibility and everyday online services. Independent developers have contributed to this technological ecosystem through lightweight applications focused on mobile usability and internet-based functionality. == Influence on modern society == The Information Age has reshaped the way individuals communicate, consume information, and interact with digital services. Social media platforms, artificial intelligence systems, cloud storage, and mobile computing continue to influence modern economies and online communities worldwide. Emerging technologies such as the Internet of things, machine learning, and advanced automation are often associated with the transition toward the Fourth Industrial Revolution. == History == The digital revolution converted technology from analog format to digital format. By doing this, it became possible to make copies that were identical to the original. In digital communications, for example, repeating hardware was able to amplify the digital signal and pass it on with no loss of information in the signal. Of equal importance to the revolution was the ability to easily move the digital information between media and to access or distribute it remotely. One turning point of the revolution was the change from analog to digitally recorded music. During the 1980s, the digital format of optical compact discs gradually replaced analog formats, such as vinyl records and cassette tapes, as the popular medium of choice. === Previous inventions === Humans have manufactured tools for counting and calculating since ancient times, such as the abacus, astrolabe, equatorium, and mechanical timekeeping devices. More complicated devices started appearing in the 1600s, including the slide rule and mechanical calculators. By the early 1800s, the Industrial Revolution had produced mass-market calculators like the arithmometer and the enabling technology of the punch card. Charles Babbage proposed a mechanical general-purpose computer called the Analytical Engine, but it was never successfully built, and was largely forgotten by the 20th century, and unknown to most of the inventors of modern computers. The Second Industrial Revolution, in the last quarter of the 19th century, developed useful electrical circuits and the telegraph. In the 1880s, Herman Hollerith developed electromechanical tabulating and calculating devices using punch cards and unit record equipment, which became widespread in business and government. Meanwhile, various analog computer systems used electrical, mechanical, or hydraulic systems to model problems and calculate answers. These included an 1872 tide-predicting machine, differential analysers, perpetual calendar machines, the Deltar for water management in the Netherlands, network analyzers for electrical systems, and various machines for aiming military guns and bombs. The construction of problem-specific analog computers continued in the late 1940s and beyond, with FERMIAC for neutron transport, Project Cyclone for various military applications, and the Phillips Machine for economic modeling. Building on the complexity of the Z1 and Z2, German inventor Konrad Zuse used electromechanical systems to complete in 1941 the Z3, the world's first working programmable, fully automatic digital computer. Also, during World War II, Allied engineers constructed electromechanical bombes to break the German Enigma machine encoding. The base-10 electromechanical Harvard Mark I was completed in 1944, and was to some degree improved with inspiration from Charles Babbage's designs. === 1947–1969: Origins === In 1947, the first working transistor, the germanium-based point-contact transistor, was invented by John Bardeen and Walter Houser Brattain while working under William Shockley at Bell Labs. This led the way to more advanced digital computers. From the late 1940s, universities, the military, and businesses developed computer systems to digitally replicate and automate previously manually performed mathematical calculations, with the LEO being the first commercially available general-purpose computer. Digital communication became economical for widespread adoption after the invention of the personal computer in the 1970s. Claude Shannon, a Bell Labs mathematician, is generally credited with laying the foundations of digitalization in his pioneering 1948 article, A Mathematical Theory of Communication. In 1948, Bardeen and Brattain patented an insulated-gate transistor (IGFET) with an inversion layer. Their concept forms the basis of CMOS and DRAM technology today. In 1957, at Bell Labs, Frosch and Derick were able to manufacture planar silicon dioxide transistors, later a team at Bell Labs demonstrated a working MOSFET. The first integrated circuit milestone was achieved by Jack Kilby in 1958. Other important technological developments included the invention of the monolithic integrated circuit chip by Robert Noyce at Fairchild Semiconductor in 1959, made possible by the planar process developed by Jean Hoerni. In 1963, complementary MOS (CMOS) was developed by Chih-Tang Sah and Frank Wanlass at Fairchild Semiconductor. The self-aligned gate transistor, which further facilitated mass production, was invented in 1966 by Robert Bower at Hughes Aircraft and independently by Robert Kerwin, Donald Klein, and John Sarace at Bell Labs. In 1962, AT&T deployed the T-carrier for long-haul pulse-code modulation (PCM) digital voice transmission. The T1 format carried 24 pulse-code modulated, time-division multiplexed speech signals, each encoded in 64 kbit/s streams, leaving 8 kbit/s of framing information, which facilitated the synchronization and demultiplexing at the receiver. Over the subsequent decades, the digitisation of voice became the norm for all but the last mile (where analogue continued to be the norm right into the late 1990s). Following the development of MOS integrated circuit chips in the early 1960s, MOS chips reached higher transistor density and lower manufacturing costs than bipolar integrated circuits by 1964. MOS chips further increased in complexity at a rate predicted by Moore's law, leading to large-scale integration (LSI) with hundreds of transistors on a single MOS chip by the late 1960s. The application of MOS LSI chips to computing was the basis for the first microprocessors, as engineers began recognizing that a complete computer processor could be contained on a single MOS LSI chip. In 1968, Fairchild engineer Federico Faggin improved MOS technology with his development of the silicon-gate MOS chip, which he later used to develop the Intel 4004, the first single-chip microprocessor. It was released by Intel in 1971 and laid the foundations for the microcomputer revolution that began in the 1970s. MOS technology also led to the development of semiconductor image sensors suitable for digital cameras. The first such image sensor was the charge-coupled device, developed by Willard S. Boyle and George E. Smith at Bell Labs in 1969, based on MOS capacitor technology. === 1969–1989: Invention of the internet, rise of home computers === The public was first introduced to the concepts that led to the Internet when a message was sent over the ARPANET in 1969. Packet switched networks such as ARPANET, Mark I, CYCLADES, Merit Network, Tymnet, and Telenet, were developed in the late 1960s and early 1970s using a variety of protocols. The ARPANET in particular led to the development of protocols for internetworking, in which multiple separate networks could be joined into a network of networks. The Whole Earth movement of the 1960s advocated the use of new technology. In the 1970s, the home computer was introduced, time-sharing computers, the video game console, the first coin-op vide

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  • Media preservation

    Media preservation

    Preservation of documents, pictures, recordings, digital content, etc., is a major aspect of archival science. It is also an important consideration for people who are creating time capsules, family history, historical documents, scrapbooks and family trees. Common storage media are not permanent, and there are few reliable methods of preserving documents and pictures for the future. == Paper/prints (photos) == Color negatives and ordinary color prints may fade away to nothing in a relatively short period if not stored and handled properly. This happens even if the negatives and prints are kept in the dark, because ambient light is not the determining factor, but heat and humidity are. The color degradation is the result of the dyes used in the color processes. Because color processing results in a less stable image than traditional black-and-white processing, black-and-white pictures from the 1920s are more likely to survive long-term than color films and photographs from after the middle 20th century. Black-and-white photographic films using silver halide emulsions are the only film types that have proven to last for archival storage. The determining factors for longevity include the film base type, proper processing (develop, stop, fix and wash) and proper storage. Early films used a Cellulose nitrate base which was prone to decomposition and highly flammable. Nitrate film was replaced with acetate-base films. These Cellulose acetate films were later discovered to outgass acids (also referred to as vinegar syndrome). Acetate films were replaced in the early 1980s by polyester film base materials which have been determined to be more stable than film stocks with a nitrate or acetate base. Color prints made on most inkjet printers look very good at first but they have a very short lifespan, measured in months rather than in years. Even prints from commercial photo labs will start to fade in a matter of years if not processed properly and stored in cool, dry environments. == Documents/books == With documents for which the media are not so critical as what the documents contain, the information in documents can be copied by using photocopiers and image scanners. Books and manuscripts can also have their information saved without destruction by using a book scanner. Where the medium itself needs to be preserved, for example if a document is a crayon sketch by a famous artist on paper, a complex process of preservation may be used. Depending on the condition and importance of the item this can include gluing the media onto more stable media, or protective enclosing of the media. Polyester sleeves, acid-free folders, and pH buffered document boxes are common supportive protective enclosures whose selection must match the media's chemical and physical properties. Other considerations in preserving paper/books are: Damaging light, particularly UV light, which fades and destroys media over time by breaking down the molecules. Atmosphere contains small traces of sulfur dioxide and nitric acid which turn media yellow and break the fibers down. Humidity and moisture also aid in the breakdown of media. If there is too much, the document can be attacked by bacteria, and if too little, cellulose material breaks down. Temperature, particularly elevated ones, can destroy some media. Low temperatures can cause the water to form crystals which expands destroying the structure of paper-based documents. == Online photo albums == Although there are many websites that allow the upload of photographs and videos, digital preservation for the long-term is still considered an issue. There is a lack of confidence that such websites are capable of storing data for long periods of time (ex. 50 years) without data degradation or loss. == Optical media - CD, DVD, Blu-ray, M-Disc == Write-once optical media, such as CD-Rs and DVD-Rs, typically contain an organic dye that distinguishes data reading from data writing based on the dye's transparency along the disc. Conventional CDs and DVDs have finite shelf-life due to natural degradation of the dye; the newer M-DISC uses inorganic material technology to produce molded DVDs and Blu-Rays (up to 3-layer 100GB BDXL) with a claimed lifespan of 100-1000 years if stored correctly with most BD & BDXL rated read/writers enabling the higher power mode for the M-Disc format after 2011. The National Archives and Records Administration lists published life expectancies to be 10 or 25 years or more for normal CDs and DVDs and conservative life expectancies to be between 2 and 5 years. Storage environments, such as temperature and humidity, as well as handling conditions such as frequency of media use and compatibility between the recorder and media, affect media shelf-life. Improvements in media storage and migrations to new recording technologies can make certain formats obsolete within their respective lifespan. Technologists have pointed to internet streaming services, where services such as video-on-demand have contributed to the 33 percent decline in DVD sales the past 5 years, as a challenge for digital preservation. == Magnetic media - video cassettes, tapes, hard drives == Magnetic media such as audio and video tape and floppy disks also have limited life spans. Audio and video tapes require specific care and handling to ensure that the recorded information will be preserved. For information that must be preserved indefinitely, periodic transcription from old media to new ones is necessary, not only because the media are unstable but also because the recording technology may become obsolete. Magnetic media also deteriorates naturally with typical shelf lives between 10 and 20 years. Magnetic tape can degrade from binder hydrolysis or magnetic remanence decay. Binder hydrolysis, also known as sticky-shed syndrome, refers to the breakdown of binder, or glue, that holds the magnetic particles to the polyester base of the tape. Tapes which have been stored in hot, humid conditions are particularly vulnerable to this phenomenon and may suffer from accelerated degradation. Severe binder can cause the magnetic material to fall off or sheds from the base, leaving a pile of dust and clear backing. Archivists can bake the tape, which evaporates water molecules on the tape, to temporarily restore the binder before making a copy. Magnetic tape can also be destabilized by magnetic remanence decay, which refers to the weakening of the tape's magnetization over time. This weakens the affected tape's readability, leading to reduced sound clarity and volume or picture hue and contrast. Baking the tape will not restore magnetization. Media at risk include recorded media such as master audio recordings of symphonies and videotape recordings of the news gathered over the last 40 years. Threats to media that must be considered when archiving important record media include accidental erasure, physical loss due to disasters such as fires and floods, and media degradation. Along with the actual media being degraded over the years, the machines that are available to play back or reproduce the audio sources are becoming archaic themselves. Manufacturers and their support (parts, technical updates) for their machines have disappeared throughout the years. Even if the medium is vaulted and archived correctly, the mechanical properties of the machines have deteriorated to the point that they could do more harm than good to the tape being played. Many major film studios are now backing up their libraries by converting them to electronic media files, such as .AIFF or .WAV-based files via digital audio workstations. That way, even if the digital platform manufacturer goes out of business or no longer supports their product, the files can still be played on any common computer. There is a detailed process that must take place previous to the final archival product now that a digital solution is in place. Sample rates and their conversion and reference speed are both critical in this process. In floppy disks, the lubricants inside the plastic jackets of many older floppies promote the decay of the magnetic medium. Also, the alignment of the magnetic particles of the disk substrate may gradually degrade, leading to a loss of formatting and data. Early laser disk media were prone to degradation as the layers of the disk substrate were bonded with an adhesive that was vulnerable to decay and would crumble over time. This would lead the different layers of the disk to peel apart, damaging the pitted data surface and rendering the disk unreadable.

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  • Information schema

    Information schema

    In relational databases, the information schema (information_schema) is an ANSI-standard set of read-only views that provide information about all of the tables, views, columns, and procedures in a database. It can be used as a source of the information that some databases make available through non-standard commands, such as: the SHOW command of MySQL the DESCRIBE command of Oracle's SQLPlus the \d command in psql (PostgreSQL's default command-line program). => SELECT count(table_name) FROM information_schema.tables; count ------- 99 (1 row) => SELECT column_name, data_type, column_default, is_nullable FROM information_schema.columns WHERE table_name='alpha'; column_name | data_type | column_default | is_nullable -------------+-----------+----------------+------------- foo | integer | | YES bar | character | | YES (2 rows) => SELECT FROM information_schema.information_schema_catalog_name; catalog_name -------------- johnd (1 row) == Implementation == As a notable exception among major database systems, Oracle does not as of 2015 implement the information schema. An open-source project exists to address this. RDBMSs that support information_schema include: Amazon Redshift Apache Hive Microsoft SQL Server MonetDB Snowflake MySQL PostgreSQL H2 Database HSQLDB InterSystems Caché MariaDB SingleStore (formerly MemSQL) Mimer SQL Snowflake Trino Presto CrateDB ClickHouse CockroachDB Kinetica DB TiDB RDBMSs that do not support information_schema include: Apache Derby Apache Ignite Firebird Microsoft Access IBM Informix Ingres IBM Db2 Oracle Database SAP HANA SQLite Sybase ASE Sybase SQL Anywhere Teradata Vertica

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  • International World Wide Web Conference Committee

    International World Wide Web Conference Committee

    The International World Wide Web Conference Committee (abbreviated as IW3C2 also written as IW3C2) is a professional non-profit organization registered in Switzerland (Article 60ff of the Swiss Civil Code) that promotes World Wide Web research and development. The IW3C2 organizes and hosts the annual World Wide Web Conference in conjunction with the W3C. The IW3C2 was founded by Joseph Hardin and Robert Cailliau at a meeting held in Boston, United States, on 14 August 1994 to prepare for the upcoming Second International World Wide Web Conference in Chicago. The IW3C2 formally became an incorporated entity in May 1996 at the fifth conference in Paris, France. The organization is governed by laws of the Swiss Confederation and the By-laws. == Abbreviation == The abbreviation for the International World Wide Web Conference Committee as IW3C2 is as follow: I- The I is represents the leading I in International. W3- The W3 represents the three 3 leading W's in World Wide Web. C2- The C2 represents the three 2 leading C's in Conference Committee. == Mission == The mission of the IW3C2 is: To coordinate the organization and planning of the international WWW conference series and ensure that it remains the foremost conference addressing World Wide Web research and development; To promote a collaborative spirit among conference attendees that is essential to the success of the series; To ensure the global geographical diversity of conference sites and provide support to local organizers at those sites; To make sure that all content arising from these conferences and forums is permanently and openly available on the widest possible scale; To preserve the history of the conference series; To encourage the global development of the World Wide Web through collaboration with WWW standards organizations; To provide a permanent, broad-based international body to achieve these purposes. == Conferences == The conferences are organized by the IW3C2 in collaboration with local organizing committees and technical program committees. The series provides an open forum in which all opinions can be presented, subject to a strict process of peer review. The proceedings of the conference are published in the ACM Digital Library. === Endorsed conferences === The IW3C2 has endorsed regional conferences devoted to a special topic of the Web by working with endorsed conferences on cross-promotion, publicity and programs. == Membership == Members of the IW3C2 are ordinary members, ex officio members, non-voting members, and officers. === Ordinary members === Ordinary members are elected for a period of 3 years during a general meeting. Members are nominated due to their recognition in the WWW community and represent themselves. Members can be re-elected only after at least one year of absence. The following are the founding members at the time when IW3C2 was officially incorporated in May 1996: Jean-François Abramatic Tim Berners-Lee Robert Cailliau Dale Dougherty Ira Goldstein Joseph Hardin Tim Krauskopf Detlef Krömker Corinne Moore R. P. Channing Rodgers Albert Vezza Stuart Weibel Yuri Rubinsky (died prior to incorporation) The following are the current (April 2016) ordinary members: Robin Chen Chin-Wan Chung Allan Ellis Wendy Hall - IW3C2 Chair Ivan Herman Arun Iyengar - IW3C2 Vice Chair Irwin King Yoelle Maarek Luc Mariaux - IW3C2 Treasurer Daniel Schwabe - IW3C2 Vice-Chair === Ex officio members === Ex officio members are selected from the immediate past conference general co-chairs and from future conference co-chairs. Their term expires one year after the conference they organized. Ex officio members can be elected as ordinary members. The following are current (April 2016) ex officio members and the conference with which they are affiliated: Jacqueline Bourdeau - WWW2016 James Hendler - WWW2016 Rick Barrett - WWW2017 Rick Cummings - WWW2017 Laurent Flory - WWW2018 Fabien Gandon - WWW2018 === Officers === The IW3C2 officers consist of a chairperson, a vice-chair (chairperson-elect), a secretary, a treasurer, and other appointees. Officers are elected during a general meeting (usually at the annual WWW conference) and serve for one year. They can be re-elected an indefinite number of times. == The Seoul Test of Time Award == This annual award, presented at the WWW conference, is made possible by a generous contribution from the organizers of WWW2014 (Seoul Korea). Recipients are determined by the IW3C2 and honor the author, or authors, of a paper presented at a previous WWW conference that has "stood the test of time." The first award, announced at WWW2015 (Florence Italy), recognized Sergey Brin and Larry Page, the founders of Google. The recipients of the WWW2016 award are LinkIn scientist Dr. Badrul Sarwar and University of Minnesota professors George Karypis, Joseph Konstan, and John Riedl (posthumous) for their work in item-item collaborative filtering.

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  • Quality of experience

    Quality of experience

    Quality of experience (QoE) is a measure of the delight or annoyance of a customer's experiences with a service (e.g., web browsing, phone call, TV broadcast). QoE focuses on the entire service experience; it is a holistic concept, similar to the field of user experience, but with its roots in telecommunication. QoE is an emerging multidisciplinary field based on social psychology, cognitive science, economics, and engineering science, focused on understanding overall human quality requirements. == Definition and concepts == In 2013, within the context of the COST Action QUALINET, QoE has been defined as:The degree of delight or annoyance of the user of an application or service. It results from the fulfillment of his or her expectations with respect to the utility and / or enjoyment of the application or service in the light of the user’s personality and current state.This definition has been adopted in 2016 by the International Telecommunication Union in Recommendation ITU-T P.10/G.100. Before, various definitions of QoE had existed in the domain, with the above-mentioned definition now finding wide acceptance in the community. QoE has historically emerged from Quality of Service (QoS), which attempts to objectively measure service parameters (such as packet loss rates or average throughput). QoS measurement is most of the time not related to a customer, but to the media or network itself. QoE however is a purely subjective measure from the user's perspective of the overall quality of the service provided, by capturing people's aesthetic and hedonic needs. QoE looks at a vendor's or purveyor's offering from the standpoint of the customer or end user, and asks, "What mix of goods, services, and support, do you think will provide you with the perception that the total product is providing you with the experience you desired and/or expected?" It then asks, "Is this what the vendor/purveyor has actually provided?" If not, "What changes need to be made to enhance your total experience?" In short, QoE provides an assessment of human expectations, feelings, perceptions, cognition and satisfaction with respect to a particular product, service or application. QoE is a blueprint of all human subjective and objective quality needs and experiences arising from the interaction of a person with technology and with business entities in a particular context. Although QoE is perceived as subjective, it is an important measure that counts for customers of a service. Being able to measure it in a controlled manner helps operators understand what may be wrong with their services and how to improve them. == QoE factors == QoE aims at taking into consideration every factor that contributes to a user's perceived quality of a system or service. This includes system, human and contextual factors. The following so-called "influence factors" have been identified and classified by Reiter et al.: Human Influence Factors Low-level processing (visual and auditory acuity, gender, age, mood, …) Higher-level processing (cognitive processes, socio-cultural and economic background, expectations, needs and goals, other personality traits…) System Influence Factors Content-related Media-related (encoding, resolution, sample rate, …) Network-related (bandwidth, delay, jitter, …) Device-related (screen resolution, display size, …) Context Influence Factors Physical context (location and space) Temporal context (time of day, frequency of use, …) Social context (inter-personal relations during experience) Economic context Task context (multitasking, interruptions, task type) Technical and information context (relationship between systems) Studies in the field of QoE have typically focused on system factors, primarily due to its origin in the QoS and network engineering domains. Through the use of dedicated test laboratories, the context is often sought to be kept constant. == QoE versus User Experience == QoE is strongly related to but different from the field of User Experience (UX), which also focuses on users' experiences with services. Historically, QoE has emerged from telecommunication research, while UX has its roots in Human–Computer Interaction. Both fields can be considered multi-disciplinary. In contrast to UX, the goal of improving QoE for users was more strongly motivated by economic needs. Wechsung and De Moor identify the following key differences between the fields: == QoE measurement == As a measure of the end-to-end performance at the service level from the user's perspective, QoE is an important metric for the design of systems and engineering processes. This is particularly relevant for video services because – due to their high traffic demands –, bad network performance may highly affect the user's experience. So, when designing systems, the expected output, i.e. the expected QoE, is often taken into account – also as a system output metric and optimization goal. To measure this level of QoE, human ratings can be used. The mean opinion score (MOS) is a widely used measure for assessing the quality of media signals. It is a limited form of QoE measurement, relating to a specific media type, in a controlled environment and without explicitly taking into account user expectations. The MOS as an indicator of experienced quality has been used for audio and speech communication, as well as for the assessment of quality of Internet video, television and other multimedia signals, and web browsing. Due to inherent limitations in measuring QoE in a single scalar value, the usefulness of the MOS is often debated. Subjective quality evaluation requires a lot of human resources, establishing it as a time-consuming process. Objective evaluation methods can provide quality results faster, but require dedicated computing resources. Since such instrumental video quality algorithms are often developed based on a limited set of subjective data, their QoE prediction accuracy may be low when compared to human ratings. QoE metrics are often measured at the end devices and can conceptually be seen as the remaining quality after the distortion introduced during the preparation of the content and the delivery through the network, until it reaches the decoder at the end device. There are several elements in the media preparation and delivery chain, and some of them may introduce distortion. This causes degradation of the content, and several elements in this chain can be considered as "QoE-relevant" for the offered services. The causes of degradation are applicable for any multimedia service, that is, not exclusive to video or speech. Typical degradations occur at the encoding system (compression degradation), transport network, access network (e.g., packet loss or packet delay), home network (e.g. WiFi performance) and end device (e.g. decoding performance). == QoE management == Several QoE-centric network management and bandwidth management solutions have been proposed, which aim to improve the QoE delivered to the end-users. When managing a network, QoE fairness may be taken into account in order to keep the users sufficiently satisfied (i.e., high QoE) in a fair manner. From a QoE perspective, network resources and multimedia services should be managed in order to guarantee specific QoE levels instead of classical QoS parameters, which are unable to reflect the actual delivered QoE. A pure QoE-centric management is challenged by the nature of the Internet itself, as the Internet protocols and architecture were not originally designed to support today's complex and high demanding multimedia services. As an example for an implementation of QoE management, network nodes can become QoE-aware by estimating the status of the multimedia service as perceived by the end-users. This information can then be used to improve the delivery of the multimedia service over the network and proactively improve the users' QoE. This can be achieved, for example, via traffic shaping. QoE management gives the service provider and network operator the capability to minimize storage and network resources by allocating only the resources that are sufficient to maintain a specific level of user satisfaction. As it may involve limiting resources for some users or services in order to increase the overall network performance and QoE, the practice of QoE management requires that net neutrality regulations are considered.

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  • Industry Dive

    Industry Dive

    Industry Dive is a United States-based business-to-business news organization with an estimated 18 million readers in more than 25 industries, such as banking and waste management. Since 2022, it has been owned by Informa plc. Industry Dive aims to serve business executives who read news on their mobile phones. The company had an estimated revenue of more than of more than $110 million in 2023. As of 2020, it has more than 300 employees, including 80 journalists and 12 engineers. Its headquarters is in Washington, D.C. == History == Industry Dive was formed in 2012 by Sean Griffey (president), Eli Dickinson (chief technology officer), and Ryan Willumson (chief revenue officer). It was funded with $900,000 from private investors in 2012 and 2013. The company covered five industries: construction, education, marketing, utility, and waste. In 2016, it began its Dive Awards. Industry Dive's revenues quadrupled from 2015 to 2018, putting it in the top half of the Deloitte Technology Fast 500 and the top 20 percent of the Inc. Top 5000 list. In 2019, Falfurrias Capital Partners acquired a majority stake in the company. ID's content marketing clients included IBM, Siemens, and UPS. In 2020, DCA Live named Industry Dive to its "Red Hot Companies" list, which recognizes the D.C. area's 'fastest-growing' companies. In the same year, Industry Dive acquired CFO. In 2021, Industry Dive acquired PharmaVOICE. In 2022, it was purchased by Informa plc, which bought its majority stake from Falfurrias Capital Partners for about $530 million. == Publications == Industry Dive provides news coverage of a variety of industries including agriculture, banking, construction, education, fashion, healthcare, and manufacturing, each using a different website: == Awards == Industry Dive publications have received several national and regional Awards of Excellence from the American Society of Business Publication Editors, including for a series of 2020 articles about Big Pharma and the race for the coronavirus vaccine. The Washington Post recognized Industry Dive as a top place to work for four consecutive years, from 2016 to 2020.

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  • Parkerian Hexad

    Parkerian Hexad

    The Parkerian Hexad is a set of six elements of information security proposed by Donn B. Parker in 1998. The Parkerian Hexad adds three additional attributes to the three classic security attributes of the CIA triad (confidentiality, integrity, availability). The Parkerian Hexad attributes are the following: Confidentiality Possession or Control Integrity Authenticity Availability Utility These attributes of information are atomic in that they are not broken down into further constituents; they are non-overlapping in that they refer to unique aspects of information. Any information security breach can be described as affecting one or more of these fundamental attributes of information. == Attributes from the CIA triad == === Confidentiality === Confidentiality refers to the "quality or state of being private or secret; known only to a limited few", or "the property that information is not made available or disclosed to unauthorized individuals, entities, or processes". For example: If an enterprise's strategic plans are leaked to competitors then this is a breach of confidentiality; If unauthorized persons gain access to an individual's financial records then that individual's confidentiality is breached. === Integrity === Integrity refers to being correct or consistent with the intended state of information. Any unauthorized modification of data, whether deliberate or accidental, is a breach of data integrity. For example: Data stored on disk are expected to be stable. If the data is changed at random by problems with a disk controller then this is a breach of integrity; Data generated by a medical device is transmitted and stored in the healthcare center but neither altered nor tampered with; Application programs are supposed to record information correctly. If the application introduces deviations from the intended values then this is a breach of integrity. "From Donn Parker: My definition of information integrity comes from the dictionaries. Integrity means that the information is whole, sound, and unimpaired (not necessarily correct). It means nothing is missing from the information it is complete and in intended good order". === Availability === Availability means having timely access to information. For example: A disk crash or denial-of-service attacks both cause a breach of availability. Any delay in response of a system that exceeds the expected service levels for that system can be described as a breach of availability. GPS jamming can lead to loss of Availability of the GPS system. == Parker's added attributes == === Authenticity === Authenticity is the "quality of being authentic or of established authority for truth and correctness". Parker defines it thus: "is the information genuine and accurate? Does it conform to reality and have validity?" and "authoritative, valid, true, real, genuine, or worthy of acceptance or belief by reason of conformity to fact and reality". === Possession or control === Possession or control refers to the loss of data by the authorized user (even if the ʺthiefʺ cannot access the data). From a control systems perspective, it is any loss of control (the ability to change settings and functions) or loss of view (the ability to monitor the system’s operation and its response to controls). Suppose a thief were to steal a sealed envelope containing a bank debit card and its personal identification number. Even if the thief did not open that envelope, it's reasonable for the victim to be concerned that the thief could do so at any time. That situation illustrates a loss of control or possession of information but does not involve the breach of confidentiality. === Utility === Utility refers to the data's usefulness. For example: Suppose someone encrypted data on disk to prevent unauthorized access or undetected modifications–and then lost the decryption key: that would be a breach of utility. The data would be confidential, controlled, integral, authentic, and available–they just wouldn't be useful in that form. The conversion of salary data from one currency into an inappropriate currency would be a breach of utility, as would the storage of data in a format inappropriate for a specific computer architecture; e.g., EBCDIC instead of ASCII or 9-track magnetic tape instead of DVD-ROM. A tabular representation of data substituted for a graph could be described as a breach of utility if the substitution made it more difficult to interpret the data. Utility is often confused with availability because breaches such as those described in these examples may also require time to work around the change in data format or presentation. However, the concept of usefulness is distinct from that of availability.

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  • Frictionless sharing

    Frictionless sharing

    Frictionless sharing refers to the transparent or automatic dissemination of user activity across social media platforms, typically without requiring explicit action from the user each time content is shared. The concept gained prominence in 2011 after Mark Zuckerberg announced a series of new features for Facebook at the F8 developers conference, framing the changes as enabling “real-time serendipity in a friction-less experience.” == History and concept == Before 2011, the term “frictionless sharing” was occasionally used in academic and technical contexts to describe sharing of resources with minimal effort, such as through social bookmarking or Creative Commons licensing to reduce barriers to reuse of research data. The concept took on a broader cultural meaning when Facebook introduced its Timeline interface and new “social apps” in 2011. These features enabled third-party applications to automatically publish user activity to the platform—effectively shifting sharing from a deliberate act to a passive process. For example, integrating music streaming service Spotify meant that any song a user listened to could automatically appear in a Facebook “Ticker,” allowing friends to see the activity and click through to play the song themselves. == Zuckerberg’s vision == Zuckerberg articulated a vision of a Web in which sharing occurs by default rather than by choice: “You read, you watch, you listen, you buy—and everyone you know will hear all about it on Facebook.” This “frictionless” model assumes ongoing consent after an initial opt-in. Once users connect an app to their profile, any future activity with that app may be automatically shared. This shift from intentional posting to ambient sharing represented a significant evolution in how personal data is distributed online. == Criticism and debate == Many commentators and users have raised concerns about frictionless sharing. While some criticism centers on online privacy, others focus on how automatic updates can flood news feeds and erode the social value of sharing. Critics argue that when sharing becomes automatic, it dilutes the personal curation that makes social media exchanges meaningful. According to Slate, this approach risks “killing taste,” because users typically choose to share only select content they find worth highlighting, rather than everything they consume. AL.com similarly observed that the frictionless model encourages over-sharing, overwhelming both users and their networks with minor or trivial activities. For example, integrating multiple platforms—such as Twitter, Foursquare, Pinterest, Spotify, and others—can create an incessant stream of updates that some users may find intrusive or irritating. This can lead to what critics describe as “narcissistic” or noisy timelines, potentially undermining the “social” nature of social media. == Business model and data implications == For Facebook, frictionless sharing offers clear business advantages. More frequent and detailed sharing provides valuable data that can be used to refine targeted advertising and personalize content delivery. The model also encourages users to spend more time on the platform, reinforcing its position as a central hub of online social activity. Other technology companies have experimented with similar approaches. Google has introduced forms of cross-platform integration that facilitate automatic activity sharing, though with a more explicit opt-in structure compared to Facebook. This approach has been described as “friction with consent,” allowing users to manually enable or disable integrations on a per-service basis.

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  • Friending and following

    Friending and following

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

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  • Redshift (theory)

    Redshift (theory)

    Redshift is a techno-economic theory suggesting hypersegmentation of information technology markets based on whether individual computing needs are over or under-served by Moore's law, which predicts the doubling of computing transistors (and therefore roughly computing power) every two years. The theory, proposed and named by New Enterprise Associates partner and former Sun Microsystems CTO Greg Papadopoulos, categorized a series of high growth markets (redshifting) while predicting slower GDP-driven growth in traditional computing markets (blueshifting). Papadopoulos predicted the result will be a fundamental redesign of components comprising computing systems. == Hypergrowth market segments (redshifting) == According to the Redshift theory, applications "redshift" when they grow dramatically faster than Moore's Law allows, growing quickly in their absolute number of systems. In these markets, customers are running out of datacenter real-estate, power and cooling infrastructure. According to Dell Senior Vice President Brad Anderson, “Businesses requiring hyperscale computing environments – where infrastructure deployments are measured by up to millions of servers, storage and networking equipment – are changing the way they approach IT.” While various Redshift proponents offer minor alterations on the original presentation, “Redshifting” generally includes: === ΣBW (Sum-of-Bandwidth) === These are companies that drive heavy Internet traffic. This includes popular web-portals like Google, Yahoo, AOL and MSN. It also includes telecoms, multimedia, television over IP, online games like World of Warcraft and others. This segment has been enabled by widespread availability of high-bandwidth Internet connections to consumers through a DSL or cable modem. A simple way to understand this market is that for every byte of content served to a PC, mobile phone or other device over a network, there must exist computing systems to send it over the network. === High performance computing (HPC) === These are companies that do complex simulations that involve (for example) weather, stock markets or drug-design simulations. This is a generally elastic market because businesses frequently spend every "available" dollar budgeted for IT. A common anecdote claims that cutting the cost of computing by half causes customers in this segment to buy at least twice as much, because each marginal IT dollar spent contributes to business advantage. === prise (or "Star-prise") === These are companies that aggregate traditional computing applications and offer them as services, typically in the form of Software as a Service (SaaS). For example, companies that deploy CRM are over-served by Moore's Law, but companies that aggregate CRM functions and offer them as a service, such as Salesforce.com, grow faster than Moore's Law. === The eBay crisis === A prime example of redshift was a crisis at eBay. In 1999 eBay suffered a database crisis when a single Oracle Database running on the fastest Sun machine available (these tracking Moore's law in this period) was not enough to cope with eBay's growth. The solution was to massively parallelise their system architecture. == Traditional computing markets (blueshifting) == Redshift theory suggests that traditional computing markets, such as those serving enterprise resource planning or customer relationship management applications, have reached relative saturation in industrialized nations. Thereafter, proponents argued further market growth will closely follow gross domestic product growth, which typically remains under 10% for most countries annually. Given that Moore's Law continues to predict accurately the rate of computing transistor growth, which roughly translates into computing power doubling every two years, the Redshift theory suggests that traditional computing markets will ultimately contract as a percentage of computing expenditures over time. Functionally, this means “Blueshifting” customers can satisfy computing requirement growth by swapping in faster processors without increasing the absolute number of computing systems. == Consequences and industry commentary == Papadopoulos argued that while traditional computing markets remain the dominant source of revenue through the late 2000s, a shift to hypergrowth markets will inevitably occur. When that shift occurs, he argued computing (but not computers) will become a utility, and differentiation in the IT market will be based upon a company's ability to deliver computing at massive scale, efficiently and with predictable service levels, much like electricity at that time. If computing is to be delivered as a utility, Nicholas Carr suggested Papadopoulos' vision compares with Microsoft researcher Jim Hamilton, who both agree that computing is most efficiently generated in shipping containers. Industry analysts are also beginning to quantify Redshifting and Blueshifting markets. According to International Data Corporation vice president Matthew Eastwood, "IDC believes that the IT market is in a period of hyper segmentation... This a class of customers that is Moore's law driven and as price performance gains continue, IDC believes that these organizations will accelerate their consumption of IT infrastructure.” == History and nomenclature == Key portions of Papadopoulos' theory were first presented by Sun Microsystems CEO Jonathan Schwartz in late 2006. Papadopoulos later gave a full presentation on Redshift to Sun's annual Analyst Summit in February 2007. The term Redshift refers to what happens when electromagnetic radiation, usually visible light, moves away from an observer. Papadopoulos chose this term to reflect growth markets because redshift helped cosmologists explain the expansion of the universe. Papadopoulos originally depicted traditional IT markets as green to represent their revenue base, but later changed them to “blueshift,” which occurs when a light source moves toward an observer, similar to what would happen during a contraction of the universe.

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  • Speech recognition

    Speech recognition

    Speech recognition (automatic speech recognition (ASR), computer speech recognition, or speech-to-text (STT)) is a sub-field of computational linguistics concerned with methods and technologies that translate spoken language into text or other interpretable forms. Speech recognition applications include voice user interfaces, where the user speaks to a device, which "listens" and processes the audio. Common voice applications include interpreting commands for calling, call routing, home automation, and aircraft control. These applications are called direct voice input. Productivity applications include searching audio recordings, creating transcripts, and dictation. Speech recognition can be used to analyse speaker characteristics, such as identifying native language using pronunciation assessment. Voice recognition (speaker identification) refers to identifying the speaker, rather than speech contents. Recognizing the speaker can simplify the task of translating speech in systems trained on a specific person's voice. It can also be used to authenticate the speaker as part of a security process. == History == Applications for speech recognition developed over many decades, with progress accelerated due to advances in deep learning and the use of big data. These advances are reflected in an increase in academic papers, and greater system adoption. Key areas of growth include vocabulary size, more accurate recognition for unfamiliar speakers (speaker independence), and faster processing speed. === Pre-1970 === 1952 – Bell Labs researchers, Stephen Balashek, R. Biddulph, and K. H. Davis, built Audrey for single-speaker digit recognition. Their system located the formants in the power spectrum of each utterance. 1960 – Gunnar Fant developed and published the source–filter model of speech production. 1962 – IBM's 16-word "Shoebox" machine's speech recognition debuted at the 1962 World's Fair. 1966 – Linear predictive coding, a speech coding method, was proposed by Fumitada Itakura of Nagoya University and Shuzo Saito of Nippon Telegraph and Telephone. 1969 – Funding at Bell Labs came to a halt for several years after the company's head engineer, John R. Pierce, wrote an open letter criticizing speech recognition research. This defunding lasted until Pierce retired and James L. Flanagan took over. Raj Reddy was the first person to work on continuous speech recognition, as a graduate student at Stanford University in the late 1960s. Previous systems required users to pause after each word. Reddy's system issued spoken commands for playing chess. Around this time, Soviet researchers invented the dynamic time warping (DTW) algorithm and used it to create a recognizer capable of operating on a 200-word vocabulary. DTW processed speech by dividing it into short frames (e.g. 10 ms segments) and treating each frame as a unit. Speaker independence, however, remained unsolved. === 1970–1990 === 1971 – DARPA funded a five-year speech recognition research project, Speech Understanding Research, seeking a minimum vocabulary size of 1,000 words. The project considered speech understanding a key to achieving progress in speech recognition, which was later disproved. BBN, IBM, Carnegie Mellon (CMU), and Stanford Research Institute participated. 1972 – The IEEE Acoustics, Speech, and Signal Processing group held a conference in Newton, Massachusetts. 1976 – The first ICASSP was held in Philadelphia, which became a major venue for publishing on speech recognition. During the late 1960s, Leonard Baum developed the mathematics of Markov chains at the Institute for Defense Analysis. A decade later, at CMU, Raj Reddy's students James Baker and Janet M. Baker began using the hidden Markov model (HMM) for speech recognition. James Baker had learned about HMMs while at the Institute for Defense Analysis. HMMs enabled researchers to combine sources of knowledge, such as acoustics, language, and syntax, in a unified probabilistic model. By the mid-1980s, Fred Jelinek's team at IBM created a voice-activated typewriter called Tangora, which could handle a 20,000-word vocabulary. Jelinek's statistical approach placed less emphasis on emulating human brain processes in favor of statistical modelling. (Jelinek's group independently discovered the application of HMMs to speech.) This was controversial among linguists since HMMs are too simplistic to account for many features of human languages. However, the HMM proved to be a highly useful way for modelling speech and replaced dynamic time warping as the dominant speech recognition algorithm in the 1980s. 1982 – Dragon Systems, founded by James and Janet M. Baker, was one of IBM's few competitors. === Practical speech recognition === The 1980s also saw the introduction of the n-gram language model. 1987 – The back-off model enabled language models to use multiple-length n-grams, and CSELT used HMM to recognize languages (in software and hardware, e.g. RIPAC). At the end of the DARPA program in 1976, the best computer available to researchers was the PDP-10 with 4 MB of RAM. It could take up to 100 minutes to decode 30 seconds of speech. Practical products included: 1984 – the Apricot Portable was released with up to 4096 words support, of which only 64 could be held in RAM at a time. 1987 – a recognizer from Kurzweil Applied Intelligence 1990 – Dragon Dictate, a consumer product released in 1990. AT&T deployed the Voice Recognition Call Processing service in 1992 to route telephone calls without a human operator. The technology was developed by Lawrence Rabiner and others at Bell Labs. By the early 1990s, the vocabulary of the typical commercial speech recognition system had exceeded the average human vocabulary. Reddy's former student, Xuedong Huang, developed the Sphinx-II system at CMU. Sphinx-II was the first to do speaker-independent, large vocabulary, continuous speech recognition, and it won DARPA's 1992 evaluation. Handling continuous speech with a large vocabulary was a major milestone. Huang later founded the speech recognition group at Microsoft in 1993. Reddy's student Kai-Fu Lee joined Apple, where, in 1992, he helped develop the Casper speech interface prototype. Lernout & Hauspie, a Belgium-based speech recognition company, acquired other companies, including Kurzweil Applied Intelligence in 1997 and Dragon Systems in 2000. L&H was used in Windows XP. L&H was an industry leader until an accounting scandal destroyed it in 2001. L&H speech technology was bought by ScanSoft, which became Nuance in 2005. Apple licensed Nuance software for its digital assistant Siri. ==== 2000s ==== In the 2000s, DARPA sponsored two speech recognition programs: Effective Affordable Reusable Speech-to-Text (EARS) in 2002, followed by Global Autonomous Language Exploitation (GALE) in 2005. Four teams participated in EARS: IBM; a team led by BBN with LIMSI and the University of Pittsburgh; Cambridge University; and a team composed of ICSI, SRI, and the University of Washington. EARS funded the collection of the Switchboard telephone speech corpus, which contained 260 hours of recorded conversations from over 500 speakers. The GALE program focused on Arabic and Mandarin broadcast news. Google's first effort at speech recognition came in 2007 after recruiting Nuance researchers. Its first product, GOOG-411, was a telephone-based directory service. Since at least 2006, the U.S. National Security Agency has employed keyword spotting, allowing analysts to index large volumes of recorded conversations and identify speech containing "interesting" keywords. Other government research programs focused on intelligence applications, such as DARPA's EARS program and IARPA's Babel program. In the early 2000s, speech recognition was dominated by hidden Markov models combined with feed-forward artificial neural networks (ANN). Later, speech recognition was taken over by long short-term memory (LSTM), a recurrent neural network (RNN) published by Sepp Hochreiter & Jürgen Schmidhuber in 1997. LSTM RNNs avoid the vanishing gradient problem and can learn "Very Deep Learning" tasks that require memories of events that happened thousands of discrete time steps earlier, which is important for speech. Around 2007, LSTMs trained with Connectionist Temporal Classification (CTC) began to outperform. In 2015, Google reported a 49 percent error‑rate reduction in its speech recognition via CTC‑trained LSTM. Transformers, a type of neural network based solely on attention, were adopted in computer vision and language modelling, and then to speech recognition. Deep feed-forward (non-recurrent) networks for acoustic modelling were introduced in 2009 by Geoffrey Hinton and his students at the University of Toronto, and by Li Deng and colleagues at Microsoft Research. In contrast to the prioer incremental improvements, deep learning decreased error rates by 30%. Both shallow and deep forms (e.g., recurrent nets) of ANNs had been explored since the 1980s. Howev

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  • Bare machine

    Bare machine

    In information technology, a bare machine (or bare-metal computer) is a computer which has no operating system. The software executed by a bare machine, commonly called a bare metal program or bare metal application, is designed to interact directly with hardware. Bare machines are widely used in embedded systems, particularly in cases where resources are limited or high performance is required. == Bare machine computing == Bare Machine Computing is a computing paradigm in which application software runs directly on a bare machine as a single, stand-alone executable, without an operating system or device drivers. The application software has direct access to hardware resources, and there is typically no distinction between user and kernel mode. It is self-managed software that boots, loads and runs without using any other software components. Bare metal programs are typically written in a close-to-hardware language such as C or assembly language. == Advantages == Typically, a bare-metal application will run faster, use less memory and be more power efficient than an equivalent program that relies on an operating system, due to the inherent overhead imposed by system calls. For example, hardware inputs and outputs are directly accessible to bare metal software, whereas they must usually be accessed through system calls when using an OS. It has no OS and therefore has no OS-related vulnerabilities. == Disadvantages == Bare metal applications typically require more effort to develop because operating system services such as memory management and task scheduling are not available. Debugging a bare-metal program may be complicated by factors such as: Lack of a standard output. The target machine may differ from the hardware used for program development (e.g., emulator, simulator). This forces setting up a way to load the bare-metal program onto the target (flashing), start the program execution and access the target resources. == Examples == === Early computers === Early computers, such as the PDP-11, allowed programmers to load a program, supplied in machine code, to RAM. The resulting operation of the program could be monitored by lights, and output derived from magnetic tape, print devices, or storage. Amdahl UTS's performance improves by 25% when run on bare metal without VM, the company said in 1986. === Embedded systems === Bare machine programming is a common practice in embedded systems, in which microcontrollers or microprocessors boot directly into monolithic, single-purpose software without loading an operating system. Such embedded software can vary in structure. For example, one such program paradigm, known as foreground-background or superloop architecture, consists of an infinite main loop in which each task is executed sequentially and must voluntarily return control back to the loop. The loop runs these cooperative background processes that are not time-critical, while interrupt service routines momentarily interrupt the loop to handle time-critical foreground tasks.

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  • Institute of Telecommunications Professionals

    Institute of Telecommunications Professionals

    The Institute of Telecommunications Professionals (ITP) is a membership organisation for professionals in the telecommunications industry, based in the United Kingdom. The Institute was originally founded in 1906. It is now a registered company with Companies House in the United Kingdom, incorporated in 2002. Brendan O' Mahony has been the chief executive of the ITP. Lucy Woods presided over ITP for fifteen years, until 2018, when the organization named Kevin Paige chairman for five years. In 2022 the ITP appointed its new CEO, Charlotte Goodwill. In 2021, the ITP assisted a UK fibre network Vorboss in establishing its training academy. In 2023, the ITP appointed Tim Creswick, the CEO of Vorboss, as the new chair of its board of directors. The institute has an associated journal, the Journal of the Institute of Telecommunications Professionals, established in 2007 and published quarterly.

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