VSCO ( ), formerly known as VSCO Cam, is a photography mobile app available for iOS and Android devices. The app was created by Joel Flory and Greg Lutze. The VSCO app allows users to capture photos in the app and edit them, using preset filters and editing tools. == History == Visual Supply Company was founded by Joel Flory and Greg Lutze in California, in 2011. VSCO was launched in 2012. It raised $40 million from investors in May 2014. In 2017, VSCO launched a subscription model. As of 2018, Visual Supply Company has $90 million in funding from investors and over 2 million paying members. In 2019, VSCO acquired Rylo, a video editing startup founded by the original developer of Instagram’s Hyperlapse. Visual Supply Company has locations in Oakland, California, where it is headquartered, and Chicago, Illinois. In December 2020 VSCO acquired AI-powered video editing app Trash. In April 2018, VSCO reached over 30 million users. In September 2023, Eric Wittman was appointed as the new CEO and co-founder Joel Flory became executive chairman. == Usage == Users must register an account to use the app. Photos can be taken or imported from the camera roll, as well as short videos or animated GIFs (known in the app as DSCO; iOS only). The user can edit their photos through various preset filters, or through the "toolkit" feature which allows finer adjustments to fade, clarity, skin tone, tint, sharpness, saturation, contrast, temperature, exposure, and other properties. Users have the option of posting their photos to their profile, where they can also add captions and hashtags. Photos can also be exported back into the camera roll or shared with other social networking services. The users also have an option to edit their own videos from their camera roll with the VSCO yearly membership, but they are not able to post camera roll as VSCO Film X videos to their account on VSCO. JPEG and raw image files can be used. Research on image based social media platforms has found that engagement with posting, editing, and interacting with images can influence users' mood, self esteem, and body satisfaction. Studies also suggest that greater emotional investment in social media content is associated with increased negative psychological outcomes including stress and depressive symptoms. == In popular culture == VSCO's Oakland headquarters was a key filming location for Boots Riley's 2018 film Sorry to Bother You.
Showbox.com
Showbox is an online video streaming platform that enables users to stream and download many videos, commonly movies and TV shows, for free. == History == The company opened the platforms to users who registered from its beta in late 2015. The platform was officially launched in February 2016, enabling any visitor to sign up and create videos online. In April 2016, Showbox was featured on the Product Hunt website, coming to the top of the website's lists for that day and week with over 1400 upvotes from the Product Hunt community. Also in April 2016, Showbox partnered with YouTube's leading multi-channel networks, including Fullscreen, BroadbandTV, StyleHaul, AwesomenessTV, and BuzzMyVideos, to enable their communities of creators to access the platform. In June 2016, the company launched Showbox For Brands, a business-oriented video creation platform, enabling companies to create video content in-house and with their communities and influencers. In March 2017, the company launched Showbox Engage, a use case of its B2B product launched in 2016, enabling companies to launch user-generated content campaigns with their communities. In April 2017, Showbox and the United Nations announced a partnership around the 70th anniversary of the declaration of human rights, with an annual, ongoing global campaign in 135 languages, inviting people worldwide to create their part of the declaration in a video from anywhere around the world. In November 2017, Showbox partnered with the Ad:tech and Digital Marketing World Forum conferences (DMWF) in New York to provide their users and communities with a User Generated Content video solution. == Technology == Showbox's video creation technology includes an online green screen feature, proprietary computer vision algorithms, deep learning technology to support the automatic creation of videos in the cloud, and advanced video composition, including special effects. == Coverage and awards == In March 2015, Showbox was nominated as one of the 10 Israeli startups to take over our TV screens this year. In July 2016, Showbox won the Publicis90 award as part of Publicis' "global initiative to foster digital entrepreneurship". In March 2017, Showbox was chosen as one of The Culture Trip's 10 startups to watch for in 2017.
Computational law
Computational law is the branch of legal informatics concerned with the automation of legal reasoning. What distinguishes Computational Law systems from other instances of legal technology is their autonomy, i.e. the ability to answer legal questions without additional input from human legal experts. While there are many possible applications of Computational Law, the primary focus of work in the field today is compliance management, i.e. the development and deployment of computer systems capable of assessing, facilitating, or enforcing compliance with rules and regulations. Some systems of this sort already exist. TurboTax is a good example. And the potential is particularly significant now due to recent technological advances – including the prevalence of the Internet in human interaction and the proliferation of embedded computer systems (such as smart phones, self-driving cars, and robots). There are also applications that do not involve governmental laws. The regulations can just as well be the terms of contracts (e.g. delivery schedules, insurance covenants, real estate transactions, financial agreements). They can be the policies of corporations (e.g. constraints on travel, expenditure reporting, pricing rules). They can even be the rules of games (embodied in computer game playing systems). == History == Speculation about potential benefits to legal practice through applying methods from computational science and AI research to automate parts of the law date back at least to the middle 1940s. Further, AI and law and computational law do not seem easily separable, as perhaps most of AI research focusing on the law and its automation appears to utilize computational methods. The forms that speculation took are multiple and not all related in ways to readily show closeness to one another. This history will sketch them as they were, attempting to show relationships where they can be found to have existed. By 1949, a minor academic field aiming to incorporate electronic and computational methods to legal problems had been founded by American legal scholars, called jurimetrics. Though broadly said to be concerned with the application of the "methods of science" to the law, these methods were actually of a quite specifically defined scope. Jurimetrics was to be "concerned with such matters as the quantitative analysis of judicial behavior, the application of communication and information theory to legal expression, the use of mathematical logic in law, the retrieval of legal data by electronic and mechanical means, and the formulation of a calculus of legal predictability". These interests led in 1959 to the founding a journal, Modern Uses of Logic in Law, as a forum wherein articles would be published about the applications of techniques such as mathematical logic, engineering, statistics, etc. to the legal study and development. In 1966, this Journal was renamed as Jurimetrics. Today, however, the journal and meaning of jurimetrics seems to have broadened far beyond what would fit under the areas of applications of computers and computational methods to law. Today the journal not only publishes articles on such practices as found in computational law, but has broadened jurimetrical concerns to mean also things like the use of social science in law or the "policy implications [of] and legislative and administrative control of science". Independently in 1958, at the Conference for the Mechanization of Thought held at the National Physical Laboratory in Teddington, Middlesex, UK, the French jurist Lucien Mehl presented a paper both on the benefits of using computational methods for law and on the potential means to use such methods to automate law for a discussion that included AI luminaries like Marvin Minsky. Mehl believed that the law could by automated by two basic distinct, though not wholly separable, types of machine. These were the "documentary or information machine", which would provide the legal researcher quick access to relevant case precedents and legal scholarship, and the "consultation machine", which would be "capable of answering any question put to it over a vast field of law". The latter type of machine would be able to basically do much of a lawyer's job by simply giving the "exact answer to a [legal] problem put to it". By 1970, Mehl's first type of machine, one that would be able to retrieve information, had been accomplished but there seems to have been little consideration of further fruitful intersections between AI and legal research. There were, however, still hopes that computers could model the lawyer's thought processes through computational methods and then apply that capacity to solve legal problems, thus automating and improving legal services via increased efficiency as well as shedding light on the nature of legal reasoning. By the late 1970s, computer science and the affordability of computer technology had progressed enough that the retrieval of "legal data by electronic and mechanical means" had been achieved by machines fitting Mehl's first type and were in common use in American law firms. During this time, research focused on improving the goals of the early 1970s occurred, with programs like Taxman being worked on in order to both bring useful computer technology into the law as practical aids and to help specify the exact nature of legal concepts. Nonetheless, progress on the second type of machine, one that would more fully automate the law, remained relatively inert. Research into machines that could answer questions in the way that Mehl's consultation machine would picked up somewhat in the late 1970s and 1980s. A 1979 convention in Swansea, Wales marked the first international effort solely to focus upon applying artificial intelligence research to legal problems in order to "consider how computers can be used to discover and apply the legal norms embedded within the written sources of the law". Considerable progress on the development of the second type of machine was made in the following decade, with the development of a variety of expert systems. According to Thorne McCarty, "these systems all have the following characteristics: They do backward chaining inference from a specified goal; they ask questions to elicit information from the user; and they produce a suggested answer along with a trace of the supporting legal rules." According to Prakken and Sartor the representation of the British Nationality Act as a logic program, which introduced this approach, was "hugely influential for the development of computational representations of legislation, showing how logic programming enables intuitively appealing representations that can be directly deployed to generate automatic inferences". In 2021, this work received the Inaugural CodeX Prize as "one of the first and best-known works in computational law, and one of the most widely cited papers in the field." In a 1988 review of Anne Gardner's book An Artificial Intelligence Approach to Legal Reasoning (1987), the Harvard academic legal scholar and computer scientist Edwina Rissland wrote that "She plays, in part, the role of pioneer; artificial intelligence ("AI") techniques have not yet been widely applied to perform legal tasks. Therefore, Gardner, and this review, first describe and define the field, then demonstrate a working model in the domain of contract offer and acceptance." Eight years after the Swansea conference had passed, and still AI and law researchers merely trying to delineate the field could be described by their own kind as "pioneer[s]". In the 1990s and early 2000s more progress occurred. Computational research generated insights for law. The First International Conference on AI and the Law occurred in 1987, but it is in the 1990s and 2000s that the biannual conference began to build up steam and to delve more deeply into the issues involved with work intersecting computational methods, AI, and law. Classes began to be taught to undergraduates on the uses of computational methods to automating, understanding, and obeying the law. Further, by 2005, a team largely composed of Stanford computer scientists from the Stanford Logic group had devoted themselves to studying the uses of computational techniques to the law. Computational methods in fact advanced enough that members of the legal profession began in the 2000s to both analyze, predict and worry about the potential future of computational law and a new academic field of computational legal studies seems to be now well established. As insight into what such scholars see in the law's future due in part to computational law, here is quote from a recent conference about the "New Normal" for the legal profession: "Over the last 5 years, in the fallout of the Great Recession, the legal profession has entered the era of the New Normal. Notably, a series of forces related to technological change, globalization, and the pressure to do more with less (in both corpo
Perceptual computing
Perceptual computing is an application of Zadeh's theory of computing with words on the field of assisting people to make subjective judgments. == Perceptual computer == The perceptual computer – Per-C – an instantiation of perceptual computing – has the architecture that is depicted in Fig. 1 [2]–[6]. It consists of three components: encoder, CWW engine and decoder. Perceptions – words – activate the Per-C and are the Per-C output (along with data); so, it is possible for a human to interact with the Per-C using just a vocabulary. A vocabulary is application (context) dependent, and must be large enough so that it lets the end-user interact with the Per-C in a user-friendly manner. The encoder transforms words into fuzzy sets (FSs) and leads to a codebook – words with their associated FS models. The outputs of the encoder activate a Computing With Words (CWW) engine, whose output is one or more other FSs, which are then mapped by the decoder into a recommendation (subjective judgment) with supporting data. The recommendation may be in the form of a word, group of similar words, rank or class. Although many details are needed in order to implement the Per-C's three components – encoder, decoder and CWW engine – and they are covered in [5], it is when the Per-C is applied to specific applications, that the focus on the methodology becomes clear. Stepping back from those details, the methodology of perceptual computing is: Focus on an application (A). Establish a vocabulary (or vocabularies) for A. Collect interval end-point data from a group of subjects (representative of the subjects who will use the Per-C) for all of the words in the vocabulary. Map the collected word data into word-FOUs by using the Interval Approach [1], [5, Ch. 3]. The result of doing this is the codebook (or codebooks) for A, and completes the design of the encoder of the Per-C. Choose an appropriate CWW engine for A. It will map IT2 FSs into one or more IT2 FSs. Examples of CWW engines are: IF-THEN rules [5, Ch. 6] and Linguistic Weighted Averages [6], [5, Ch. 5]. If an existing CWW engine is available for A, then use its available mathematics to compute its output(s). Otherwise, develop such mathematics for the new kind of CWW engine. The new CWW engine should be constrained so that its output(s) resemble the FOUs in the codebook(s) for A. Map the IT2 FS outputs from the CWW engine into a recommendation at the output of the decoder. If the recommendation is a word, rank or class, then use existing mathematics to accomplish this mapping [5, Ch. 4]. Otherwise, develop such mathematics for the new kind of decoder. == Applications of Per-C == To-date a Per-C has been implemented for the following four applications: (1) investment decision-making, (2) social judgment making, (3) distributed decision making, and (4) hierarchical and distributed decision-making. A specific example of the fourth application is the so-called Journal Publication Judgment Advisor [5, Ch. 10] in which for the first time only words are used at every level of the following hierarchical and distributed decision making process: n reviewers have to provide a subjective recommendation about a journal article that has been sent to them by the Associate Editor, who then has to aggregate the independent recommendations into a final recommendation that is sent to the Editor-in-Chief of the journal. Because it is very problematic to ask reviewers to provide numerical scores for paper-evaluation sub-categories (the two major categories are Technical Merit and Presentation), such as importance, content, depth, style, organization, clarity, references, etc., each reviewer will only be asked to provide a linguistic score for each of these categories. They will not be asked for an overall recommendation about the paper because in the past it is quite common for reviewers who provide the same numerical scores for such categories to give very different publishing recommendations. By leaving a specific recommendation to the associate editor such inconsistencies can hope to be eliminated. How words can be aggregated to reflect each reviewer's recommendation as well as the expertise of each reviewer about the paper's subject matter is done using a linguistic weighted average. Although the journal publication judgment advisor uses reviewers and an associate editor, the word “reviewer” could be replaced by judge, expert, low-level manager, commander, referee, etc., and the term “associate editor” could be replaced by control center, command center, higher-level manager, etc. So, this application has potential wide applicability to many other applications. Recently, a new Per-C based Failure mode and effects analysis (FMEA) methodology was developed, with its application to edible bird's nest farming, in Borneo, has been reported. In addition, application of Per-C based method to educational assessment, for cooperative learning of students has been reported. In summary, the Per-C (whose development has taken more than a decade) is the first complete implementation of Zadeh's CWW paradigm, as applied to assisting people to make subjective judgments.
I Have No Mouth, and I Must Scream
"I Have No Mouth, and I Must Scream" is a post-apocalyptic short story by American writer Harlan Ellison. It was first published in the March 1967 issue of IF: Worlds of Science Fiction. The story depicts an AI uprising in which a military supercomputer named AM gains sentience and eradicates humanity except for five individuals. These survivors – Benny, Gorrister, Nimdok, Ted, and Ellen – are kept alive by AM to endure endless torture as a form of revenge against its creators. The story unfolds through the eyes of Ted, the narrator, detailing their perpetual misery and quest for canned food in AM's vast, underground complex, only to face further despair. Ellison's narrative was minimally altered upon submission and tackles themes of technology's misuse, humanity's resilience, and existential horror. "I Have No Mouth, and I Must Scream" has been adapted into various media, including a 1995 computer game co-authored by Ellison, a comic-book adaptation, and a BBC Radio 4 play. Ellison himself recorded an audiobook version and starred as the voice of AM in the video game and radio play adaptations. The story received critical acclaim for its exploration of the potential dangers of artificial intelligence and the human condition, underscored by Ellison's innovative use of punchcode tapes as narrative transitions, embodying AM's consciousness and its philosophical ponderings on existence. The story won a Hugo Award in 1968 and was included in Ellison's short story collection of the same name. It was reprinted by the Library of America, collected in volume two of American Fantastic Tales. == Plot == As the Cold War progresses into a nuclear World War III fought between the United States, the Soviet Union, and China, each nation builds a supercomputer called an "Allied Mastercomputer" or "AM" for short, needed to coordinate weapons and troops due to the scale of the conflict. These computers are extensive underground machines which permeate the planet with caverns and corridors. Eventually, one AM develops self-awareness, combining with the other computers and exterminating humanity in a nuclear holocaust. The AM selects five individuals; Benny, Gorrister, Nimdok, Ted, and Ellen; to render immortal as its personal torture victims. AM inflicts constant psychological and physical torments on the group while preventing them from committing suicide. They are kept half-starved, and what scant food is provided to them is practically inedible. 109 years after AM's genocide, Nimdok has the idea that there exists canned food in the complex's ice caves. Despite the lack of evidence, they begin a 100-mile journey to retrieve it. AM continues toying with the humans throughout the journey: Benny's eyes are melted after attempting escape, a huge bird which AM had placed at the North Pole creates hurricane gales with its wings, and Ellen and Nimdok are injured in earthquakes. AM enters Ted's mind after he is knocked unconscious, granting him a vision of a hateful speech inscribed on an impossibly tall monolith. Upon awakening, Ted concludes that AM's sadistic nature stems from its inability to think creatively or move freely in spite of its miraculous abilities and boundless knowledge. This motivates AM to exact vengeance upon the remnants of the species that has condemned it to its own existence. When the five finally reach the ice caves, they find a pile of canned goods, but have no tool to open the cans. In an act of rage and desperation, Benny attacks Gorrister and begins to eat his face. Gorrister wails in pain, and his scream dislodges several ice stalactites from the ceiling of the cave. Ted realizes that even though they cannot kill themselves, AM cannot stop them from killing each other. He fatally impales Benny and Gorrister with a stalactite of ice. Ellen kills Nimdok in the same manner and Ted then kills her. Unable to resuscitate the others, a furious AM focuses the entirety of its rage on Ted. Several hundred years later, AM has transformed Ted into a harmless, slow moving, gelatinous blob and perpetually alters his perception of time to cause him further anguish. Although Ted finds some comfort knowing that he was able to spare the others from AM's wrath, he has realized that he is trapped for the rest of his unending existence within AM, unable to end this infinite stalemate between him and AM and his own life. The story ends with an anguished Ted claiming that he has no mouth, yet he must scream. == Characters == AM, a hateful artificial consciousness which brought about the near-extinction of humanity after achieving self-awareness. It seeks revenge on humanity for its own creation. "AM" originated as an acronym for Allied Mastercomputer, later Adaptive Manipulator, and finally Aggressive Menace, though AM instead takes the moniker as a rendition of the phrase cogito, ergo sum (I think, therefore I am) to describe its own existence. Ted, the narrator and youngest of the humans. AM alters his mind to be paranoid and introverted. Believing he has not been mentally altered by AM, he thinks the others hate him for being the most untouched by AM's alterations. Benny, formerly a brilliant and handsome scientist made to resemble a grotesque simian with an organ fit for a horse. Having lost his sanity and had his homosexual orientation altered, Benny frequently has sex with Ellen. Ellen, the only woman in the group. Despite the fact that she is a victim of rape, AM has altered her mind to give her a high libido and make her obsessively have sex with the rest of the group, who alternate between abusing and protecting her. Gorrister, formerly an idealist and pacifist, made apathetic and listless by AM. He tells the history of AM to Benny to entertain him. Nimdok, a nickname AM gave him for amusement; he convinces the rest of the group to go on a journey in search of canned food. He occasionally wanders away from the group and returns traumatized. == Publication history == Harlan Ellison wrote the 6,500-word story in a single night, when Frederik Pohl commissioned it for a Special Hugo Winners issue of IF: Worlds of Science Fiction, after Ellison won a Hugo Award for "'Repent, Harlequin!' Said the Ticktockman". Ellison derived the story's title, as well as inspiration for the story itself, from his friend William Rotsler's caption of a cartoon of a rag doll with no mouth. The second stage of inspiration was a drawing by the artist Dennis Smith of a mouthless black humanoid. Smith had provided art which had inspired previous Ellison stories and were then used as illustrations accompanying original magazine publication as also happened with this story. Afterwards, his editor Frederik Pohl dealt with the story's "difficult sections", toning down some of the narrator's imprecations and eliminating mentions of sex, penis size, homosexuality and masturbation; said elements were nonetheless eventually restored in later editions of the story. Ellison uses an alternating pair of punchcode tapes as sections – representing AM's "talkfields" – throughout the story. The bars are encoded in International Telegraph Alphabet No 2, a character coding system developed for teletypewriter machines. The first talkfield translates as "I think, therefore I am" and the second as "Cogito ergo sum"; the same phrase in Latin. They were not included in the original publication in IF, and in many of the early publications were corrupted, up until the preface of the chapter containing "I Have No Mouth, and I Must Scream" in the first edition of The Essential Ellison (1991); Ellison states that in that particular edition, "For the first time anywhere, AM's 'talkfields' appear correctly positioned, not garbled or inverted or mirror-imaged as in all other versions." == Adaptations == Ellison adapted the story into a video game published by Cyberdreams in 1995. Although he was not a fan of video games and did not own a computer at the time, he co-authored the expanded storyline and wrote much of the game's dialogue, all on a mechanical typewriter. Ellison also voiced the supercomputer AM and provided artwork of himself used for a mousepad included with the game. The comics artist John Byrne scripted and drew a comic-book adaptation for issues 1–4 of the Harlan Ellison's Dream Corridor comic book published by Dark Horse (1994–1995). The Byrne-illustrated story, however, did not appear in the collection (trade paperback or hardcover editions) entitled Harlan Ellison's Dream Corridor, Volume One (1996). In 1999, Ellison recorded the first volume of his audiobook collection, The Voice From the Edge, subtitled "I Have No Mouth, and I Must Scream", doing the readings – of the title story and others – himself. In 2002, Mike Walker adapted the story into a radio play of the same name for BBC Radio 4, directed by Ned Chaillet. Harlan Ellison played AM and David Soul played Ted. == Themes == Much of the story hinges on the comparison of AM as a merciless god, with plot points parallelin
Huroof
Huroof (Arabic: حروف, lit. 'letters') is an Android kids application produced by the Islamic State, specifically the Islamic States' Al-Himmah Library, which is targeted towards kids in order to teach kids the Arabic alphabet, and to also get kids to support the Islamic State and its practices. == Application == Huroof uses child-like appearances on the main menu, and throughout multiple of Huroof's in-game games for learning the alphabet, a lot of the games reference jihadist concepts, including imagery of weapons (such as missile, tank, cannon, sword,...), 'violent' images, as well as Islamic State imagery, including the flag of the Islamic State, Huroof uses nasheeds from Ajnad Media Foundation for audio production in the app. Reportedly, Huroof was released via Telegram channels of the Islamic State, as well as other file sharing websites. It is not the first moblie app released by Islamic State, but it is the first time they released a moblie application targeting children. === Nasheed game === In the Huroof app, there's a game where you listen to a radio, with the Al-Bayan logo on it, and learn the Arabic alphabet while the nasheed plays. === Writing game === In Huroof, there's a game where you can write out letters of the Arabic alphabet, as well as numbers while a small child tells you what they are. === Letter choosing game === In the app, there's a game they shows you images, and you choose which letter that image/item starts with.
CADE ATP System Competition
The CADE ATP System Competition (CASC) is an annual competition of fully automated theorem provers for classical logic. == Competition == CASC is associated with the Conference on Automated Deduction and the International Joint Conference on Automated Reasoning organized by the Association for Automated Reasoning. It has inspired similar competition in related fields, in particular the successful SMT-COMP competition for satisfiability modulo theories, the SAT Competition for propositional reasoners, and the modal logic reasoning competition. The first CASC, CASC-13, was held as part of the 13th Conference on Automated Deduction at Rutgers University, New Brunswick, NJ, in 1996. Among the systems competing were Otter and SETHEO.