AI Coding Claude

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List of video editing software

The following is a list of video editing software. The criterion for inclusion in this list is the ability to perform non-linear video editing. Most modern transcoding software supports transcoding a portion of a video clip, which would count as cropping and trimming. However, items in this article have one of the following conditions: Can perform other non-linear video editing function such as montage or compositing Can do the trimming or cropping without transcoding == Free (libre) or open-source == The software listed in this section is either free software or open source, and may or may not be commercial. === Active and stable === === Inactive === == Proprietary (non-commercial) == The software listed in this section is proprietary, and freeware or freemium. === Active === === Discontinued === == Proprietary (commercial) == The software listed in this section is proprietary and commercial. === Active === === Discontinued ===
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Grokipedia

Grokipedia is an AI-generated online encyclopedia operated by the American company xAI. The site was launched on October 27, 2025. Some entries are generated by Grok, a large language model owned by the same company, while others were forked from Wikipedia, with some altered and some used nearly verbatim. Articles cannot be directly edited, though logged-in visitors to the encyclopedia can suggest new articles or corrections via a pop-up form, which are reviewed by Grok. The xAI founder Elon Musk suggested Grokipedia could be an alternative to Wikipedia that would "purge out the propaganda" he believes is promoted by the latter, describing Wikipedia as "woke" and an "extension of legacy media propaganda". External analysis of Grokipedia's content has focused on its accuracy and biases due to hallucinations and potential algorithmic bias, which reviewers have described as promoting right-wing perspectives and Musk's views. The majority of coverage has described the website as validating, promoting, and legitimizing a variety of debunked conspiracy theories and ideas against scientific consensus on topics such as HIV/AIDS denialism, vaccines and autism, climate change, and race and intelligence. The site has been accused of whitewashing far-right extremism, such as by falsely claiming a white genocide is actively occurring. Several right-wing figures have welcomed the site. Studies have highlighted its use of sources deemed as having very low credibility such as X conversations and neo-Nazi websites, and for writing about far-right figures and topics in a promotional manner. == Background == Wikipedia is an online encyclopedia written and maintained by a community of volunteers. Its possible bias has been studied and debated. In 2018, Haaretz noted "Wikipedia has succeeded in being accused of being both too liberal and too conservative, and has critics from across the spectrum". xAI is an American AI company founded by Elon Musk in 2023. Its flagship product is the family of large language models called Grok. == History == In 2021, Musk expressed affection for Wikipedia on its 20th anniversary. In 2022, however, Musk argued that Wikipedia was "losing its objectivity", and in 2023, said he would donate US$1 billion to the project if it was pejoratively renamed "Dickipedia". In December 2024, Musk called for a boycott of donations to Wikipedia over its perceived left-wing bias, calling it "Wokepedia". In January 2025, Musk made a series of statements on Twitter denouncing Wikipedia for its description of the incident where he made a controversial gesture, which many viewed as resembling a Nazi salute, at president Donald Trump's second inauguration. Musk has since positioned Grokipedia as an alternative to Wikipedia that would "purge out the propaganda" in the latter, with Musk describing Wikipedia as "woke" and an "extension of legacy media propaganda". === Idea and announcement === In September 2025, Musk spoke at the All-In podcast conference with David O. Sacks, the White House advisor on AI and cryptocurrency, about how Grok consumed data from Wikipedia and other sources to gain more complete knowledge of the world. Sacks suggested publishing its knowledge base as an artifact called "Grokipedia", saying "Wikipedia is so biased, it's a constant war". Following the conversation, Musk announced that xAI was building a new AI-generated online encyclopedia called Grokipedia. According to Musk's announcement, it would be an AI-powered knowledge base designed to rival Wikipedia by addressing its perceived biases, errors, and ideological slants. The project positioned itself within a history of ideologically driven alternatives to Wikipedia, such as the conservative Conservapedia (launched in 2006) and the Russian-government-friendly Ruwiki (launched in 2023). However, Grokipedia is distinct in its core reliance on artificial intelligence rather than human community editing. === Launch and traffic === On October 6, 2025, Musk announced that the early version of Grokipedia was scheduled for release in two weeks, but the project was postponed briefly to address content quality issues. It launched on October 27, 2025, labeled "v 0.1", with over 800,000 articles, compared to over seven million English Wikipedia articles as of September 1, 2025. According to an initial analysis of usage figures by Similarweb, which evaluates data from registered users and partners, Grokipedia recorded a peak of over 460,000 website visits in the US on October 28, 2025. After that, traffic dropped significantly and settled at around 35,000 visits per day between November 8 and 11, 2025. As of early 2026, it had over 5.6 million articles. In January 2026, The Guardian reported that GPT-5.2 frequently cited Grokipedia as a source in responses, raising concerns of misinformation on ChatGPT. The same month, The Verge reported that Google's AI Overviews, AI Mode, and Gemini language model, as well as Microsoft Copilot and Perplexity AI, used Grokipedia to answer niche, obscure, or highly specific factual questions or "non-sensitive queries." According to a case study published by SEO Engico, the site received only 19 clicks from Google Search in November 2025 but reached approximately 3.2 million monthly clicks by January 2026, with over 900,000 pages indexed and millions of ranking keywords. Analysts attributed the surge in part to the site's technical structure and large-scale AI-generated content production. In early February 2026, Grokipedia's visibility in Google Search declined sharply. SEO analysts, including Glenn Gabe and Malte Landwehr, reported a significant drop in rankings across Google organic results as well as in Google AI Overviews and AI Mode. The same case study cited independent reviews that identified citation quality concerns, including references to low-credibility sources and instances of self-citation. By mid-February 2026, Grokipedia had reportedly lost much of its previous search visibility, and Wikipedia ranked above it for searches related to its own name. === Updates === ==== Future ==== In November 2025, Musk announced that he eventually plans to change the name of the site to Encyclopedia Galactica when Grokipedia is "good enough", saying that it had a "long way to go". This name is taken from the publication of that title in the works of Isaac Asimov and Douglas Adams. Musk said that he hoped to send copies of the encyclopedia to "the Moon and Mars and out to deep space". == Content == The Grok large language model generates and fact-checks articles on Grokipedia. Users cannot directly edit Grokipedia articles, but logged-in users can suggest edits and report errors, with such submissions being reviewed and implemented by the Grok AI. Some articles are nearly identical to their Wikipedia entries, but the format of Grokipedia citations is different, and some Grokipedia articles were republished almost verbatim, accompanied by a disclaimer noting that the content was "adapted from Wikipedia" under a Creative Commons license. Others were completely rewritten from scratch using Musk's AI chatbot, Grok. Forbes identified the articles AMD, Lamborghini, and PlayStation 5 as examples of copied Wikipedia articles. Articles attributed to Wikipedia carry a Creative Commons Attribution-ShareAlike license, while the license of other articles is licensed under the "X Community License", a license that accepts reuse and remixing for "non-commercial and research purposes" and commercial use that abides to "all of the guardrails provided in xAI's Acceptable Use Policy". On October 31, 2025, Musk clarified that the duplication of Wikipedia articles was intentional, saying that the Grokipedia team instructed Grok to compile Wikipedia's top 1 million articles and make content changes to them. The site's design has been described as minimalist with a simple homepage including little more than a large search bar. In a comparative textual analysis of the most heavily edited matched article pairs from Grokipedia and Wikipedia, Grokipedia entries are substantially longer and less densely referenced, indicating that AI-produced encyclopedias prioritize exposition rather than source-based validation. Starting in version 0.2, Grok reviews and implements approved suggested edits, and a small panel rotates through a display of the names of several recently edited articles. In February 2026, the Columbia Journalism Review reported on an analysis by the Tow Center for Digital Journalism finding that Grok, the AI behind Grokipedia, had increasingly begun suggesting and approving edits to the site itself without human involvement. According to the report, AI-generated edit suggestions overtook human submissions in December 2025 and accounted for more than three-quarters of proposed changes. The analysis raised concerns about transparency, editorial oversight, and fact-checking standards, particularly after instances in which Grok proposed or modified politically s
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R.U.R.

R.U.R. is a 1920 science fiction play by the Czech writer Karel Čapek. "R.U.R." stands for Rossumovi Univerzální Roboti (Rossum's Universal Robots, a phrase that has been used as a subtitle in English versions). The play had its world premiere on 2 January 1921 in Hradec Králové. It introduced the word "robot" to the English language and to science fiction as a whole. R.U.R. became influential soon after its publication. By 1923, it had been translated into thirty languages. R.U.R. was successful in its time in Europe and North America. Čapek later took a different approach to the same theme in his 1936 novel War with the Newts, in which non-humans become a servant-class in human society. == Characters == Parentheses indicate names which vary according to translation. On the meaning of the names, see Ivan Klíma: Karel Čapek: Life and Work (2002). == Plot == === Synopsis === The play begins in a factory that makes artificial workers from synthetic organic matter. (As living creatures of artificial flesh and blood, that later terminology would call androids, the playwright's 'roboti' differ from later fictional and scientific concepts of inorganic constructs.) Robots may be mistaken for humans but have no original thoughts. Though most are content to work for humans, eventually a rebellion causes the extinction of the human race. === Prologue (Act I in the Selver translation) === Helena, the daughter of the president of a major industrial power, arrives at the island factory of Rossum's Universal Robots. Here, she meets Domin, the General Manager of R.U.R., who relates to her the history of the company. Rossum had come to the island in 1920 to study marine biology. In 1932, Rossum had invented a substance like organic matter, though with a different chemical composition. He argued with his nephew about their motivations for creating artificial life. While the elder wanted to create animals to prove or disprove the existence of God, his nephew only wanted to become rich. Young Rossum finally locked away his uncle in a lab to play with the monstrosities he had created and created thousands of robots. By the time the play takes place (circa the year 2000), robots are cheap and available all over the world. They have become essential for industry. After meeting the heads of R.U.R., Helena reveals that she is a representative of the League of Humanity, an organization that wishes to liberate the robots. The managers of the factory find this absurd. They see robots as appliances. Helena asks that the robots be paid, but according to R.U.R. management, the robots do not "like" anything. Eventually Helena is convinced that the League of Humanity is a waste of money, but still argues robots have a "soul". Later, Domin confesses that he loves Helena and forces her into an engagement. === Act I (Act II in Selver) === Ten years have passed. Helena and her nurse Nana discuss current events, the decline in human births in particular. Helena and Domin reminisce about the day they met and summarize the last ten years of world history, which has been shaped by the new worldwide robot-based economy. Helena meets Dr. Gall's new experiment, Radius. Dr. Gall describes his experimental robotess, also named Helena. Both are more advanced, fully-featured robots. In secret, Helena burns the formula required to create robots. The revolt of the robots reaches Rossum's island as the act ends. === Act II (Act III in Selver) === The characters sense that the very universality of the robots presents a danger. Echoing the story of the Tower of Babel, the characters discuss whether creating national robots who were unable to communicate beyond their languages would have been a good idea. As robot forces lay siege to the factory, Helena reveals she has burned the formula necessary to make new robots. The characters lament the end of humanity and defend their actions, despite the fact that their imminent deaths are a direct result of their choices. Busman is killed while attempting to negotiate a peace with the robots. The robots storm the factory and kill all the humans except for Alquist, the company's Clerk of the Works (Head of Construction). The robots spare him because they recognize that "He works with his hands like a robot. He builds houses. He can work." === Act III (Epilogue in Selver) === Years have passed. Alquist, who still lives, attempts to recreate the formula that Helena destroyed. He is a mechanical engineer, though, with insufficient knowledge of biochemistry, so he has made little progress. The robot government has searched for surviving humans to help Alquist and found none alive. Officials from the robot government beg him to complete the formula, even if it means he will have to kill and dissect other robots for it. Alquist yields. He will kill and dissect robots, thus completing the circle of violence begun in Act Two. Alquist is disgusted. Robot Primus and Helena develop human feelings and fall in love. Playing a hunch, Alquist threatens to dissect Primus and then Helena; each begs him to take him- or herself and spare the other. Alquist now realizes that Primus and Helena are the new Adam and Eve, and gives the charge of the world to them. == Čapek's conception of robots == The robots described in Čapek's play are not robots in the popularly understood sense of an automaton. They are not mechanical devices, but rather artificial biological organisms that may be mistaken for humans. A comic scene at the beginning of the play shows Helena arguing with her future husband, Harry Domin, because she cannot believe his secretary is a robotess: His robots resemble more modern conceptions of man-made life forms, such as the Replicants in Blade Runner, the "hosts" in the Westworld TV series and the humanoid Cylons in the re-imagined Battlestar Galactica, but in Čapek's time there was no conception of modern genetic engineering (DNA's role in heredity was not confirmed until 1952). There are descriptions of kneading-troughs for robot skin, great vats for liver and brains, and a factory for producing bones. Nerve fibers, arteries, and intestines are spun on factory bobbins, while the robots themselves are assembled like automobiles. Čapek's robots are living biological beings, but they are still assembled, as opposed to grown or born. One critic has described Čapek's robots as epitomizing "the traumatic transformation of modern society by the First World War and the Fordist assembly line". === Origin of the word robot === The play introduced the word robot, which displaced older words such as "automaton" or "android" in languages around the world. In an article in Lidové noviny, Karel Čapek named his brother Josef as the true inventor of the word. In Czech, robota means forced labour of the kind that serfs had to perform on their masters' lands and is derived from rab, meaning "slave". The name Rossum is an allusion to the Czech word rozum, meaning "reason", "wisdom", "intellect" or "common sense". It has been suggested that the allusion might be preserved by translating "Rossum" as "Reason" but only the Majer/Porter version translates the word as "Reason". == Production history and translations == The work was published in two differing versions in Prague by Aventinum, first in 1920, followed by a revised version in 1921. After being postponed, it premiered at the city's National Theatre on 25 January 1921, although an amateur group had by then already presented a production. By 1921, Paul Selver translated either the original 1920 edition of R.U.R. or a manuscript copy close to this version into English. He probably translated the play freelance, and sold it to St Martin's Theatre in London. Selver's translation was adapted for the British stage by Nigel Playfair in 1922, but it was not produced straight away. Later that year performance rights for the U.S. and Canada were sold to the New York Theatre Guild, perhaps during Lawrence Langner's visit to Britain. Playfair's version included several changes to Čapek's original play, such as renaming the acts (the prologue became act one, and the heavily abridged final act became the epilogue), omitting around sixty lines (including most of Alquist's final speech), adding several more lines, and removing the robot character Damon (giving his lines to Radius). The omission of some lines may have been censorship from the Lord Chamberlain's Office, or self-censorship in anticipation of this, while some other changes might have been made by Čapek himself if Selver was working from a manuscript copy. An edition of Playfair's adaptation was published by the Oxford University Press in 1923, and Selver went on to write a satiric novel One, Two, Three (1926) based on his experiences getting R.U.R. staged. The American première was produced by the Theatre Guild at the Garrick Theatre in New York City in October 1922, where it ran for 184 performances. In the first performance, Domin was portrayed by Basil Sydney,
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Alice and Sparkle

Alice and Sparkle is a 2022 illustrated children's book published by American technology product designer Ammaar Reshi. Reshi created the book using artificial intelligence programs ChatGPT and Midjourney in one weekend, which sparked controversy among artists, both in regard to the copyright status of the book and the quality of the illustration and text. == Plot == A girl named Alice discovers a group of magical and benevolent artificial intelligence beings. She knows that artificial intelligence is powerful, and that it has the power to do good and evil depending on how it is used. One day, she creates her own artificial intelligence and names it Sparkle. Sparkle helps Alice with her homework and plays with her, and they quickly become good friends. However, Sparkle soon grows more powerful and begins to make its own decisions, which makes Alice both proud and scared. She knows that it is her responsibility to guide Sparkle to do good, not evil. Together, Alice and Sparkle use their knowledge to make the world a better place and to teach people about the power of artificial intelligence. The two live happily ever after, spreading the magic of artificial intelligence. == Structure == Including the dedication and postscript, the book contains twenty four pages, about half of which being illustrations provided by Midjourney. The very short story, composed of text generated by ChatGPT, contains 343 words. Some of the illustrations are accompanied by descriptions, at least one of which was provided by Reshi. Both Alice's and Sparkle's appearances change significantly between illustrations, although Alice's is more consistent. Reshi said Midjourney was unable to generate consistent images of Sparkle, so he had to include a line in the book saying that it could turn "into all kinds of robot shapes". == Creation == When reading a children's book to his friend's daughter, Ammaar Reshi "decided he wanted to write his own". He had no experience with creative writing or illustration, so instead used the chatbot ChatGPT to write the story for him and used the image generation software Midjourney to illustrate it. On December 4, 2022, 72 hours after having the idea for the book, he published it on Amazon's digital bookstore, and published a paperback version the following day. == Controversy == On December 9, 2022, Reshi made a thread on Twitter about his experience publishing the book, which soon went viral. Reshi received heavy backlash from artists with concerns over the ethics of art generated by artificial intelligence. He also received death threats and messages encouraging self-harm because of his publication. Many writers and illustrators criticized both the creation process and the product itself, claiming that if artificial intelligence programs such as Midjourney are trained on existing illustrations, then the original artists should be financially compensated for derivative works such as Alice and Sparkle. The book was temporarily removed from Amazon in January 2023 because of "suspicious review activity", caused by a high volume of both five-star and one-star reviews.
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Local ternary patterns

Local ternary patterns (LTP) are an extension of local binary patterns (LBP). Unlike LBP, it does not threshold the pixels into 0 and 1, rather it uses a threshold constant to threshold pixels into three values. Considering k as the threshold constant, c as the value of the center pixel, a neighboring pixel p, the result of threshold is: { 1 , if p > c + k 0 , if p > c − k and p < c + k − 1 if p < c − k {\displaystyle {\begin{cases}1,&{\text{if }}p>c+k\\0,&{\text{if }}p>c-k{\text{ and }}p Read more →
Padre Pio (2022 film)

Padre Pio is a 2022 biographical drama film co-written and directed by Abel Ferrara. It stars Shia LaBeouf as the titular role of Padre Pio, a Capuchin Franciscan priest who receives the stigmata, in the background of the World War I in Italy. The film is a co-production of Italy, Germany and the United Kingdom. During its production, LaBeouf converted to Catholicism as result of his spiritual experiences in character as Pio, who is venerated as a saint by the Catholic Church. The film had its world premiere in the Giornate degli Autori section of the 79th Venice International Film Festival on 2 September 2022. It was released theatrically in the United Kingdom on 26 January 2024 by Dazzler Media and in Italy on 18 July 2024 by RS Productions. == Plot == It is the year 1920. Italian WWI veterans have returned to their impoverished villages. Padre Pio arrives at San Giovanni Rotondo after living with his family in Pietrelcina for a number of years. While still sick, he continues to encounter Satan. Satan reveals himself as the instigator of the war and the sociopolitical problems of San Giovanni. While having little contact with the people of this town, Padre Pio learns what the poor are suffering from in the Sacrament of Confession and the Holy Mass, such as when a crippled man walks again because of Padre Pio's prayer. Besides the effects of war, such as medical inadequacy, health conditions and labourers dying from the effects of mustard gas, the people suffer from corrupt, wealthy landowners. Gerardo, a militaristic anti-socialist, threatens to kill any communal labourers tending his land. Many of them join the socialist party as a way to improve their lives. However, after they win the first free election in San Giovanni, Gerardo's forces massacre many of them. Padre Pio asks God that he may become a suffering servant for their salvation. He receives the wounds of Jesus Christ. The stigmata disrupts Satan's influence on San Giovanni Rotondo. == Cast == Shia LaBeouf as Padre Pio Marco Leonardi as Gerardo Salvatore Ruocco as Vincenzo Cristina Chiriac as Giovanna Brando Pacitto as Renato Luca Lionello as Silvestro Asia Argento as Tall Man == Production == According to Abel Ferrara, actor Willem Dafoe suggested that Shia LaBeouf should be cast for the film's leading role. After Ferrara held several Zoom calls with LaBeouf, the latter agreed to join the film, even though very little money was raised (the film was almost never made) and LaBeouf did the project for free. LaBeouf arrived at Old Mission Santa Inés in July 2021 to learn about Padre Pio with the Capuchin Franciscan friars. Thanks to Father Bobby Barbato and Brother Jude Quinto, Br. Alexander Rodriguez met LaBeouf while he attended Mass every day. He learned about the Catholic Church and the Capuchins while living in his truck or spending a few nights in the Capuchin's guest room. He was immersing himself in the Catholic faith. He enrolled in RCIA, revised the script with Rodriguez and trained to do the Latin Mass. Rodriguez traveled with LaBeouf as his spiritual adviser and catechist and was in the film as Padre Pio's companion. Filming occurred in Apulia, Italy, in December 2021. The first place was at the Capuchin friary in San Marco la Catola. Padre Pio exchanged letters with his provincial and spiritual director while living in Pietrelcina with his family. The time was around 1909–1916. Both directors were living in San Marco during these years. Padre Pio expressed in his letters his deep and mysterious relationship with God and health difficulties. This event is in the film. While filming, LaBeouf slept in Padre Pio's bedroom. After San Marco, filming continued outside the Sanctuary of Saint Michael the Archangel in Monte Sant'Angelo. Traditionally, St. Michael appeared here in the late 400s. LaBeouf stayed and filmed for a few weeks at the Abbey of Saint Mary of Pulsano. It is near the sanctuary. The rest of the filming took place outside the sanctuary. Ferrara said in 2024 that he used AI for the Italian dub of this film. == Release == Padre Pio had its world premiere in the Giornate degli Autori section of the 79th Venice International Film Festival on 2 September 2022. It received a four-minute ovation. It also competed at the Rio de Janeiro International Film Festival. At the Lisbon & Estoril Film Festival, it was chosen to compete for the "Best Film Award." During its North American premiere at the Mammoth Film Festival, it won the "Achievement for Filmmaking" award for cinematography. At the Taormina Film Festival, it premiered worldwide in Italian. In March 2023, Gravitas Ventures acquired North American rights to the film. It was released in select theaters and on video on demand in the United States on 2 June 2023. The film was released in the United Kingdom and Ireland on 26 January 2024 by Dazzler Media. RS Productions released it in Italy on 18 July 2024. == Reception == On the review aggregator website Rotten Tomatoes, the film holds an approval rating of 30% based on 43 reviews, with an average rating of 4.5/10. The website's critics consensus reads, "Tonally unbalanced and burdened with a distracting Shia LaBeouf performance, Padre Pio is one of Abel Ferrara's less divine works." Metacritic, which uses a weighted average, assigned the film a score of 45 out of 100, based on 6 critics, indicating "mixed or average" reviews.. Jordan Mintzer of The Hollywood Reporter gave the film a negative review, describing it as "clunky" and criticizing its political themes for possessing "the subtlety of a cartoon for preschoolers." Brian Tallerico of RogerEbert.com gave the film one and a half stars out of four, describing it as a "dull slog". Journalist Glenn Kenny of The New York Times found the film "occasionally rank" and panned LaBeouf's performance, though complimented Ferrara's "sometimes Brechtian consideration of the nodes of political history and spirituality." Film critic Armond White of National Review also criticized the film, describing it as "a work of deluded, semi-improvisational navel-gazing". Film critic Peter Bradshaw of The Guardian gave the film a positive review, with three out of five stars, writing that it is "a weird film...with an undeveloped, improvised feel, like a fragment or shard of something else. Yet there is a background hum there...an awareness of something dark and malign. It is a minor film but interesting." Writing for The New Yorker, Richard Brody considered that "in its hectic, scattershot way, Padre Pio feels very much of the desperate present day," describing it as "a historical drama without historical distance" and "a wild effort to reach the immediate experience of the past and its furies." Faith-based reviews for the film were generally negative. It received negative reviews from Catholic Answers, The Catholic World Report, The Catholic Weekly, The Catholic Thing, and Crisis Magazine. Conversely, it received a mixed review from The Catholic Review, as well as a positive review from America. Criticisms were generally aimed at the film's sexual content and perceived support of left-wing politics.
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Fuzzy differential inclusion

Fuzzy differential inclusion is the extension of differential inclusion to fuzzy sets introduced by Lotfi A. Zadeh. x ′ ( t ) ∈ [ f ( t , x ( t ) ) ] α {\displaystyle x'(t)\in [f(t,x(t))]^{\alpha }} with x ( 0 ) ∈ [ x 0 ] α {\displaystyle x(0)\in [x_{0}]^{\alpha }} Suppose f ( t , x ( t ) ) {\displaystyle f(t,x(t))} is a fuzzy valued continuous function on Euclidean space. Then it is the collection of all normal, upper semi-continuous, convex, compactly supported fuzzy subsets of R n {\displaystyle \mathbb {R} ^{n}} . == Second order differential == The second order differential is x ″ ( t ) ∈ [ k x ] α {\displaystyle x''(t)\in [kx]^{\alpha }} where k ∈ [ K ] α {\displaystyle k\in [K]^{\alpha }} , K {\displaystyle K} is trapezoidal fuzzy number ( − 1 , − 1 / 2 , 0 , 1 / 2 ) {\displaystyle (-1,-1/2,0,1/2)} , and x 0 {\displaystyle x_{0}} is a trianglular fuzzy number (-1,0,1). == Applications == Fuzzy differential inclusion (FDI) has applications in Cybernetics Artificial intelligence, Neural network, Medical imaging Robotics Atmospheric dispersion modeling Weather forecasting Cyclone Pattern recognition Population biology
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Artificial intelligence engineering

Artificial intelligence engineering (AI engineering) is a technical discipline that focuses on the design, development, and deployment of AI systems. AI engineering involves applying engineering principles and methodologies to create scalable, efficient, and reliable AI-based solutions. It merges aspects of data engineering and software engineering to create real-world applications in diverse domains such as healthcare, finance, autonomous systems, and industrial automation. == Terminology ambiguity == According to Chip Huyen's book AI Engineering: Building Applications with Foundation Models, the term AI engineering refers to the process of building applications that use foundation models, which are typically models developed by a small number of research laboratories and made available as a service. Huyen distinguishes this from machine learning (ML) engineering, which involves building and deploying models developed in-house. She notes that most practical AI systems combine both approaches. For example, a customer-support chatbot may use a generative model to produce responses while also incorporating locally built components such as request classifiers or scoring mechanisms to assess response quality. As a result, the terms AI engineering and ML engineering are often used together or interchangeably in practice. The distinction and broader usage of the term have been discussed in industry publications and interviews, where AI engineering has been described as an emerging discipline focused on productionizing applications built with foundation models. == Key components == AI engineering integrates a variety of technical domains and practices, all of which are essential to building scalable, reliable, and ethical AI systems. === Data engineering and infrastructure === Data serves as the cornerstone of AI systems, necessitating careful engineering to ensure premium quality, wide spread availability, and usability. AI engineers gather large, diverse datasets from multiple sources such as databases, APIs, and real-time streams. This data undergoes cleaning, normalization, and preprocessing, often facilitated by automated data pipelines that manage extraction, transformation, and loading (ETL) processes. Efficient storage solutions, such as SQL (or NoSQL) databases and data lakes, must be selected based on data characteristics and use cases. Security measures, including encryption and access controls, are critical for protecting sensitive information and ensuring compliance with regulations like GDPR. Scalability is essential, frequently involving cloud services and distributed computing frameworks to handle growing data volumes effectively. === Algorithm selection and optimization === Selecting the appropriate algorithm is crucial for the success of any AI system. Engineers evaluate the problem (which could be classification or regression, for example) to determine the most suitable machine learning algorithm, including deep learning paradigms. Once an algorithm is chosen, optimizing it through hyperparameter tuning is essential to enhance efficiency and accuracy. Techniques such as grid search or Bayesian optimization are employed, and engineers often utilize parallelization to expedite training processes, particularly for large models and datasets. For existing models, techniques like transfer learning can be applied to adapt pre-trained models for specific tasks, reducing the time and resources needed for training. === Deep learning engineering === Deep learning is particularly important for tasks involving large and complex datasets. Engineers design neural network architectures tailored to specific applications, such as convolutional neural networks for visual tasks or recurrent neural networks for sequence-based tasks. Transfer learning, where pre-trained models are fine-tuned for specific use cases, helps streamline development and often enhances performance. Optimization for deployment in resource-constrained environments, such as mobile devices, involves techniques like pruning and quantization to minimize model size while maintaining performance. Engineers also mitigate data imbalance through augmentation and synthetic data generation, ensuring robust model performance across various classes. === Natural language processing === Natural language processing (NLP) is a crucial component of AI engineering, focused on enabling machines to understand and generate human language. The process begins with text preprocessing to prepare data for machine learning models. Recent advancements, particularly transformer-based models like BERT and GPT, have greatly improved the ability to understand context in language. AI engineers work on various NLP tasks, including sentiment analysis, machine translation, and information extraction. These tasks require sophisticated models that utilize attention mechanisms to enhance accuracy. Applications range from virtual assistants and chatbots to more specialized tasks like named-entity recognition (NER) and Part of speech (POS) tagging. === Reasoning and decision-making systems === Developing systems capable of reasoning and decision-making is a significant aspect of AI engineering. Whether starting from scratch or building on existing frameworks, engineers create solutions that operate on data or logical rules. Symbolic AI employs formal logic and predefined rules for inference, while probabilistic reasoning techniques like Bayesian networks help address uncertainty. These models are essential for applications in dynamic environments, such as autonomous vehicles, where real-time decision-making is critical. === Security === Security is a critical consideration in AI engineering, particularly as AI systems become increasingly integrated into sensitive and mission-critical applications. AI engineers implement robust security measures to protect models from adversarial attacks, such as evasion and poisoning, which can compromise system integrity and performance. Techniques such as adversarial training, where models are exposed to malicious inputs during development, help harden systems against these attacks. Additionally, securing the data used to train AI models is of paramount importance. Encryption, secure data storage, and access control mechanisms are employed to safeguard sensitive information from unauthorized access and breaches. AI systems also require constant monitoring to detect and mitigate vulnerabilities that may arise post-deployment. In high-stakes environments like autonomous systems and healthcare, engineers incorporate redundancy and fail-safe mechanisms to ensure that AI models continue to function correctly in the presence of security threats. === Ethics and compliance === As AI systems increasingly influence societal aspects, ethics and compliance are vital components of AI engineering. Engineers design models to mitigate risks such as data poisoning and ensure that AI systems adhere to legal frameworks, such as data protection regulations like GDPR. Privacy-preserving techniques, including data anonymization and differential privacy, are employed to safeguard personal information and ensure compliance with international standards. Ethical considerations focus on reducing bias in AI systems, preventing discrimination based on race, gender, or other protected characteristics. By developing fair and accountable AI solutions, engineers contribute to the creation of technologies that are both technically sound and socially responsible. == Workload == An AI engineer's workload revolves around the AI system's life cycle, which is a complex, multi-stage process. This process may involve building models from scratch or using pre-existing models through transfer learning, depending on the project's requirements. Each approach presents unique challenges and influences the time, resources, and technical decisions involved. === Problem definition and requirements analysis === Regardless of whether a model is built from scratch or based on a pre-existing model, the work begins with a clear understanding of the problem. The engineer must define the scope, understand the business context, and identify specific AI objectives that align with strategic goals. This stage includes consulting with stakeholders to establish key performance indicators (KPIs) and operational requirements. When developing a model from scratch, the engineer must also decide which algorithms are most suitable for the task. Conversely, when using a pre-trained model, the workload shifts toward evaluating existing models and selecting the one most aligned with the task. The use of pre-trained models often allows for a more targeted focus on fine-tuning, as opposed to designing an entirely new model architecture. === Data acquisition and preparation === Data acquisition and preparation are critical stages regardless of the development method chosen, as the performance of any AI system relies heavily on high-quality, re
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AdTruth

AdTruth is a software product and the digital media division of 41st Parameter, a company headquartered in Scottsdale, Arizona, with regional offices in San Jose, California; London, England; and Munich, Germany. AdTruth allows marketers to recognize and reach target audiences across online devices. AdTruth software identifies users for targeting, tracking, performance tracking across digital media, including mobile and desktop, by analysing patterns in large numbers of advertisements served over the internet, rather than through the use of cookies. == History == AdTruth was founded in 2011 by Ori Eisen of 41st Parameter, to repurpose the company's fraud detection and prevention technology, for use within the advertising industry to accurately target intended audiences, particularly in mobile. Eisen was joined by James Lamberti in the role of vice president and general manager. In 2012 41st Parameter raised $13 million in Series D financing from Norwest Venture Partners, Kleiner Perkins Caufield & Byers, Jafco Ventures and Georgian Partners, bringing total funding to about $35 million. In May 2012, AdTruth hosted a meeting of digital media executives to discuss Apple’s UDID deprecation, with the intent of developing a device-neutral replacement standard. AdTruth joined the World Wide Web Consortium's Tracking Protection Working Group, which provides guidance for implementing and adhering to Do Not Track policies. AdTruth also worked with privacy firm Truste to create a privacy compliant Do Not Track-style mechanism for mobile. In 2013, the company Experian purchased 41st Parameter, acquiring AdTruth as part of the deal. == Product == AdTruth software helps marketers track, target and retarget consumers using more than 100 parameters, including milliseconds in differences in the internal clock setting, to recognize a particular device anonymously. AdTruth's technology uses non-UDID information to identify a wide range of devices for cookieless ad targeting. Its technology currently has about a 90 percent accuracy rate on iOS, higher on Android and desktop. AdTruth also has mobile web to app bridging capabilities as well as DeviceInsight technology, enabling marketers to identify users across mobile web and app content. 41st Parameter's patented AdTruth technology is being used by MdotM, in response to the deprecation of the UDID that included tracking and targeting capabilities. == Competitors == AdTruth's main competitor is BlueCava, which deploys a similar device-fingerprinting technology.
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Taylor Swift deepfake pornography controversy

In late January 2024, sexually explicit AI-generated deepfake images of American musician Taylor Swift were proliferated on social media platforms 4chan and X (formerly Twitter). Several artificial images of Swift of a sexual or violent nature were quickly spread, with one post reported to have been seen over 47 million times before its eventual removal. The images led Microsoft to enhance Microsoft Designer's text-to-image model to prevent future abuse. Moreover, these images prompted responses from anti-sexual assault advocacy groups, US politicians, Swifties, and Microsoft CEO Satya Nadella, among others, and it has been suggested that Swift's influence could result in new legislation regarding the creation of deepfake pornography. A similar controversy emerged in August 2025, when The Verge reported AI image and video tool Grok Imagine generated sexually explicit images and videos of Swift from an otherwise innocuous text prompt. == Background == American musician Taylor Swift has been the target of misogyny and slut-shaming throughout her career. American technology corporation Microsoft offers AI image creators called Microsoft Designer and Bing Image Creator, which employ censorship safeguards to prevent users from generating unsafe or objectionable content. Members of a Telegram group discussed ways to circumvent these censors to create pornographic images of celebrities. Graphika, a disinformation research firm, traced the creation of the images back to a 4chan community. == Reactions == For some, the deepfake images of Swift immediately became a source of controversy and outrage. Other internet users found them humorous and absurd, such as the image making it appear as though Swift was to engage in sexual intercourse with Oscar the Grouch. The images drew condemnations from Rape, Abuse & Incest National Network and SAG-AFTRA. The latter group, who had been following issues regarding AI-generated media prior to Swift's involvement, considered the images "upsetting, harmful and deeply concerning." Microsoft CEO Satya Nadella, whose company's products were believed to be used to make these images, responded to the controversy as "alarming and terrible", further stating his belief that "we all benefit when the online world is a safe world." === Taylor Swift === A source close to Swift told the Daily Mail that she would be considering legal action, saying, "Whether or not legal action will be taken is being decided, but there is one thing that is clear: These fake AI-generated images are abusive, offensive, exploitative, and done without Taylor's consent and/or knowledge." === Politicians === White House press secretary Karine Jean-Pierre expressed concern over the counterfeit images, deeming them "alarming", and emphasized the obligation of social media platforms to curb the dissemination of misinformation. Several members of American politics called for legislation against AI-generated pornography. Later in the month, a bipartisan bill was introduced by US senators Dick Durbin, Lindsey Graham, Amy Klobuchar and Josh Hawley. The bill would allow victims to sue individuals who produced or possessed "digital forgeries" with intent to distribute, or those who received the material knowing it was made without consent. The European Union struck a deal in February 2024 on a similar bill that would criminalize deepfake pornography, as well as online harassment and revenge porn, by mid-2027. === Social media platforms === X responded to the sharing of these images on their own website with claims they would suspend accounts that participated in their spread. Despite this, the photos continued to be reshared among accounts of X, and spread to other platforms including Instagram and Reddit. X enforces a "synthetic and manipulated media policy", which has been criticized for its efficacy. They briefly blocked searches of Swift's name on January 27, 2024, reinstating them two days later. === Swifties === Fans of Taylor Swift, known as Swifties, responded to the circulation of these images by pushing the hashtag #ProtectTaylorSwift to trend on X. They also flooded other hashtags related to the images with more positive images and videos of her live performances. == Cultural significance == Deepfake pornography has remained highly controversial and has affected figures from other celebrities to ordinary people, most of whom are women. Journalists have opined that the involvement of a prominent public figure such as Swift in the dissemination of AI-generated pornography could bring public awareness and political reform to the issue.
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Jake Elwes

Jake Elwes () is a British media artist, hacker and researcher. Their practice is the exploration of artificial intelligence (AI), queer theory and technical biases. They are known for using AI to create art in mediums such as video, performance and installation. Elwes considers themselves to be neuroqueer, and their work on queering technology addresses issues caused by the normative biases of artificial intelligence. == Education and early life == Elwes was born in London to British contemporary artist and painter Luke Elwes and Anneke, daughter of Hans Dumoulin. Elwes is the great grandchild of Army officer James Hennessy and portrait painter Simon Elwes RA, son of Victorian opera singer Gervase Elwes. Elwes studied at the Slade School of Fine Art from 2013 to 2017, where they began using computer code as a medium. In 2016 they attended the School of Machines, Making & Make-Believe in Berlin with artist and educator Gene Kogan. Elwes was introduced to drag performance by their collaborator Dr Joe Parslow who holds a PhD in drag performance. Drag performance has since become instrumental to Elwes' work. == Career == Elwes' work with artificial intelligence is cited as a hopeful strategy to make AI more playful and diverse. Elwes' work has been exhibited in numerous international art museums and galleries and was featured in a BBC documentary on the history of video art, they were a 2021 finalist for the Lumen Prize, and received the Honorary Mention of the 2022 Prix Ars Electronica in the Interactive Art + category. They also curated and presented the opening provocation "The New Real - Artistic and Queer Visions of AI Futures" to the UK government with two drag artists at the AI UK conference 2024. Elwes is part of the Radical Faeries countercultural movement. They have exhibited in museums and galleries across Europe and Asia including: Victoria and Albert Museum (London, UK) - The Zizi Show (2023-2024) for the first digital commission in their photography center's digital gallery Pinakothek der Moderne (Munich, Germany) - Glitch. Die Kunst Der Störung (2023-2024) ZKM (Karlsruhe, Germany) - Biomedia (2021-2022) National Museum of Modern and Contemporary Art (Cheongju, South Korea) - What an Artificial World (2024) Somerset House (London, UK) - The Horror Show! (2022-2023) Gazelli Art House (London, UK) - Jake Elwes: Data • Glitch • Utopia (2023) (survey exhibition) Jut Art Museum (Taipei, Taiwan) - Future Lives, Future You (2023-2024) Max Ernst Museum (Brühl, Germany) - Surreal Futures (2023-2024) Zabludowicz Collection (London, UK) - Among the Machines (2022) Ars Electronica (Linz, Austria) - Prix Ars Electronica, CyberArts Exhibition (2022) Institute of Contemporary Arts (ICA) (London, UK) - Do Androids Dream on Silver Screens? (2023) Arebyte gallery (London, UK) - Real-Time Constraints (2020) Ming Contemporary Art Museum (McaM) (Shanghai, China) - Mind the Deep (2019) HMKV (Hartware MedienKunstVerein) (Dortmund, Germany) - House of Mirrors: Artificial Intelligence as Phantasm (2022) Today Art Museum (Beijing, China) - Future of Today: DEJA VU (2019) Science Gallery (Dublin, Ireland) - BIAS (2021-2022) Yuz Museum (Shanghai, China) - Lying Sophia and Mocking Alexa (2021) Fotomuseum Winterthur The Onassis Foundation (Athens, Greece) - You and AI (2021) Royal College of Art (London, UK) - Event Two (2019) (50th anniversary of Computer Arts Society & Event One) Museum für Naturkunde (Berlin, Germany) - Forschungsfall Nachtigall (2019) Frankfurter Kunstverein (Frankfurt, Germany) - I am here to learn (2018) Nature Morte (Delhi, India) - Gradient Descent (2018) BALTIC Centre for Contemporary Art (Newcastle, UK) - Bloomberg New Contemporaries (2017) == Artworks == === The Zizi Project - a deepfake drag cabaret === The Zizi Project is a series of works that explore the interaction of drag and A.I. Currently, The Zizi Project is made up of multiple artworks. ==== Zizi - Queering the Dataset (2019) ==== Knowing that facial recognition technology statically struggle to recognize black women or transgender people, Elwes set out to "Queer the Dataset" through an open-sourced generative adversarial network (GAN, a type of machine learning model and an early Generative artificial intelligence). Elwes added a dataset of 1,000 photos of drag kings and queens into the GAN's 70,000 faces collected in a standardised facial recognition dataset called Flickr-Faces-HQ Dataset (FFHQ). They then created new simulacra faces, known as deep fakes. "We queer that data so it shifts all of the weights in this neural network from a space of normativity into a space of queerness and otherness. Suddenly all of the faces start to break down and you see mascara dissolve into lipstick and blue eye shadow turn into a pink wig" said Elwes in a 2023 interview for Artnet. ==== Zizi & Me (2020–2023) ==== Zizi & Me is an ongoing multimedia collaboration between drag queen Me The Drag Queen and a deepfake A.I. clone of Me The Drag Queen. Using neural networks trained on filmed footage, the project creates a virtual body that can mimic reference movements. The first act, which features a digital lip-sync duet to Anything You Can Do (I Can Do Better), satirises the idea of A.I. being mistaken for a human, using drag performance and cabaret to critique societal narratives about A.I. and its role in shaping identity. The project is part of The Zizi Project by Jake Elwes, which explores the intersection of drag performance and A.I. ==== The Zizi Show - A Deepfake Drag Cabaret (2020) ==== The Zizi Show is a deep fake drag act based on artificial intelligence (AI). It has been presented live and as interactive online artwork. It is an exploration of queer culture and the algorithms philosophy and ethics of AI. The Zizi Show was exhibited as the inaugural exhibition in the digital gallery at the V&A’s Photography Center from 2023 to 2024. ==== Zizi in Motion: A Deepfake Drag Utopia (Movement by Wet Mess) (2023) ==== "Zizi in Motion" is a multichannel silent video installation featuring AI-generated deepfake performances, which are dynamically re-animated through the movements of London drag artist Wet Mess. The movements of Wet Mess cause the AI-generated visuals to glitch and distort, showcasing the interaction between drag performance and artificial intelligence. The work explore the potential for queer communities to ethically and creatively reclaim and repurpose deepfake technology, using it to celebrate queer bodies and identities. === Art in the Cage of Digital Reproduction (2024) === In an act of protest on 26 November 2024, Elwes facilitated indirect access to an early access token for OpenAI’s Sora text-to-video model through a Hugging Face frontend under the account "PR Puppets". The accompanying statement called to 'denormalize the exploitation of artists by major AI companies for training data, R&D, and publicity'. The incident attracted international press coverage calling into question the role of artists in shaping the future of generative AI versus merely serving as data and credibility providers for tech giants. Elwes also coordinated a collection of mini essays with responses and reflections from the signees and guest writers titled "Art in the Cage of Digital Reproduction". === Installations exploring interpretation and feedback loops between neural networks === Elwes has created works based on the interpretations and misinterpretations between different neural networks and training datasets including: A.I. Interprets A.I. Interpreting ‘Against Interpretation’ (Sontag 1966) from 2023, Closed Loop from 2017, and Auto-Encoded Buddha from 2016. ==== A.I. Interprets A.I. Interpreting ‘Against Interpretation’ (Sontag 1966) (2023) ==== A.I. Interprets A.I. Interpreting ‘Against Interpretation (Sontag 1966) is a three-channel video artwork where an AI interprets Susan Sontag’s essay into images, and then and another AI reinterprets those images back into language. The piece highlights how AI-generated art can misinterpret and introduce bias. ==== Closed Loop (2017) ==== Closed Loop is a two-channel video where two neural networks engage in a continuous feedback loop, one generating images based on the text output and the other creating text based on the image output. The work explores how AI models misinterpret and evolve in a surreal, self-perpetuating conversation, without human input. ==== Auto-Encoded Buddha (2016) ==== Auto-Encoded Buddha is a mixed-media piece where an AI attempts to generate an image of a Buddha statue, trained on 5,000 Buddha images. The AI struggles to accurately represent the Buddha, highlighting the limitations of early generative neural networks. The work is a tribute to Nam June Paik’s TV Buddha (1974). === CUSP (2019) === In their video work CUSP (2019) Elwes places marsh birds generated using artificial intelligence into a tidal landscape. These digitally generated and constantly shifting birds are recorded in dialogue with native
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Oriented energy filters

Oriented energy filters are used to grant sight to intelligent machines and sensors. The light comes in and is filtered so that it can be properly computed and analyzed by the computer allowing it to “perceive” what it is measuring. These energy measurements are then calculated to take a real time measurement of the oriented space time structure. 3D Gaussian filters are used to extract orientation measurements. They were chosen due to their ability to capture a broad spectrum and easy and efficient computations. The use of these vision systems can then be used in smart room, human interface and surveillance applications. The computations used can tell more than the standalone frame that most perceived motion devices such as a television frame. The objects captured by these devices would tell the velocity and energy of an object and its direction in relation to space and time. This also allows for better tracking ability and recognition.
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Pharmacy automation

Pharmacy automation involves the mechanical processes of handling and distributing medications. Any pharmacy task may be involved, including counting small objects (e.g., tablets, capsules); measuring and mixing powders and liquids for compounding; tracking and updating customer information in databases (e.g., personally identifiable information (PII), medical history, drug interaction risk detection); and inventory management. This article focuses on the changes that have taken place in the local, or community pharmacy since the 1960s. == History == Dispensing medications in a community pharmacy before the 1970s was a time-consuming operation. The pharmacist dispensed prescriptions in tablet or capsule form with a simple tray and spatula. Many new medications were developed by pharmaceutical manufacturers at an ever-increasing pace, and medications prices were rising steeply. A typical community pharmacist was working longer hours and often forced to hire staff to handle increased workloads which resulted in less time to focus on safety issues. These additional factors led to use of a machine to count medications. The original electronic portable digital tablet counting technology was invented in Manchester, England between 1967 and 1970 by the brothers John and Frank Kirby. I had the original idea of how the machine would work and it was my patent, but it was a joint effort getting it to work in a saleable form. It was 3 years of very hard work. I had originally studied heavy electrical engineering before changing over to Medical School and qualifying as a Medical Doctor in 1968. In fact I was Senior House (Casualty) Officer (A&E or ER) in 1970 at North Manchester General Hospital when I filed the patent. I must have been the only hospital doctor in Britain with an oscilloscope, a soldering iron and a drawing board in his room in the Doctors' Residence. The housekeepers were bemused by all the wires. Frank originally trained as a Banker but quit to take a job with a local electronics firm during the development. He died in 1987, a terrible loss. [Extract from personal communication received in March 2010 from John Kirby.] Frank and John Kirby and their associate Rodney Lester were pioneers in pharmacy automation and small-object counting technology. In 1967, the Kirbys invented a portable digital tablet counter to count tablets and capsules. With Lester they formed a limited company. In 1970, their invention was patented and put into production in Oldham, England. The tablet counter aided the pharmacy industry with time-consuming manual counting of drug prescriptions. A counting machine consistently counted medications accurately and quickly. This aspect of pharmacy automation was quickly adopted, and innovations emerged every decade to aid the pharmacy industry to deliver medications quickly, safely, and economically. Modern pharmacies have many new options to improve their workflow by using the new technology, and can choose intelligently from the many options available. === Chronology === On 1 January 1971 commercial production of the first portable digital tablet counters in the World began. John Kirby had filed U.K. Patent number GB1358378(A) on 8 September 1970 and U.S. patent number 3789194 on 9 August 1971. These early electronic counters were designed to help pharmacies replace the common (but often inaccurate) practice of counting medications by hand. In 1975, the digital technology was exported to America. In early 1980 a dedicated research, development and production facility was built in Oldham, England at a cost of £500,000. Between 1982 and 1983, two separate development facilities had been created. In America, overseen by Rodney Lester; and in England, overseen by the Kirby brothers. In 1987, Frank Kirby died. In 1989, John Kirby moved his UK facility to Devon, England. A simple to operate machine had been developed to accurately and quickly count prescription medications. Technology improvements soon resulted in a more compact model. The price of such equipment in 1980 was around £1,300. This substantial investment in new technology was a major financial consideration, but the pharmacy community considered the use of a counting machine as a superior method compared to hand-counting medications. These early devices became known as tablet counter, capsule counter, pill counter, or drug counter. The new counting technology replaced manual methods in many industries such as, vitamin and diet supplement manufacturing. Technicians needed a small, affordable device to count and bottle medications. In England and America, the 1980s and 1990s saw new the development of high-speed machines for counting and bottle filling, Like their pharmacy-based counterparts, these industrial units were designed to be fast and simple to operate, yet remain small and cost effective. In America, in the late 1990s/early 2000s a new type of tablet counter appeared. It was simple to use, compact, inexpensive, and had good counting accuracy. At the turn of the millennium technical advances allowed the design of counters with a software verification system. With an onboard computer, displaying photo images of medications to assist the pharmacist or pharmacy technician to verify that the correct medication was being dispensed. In addition, a database for storing all prescriptions that were counted on the device. Between September 2005 and May 2007, American Capital made a major financial investment in Kirby Lester, which then relocated to a larger facility to expand its research and development capabilities. This move added extra space for product research and development facility (R&D). It allowed the opportunity to develop new advanced technology products that met the pharmacy's needs for simple, accurate, and cost-effective ways to dispense prescriptions safely. Pictured here is an early American type of integrated counter and packaging device. This machine was a third generation step in the evolution of pharmacy automated devices. Later models held pre-counted containers of commonly-prescribed medications. == Global variations == In the EU member states legislation was introduced in 1998 which had a major effect on UK Pharmacy operations. It effectively prohibited the use of tablet counters for counting and dispensing bulk packaged tablets. Both usage and sales of the machines in the UK declined rapidly as a result of the introduction of blister packaging for medicines. == Current state of the industry == A tablet counter has become a standard in more than 30,000 sites in 35 countries (as of 2010) (including many non-pharmacy sites, such as manufacturing facilities that use a counting machine as a check for small items). During the 1990s through 2012, numerous new pharmacy automation products came to market. During this timeframe, counting technologies, robotics, workflow management software, and interactive voice recognition (IVR) systems for retail (both chain and independent), outpatient, government, and closed-door pharmacies (mail order and central fill) were all introduced. Additionally, the concept of scalability - of migrating from an entry-level product to the next level of automation (e.g., counting technology to robotics) - was introduced and subsequently launched a new product line in 1997. Pharmacists everywhere are making the switch to automation for its increased speed, greater accuracy, and better security. As the industry evolves and customer expectations grow, automation is becoming less of a luxury and more of a necessity. Especially for independent pharmacies, automation is now a means of keeping up with the competition of large chain pharmacies. == Technological changes and design improvements == Constant developments in technology make the dispensing of prescription medications safer, more accurate and more efficient. In America, in 2008, "next-generation" counting and verification systems were introduced. Based on the counting technology employed in preceding models, later machines included the ability to help the pharmacy operate more effectively. Equipped with a new computer interface to a pharmacy management system, with workflow and inventory software. It also included "checks and balances" to ensure the technician and pharmacist were dispensing the correct medication for each patient. This is something that is important to keep reported correctly when dealing with controlled substances like narcotics. This was a step forward to verify all 100% of prescriptions that were dispensed by pharmacy staff. In America, in 2009, further advanced counters were designed that included the ability to dispense hands-free – a feature that many operators had desired. This allowed pharmacies to automate their most commonly dispensed medications via calibrated cassettes. Thirty of a pharmacy's common medications would now be dispensed automatically. Another new model doubled that throughput via an enclosed robotic mechanism. Robo
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Supreme Commander (video game)

Supreme Commander (sometimes SupCom) is a 2007 real-time strategy video game designed by Chris Taylor and developed by his company, Gas Powered Games. The game is considered to be a spiritual successor, not a direct sequel, to Taylor's 1997 game Total Annihilation. First announced in the August 2005 edition of PC Gamer magazine, the game was released in Europe on February 16, 2007, and in North America on February 20. The standalone expansion Supreme Commander: Forged Alliance was released on November 6 of the same year. The sequel, Supreme Commander 2, was released in 2010. Nowadays, the original Supreme Commander is played through the community client called Forged Alliance Forever; the game has been further developed and balanced, and offers a wide variety of community mods. The gameplay of Supreme Commander focuses on using a giant bipedal mech called an Armored Command Unit (ACU), the so-called "Supreme Commander", to build a base, upgrading units to reach higher technology tiers, and conquering opponents. The player can command one of three factions: the Aeon Illuminate, the Cybran Nation, or the United Earth Federation (UEF). The expansion game added the Seraphim faction. Supreme Commander was highly anticipated in pre-release previews, and was well received by critics, with a Metacritic average of 86 out of 100. == Gameplay == Supreme Commander, like its spiritual predecessors, Total Annihilation and Spring, begins with the player solely possessing a single, irreplaceable construction unit called the "Armored Command Unit," or ACU, the titular Supreme Commander. Normally the loss of this unit results in the loss of the game (Skirmish missions can be set for a variety of victory conditions). These mech suits are designed to be transported through quantum gateways across the galaxy and contain all the materials and blueprints necessary to create an army from a planet's native resources in hours. All standard units except Commanders and summoned Support Commanders (sACU) are self-sufficient robots. All units and structures belong to one of four technology tiers, or "Tech" levels, each tier being stronger and/or more efficient than the previous. Certain lower-tier structures can be upgraded into higher ones without having to rebuild them. The first tier is available at the start of the game and consists of small, relatively weak units and structures. The second tier expands the player's abilities greatly, especially in terms of stationary weapons and shielding, and introduces upgraded versions of tier one units. The third tier level has very powerful assault units designed to overcome the fortifications of the most entrenched player. The fourth tier is a limited range of "experimental" technology. These are usually massive units which take a lot of time and energy to produce, but provide a significant tactical advantage. Supreme Commander features a varied skirmish AI. The typical Easy' and Normal modes are present, but the Hard difficulty level has four possible variants. Horde AI will swarm the player with hordes of lower level units, Tech AI will upgrade its units as fast as possible and assault the player with advanced units, the Balanced AI attempts to find a balance between the two, and the Supreme AI decides which of the three hard strategies is best for the map. The single player campaign consists of eighteen missions, six for each faction. The player is an inexperienced Commander who plays a key role in their faction's campaign to bring the "Infinite War" to an end. Despite the low number of campaign missions, each mission can potentially last hours. At the start of a mission, objectives are assigned for the player to complete. Once the player accomplishes them, the map is expanded, sometimes doubling or tripling in size, and new objectives are assigned. As the mission is commonly divided into three segments, the player will often have to overcome several enemy positions to achieve victory. === Resource management === Because humans have developed replication technology, making advanced use of rapid prototyping and nanotechnology, only two types of resources are required to wage war: Energy and Mass. Energy is obtained by constructing power generators on any solid surface (except fuel generators, which can only be built on fuel deposits), while Mass is obtained either by placing mass extractors on limited mass deposit spots (the most efficient method, although it requires map control) or by building mass fabricators to convert energy into mass. Constructor units can gather energy by "reclaiming" it from organic debris such as trees and mass from rocks and wrecked units. Each player has a certain amount of resource storage, which can be expanded by the construction of storage structures. This gives the player reserves in times of shortage or allows them to stockpile resources. If the resource generation exceeds the player's capacity, the material is wasted. On the contrary, if the storages are depleted and the demand of one of the resources exceeds the production, then all the productions speed is reduced. In addition, if an energy deficit occurs, shields will stop working. An adjacency system allows certain structures to benefit from being built directly adjacent to others. Energy-consuming structures will use less energy when built adjacent to power generators and power generators will produce more energy when built adjacent to power storage structures. The same applies to their mass-producing equivalents. Likewise, factories will consume less energy and mass when built adjacent to power generators and mass fabricators/extractors, respectively. However, by placing structures in close proximity, they become more vulnerable to collateral damage if an adjacent structure is destroyed. Furthermore, most resource generation structures can cause chain reactions when destroyed (especially Tier III structures, which produce large amounts of resources but often have large detonations that can wipe out a nearby army). === Warfare === Supreme Commander uses a "strategic zoom" system that allows the player to seamlessly zoom from a detailed close up view of an individual unit all the way out to a view of the entire map, at which point it resembles a fullscreen version of the minimap denoting individual units with icons. The camera also has a free movement mode and can be slaved to track a selected unit and there is a split screen mode which also supports multiple monitors. This system allows Supreme Commander to use vast maps up to 80 km x 80 km, with players potentially controlling a thousand units each. Units in Supreme Commander are built to scale as they would be in the real world. For example, battleships dwarf submarines. Late into the game, the larger "experimental" units, such as the Cybran Monkeylord, an enormous spider-shaped assault unit, can actually crush smaller enemy units by stepping on them. Because of the wide range of planets colonized by humanity in the setting, the theatres of war range from desert to arctic, and all battlespaces are employed. Technologies emerging in modern warfare are frequently employed in Supreme Commander. For example, stealth technology and both tactical and strategic missile and missile defense systems can be used. Supreme Commander introduced several innovations designed to reduce the amount of micromanagement inherent in many RTS games. Engineers units have the command "assist", that will help follow other engineers and help them finish their orders or improve production rate of factories. In addition, engineers with the order "patrol" will repair units, buildings and recycle wrecks in their along their patrol route. Holding the shift key causes any orders given to a unit (or group of units) to be queued. In this manner a unit may be ordered to attack several targets in succession, or to make best speed to a given point on the map and then attack towards a specified location engaging any hostiles it encounters along the way. After orders have been issued, holding the shift key causes all issued orders to be displayed on the map where they can be subsequently modified to accommodate a change of plan. Further, when a unit is ordered to attack a target, the player can issue an order to perform a coordinated attack to another unit. This order coordinates the arrival time of the units at the target automatically by adjusting the speed of the units involved. As in other RTS games, air transports can be used to convey units to specified destinations, in Supreme Commander though by shift queuing orders a transport containing several units can be ordered to drop specific units at subsequent waypoints. An air transport can also be ordered to create a ferry route, an airbridge wherein any land units ordered to the start of the ferry route will be conveyed by the air transport to the specified destination. The output from a production factory can be routed to a ferry route causing all units co
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Herbrand Award

The Herbrand Award for Distinguished Contributions to Automated Reasoning is an award given by the Conference on Automated Deduction (CADE), Inc., (although it predates the formal incorporation of CADE) to honour persons or groups for important contributions to the field of automated deduction. The award is named after the French scientist Jacques Herbrand and given at most once per CADE or International Joint Conference on Automated Reasoning (IJCAR). It comes with a prize of US$1,000. Anyone can be nominated, the award is awarded after a vote among CADE trustees and former recipients, usually with input from the CADE/IJCAR programme committee. == Recipients == Past award recipients are: === 1990s === Larry Wos (1992) Woody Bledsoe (1994) John Alan Robinson (1996) Wu Wenjun (1997) Gérard Huet (1998) Robert S. Boyer and J Strother Moore (1999) === 2000s === William W. McCune (2000) Donald W. Loveland (2001) Mark E. Stickel (2002). Peter B. Andrews (2003) Harald Ganzinger (2004) Martin Davis (2005) Wolfgang Bibel (2006) Alan Bundy (2007) Edmund M. Clarke (2008) Deepak Kapur (2009) === 2010s === David Plaisted (2010) Nachum Dershowitz (2011) Melvin Fitting (2012) C. Greg Nelson (2013) Robert L. Constable (2014) Andrei Voronkov (2015) Zohar Manna and Richard Waldinger (2016) Lawrence C. Paulson (2017) Bruno Buchberger (2018) Nikolaj Bjørner and Leonardo de Moura (2019) === 2020s === Franz Baader (2020) Tobias Nipkow (2021) Natarajan Shankar (2022) Moshe Vardi (2023) Armin Biere (2024) Aart Middeldorp (2025)
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