The Shorty Awards (also known as "The Shortys") are awards for outstanding and innovative work in digital and social media content by brands, advertising agencies, and creators. The awards, which generally focus on short-term content, honor achievements in content creation on Twitter, Facebook, YouTube, Instagram, TikTok, Twitch, and other social networking sites. The Shorty Awards began in 2008 and initially recognized achievements by independent creators on Twitter, with the first formal awards ceremony occurring in February 2009. Since then, the awards, which are now awarded each spring, have shifted their focus to recognize content across numerous platforms. Entrant work is judged on the merits of excellence in creativity, strategy, and engagement by the Real Time Academy, a group of industry professionals selected by the Shorty Awards on the basis of their professional reputations, industry knowledge, and personal achievements (which may include previous Shorty wins). An additional public voting component, known as Audience Honor Voting, is also used to select Shorty Awards contenders. Notable Shorty Award winners include Malala Yousafzai, Trevor Noah, Michelle Obama, Conan O’Brien, Lady Gaga, Bill Nye, Jacob Reed, and Lizzo. Brands and organizations such as Chipotle, Duolingo, Marvel Studios, HBO, Red Bull, Airbnb, Nestle, BMW, UNICEF and the Human Rights Campaign have also been awarded. The Shorty Awards also produces an annual award program called The Shorty Impact Awards, a competition dedicated to showcasing digital and social media-based projects by brands, agencies, and organizations that seek to make the world a better place. == List of ceremonies == == 1st Shorty Awards == The awards were created in 2008 by tech entrepreneurs Greg Galant, Adam Varga, and Lee Semel of Sawhorse Media. They invited Twitter account holders to nominate the best Twitter users in general categories such as humor, news, food, and design. Winners were chosen by more than 30,000 Twitter users during the voting period. The founders of Twitter first heard about the awards after the contest had gotten underway and expressed support for it. The first Shorty Awards ceremony was held on February 11, 2009, at the Galapagos Art Space in Brooklyn, New York. Approximately 300 people attended the event. The event was hosted by CNN anchor Rick Sanchez and featured appearances by prominent Twitter users MC Hammer and Gary Vaynerchuk and a video appearance by Shaquille O'Neal. The awards, in 26 categories, were voted on by Twitter users. == 2nd Shorty Awards == Voting for the second Shorty Awards opened in January 2010 in 26 official categories. A Real-Time Photo of the Year category was added to the list of official categories for the first time, recognizing the best photo posted to services such as Twitpic, Yfrog, or Facebook. The second Shorty Awards competition introduced a panel of judges called the Real-Time Academy of Short Form Arts & Sciences whose members were Craig Newmark, David Pogue, Kurt Andersen, Caterina Fake, Joi Ito, Frank Moss, Alberto Ibargüen, Sreenath Sreenivasan, MC Hammer, Alyssa Milano and Jimmy Wales. After public nominations determined the finalists, the academy decided on the winners. Winners were announced at a ceremony held in the Times Center in The New York Times building in Manhattan that was also streamed online. The ceremony was hosted by CNN anchor Rick Sanchez, who presented awards in the official categories as well as the newly added Real-Time Photo of the Year and a special humanitarian award. == 3rd Shorty Awards == The nomination period for the third annual Shorty Awards opened in January 2011 and ran through February 11, 2011, except for new categories that had extended nomination deadlines. There were 30 official categories and five special categories. In addition to Real-Time Photo of the Year, for the first time the awards accepted nominations for Foursquare Mayor of the Year, Foursquare Location of the Year, Microblog of the Year on Tumblr, and a Connecting People award. The awards also introduced new Shorty Industry Awards to recognize the best uses of social media by brands and agencies. Winners were announced at a ceremony on March 28, 2011, hosted by Aasif Mandvi in the Times Center. Other Shorty Awards presenters were scheduled to include Kiefer Sutherland, Jerry Stiller, Anne Meara, Stephen Wallem, Miss USA Rima Fakih, and Miss Teen USA Kamie Crawford. == 4th Shorty Awards == The 4th Annual Shorty Awards featured Ricky Gervais and Tiffani Thiessen. 1.6 million tweeted nominations were made across all the categories to honor the top users on Twitter, Facebook, Tumblr, Foursquare, YouTube and other internet platforms. == 5th Shorty Awards == The 5th Annual Shorty Awards ceremony featured Felicia Day, James Urbaniak, Kristian Nairn, Hannibal Buress, Carrie Keagan, Chris Hardwick, David Karp and Coco Rocha. 2.4 million tweeted nominations were made across all the categories to honor the top users on Twitter, Facebook, Tumblr, Foursquare, YouTube and other internet sites. == 6th Shorty Awards == The ceremony took place on April 7, 2014, at the New York TimesCenter and was hosted by Comedian Natasha Leggero. The show included appearances by Patton Oswalt, Jamie Oliver, Kristen Bell, Jerry Seinfeld, Moshe Kasher, Julie Klausner, Erin Brady, Guy Kawasaki, Matt Walsh, Retta, Us the Duo, Big Boi, Gilbert Gottfried, Thomas Middleditch, Billie Jean King and Leandra Medine. Winners included Jerry Seinfeld and Will Ferrell. == 7th Shorty Awards == The Seventh Annual Shorty Awards was hosted by comedian Rachel Dratch and took place on April 20, 2015, at The Times Center in NYC. The Real-Time Academy, the judging body of the Shortys, tripled in size for the 7th annual Awards and included Alton Brown, Mamrie Hart, Nikki Glaser, OK Go, The Fine Bros, Debbie Sterling, Dan Savage, Deena Varshavskaya and Palmer Luckey. Panic! at the Disco was the musical guest at the ceremony. On-stage presenters included Kevin Jonas, Bill Nye, Bella Thorne, Wyclef Jean, Emily Kinney and Tyler Oakley. == 8th Shorty Awards == The Eighth Annual Shorty Awards were held in NYC at the TimesCenter on April 11, 2016. They were hosted by YouTuber, Writer and Comedian Mamrie Hart with musical performances from Nico & Vinz. Winners of the night included Bill Wurtz, DJ Khaled, Misty Copeland, Casey Neistat, Dwayne Johnson, Hannah Hart, Troye Sivan, Baddie Winkle, Kevin Hart, Taraji P. Henson, King Bach, and Zach King. == 9th Shorty Awards == The Ninth Annual Shorty Awards were held in NYC at the PlayStation Theater on April 23, 2017. They were hosted by two-time Emmy Award winner Tony Hale with a musical performance by Lizzo. Winners of the night included Bill Nye, Shay Mitchell, Doug the Pug, Gigi Gorgeous, Simone Biles, Mara Wilson, Gaten Matarazzo and Chrissy Teigen. == 10th Shorty Awards == The 10th Annual Shorty Awards, took place on April 15, 2018, at the PlayStation Theater, New York City. The ceremony was hosted by actress, singer, and songwriter Keke Palmer with a musical performance by Betty Who. == 11th Shorty Awards == The 11th Annual Shorty Awards were held on May 5, 2019, in New York City at the PlayStation Theater. The ceremony was hosted by American actress and comedian Kathy Griffin, with a musical performance by Tank and the Bangas. == 12th Shorty Awards == The 12th Annual Shorty Awards were held on May 3, 2020. Due to the COVID-19 pandemic, the ceremony took place online for the first time, with presenters and award winners filming from their own homes. The ceremony was hosted by actor J.B. Smoove and featured a remixed performance of Trap Queen by Fetty Wap. Award winners included Jack Stauber, Supercar Blondie, Rose and Rosie, and Greta Thunberg. == 13th Shorty Awards == The 13th Annual Shorty Awards took place from April 26 to May 14, 2021. The ceremony was hosted on different social media platforms, such as Instagram and Clubhouse, to create a more tailored experience. Winners were announced from May 11 to May 14, with 10 winners being revealed each hour from 1 to 4 p.m. EST on the Shorty Awards Instagram account. == 14th Shorty Awards == The 14th Annual Shorty Awards were held virtually on May 15, 2022, honoring the best in social media and digital content. Hosted by Jay Shetty, the event recognized influencers, brands, and organizations across various categories, celebrating excellence in digital storytelling and innovative online campaigns. Notable winners included Tabitha Brown for her food content and the D'Amelio Family for their contributions to family and parenting content. The event highlighted the role of digital media in connecting and inspiring audiences during challenging times. == 15th Shorty Awards == The 15th Annual Shorty Awards celebrated the best in social media and digital content on May 24, 2023, at Tribeca 360° in New York City. Hosted by Jay Pharoah, the event honored creators, brands, and organizations ac
Visible (mobile app)
Visible is a health tracking mobile app for people with long COVID and myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS). The company was founded by a Harry Leeming, an engineer from London living with long Covid since 2020, and Luke Martin-Fuller. In November 2022, Visible released an open beta of an app that aims to help people pace their activities to avoid post-exertional malaise. The app gathers data on exertion levels, symptom severity, and heart-rate variability. HRV is approximated using a smartphone's camera via a technique called photoplethysmography, and according to the app's developers, can indicate how much someone needs rest. The app is currently free, but is expected to be freemium in the future. Users can also opt to allow their data be used for research purposes. In July 2023, Visible and Imperial College London announced the start of the first two studies. One is on the effects of the menstrual cycle on long COVID symptoms, and the other is on the condition's epidemiology and economic impact. Visible has announced plans to couple the app with activity trackers for continuous monitoring of heart-rate and actimetry data, which the developers claim will be more effective. As of 2022, no clinical trials on Visible's effectiveness have been conducted.
Semantic triple
A semantic triple, or RDF triple or simply triple, is the atomic data entity in the Resource Description Framework (RDF) data model. As its name indicates, a triple is a sequence of three entities that codifies a statement about semantic data in the form of subject–predicate–object expressions (e.g., "Bob is 35", or "Bob knows John"). == Subject, predicate and object == This format enables knowledge to be represented in a machine-readable way. Particularly, every part of an RDF triple is individually addressable via unique URIs—for example, the statement "Bob knows John" might be represented in RDF as: http://example.name#BobSmith12 http://xmlns.com/foaf/spec/#term_knows http://example.name#JohnDoe34. Given this precise representation, semantic data can be unambiguously queried and reasoned about. The components of a triple, such as the statement "The sky has the color blue", consist of a subject ("the sky"), a predicate ("has the color"), and an object ("blue"). This is similar to the classical notation of an entity–attribute–value model within object-oriented design, where this example would be expressed as an entity (sky), an attribute (color) and a value (blue). From this basic structure, triples can be composed into more complex models, by using triples as objects or subjects of other triples—for example, Mike → said → (triples → can be → objects). Given their particular, consistent structure, a collection of triples is often stored in purpose-built databases called triplestores. == Difference from relational databases == A relational database is the classical form for information storage, working with different tables, which consist of rows. The query language SQL is able to retrieve information from such a database. In contrast, RDF triple storage works with logical predicates. No tables nor rows are needed, but the information is stored in a text file. An RDF-triple store can be converted into an SQL database and the other way around. If the knowledge is highly unstructured and dedicated tables aren't flexible enough, semantic triples are used over classic relational storage. In contrast to a traditional SQL database, an RDF triple store isn't created with a table editor. The preferred tool is a knowledge editor, for example Protégé. Protégé looks similar to an object-oriented modeling application used for software engineering, but it's focused on natural language information. The RDF triples are aggregated into a knowledge base, which allows external parsers to run requests. Possible applications include the creation of non-player characters within video games. == Limitations == One concern about triple storage is its lack of database scalability. This problem is especially pertinent if millions of triples are stored and retrieved in a database. The seek time is larger than for classical SQL-based databases. A more complex issue is a knowledge model's inability to predict future states. Even if all the domain knowledge is available as logical predicates, the model fails in answering what-if questions. For example, suppose in the RDF format a room with a robot and table is described. The robot knows what the location of the table is, is aware of the distance to the table and knows also that a table is a type of furniture. Before the robot can plan its next action, it needs temporal reasoning capabilities. Thus, the knowledge model should answer hypothetical questions in advance before an action is taken.
Vilém Flusser
Vilém Flusser (May 12, 1920 – November 27, 1991) was a Czech-born Brazilian philosopher, writer and journalist, best known for his contributions to media studies, communication theory, and the philosophy of language. He lived for a long period in São Paulo (where he became a Brazilian citizen) and later in France, and his works are written in many different languages. His early work was marked by discussion of the thought of Martin Heidegger, and by the influence of existentialism and phenomenology. Phenomenology would play a major role in the transition to the later phase of his work, in which he turned his attention to the philosophy of communication and of artistic production. He contributed to the dichotomy logic theory through history: the period of image worship, and period of text worship, with deviations consequently into idolatry and "textolatry". == Life == Flusser was born in 1920 in Prague, Czechoslovakia into a family of Jewish intellectuals. His father, Gustav Flusser, studied mathematics and physics (under Albert Einstein among others). Vilém attended German and Czech primary schools and later a German grammar school. In 1938, Flusser started to study philosophy at the Juridical Faculty of the Charles University in Prague. In 1939, shortly after the Nazi occupation, Flusser emigrated to London (with Edith Barth, his later wife, and her parents) to continue his studies for one term at the London School of Economics and Political Science. Vilém Flusser lost all of his family in the German concentration camps: his father died in Buchenwald in 1940; his grandparents, his mother and his sister were brought to Theresienstadt and later to Auschwitz where they were killed. The next year, he emigrated to Brazil, living both in São Paulo and Rio de Janeiro. He started working at a Czech import/export company and then at Stabivolt, a manufacturer of radios and transistors. In 1960 he started to collaborate with the Brazilian Institute of Philosophy (IBF) in São Paulo and published in the Revista Brasileira de Filosofia; by these means he seriously approached the Brazilian intellectual community. Flusser had as his friend and closest interlocutor the Brazilian philosopher Vicente Ferreira da Silva. Flusser and Vicente Ferreira da Silva met in São Paulo in the 1960s and began a close intellectual dialogue that continued until Ferreira da Silva's death in 1963. Flusser wrote several essays on Ferreira da Silva's work and that Ferreira da Silva's concept of "Fundamental ontology” had a significant impact on Flusser's understanding of the nature of reality. During the 60s Flusser published and taught at several schools in São Paulo, being Lecturer for Philosophy of Science at the Escola Politécnica of the University of São Paulo and Professor of Philosophy of Communication at the Escola Dramática and the Escola Superior de Cinema in São Paulo. He also participated actively in the arts, collaborating with the Bienal de São Paulo, among other cultural events. Beginning in the 1950s he taught philosophy and worked as a journalist, before publishing his first book Língua e realidade (Language and Reality) in 1963. In 1972 he decided to leave Brazil. Some say it was because it was becoming difficult to publish because of the military regime. Others dispute this reason, since his work on communication and language did not threaten the military. In 1970, when a reform took place at the University of São Paulo by the Brazilian military government, all Lecturers of Philosophy (members of the Department of Philosophy) were dismissed. Flusser, who taught at the Engineering School (Escola Politécnica), had to leave the university as well. In 1972 he and his wife Edith settled temporarily in Merano (Tyrol). Further short stays in various European countries followed until they moved to Robion in southern France in 1981, where they remained until Flusser's death in 1991. To the end of his life, he was quite active writing and giving lectures around media theory and working with new topics (Philosophy of Photography, Technical Images, etc.). He died in 1991 in a car accident near the Czech–German border, while trying to visit his native city, Prague, to give a lecture. Vilém Flusser is the cousin of David Flusser. == Philosophy == Flusser's essays are short, provocative and lucid, with a resemblance to the style of journalistic articles. Critics have noted he is less a 'systematic' thinker than a 'dialogic' one, purposefully eclectic and provocative (Cubitt 2004). However, his early books, written in the 1960s, primarily in Portuguese, and published in Brazil, have a slightly different style. Flusser's writings relate to each other, however, which means that he intensively works over certain topics and dissects them into a number of brief essays. His main topics of interest were: epistemology, ethics, aesthetics, ontology, language philosophy, semiotics, philosophy of science, the history of Western culture, the philosophy of religion, the history of symbolic language, technology, writing, the technical image, photography, migration, media and literature, and, especially in his later years, the philosophy of communication and of artistic production. His writings reflect his wandering life: although the majority of his work was written in German and Portuguese, he also wrote in English and French, with scarce translation to other languages. Because Flusser's writings in different languages are dispersed in the form of books, articles or sections of books, his work as a media philosopher and cultural theorist is only now becoming more widely known. The first book by Flusser to be published in English was Towards a Philosophy of Photography in 1984 by the then new journal European Photography, which was his own translation of the work. The Shape of Things, was published in London in 1999 and was followed by a new translation of Towards a Philosophy of Photography. Flusser's archives have been held by the Academy of Media Arts in Cologne and are currently housed at the Berlin University of the Arts. === Philosophy of photography === Writing about photography in the 1970s and 80s, in the face of the early worldwide impact of computer technologies, Flusser argued that the photograph was the first in a number of technical image forms to have fundamentally changed the way in which the world is seen. Historically, the importance of photography had been that it introduced nothing less than a new epoch: 'The invention of photography constitutes a break in history that can only be understood in comparison to that other historical break constituted by the invention of linear writing.' Whereas ideas might previously have been interpreted in terms of their written form, photography heralded new forms of perceptual experience and knowledge. As Flusser Archive Supervisor Claudia Becker describes, "For Flusser, photography is not only a reproductive imaging technology, it is a dominant cultural technique through which reality is constituted and understood". In this context, Flusser argued that photographs have to be understood in strict separation from 'pre-technical image forms'. For example, he contrasted them to paintings which he described as images that can be sensibly 'decoded', because the viewer is able to interpret what he or she sees as more or less direct signs of what the painter intended. By contrast, even though photography produces images that seem to be 'faithful reproductions' of objects and events they cannot be so directly 'decoded'. The crux of this difference stems, for Flusser, from the fact that photographs are produced through the operations of an apparatus. And the photographic apparatus operates in ways that are not immediately known or shaped by its operator. For example, he described the act of photographing as follows: The photographer's gesture as the search for a viewpoint onto a scene takes place within the possibilities offered by the apparatus. The photographer moves within specific categories of space and time regarding the scene: proximity and distance, bird- and worm's-eye views, frontal- and side-views, short or long exposures, etc. The Gestalt of space–time surrounding the scene is prefigured for the photographer by the categories of his camera. These categories are an a priori for him. He must 'decide' within them: he must press the trigger. Roughly put, the person using a camera might think that they are operating its controls to produce a picture that shows the world the way they want it to be seen, but it is the pre-programmed character of the camera that sets the parameters of this act and it is the apparatus that shapes the meaning of the resulting image. Given the central role of photography to almost all aspects of contemporary life, the programmed character of the photographic apparatus shapes the experience of looking at and interpreting photographs as well as most of the cultural contexts in which we do so. Flusse
AlphaGo Zero
AlphaGo Zero is a version of DeepMind's Go software AlphaGo. AlphaGo's team published an article in Nature in October 2017 introducing AlphaGo Zero, a version created without using data from human games, and stronger than any previous version. By playing games against itself, AlphaGo Zero: surpassed the strength of AlphaGo Lee in three days by winning 100 games to 0; reached the level of AlphaGo Master in 21 days; and exceeded all previous versions in 40 days. Training artificial intelligence (AI) without datasets derived from human experts has significant implications for the development of AI with superhuman skills, as expert data is "often expensive, unreliable, or simply unavailable." Demis Hassabis, the co-founder and CEO of DeepMind, said that AlphaGo Zero was so powerful because it was "no longer constrained by the limits of human knowledge". Furthermore, AlphaGo Zero performed better than standard deep reinforcement learning models (such as Deep Q-Network implementations) due to its integration of Monte Carlo tree search. David Silver, one of the first authors of DeepMind's papers published in Nature on AlphaGo, said that it is possible to have generalized AI algorithms by removing the need to learn from humans. Google later developed AlphaZero, a generalized version of AlphaGo Zero that could play chess and shōgi in addition to Go. In December 2017, AlphaZero beat the 3-day version of AlphaGo Zero by winning 60 games to 40, and with 8 hours of training it outperformed AlphaGo Lee on an Elo scale. AlphaZero also defeated a top chess program (Stockfish) and a top Shōgi program (Elmo). == Architecture == The network in AlphaGo Zero is a ResNet with two heads. The stem of the network takes as input a 17x19x19 tensor representation of the Go board. 8 channels are the positions of the current player's stones from the last eight time steps. (1 if there is a stone, 0 otherwise. If the time step go before the beginning of the game, then 0 in all positions.) 8 channels are the positions of the other player's stones from the last eight time steps. 1 channel is all 1 if black is to move, and 0 otherwise. The body is a ResNet with either 20 or 40 residual blocks and 256 channels. There are two heads, a policy head and a value head. Policy head outputs a logit array of size 19 × 19 + 1 {\displaystyle 19\times 19+1} , representing the logit of making a move in one of the points, plus the logit of passing. Value head outputs a number in the range ( − 1 , + 1 ) {\displaystyle (-1,+1)} , representing the expected score for the current player. -1 represents current player losing, and +1 winning. == Training == AlphaGo Zero's neural network was trained using TensorFlow, with 64 GPU workers and 19 CPU parameter servers. Only four TPUs were used for inference. The neural network initially knew nothing about Go beyond the rules. Unlike earlier versions of AlphaGo, Zero only perceived the board's stones, rather than having some rare human-programmed edge cases to help recognize unusual Go board positions. The AI engaged in reinforcement learning, playing against itself until it could anticipate its own moves and how those moves would affect the game's outcome. In the first three days AlphaGo Zero played 4.9 million games against itself in quick succession. It appeared to develop the skills required to beat top humans within just a few days, whereas the earlier AlphaGo took months of training to achieve the same level. According to Epoch.ai, training cost 3e23 FLOPs. For comparison, the researchers also trained a version of AlphaGo Zero using human games, AlphaGo Master, and found that it learned more quickly, but actually performed more poorly in the long run. DeepMind submitted its initial findings in a paper to Nature in April 2017, which was then published in October 2017. == Hardware cost == The hardware cost for a single AlphaGo Zero system in 2017, including the four TPUs, has been quoted as around $25 million. == Applications == According to Hassabis, AlphaGo's algorithms are likely to be of the most benefit to domains that require an intelligent search through an enormous space of possibilities, such as protein folding (see AlphaFold) or accurately simulating chemical reactions. AlphaGo's techniques are probably less useful in domains that are difficult to simulate, such as learning how to drive a car. DeepMind stated in October 2017 that it had already started active work on attempting to use AlphaGo Zero technology for protein folding, and stated it would soon publish new findings. == Reception == AlphaGo Zero was widely regarded as a significant advance, even when compared with its groundbreaking predecessor, AlphaGo. Oren Etzioni of the Allen Institute for Artificial Intelligence called AlphaGo Zero "a very impressive technical result" in "both their ability to do it—and their ability to train the system in 40 days, on four TPUs". The Guardian called it a "major breakthrough for artificial intelligence", citing Eleni Vasilaki of Sheffield University and Tom Mitchell of Carnegie Mellon University, who called it an impressive feat and an “outstanding engineering accomplishment" respectively. Mark Pesce of the University of Sydney called AlphaGo Zero "a big technological advance" taking us into "undiscovered territory". Gary Marcus, a psychologist at New York University, has cautioned that for all we know, AlphaGo may contain "implicit knowledge that the programmers have about how to construct machines to play problems like Go" and will need to be tested in other domains before being sure that its base architecture is effective at much more than playing Go. In contrast, DeepMind is "confident that this approach is generalisable to a large number of domains". In response to the reports, South Korean Go professional Lee Sedol said, "The previous version of AlphaGo wasn’t perfect, and I believe that’s why AlphaGo Zero was made." On the potential for AlphaGo's development, Lee said he will have to wait and see but also said it will affect young Go players. Mok Jin-seok, who directs the South Korean national Go team, said the Go world has already been imitating the playing styles of previous versions of AlphaGo and creating new ideas from them, and he is hopeful that new ideas will come out from AlphaGo Zero. Mok also added that general trends in the Go world are now being influenced by AlphaGo's playing style. "At first, it was hard to understand and I almost felt like I was playing against an alien. However, having had a great amount of experience, I’ve become used to it," Mok said. "We are now past the point where we debate the gap between the capability of AlphaGo and humans. It’s now between computers." Mok has reportedly already begun analyzing the playing style of AlphaGo Zero along with players from the national team. "Though having watched only a few matches, we received the impression that AlphaGo Zero plays more like a human than its predecessors," Mok said. Chinese Go professional Ke Jie commented on the remarkable accomplishments of the new program: "A pure self-learning AlphaGo is the strongest. Humans seem redundant in front of its self-improvement." == Comparison with predecessors == == AlphaZero == On 5 December 2017, DeepMind team released a preprint on arXiv, introducing AlphaZero, a program using generalized AlphaGo Zero's approach, which achieved within 24 hours a superhuman level of play in chess, shogi, and Go, defeating world-champion programs, Stockfish, Elmo, and 3-day version of AlphaGo Zero in each case. AlphaZero (AZ) is a more generalized variant of the AlphaGo Zero (AGZ) algorithm, and is able to play shogi and chess as well as Go. Differences between AZ and AGZ include: AZ has hard-coded rules for setting search hyperparameters. The neural network is now updated continually. Chess (unlike Go) can end in a tie; therefore AZ can take into account the possibility of a tie game. An open source program, Leela Zero, based on the ideas from the AlphaGo papers is available. It uses a GPU instead of the TPUs recent versions of AlphaGo rely on.
ChromaDB
Chroma or ChromaDB is open-source data infrastructure tailored to applications with large language models. Its headquarters are in San Francisco. In April 2023, it raised 18 million US dollars as seed funding. ChromaDB has been used in academic studies on artificial intelligence, particularly as part of the tech stack for retrieval-augmented generation.
D3web
d3web is a free, open-source platform for knowledge-based systems (expert systems). Its core is written in Java using XML and/or Office-based formats for the knowledge storage. All of its components are distributed under the terms of the Lesser General Public Licence (LGPL). The d3web diagnostic core implements reasoning and persistence components for problem-solving knowledge including decision trees, (heuristic) rules, set-covering models and diagnostic flowcharts. The software can be integrated into foreign applications (embedded or OEM), but a number of off-the-shelf components already exist. == Components == d3web is a component-based software platform providing applications for authoring and using/executing problem-solving knowledge. The following applications are primarily using d3web: KnowWE (Knowledge Wiki Environment): A semantic wiki building on JSPWiki. Problem-solving knowledge can be authored and executed through the wiki interface. Developed knowledge bases can be exported to be used in OEM or embedded reasoners. Additionally, knowledge exchange via OWL ontologies is provided. KnowME (Knowledge Modelling Environment): A rich-client application for the development of d3web knowledge bases. Problem-solving knowledge can be authored and executed within the desktop application. Developed knowledge bases can be used in OEM or embedded reasoners. The software KnowME is no longer under active development. It is replaced by the KnowWE component (see above). Dialog2: A web-based application for demonstrating the capabilities of the d3web core reasoner. The web servlet is based on Java Server Faces. It can be used out of box or as a starting point for own developments for building knowledge-based interview systems. == Application Domains == A number of industrial and academic projects already used or are currently using the d3web platform. The main application domains are: medical diagnosis, documentation, and therapy: technical fault diagnosis monitoring of technical devices. Some applications (both, commercial and free) created using the d3web diagnostic engine: SmartCare(c): a medical closed-loop system for weaning mechanically ventilated patients, created by Dräger SonoConsult Archived 2011-12-16 at the Wayback Machine: a medical support system for evaluating sonographic examinations (German only) eDOC: a web-based system for self-diagnosing various medical issues (German only) == History == The development of d3web originates from the research work of Prof. Dr. Frank Puppe (University Würzburg, Germany) going back to the 1980s, starting with the medical expert systems MED1 and MED2 . Whereas the original systems were focussed on medical diagnosis the applicability of the approach was generalized by the successor D3 . As the predecessors were implemented in the LISP programming language, d3web is a full Java re-implementation.