Pythia is an ancient text restoration model that recovers missing characters from damaged text input using deep neural networks. It was created by Yannis Assael, Thea Sommerschield, and Jonathan Prag, researchers from Google DeepMind and the University of Oxford. To study the society and the history of ancient civilisations, ancient history relies on disciplines such as epigraphy, the study of ancient inscribed texts. Hundreds of thousands of these texts, known as inscriptions, have survived to our day, but are often damaged over the centuries. Illegible parts of the text must then be restored by specialists, called epigraphists, in order to extract meaningful information from the text and use it to expand our knowledge of the context in which the text was written. Pythia takes as input the damaged text, and is trained to return hypothesised restorations of ancient Greek inscriptions, working as an assistive aid for ancient historians. Its neural network architecture works at both the character- and word-level, thereby effectively handling long-term context information, and dealing efficiently with incomplete word representations. Pythia is applicable to any discipline dealing with ancient texts (philology, papyrology, codicology) and can work in any language (ancient or modern).
EyeOS
eyeOS was a web desktop for cloud computing, whose main purpose is to enable collaboration and communication among users. It is mainly written in PHP, XML, and JavaScript. It is a private-cloud application platform with a web-based desktop interface. eyeOS delivers a whole desktop from the cloud with file management, personal management information tools, and collaborative tools, with the integration of the client's applications. == History == The first publicly available eyeOS version was released on August 1, 2005, as eyeOS 0.6.0 in Olesa de Montserrat, Barcelona (Spain). A worldwide community of developers soon took part in the project and helped improve it by translating, testing, and developing it. After two years of development, the eyeOS Team published eyeOS 1.0 on June 4, 2007. Compared with previous versions, eyeOS 1.0 introduced a complete reorganization of the code and some new web technologies, like eyeSoft, a portage-based web software installation system. Moreover, eyeOS also included the eyeOS Toolkit, a set of libraries allowing easy and fast development of new web applications. With the release of eyeOS 1.1 on July 2, 2007, eyeOS changed its license and migrated from GNU GPL Version 2 to Version 3. Version 1.2 was released just a month after the 1.1 version and integrated full compatibility with Microsoft Word files. eyeOS 1.5 Gala was released on January 15, 2008. This version was the first to support both Microsoft Office and OpenOffice.org file formats for documents, presentations, and spreadsheets. With this version, eyeOS also gained the ability to import and export documents in both formats using server-side scripting. eyeOS 1.6 was released on April 25, 2008, and included many improvements such as synchronization with local computers, drag and drop, a mobile version, and more. eyeOS 1.8 Lars was released on January 7, 2009, and featured a completely rewritten file manager and a new sound API to develop media-rich applications. Later, on April 1, 2009, 1.8.5 was released with a new default theme and some rewritten apps, such as the Word Processor and the Address Book. On July 13, 2009, 1.8.6 was released with an interface for the iPhone and a new version of eyeMail with support for POP3 and IMAP. eyeOS 1.9 was released on December 29, 2009. It was followed up with the 1.9.0.1 release with minor fixes on February 18, 2010. These releases were the last of the "classic desktop" interfaces. A major re-work was completed in March 2010, now called eyeOS 2.x. However, a small group of eyeOS developers still maintain the code within the eyeOS forum, where support is provided, but the eyeOS group itself has stopped active 1.x development. It is now available as the On-eye project on GitHub. Active development was halted on 1.x as of February 3, 2010. eyeOS 2.0 release took place on March 3, 2010. This was a total restructure of the operating system. The 2.x stable is the new series of eyeOS, which is in active development and will replace 1.x as stable in a few months. It includes live collaboration and more social capabilities than eyeOS 1.x. eyeOS then released 2.2.0.0 on July 28, 2010. On December 14, 2010, a working group inside the eyeOS open-source development community began the structure development and further upgrade of eyeOS 1.9.x. The group's main goal is to continue the work eyeOS has stopped on 1.9.x. eyeOS released 2.5 on May 17, 2011. This was the last release under an open source license. It is available on SourceForge for download under another project called eyeOS 2.5 Open Source Version. On April 1, 2014, Telefónica announced their acquisition of eyeOS. eyeOS would maintain its headquarters in the Catalonia, Spain, where their staff would continue to work but now as part of Telefónica. After its integration into Telefónica, eyeOS would continue to function as an independent subsidiary under CEO Michel Kisfaludi. == Structure and API == For developers, EyeOS provides the eyeOS Toolkit, a set of libraries and functions to develop applications for eyeOS. Using the integrated Portage-based eyeSoft system, one can create their own repository for eyeOS and distribute applications through it. Each core part of the desktop is its own application, using JavaScript to send server commands as the user interacts. As actions are performed using AJAX (such as launching an application), it sends event information to the server. The server then sends back tasks for the client to do in XML format, such as drawing a widget. On the server, eyeOS uses XML files to store information. This makes it simple for a user to set up on the server, as it requires zero configuration other than the account information for the first user, making it simple to deploy. To avoid bottlenecks that flat files present, each user's information and settings are stored in different files, preventing resource starvation from occurring, though this in turn may create issues in high volume user environments due to host operating system open file descriptor limits. == Professional edition == A Professional Edition of eyeOS was launched on September 15, 2011, as an operating system for businesses. It uses a new version number and was released under version 1.0 instead of continuing with the next version number in the open source project. The Professional Edition retains the web desktop interface used by the open source version while targeting enterprise users. A host of new features designed for enterprises, like file sharing and synchronization (called eyeSync), Active Directory/LDAP connectivity, system-wide administration controls, and a local file execution tool called eyeRun were introduced. A new suite of Web Apps (a mail client, calendar, instant messaging, and collaboration tools) was also introduced, specific to the enterprise edition for the web desktop. With eyeOS Professional Edition 1.1, a to-do task manager tool, Citrix XenApp integration, and a Facebook like 'wall' for collaboration were introduced. == Awards == 2007 – Received the Softpedia's Pick award. 2007 – Finalist at SourceForge's 2007 Community Choice Awards at the "Best Project" category. The winner for that category was 7-Zip. 2007 – Won the Yahoo! Spain Web Revelation award in the Technology category. 2008 – Finalist for the Webware 100 awards by CNET, under the "Browsing" category. 2008 – Finalist at the SourceForge's 2008 Community Choice Awards at the "Most Likely to Change the World" category. The winner for that category was Linux. 2009 – Selected Project of the Month (August 2009) by SourceForge. 2009 – BMW Innovation Award. 2010 – Winner of Accelera (Ernst & Young). 2010 – Asturias & Girona Spanish Prince award “IMPULSA”. 2011 – Winner of MIT's TR35 award as Innovator of the Year in Spain. == Community == eyeOS community is formed with the eyeOS forums, which reached 10,000 members on April 4, 2008; the eyeOS wiki; and the eyeOS Application Communities, available at the eyeOS-Apps website, hosted and provided by openDesktop.org as well as Softpedia.
Argument mining
Argument mining, or argumentation mining, is a research area within the natural language processing field. The goal of argument mining is the automatic extraction and identification of argumentative structures from natural language text with the aid of computer programs. Such argumentative structures include the premise, conclusions, the argument scheme and the relationship between the main and subsidiary argument, or the main and counter-argument within discourse. The Argument Mining workshop series is the main research forum for argument mining related research. == Applications == Argument mining has been applied in many different genres including the qualitative assessment of social media content (e.g. Twitter, Facebook), where it provides a powerful tool for policy-makers and researchers in social and political sciences. Other domains include legal documents, product reviews, scientific articles, online debates, newspaper articles and dialogical domains. Transfer learning approaches have been successfully used to combine the different domains into a domain agnostic argumentation model. Argument mining has been used to provide students individual writing support by accessing and visualizing the argumentation discourse in their texts. The application of argument mining in a user-centered learning tool helped students to improve their argumentation skills significantly compared to traditional argumentation learning applications. == Challenges == Given the wide variety of text genres and the different research perspectives and approaches, it has been difficult to reach a common and objective evaluation scheme. Many annotated data sets have been proposed, with some gaining popularity, but a consensual data set is yet to be found. Annotating argumentative structures is a highly demanding task. There have been successful attempts to delegate such annotation tasks to the crowd but the process still requires a lot of effort and carries significant cost. Initial attempts to bypass this hurdle were made using the weak supervision approach.
Niceaunties
Niceaunties is the pseudonym of a Singapore-based artist and designer whose work incorporates generative artificial intelligence, video, and digital installation. Her practice centers around the figure of the "auntie", a common term for older women in Southeast Asian contexts, and explores themes such as aging, care, domesticity, and gender roles. Her work has been featured in exhibitions and media platforms including TED, Christie's Art + Tech, Expanded.Art, and publications such as The Guardian, The Straits Times. == Early life and career == Niceaunties was born in 1981 in Singapore. She attributes her inspiration for "auntie culture" to the matriarchal environment and older women of her household, including her grandmother, while growing up. She is also an architectural designer with Spark Architect. The Niceaunties project began in 2023 after she encountered AI-generated images in her work as an architect. It draws inspiration from women in the artist's family and broader Southeast Asian cultural dynamics. Her work often features AI-generated visuals created with tools such as DALL-E, Krea, RunwayML, and SORA. Her imagery and narratives center on the fictional "Auntieverse", which features older women in imagined settings involving community, ecology, and labor. Her notable works include 'Auntlantis', a five-part video series imagining older women engaged in ocean clean-up and collective ritual, and 'Goddess,' a video created with Sora, featuring a character who gradually forgets her divine identity through years of domestic labor. == Exhibitions == 2024 – Expanded.Art, Berlin – Auntiedote solo exhibition 2024 – TED (conference), Vancouver – Speaker and screening 2024 – Victoria and Albert Museum, London – Digital Art Weekend 2024 – Louisiana Museum of Modern Art, Denmark – Ocean exhibition 2025 – Christie's Augmented Intelligence Auction, New York == Reception == In 2024, Niceaunties gave a TED Talk titled The Weird and Wonderful Art of Niceaunties. Journalist Rebecca Ratcliffe, writing for The Guardian, described her work as combining AI with "the surreal and the political," noting her focus on older women as central characters. Her work has also received criticism for being reliant on generative AI, which many feel exploits and steals from traditional artists.
Sora (text-to-video model)
Sora was a text-to-video model and social media app developed by OpenAI. Using artificial intelligence, the model generated short video clips based on prompts, and could also extend existing short videos. In February 2024, OpenAI previewed examples of its output to the public, with the first generation of Sora released publicly for ChatGPT Plus and ChatGPT Pro users in the United States and Canada in December 2024. The second generation of Sora was released to select users in the US and Canada at the end of September 2025. Sora 2 integrated social media features into the app. The app was shut down on April 26, 2026 and the application programming interface (API) is planned to be discontinued on September 24, 2026, marking the end of the Sora AI brand as a whole. By default, the generator used copyrighted material in its videos, unless copyright holders actively opt out of having their content included. Videos contained a visible, moving digital watermark to prevent misuse, but a week after Sora 2's release, third-party programs became available which could remove the watermark. == Background == Several other models capable of generating video from text had been created prior to Sora, including Meta's Make‑A‑Video, Runway's Gen‑2 and Google Veo. OpenAI, the company behind Sora, had released DALL·E 3, the third of its DALL-E text-to-image models, in September 2023. == History == === Initial release === The team that developed Sora named it after the Japanese word for 'sky' to signify its "limitless creative potential". On February 15, 2024, OpenAI first previewed Sora by releasing multiple clips of high-definition videos that it had created, including an SUV driving down a mountain road, an animation of a "short fluffy monster" next to a candle, two people walking through Tokyo in the snow, and fake historical footage of the California gold rush. OpenAI stated that it was able to generate videos as long as one minute. The company then shared a technical report that highlighted the methods used to train the model. OpenAI CEO Sam Altman also posted a series of tweets responding to Twitter users' prompts with Sora-generated videos of the prompts. As of December 9, 2024, OpenAI had gradually made Sora available to the public for ChatGPT Pro and ChatGPT Plus users in the U.S. and Canada. Prior to this, the company had provided limited access to a small "red team", including experts in misinformation and bias, to perform adversarial testing on the model. The company also shared Sora with a small group of creative professionals, including video makers and artists, to seek feedback on its usefulness in creative fields. In February 2025, OpenAI announced plans to integrate Sora into ChatGPT by letting users generate Sora videos from the chatbot. === Sora 2 === Sora 2 was unveiled on September 30, 2025, with an iOS app at the same time, as well as an Android app two months later. All videos generated by the model feature a visible, moving watermark to prevent misuse of the tool. The previous version of Sora also added a safety watermark to allow viewers to distinguish between real and fictional content. On October 7, 404 Media reported that third-party programs that could remove the watermark from Sora 2 videos had become prevalent. Many outlets, such as Wired magazine, have noted that the Sora 2 app is overtly similar to TikTok in style and features. === Discontinuation === On March 24, 2026, OpenAI announced on X that it was discontinuing Sora in both the mobile app and the API. The Sora app was shut down on April 26, 2026, while the API is planned to be shut down on September 24, 2026. OpenAI's partnership with Disney, which included a licensing agreement allowing Disney characters to be used within Sora, was also coming to an end. The decision prompted British technology news website The Register to label OpenAI a "product-killer", following in the footsteps of other technology companies such as Google, Amazon Web Services, Broadcom, Cloud Software Group, and Netscape. OpenAI did not provide a specific reason for discontinuing Sora in its shutdown notice. The reports that emerged regarding this discontinuity linked the decision to computation shortages, cost pressures, and a broader shift toward core enterprise products. Following its public launch, Sora's worldwide users peaked at around a million before declining to fewer than 500,000, while the service cost an estimated $1 million per day to operate due to the computational demands of video generation. == Legal regulation == In November 2024, an API key for Sora access was leaked by a group of testers on Hugging Face who posted a manifesto stating that they were protesting that Sora was used for "art washing". OpenAI revoked all access three hours after the leak was made public and stated that "hundreds of artists" have shaped the development and that "participation is voluntary". At the time of its launch, Sora 2 allowed copyrighted content by default unless copyright holders contacted OpenAI to restrict the generation of their content on the platform. On October 3, 2025, OpenAI stated that a future update to Sora 2 would give copyright holders "more granular control" over the generation of copyrighted content, but the company did not state whether existing content would be removed. On October 6, the chairman of the MPA criticized OpenAI's approach to copyright with Sora 2. On December 11, 2025, the Walt Disney Company announced that it would invest $1 billion in OpenAI to allow users to generate more than 200 of its copyrighted characters on Sora 2. These characters include those from Disney Animation, Pixar, Marvel Studios, and Star Wars. == Capabilities and limitations == The technology behind Sora is an adaptation of the technology behind DALL-E 3. According to OpenAI, Sora is a diffusion transformer, a denoising latent diffusion model with one transformer as its denoiser. A video is generated in latent space by denoising 3D "patches", then transformed to standard space by a video decompressor. Recaptioning is employed to augment training data by using a video-to-text model to create detailed captions for videos. OpenAI trained the model using publicly available videos as well as copyrighted videos licensed for the purpose, but did not reveal the number or the exact source of the videos. Upon its release, OpenAI acknowledged some of Sora's shortcomings, including its limited capacity to simulate complex physics, to understand causality and to differentiate left from right. OpenAI also stated that, in adherence to the company's existing safety practices, Sora will restrict text prompts for sexual, violent, hateful or celebrity imagery, as well as content featuring existing intellectual property. Sora researcher Tim Brooks stated that the model learned how to create 3D graphics from its dataset alone, while fellow Sora researcher Bill Peebles said that the model automatically created different video angles without being prompted. According to OpenAI, Sora-generated videos are also tagged with C2PA metadata to indicate that they are AI-processed. === Comparison with other models === The Artificial Analysis have placed Sora 2 pro lower than other text-to-video AI generators in the market on its leaderboard. Other models, such as Seedance 2.0 from ByteDance, Runaway 4.5 from Runaway, and Kling 3.0 from KlingAI, have ranked higher than Sora 2.0. == Reception == === Positive === In 2024, Will Douglas Heaven of the MIT Technology Review called the demonstration videos "impressive", but noted that they must have been cherry-picked and may not be representative of Sora's typical output. Lisa Lacy of CNET called its example videos "remarkably realistic – except perhaps when a human face appears close up or when sea creatures are swimming". In October 2025, The New York Times remarked that the release of the Sora 2 app in September 2025 was "jaw-dropping (for better and worse)" though also remarked that the app was a "social network in disguise" and "the type of product that companies like Meta and X have sought to build: a way to bring A.I. to the masses that people can share." The article expressed concern regarding the product's potential impact on society and its potential use to promote misinformation, disinformation, and scams. A 2025 study in Science Advances found that generative AI tools can lower barriers to entry in creative work. It enables users with diverse skill sets, including people with less formal artistic training and technical skills, to act on their creative and imaginative ideas. The lower barrier to entry allows such users previously locked out of the creative industry to produce content and easily act on their creative ideas. === Negative === Some internet users and online content creators, such as Hank Green, called the mobile app "SlopTok," a reference to both the mobile app TikTok and the term AI slop. Filmmaker Tyler Perry announced he would be putting a planned
Elements (toolchain)
RemObjects Elements is a toolchain for software development, comprising six programming languages: C#, Swift, Go, Java, Oxygene (a form of modern Object Pascal), and Visual Basic .NET. All languages interoperate, meaning a single project can use any combination of languages, and they can all be compiled to .NET, the JVM, native, or WebAssembly. Elements supports Microsoft Windows, all Apple Inc. platforms (including iOS, visionOS and watchOS), Android, and Linux. Elements also supports language conversion, allowing source code in one language to be rewritten in another. Elements is supported in Visual Studio, but RemObjects also makes their own IDEs, Fire (on MacOS) and Water (on Windows.) == Background == RemObjects began in 2002, creating software for Delphi, but in 2005 in response to the growth of .NET and that Delphi was targeting only native Windows, they released Oxygene (known as Chrome at the time) as a new version of Object Pascal, with more modern syntax as well as being .NET-native. Since then, five other languages have been added to the suite, as well as compiling for the web via WebAssembly and to native architectures (eg Intel 32/64 or ARM64). Elements is primarily intended for developers who want to pull together libraries and codebases written in multiple languages, including legacy codebases in older languages while modernizing either with newer syntax and features or by adding in the use of newer or more popular languages. Because of the Oxygene flavour of Object Pascal, supporting Delphi apps is a primary focus, including allowing Pascal to be compiled for other architectures or providing language features that match other prominent languages. == Approach == New versions of the Elements come out approximately every week. RemObjects names its programming languages after chemical elements, sometimes with poetic or musical spelling, rather than referring to them directly. They are: C#: Hydrogene Object Pascal: Oxygene Java: Iodine Visual Basic: Mercury Go: Gold Swift: Silver == History == The Elements compiler was first introduced with version 1.0 in 2005 under the name "Chrome", with support for only the Oxygene language on the .NET platform, primarily as a response to the then-new and not well-received Delphi .NET compiler from Embarcadero. Chrome saw updates to version 1.5 'Floorshow' and Chrome 2.0 'Joyride' over the next few years, moving in parallel with major advancements on the .NET platform for .NET 2.0 (Generics) and .NET 3.x (LINQ), respectively. With the release of version 3.0 (code-named Oxygène after the Jean-Michel Jarre album of the same name) Chrome was rebranded to Oxygene in 2008, and also shipped co-branded by Embarcadero as Delphi Prism (later just Prism) as part of RAD Studio, replacing Embarcadero's own and now-defunct Delphi.NET compiler. 2010 saw the release of Oxygene 4 ("Echoes"), the last version to focus on just a single language and platform. With Oxygene 5 in 2011 and Oxygene 6 in 2013, RemObjects introduced new platform support for Java/Android (code-name "Cooper") and then Cocoa, the Apple development platform (code-name "Toffee"). Elements 7.0 was released at the beginning of 2014, adding the second programming language, C# to the compiler, and delegating Oxygene from the product name to merely branding the Object Pascal-based language. Over the subsequent years, Elements gained support for additional languages, with Apple Swift in 2015, Java in 2017, and subsequently Google's Go and Mercury, a revitalized Visual Basic.NET. Elements also gained support for its fourth target platform, "Island", for CPU-native compilation for Windows, Linux, and WebAssembly. In addition to the chemical elements-based names for the different languages, the "Elements" concept was carried on with the introduction of dedicated development environments alchemically named Fire (for the Mac, in 2015) and Water (for Windows, in 2018). == Fire and Water (IDEs) == Fire and Water are integrated development environments developed by RemObjects Software. They are designed specifically for use with the Elements Compiler. Fire is the version developed for macOS, while Water is intended for Microsoft Windows. Both IDEs are designed to work closely with the Elements compiler and are primarily intended for developers using the RemObjects language ecosystem. They support software development across multiple platforms, including .NET, Android, iOS, macOS, Windows, Linux, and WebAssembly. The IDEs include standard development tools such as syntax highlighting, code completion, debugging, and project navigation. Build operations are managed using a custom system known as EBuild, which is part of the broader Elements toolchain. The IDEs are distributed as part of the RemObjects Elements package and are updated in coordination with the compiler itself. == In media == Oxygene has been mentioned several times by Verity Stob in their Chronicles of Delphi series, currently living at The Register.
Noise-based logic
Noise-based logic (NBL) is a class of multivalued deterministic logic schemes, developed in the twenty-first century, where the logic values and bits are represented by different realizations of a stochastic process. The concept of noise-based logic and its name was created by Laszlo B. Kish. In its foundation paper it is noted that the idea was inspired by the stochasticity of brain signals and by the unconventional noise-based communication schemes, such as the Kish cypher. == The noise-based logic space and hyperspace == The logic values are represented by multi-dimensional "vectors" (orthogonal functions) and their superposition, where the orthogonal basis vectors are independent noises. By the proper combination (products or set-theoretical products) of basis-noises, which are called noise-bit, a logic hyperspace can be constructed with D(N) = 2N number of dimensions, where N is the number of noise-bits. Thus N noise-bits in a single wire correspond to a system of 2N classical bits that can express 22N different logic values. Independent realizations of a stochastic process of zero mean have zero cross-correlation with each other and with other stochastic processes of zero mean. Thus the basis noise vectors are orthogonal not only to each other but they and all the noise-based logic states (superpositions) are orthogonal also to any background noises in the hardware. Therefore, the noise-based logic concept is robust against background noises, which is a property that can potentially offer a high energy-efficiency. == The types of signals used in noise-based logic == In the paper, where noise-based logic was first introduced, generic stochastic-processes with zero mean were proposed and a system of orthogonal sinusoidal signals were also proposed as a deterministic-signal version of the logic system. The mathematical analysis about statistical errors and signal energy was limited to the cases of Gaussian noises and superpositions as logic signals in the basic logic space and their products and superpositions of their products in the logic hyperspace (see also. In the subsequent brain logic scheme, the logic signals were (similarly to neural signals) unipolar spike sequences generated by a Poisson process, and set-theoretical unifications (superpositions) and intersections (products) of different spike sequences. Later, in the instantaneous noise-based logic schemes and computation works, random telegraph waves (periodic time, bipolar, with fixed absolute value of amplitude) were also utilized as one of the simplest stochastic processes available for NBL. With choosing unit amplitude and symmetric probabilities, the resulting random-telegraph wave has 0.5 probability to be in the +1 or in the −1 state which is held over the whole clock period. == The noise-based logic gates == Noise-based logic gates can be classified according to the method the input identifies the logic value at the input. The first gates analyzed the statistical correlations between the input signal and the reference noises. The advantage of these is the robustness against background noise. The disadvantage is the slow speed and higher hardware complexity. The instantaneous logic gates are fast, they have low complexity but they are not robust against background noises. With either neural spike type signals or with bipolar random-telegraph waves of unity absolute amplitude, and randomness only in the sign of the amplitude offer very simple instantaneous logic gates. Then linear or analog devices unnecessary and the scheme can operate in the digital domain. However, whenever instantaneous logic must be interfaced with classical logic schemes, the interface must use correlator-based logic gates for an error-free signal. == Universality of noise-based logic == All the noise-based logic schemes listed above have been proven universal. The papers typically produce the NOT and the AND gates to prove universality, because having both of them is a satisfactory condition for the universality of a Boolean logic. == Computation by noise-based logic == The string verification work over a slow communication channel shows a powerful computing application where the methods is inherently based on calculating the hash function. The scheme is based on random telegraph waves and it is mentioned in the paper that the authors intuitively conclude that the intelligence of the brain is using similar operations to make a reasonably good decision based on a limited amount of information. The superposition of the first D(N) = 2N integer numbers can be produced with only 2N operations, which the authors call "Achilles ankle operation" in the paper. == Computer chip realization of noise-based logic == Preliminary schemes have already been published to utilize noise-based logic in practical computers. However, it is obvious from these papers that this young field has yet a long way to go before it will be seen in everyday applications.