AI Art Enhancer

AI Art Enhancer — independent reviews, comparisons, pricing and step-by-step guides on Aizhi.

  • Clubdjpro

    Clubdjpro

    ClubDJPro (often referred to as ClubDJ) is a DJ console and video mixing tool developed by Cube Software Solutions Inc. software. It was released in June 2005. == User interface == ClubDJPro has a GUI that was designed to allow aesthetic revisions via Skins. The skin engine that ClubDJPro uses allows for the ability to expand the software to take up the entire screen. As of 4.4.3.3 there are 3 user changeable skins included in the program which are changeable in the preferences tab. They are called 'AquaLung', 'Eleanor', and 'Grabber'. == Editions == ClubDJPro is available in two different editions, with separate features depending upon their target consumer group. DJ Edition - Can play audio files only. VJ Edition - Contains all of the features of the DJ Edition, in addition to support for video, karaoke, and visualizations. == Supported MIDI Controllers == Supported since version 2.0: Hercules Console Hercules Console MK2 Hercules Control MP3 PCDJ DAC-2 Controller == History == The initial "final release" of ClubDJPro was released on June 24, 2005. On June 26, 2009, the 4th iteration of the ClubDJPro software was released. The development of the software and website appears to have halted. As of March 2018 the website continues to show a new version "Coming Spring 2016".

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  • Theaitre

    Theaitre

    Theaitre (stylized as THEaiTRE) is an interdisciplinary research project investigating to what extent artificial intelligence is able to generate theatre play scripts. The first theatre play produced within the project, AI: When a Robot Writes a Play, premiered online on February 26, 2021. == Goal == Following similar previous projects such as Sunspring, a short sci-fi movie with an automatically generated script, the THEaiTRE project investigates whether current language generation approaches are mature enough to generate a theatre play script that could be successfully performed in front of an audience. The project falls within the area of generative art, famously represented e.g. by the portrait of Edmond de Belamy which was generated by an artificial neural network. In this field, artists are trying to use automated techniques to create "art", questioning the modern definition of art itself. More broadly, the project aims at promoting cooperation rather than competition of humans and artificial intelligence as the more beneficial approach for both. The first theatre play created within the project, titled AI: When a Robot Writes a Play, was presented in February 2021 at the 100th anniversary of the premiere of the R.U.R. theatre play by the Czech author Karel Čapek to celebrate the invention of the word "robot". While R.U.R. was a play written by a human about robots (and humans), THEaiTRE tried to reverse this idea by presenting a play written by a "robot" (artificial intelligence) about humans (and robots). The script of the play was published online, with marked parts of the text which were written manually or manually post-edited. The analysis shows that 90% of the script is automatically generated, with 10% manually written or manually post-edited. The project also plans to produce a second play in 2022, addressing some of the many shortcomings of the approach used to generate the first play, as well as attempting to further minimize the amount of human influence on the script. == Approach == At the core of the project is the GPT-2 language model by OpenAI with various adjustments motivated by the task of generating theatre play scripts, for which the model is not particularly trained. The GPT-2 model is used in the usual way, providing it with a start of a document and prompting it to generate a continuation of the document. Specifically, the input for GPT-2 in this project is typically a short description of the scene setting, followed by a few lines to introduce the characters and start the dialogue. The model then generates 10 continuation lines, and hands control to the user, who can then either ask the model to continue generating, or make various edits before letting the model to generate further, deleting some parts of the script or adding new lines into the script. The adjustments include restricting the generator to only produce lines pertaining to characters appearing in the input prompt, limiting the repetitiveness of the generated text, and employing automatic summarization of the input prompt and the generated text to overcome the limitation of the GPT-2 model which only attends to the last 1,024 subword tokens. The limitations of the model include, among other, a lack of distinctiveness and self-consistency of the characters, an inability to generate the script for the whole play (scripts for individual scenes are generated independently), and errors due to the employment of automated machine translation, as GPT-2 generates English texts but the final play script is being produced in Czech language. The source codes of the project are available under the MIT licence. The project has also published some sample outputs. == Team == The project is a cooperation of the following experts, all based in Prague, Czech Republic: computational linguists from the Faculty of Mathematics and Physics, Charles University theatre experts from the Švanda Theatre and from the Theatre Faculty of the Academy of Performing Arts in Prague hackers from CEE Hacks The project is financially supported by the Technology Agency of the Czech Republic.

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  • Dominic Harris

    Dominic Harris

    Dominic Harris (born 16 November 1976) is a British artist known for integrating modern technology and classical design in his interactive artworks. == Background == Dominic Harris was born in London on 16 November 1976, and grew up in London, Brussels, and Michigan before returning to London in 1995. Harris attended the Cranbrook Kingswood Upper School, and then trained as an architect at the Bartlett School of Architecture, and has been ARB registered since 2011. Harris designs and fabricates his artworks at Dominic Harris Studio, a multi-disciplinary practice he founded in 2007. This studio consists of 25 people with diverse backgrounds including architecture, product design, electronics, programming, graphic design, and workshop skills. Harris uses the resources of his studio for the ongoing development, prototyping and production of his artworks. Harris also oversees the studio's international projects where his fascinations are translated into larger scale projects that span residential, retail, and public art projects. In 2015, Harris was granted permission by the Walt Disney Company to use their Intellectual Property for the purpose of making new interactive artworks. Harris is the only artist to gain permission to use Disney's back catalogue of characters, and led him to creating his interactive versions of "Snow White and the Seven Dwarfs" and "Mickey and Minnie: An Interactive Diptych". Harris is fascinated by the idea of using data streams, algorithms, and computer code to generate dynamic and ever-changing artworks. He sees data as a raw material that can be transformed into visual poetry. Many of his installations and sculptures are interactive, responding to the presence and movement of viewers/participants. This creates an immersive experience where the observer becomes part of the artwork itself. Harris is also the founding partner of a sister studio in London called Cinimod Studio that creates large commissioned installations, interactive events and lighting designs for large brands. == Works == == Exhibitions == The works of Dominic Harris have been exhibited internationally, both through direct and gallery representation. Solo shows: "Feeding Consciousness" at Halcyon Gallery, Mayfair, London, UK – 2023 "US: NOW" at Halcyon Gallery, Mayfair, London, UK – 2020 "Imagine" at Halcyon Gallery, Mayfair, London, UK – 2019 "5 Year Celebration", Priveekollektie Contemporary Art | Design, London, UK – 2016. "Moments of Reflection" at PHOS ART + DESIGN, Mayfair, London, UK – 2015 Recent exhibitions include: In Plain Sight, 2024 Halcyon Gallery Victoria & Albert Museum Dublin Science Museum Design Miami / Basel Design Miami Art Miami Art 14, London PAD Paris PAD London Art Geneva == Gallery Representation == 2010 to 2019: Dominic Harris was represented by Priveekollektie Contemporary Art | Design, a Dutch gallery based in Heusden, the Netherlands, and with a regular presence on the international art and design circuits. 2015: Dominic Harris was shown with PHOS ART + DESIGN Gallery, in Mayfair, London, UK. 2019 – ongoing: Dominic Harris is exclusively represented by the Halcyon Gallery, an established international gallery based in Mayfair, London. == Collections == The majority of Harris's work has been bought by private collectors. Since 2012 Harris's work is also being acquired by several large institutional collections, including the Borusan Contemporary Art Collection in Istanbul. Harris's artworks include some of the biggest and most respected international art collectors and are also displayed in public spaces. == Books == Dominic Harris: Feeding Consciousness. Halcyon Gallery, 2023. Imagine: Dominic Harris (exhibition catalogue). Halcyon Gallery, 2019. A Touch Of Code: Documents the "Beacon" art installation and "Flutter" artwork (ISBN 978-3899553314) Dominic Harris, Artworks, Edition Eight. (ISBN 978-0957306325) Digital Real: Kunst & Nachhaltigkeit Vol 8.

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  • Vidby

    Vidby

    Vidby AG (stylized in lower-case) is a start-up based in Rotkreuz, Switzerland specializing in AI language translation for videos. Founded by Alexander Konovalov (uk:Олександр Коновалов) and Eugen von Rubinberg in September 2021, the company has especially garnered attention for its use in translating speeches given by President Volodymyr Zelenskyy during the Russian invasion of Ukraine. == History == Vidby AG was founded by Alexander Konovalov and Eugen von Rubinberg. Konovalov is a native of Ukraine and retains Ukrainian citizenship; Rubinberg came to Switzerland from Germany and holds German citizenship. Both are residents of Switzerland. The latter founded his first business, a trading company, at age 16. In 2013, the business partners launched a consumer-oriented video-call translation service called DROTR (Droid Translator) AG, utilizing a Konovalov-created AI-powered language translation technology enabling simultaneous translation of messages, voice and video calls in 104 languages (written), with 44 available in spoken form. This was the world's first video calling app with translation. The technology was pronounced a competitor of Skype and Viber by Forbes and claimed first prize at the "Innovative Breakthrough 2013" Competition. In 2021, with a new business-oriented focus, DROTR became Vidby, with the former Google technology partners Konovalov and Rubinberg remaining at the helm, each with the title Co-CEO. While headquartered in Switzerland, Vidby's development team is, according to the company's founders, based in Ukraine. The technology behind Vidby has an accuracy level variously reported as up to 99 percent or 99 to 100 percent, equalling the highest level of human translation. Additionally, the technology is capable of removing the original language while maintaining ambient sounds. Currently, some 70 languages plus 60 dialects are possible with the algorithm-based technology. == Notable use == In addition to its use with speeches delivered by Pope Francis, the technology has been provided to Ukrainian authorities and embassies during the ongoing military conflict with Russia free of remuneration. By July, 2022, some 70 speeches given by President Zelenskyy totalling 650 minutes had been translated into 30 languages, for a total of over 10,000 minutes of video material. Of its use in translating Zelenskyy's wartime speeches, Konovalov has said, "Like any citizen, I want to help defend my country." Notable corporate clients of Vidby include Samsung, Siemens, Cisco, Kärcher, Generali and McDonald's Corporation; an academic client is Harvard University. Google Cloud Technology Partner status of Vidby was confirmed officially after a six-month audit in December 2022. Denys Krasnikov, a Vidby co-founder, is responsible for cooperation with Google, YouTube, Microsoft, and other key partners. After the launch of multilingual YouTube channels, Vidby started AI translating and dubbing creators' videos for this new type of channel at the end of February 2023. == Accolades == Vidby headed a list of the five best video translation services as named by TechRadar Deutschland in September, 2022. In the same month, Tech Times named Vidby #1 in their list of the five best such services. It similarly topped a list of the five best content translation technologies as judged by European Business Review in October, 2022. Prior to these lead-position rankings (August, 2022), it was featured as Business Insider's special start-up recommendation (German: "Unser Lesetipp auf Gründerszene"). In 2023, YouTube recognized Vidby as its recommended vendor.

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  • Clef (app)

    Clef (app)

    Clef was a San Francisco-based technology company, known for developing a mobile app that created a two-factor authentication for websites. It allowed users to access sites with a single login password management service which stores encrypted passwords in private accounts. It had a standard verification method that requires access to data on the mobile phone to confirm the user's identity. The application required a Wi-Fi or mobile network, and the user could log in by scanning the computer screen with their phone. == History == Clef was founded in 2013 by Mark Hudnall, B. Byrne and Jesse Pollak. It raised $1.6 million in seed funding in November 2014. Clef integrated with many websites and applications, including WordPress. On March 17, 2017, Clef announced they would no longer support the plugin after June 6, 2017; Clef was acquired by Authy, another 2FA service, which later got acquired by Twilio.

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  • Fuzzy finite element

    Fuzzy finite element

    The fuzzy finite element method combines the well-established finite element method with the concept of fuzzy numbers, the latter being a special case of a fuzzy set. The advantage of using fuzzy numbers instead of real numbers lies in the incorporation of uncertainty (on material properties, parameters, geometry, initial conditions, etc.) in the finite element analysis. One way to establish a fuzzy finite element (FE) analysis is to use existing FE software (in-house or commercial) as an inner-level module to compute a deterministic result, and to add an outer-level loop to handle the fuzziness (uncertainty). This outer-level loop comes down to solving an optimization problem. If the inner-level deterministic module produces monotonic behavior with respect to the input variables, then the outer-level optimization problem is greatly simplified, since in this case the extrema will be located at the vertices of the domain.

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  • Artificial intelligence engineering

    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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  • Fuzzy architectural spatial analysis

    Fuzzy architectural spatial analysis

    Fuzzy architectural spatial analysis (FASA) (also fuzzy inference system (FIS) based architectural space analysis or fuzzy spatial analysis) is a spatial analysis method of analysing the spatial formation and architectural space intensity within any architectural organization. Fuzzy architectural spatial analysis is used in architecture, interior design, urban planning and similar spatial design fields. == Overview == Fuzzy architectural spatial analysis was developed by Burcin Cem Arabacioglu (2010) from the architectural theories of space syntax and visibility graph analysis, and is applied with the help of a fuzzy system with a Mamdani inference system based on fuzzy logic within any architectural space. Fuzzy architectural spatial analysis model analyses the space by considering the perceivable architectural element by their boundary and stress characteristics and intensity properties. The method is capable of taking all sensorial factors into account during analyses in conformably with the perception process of architectural space which is a multi-sensorial act.

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  • Fred (chatbot)

    Fred (chatbot)

    Fred, or FRED, was an early chatbot written by Robby Garner. == History == The name Fred was initially suggested by Karen Lindsey, and then Robby jokingly came up with an acronym, "Functional Response Emulation Device." Fred has also been implemented as a Java application by Paco Nathan called JFRED Archived 2008-08-24 at the Wayback Machine. Fred Chatterbot is designed to explore Natural Language communications between people and computer programs. In particular, this is a study of conversation between people and ways that a computer program can learn from other people's conversations to make its own conversations. Fred used a minimalistic "stimulus-response" approach. It worked by storing a database of statements and their responses, and made its own reply by looking up the input statements made by a user and then rendering the corresponding response from the database. This approach simplified the complexity of the rule base, but required expert coding and editing for modifications. Fred was a predecessor to Albert One, which Garner used in 1998 and 1999 to win the Loebner Prize.

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  • Your AI Slop Bores Me

    Your AI Slop Bores Me

    Your AI Slop Bores Me (stylized in all lowercase) is a website and social experiment created by programmer Mihir Maroju. Serving as a parody of large language models (LLMs) like ChatGPT and Claude, all questions and image prompts posed by users are answered by other, randomly-selected human users of the site. As of March 2026, the site has reached 50 million hits and sits at 16,000 concurrent users. == Background == In an interview with Fast Company, Maroju said he was inspired to create the site by his frustration with AI proliferating the internet with AI generated content, saying the site came from "a frustration for AI art and its proliferation, making artists' lives worse and also just filling the internet with low-effort generic slop". == Overview == The site has a credit system, in which a first-time user will be given 1 credit for free. Every 10 minutes, if a user has 0 credits, they will receive 2 credits. Once the credits are used up, the user can no longer do prompts unless the user earns them. The user can earn credits by responding to other user's prompts by "larping as AI" while given a 75-second time limit. Prompts can either be for a written response, or a drawing for the other user to fulfill the prompt. The maximum amount of credits a user can have is 6 credits, and cannot exceed the maximum limit. If the prompting user activates "thinking mode", the countdown is extended to 150 seconds for the cost of 2 credits. == Reception == The site has garnered attention and praise from X users, and across many online communities. The Daily Dot's Rachel Kiley wrote that "the best part about the game is that there's really no right or wrong way to do it. Humans aren't LLMs trained on copyrighted material and the whole of the free internet, but we do retain a certain amount of the information we've learned from those things over the course of our lives, while also being capable of creativity". Chris Taylor of Mashable called the site "amateurish and charming". Aftermath's Nicole Carpenter wrote that the site reminded her of "the human touch of chaos".

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  • Fuzzy relation

    Fuzzy relation

    A fuzzy relation is the cartesian product of mathematical fuzzy sets. Two fuzzy sets are taken as input, the fuzzy relation is then equal to the cross product of the sets which is created by vector multiplication. Usually, a rule base is stored in a matrix notation which allows the fuzzy controller to update its internal values. From a historical perspective, the first fuzzy relation was mentioned in the year 1971 by Lotfi A. Zadeh. A practical approach to describe a fuzzy relation is based on a 2d table. At first, a table is created which consists of fuzzy values from 0..1. The next step is to apply the if-then-rules to the values. The resulting numbers are stored in the table as an array. Fuzzy relations can be utilized in fuzzy databases.

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  • Ghost in the Shell

    Ghost in the Shell

    Ghost in the Shell is a Japanese cyberpunk military science fiction media franchise that began with the eponymous manga series, written and illustrated by Masamune Shirow. The manga, first serialized from 1989 to 1991, is set in the mid-21st-century and follows the fictional counter-cyberterrorist organization Public Security Section 9, led by protagonist Major Motoko Kusanagi. Animation studio Production I.G has produced several anime adaptations of the series. These include the 1995 film of the same name and its 2004 sequel, Ghost in the Shell 2: Innocence; the 2002 television series Ghost in the Shell: Stand Alone Complex and its 2020 follow-up, Ghost in the Shell: SAC_2045; and the Ghost in the Shell: Arise original video animation series. In addition, an American-produced live-action film was released in March 2017. == Overview == === Title === The original editor Koichi Yuri says: At first, Ghost in the Shell came from Shirow, but when Yuri asked for "something more flashy", Shirow came up with "攻殻機動隊 Koukaku Kidou Tai (Shell Squad)" for Yuri. But Shirow was attached to including "Ghost in the Shell" as well even if in smaller type. === Setting === Primarily set in the mid-twenty-first century in the fictional Japanese city of Niihama, Niihama Prefecture (新浜県新浜市, Niihama-ken Niihama-shi), otherwise known as New Port City (ニューポートシティ, Nyū Pōto Shiti), the manga and the many anime adaptations follow the members of Public Security Section 9, a task-force consisting of various professionals skilled at solving and preventing crime, mostly with some sort of police background. Political intrigue and counter-terrorism operations are standard fare for Section 9, but the various actions of corrupt officials, companies, and cyber-criminals in each scenario are unique and require the diverse skills of Section 9's staff to prevent a series of incidents from escalating. In this post-cyberpunk iteration of a possible future, computer technology has advanced to the point that many members of the public possess cyberbrains, technology that allows them to interface their biological brain with various networks. The level of cyberization varies from simple minimal interfaces to almost complete replacement of the brain with cybernetic parts, in cases of severe trauma. This can also be combined with various levels of prostheses, with a fully prosthetic body enabling a person to become a cyborg. The main character of Ghost in the Shell, Major Motoko Kusanagi, is such a cyborg, having had a terrible accident befall her as a child that ultimately required her to use a full-body prosthesis to house her cyberbrain. This high level of cyberization, however, opens the brain up to attacks from highly skilled hackers, with the most dangerous being those who will hack a person to bend to their whims. == Media == === Literature === ==== Original manga ==== The original Ghost in the Shell manga ran in Japan from April 1989 to November 1990 in Kodansha's manga anthology Young Magazine, and was released in a tankōbon volume on October 2, 1991. Ghost in the Shell 2: Man-Machine Interface followed in 1997 for nine issues in Young Magazine, and was collected in the Ghost in the Shell: Solid Box on December 1, 2000. Then a standard version with modifications and new pages was published on June 26, 2001. Four stories from Man-Machine Interface that were not released in tankobon format from previous releases were later collected in Ghost in the Shell 1.5: Human-Error Processor, and published by Kodansha on July 17, 2003. Several art books have also been published for the manga. === Films === ==== Animated films ==== Two animated films based on the original manga have been released, both directed by Mamoru Oshii and animated by Production I.G. Ghost in the Shell was released in 1995 and follows the "Puppet Master" storyline from the manga. It was re-released in 2008 as Ghost in the Shell 2.0 with new audio and updated 3D computer graphics in certain scenes. Innocence, otherwise known as Ghost in the Shell 2: Innocence, was released in 2004, with its story based on a chapter from the first manga. ==== Live-action film ==== In 2008, DreamWorks and producer Steven Spielberg acquired the rights to a live-action film adaptation of the original Ghost in the Shell manga. On January 24, 2014, Rupert Sanders was announced as director, with a screenplay by William Wheeler. In April 2016, the full cast was announced, which included Juliette Binoche, Chin Han, Lasarus Ratuere and Kaori Momoi, and Scarlett Johansson in the lead role; the casting of Johansson drew accusations of whitewashing. Principal photography on the film began on location in Wellington, New Zealand, on February 1, 2016. Filming wrapped in June 2016. Ghost in the Shell premiered in Tokyo on March 16, 2017, and was released in the United States on March 31, 2017, in 2D, 3D and IMAX 3D. It received mixed reviews, with praise for its visuals and Johansson's performance but criticism for its script. === Television === ==== Stand Alone Complex TV series, film and ONA ==== In 2002, Ghost in the Shell: Stand Alone Complex premiered on Animax, presenting a new telling of Ghost in the Shell independent from the original manga, focusing on Section 9's investigation of the Laughing Man hacker. It was followed in 2004 by a second season titled Ghost in the Shell: S.A.C. 2nd GIG, which focused on the Individual Eleven terrorist group. The primary storylines of both seasons were compressed into OVAs broadcast as Ghost in the Shell: Stand Alone Complex The Laughing Man in 2005 and Ghost in the Shell: Stand Alone Complex Individual Eleven in 2006. Also in 2006, Ghost in the Shell: Stand Alone Complex - Solid State Society, featuring Section 9's confrontation with a hacker known as the Puppeteer, was broadcast, serving as a finale to the anime series. The extensive score for the series and its films was composed by Yoko Kanno. On April 7, 2017, Kodansha and Production I.G announced that Kenji Kamiyama and Shinji Aramaki would be co-directing a new Kōkaku Kidōtai anime production. On December 7, 2018, it was reported by Netflix that they had acquired the worldwide streaming rights to the original net animation (ONA) anime series, titled Ghost in the Shell: SAC_2045, and that it would premiere on April 23, 2020. The series is in 3DCG and Sola Digital Arts collaborated with Production I.G on the project. Ilya Kuvshinov handled character designs. The series had two seasons of 12 episodes each. In addition to the anime, a series of published books, two separate manga adaptations, and several video games for consoles and mobile phones have been released for Stand Alone Complex. ==== Arise OVA, TV series and film ==== In 2013, a new iteration of the series titled Ghost in the Shell: Arise premiered, taking an original look at the Ghost in the Shell world, set before the original manga. It was released as a series of four original video animation (OVA) episodes (with limited theatrical releases) from 2013 to 2014, then recompiled as a 10-episode television series under the title of Kōkaku Kidōtai: Arise - Alternative Architecture. An additional fifth OVA titled Pyrophoric Cult, originally premiering in the Alternative Architecture broadcast as two original episodes, was released on August 26, 2015. Kazuchika Kise served as the chief director of the series, with Tow Ubukata as head writer. Cornelius was brought onto the project to compose the score for the series, with the Major's new voice actress Maaya Sakamoto also providing vocals for certain tracks. Ghost in the Shell: The New Movie, also known as Ghost in the Shell: Arise − The Movie or New Ghost in the Shell, is a 2015 film directed by Kazuya Nomura that serves as a finale to the Ghost in the Shell: Arise story arc. The film is a continuation to the plot of the Pyrophoric Cult episode of Arise, and ties up loose ends from that arc. A manga adaptation was serialized in Kodansha's Young Magazine, which started on March 13 and ended on August 26, 2013. ==== 2026 anime ==== On May 25, 2024, it was announced that a new anime television series adaptation will be produced by Science Saru for a July 2026 premiere. Saru will be in a production committee with Bandai Namco Filmworks, Kodansha and Production I.G. The series will be directed by Monkochan, with a script by EnJoe Toh. === Video games === Ghost in the Shell was developed by Exact and released for the PlayStation on July 17, 1997, in Japan by Sony Computer Entertainment. It is a third-person shooter featuring an original storyline where the character plays a rookie member of Section 9. The video game's soundtrack Megatech Body features various techno artists, such as Takkyu Ishino, Scan X and Mijk Van Dijk. Several video games were also developed to tie into the Stand Alone Complex television series, in addition to a first-person shooter by Nexon and Neople titled Ghost in the Shell: Stand Alone Complex - First Assault Online,

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  • Tandem (app)

    Tandem (app)

    Tandem is a mobile language exchange and language learning app. == History == Tandem was founded in Hannover, Germany in 2014 by Arnd Aschentrup, Tobias Dickmeis, and Matthias Kleimann. Prior to founding Tandem, the trio had launched Vive, a members-only mobile video chat platform. Tandem has been criticised for not accepting members into the community immediately, as opposed to competitors including HelloTalk, Speaky or Cafehub. In some countries, there is a waiting list and applicants can wait up to seven days for their application to be processed by human moderators. In 2015, Tandem completed its first funding round (seed funding) of €600,000. Participating investors included business angels such as Atlantic Labs (Christophe Maire), Hannover Beteiligungsfonds, Marcus Englert (Chairman of the Supervisory Board of Rocket Internet SE ), Catagonia, Ludwig zu Salm, Florian Langenscheidt, Heiko Hubertz, Martin Sinner, and Zehden Enterprises. In 2016, the company received a further €2 million from new investors Rubylight and Faber Ventures, as well as from existing investors Hannover Beteiligungsfonds, Atlantic Labs, and Zehden Enterprises. Since 2018, the premium membership Tandem Pro has been available, which offers members unlimited access to all language learning features of the app as well as the removal of advertising for a monthly fee.

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  • Fragile Dreams: Farewell Ruins of the Moon

    Fragile Dreams: Farewell Ruins of the Moon

    Fragile Dreams: Farewell Ruins of the Moon (フラジール ~さよなら月の廃墟~, Furajīru: Sayonara Tsuki no Haikyo; known in Japan as Fragile) is an action role-playing game for the Wii developed by Namco Bandai Games in co-operation with Tri-Crescendo. The game was released by Namco Bandai Games in Japan on January 22, 2009. It was later published by Xseed Games in North America on March 16, 2010, and in Europe by Rising Star Games on March 19, 2010, followed by its release in Australia on April 1, 2010. == Gameplay == In Fragile Dreams, the player character, Seto, must traverse the ruins of Tokyo and the surrounding areas, fighting off ghosts that lurk within these ruins. The game's heads-up display includes a mini-map and HP gauge for Seto's location and health, respectively. Seto will fall unconscious if his HP reaches zero, resulting in a game over. The player controls Seto from a third-person perspective with the Wii Remote and Nunchuk. Seto can use his flashlight (controlled by the Wii Remote pointer) to illuminate his surroundings or solve puzzles and interact with the environment. When searching for certain objectives or hidden enemies, pointing Seto's light in their direction picks up and plays their sounds through the Wii Remote's mini speaker. The Wii Nunchuk, meanwhile, directly controls Seto's movement: aside of basic movement, he can crouch to hide and crawl through small spaces. Seto will often come across damaged floors, which require slow movement (and for heavily damaged floors, crouching) to cross without falling through. As Seto, the player can use weapons found throughout the world to fight off ghosts, ranging from slingshots and golf clubs to crossbows and katanas. Each weapon can only take a certain amount of use: once a weapon reaches its limit, it will break after battle. The player can also find other usable and collectable items in the field, marked with fireflies. The player can only save their game by resting at small fire pits scattered throughout the world: used fire pits are marked with a bonfire. The player can also examine and identify Mystery Items, organize their inventory, as well as after encountering the Merchant, buy and sell items. As stated by the producer of the game, Kentarō Kawashima, Fragile Dreams is not strictly a survival horror: rather, its story focuses on human drama. In Fragile Dreams, aside of the main story, the player can find and examine objects and graffiti throughout the world. Objects called memory items (ranging from origami and stones to cell phones and books) hold the memories of their former owners (only accessible at bonfires), while the graffiti contains messages only seen by pointing at them in first-person. By examining these messages, the player can piece together hints to the game's backstory. == Story == === Setting and characters === Fragile Dreams is set in a post-apocalyptic version of Earth in the near-future. Almost all the world's population has vanished, leaving the surviving buildings and structures abandoned. The game is set in and near the ruins of Tokyo, Japan, where the event that nearly wiped out humanity may have originated. The protagonist, Seto, is a 15-year-old boy who searches the world for other living humans. He encounters Ren, a silver-haired girl who often leaves behind large, cryptic drawings. Other characters include: Sai, the ghost of a young woman; Crow, a mischievous and straightforward amnesiac boy; Personal Frame (P.F.), a portable computer who loves having conversations more than anything else; Chiyo, the ghost of a little girl; and the Merchant, a mysterious yet merry man who trades various goods. The game's host of enemies mainly consist of ghosts, but also include humanoid robots and security proxies. The main antagonist, Shin, is the AI of a scientist who considers speech to be an inferior means of communication. Various memory items include a greater set of characters, each giving hints to the game's backstory. === Plot === At the end of Seto's fifteenth summer, his grandfather dies. Seto buries him in front of their home, an old observatory, and that from then on he became "truly alone". At night, he searches for anything the old man had left for him and discovers a letter, along with a strange blue stone in a locket. Suddenly, a mask-like ghost appears and attacks Seto. After driving the creature off, Seto reads the old man's letter, who tells him to "reach a tall red tower" east of the observatory, where he might find other survivors. After departing for the tower, Seto reaches an old subway entrance in the Azabudai district and finds Ren sitting on a collapsed pillar, singing to the stars. He accidentally startles her and the frightened Ren flees into the subway station: getting over the shock of meeting another person, Seto follows her. While searching the station, he discovers a Personal Frame, who guides him towards Ren. Unfortunately, just as they reach the exit, P.F.'s battery dies out: Seto buries the device, keeping a screw from it in his locket. From the underground, Seto finds himself at an abandoned amusement park and encounters Crow, who steals Seto's locket. After a long chase across the park and another encounter with the masked ghost, Crow returns Seto's locket and directs him to a hotel nearby, where he saw a girl who might know something about Ren. Crow also gives Seto his skull ring to keep in his locket and kisses him. At the hotel, Seto encounters Sai and fights the masked ghost again. After laying to rest the spirit of an old woman named Chiyo, the two discover Ren's drawings by a sewer. Returning to the underground, Seto and Sai find themselves at a hydropower dam. While searching for Ren, Seto discovers that Crow is actually a robot, but his battery begins to fail and Seto mourns for him as he "die[s]". Finally, they encounter Ren in a cell: although glad to see him again, Ren runs off after Shin calls. Sai explains to Seto that most of humanity died because of a "human empathy expansion project" called Glass Cage. The project was meant to make human thoughts transparent, meaning that no one would need words to communicate. However, after Glass Cage activated, people who went to sleep never woke up again. Sai reveals that she was Glass Cage's first catalyst: this time, Shin intends to use Ren as the catalyst. After exiting the dam, a demolition crane attempts to destroy it. Hearing both Shin's and the masked ghost's voices from the crane — saying, "Any threat to the project must be eliminated." — the player realizes both are manifestations of Glass Cage. After Seto destroys the crane, Sai leads him to the facility where Ren was taken to. Entering the laboratory, Seto and Sai are confronted by Shin, who coldly dismisses Sai's attempts at reasoning with him and is adamant about proceeding with his plans. As they traverse the laboratory, they overhear a voice announcing "Glass Cage Launch Preparations Complete", strengthening their resolve to save Ren. Making it into the room where Ren is being held, Shin tells them of his intention to use Glass Cage to "obliterate corporeal beings". After Seto defeats him, Shin disappears and Seto releases Ren from the device holding her. Their reunion is cut short as Sai tells them that the backup system has "finished copying her psyche to the AI", allowing Glass Cage to proceed. Ren reveals Shin has escaped to the top of the Tokyo Tower and Seto asks Ren to wait at the base of the tower and for Sai to accompany her. On his way up the tower, Seto hears the voices of P.F., Chiyo and Crow wishing him luck. He confronts and defeats Shin a second time, who reveals his motivations: he had secretly used himself as the first test subject of the human empathy expansion project and gained the ability to hear the thoughts of those around him. Despite his initial belief in the project as a way for humans to empathize with one another, all he heard around him was "jealousy and contempt" and he soon grew disillusioned with the world as even his parents turned against him. Believing no person loved him, Shin wants to put an end to humanity. His words meet with a vehement response from Sai, as she tells him that she loves him, having developed those feelings while she was the catalyst and all she ever wanted was to be part of his life. Hearing this, Shin finds peace, tossing the AI mainframe away so Glass Cage can never be reactivated and vanishes together with Sai, hand-in-hand, after thanking Seto. Descending from the tower, Seto finally learns Ren's name and they resolve to look for other survivors together. == Development == Fragile Dreams was developed by the team at Namco Bandai Games. Director and producer Kentarō Kawashima came up with the concept for the game in 2003, before the Wii console was revealed. When the Wii was unveiled, it became the obvious choice as the game's platform as the Wii remote could be used to control the flashlight. Kawashima wrote the main scenario for the title, w

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  • Recraft

    Recraft

    Recraft is a generative artificial intelligence program and service developed by the London-based startup Recraft, Inc. The company also offers Recraft Studio, a web-based workspace that lets users create and edit images, vectors, and mockups using various text-to-image models. Like models such as Midjourney and DALL-E, the Recraft model generates digital images from natural language prompts, and is specifically tailored for creative workflows, with features that emphasize brand consistency, text fidelity, and layout control. == History and background == Recraft, Inc. was founded in 2022 by machine learning scientist Anna Veronika Dorogush, best known for co-creating the CatBoost machine learning library at Yandex. The company emerged from stealth on May 31, 2023, with a public release of its vector graphics generation capability on Product Hunt. On January 17, 2024, TechCrunch profiled Recraft’s foundational model for graphic design, noting its emphasis on addressing copyright and ethical concerns associated with AI-generated imagery. On October 28, 2024, TechCrunch reported that Recraft's third major model, V3, had topped a crowdsourced benchmark, surpassing Midjourney and OpenAI's DALL-E in overall image quality. On May 5, 2025, Recraft announced a $30 million Series B funding round led by Accel, reporting more than four million registered users at the time of the announcement. == Models == Recraft has developed multiple generations of its text-to-image models since 2022. Each generation reflects improvements in fidelity, controllability, and support for both raster and vector outputs. The models are proprietary and accessible through the Recraft API, Recraft Studio. Recraft models are also hosted as an image generation API on fal, Replicate, Prodia, and others. === Recraft V2 === Recraft V2 was released in March 2024 and was the company’s first model trained from scratch. It contained roughly 20 billion parameters and introduced native vector image generation, brand-color conditioning, and improved stylistic consistency for icons and illustrations. === Recraft V3 === Recraft V3 was released in October 2024 and achieved first place on the Artificial Analysis benchmark hosted on Hugging Face. The model introduced advances in photorealism, improved rendering of multi-word text, and increased responsiveness to detailed descriptive prompts. It also added the “Artistic” parameter, which allowed users to adjust stylistic intensity within generated images. === Recraft V4 === Recraft V4 was released in February 2026. According to Recraft, V4 is a “ground-up rebuild” aimed at improving prompt accuracy and output quality for design workflows, with the company emphasizing “design taste” and art-directed results. Recraft states that V4 is available in two versions: V4 for faster iteration and V4 Pro for higher-resolution, print-ready assets; the API documentation describes V4 as 1-megapixel output and V4 Pro as 4-megapixel output, with vector variants available for each. === Features === Vectorization: Recraft’s models can generate and convert images into native vector formats, producing scalable graphics composed of editable paths rather than fixed pixels. Style reference: The models support the use of reference images to guide stylistic characteristics such as color palette, line quality, composition, or visual tone. Style mixing: Recraft models can combine multiple stylistic inputs within a single generation. By blending attributes from different references or stylistic instructions, the system produces images that reflect hybrid visual characteristics while maintaining internal consistency. Inpainting editing: The models support localized image modification through inpainting, enabling users to regenerate selected regions of an image while preserving surrounding content. === Model capabilities === Recraft’s models generate raster and vector images from natural-language prompts and are designed to interpret detailed descriptions with attention to composition, style, and text placement. The models support controlled stylistic variation through preset or reference-based guidance and can maintain coherent line, color, or layout structure across multiple outputs. They produce scalable vector graphics alongside high-resolution raster images, and include features for localized image modification through inpainting or outpainting operations. === Technology === Recraft has not publicly disclosed the detailed technical architecture of its models. However, third-party reviews and benchmarks have noted that its performance resembles diffusion models such as Midjourney and Stable Diffusion. The model is designed for creative workflows requiring visual consistency and flexible output formats. Reviewers have noted its ability to generate legible multi-line text, produce high-resolution imagery at various canvas sizes, and to maintain alignment with user-defined brand palettes and design themes. Though not open-source, Recraft's models are accessible through a web interface and commercial API. Advanced features such as style settings and positioning control differentiate it from general-purpose text-to-image models. == Recraft Studio == Recraft Studio is a web-based workspace for generating and editing images using Recraft’s image models and selected external models. The infinite canvas interface provides access to a range of creation and refinement tools within a single environment. Raster and vector generation with styles: Recraft Studio supports the generation of both raster and vector images. Users can apply predefined or reference-based styles during generation, allowing for visual consistency across multiple outputs. Mockups: The studio includes mockup tools that allow generated designs to be placed onto predefined surfaces or templates for visualization and presentation purposes. Vectorization: Recraft Studio provides vectorization tools that convert raster images into editable vector graphics, enabling further modification of shapes, colors, and layout. Image upscaling: The workspace includes image upscaling functionality for increasing resolution while preserving visual detail. Editing tools and natural-language editing: Recraft Studio offers a set of editing tools for modifying images within the canvas, including localized adjustments and natural-language–based editing commands that allow users to describe changes using text. === Supported models === Recraft Studio provides access to Recraft’s proprietary image models as well as other external frontier image models such as Nano Banana, GPT 4-o, Imagen, Flux, and others. == Business model == Recraft develops proprietary image models that are accessible through Recraft Studio and the Recraft API. Recraft Studio operates on a freemium model, offering a free tier with limited daily credits and paid subscriptions for access to additional features. The API follows a credit-based system in which units are purchased separately for programmatic image generation. A team plan supports collaborative use, and the API enables organizations and developers to integrate Recraft’s image generation and editing capabilities into their own systems and workflows.

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