AI Art Or Not Game

AI Art Or Not Game — independent reviews, comparisons, pricing and step-by-step guides on Aizhi.

  • Jive (software)

    Jive (software)

    Jive (formerly known as Clearspace, then Jive SBS, then Jive Engage) is a commercial Java EE-based Enterprise 2.0 collaboration and knowledge management tool produced by Jive Software. It was first released as "Clearspace" in 2006, then renamed SBS (for "Social Business Software") in March 2009, then renamed "Jive Engage" in 2011, and renamed simply to "Jive" in 2012. Jive integrates the functionality of online communities, microblogging, social networking, discussion forums, blogs, wikis, and IM under one unified user interface. Content placed into any of the systems (blog, wiki, documentation, etc.) can be found through a common search interface. Other features include RSS capability, email integration, a reputation and reward system for participation, personal user profiles, JAX-WS web service interoperability, and integration with the Spring Framework. The product is a pure-Java server-side web application and will run on any platform where Java (JDK 1.5 or higher) is installed. It does not require a dedicated server - users have reported successful deployment in both shared environments and multiple machine clusters. As of Jive 8, released March 30, 2015, there is a Jive-n version which is for internal use (hosted by the consumer or hosted by Jive as a service) and a Jive-x version which is an external version hosted as a service. Jive no longer supports wiki markup language. == Server requirements for Jive 8-n == The following are the server requirements for Jive 8-n Operating systems: RHEL version 6 or 7 for x86_64, CentOS version 6 or 7 for x86_64 or SuSE Enterprise Linux Server (SLES) 11 and 12 for x86_64 Application Servers: Jive ships with its own embedded Apache HTTPD and Tomcat servers as part of the install package. It is not possible to deploy the application onto other appservers. Databases: MySQL (5.1, 5.5, 5.6) Oracle (11gR2, 12c) Postgres (9.0, 9.1, 9.2, 9.3, 9.4 - 9.2 or higher recommended) Microsoft SQL Server (2008R2, 2012, 2014) Environment: Jive recommends a server with at least 4GB of RAM and a dual-core 2 GHz processor with x86_64 architecture The product integrates with an LDAP repository or Active Directory For optimal deployment with a large community Jive Software recommends: using dedicated cache and document-conversion servers hosting the application and database servers separately == Releases == Jive 8, released on March 30, 2015 Jive 7, released in October 2013 Jive 9.0.x, released in November 2016 Jive 9, released in November 2016, supported now

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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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  • Libby Heaney

    Libby Heaney

    Libby Heaney is a British artist and quantum physicist known for her pioneering work on AI and quantum computing. She works on the impact of future technologies and is widely known to be the first artist to use quantum computing as a functioning artistic medium. Her work has been featured internationally, including in the Victoria and Albert Museum, Tate Modern and the Science Gallery. == Early life and scientific career == Heaney is from Tamworth, Staffordshire. She lived in Amington, and went to Greenacres Primary School and Woodhouse High School, now called Landau Forte Academy Amington. She took her GCSEs in 1999. She studied physics at Imperial College London, graduating in 2005 with first class honours. Libby pursued a successful career in quantum physics, completing a PhD thesis on mode entanglement in ultra-cold atomic gases at the University of Leeds, and pursued her own research as a postdoctoral fellow at the University of Oxford and at the National University of Singapore. In 2008, Heaney was awarded the Institute of Physics Very Early Career Woman in Physics Award (now Jocelyn Bell Burnell Medal and Prize). == Artistic career == In 2013 Heaney returned to the UK and completed a master's degree at the University of the Arts London. She studied arts and science at Central Saint Martins and graduated in 2015. She then became a lecturer at the Royal College of Art, teaching Information Experience Design. In 2016, she created Lady Chatterley's Tinderbot which presented Tinder conversations between real users and AI bots programmed using Lady Chatterley's Lover. Lady Chatterley's Tinderbot was covered by BBC News, TheJournal.ie and the Irish Examiner and was exhibited internationally. In 2017, Heaney was commissioned by Sky Arts and the Barbican Centre to design Britbot, an internet bot built using artificial intelligence and the citizenship book Life in the UK: a guide for new residents. The book, a manual for the citizenship test, has been described by Heaney as being "largely a white male privileged version of British history and culture". The bot spoke to the public about what it meant to be British and learnt from their responses to become an ever changing, plural version of Britishness. She was awarded an Arts Council England grant to widen participation of the Britbot to social media. Heaney has exhibited Britbot at the Victoria and Albert Museum, at CogX, the Sheffield Documentary Festival the Edinburgh TV festival, and Art Ai in Leicester. She has been creating with quantum computing since 2019, and has created artworks using quantum computing for Light Art Space (LAS) in Berlin, Somerset House and arebyte in London. Using quantum code, storytelling, and immersive installations and performances, Libby Heaney's works such as Ent- and slimeqore explore and warn against the double-edged potential of quantum computing and its exploitation by private companies. In 2022, Ent- received the Lumen Prize immersive environment award. == Major works == === Ent- and The Evolution of Ent-: QX (2022) === In 2022, Libby Heaney was commissioned by Light Art Space to create Ent-, a 360 immersive installation that revisits Bosch's Garden of Earthly Delights through quantum. The work uses quantum computing as both a medium and a paradigm through which to conceive human and non-human relations. Ent- was exhibited at LAS, Ars Electronica, and arebyte gallery in London. The work was also modified to fit a full dome projection at the Deutsches Museum in Munich, projected onto a public facade in Seoul, and turned into a playable version for an exhibition at Nahmad Contemporary in New York. In 2022, Ent- was a winner in the Art Science Category of the Falling Walls prize and received the Lumen Prize immersive environment award. The Evolution of Ent-:QX, first displayed at arebyte gallery in London, builds on Ent- and imagines a fictional quantum computing company (QX) that appropriates, parodies and subverts the language of big tech in order to educate the viewer on current profit-oriented uses of quantum computing as well as propose new ways to think about and use the technology. In 2023, Ent- was acquired and displayed by the 0xCollection, a new media arts institution based in Basel, in their inaugural exhibition in Prague. === Touch is response-ability (2020) === Touch is response-ability is an instagram performance and touch screen installation where participants activate animations by flicking through instagram stories. The performance investigates representations of the female body in art history and through computer vision to see how stereotypes are socially constructed and maintained. Images of the body are passed through a quantum algorithm, and as the users interact with them they progressively become fragmented and dissolve beyond recognition. The work was originally commissioned by Hervisions at LUX in 2020 and performed on the LUX instagram account. It was also exhibited at Etopia Zaragoza in 2021 and at Art SG with Gazelli Art House in 2023. === Lady Chatterley's Tinderbot (2016) === In Lady Chatterley's Tinderbot, Libby Heaney programmed a bot to engage in conversations on Tinder by using lines from the 1928 novel Lady Chatterley's Lover, by D.H. Lawrence. The work was first shown as an interactive installation in 2016 at the Dublin Science Gallery, allowing visitors to swipe left or right to navigate through various conversations. Lady Chatterley's Tinderbot was also exhibited at Sonar+D in Barcelona (2017), the Telefonica Fundacion in Lima (2017), the Lowry in Salford (2018), RMIT gallery in Melbourne (2021), Microwave Festival in Hong Kong (2022) and was shortlisted for the HEK-Basel Net-based art award in 2018. == Selected exhibitions == 2023 - Synesthetic Immersion, 0xCollection, Prague 2023 - slimeQrawl, Shoreditch Arts Club, London 2023 - ...and that's only (half) the story, PLUS ONE Gallery, Antwerp 2023–Present Futures Festival, Centre of Contemporary Art, Glasgow 2023 - Realtime: Lilypads: Mediating Exponential Systems, NXT Museum, Amsterdam 2023 - My Rhino is not a Myth, Art Encounters Biennial, Timisoara 2023 - Ent-er the Garden of Forking Paths, Gazelli Art House, London 2023 - Energeia, Etopia, Zaragoza 2022 - Every Kind of Wind: Calder and the 21st Century, Nahmad Contemporary, New York 2022 - remiQXing still, Fiumano Clase, London 2022 - the Evolution of Ent-: QX, arebyte, London 2022 - Ent-, Light Art Space x Schering Stiftung, Berlin 2022 - Among the Machines, Zabludowicz Collection, London 2022 - BioMedia, ZKM, Karlsruhe 2021 - CASCADE, Southbank Centre, London 2021 - Agency is the Ability to Act, Holden Gallery, Manchester 2021 - BIAS, Science Gallery, Dublin 2021 - Ars Electronica, Linz 2021 - AI & Music, S+T+ARTS & Sonar Festival, CCCB, Barcelona 2020 - Real Time Constraints, arebyte, London 2019 - Euro(re)visions, Goethe Institut, London 2019 - Higher Resolutions with Hyphen Labs, Tate Modern, London 2019 - Open Fest with Sky Arts, Barbican, London 2018 - Digital Design Weekend, V&A, London 2018 - FAKE, Science Gallery, Dublin 2017 - Ars Electronica, Linz 2017 - Entangled: Quantum Computer Art, Royal College of Art, London 2017 - Humans Need Not Apply, Science Gallery, Dublin == Awards and honours == Her awards include: 2022 - Lumen Prize, BCS Immersive Environment Award (for Ent-) 2022 - Mozilla Foundation Creative Media Award, USA 2022 - nominated for the S+T+ARTS prize 2021 - Adaptation Award, Artquest, London 2021 - British Council Amplify Collaboration Award 2018 - Arts Council England, National Lottery Project Grant 2018 - HeK Basel Net Based Art Award (shortlisted for Tinderbot)

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  • India AI Impact Summit 2026

    India AI Impact Summit 2026

    The India AI Impact Summit 2026 (also abbreviated as the AI Impact Summit) was an international summit on artificial intelligence held at Bharat Mandapam, New Delhi, India, from 16 to 21 February 2026. It is the fourth in a series of global AI summits following the Bletchley Park AI Safety Summit in 2023, the AI Seoul Summit in 2024, and the AI Action Summit in Paris in 2025. Organised under the IndiaAI Mission by the Ministry of Electronics and Information Technology, it is the first summit in the series to be hosted by a Global South nation. This series of AI summits will continue with the AI Summit in Geneva to be hosted by Switzerland in 2027. The summit was inaugurated by Prime Minister Narendra Modi on 19 February 2026. The opening ceremony was also addressed by French President Emmanuel Macron and United Nations Secretary-General António Guterres. The summit was attended by over 20 heads of state and a delegation of global technology leaders including Sundar Pichai (Google), Sam Altman (OpenAI), and Demis Hassabis (DeepMind). The event faced criticism for organisational issues, misrepresentation of non-Indian products as Indian, and a perceived focus on trade fair activities over substantive governance. == Background == The AI Impact Summit was an international summit on artificial intelligence (AI) held in New Delhi from 16 to 20 February 2026. It followed the AI Action Summit in Paris in February 2025, the AI Seoul Summit in 2024 and the Bletchley Park AI Safety Summit in 2023. According to Crowell & Moring, the changing summit titles seemed to reflect a broader shift in focus away from AI safety and governance toward practical impact, implementation, and measurable outcomes. Ahead of the summit, an international panel of experts published the second International AI Safety Report. The summit was structured around three foundational pillars, termed "Sutras": People, Planet, and Progress. Seven thematic working groups were established to deliver outcomes across these pillars, covering AI for economic growth and social good; democratising AI resources; inclusion for social empowerment; safe and trusted AI; human capital; science; and resilience, innovation, and efficiency. == Programme == The summit ran over five days, later extended to six following overwhelming public response. Originally scheduled to conclude on 20 February, the event was extended to 21 February with expanded evening hours for the exhibition. === India AI Impact Expo === The India AI Impact Expo, inaugurated by Prime Minister Modi on 16 February, featured over 300 exhibitors from 30 countries across more than 10 thematic pavilions. Pavilions were organised across thematic zones aligned with the summit's three pillars, showcasing AI applications in healthcare, agriculture, education, and sustainable industry. === Leaders' Plenary and CEO Roundtable === The Leaders' Plenary on 19 February brought together heads of state, ministers, and representatives from multilateral institutions to outline national and global priorities on AI governance, infrastructure, and international cooperation. A CEO Roundtable, held the same evening, convened senior executives from global technology and industry firms with government leaders to discuss investment, research collaboration, and deployment of AI systems. === Research Symposium === A Research Symposium on AI and its Impact was held on 18 February, with the IIIT Hyderabad as knowledge partner. Discussions covered sovereign AI infrastructure, global adoption challenges, research breakthroughs, and policy priorities. == Participants == The summit drew delegations from over 100 countries, including more than 20 heads of state and 60 ministers. Notable attendees from the technology industry included Sundar Pichai (Google), Sam Altman (OpenAI), Dario Amodei (Anthropic), Demis Hassabis (Google DeepMind), and Mukesh Ambani (Reliance Industries). Representatives from multilateral institutions included Sangbu Kim of the World Bank. == Announcements and outcomes == === Indian AI models === Several Indian AI models and products were unveiled during the summit. Sarvam AI, an Indian AI laboratory, launched a new generation of large language models, including 30-billion and 105-billion parameter models using a mixture of experts architecture, as well as text-to-speech, speech-to-text, and vision models. Sarvam also introduced the Kaze smartglasses, described as the company's first hardware product, which Prime Minister Modi tested at the expo. The government-backed BharatGen Param2 model, a 17-billion parameter model supporting 22 Indian languages with multimodal capabilities, was also launched at the summit. === Infrastructure commitments === Union Minister Ashwini Vaishnaw outlined India's "whole-of-nation" AI strategy, describing plans to build a "frugal, sovereign and scalable" AI ecosystem. The government announced plans to add more than 20,000 GPUs to India's existing base of 38,000 under the IndiaAI Compute Portal. Microsoft announced at the summit that it was on track to invest US$50 billion by the end of the decade to bring AI to lower-income countries. Goa reaffirmed its commitment to artificial intelligence at the India AI Impact Summit 2026. === Guinness World Record === During the summit, India set a Guinness World Record for the most pledges received for an AI responsibility campaign in 24 hours, with 250,946 valid pledges collected between 16 and 17 February 2026. The campaign, conducted in partnership with Intel India as part of the IndiaAI Mission, exceeded its initial target of 5,000 pledges. == Controversies and criticisms == === Galgotias University incident === On 18 February, Galgotias University faced widespread criticism after a representative presented a robot dog at the university's exhibition pavilion as an indigenous development. Social media users identified the robot as the Unitree Go2, a commercially available product manufactured by Chinese company Unitree Robotics. IT Secretary S. Krishnan stated that the government did not want exhibitors to showcase items that were not their own, and the university was directed to vacate its stall. Galgotias University issued an apology, stating that the representative had been "ill-informed" and was not authorised to speak to the press. The incident drew political reactions, with the Indian National Congress using it to criticise the government. The controversy was amplified after Union IT Minister Ashwini Vaishnaw had earlier shared a video clip of the robot on social media, which was subsequently deleted. === Organisational issues === On day 1 of the Summit, Dhananjay Yadav, a Bengaluru-based entrepreneur had alleged that his product was stolen in the Summit. He called it as a pain for the people in an X post. He further wrote, "Think about this: We paid for flights, accommodation, logistics and even the booth. Only to see our wearables disappear inside a high-security zone". Later, the stolen devices were recovered by The Delhi Police. Bloomberg reported that delegates were left stranded without food or water during a security lockdown ahead of the Prime Minister's visit on 19 February. The summit venue was closed to the public on 19 February for the Prime Minister's visit, leading to criticism from attendees who had registered for that day. === Protests by the Indian Youth Congress (IYC) === On 20 February, some members of the Indian Youth Congress (IYC) carried out protests inside the venue with slogans such as "PM is compromised" and the criticism of the recent trade deal between India and the US. 4 of these members were sent to police custody by the court on 22 February. While Bharatiya Janta Party condemned these protests, with its spokesperson Shehzad Poonawalla saying, "From being anti-BJP, you have gone to being anti-national? If you have a problem with the BJP, then protest at the BJP office, Jantar Mantar, or outside the PM's office. But the people of the country and their alliance partners condemn them for their attempt to defame India in front of the entire world at the AI Summit." Congress leader Harish Rawat defended the protests, saying "it's also a fact that AI might become a tool in the hands of a few individuals… It's the opposition's job to warn against that… It's not the first time such international events have been opposed. I know how the BJP protested during the Commonwealth Games… To say that such opposition has happened for the first time is not correct. The BJP has been doing this while in the opposition." These protestors were granted bail by the Delhi high court on 2 March. == Reception and analysis == Bloomberg News reported that Prime Minister Modi used the summit to assert India's global AI ambitions following a challenging year in foreign policy. TechPolicy.Press published several critical analyses of the summit. One article argued that the summit's structure granted "multinational corporations parity with sovereign governments

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  • Aporia (company)

    Aporia (company)

    Aporia is a machine learning observability platform based in Tel Aviv, Israel. The company has a US office located in San Jose, California. Aporia has developed software for monitoring and controlling undetected defects and failures used by other companies to detect and report anomalies, and warn in the early stages of faults. == History == Aporia was founded in 2019 by Liran Hason and Alon Gubkin. In April 2021, the company raised a $5 million seed round for its monitoring platform for ML models. In February 2022, the company closed a Series A round of $25 million for its ML observability platform. Aporia was named by Forbes as the Next Billion-Dollar Company in June 2022. In November, the company partnered with ClearML, an MLOPs platform, to improve ML pipeline optimization. In January 2023, Aporia launched Direct Data Connectors, a novel technology allowing organizations to monitor their ML models in minutes (previously the process of integrating ML monitoring into a customer’s cloud environment took weeks or more.) DDC (Direct Data Connectors) enables users to connect Aporia to their preferred data source and monitor all of their data at once, without data sampling or data duplication (which is a huge security risk for major organizations. In April 2023, Aporia announced the company partnered with Amazon Web Services (AWS) to provide more reliable ML observability to AWS consumers by deploying Aporia's architecture to their AWS environment, this will allow customers to monitor their models in production regardless of platform.

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  • The Last Question

    The Last Question

    "The Last Question" is a science fiction short story by American writer Isaac Asimov. It first appeared in the November 1956 issue of Science Fiction Quarterly; and in the anthologies in the collections Nine Tomorrows (1959), The Best of Isaac Asimov (1973), Robot Dreams (1986), The Best Science Fiction of Isaac Asimov (1986), the retrospective Opus 100 (1969), and Isaac Asimov: The Complete Stories, Vol. 1 (1990). While he also considered it one of his best works, "The Last Question" was Asimov's favorite short story of his own authorship, and is one of a loosely connected series of stories concerning a fictional computer called Multivac. Through successive generations, humanity questions Multivac on the subject of entropy. The story blends science fiction, theology, and philosophy. It has been recognized as a counterpoint to Fredric Brown's short short story "Answer", published two years earlier. == History == In conceiving Multivac, Asimov was extrapolating the trend towards centralization that characterized computation technology planning in the 1950s to an ultimate centrally managed global computer. After seeing a planetarium adaptation of his work, Asimov "privately" concluded that the story was his best science fiction yet written. He placed it just higher than "The Ugly Little Boy" (September 1958) and "The Bicentennial Man" (1976). The story asks the question of humanity's fate, and human existence as a whole, highlighting Asimov's focus on important aspects of our future like population growth and environmental issues. "The Last Question" ranks with "Nightfall" (1941) as one of Asimov's best-known and most acclaimed short stories. He wrote in 1973 that he appreciated how easy the story was to write after he had the idea. He was so often approached by fans who remembered the story but not the title, that in one instance he gave the answer, correctly, before the fan had even described the story. == Plot summary == By the year 2061, Multivac, a self-adjusting and self-correcting computer, has allowed mankind to reach beyond the planetary confines of Earth and harness solar energy. Two technicians, Adell and Lupov, celebrate Multivac's role in this development. Over drinks, they discuss that the sun will expire due to the second law of thermodynamics, which states that entropy inevitably increases. When Adell asks Multivac whether this can be reversed, the computer responds that it has insufficient data to answer. In several episodes over ten trillion years, increasingly advanced humans pose the same question to the computers of their time. Each time the computer gives the same response. At the heat death of the universe, the last disembodied consciousness of Man asks the question a final time of a computer that resides in hyperspace before merging with it. After collecting the last data from the dead universe, the computer continues to process it alone and finds an answer to the last question. Having no one to tell it to, it proceeds to demonstrate by saying "LET THERE BE LIGHT!" == Themes == === Philosophy === Although science and religion are frequently presented as having an oppositional relationship, "The Last Question" explores some biblical contexts ("Let there be light"). In Asimov's story, aspects like the great meaning of existence are culminated through both technology and human knowledge. The evolution from Multivac to AC also emulates a sort of cycle of existence. === Dystopian happy ending === Multivac's purpose was conceptualized with a desire for knowledge, promoting the idea that more knowledge will lead to a better and more fruitful future for humanity. However, the computer's answers regarding the future suggest an inevitable exhaustion of the Sun, and this thirst for knowledge becomes an obsession with the future. The story's end displays a dichotomy between annihilation and peace. == Dramatic adaptations == === Planetarium shows === "The Last Question" was first adapted for the Abrams Planetarium at Michigan State University (in 1966), featuring the voice of Leonard Nimoy, as Asimov wrote in his autobiography In Joy Still Felt (1980). It was adapted for the Strasenburgh Planetarium in Rochester, New York (in 1969), under the direction of Ian C. McLennan. It was adapted for the Edmonton Space Sciences Centre in Edmonton, Alberta (early 1970s), under the direction of John Hault. It was adapted for the Gates Planetarium at the Denver Museum of Natural History in 1973 under the direction of Mark B. Peterson It subsequently played at the: Fels Planetarium of the Franklin Institute in Philadelphia in 1973 Planetarium of the Reading School District in Reading, Pennsylvania in 1974 Buhl Planetarium, Pittsburgh in 1974 The Space Transit Planetarium of the Museum of Science in Miami during 1977 Vanderbilt Planetarium in Centerport New York, in 1978, read by singer-songwriter and Long Island resident Harry Chapin. Hansen Planetarium in Salt Lake City, Utah (in 1980 and 1989) A reading of the story was played on BBC Radio 7 in 2008 and 2009. Gates Planetarium in Denver, Colorado (in early 2020) In 1989 Asimov updated the star show adaptation to add in quasars and black holes. The story was adapted as a comic book by Don Thompson and drawn by John Estes in the third issue of ORBiT.

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  • Trevor Paglen

    Trevor Paglen

    Trevor Paglen (born 1974) is an American artist, geographer, and author whose work covers mass surveillance and data collection. In 2016, Paglen won the Deutsche Börse Photography Foundation Prize and he has also won The Cultural Award from the German Society for Photography. In 2017, he was a recipient of a MacArthur Fellowship. On March 17, 2026, Paglen was awarded the 2026 LG Guggenheim Award (a collaboration between LG and Guggenheim New York). == Early life and education == Paglen earned a B.A. degree in religious studies in 1998 from the University of California at Berkeley, a M.F.A. degree in 2002 from the School of the Art Institute of Chicago, and a Ph.D. in Geography in 2008 from the University of California at Berkeley. While at UC Berkeley, Paglen lived in the Berkeley Student Cooperative, residing in Chateau, Fenwick, and Rochdale co-ops. == Work == Sean O'Hagan, writing in The Guardian in 2015, said that Paglen, whose "ongoing grand project [is] the murky world of global state surveillance and the ethics of drone warfare", "is one of the most conceptually adventurous political artists working today, and has collaborated with scientists and human rights activists on his always ambitious multimedia projects." His visual work such as his "Limit Telephotography" and "The Other Night Sky" series have received widespread attention for both his technical innovations and for his conceptual project that involves simultaneously making and negating documentary-style truth-claims. Paglen’s work relies on contemporary technology in two meaningful ways. Firstly, the views he photographs would be impossible to shoot without media tech, that includes the cameras, the microscopes, and even helicopters. But interestingly enough, the shots would not be possible if not for the existence of the subject. The contrasts between secrecy and revelation, evidence and abstraction distinguish Paglen's work. With that the artist presents not so much "evidence" as admonitions to awareness. He was an Eyebeam Commissioned Artist in 2007. In 2008 the Berkeley Art Museum devoted a comprehensive solo exhibition to his work. In the next year, Paglen took part in the Istanbul Biennial, and in 2010 he exhibited at the Vienna Secession. Autonomy Cube was a project by Paglen and Jacob Appelbaum that placed relays for the anonymous communication network Tor in traditional art museums. He contributed to the Oscar-winning documentary film Citizenfour (2014), directed by Laura Poitras. Paglen features in the nerd-culture documentary Traceroute (2016). Orbital Reflector was a reflective, mylar sculpture by Paglen intended to be the first "purely artistic" object in space. The temporary satellite, containing an inflatable mylar balloon with reflective surface, launched into space 3 December 2018. A mid-career survey in 2018–2019, Trevor Paglen: Sites Unseen, was a traveling exhibition shown at the Smithsonian American Art Museum in Washington DC and the Museum of Contemporary Art San Diego. In September 2020, Pace Gallery in London held an exhibition of Paglen's work, exploring "the weird, partial ways computers look back at us". His work is included in the permanent collections of the San Francisco Museum of Modern Art, the Columbus Museum of Art, and the Metropolitan Museum. === Experimental Geography === Paglen is credited with coining the term "Experimental Geography" to describe practices coupling experimental cultural production and art-making with ideas from critical human geography about the production of space, materialism, and praxis. The 2009 book Experimental Geography: Radical Approaches to Landscape, Cartography, and Urbanism is largely inspired by Paglen's work. == Publications == Paglen has published a number of books. Torture Taxi (2006) (co-authored with investigative journalist A. C. Thompson) was the first book to comprehensively describe the CIA's extraordinary rendition program. I Could Tell You But Then You Would Have to be Destroyed by Me (2007), is a look at the world of black projects through unit patches and memorabilia created for top-secret programs. Blank Spots on the Map: The Dark Geography of the Pentagon's Secret World (2009) is a broader look at secrecy in the United States. The Last Pictures (2012) is a collection of 100 images to be placed on permanent media and launched into space on EchoStar XVI, as a repository available for future civilizations (alien or human) to find. === Publications by Paglen === I Could Tell You But Then You Would Have to be Destroyed by Me. Brooklyn, NY: Melville House, 2007. ISBN 1-933633-32-8. Blank Spots on the Map: The Dark Geography of the Pentagon's Secret World. New York: Dutton, 2009. ISBN 9781101011492. Invisible: Covert Operations and Classified Landscapes, Photographs by Trevor Paglen. New York: Aperture, 2010. ISBN 9781597111300. With an essay by Rebecca Solnit. The Last Pictures. Oakland, CA: University of California, 2012. ISBN 9780520275003. Trevor Paglen. London: Phaidon, 2018. ISBN 0714873446. With essays by Laren Cornell, Julia Bryan-Wilson, Omar Kholeif. === Publications co-authored === Torture Taxi. Co-authored with A. C. Thompson. Brooklyn, NY: Melville House Publishing, 2006. ISBN 1-933633-09-3. Icon, 2007. ISBN 9781840468304. === Publications with contributions by Paglen === Experimental Geography: Radical Approaches to Landscape, Cartography, and Urbanism. Brooklyn, NY: Melville House, 2009. ISBN 978-0091636586. Edited by Nato Thompson. With essays by Paglen, Thompson, and Jeffrey Kastner. Trevor Paglen and Jacob Appelbaum – Autonomy Cube. Revolver, 2016. ISBN 978-3957633026. Essays by Luke Skrebowski and Keller Easterling on Autonomy Cube, a piece of sculpture by Paglen and Jacob Appelbaum. In English and German. == Exhibitions == Bellwether Gallery, New York, November–December 2006 The Other Night Sky, Berkeley Art Museum, 2008 A Compendium of Secrets, Cologne Still Revolution: Suspended in Time, Museum of Contemporary Canadian Art, Toronto, May–June 2009. Group exhibition with Paglen, Barbara Astman, Walead Beshty, Mat Collishaw, Stan Douglas, Idris Khan, Martha Rosler, and Mikhael Subotzky A Hidden Landscape, Aksioma, Ljubljana, Slowenia Geographies of Seeing, Lighthouse, Brighton, England, October–November 2012 The Last Pictures, New York, 2012–13 Trevor Paglen, Altman Siegel gallery, San Francisco, CA, March–May 2015 The Octopus, Frankfurter Kunstverein, Frankfurt am Main, 2015 Autonomy Cube, Edith-Russ-Haus, Oldenburg, Germany, October 2015 – January 2016. Sculpture by Paglen and Jacob Appelbaum. Deutsche Börse Photography Foundation Prize 2016, The Photographers' Gallery, London, April–July 2016. Deutsche Börse Photography Prize shortlist with Paglen, Erik Kessels, Laura El-Tantawy, and Tobias Zielony. Radical Landscapes, di Rosa, Napa, February–April 2016 L’Image volée, Americas II, Bahamas Internet Cable System (BICS-1) and Globenet, Fondazione Prada, Milan (group exhibition), 2016 A Study of Invisible Images, Metro Pictures, New York, September–October 2017 == Awards == 2014: Pioneer Award from the Electronic Frontier Foundation. 2015: The Cultural Award from the German Society for Photography (DGPh) 2015: Academy Award as cameraman and director for the documentary film Citzenfour. 2016: Deutsche Börse Photography Foundation Prize 2017: MacArthur Fellowship, John D. and Catherine T. MacArthur Foundation, Chicago, IL 2018: Nam June Paik Art Center Prize == Films about Paglen == Unseen Skies (2021) == Works ==

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  • Pommerman Challenge

    Pommerman Challenge

    The Pommerman Challenge is a multi-agent game to test autonomous artificial intelligence systems. == Game structure == Two-agent team compete against each other on an 11 x 11 board. Each agent can observe only part of the board, and the agents cannot communicate. The goal is to knock down the opponents. Agents place explosives to destroy walls and collect power-ups that appear from those walls, while avoiding death. Game objects can move unpredictably or be moved by an agent. == Play == The game involves real-time decision making. Agents must choose moves in about .1 seconds. == Algorithms == The real-time requirement limits the use of compute-heavy techniques such as Monte Carlo tree search. The branching factor at each move can be as large as 1,296, because all four agents act in each step, choosing among six possibilities. The agents choose by accounting for explosions, which have lifetimes of 10 steps. Explosions derail tree search techniques, as searches with less than 10 levels ignore explosions while deeper searches consider too many choices (given the branching factor). A hybrid approach uses a limited-depth tree search followed by exploring a deterministic/pessimistic scenario. Limiting the depth keeps the search tree small. The deterministic approach can predict far in the future, by omitting branching. "Good" actions are often those that perform well under pessimistic scenarios, particularly if safety is important. Identifying the worst sequence of positions for an object can suggest where to move it. After generating pessimistic scenarios, the agent quantifies the survivability of each move, notionally the number of positions in which the agent can then remain safely (without encountering other agents). == Competitions == 3 competitions were organized with slightly changing rules during 2018–2019. === Online - FFA === This round was a warm-up online event, where each competitor controlled only one agent. Results: 1st: Agent47Agent by Yichen Gong 2nd: aiKiller by Márton Görög === NeurIPS 2018 - Team === The first Pommerman competition with in-person finals. Results: 1st: hakozakijunctions by Toshihiro Takahashi 2nd: eisenach by Márton Görög 3rd: dypm by Takayuki Osogami The 3 best performing solutions used online tree search. === NeurIPS 2019 - Team Radio === The second competition with in-person finals improved communication between teammate agents. Results: 1st: Márton Görög 2nd: Paul Jasek 3rd: Yifan Zhang

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  • Report generator

    Report generator

    A report generator is a computer program whose purpose is to take data from a source such as a database, XML stream or a spreadsheet, and use it to produce a document in a format which satisfies a particular human readership. Report generation functionality is almost always present in database systems, where the source of the data is the database itself. It can also be argued that report generation is part of the purpose of a spreadsheet. Standalone report generators may work with multiple data sources and export reports to different document formats. Information systems theory specifies that information delivered to a target human reader must be timely, accurate and relevant. Report generation software targets the final requirement by making sure that the information delivered is presented in the way most readily understood by the target reader. == History == An early report writer was part of NOMAD developed in the 1970s. The evolution of reporting software has a rich history dating back to the mid-20th century, driven by the increasing need for businesses to efficiently analyze and present data. Initially, manual extraction and tabulation were commonplace, but the advent of computers in the 1960s marked a transformative phase with the emergence of basic reporting tools. The 1980s saw the widespread adoption of database management systems, laying the groundwork for more sophisticated reporting capabilities. Notable dedicated reporting software, such as Crystal Reports and BusinessObjects, gained prominence in the 1990s amidst the growing demand for business intelligence. The 21st century witnessed a paradigm shift towards web-based reporting solutions and the rise of self-service BI tools, empowering users to create reports independently. Presently, reporting software continues to evolve with a focus on data visualization, integration of artificial intelligence, and the imperative for real-time analytics in decision-making.

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  • Cruel World of Dreams and Fears

    Cruel World of Dreams and Fears

    Cruel World of Dreams and Fears is the debut album from Ukrainian-born Czech black metal artist Draugveil, released independently on 13 June 2025. The album became notable among metal fans due to its cover, featuring Draugveil in a suit of armour and corpse paint, and lying in a field of red roses. The cover was the subject of parodying internet memes, as well as accusations of using artificial intelligence (AI) to make it. These claims were later expanded to suggest that AI was used to make the album's music. == Memes and AI accusations == Upon the album being released on YouTube on the channel Black Metal Promotion, the album attracted attention due to its cover, depicting Draugveil lying in a field of roses, dressed in armour, wearing corpse paint and having a sword stuck in the ground. Some compared it to covers where other artists are lying on the ground, such as Michael Jackson's Thriller, Luther Vandross's Give Me the Reason, and the UK cover of Lionel Richie's You Are. Critics of the album, however, suggested that AI was used to make the cover. This was partly due to suggestions that the rose stems in the picture come out from the ground in an unrealistic way. This later resulted in claims from some fans that AI was also used to produce the music, and later the lyrics and vocals. These claims began on a Facebook page entitled "AI Generated Nonsense", which was later deleted. No definitive evidence, however, was produced to back these claims. Derek McArthur, a journalist for Glasgow-based newspaper The Herald, wrote: "The music is in line with what one would expect from a one-man black metal project in the vein of Judas Iscariot and Burzum, but then if AI was asked to create music in a black metal style, that is probably what it would decide to generically produce and spit out." Draugveil's reaction to the claims was: "Let people decide." The result of the claims of AI has led to some writers to claim that artists in the future will have to prove they are human to be taken seriously, and that members of the public will be increasing doubt as to whether creative works are produced by either humans or AI. == Track listing ==

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  • Residuated Boolean algebra

    Residuated Boolean algebra

    In mathematics, a residuated Boolean algebra is a residuated lattice whose lattice structure is that of a Boolean algebra. Examples include Boolean algebras with the monoid taken to be conjunction, the set of all formal languages over a given alphabet Σ {\displaystyle \Sigma } under concatenation, the set of all binary relations on a given set X {\displaystyle X} under relational composition, and more generally the power set of any equivalence relation, again under relational composition. The original application was to relation algebras as a finitely axiomatized generalization of the binary relation example, but there exist interesting examples of residuated Boolean algebras that are not relation algebras, such as the language example. == Definition == A residuated Boolean algebra is an algebraic structure ( L , ∧ , ∨ , ¬ , 0 , 1 , ∙ , I , / , ∖ ) {\displaystyle (L,\wedge ,\vee ,\neg ,0,1,\bullet ,\mathbf {I} ,/,\backslash )} such that An equivalent signature better suited to the relation algebra application is ( L , ∧ , ∨ , ¬ , 0 , 1 , ∙ , I , ▹ , ◃ ) {\displaystyle (L,\wedge ,\vee ,\neg ,0,1,\bullet ,\mathbf {I} ,\triangleright ,\triangleleft )} where the unary operations x ∖ {\displaystyle x\backslash } and x ▹ {\displaystyle x\triangleright } are intertranslatable in the manner of De Morgan's laws via x ∖ y = ¬ ( x ▹ ¬ y ) {\displaystyle x\backslash y=\neg (x\triangleright \neg y)} , x ▹ y = ¬ ( x ∖ ¬ y ) {\displaystyle x\triangleright y=\neg (x\backslash \neg y)} , and dually / y {\displaystyle /y} and ◃ y {\displaystyle \triangleleft y} as x / y = ¬ ( ¬ x ◃ y ) {\displaystyle x/y=\neg (\neg x\triangleleft y)} , x ◃ y = ¬ ( ¬ x / y ) {\displaystyle x\triangleleft y=\neg (\neg x/y)} , with the residuation axioms in the residuated lattice article reorganized accordingly (replacing z {\displaystyle z} by ¬ z {\displaystyle \neg z} ) to read ( x ▹ z ) ∧ y = 0 ⇔ ( x ∙ y ) ∧ z = 0 ⇔ ( z ◃ y ) ∧ x = 0 {\displaystyle (x\triangleright z)\wedge y=0\ \Leftrightarrow \ (x\bullet y)\wedge z=0\ \Leftrightarrow \ (z\triangleleft y)\wedge x=0} This De Morgan dual reformulation is motivated and discussed in more detail in the section below on conjugacy. Since residuated lattices and Boolean algebras are each definable with finitely many equations, so are residuated Boolean algebras, whence they form a finitely axiomatizable variety. == Examples == Any Boolean algebra, with the monoid multiplication ∙ {\displaystyle \bullet } taken to be conjunction and both residuals taken to be material implication x → y {\displaystyle x\to y} . Of the remaining 15 binary Boolean operations that might be considered in place of conjunction for the monoid multiplication, only five meet the monotonicity requirement, namely 0 , 1 , x , y {\displaystyle 0,1,x,y} and x ∨ y {\displaystyle x\vee y} . Setting y = z = 0 {\displaystyle y=z=0} in the residuation axiom y ≤ x ∖ z ⇔ x ∙ y ≤ z {\displaystyle y\leq x\backslash z\ \Leftrightarrow \ x\bullet y\leq z} , we have 0 ≤ x ∖ 0 ⇔ x ∙ 0 ≤ 0 {\displaystyle 0\leq x\backslash 0\ \Leftrightarrow \ x\bullet 0\leq 0} , which is falsified by taking x = 1 {\displaystyle x=1} when x ∙ y = 1 {\displaystyle x\bullet y=1} , x {\displaystyle x} , or x ∨ y {\displaystyle x\vee y} . The dual argument for z / y {\displaystyle z/y} rules out x ∙ y = y {\displaystyle x\bullet y=y} . This just leaves x ∙ y = 0 {\displaystyle x\bullet y=0} (a constant binary operation independent of x {\displaystyle x} and y {\displaystyle y} ), which satisfies almost all the axioms when the residuals are both taken to be the constant operation x / y = x ∖ y = 1 {\displaystyle x/y=x\backslash y=1} . The axiom it fails is x ∙ I = x = I ∙ x {\displaystyle x\bullet \mathbf {I} =x=\mathbf {I} \bullet x} , for want of a suitable value for I {\displaystyle \mathbf {I} } . Hence conjunction is the only binary Boolean operation making the monoid multiplication that of a residuated Boolean algebra. The power set 2 X 2 {\displaystyle 2^{X^{2}}} made a Boolean algebra as usual with ∩ {\displaystyle \cap } , ∪ {\displaystyle \cup } and complement relative to X 2 {\displaystyle X^{2}} , and made a monoid with relational composition. The monoid unit I {\displaystyle \mathbf {I} } is the identity relation { ( x , x ) | x ∈ X } {\displaystyle \{(x,x)|x\in X\}} . The right residual R ∖ S {\displaystyle R\backslash S} is defined by x ( R ∖ S ) y ⇔ ∀ z ∈ X , z R x ⇒ z S y {\displaystyle x(R\backslash S)y\ \Leftrightarrow \ \forall z\in X,zRx\Rightarrow zSy} . Dually the left residual S / R {\displaystyle S/R} is defined by y ( S / R ) x ⇔ ∀ z ∈ X , x R z ⇒ y S z {\displaystyle y(S/R)x\ \Leftrightarrow \ \forall z\in X,xRz\Rightarrow ySz} . The power set 2 Σ ∗ {\displaystyle 2^{\Sigma ^{}}} made a Boolean algebra as for Example 2, but with language concatenation for the monoid. Here the set Σ {\displaystyle \Sigma } is used as an alphabet while Σ ∗ {\displaystyle \Sigma ^{}} denotes the set of all finite (including empty) words over that alphabet. The concatenation L M {\displaystyle LM} of languages L {\displaystyle L} and M {\displaystyle M} consists of all words u v {\displaystyle uv} such that u ∈ L {\displaystyle u\in L} and v ∈ M {\displaystyle v\in M} . The monoid unit is the language { ε } {\displaystyle \{\varepsilon \}} consisting of just the empty word ε {\displaystyle \varepsilon } . The right residual M ∖ L {\displaystyle M\backslash L} consists of all words w {\displaystyle w} over Σ {\displaystyle \Sigma } such that M w ⊆ L {\displaystyle Mw\subseteq L} . The left residual L / M {\displaystyle L/M} is the same with w M {\displaystyle wM} in place of M w {\displaystyle Mw} . == Conjugacy == The De Morgan duals ▹ {\displaystyle \triangleright } and ◃ {\displaystyle \triangleleft } of residuation arise as follows. Among residuated lattices, Boolean algebras are special by virtue of having a complementation operation ¬ {\displaystyle \neg } . This permits an alternative expression of the three inequalities y ≤ x ∖ z ⇔ x ∙ y ≤ z ⇔ x ≤ z / y {\displaystyle y\leq x\backslash z\ \Leftrightarrow \ x\bullet y\leq z\ \Leftrightarrow \ x\leq z/y} in the axiomatization of the two residuals in terms of disjointness, via the equivalence x ≤ y ⇔ x ∧ ¬ y = 0 {\displaystyle x\leq y\ \Leftrightarrow \ x\wedge \neg y=0} . Abbreviating x ∧ y = 0 {\displaystyle x\wedge y=0} to x # y {\displaystyle x\#y} as the expression of their disjointness, and substituting ¬ z {\displaystyle \neg z} for z {\displaystyle z} in the axioms, they become with a little Boolean manipulation ¬ ( x ∖ ¬ z ) # y ⇔ x ∙ y # z ⇔ ¬ ( ¬ z / y ) # x {\displaystyle \neg (x\backslash \neg z)\#y\ \Leftrightarrow \ x\bullet y\#z\ \Leftrightarrow \ \neg (\neg z/y)\#x} Now ¬ ( x ∖ ¬ z ) {\displaystyle \neg (x\backslash \neg z)} is reminiscent of De Morgan duality, suggesting that x ∖ {\displaystyle x\backslash } be thought of as a unary operation f {\displaystyle f} , defined by f ( y ) = x ∖ y {\displaystyle f(y)=x\backslash y} , that has a De Morgan dual ¬ f ( ¬ y ) {\displaystyle \neg f(\neg y)} , analogous to ∀ x ϕ ( x ) = ¬ ∃ x ¬ ϕ ( x ) {\displaystyle \forall x\phi (x)=\neg \exists x\neg \phi (x)} . Denoting this dual operation as x ▹ {\displaystyle x\triangleright } , we define x ▹ z {\displaystyle x\triangleright z} as ¬ x ∖ ¬ z {\displaystyle \neg x\backslash \neg z} . Similarly we define another operation z ◃ y {\displaystyle z\triangleleft y} as ¬ ( ¬ z / y ) {\displaystyle \neg (\neg z/y)} . By analogy with x ∖ {\displaystyle x\backslash } as the residual operation associated with the operation x ∙ {\displaystyle x\bullet } , we refer to x ▹ {\displaystyle x\triangleright } as the conjugate operation, or simply conjugate, of x ∙ {\displaystyle x\bullet } . Likewise ◃ y {\displaystyle \triangleleft y} is the conjugate of ∙ y {\displaystyle \bullet y} . Unlike residuals, conjugacy is an equivalence relation between operations: if f {\displaystyle f} is the conjugate of g {\displaystyle g} then g {\displaystyle g} is also the conjugate of f {\displaystyle f} , i.e. the conjugate of the conjugate of f {\displaystyle f} is f {\displaystyle f} . Another advantage of conjugacy is that it becomes unnecessary to speak of right and left conjugates, that distinction now being inherited from the difference between x ∙ {\displaystyle x\bullet } and ∙ x {\displaystyle \bullet x} , which have as their respective conjugates x ▹ {\displaystyle x\triangleright } and ◃ x {\displaystyle \triangleleft x} . (But this advantage accrues also to residuals when x ∖ {\displaystyle x\backslash } is taken to be the residual operation to x ∙ {\displaystyle x\bullet } .) All this yields (along with the Boolean algebra and monoid axioms) the following equivalent axiomatization of a residuated Boolean algebra. y # x ▹ z ⇔ x ∙ y # z ⇔ x # z ◃ y {\displaystyle y\#x\triangleright z\ \Leftrightarrow \ x\bullet y\#z\ \Leftrightarrow \ x\#z\triangleleft y} With this signature it remains the case that this axiomatization can be expressed as

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  • Lymphater's Formula

    Lymphater's Formula

    "Lymphater's Formula" (Polish: "Formula Lymphatera") is a 1961 science fiction short story by Polish writer Stanisław Lem. It is a story of a "mad scientist", mathematician Ammon Lymphater, who invents an artificial intelligence, and then he realizes that it is capable of rendering the humankind obsolete. It was first published in the 1961 collection Księga robotów (Book of Robots) with the pre-annotation "from the memoirs of Ijon Tichy". The story was never republished with this pre-annotation, and nothing in the novel gives any indication at Ijon Tichy. Piotr Krywak tried to figure out possible explanations for this, apart from a typographical error. == Plot == Ammon Lymphater became interested in the emerging science of cybernetics and information theory, and started studying the works of an animal brain, the ant's brain in particular. He took note that the inherited knowledge is an evolutionary advantage somehow not exploited in full by the evolution. Eventually he came to a conclusion that only by pure biological restrictions that adaptive abilities of insects were stopped in their tracks by the evolution. He went on further wondering whether the ants have an ability to apriori knowledge, i.e., knowledge neither inherited nor learned. He decided to consult a famous myrmecologist, who told him about a rare ant species Acanthis Rubra Willinsoniana with an exceptionally high adaptability. Eventually Lymphater devised and constructed "It" capable of instant precognition of everything within "Its" rapidly expanding range of perception. From "It" Lymphater learns that the humanity is not the "crown of evolution", but rather evolution's tool to create "It", because the evolution could not create "It" directly (confirming Lymphater's reasoning about ants). Realizing that the Superentity "It" renders the human civilization redundant and obsolete, Lymphater destroys "It". "It" already knew Lymphater's intentions, but was not worried, knowing that sooner or later someone else will create "It" again and again. "It" was only the first variant of Lymphater's formula and the second variant is possible. Lyphater wonders whether the second one would be capable to create the third stage of the evolution which would amount to an artificial God. == Publication history == It was translated in Russian (as "Формула Лимфатера") in 1963, in Hungarian (as "Lymphater utolsó képlete") in 1966, and in Bulgarian (as "Формулата на Лимфатер" by Георги Димитров Георгиев) in 1969. In 1973 an audiobook was released in German (as "Die lymphatersche Formel"), narrated by Martin Held. It was also republished (and translated) in some other collections of Lem's short stories.

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  • Celia (virtual assistant)

    Celia (virtual assistant)

    Celia is an artificially intelligent virtual assistant developed by Huawei for their latest HarmonyOS and Android-based EMUI smartphones that lack Google Services and a Google Assistant. The assistant can perform day-to-day tasks, which include making a phone call, setting a reminder and checking the weather. It was unveiled on 7 April 2020 and got publicly released on 27 April 2020 via an OTA update solely to selected devices that can update their software to EMUI 10.1. Huawei had initially referred to the new assistant in late 2019 by having announced that there would be an English version of their already 2018 Chinese speaker assistant—Xiaoyi—to be released into the European markets. Due to the on-going China–United States trade war, the company's newly released smartphones were left without any Google services, including the loss of Google Assistant. This subsequently led to the development and release of Celia. AI technology is integrated into the software of Celia, which allows it to translate text using a phones camera and to identify everyday objects — similar to that of Google Lens. == Features == Celia has many features that are similar to that of its rivals: the Google Assistant and Siri. It can be triggered by the words, 'Hey Celia' or be summoned by pressing and holding down on the power button. The default search engine for Celia is Bing, but this can be changed in settings. Celia can make calls, check the agenda, send a message, show the weather, set alarms and control home appliances. The assistant also has the ability to integrate itself with the stock apps of the EMUI software and toggle with the device's settings, such as by turning on the flashlight and playing multimedia content, but with the users command. With the AI that is installed in Celia, it can identify food, everyday objects and translate text using the phones camera. In China, Chinese Xiaoyi packs with an LLM model called PanGu-Σ 3.0 AI on HarmonyOS 4.0 major upgrade improvements from Celia, making the assistant smarter and more advanced compared to when it was launched in 2020 on EMUI handsets in China and internationally, surpassing Apple and Google by the being the first in the AI industry, with a dedicated AI system framework of APIs on the latest operating system that evolves to a complete large dedicated AI software stack called Harmony Intelligence of Pangu Embedded variant model and MindSpore AI framework with Neural Network Runtime on OpenHarmony-based HarmonyOS NEXT base system to replace the dual framework system with a single frame HarmonyOS 5.0 version by Q4 2024, first introduced on June 21, 2024, in Developer Beta 1 preview release at HDC 2024. == Availability by country and language == Currently, Celia is available only in German, English, French and Spanish, and has been released in Germany, the UK, France, Spain, Chile, Mexico and Colombia. Huawei has said, that there will be more regions and languages to come. == Compatible devices == Celia only became available with the EMUI 10.1 update that was released in April, which means that a limited number of devices are compatible with it. More devices will be added to the list throughout the coming months as Celia's availability increases. The current list is shown below: === Huawei P series === Huawei P50 (Pro) Huawei P40 (Lite, Pro & Pro+) Huawei P30 (Pro) === Huawei Mate series === Huawei Mate 40 Huawei Mate 30 (Lite, Pro & RS Porche Design) Huawei MatePad Pro Huawei Mate 20 (Pro, 20X 4G, 20X 5G and RS Porche Design) Huawei Mate X & Xs === Huawei Nova series === Huawei Nova 6 (Nova 6 5G & Nova 6 SE) Huawei Nova 5 (Nova 5 Pro, Nova 5i Pro & Nova 5Z) Huawei Nova Y60 === Huawei Enjoy series === Huawei Enjoy 10S == Issues == Technology news website Engadget has noted that when saying, 'Hey Celia', out aloud in the presence of an iPhone, Siri will respond along with Celia; this is apparently because 'Celia' sounds similar to 'Siri'.

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  • Probabilistic database

    Probabilistic database

    Most real databases contain data whose correctness is uncertain. In order to work with such data, there is a need to quantify the integrity of the data. This is achieved by using probabilistic databases. A probabilistic database is an uncertain database in which the possible worlds have associated probabilities. Probabilistic database management systems are currently an active area of research. "While there are currently no commercial probabilistic database systems, several research prototypes exist..." Probabilistic databases distinguish between the logical data model and the physical representation of the data much like relational databases do in the ANSI-SPARC Architecture. In probabilistic databases this is even more crucial since such databases have to represent very large numbers of possible worlds, often exponential in the size of one world (a classical database), succinctly. == Terminology == In a probabilistic database, each tuple is associated with a probability between 0 and 1, with 0 representing that the data is certainly incorrect, and 1 representing that it is certainly correct. === Possible worlds === A probabilistic database could exist in multiple states. For example, if there is uncertainty about the existence of a tuple in the database, then the database could be in two different states with respect to that tuple—the first state contains the tuple, while the second one does not. Similarly, if an attribute can take one of the values x, y or z, then the database can be in three different states with respect to that attribute. Each of these states is called a possible world. Consider the following database: (Here {b3, b3′, b3′′} denotes that the attribute can take any of the values b3, b3′ or b3′′) Assuming that there is uncertainty about the first tuple, certainty about the second tuple, and uncertainty about the value of attribute B in the third tuple. Then the actual state of the database may or may not contain the first tuple (depending on whether it is correct or not). Similarly, the value of the attribute B may be b3, b3′ or b3′′. Consequently, the possible worlds corresponding to the database are as follows: === Types of Uncertainties === There are essentially two kinds of uncertainties that could exist in a probabilistic database, as described in the table below: By assigning values to random variables associated with the data items, different possible worlds can be represented. == History == The first published use of the term "probabilistic database" was probably in the 1987 VLDB conference paper "The theory of probabilistic databases", by Cavallo and Pittarelli. The title (of the 11 page paper) was intended as a bit of a joke, since David Maier's 600 page monograph, The Theory of Relational Databases, would have been familiar at that time to many of the conference participants and readers of the conference proceedings.

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  • SpreeAI

    SpreeAI

    SpreeAI (stylized as SPREEAI) is an American fashion technology company headquartered in Incline Village, Nevada that develops artificial intelligence software for the apparel and retail industries, including photorealistic virtual try-on, AI-powered sizing recommendations, and digital model generation. Founded in 2022 by John Imah and Bob Davidson, the company achieved unicorn status in 2025 following a Series B round led by Davidson Group that valued the company at approximately US$1.5 billion. TechCrunch identified SpreeAI as one of the more than 100 new tech unicorns minted in 2025. Its board of directors includes supermodel Naomi Campbell and hospitality executive Larry Ruvo. == History == SpreeAI was founded in 2022 by John Imah and Bob Davidson with a focus on artificial intelligence applications in fashion retail. By 2024, the company had raised approximately US$60 million in venture funding. In May 2025, SpreeAI announced a Series B round led by Davidson Group; reporting at the time placed the company's valuation at approximately US$1.5 billion, making it one of a small number of fashion-technology companies to reach unicorn status. In January 2026, TechCrunch listed SpreeAI among the more than 100 new tech unicorns minted in 2025. == Technology == SpreeAI develops a suite of artificial intelligence tools for the apparel industry. Its consumer-facing platform allows shoppers to upload a single photograph or select a digital model and then visualize clothing items on that figure with photorealistic rendering, while a complementary sizing engine generates fit recommendations intended to reduce returns. The platform is designed for integration with online retailers so that shoppers can preview garments before purchase. The company has stated that its models were developed in part through research collaborations with the Massachusetts Institute of Technology and Carnegie Mellon University. == Leadership and board == John Imah, a Nigerian-American technology executive who previously held roles at Samsung, Twitch, Meta Platforms, and Snap Inc., is co-founder and chief executive officer. Co-founder Bob Davidson, through Davidson Group, led the company's Series B financing. The company's board of directors includes supermodel Naomi Campbell, who joined in 2024, and Las Vegas hospitality executive Larry Ruvo. == Partnerships == SpreeAI has formed partnerships across both academia and the fashion industry. Council of Fashion Designers of America (CFDA). In 2025, SpreeAI entered a partnership with the CFDA to support American designers and brands with AI-driven tools; the CFDA described SpreeAI as "a fashion technology leader delivering innovative solutions to help designers and brands thrive." Massachusetts Institute of Technology and Carnegie Mellon University. The company has cited ongoing research and talent collaborations with both institutions. Sergio Hudson and Kai Collective. In 2025, SpreeAI made what WWD described as its Met Gala debut through a custom collaboration with designer Sergio Hudson and Nigerian-British label Kai Collective; the collaboration paired Hudson's couture with SpreeAI's virtual try-on platform. == Recognition == In 2025, TechCrunch named SpreeAI among the new tech unicorns of the year. In 2025, SpreeAI was named an honoree in Inc.'s Best in Business awards, and CEO John Imah was included on Inc.'s list of 40 business leaders who "propelled their organizations to success." In 2025, Imah was named to the Observer's AI Power Index, a list of 100 leaders shaping the future of artificial intelligence. In 2025, Imah was included in AfroTech's Future 50, recognizing Black innovators in technology. SpreeAI and Imah have been the subject of profile coverage in The Washington Post, Rolling Stone UK, WWD, Vogue UA, L'Officiel Arabia, GQ South Africa, and Inc..

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