AI Detector In Photos

AI Detector In Photos — independent reviews, comparisons, pricing and step-by-step guides on Aizhi.

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  Anna Becker

  Anna Becker is an Israeli researcher known in the field of artificial intelligence and computer science within the financial field. == Early life and education == Becker was born in Russia and immigrated to Israel at 16 after graduating from a school in Moscow. At 17, she began her studies at Technion – Israel Institute of Technology. During her master's degree in computer science, she taught first-year students of the same course, and at 27, Becker completed her PhD in Computer Science and Artificial Intelligence. == Career == While pursuing her PhD, Becker resolved an NP-complete approximation algorithm that had been unresolved for over twenty years. This made her a recognized scholar in the field. After completing her PhD, she developed an approximation technique by a factor of two. This technique is widely used today in operating systems, database systems, and VLSI chip designs. She then founded and sold Strategy Runner, a fintech software. After this, she founded EndoTech, an algorithmic trading platform based on artificial intelligence and machine learning. EndoTech's trading strategies have been operating in live cryptocurrency markets since 2017. The platform's BTC Alpha strategy has reported an average annual return of 163% on fixed capital over eight years of live operation, with a maximum drawdown of 14% and a trade accuracy rate of approximately 83%. In 2026, EndoTech entered a partnership with Bit1 Exchange to make its BTC Alpha and ETH Alpha copy trading strategies accessible to retail investors with no minimum deposit requirement, through a full-custody model in which user funds remain in their own exchange wallets at all times.As of 2023, Becker is working on Fianchetto Fund, an AI-based investing analysis platform. Becker has also co-authored a book on Bayesian networks, which has been published widely in the field of computer science and artificial intelligence.

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  International Conference on Automated Planning and Scheduling

  The International Conference on Automated Planning and Scheduling (ICAPS) is a leading international academic conference in automated planning and scheduling held annually for researchers and practitioners in planning and scheduling. ICAPS is supported by the National Science Foundation, the journal Artificial Intelligence, and other supporters. == The IPC and PDDL == ICAPS conducts the International Planning Competition (IPC), a competition scheduled every few years that empirically evaluates state-of-the-art planning systems on a collection of benchmark problems. The Planning Domain Definition Language (PDDL) was developed mainly to make the 1998/2000 International Planning Competition possible, and then evolved with each competition. PDDL is an attempt to standardize Artificial Intelligence (AI) planning languages. PDDL was first developed by Drew McDermott and his colleagues in 1998, inspired by STRIPS, ADL, and other sources. == History == The ICAPS conferences began in 2003 as a merge of two bi-annual conferences, the International Conference on Artificial Intelligence Planning and Scheduling (AIPS) and the European Conference on Planning (ECP). == List of events ==

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  AI takeover

  An AI takeover is a theorized future event, often depicted in fiction, in which autonomous artificial intelligence systems acquire the capability to supersede human decisions. This could occur through economic manipulation, infrastructure control, or direct intervention, leading to de facto governance. Scenarios range from gradual economic dominance, as automation supplants the human workforce, up to a sudden or aggressive global takeover by a robot uprising or other forms of rogue AI. Stories of AI takeovers have been popular throughout science fiction. Commentators argue that recent advancements in the field have heightened concern about such scenarios. In public debate, prominent figures such as Stephen Hawking have advocated research into precautionary measures to ensure future superintelligent machines remain under human control. == Types == === Automation of the economy === The traditional consensus among economists has been that technological progress does not cause long-term unemployment. However, recent innovation in the fields of robotics and artificial intelligence has raised worries that human labor will become obsolete, leaving workers in some sectors without employment. Many small and medium-sized firms may also be forced to close if they cannot afford or license the latest robotic and AI technology, and may need to focus on areas or services that cannot easily be replaced for continued viability in the face of such technology. ==== Technologies that may displace workers ==== While these technologies have replaced some traditional workers, they also create new opportunities. Industries that are most susceptible to AI-driven automation include transportation, retail, and the military. AI military technologies, for example, can reduce risk by enabling remote operation. A study in 2024 highlights AI's ability to perform routine and repetitive tasks poses significant risks of job displacement, especially in sectors like manufacturing and administrative support. Author Dave Bond argues that as AI technologies continue to develop and expand, the relationship between humans and robots will change; they will become closely integrated in several aspects of life. AI will likely displace some workers while creating opportunities for new jobs in other sectors, especially in fields where tasks are repeatable. Researchers from Stanford's Digital Economy Lab reported in 2025 that since the widespread adoption of generative AI in late 2022, early-career workers (ages 22–25) in the most AI-exposed occupations have experienced a 13 percent relative decline in employment—even after controlling for firm-level shocks—while overall employment has continued to grow robustly. The study further finds that job losses are concentrated in roles where AI automates routine tasks, whereas occupations that leverage AI to augment human work have seen stable or increasing employment. ==== Computer-integrated manufacturing ==== Computer-integrated manufacturing uses computers to control the production process. This allows individual processes to exchange information with each other and initiate actions. Although manufacturing can be faster and less error-prone through the integration of computers, the main advantage is the ability to create automated manufacturing processes. Computer-integrated manufacturing is used in automotive, aviation, space, and shipbuilding industries. ==== White-collar machines ==== The 21st century has seen a variety of skilled tasks partially taken over by machines, including translation, legal research, and journalism. Care work, entertainment, and other tasks requiring empathy, previously thought safe from automation, are increasingly performed by robots and AI systems. ==== Autonomous cars ==== An autonomous car is a vehicle that is capable of sensing its environment and navigating without human input. Many such vehicles are operational and others are being developed, with legislation rapidly expanding to allow their use. Obstacles to widespread adoption of autonomous vehicles have included concerns about the resulting loss of driving-related jobs in the road transport industry, and safety concerns. On March 18, 2018, a pedestrian was struck and killed in Tempe, Arizona by an Uber self-driving car. ==== AI-generated content ==== In the 2020s, automated content became more relevant due to technological advancements in AI models, such as ChatGPT, DALL-E, and Stable Diffusion. In most cases, AI-generated content such as imagery, literature, and music are produced through text prompts. These AI models are sometimes integrated into creative programs. AI-generated art may sample and conglomerate existing creative works, producing results that appear similar to human-made content. Low-quality AI-generated visual artwork can be informally referred to as AI slop. Some artists use a tool called Nightshade that alters images to make them detrimental to the training of text-to-image models if scraped without permission, while still looking normal to humans. AI-generated images are a potential tool for scammers and those looking to gain followers on social media, either to impersonate a famous individual or group or to monetize their audience. The New York Times has sued OpenAI, alleging copyright infringement related to the training and outputs of its AI models. === Eradication === Scientists such as Stephen Hawking are confident that superhuman artificial intelligence is physically possible, stating "there is no physical law precluding particles from being organised in ways that perform even more advanced computations than the arrangements of particles in human brains". According to Nick Bostrom, a superintelligent machine would not necessarily be motivated by the same emotional desire to collect power that often drives human beings but might rather treat power as a means toward attaining its ultimate goals; taking over the world would both increase its access to resources and help to prevent other agents from stopping the machine's plans. As a simplified example, a paperclip maximizer designed solely to create as many paperclips as possible would want to take over the world so that it can use all of the world's resources to create as many paperclips as possible, and, additionally, prevent humans from shutting it down or using those resources on things other than paperclips. There are debates on how realistic AI takeover scenarios are. According to a 2026 research paper, many of the arguments about existential risks are based on speculative assumptions about how intelligent AI systems could become, how they would behave and what goals they might develop over time. A 2023 Reuters/Ipsos survey showed that 61% of American adults feared AI could pose a threat to civilization. Philosopher Niels Wilde refutes the common thread that artificial intelligence inherently presents a looming threat to humanity, stating that these fears stem from perceived intelligence and lack of transparency in AI systems that more closely reflects the human aspects of it rather than those of a machine. AI alignment research studies how to design AI systems so that they follow intended objectives. == Debate == Physicist Stephen Hawking, Microsoft founder Bill Gates, and SpaceX founder Elon Musk have expressed concerns about the possibility that AI could develop to the point that humans could not control it, with Hawking theorizing that this could "spell the end of the human race". Stephen Hawking said in 2014 that "Success in creating AI would be the biggest event in human history. Unfortunately, it might also be the last, unless we learn how to avoid the risks." Hawking believed that in the coming decades, AI could offer "incalculable benefits and risks" such as "technology outsmarting financial markets, out-inventing human researchers, out-manipulating human leaders, and developing weapons we cannot even understand." In January 2015, Nick Bostrom joined Stephen Hawking, Max Tegmark, Elon Musk, Lord Martin Rees, Jaan Tallinn, and numerous AI researchers in signing the Future of Life Institute's open letter speaking to the potential risks and benefits associated with artificial intelligence. The signatories "believe that research on how to make AI systems robust and beneficial is both important and timely, and that there are concrete research directions that can be pursued today." Some focus has been placed on the development of trustworthy AI. Three statements have been posed as to why AI is not inherently trustworthy: 1. An entity X is trustworthy only if X has the right motivations, goodwill and/or adheres to moral obligations towards the trustor; 2. AI systems lack motivations, goodwill, and moral obligations; 3. Therefore, AI systems cannot be trustworthy. There are additional considerations within this framework of trustworthy AI that go further into the fields of explainable artificial intelligence and respect for human privacy. Zanotti and colleagues

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  Constructive cooperative coevolution

  The constructive cooperative coevolutionary algorithm (also called C3) is a global optimisation algorithm in artificial intelligence based on the multi-start architecture of the greedy randomized adaptive search procedure (GRASP). It incorporates the existing cooperative coevolutionary algorithm (CC). The considered problem is decomposed into subproblems. These subproblems are optimised separately while exchanging information in order to solve the complete problem. An optimisation algorithm, usually but not necessarily an evolutionary algorithm, is embedded in C3 for optimising those subproblems. The nature of the embedded optimisation algorithm determines whether C3's behaviour is deterministic or stochastic. The C3 optimisation algorithm was originally designed for simulation-based optimisation but it can be used for global optimisation problems in general. Its strength over other optimisation algorithms, specifically cooperative coevolution, is that it is better able to handle non-separable optimisation problems. An improved version was proposed later, called the Improved Constructive Cooperative Coevolutionary Differential Evolution (C3iDE), which removes several limitations with the previous version. A novel element of C3iDE is the advanced initialisation of the subpopulations. C3iDE initially optimises the subpopulations in a partially co-adaptive fashion. During the initial optimisation of a subpopulation, only a subset of the other subcomponents is considered for the co-adaptation. This subset increases stepwise until all subcomponents are considered. This makes C3iDE very effective on large-scale global optimisation problems (up to 1000 dimensions) compared to cooperative coevolutionary algorithm (CC) and Differential evolution. The improved algorithm has then been adapted for multi-objective optimization. == Algorithm == As shown in the pseudo code below, an iteration of C3 exists of two phases. In Phase I, the constructive phase, a feasible solution for the entire problem is constructed in a stepwise manner. Considering a different subproblem in each step. After the final step, all subproblems are considered and a solution for the complete problem has been constructed. This constructed solution is then used as the initial solution in Phase II, the local improvement phase. The CC algorithm is employed to further optimise the constructed solution. A cycle of Phase II includes optimising the subproblems separately while keeping the parameters of the other subproblems fixed to a central blackboard solution. When this is done for each subproblem, the found solution are combined during a "collaboration" step, and the best one among the produced combinations becomes the blackboard solution for the next cycle. In the next cycle, the same is repeated. Phase II, and thereby the current iteration, are terminated when the search of the CC algorithm stagnates and no significantly better solutions are being found. Then, the next iteration is started. At the start of the next iteration, a new feasible solution is constructed, utilising solutions that were found during the Phase I of the previous iteration(s). This constructed solution is then used as the initial solution in Phase II in the same way as in the first iteration. This is repeated until one of the termination criteria for the optimisation is reached, e.g. a maximum number of evaluations. {Sphase1} ← ∅ while termination criteria not satisfied do if {Sphase1} = ∅ then {Sphase1} ← SubOpt(∅, 1) end if while pphase1 not completely constructed do pphase1 ← GetBest({Sphase1}) {Sphase1} ← SubOpt(pphase1, inext subproblem) end while pphase2 ← GetBest({Sphase1}) while not stagnate do {Sphase2} ← ∅ for each subproblem i do {Sphase2} ← SubOpt(pphase2,i) end for {Sphase2} ← Collab({Sphase2}) pphase2 ← GetBest({Sphase2}) end while end while == Multi-objective optimisation == The multi-objective version of the C3 algorithm is a Pareto-based algorithm which uses the same divide-and-conquer strategy as the single-objective C3 optimisation algorithm . The algorithm again starts with the advanced constructive initial optimisations of the subpopulations, considering an increasing subset of subproblems. The subset increases until the entire set of all subproblems is included. During these initial optimisations, the subpopulation of the latest included subproblem is evolved by a multi-objective evolutionary algorithm. For the fitness calculations of the members of the subpopulation, they are combined with a collaborator solution from each of the previously optimised subpopulations. Once all subproblems' subpopulations have been initially optimised, the multi-objective C3 optimisation algorithm continues to optimise each subproblem in a round-robin fashion, but now collaborator solutions from all other subproblems' subspopulations are combined with the member of the subpopulation that is being evaluated. The collaborator solution is selected randomly from the solutions that make up the Pareto-optimal front of the subpopulation. The fitness assignment to the collaborator solutions is done in an optimistic fashion (i.e. an "old" fitness value is replaced when the new one is better). == Applications == The constructive cooperative coevolution algorithm has been applied to different types of problems, e.g. a set of standard benchmark functions, optimisation of sheet metal press lines and interacting production stations. The C3 algorithm has been embedded with, amongst others, the differential evolution algorithm and the particle swarm optimiser for the subproblem optimisations.

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  Desktop video

  Desktop video refers to a phenomenon lasting from the mid-1980s to the early 1990s when the graphics capabilities of personal computers such as the Amiga, Macintosh II, and specially-upgraded IBM PC compatibles had advanced to the point where individuals and local broadcasters could use them for analog non-linear editing and vision mixing in video production. Despite the use of computers, desktop video should not be confused with digital video since the video data remained analog, and it uses items like a VCR and a camcorder to record the video. Full-screen, full-motion video's vast storage requirements meant that the promise of digital encoding would not be realized on desktop computers for at least another decade. == Description == There were multiple models of genlock cards available to synchronize the content; the Newtek Video Toaster was commonly used in Amiga in countries that used NTSC (PAL-M in Brazil), while PCs had Truevision and Matrox Illuminator cards and Mac systems had the SuperMac Video Spigot and Radius VideoVision cards. Apple later introduced the Macintosh Quadra 840AV and Centris 660AV systems to specifically address this market. Desktop video was a parallel development to desktop publishing and enabled many small production houses and local TV stations to produce their own original content for the first time. Along with the advent of public-access cable channels, desktop video meant that television advertising became affordable for local businesses such as retailers, restaurants, real estate agents, contractors and auto dealers. As with the phrase desktop publishing, use of the term died out as the technologies to which it referred become the norm for any kind of video production.

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  Felix, Net i Nika

  Felix, Net i Nika ("Felix, Net and Nika") is a series of Polish language science fiction books for teenagers, written by Rafał Kosik. It tells the adventures of three friends - Felix Polon, Net Bielecki and Nika Mickiewicz - who attend fictional Professor Kuszmiński Middle School in Warsaw. As of 2024, eighteen books have been published. == Books == There are currently 18 books in the series: Felix, Net and Nika and the Gang of Invisible People - November 2004. Felix, Net and Nika and the Theoretically Possible Catastrophe - November 2005 Felix, Net and Nika and the Palace of Dreams - November 2006 Felix, Net and Nika and the Trap of Immortality - November 2007 Felix, Net and Nika and the Orbital Conspiracy - November 2008 Felix, Net and Nika and the Orbital Conspiracy 2: Small Army - May 2009 Felix, Net and Nika and the Third Cousin - November 2009 Felix, Net and Nika and the Rebellion of Machines - March 2011 Felix, Net and Nika and the World Zero - November 2011 Felix, Net and Nika and the World Zero 2. Alternauts - November 2012 Felix, Net and Nika and the Extracurricular Stories - April 2013 Felix, Net and Nika and the Secret of Czerwona Hańcza - November 2013 Felix, Net and Nika and Curse of McKillian's House - November 2014 Felix, Net and Nika and (un)Safe Growing up - November 2015 Felix, Net and Nika and The End of The World as We Know It - November 2018 Felix, Net and Nika and No Chance - November 2022 Felix, Net and Nika and No Chance 2: other tomorrrow - 2023 Felix, Net and Nika and Fantology - June 2024 == Film == A feature motion picture, Felix, Net i Nika oraz Teoretycznie Możliwa Katastrofa (Felix, Net and Nika and the Theoretically Possible Catastrophe) was released in Poland on September 28, 2012. == Main characters == Felix Polon - a foresighted, fair-haired boy with dark brown eyes. He inherited the talent of constructing various things, especially robots, from his father- it saved his friends many times. He can make anything from nothing, always finds a way out of a situation; almost always has a plan. Together with his parents Marlene and Peter, grandmother Lucy, his dog Caban (a Black Russian Terrier) and Golem Golem a robot he built, Felix lives on Serdeczna Street in a small family house. Net Bielecki is quite tall & slim, has blue eyes and a high IQ level. "Net" is his nickname; his true name is unknown. He is the most trendy and 'awesome' in his entire class. He is a human calculator and is excellent in mathematics. He hates dictations and spelling because he is dyslexic. He is also quite lazy, absent-minded and sometimes hysterical, or panicking. His dark blond hair looks like a heap of hay after a grenade explosion. He is best in ICT and writes many of his own programs. His love interest is Nika Mickiewicz. Together with his parents Lila and Mark, and their newborn twins nicknamed Pompek and Prumcia he lives on the top floor of a Penthouse apartment. Nika Mickiewicz is a girl with a character. She is very brave and mature. She likes reading books. She has curly, red hair, green eyes and a few freckles. She is not very rich; she wears second-hand clothes and her only pair of black Dr. Martens shoes. She lives in a tiny apartment. She is an orphan, but hides that fact from people for almost 3 years. However, Felix and Net, her best and possibly only friends, find out about it. She also has abnormal abilities. She can move distant objects using her powers, ski uphill and knows some things by intuition. In other words, she is telekinetic. Manfred is a friendly AI program started and never finished by Net's father, and mastered and programmed further by Net himself. He likes going on adventures and solving mysteries with the trio much more than his actual job, which is controlling the traffic lights. He helped out the three friends many times and is their reliable and faithful friend. Morten is also an AI program, but he is the antagonist of the trio. He appears in all 6 books of Felix Net and Nika. In the first book, the trio thinks they finished him off for good, but as we find out later, he comes back in the third book. In the fifth/sixth book, he was the mastermind of the Orbital Conspiracy. Also, Morten's logo, appears in all 6 books and it is still a mystery what he has to do with each event.

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  Jake Elwes

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

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  Plants vs. Zombies: Replanted

  Plants vs. Zombies: Replanted is a 2025 tower defense video game developed by PopCap Seattle, The Lost Pixels, and published by Electronic Arts. It is a remaster of the 2009 game Plants vs. Zombies, introducing upscaled graphics and new additional content. Plants vs. Zombies: Replanted was released for video game consoles and personal computers on October 23, 2025. It received generally positive reviews from critics, but was criticized by the original game's development team for including fabricated concept art and for mishandling the soundtrack. == Gameplay == Plants vs. Zombies: Replanted follows the same gameplay of the original Plants vs. Zombies game with very minor changes. It is a lane-based tower defense game where the player has to defend their home from incoming zombies. The player can place various plants by spending "sun", the game's currency during levels. Sun icons can be collected from the sky during daytime and from sun-producing plants such as sunflowers. Some plants can attack zombies while some can act as defense. If all zombies are defeated in a level, the player wins. If a zombie reaches the left side of the line, a lawn mower—or other similar, relevant object—will activate and clear the row of any zombies, but if the lawn mower has already been used, and another zombie crosses, the game is over. === Replanted features === Plants vs. Zombies: Replanted contains up to 4K upscaled graphics and widescreen support, in comparison to the original game's static 800x600 resolution and 4:3 aspect ratio. Replanted now has full controller support and features local multiplayer modes ported from the original game's seventh generation console ports: co-op, where two players play together with assigned roles; and Versus, where one plays as the plants and the other as the zombies. No online multiplayer is planned, however support for Steam Remote Play was later added in a patch as an alternative for Windows users. Replanted also contains quality-of-life features. Gameplay can now be sped up by the player's will, with a max speed increase of 2.5x. Sun icons can now be mass collected using the "Sun Magnet." On Windows, players can quick-select plants from their seed bank using the number keys as hotkeys. Replanted also introduces two new additional game modes. "Cloudy Day" is a set of non-linear levels in the Adventure campaign. These levels only allow Sunflowers as sun-producing plants. During these levels, the amount of sun dropped from the sky and produced by plants are lowered. At certain times, rain clouds will move over the lawn. While these clouds are present, sun will stop appearing from the sky and from Sunflowers. However, all plants will cost around half their original price and have significantly faster recharge times. "R.I.P. Mode" is a harder difficulty of the Adventure campaign, but the player is forced back to the beginning if they lose a single level. Replanted additionally features "bonus levels" included as non-linear levels in the Adventure campaign. These include 10 new minigames that were previously unused in the original game. In a later update, Replanted added "Survival: Endless" levels to all five areas of the game instead of just the daytime pool. == Development == The existence of a Plants vs. Zombies remaster was revealed in an interview with Janet Robin from The String Revolution, who they did a vinyl collaboration with the franchise in 2025 with Iam8bit. Janet stated that EA commissioned them to record an acoustic composition of the track "Crazy Dave" to be used for an "anniversary edition" of the game. The song would be additionally be a tribute to the song "Bad Guy", which artist Billie Eilish has stated to be somewhat similar to the track. Plants vs. Zombies Replanted was officially announced in a Nintendo Direct presentation in late July 2025. As an incentive, people who pre-ordered the game are given an in-game retro-styled skin of the Peashooter. Replanted was showcased at PAX West on August 25, 2025. A dev diary for Plants vs. Zombies: Replanted was uploaded to YouTube on October 17, 2025. The video features Nick Reinhart, Jake Neri, and Matt Townsend. A developer panel for the game was available during TwitchCon 2025. == Release == Plants vs. Zombies: Replanted was released for Nintendo Switch, Nintendo Switch 2, PlayStation 4, PlayStation 5, Xbox One, Xbox Series X and Series S, and personal computers on October 23, 2025. It was leaked onto the internet on October 17, 2025. Players discovered multiple software bugs, and multiple assets alleged to be upscaled by generative artificial intelligence were found, leading to backlash. Numerous bugs were fixed in a day-one patch on October 23, 2025. == Reception == === Critical response === The versions of Plants vs. Zombies: Replanted for Windows, PlayStation 5, and Nintendo Switch 2 received "generally favorable" reviews from critics, according to review aggregator website Metacritic, while the Xbox Series X version received "mixed or average" reviews. According to OpenCritic, 57% of critics recommended it. IGN's Alessandro Fillari called it "a good way to get re-acquainted with one of the quirkiest puzzle-strategy games of the 2000s", while acknowledging its questionable decisions. Shacknews' David Craddock said it was his favorite version of Plants vs. Zombies, stating, "it packs everything fans loved about the original game, plus lots more" while justifying its US$20 price. The Verge described Replanted as "a time capsule from a simpler, happier time". Kyle Hilliard from Game Informer praised its faithfulness, complimenting the new animations and character designs that did not alter its memorability. Noah Hunter for Final Weapon described the remake as solid, though criticized the lack of certain features and containing bugs that gate it from being excellent. Ben Lyons from Gamereactor stated Replanted is the same as the original overall, despite believing the £18 price is not justified. === Original developers === Rich Werner, the original game's character designer, claims that some concept art contained in the game, speculated to be for Plants vs. Zombies: Garden Warfare (2014), did not originate from the original's development. Werner also stated that concept art for the Disco Zombie is fabricated; the design for the Disco Zombie was created after the estate of Michael Jackson requested the original Dancing Zombie, who resembles Michael Jackson from his Thriller music video, be removed from the game. On October 19, 2026, composer Laura Shigihara expressed her dissatisfaction with the lack of dynamic music in the game. Dynamic music would later be implemented in a later patch. In an interview featuring Rich Werner and user interface designer Matt Holmberg on April 29, 2026, Werner revealed that he and Shigihara were contacted by EA to make a music video to market Replanted. However, after the game was leaked, Werner's response on social media led EA to cancel the collaboration.

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  Dynamic texture

  Dynamic texture ( sometimes referred to as temporal texture) is the texture with motion which can be found in videos of sea-waves, fire, smoke, wavy trees, etc. Dynamic texture has a spatially repetitive pattern with time-varying visual pattern. Modeling and analyzing dynamic texture is a topic of images processing and pattern recognition in computer vision. Extracting features that describe the dynamic texture can be utilized for tasks of images sequences classification, segmentation, recognition and retrieval. Comparing with texture found within static images, analyzing dynamic texture is a challenging problem. It is important that the extracted features from dynamic texture combine motion and appearance description, and also be invariance to some transformation such as rotation, translation and illumination. == Analysis methods of dynamic texture == The methods of dynamic texture recognition can categorized as follows: Methods based on optical flow: by applying optical flow to the dynamic texture, velocity with direction and magnitude can be detected and used to recognize the dynamic texture. Due to simplicity of its computation, it is currently the most popular method. Methods computing geometric properties: this methods track the surfaces of motion trajectories in spatiotemporal domain. Methods based on local spatiotemporal filtering : this methods analyze the local spatiotemporal patterns and its orientation and energy and employ them as feature used for classification. Methods based on global spatiotemporal transform: this method characterize the motion at different scale using wavelets that can decompose the motion into local and global. Model-based methods : These methods aims at generating a model to describe the motion by a set of parameters. == Applications == - Segmenting the sequence images of natural scenes. This helps on differentiate between streets and grass alongside these streets which could be used in the application of navigations. - Motion detection : Dynamic texture features extracted from footage videos can be exploited to detect abnormal crowd activities. - Video classification: video of natural scenes or other scenes that exhibit dynamic textures. - Video retrieval : Dynamic textures can be employed as a feature retrieve videos that contain, for example, sea-waves, smoke, clouds, wavy trees.

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  Refik Anadol

  Refik Anadol (born November 7, 1985) is a Turkish American media artist and the co-founder of Refik Anadol Studio and Dataland. Recognized as a pioneer in the aesthetics of data visualization and AI arts, his work merges art, technology, science, and architecture. Through media embedded into existing architecture, live audio-visual performances, immersive rooms, exhibitions, AI data paintings and sculptures, and digital collections, Anadol explores collective memories, humanity's relationship to nature, the perception of space and time, and human-machine collaborations. His work has been exhibited in more than seventy cities on six continents. == Early life and education == Anadol was born and raised in Istanbul and grew up in a family of teachers. He taught himself basic programming on a Commodore 64 when he was eight. His connection to machines began with coding and video games. Anadol saw Blade Runner for the first time when he was eight; his mother said the way he perceived his surroundings shifted the day after he saw the film. He was fascinated with its futuristic depiction of downtown Los Angeles, and transfixed by as a scene during which a replicant discovers that her memories are an implanted component of her machine mind, In a 2024 interview with the Financial Times, he said: "Since that moment, one of my inspirations has been that question: 'What can a machine do with someone else's memories?" Anadol attended Istanbul Bilgi University, where he received a BA in photography and video in 2009 and an MFA in visual communication in 2011. In 2014 he earned an MFA in design media arts at UCLA. He was mentored by Casey Reas, Jennifer Steinkamp, and Christian Moeller. == Career and selected works == === 2008–2012: Data painting, Quadrature and Quadrangle, Istanbul Biennial === As an undergraduate, Anadol read a paper by Lev Manovich on augmented space. Manovich's assertion that collaborations between architects and artists could make the "invisible flow of data visible" triggered Anadol's imagination, and in 2008, he altered built space for the first time. Bringing a projector outside, he projected large-scale images onto a concrete to create the illusion of movement. Coining the term "data painting," the piece inspired Anadol to use light as material and data as pigment. In 2010 he created Quadrature with Alican Aktürk, a fellow graduate student, at the SantralIstanbul Art and Culture Center's main gallery building. A live audio-visual performance that examined the relationship between architecture and media, Quadrature used video projection techniques to manipulate footage of quadrilaterals. He followed Quadrature with Quadrangle at SANAA School of Design in Essen, Germany, using the entire 360 degrees of the building as a canvas. In 2011, he was invited to create a media installation at the Istanbul Biennial on the heavily trafficked İstiklal Avenue. He created a site-specific large-scale interpretation of sounds he recorded during different times of day, and used nine projectors to project reinterpreted images. The work was titled Augmented Structures v1.0. Anadol's first solo exhibition, Sceptical Interventions, was held at the Piveneli Gallery in Istanbul in early 2012. Later that year he moved to Los Angeles to attend UCLA's Design Media Arts program. The first place he went after his arrival was downtown Los Angeles. [6] === 2013–2016: Visions of America: Amériques, Infinity Room, Google AMI === In 2013, at Microsoft Research's annual Design Expo, Anadol presented his idea to use the external walls of Walt Disney Concert Hall as a canvas. His presentation brought him to the attention of Gehry Technologies, and with the support of Gehry and his team, Anadol was offered the use of the original 3D model of the concert hall. For his 2014 thesis project, with assistance from architects and UCLA researchers, he created a site-specific architectural video installation inside the concert hall that accompanied a Los Angeles Philharmonic performance of Edgard Varèse's Amérique. Titled Visions of America: Amériques, Anadol used algorithmic sound analysis to listen and respond to the music in real-time. He tracked conductor Esa-Pekka Salonen's heartbeat with a sensor and used a 3-D camera system to integrate Salonen's movements. He created Infinity Room at the Zorlu PSM for the 2015 Istanbul Biennial. Rather than creating an illusion only with mirrors, Anadol used pixel and 3D projection mapping to transform every surface of the room into an abstract infinite moving space. A temporary immersive environment, Infinity Room was also exhibited at events including South by Southwest in Austin, Texas, the New Zealand Festival in Wellington, New Zealand, and Jeffrey Deitch in Los Angeles. In 2016, Anadol was awarded the first Google Artists and Machine Intelligence Artist Residency; it was just after a team at Google opened up the algorithm for DeepDream, a computer vision program that prompted Anadol's realization that if a machine could learn, it could remember, dream, and hallucinate. === 2017–2018: Winds of Boston, Archive Dreaming, Melting Memories, WDCH Dreams === In 2017, he created the data painting Winds of Boston, a 6' x 13' foot video installation in the lobby of a Boston office building, using software he created to read, analyze and visualize wind speed, direction, and gust patterns along with time and temperature at 20-second intervals recorded over a one-year period at Logan International Airport. Later in the year, he used AI to generate infinite new outputs based on a massive dataset for Archive Dreaming, an immersive installation at Salt Research, a contemporary gallery and library in Istanbul. Inspired by his idea of consciousness and its context within AI, as well as Jorge Luis Borges' The Library of Babel, Anadol used AI and machine learning to look at and discover interactions and correlations between 1.7 million items culled from 40,000 publications covering Turkish contemporary and modern art, architecture, and economics from 1997 to 2010. Archive Dreaming, which could be controlled by users with a joystick, dreamed of unexpected correlations among documents when idle. In 2018, after his uncle was diagnosed with Alzheimer's, Anadol created Melting Memories. Working with scientists from the neuroscape laboratory at the University of California, San Francisco, he used academic data from the neuroscience archives and EEG scans of an anonymous Alzheimer's disease dataset to create AI-generated visuals related to memory, health, degeneration, and decay.Melting Memories was projected on the walls of Pilevneli Gallery; visitors to the exhibition could watch as millions of pixels reconstructed people's memories. Anadol won the Lumen Prize Gold Award for Melting Memories. Anadol was commissioned by the Los Angeles Philharmonic to create an installation to celebrate the orchestra's centennial anniversary in 2018. He worked with Google's Kenric MacDowell to create WDCH Dreams, using algorithmic visualizations of data to mimic the process of human dreaming. Projected across the exterior walls of Walt Disney Concert Hall using 42 large-scale projectors with 50K visual resolution, 8-channel sound, and 1.2M luminance, Anadol painted with data points culled from the orchestra's archives, including 587,763 images, 1,880 videos, 1,483 metadata files, and 17,773 audio files. Because Gehry gave him access to the 3D architectural files of Walt Disney Concert Hall, Anadol knew the exact contours of the building. WDCH Dreams debuted in September 2018. A 12-minute performance in three parts staged every 30 minutes over ten nights, "Centennial Memories,” the first piece, used 44.5 terabytes of historical data from the Phil's archives. It was followed by "Consciousness", which processed every note the orchestra has ever recorded, using billions of data points to generate connections; and "Dream," which merged "Centennial Memories" and "Consciousness" to create hallucinations that were described in the New York Times as "a sort of combinatorial Fantasia. === 2019–2021: Machine Hallucinations: NYC, Machine Hallucinations: Nature Dreams, Machine Memories: Space, Quantum Memories === In 2019, Refik Anadol presented Latent History at Fotografiska Stockholm. The site specific installation transformed photographic archives of Stockholm into a large scale, machine generated visual projection displayed in the museum’s main exhibition hall. Drawing on thousands of archival images spanning approximately 150 years, the work used artificial intelligence to reinterpret the city’s historical imagery as a continuously evolving visual narrative.. Anadol began thinking about the work that would become the Machine Hallucinations series while in residence at Google. In 2019, he completed the first work in the series, Machine Hallucinations: NYC, which used 300 million photos of New York City and 113 million additional data points, including subway sounds, ra

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  Age Of

  Age Of is the eighth studio album by American electronic producer Oneohtrix Point Never, released on June 1, 2018, on Warp Records. Recorded over two years, it is the first Oneohtrix Point Never album to prominently feature Daniel Lopatin's own vocals. The album was accompanied by the MYRIAD tour, which premiered as a "conceptual concertscape" in 2018 at the Park Avenue Armory and ended its run in 2019. It features contributions from James Blake (who additionally produced and mixed the album), Anohni, Prurient, Kelsey Lu and Eli Keszler. The artwork, which employs Jim Shaw's "The Great Whatsit" as a central image, was designed by David Rudnick. While not entering the official United States Billboard 200 chart, it peaked at number 59 on the magazine's Top Current Albums chart. == Background == Lopatin produced Age Of in parts of a two-year period, during which he was also producing for other artists, including Anohni, FKA Twigs, Iggy Pop, and David Byrne. After composing the soundtrack for the Safdie Brothers' 2017 film Good Time, Lopatin moved to an Airbnb lodge in South Central Massachusetts, derived from his aspiration to live out the modern cliche of musicians moving to the woods to record albums; the eerie atmosphere in the lodge at nighttime influenced his desire to make "weird, little nightmare ballads". In addition to Lopatin's own singing, the album also features vocal performances from Anohni and Prurient, while instrumentalists Kelsey Lu and Eli Keszler contribute to several tracks. When the record was nearly finished, Lopatin reached out to musician James Blake to contribute to the mixing process, eventually traveling to Los Angeles to complete the album. The track "The Station" was originally composed as a demo for R&B singer Usher which was ultimately not used. On July 9, 2018, Lopatin released the original topline (vocal melody) demo for The Station through Sendspace. The track "Toys 2" imagines a theoretical sequel to the 1992 film Toys where actor Robin Williams' image has been recreated with CGI (as his will specifically forbade any usage of his image after his death), and pokes fun at the common electronic music trope of composing a soundtrack to a theoretical film (which Lopatin described as "horribly cliché"). == Concept and MYRIAD == Influences on Age Of included Stanley Kubrick's 1968 film 2001: A Space Odyssey, which inspired the narrative of the album's accompanying performance installation and tour MYRIAD, as well as William Strauss's The Fourth Turning, a favorite book of former White House Chief Strategist Steve Bannon, which Lopatin described as "insidious, like the voice of a computer insisting on the truth about history without any sensitivity given to how complex and non-linear systems might be"; Lopatin was subsequently inspired to "[use] that sort of taxonomy as a kind of farce to then create these little frameworks for understanding". Other inspirations included the writings of the 1990s multidisciplinary collective Cybernetic Culture Research Unit and the works of singer-songwriters such as Bruce Cockburn, Bob Dylan, and Paul Simon. Around the time Lopatin began finalizing Age Of in his Airbnb lodge, he began working on the concept for MYRIAD, a conceptual concert performance which premiered at Park Avenue Armory. He described the concept as a four-part "epochal song cycle" showcasing the idiocy of previous generations of living organisms. The loose story concerns a group of artificial intelligences near the end of time named a "Limitless Living Informational Intelligence" (represented in the MYRIAD logo as nine squares) which, for leisurely purposes, attempt to replicate the cultures and behaviors of the previously existent human species. It does this by determining an "average" of human experiences through the species' "recorded output", and does so through imperfect, heuristic techniques. The show was consequently divided into four sections, each representing an epoch of the cycle concept loosely inspired by the Strauss–Howe generational theory: the Age of Ecco, the Age of Harvest, the Age of Excess, and the Age of Bondage. Ecco is "a phase of pre-evolutionary ignorance", Harvest is "living in agrarian harmony with the world", Excess is "the age of unchecked industrial ambition", and Bondage is "an era of engorgement, wherein "we keep making more and more shit until there's no space left." MYRIAD mainly featured "three-hundred pound sculptures that hang from the ceiling like kebabs that secrete ooze", and a full ensemble that toured to perform songs from Age Of, including Eli Keszler, Kelly Moran and Aaron David Ross. The sculptures, as well as the visuals displayed on five polygon panels, were created by frequent Oneohtrix Point Never collaborator Nate Boyce. Initially, Lopatin planned for each of the album's four epoches to be represented by fragrances, the more noisy epochs being pleasant to the nose to make a "weird dissonance". However, due to lack of time and resources, that part of the plan was scrapped. == Composition == Whereas previous Oneohtrix Point Never albums followed musical styles from only distinctive eras, Age Of is the first album by Lopatin to incorporate elements of unique genres from a variety of periods, hence the "incompleteness" of its title according to reviewer Heather Phares, and his first pop-song-oriented release since his work for Ford & Lopatin. The sound palettes it uses are those from a variety of styles such as chamber pop, "android"-like folk and country music, yacht rock, smooth jazz, R&B, Future-style soul, black metal, new age, and stadium pop, as well as post-industrial sounds on tracks like "Warning", "We'll Take It" and "Same", and, in particular, baroque music and medieval music on the opening title track, "Age Of". Critics also noted elements of Lopatin's past discography being present on Age Of. The instrumentation of Age Of is made up of MIDI harpsichords, guitars, pianos, brass and vocals, as well as Lopatin's trademark unorthodox sound design, samples and synth presets. The LP's use of the harpsichord shows its similarities "with Eastern instruments such as the koto and with rapid-fire electronic melodies", wrote Phares. == Critical reception == Age Of was critically well-received upon its distribution. Some reviewers praised the album's use of collaborators. Reviewing the album for AllMusic, Heather Phares called Age Of a "landmark work" for Lopatin. She praised it as his "widest-ranging" release, elaborating that he "matches the album's ambition with plenty of emotion" and "gives his music exciting new shapes." Ross Devlin of The Skinny, in a five-star review of the record, also highlighted the album's amount of ambition, particularly the "wealth of exquisitely baroque moments, exploring history as a pliable, multi-dimensional rift", that gave it "exceptional sonic depth". The Observer praised Age Of for continuing the "off-kilter composition and unexpected instrumentation" of Lopatin's previous releases, and critic Matt McDermott highlighted that the producer increased his musical range with the record: "It's a dizzying trip meant to shore up Lopatin's status as an avant-garde auteur while aiding his forays into mainstream pop culture." Age Of was ranked the 15th best release of the year in The Wire magazine's annual critics' poll. == Track listing == Notes "Myriad Industries" is stylized as "myriad.industries". Sample credits "Age Of" contains a sample of "Blow the Wind" by Jocelyn Pook. "Manifold" contains a sample from "Overture (Ararat the Border Crossing)" by Tayfun Erdem; and a sample from "Venice Beach in Winter" (listed in the liner notes as "a keyboard sample from Reharmonization") by Julian Bradley. "Myriad Industries" contains a sample of "EchoSpace" by Gil Trythall. == Accolades == == Personnel == Daniel Lopatin – production, lead vocals, album art, design James Blake – additional production, mixing, keyboards Gabriel Schuman, Joshua Smith and Evan Sutton – assistance Greg Calbi – mastering David Rudnick – album art, design Prurient – vocals Kelsey Lu – keyboards Anohni – vocals Eli Keszler – drums Shaun Trujillo – words == Charts ==

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  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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  Geofence warrant

  A geofence warrant or a reverse location warrant is a search warrant issued by a court to allow law enforcement to search a database to find all active mobile devices within a particular geo-fence area. Courts have granted law enforcement geo-fence warrants to obtain information from databases such as Google's Sensorvault, which collects users' historical geolocation data. Geo-fence warrants are a part of a category of warrants known as reverse search warrants. == History == Geofence warrants were first used in 2016. Google reported that it had received 982 such warrants in 2018, 8,396 in 2019, and 11,554 in 2020. A 2021 transparency report showed that 25% of data requests from law enforcement to Google were geo-fence data requests. Google is the most common recipient of geo-fence warrants and the main provider of such data, although companies including Apple, Snapchat, Lyft, and Uber have also received such warrants. == Legality == === United States === Some lawyers and privacy experts believe reverse search warrants are unconstitutional under the Fourth Amendment to the United States Constitution, which protects people from unreasonable searches and seizures, and requires any search warrants be specific to what and to whom they apply. The Fourth Amendment specifies that warrants may only be issued "upon probable cause, supported by Oath or affirmation, and particularly describing the place to be searched, and the persons or things to be seized." Some lawyers, legal scholars, and privacy experts have likened reverse search warrants to general warrants, which were made illegal by the Fourth Amendment. Groups including the Electronic Frontier Foundation have opposed geo-fence warrants in amicus briefs filed in motions to quash such orders to disclose geo-fence data. In 2024, a panel of the United States Fourth Circuit Court of Appeals considered data acquired from Google’s Sensorvault not to be a search, but non-private business records when users opt-in to Google’s location history. However, upon a rehearing en banc, the Court vacated that decision. In April 2025, the full Court affirmed the judgment solely on the 'good faith' exception, leaving the underlying constitutional question of whether geofence warrants constitute a search unsettled in the Circuit. However, the United States Fifth Circuit Court of Appeals found that geofence warrants are "categorically prohibited by the Fourth Amendment." The split in Circuits prompted the United States Supreme Court to agree to hear Chatrie v. United States in January 2026.

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  Ensemble averaging (machine learning)

  In machine learning, ensemble averaging is the process of creating multiple models (typically artificial neural networks) and combining them to produce a desired output, as opposed to creating just one model. Ensembles of models often outperform individual models, as the various errors of the ensemble constituents "average out". == Overview == Ensemble averaging is one of the simplest types of committee machines. Along with boosting, it is one of the two major types of static committee machines. In contrast to standard neural network design, in which many networks are generated but only one is kept, ensemble averaging keeps the less satisfactory networks, but with less weight assigned to their outputs. The theory of ensemble averaging relies on two properties of artificial neural networks: In any network, the bias can be reduced at the cost of increased variance In a group of networks, the variance can be reduced at no cost to the bias. This is known as the bias–variance tradeoff. Ensemble averaging creates a group of networks, each with low bias and high variance, and combines them to form a new network which should theoretically exhibit low bias and low variance. Hence, this can be thought of as a resolution of the bias–variance tradeoff. The idea of combining experts can be traced back to Pierre-Simon Laplace. == Method == The theory mentioned above gives an obvious strategy: create a set of experts with low bias and high variance, and average them. Generally, what this means is to create a set of experts with varying parameters; frequently, these are the initial synaptic weights of a neural network, although other factors (such as learning rate, momentum, etc.) may also be varied. Some authors recommend against varying weight decay and early stopping. The steps are therefore: Generate N experts, each with their own initial parameters (these values are usually sampled randomly from a distribution) Train each expert separately Combine the experts and average their values. Alternatively, domain knowledge may be used to generate several classes of experts. An expert from each class is trained, and then combined. A more complex version of ensemble average views the final result not as a mere average of all the experts, but rather as a weighted sum. If each expert is y i {\displaystyle y_{i}} , then the overall result y ~ {\displaystyle {\tilde {y}}} can be defined as: y ~ ( x ; α ) = ∑ j = 1 p α j y j ( x ) {\displaystyle {\tilde {y}}(\mathbf {x} ;\mathbf {\alpha } )=\sum _{j=1}^{p}\alpha _{j}y_{j}(\mathbf {x} )} where α {\displaystyle \mathbf {\alpha } } is a set of weights. The optimization problem of finding alpha is readily solved through neural networks, hence a "meta-network" where each "neuron" is in fact an entire neural network can be trained, and the synaptic weights of the final network is the weight applied to each expert. This is known as a linear combination of experts. It can be seen that most forms of neural network are some subset of a linear combination: the standard neural net (where only one expert is used) is simply a linear combination with all α j = 0 {\displaystyle \alpha _{j}=0} and one α k = 1 {\displaystyle \alpha _{k}=1} . A raw average is where all α j {\displaystyle \alpha _{j}} are equal to some constant value, namely one over the total number of experts. A more recent ensemble averaging method is negative correlation learning, proposed by Y. Liu and X. Yao. This method has been widely used in evolutionary computing. == Benefits == The resulting committee is almost always less complex than a single network that would achieve the same level of performance The resulting committee can be trained more easily on smaller datasets The resulting committee often has improved performance over any single model The risk of overfitting is lessened, as there are fewer parameters (e.g. neural network weights) which need to be set.

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  Digital fashion

  Digital fashion is a field of fashion design that relies on 3D software or artificial intelligence to produce hyper-realistic, data-intensive digital 3D garment simulations that are digital-only products or digital models for physical products. Digital garments can be worn and presented in virtual environments, social media, online gaming, virtual reality (VR), and augmented reality (AR) platforms. The field aims to contribute to the development of a more sustainable future for the fashion industry. It has been praised as a possible answer to ethical and creative concerns of traditional fashion by promoting innovation, reducing waste, and encouraging conscious consumption. However, empirical research has questioned whether digital fashion communities embody the radical and anti-consumerist values they claim. A 2025 study presented by YeSeung Lee at the FACTUM international conference on fashion communication analysed 88,141 posts across nine platforms over eight months using Pulsar. It found that only 4.8% of author biographies indicated any sociopolitical focus, and that discourse predominantly relied on generic slogans and trending buzzwords, primarily reinforcing existing fashion hierarchies and consumerist frameworks rather than challenging them. Digital fashion is also the interplay between digital technology and couture. Human AI is an intersection of technology and human representation, in which human value is emphasized and enhanced by technology and the possibilities of discovering design. Information and communication technologies (ICTs) have been deeply integrated both into the fashion industry, as well as within the experience of clients and prospects. Such interplay has happened at three main levels. ICTs are used to design and produce fashion products, while the industry organization also leverages digital technologies. ICTs impact marketing, distribution and sales. ICTs are extensively used in communication activities with all relevant stakeholders and contribute to co-create the fashion world. The fashion industry in general has paved the way for digital fashion to be introduced with more technology being in the industry, like virtual dressing rooms and the gamification of the fashion industry. Digital fashion is also seen on many different online fashion retail websites. This evolution in the fashion industry has called for more education and research of digital fashion. == Design, production, and organization == Among the many applications available to fashion designers to model the fusion of creativity with digital avenues, the Digital Textile Printing can be mentioned here. === Digital textile printing === Digital textile printing has brought together the worlds of fashion, technology, art, chemistry, and printing to produce a new process for printing textiles on clothing. Digital printing is a process in which prints are directly applied to fabrics with a printer, reducing 95% of the use of water, 75% of the use of energy and minimizing textile waste. The main advantage of digital printing is the ability to do very small runs of each design (even less than 1 yard). Digital Textile printing also offers other benefits, such as fast printing speeds that help the time and space needed to print different patterns on garments of choice. == Marketing, distribution, and sales == While all digital channels can be used in order to market and sell fashion completely online (eCommerce), they usually are implemented in connection with offline channels (so-called "omni-channel"). Here, virtual and augmented reality play a crucial role. The fashion industry has faced its own problems including pollution and fabric waste, which has resulted in a shift to more sustainable methods like digital fashion. The industry is also constantly being intertwined with digital media and has allowed for the use of digital tools within the business itself and with consumers. Two of the ways digital fashion is utilized with consumers is through virtual dressing rooms and virtual cosmetic counters. Prospects and clients can use ICTs - own computers, tablets and smartphones - to virtually simulate fitting rooms and cosmetics counters and see how they look in specific outfits and makeup. Customers can give any look and decide on what suits them and buy products. Oftentimes, beauty retailers will feature virtual fitting rooms to allow users to experience the look of their product before committing to a purchase. Some examples are color contact retailers Freshlook, which allows users to simulate contact lens wear in their color contacts studio before purchase. Colorful Eyes also offers a virtual color contact lens try-on room. === Virtual dressing room === A virtual dressing room (also often referred to as virtual fitting room and virtual changing room although they do perform different functions) is the online equivalent of the near-ubiquitous in-store changing room – that is, it enables shoppers to try on clothes to check one or more of size, fit or style, but virtually rather than physically. Fashion retailer Topshop installed a Kinect-powered virtual fitting room at its Moscow store. Created by AR Door, the Augmented Fitting Room system overlays 3D augmented reality clothes on the customer. Simple gestures and on-screen buttons let users "try on" different outfits. However, the high variability of virtual fit platforms to predict consumer clothes sizes called into question the accuracy of these systems in their current form. AI-powered Wardrobe and Outfit Planning Beyond virtual fitting rooms, the integration of artificial intelligence has enabled the rise of digital wardrobe management. These platforms use computer vision and machine learning to catalog a user’s physical or digital garments, providing automated outfit recommendations based on weather, occasion, and personal style trends. Fashion-tech startups utilize AI-driven garment simulation to help users plan outfits virtually, bridging the gap between digital-only fashion and physical wardrobe utility. This "smart closet" approach aims to reduce "wardrobe fatigue" and decrease unnecessary consumption by maximizing the use of existing items through digital visualization. === Communication and experience co-creation === Fashion is also a matter of socially negotiating what is "in" or "out", fashionable or not. In other words, fashion items do not only play on the economic market of physical goods but also - and sometimes even more importantly - on the semiotic market of the production of social tastes and customs. Thanks to social media, and to all services offered by the so-called web2.0, laypeople can contribute to co-create the fashion world, shaping tastes, customs, and fashion-related values. Social media, in general, has catapulted the impact fashion has on our everyday lives and values. Fashion has taken a central role in mass production and is constantly evolving due to the ever-lasting digital transformation. Social media has also helped evolve to a point where not only can brands reach consumers, but consumers can reach brands as well. TikTok for example started a trend in 2020 with #GucciModelChallenge. This creates a space where the brand is gaining awareness from their consumers in the ever-changing digital age. === Gamification === Gaming has played an important role in fostering digital aspects of the fashion world, first beginning with dress-up games that used avatars and allowed players to select garments. Nevertheless, it seems it will now move on to the real world and start using avatars of real people. Garments from luxurious brands have been copied and adapted into the aesthetics of games such as Animal Crossing: New Horizons and The Sims. As to the former, during COVID-19 lock-downs players recreated outfits from a variety of fashion brands, including Chanel, Gucci and Versace. It became a platform for users to showcase their costume designs. In April 2019, Moschino collaborated with simulation game The Sims in a capsule collection that featured signature Jeremy Scott garments. The collection was made available to shop and the campaign was set against the backdrop of a Sims-like atmosphere. Furthermore, in May 2019, Nike partnered up with Fortnite to include their iconic Jordan sneakers. In similar fashion, in May 2020, Marc Jacobs designed 6 of the brand's favorite looks for Nintendo's Animal Crossing: New Horizons in a partnership with Instagram user @AnimalCrossingFashionArchive. They were made available to download. Similarly, the other luxury brands mentioned, Louis Vuitton partnered with game League of Legends to create skins for characters within the game. Digital fashion in different video games allows users to express themselves beyond their avatars and combine the self-expression of fashion into the digital gaming realm. == Digital fashion education and research == Nowadays, the fashion industry needs experts in digital fashion, equipped with the above-ske

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