AI Generator Emoji

AI Generator Emoji — independent reviews, comparisons, pricing and step-by-step guides on Aizhi.

  • Ulead MediaStudio Pro

    Ulead MediaStudio Pro

    Ulead MediaStudio Pro (MSP) is real-time, timeline based prosumer level video editing software by Ulead Systems. It is a suite of 5 digital video and audio applications, including: Video Capture, Video Paint, CG Infinity, Audio Editor and Video Editor. MSP is only available on the Windows platform. Since version 8.0, CG Infinity and Video Paint are separate from the MSP suite, and are being sold as a combination product called VideoGraphics Lab (VGL). On June 18, 2008, Corel formally announced that MediaStudio Pro would be discontinued. The final MediaStudio Pro version was 8.10.0039 (Pro 8 Service Pack 1) released June 2, 2006. Corel discontinued support for MediaStudio Pro in June 2009. Version 6.0 is last version to support Windows 95, although recent versions are not compatible with Windows Vista or Windows 7. == Modules == There are 5 stand-alone modules in MSP before version 8.0, they are: Video Capture – The video capturing module in MSP. Video Paint – A frame-by-frame editor which can let user to make some image or hand-drawing effects on video frames. CG Infinity – A vector-based video editing tool which allows user to create logo animation or vector graphics on video frames. Audio Editor – The audio editing tool in MSP. It can utilize DirectX audio filters and Ulead audio filters to do audio effect processing. Video Editor – The module that users do video editing with audio/video effects. It can also utilize DirectX audio filters and 3rd party video filters to do the video editing. Since version 8.0, CG Infinity and Video Paint have been separated from the MSP suite and are being sold as a combination product called VideoGraphics Lab (VGL). == Editions == Ulead MediaStudio Pro had several editions before version 7.0. They are: Full edition: this edition includes all 5 modules. Director's Cut edition: this edition has 3 modules including Video Capture, Video Editor and Audio Editor. SE edition: SE means Simple Edition or Special Edition and is an OEM bundle version. It also includes the 3 modules as Director's Cut, however, is feature limited. Sometimes it will be given freely in video magazines. After version 7.0 only Full edition is available in the MSP suite. On June 18, 2008, Corel formally announced that MediaStudio Pro would be discontinued. == Release history ==

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  • Squirrel AI

    Squirrel AI

    Squirrel Ai Learning is an international educational technology company that specializes in intelligent adaptive learning and was one of the first companies in the world to offer large scale AI-powered adaptive education solutions. == Methodology == Squirrel Ai Learning uses artificial intelligence to tailor lesson plans to each individual student. The company's AI researchers have access to the world's largest student databases, which are used to train the AI algorithms. Squirrel Ai Learning works with teachers to identify the most fine-grained possible concepts ("knowledge points") for a course in order to precisely target learning gaps. For example, middle school mathematics is broken into over 10,000 points such as rational numbers, the properties of a triangle, and the Pythagorean theorem. Each point is linked to related items, forming a "knowledge graph". Each knowledge point is addressed by videos, examples and practice problems. A textbook might address 3,000 points; ALEKS, another adaptive learning platform, uses 1,000. Each student begins with a diagnostic test to identify where to begin their learning. The system continues to refine its graph as more students proceed. Learning is not student-directed. The system decides the order of topics. == History and milestones == Squirrel Ai Learning was founded by Derek Haoyang Li in 2014. In March, 2017, The Squirrel Ai Intelligent Adaptive Learning System (IALS) was launched. IALS utilizes artificial intelligence to customize lessons, practice and evaluations for each individual student. In 2018, Squirrel Ai Learning established a joint research lab of AI adaptive learning with the institute of Automation of the Chinese Academy of Sciences. By 2019, Squirrel Ai Learning had opened 2,000 learning centers in 200 cities and registered over a million students in Asia. In 2019, Squirrel Ai Learning opened a research lab in partnership with Carnegie Mellon University. As of 2019, Squirrel Ai Learning had raised over $180 million in funding and in 2018 it surpassed $1 billion in valuation. In 2020, Squirrel Ai Learning launched the $1 million AAAI Squirrel AI Award for Artificial Intelligence for the Benefit of Humanity in partnership with AAAI. The inaugural award was given to Regina Barzilay for her work developing machine learning models to address drug synthesis and early-stage breast cancer diagnosis. In 2020, Squirrel Ai Learning established strategic partnership with DingTalk, Alibaba Group. As of 2021, Squirrel Ai Learning had served over 60,000 public schools, in over 1200 cities in Asia. Squirrel Ai plans to start offering its services in the United States in 2026. The American arm is separate from the Chinese company to avoid regulatory hurdles. As of January 2026, it had set up an "independent technology platform" in the US. == Recognition == Squirrel Ai Learning has gained recognition both in Asia and internationally including: Squirrel Ai Learning was named one of the World's Top 30 AI application case in the 2018 Synced Machine Intelligence Awards. In June 2019, Squirrel Ai Learning was named as one of the 50 smartest companies in China by MIT technology review. Squirrel Ai Learning won the GITEX 2019 Best Education Technology Award. In 2020, Squirrel Ai Learning won the UNESCO AI Innovation Award. Squirrel Ai Learning was listed in the 2020 CB Insight's AI 100, CB Insights' annual ranking of the 100 most promising AI startups in the world. Squirrel Ai Learning won Edtech Review's Best AI in Education Company of the Year award 2020.

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  • Warframe

    Warframe

    Warframe is a free-to-play action role-playing third-person shooter multiplayer online game developed and published by Digital Extremes. First released for Windows in March 2013, it was later ported to PlayStation 4 in November 2013, Xbox One in September 2014, Nintendo Switch in November 2018, PlayStation 5 in November 2020, Xbox Series X/S in April 2021, iOS in February 2024, Android in Canada on February 11, 2026 followed by a global release on February 18, 2026, and was released on Nintendo Switch 2 on March 25, 2026. Support for cross-platform play was released in 2022. Cross-platform save began in December 2023, rolling out in waves to different groups of players before becoming fully available to all players in January 2024. In Warframe, a player controls a member of the Tenno, a caste of ancient warriors who have awoken from centuries of suspended animation far into Earth's future to find themselves at war with different factions in the Origin System. The Tenno use their powered Warframes, along with a variety of weapons and abilities, to complete missions. While many of the game's missions use procedurally generated levels, it also includes large open world areas similar to other massively multiplayer online games, as well as some story-specific missions with fixed level design. The game includes elements of shooting and melee games, parkour, and role-playing to allow players to advance their Tenno with improved gear. The game features both player versus environment and player versus player elements. It is supported by microtransactions, allowing players to purchase in-game items with money, while also offering the option to earn them at no cost through grinding. The concept for Warframe originated in 2000 when Digital Extremes began work on a new game titled Dark Sector. At the time, the company had been successful in supporting other developers and publishers but wanted to develop its own game in-house. Dark Sector suffered several delays and was eventually released in 2008, incorporating some of the initial framework but differing significantly from the original plan. By 2012, in the wake of the success of free-to-play games, the developers took their earlier Dark Sector ideas and art assets and incorporated them into a new project, their self-published Warframe. Initially, the growth of Warframe was slow, hindered by moderate critical reviews and low player counts. However, since its release, the game has experienced significant growth. It is one of Digital Extremes' most successful titles, reaching nearly 50 million registered players by 2019. == Plot == Warframe is set in a far future version of the Solar System, now known as the Origin System. At the start of the game players are given control of members of the Tenno, warriors who have awoken from a millennia-long cryosleep on Earth by the Lotus, who acts as a guide for the player. They join an interplanetary war between the Grineer, a violent war-driven matriarchal race of militarized human clones; the Corpus, a cult-like megacorporation dedicated to profit; the Infested, disfigured victims of the Technocyte virus; the Sentients, a race of self-replicating machines made by a long-dead transhuman race known as the Orokin; and the Corrupted, brainwashed variants of the previous three factions' units defending ancient Orokin towers. All of the factions encountered in the game, including the Tenno, were created by or are splinter groups of the old Orokin Empire, which the Tenno learns was an ancient fallen civilization and former reigning power in the Origin System. Although virtually all of them are long dead by the time of the Tenno's awakening, their lingering presence can still be felt throughout the Origin System. Before their fall, the Orokin had realized the Origin System was becoming dangerously depleted of resources, and their solution to keep their empire alive was to colonize new star systems. The Orokin sent out colony ships through the Void, a trans-dimensional space that enabled fast travel between stellar systems. They had also sent out the Sentients beforehand, to arrive in the Tau system first, and terraform it, so the colonists would arrive to garden worlds, capable of supporting human life. None of these residential ships returned, and those they had loaded with Sentients returned with the Sentients now deciding to wipe out the Orokin, leading to the Old War, the creation of the Tenno, and finally, the collapse of the Empire. In the game's "The Second Dream" quest, which was introduced in December 2015, the player discovers that the Lotus is a Sentient known as Natah, rebelling against the Sentients to protect the Tenno, desiring to have surrogate children after losing her ability to procreate. The Lotus' father, Hunhow, sends a vengeful assassin called the Stalker to Lua (the remains of Earth's Moon), which the Lotus had hidden in the Void, to find its secret. The Lotus dispatches the Tenno there to stop the Stalker, arriving too late as the Stalker unveils the entity that the Lotus had protected: a human child known as the Operator, who is the real Tenno controlling the Warframes through the course of the game. The Operator is one of several Tenno children that survived the passage of the Zariman Ten 0 colony ship through the Void; the adults have all gone mad from its travel. When the ship returned to the Orokin Empire, the children had all been put to sleep for thousands of years, outlasting the fall of the Empire, to be found by the Lotus and becoming the Tenno (Tenno short for the "Ten Zero" of the ship's name). The power of the Void gave these children the power of Transference, an ability that allows them to control Warframes. From this point forward, the player can then engage in missions both as the Warframe and the Operator. Throughout various updates, various quests have been released after the Second Dream that elaborates on the story. "The War Within" quest introduced the Grineer Queens, rulers of the Grineer, and their asteroid-based Kuva Fortress, also giving the Operator the ability to act fully on their own as another playable entity, rather than a single-use attack. Quests afterward would introduce figures such as "The Man In The Wall," a mysterious entity, presumably from the Void, who takes on the visage of whoever sees them, most often as the playable Operator, and Ballas, one of the last living Orokin, assumed to be responsible for creating the Warframes. == Gameplay == Warframe is an online action game that includes elements of shooters, RPG, and stealth games. The player starts with a silent pseudo-protagonist in the form of an anthropomorphous biomechanical combat unit called a 'Warframe', possessing supernatural agility and special abilities, a selection of weapons (primary, secondary, and melee) and a space ship called an 'Orbiter'. The Orbiter is supported by a Cephalon, a type of Artificial Intelligence created from the minds of living people. The Cephalon in the player's Orbiter is named Ordis, and refers to the player as 'Operator'. The player's primary goal from this point is to explore the Origin System. Later in the course of the game, the player unlocks the ability to gain direct control of the Operator, which is the true Tenno protagonist in physical form. The Operator can physically manifest themselves in the environment by projecting out of the Warframe, and disappear by resuming control of it through a telekinetic process called 'Transference'. The Operator also possesses weapons and abilities of their own. After that, the Operator can use Transference to control a larger, purely mechanical combat unit called a 'Necramech', which is the technological precursor to the Warframes. Players can engage in space-bound combat using an auxiliary combat platform called 'Archwing', mounted on a Warframe, which comes with a unique set of abilities. 'Archguns' are heavy weapons designed for Archwings and Necramechs, but can be adapted for Warframe use. Late in 2019, an update to the game allowed players to pilot and manage a spacefaring gunship called the 'Railjack', which is deployed in combat, unlike the Orbiter. Railjack was designed as a co-op experience with up to four people working together, performing different tasks to keep the ship operational while destroying enemy ships and completing objectives. A Railjack-focused update was released in 2021, which brought expanded content and a new skill tree system aimed at making solo play more accessible. Through the Orbiter's console, the player can select any of the missions available to them. To progress through the Solar System, players must complete mission 'nodes' on each planet to reach Junctions, and use these Junctions to travel to other planets. Other missions rotate over time as part of the game's living universe; these can include missions with special rewards and community challenges to allow all players to reap benefits if they are successfully met. High-di

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  • Void Trilogy

    Void Trilogy

    The Void Trilogy is a space opera series by British author Peter F. Hamilton. The series is set in the same universe as The Commonwealth Saga, 1,200 years after the end of Judas Unchained. Peter F. Hamilton sold the American rights to the series to Random House. The series includes the following books: The Dreaming Void (2007) The Temporal Void (2008) The Evolutionary Void (2010) == Synopsis == === The Dreaming Void === What was formerly believed to be a supermassive black hole at the centre of the Milky Way is revealed to be an artificial construct, known as the Void. Inside, there is a strange universe where the laws of physics are very different from standard physics. It is slowly consuming the other stars of the galactic core—one day it will have devoured the entire galaxy. In AD 3320, a human member of the Commonwealth, Inigo, begins to have dreams of the wonderful existence inside the Void. His dreams inspire the disaffected, who desire to travel into the Void, where their every wish will be fulfilled. By AD 3456, the pseudo-religious Living Dream movement exceeds 5 billion members, organizing the followers into a powerful political force. Other star-faring species fear their migration will cause the Void to expand again thus devouring the galaxy. They are prepared to stop the pilgrimage fleet no matter what the cost. The Dreaming Void is broken into two distinct sections. The first follows Edeard, a young boy who lives inside the Void on a planet called Querencia, the subject of Inigo's dreams. Edeard, an orphan and apprentice, lives in Ashwell, a town in Rulan province. A gifted psychic, he is trained by Master Akeem in crafting and modding. Initially a loner, he comes to prominence in his village after designing an alternative pump mechanism for the local well. Unfortunately his luck changes for the worse after Ashwell is raided by bandits. Forced to flee, he joins the local caravan and travels to Makkathran, the capital of Querencia. In Makkathran, Edeard joins the constables and after a brutal couple of months in training, he graduates and is promoted to the commander of his Squad. He makes little progress battling the rigid and backward judicial system of Makkathran; his first real break is when his squad overcomes a trap set by the local gang, and Edeard walks on water chasing the leader of the gang. A testament to his growing psychic abilities, Edeard's stunt earns him the title of Waterwalker, and he becomes an instant star in Makkathran. The second section of The Dreaming Void is set back in the Commonwealth. Inigo, the first dreamer, and founder of Living Dream, has disappeared, leaving the 5 billion strong Living Dream movement in a state of flux. When Ethan, succeeding Inigo as the head of the movement, proclaims that the Living Dream will embark on a pilgrimage into the Void, the Commonwealth is thrown into a state of political chaos. Fearing that the human migration might cause the Void to expand (and in the process destroy whole systems or even the whole Galaxy) other spacefaring races such as the Raiel and Ocisen Empire are deeply concerned, with the latter threatening military action. This has left the Commonwealth government deeply divided, with the two largest factions in disagreement, the Accelerators faction/party supporting the pilgrimage and the Conservative faction opposing. As both parties are unable to solve the situation politically they have resolved to take matters into their own hands, with each party sending agents to further its interests. Aaron, a sleeper cell agent, is tasked with finding Inigo. He kidnaps and manipulates Corrie-Lyn, a former lover of Inigo and interrogates her for information. He also travels to Kuhmo (Inigo's homeworld) to get further information and robs Inigo's secure storage (a bank for memory). He eventually tracks Inigo to Hanko, a desolate and barren world. However, before Aaron can extract Inigo, Accelerator agents destroy Aaron's starship leaving him marooned on Hanko. Meanwhile, Accelerator agents make a deal with Ethan, agreeing to give the Living Dream movement Ultra Drives to power their ships. Accelerator plans are halted when the Delivery Man, a Conservative party agent, destroys valuable FTL Drive tech. Troblum, an Accelerator physicist, also defects, further slowing the Accelerators plans. === The Temporal Void === The Temporal Void picks up after The Dreaming Void. The Intersolar Commonwealth faces mounting turmoil as the deadline for Living Dream's Pilgrimage into the Void approaches. An Ocisen Empire fleet advances on a mission of genocide, while an internecine war erupts among post-human factions over humanity's future. Amidst the chaos, investigator Paula Myo struggles to counter the increasingly desperate actions of various agents and factions. Relentless in her pursuit, she contends with adversaries from her distant past and colleagues of uncertain loyalty, all while racing against time. At the center of the unfolding crisis is Edeard the Waterwalker, a figure from the distant past who lived deep within the Void. As the messiah of Living Dream, his life—broadcast through visions—captivates and inspires billions. His story fuels the Pilgrimage's momentum, a force seemingly impossible to stop. As Edeard approaches his ultimate victory, the true nature of the Void is finally revealed. === The Evolutionary Void === The Evolutionary Void picks up after The Temporal Void. Exposed as the Second Dreamer, Araminta has become the target of a galaxy-wide search by government agent Paula Myo and the psychopath known as the Cat, along with others equally determined to prevent, or facilitate, the pilgrimage of the Living Dream cult into the heart of the Void. An indestructible microuniverse, the Void may contain paradise, as the cultists believe, but it is also a deadly threat. For the miraculous reality that exists inside its boundaries demands energy, energy drawn from everything outside those boundaries: from planets, stars, galaxies, and everything that lives, for the Pilgrimage will trigger a super-massive expansion of the Void. Meanwhile, the parallel story of Edeard, the Waterwalker, as told through a series of dreams communicated to the gaiafield via Inigo, the First Dreamer, continues to unfold. But the inspirational tale of this idealistic young man takes a darker and more troubling turn as he finds himself faced with powerful new enemies, and temptations more powerful still, to reach fulfilment in the end. Named a Silfen Friend like her ancestress Mellanie, Araminta chooses to face her unwanted responsibilities, with no guarantee of success or survival. She takes on the role of Second Dreamer to lead the first wave of Living Dream, 24 million people, into the Void, leaving everyone confused and lost by her actions. However, in actuality, she is playing a double game. Using her original body to lead the Living Dream as a diversion, she borrows one of her fiancé's (Mr. Bovey) bodies to set out to destroy the Void. She is able to connect with a Skylord and travel the Silfen Paths. With time running out, a repentant Inigo decides to release Edeard's final dream whose message is scarcely less dangerous than the pilgrimage promises to be, where perfection is achieved, so that nothing else is left to strive for and the human race in the Void has started to devolve. He goes to the Spike to meet Ozzie and stays there to meet with Araminta, who is using one of her fiancé's bodies, and Oscar. Third Dreamer Gore Burnelli has a plan to reason with the Heart, the core of the Void. He secures the help of the Delivery Man and travels to the Anomine homeworld to retrieve the mechanism that allowed them to go post-physical. He is able to connect with Justine, his daughter, who is currently in the Void, by way of Dreams. The monomaniacal Ilanthe, leader of the breakaway Accelerator Faction, seeks dominion in the Void. It is not Fusion with the Void to attain post-physical status that she wants, but to have control over everything. Using Dark Fortress technology, she sets up a barrier around the Sol system which leaves ANA and the deterrence fleet trapped inside. It is this technology which she has equipped the ships travelling to the Void with, the ability to create a forcefield which the Warrior Raiel cannot penetrate. == Technology == The Commonwealth uses a number of advanced technologies. In the early days of the Commonwealth, humans used static and permanently opened wormholes to travel from planet to planet. However, after the events of the Starflyer War (detailed in the Commonwealth Saga), the CST corporation's monopoly on space travel was ended. With the advent of wormholes that could wrap around ships, the Commonwealth saw a shift from wormholes to spaceships. Another development in the Commonwealth is the gaiafield. Developed by Ozzie Issac in AD 3000, the gaiafield is based on Silfen technology; when Ozzie was named a friend of the Silfen during the Starflye

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  • Motor theory of speech perception

    Motor theory of speech perception

    The motor theory of speech perception is the hypothesis that people perceive spoken words by identifying the vocal tract gestures with which they are pronounced rather than by identifying the sound patterns that speech generates. It originally claimed that speech perception is done through a specialized module that is innate and human-specific. Though the idea of a module has been qualified in more recent versions of the theory, the idea remains that the role of the speech motor system is not only to produce speech articulations but also to detect them. The hypothesis has gained more interest outside the field of speech perception than inside. This has increased particularly since the discovery of mirror neurons that link the production and perception of motor movements, including those made by the vocal tract. The theory was initially proposed in the Haskins Laboratories in the 1950s by Alvin Liberman and Franklin S. Cooper, and developed further by Donald Shankweiler, Michael Studdert-Kennedy, Ignatius Mattingly, Carol Fowler and Douglas Whalen. == Origins and development == The hypothesis has its origins in research using pattern playback to create reading machines for the blind that would substitute sounds for orthographic letters. This led to a close examination of how spoken sounds correspond to the acoustic spectrogram of them as a sequence of auditory sounds. This found that successive consonants and vowels overlap in time with one another (a phenomenon known as coarticulation). This suggested that speech is not heard like an acoustic "alphabet" or "cipher," but as a "code" of overlapping speech gestures. === Associationist approach === Initially, the theory was associationist: infants mimic the speech they hear and that this leads to behavioristic associations between articulation and its sensory consequences. Later, this overt mimicry would be short-circuited and become speech perception. This aspect of the theory was dropped, however, with the discovery that prelinguistic infants could already detect most of the phonetic contrasts used to separate different speech sounds. === Cognitivist approach === The behavioristic approach was replaced by a cognitivist one in which there was a speech module. The module detected speech in terms of hidden distal objects rather than at the proximal or immediate level of their input. The evidence for this was the research finding that speech processing was special such as duplex perception. === Changing distal objects === Initially, speech perception was assumed to link to speech objects that were both the invariant movements of speech articulators the invariant motor commands sent to muscles to move the vocal tract articulators This was later revised to include the phonetic gestures rather than motor commands, and then the gestures intended by the speaker at a prevocal, linguistic level, rather than actual movements. === Modern revision === The "speech is special" claim has been dropped, as it was found that speech perception could occur for nonspeech sounds (for example, slamming doors for duplex perception). === Mirror neurons === The discovery of mirror neurons has led to renewed interest in the motor theory of speech perception, and the theory still has its advocates, although there are also critics. == Support == === Nonauditory gesture information === If speech is identified in terms of how it is physically made, then nonauditory information should be incorporated into speech percepts even if it is still subjectively heard as "sounds". This is, in fact, the case. The McGurk effect shows that seeing the production of a spoken syllable that differs from an auditory cue synchronized with it affects the perception of the auditory one. In other words, if someone hears "ba" but sees a video of someone pronouncing "ga", what they hear is different—some people believe they hear "da". People find it easier to hear speech in noise if they can see the speaker. People can hear syllables better when their production can be felt haptically. === Categorical perception === Using a speech synthesizer, speech sounds can be varied in place of articulation along a continuum from /bɑ/ to /dɑ/ to /ɡɑ/, or in voice onset time on a continuum from /dɑ/ to /tɑ/ (for example). When listeners are asked to discriminate between two different sounds, they perceive sounds as belonging to discrete categories, even though the sounds vary continuously. In other words, 10 sounds (with the sound on one extreme being /dɑ/ and the sound on the other extreme being /tɑ/, and the ones in the middle varying on a scale) may all be acoustically different from one another, but the listener will hear all of them as either /dɑ/ or /tɑ/. Likewise, the English consonant /d/ may vary in its acoustic details across different phonetic contexts (the /d/ in /du/ does not technically sound the same as the one in /di/, for example), but all /d/'s as perceived by a listener fall within one category (voiced alveolar plosive) and that is because "linguistic representations are abstract, canonical, phonetic segments or the gestures that underlie these segments." This suggests that humans identify speech using categorical perception, and thus that a specialized module, such as that proposed by the motor theory of speech perception, may be on the right track. === Speech imitation === If people can hear the gestures in speech, then the imitation of speech should be very fast, as in when words are repeated that are heard in headphones as in speech shadowing. People can repeat heard syllables more quickly than they would be able to produce them normally. === Speech production === Hearing speech activates vocal tract muscles, and the motor cortex and premotor cortex. The integration of auditory and visual input in speech perception also involves such areas. Disrupting the premotor cortex disrupts the perception of speech units such as plosives. The activation of the motor areas occurs in terms of the phonemic features which link with the vocal track articulators that create speech gestures. The perception of a speech sound is aided by pre-emptively stimulating the motor representation of the articulators responsible for its pronunciation . Auditory and motor cortical coupling is restricted to a specific range of neuronal firing frequency. === Perception-action meshing === Evidence exists that perception and production are generally coupled in the motor system. This is supported by the existence of mirror neurons that are activated both by seeing (or hearing) an action and when that action is carried out. Another source of evidence is that for common coding theory between the representations used for perception and action. == Criticisms == The motor theory of speech perception is not widely held in the field of speech perception, though it is more popular in other fields, such as theoretical linguistics. As three of its advocates have noted, "it has few proponents within the field of speech perception, and many authors cite it primarily to offer critical commentary".p. 361 Several critiques of it exist. === Multiple sources === Speech perception is affected by nonproduction sources of information, such as context. Individual words are hard to understand in isolation but easy when heard in sentence context. It therefore seems that speech perception uses multiple sources that are integrated together in an optimal way. === Production === The motor theory of speech perception would predict that speech motor abilities in infants predict their speech perception abilities, but in actuality it is the other way around. It would also predict that defects in speech production would impair speech perception, but they do not. However, this only affects the first and already superseded behaviorist version of the theory, where infants were supposed to learn all production-perception patterns by imitation early in childhood. This is no longer the mainstream view of motor-speech theorists. === Speech module === Several sources of evidence for a specialized speech module have failed to be supported. Duplex perception can be observed with door slams. The McGurk effect can also be achieved with nonlinguistic stimuli, such as showing someone a video of a basketball bouncing but playing the sound of a ping-pong ball bouncing. As for categorical perception, listeners can be sensitive to acoustic differences within single phonetic categories. As a result, this part of the theory has been dropped by some researchers. === Sublexical tasks === The evidence provided for the motor theory of speech perception is limited to tasks such as syllable discrimination that use speech units not full spoken words or spoken sentences. As a result, "speech perception is sometimes interpreted as referring to the perception of speech at the sublexical level. However, the ultimate goal of these studies is presumably to understand the neural processes supporting the ability to process spee

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  • Padre Pio (2022 film)

    Padre Pio (2022 film)

    Padre Pio is a 2022 biographical drama film co-written and directed by Abel Ferrara. It stars Shia LaBeouf as the titular role of Padre Pio, a Capuchin Franciscan priest who receives the stigmata, in the background of the World War I in Italy. The film is a co-production of Italy, Germany and the United Kingdom. During its production, LaBeouf converted to Catholicism as result of his spiritual experiences in character as Pio, who is venerated as a saint by the Catholic Church. The film had its world premiere in the Giornate degli Autori section of the 79th Venice International Film Festival on 2 September 2022. It was released theatrically in the United Kingdom on 26 January 2024 by Dazzler Media and in Italy on 18 July 2024 by RS Productions. == Plot == It is the year 1920. Italian WWI veterans have returned to their impoverished villages. Padre Pio arrives at San Giovanni Rotondo after living with his family in Pietrelcina for a number of years. While still sick, he continues to encounter Satan. Satan reveals himself as the instigator of the war and the sociopolitical problems of San Giovanni. While having little contact with the people of this town, Padre Pio learns what the poor are suffering from in the Sacrament of Confession and the Holy Mass, such as when a crippled man walks again because of Padre Pio's prayer. Besides the effects of war, such as medical inadequacy, health conditions and labourers dying from the effects of mustard gas, the people suffer from corrupt, wealthy landowners. Gerardo, a militaristic anti-socialist, threatens to kill any communal labourers tending his land. Many of them join the socialist party as a way to improve their lives. However, after they win the first free election in San Giovanni, Gerardo's forces massacre many of them. Padre Pio asks God that he may become a suffering servant for their salvation. He receives the wounds of Jesus Christ. The stigmata disrupts Satan's influence on San Giovanni Rotondo. == Cast == Shia LaBeouf as Padre Pio Marco Leonardi as Gerardo Salvatore Ruocco as Vincenzo Cristina Chiriac as Giovanna Brando Pacitto as Renato Luca Lionello as Silvestro Asia Argento as Tall Man == Production == According to Abel Ferrara, actor Willem Dafoe suggested that Shia LaBeouf should be cast for the film's leading role. After Ferrara held several Zoom calls with LaBeouf, the latter agreed to join the film, even though very little money was raised (the film was almost never made) and LaBeouf did the project for free. LaBeouf arrived at Old Mission Santa Inés in July 2021 to learn about Padre Pio with the Capuchin Franciscan friars. Thanks to Father Bobby Barbato and Brother Jude Quinto, Br. Alexander Rodriguez met LaBeouf while he attended Mass every day. He learned about the Catholic Church and the Capuchins while living in his truck or spending a few nights in the Capuchin's guest room. He was immersing himself in the Catholic faith. He enrolled in RCIA, revised the script with Rodriguez and trained to do the Latin Mass. Rodriguez traveled with LaBeouf as his spiritual adviser and catechist and was in the film as Padre Pio's companion. Filming occurred in Apulia, Italy, in December 2021. The first place was at the Capuchin friary in San Marco la Catola. Padre Pio exchanged letters with his provincial and spiritual director while living in Pietrelcina with his family. The time was around 1909–1916. Both directors were living in San Marco during these years. Padre Pio expressed in his letters his deep and mysterious relationship with God and health difficulties. This event is in the film. While filming, LaBeouf slept in Padre Pio's bedroom. After San Marco, filming continued outside the Sanctuary of Saint Michael the Archangel in Monte Sant'Angelo. Traditionally, St. Michael appeared here in the late 400s. LaBeouf stayed and filmed for a few weeks at the Abbey of Saint Mary of Pulsano. It is near the sanctuary. The rest of the filming took place outside the sanctuary. Ferrara said in 2024 that he used AI for the Italian dub of this film. == Release == Padre Pio had its world premiere in the Giornate degli Autori section of the 79th Venice International Film Festival on 2 September 2022. It received a four-minute ovation. It also competed at the Rio de Janeiro International Film Festival. At the Lisbon & Estoril Film Festival, it was chosen to compete for the "Best Film Award." During its North American premiere at the Mammoth Film Festival, it won the "Achievement for Filmmaking" award for cinematography. At the Taormina Film Festival, it premiered worldwide in Italian. In March 2023, Gravitas Ventures acquired North American rights to the film. It was released in select theaters and on video on demand in the United States on 2 June 2023. The film was released in the United Kingdom and Ireland on 26 January 2024 by Dazzler Media. RS Productions released it in Italy on 18 July 2024. == Reception == On the review aggregator website Rotten Tomatoes, the film holds an approval rating of 30% based on 43 reviews, with an average rating of 4.5/10. The website's critics consensus reads, "Tonally unbalanced and burdened with a distracting Shia LaBeouf performance, Padre Pio is one of Abel Ferrara's less divine works." Metacritic, which uses a weighted average, assigned the film a score of 45 out of 100, based on 6 critics, indicating "mixed or average" reviews.. Jordan Mintzer of The Hollywood Reporter gave the film a negative review, describing it as "clunky" and criticizing its political themes for possessing "the subtlety of a cartoon for preschoolers." Brian Tallerico of RogerEbert.com gave the film one and a half stars out of four, describing it as a "dull slog". Journalist Glenn Kenny of The New York Times found the film "occasionally rank" and panned LaBeouf's performance, though complimented Ferrara's "sometimes Brechtian consideration of the nodes of political history and spirituality." Film critic Armond White of National Review also criticized the film, describing it as "a work of deluded, semi-improvisational navel-gazing". Film critic Peter Bradshaw of The Guardian gave the film a positive review, with three out of five stars, writing that it is "a weird film...with an undeveloped, improvised feel, like a fragment or shard of something else. Yet there is a background hum there...an awareness of something dark and malign. It is a minor film but interesting." Writing for The New Yorker, Richard Brody considered that "in its hectic, scattershot way, Padre Pio feels very much of the desperate present day," describing it as "a historical drama without historical distance" and "a wild effort to reach the immediate experience of the past and its furies." Faith-based reviews for the film were generally negative. It received negative reviews from Catholic Answers, The Catholic World Report, The Catholic Weekly, The Catholic Thing, and Crisis Magazine. Conversely, it received a mixed review from The Catholic Review, as well as a positive review from America. Criticisms were generally aimed at the film's sexual content and perceived support of left-wing politics.

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  • Emma Hart (computer scientist)

    Emma Hart (computer scientist)

    Professor Emma Hart, FRSE (born 1967) is an English computer scientist known for her work in artificial immune systems (AIS), evolutionary computation and optimisation. She is a professor of computational intelligence at Edinburgh Napier University, editor-in-chief of the Journal of Evolutionary Computation (MIT Press), and D. Coordinator of the Future & Emerging Technologies (FET) Proactive Initiative, Fundamentals of Collective Adaptive Systems. == Early life and education == Hart was born in Middlesbrough, England in 1967. In 1990 she graduated from the University of Oxford with a first class BA(Hons) in Chemistry. She then continued her studies at the University of Edinburgh, graduating with an MSc in Artificial Intelligence in 1994, followed by a PhD that explored the use of immunology as an inspiration for computing, examining a range of techniques applied to optimization and data classification problems. Her dissertation was titled Immunology as a metaphor for computational information processing: Fact or fiction?, and her doctoral advisor was Peter Ross. == Career == In 2000 Hart took a position as a lecturer at Edinburgh Napier University, and was promoted to a Reader, Professor, and in 2008 Chair in Natural Computation. She is now director of the Centre of Algorithms, Visualisation and Evolving Systems (CAVES) group in the School of Computing. She continues to research in the area of developing novel bio-inspired techniques for solving a range of real-world optimisation and classification problems, as well as exploring the fundamental properties of immune-inspired computing through modelling and simulation. She is also involved in editorial activity and currently occupies the position of Editor-in-Chief of the Journal of Evolutionary Computation (MIT Press). Her interests lie in the area of bio-inspired computing, in particular artificial immune systems (AIS). She also undertakes research in three main areas: optimisation, self-organising/self-adaptive systems, and artificial intelligence. Hart is D. Coordinator of Fundamentals of Collective Adaptive Systems (FoCAS), a Future and Emerging Technologies Proactive Initiative funded by the European Commission under FP7. == Selected works == === Conference talks === Hart, Emma. "Lifelong learning in optimization (video)". 28th European Conference on Operational Research. The Association of European Operational Research Societies. Hart, Emma (December 2021). "Self-assembling robots and the potential of artificial evolution". TED talk 2021. === Journal articles === "An immune system approach to scheduling in changing environments". E.Hart, P.Ross. 1999. Proceedings of the 1st Annual Conference on Genetic and Evolutionary Computation (2), 1559–1566. "Exploiting the analogy between immunology and sparse distributed memories: A system for clustering non-stationary data". E.Hart, P.Ross. 2002. 1st International Conference on Artificial Immune Systems. "Evolutionary scheduling: A review". E Hart, P Ross, D Corne. 2005. Genetic Programming and Evolvable Machines 6(2), 191–220. DOI: https://doi.org/10.1007/s10710-005-7580-7 "Application areas of AIS: The past, the present and the future". E.Hart, J.Timmis. 2008. Applied soft computing 8(1), 191–201. DOI: https://doi.org/10.1016/j.asoc.2006.12.004 "Structure versus function: a topological perspective on immune networks". E.Hart, H.Bersini, F.Santos. 2010. Natural computing 9(3), 603–624. DOI: https://doi.org/10.1007/s11047-009-9138-8 "On the life-long learning capabilities of a nelli: A hyper-heuristic optimisation system". E.Hart, K.Sim. 2014. International Conference on Parallel Problem Solving from Nature, 282–291. DOI: https://doi.org/10.1007/978-3-319-10762-2_28 "A hyper-heuristic ensemble method for static job-shop scheduling". E.Hart, K.Sim. 2016. Evolutionary computation 24(4), 609-635. DOI: https://dx.doi.org/10.1162/EVCO_a_00183 == Awards and recognition == 2016, Featured article on Lifelong Learning in Optimisation, IFORS newsletter 2016, "A Combined Generative and Selective Hyper-heuristic for the Vehicle Routing Problem" presented at GECCO 2016 (Denver, USA), ACM 2016, "A Hybrid Parameter Control Approach Applied to a Diversity-based Multi-objective Memetic Algorithm for Frequency Assignment Problems" presented at WCCI 2016 (Vancouver, Canada), IEEE 2017, Keynote Speaker, 2017 International Joint Conference on Computational Intelligence 2018, Bronze Award in International Human-Competitive Awards (Humies), International Conference on Genetic and Evolutionary Computation, Kyoto Japan 2018, Nomination for best paper award, GECCO 18, Kyoto, Japan 2022, Elected Fellow of the Royal Society of Edinburgh

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  • Evolutionary acquisition of neural topologies

    Evolutionary acquisition of neural topologies

    Evolutionary acquisition of neural topologies (EANT/EANT2) is an evolutionary reinforcement learning method that evolves both the topology and weights of artificial neural networks. It is closely related to the works of Angeline et al. and Stanley and Miikkulainen. Like the work of Angeline et al., the method uses a type of parametric mutation that comes from evolution strategies and evolutionary programming (now using the most advanced form of the evolution strategies CMA-ES in EANT2), in which adaptive step sizes are used for optimizing the weights of the neural networks. Similar to the work of Stanley (NEAT), the method starts with minimal structures which gain complexity along the evolution path. == Contribution of EANT to neuroevolution == Despite sharing these two properties, the method has the following important features which distinguish it from previous works in neuroevolution. It introduces a genetic encoding called common genetic encoding (CGE) that handles both direct and indirect encoding of neural networks within the same theoretical framework. The encoding has important properties that makes it suitable for evolving neural networks: It is complete in that it is able to represent all types of valid phenotype networks. It is closed, i.e. every valid genotype represents a valid phenotype. (Similarly, the encoding is closed under genetic operators such as structural mutation and crossover.) These properties have been formally proven. For evolving the structure and weights of neural networks, an evolutionary process is used, where the exploration of structures is executed at a larger timescale (structural exploration), and the exploitation of existing structures is done at a smaller timescale (structural exploitation). In the structural exploration phase, new neural structures are developed by gradually adding new structures to an initially minimal network that is used as a starting point. In the structural exploitation phase, the weights of the currently available structures are optimized using an evolution strategy. == Performance == EANT has been tested on some benchmark problems such as the double-pole balancing problem, and the RoboCup keepaway benchmark. In all the tests, EANT was found to perform very well. Moreover, a newer version of EANT, called EANT2, was tested on a visual servoing task and found to outperform NEAT and the traditional iterative Gauss–Newton method. Further experiments include results on a classification problem.

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  • Inverse consistency

    Inverse consistency

    In image registration, inverse consistency measures the consistency of mappings between images produced by a registration algorithm. The inverse consistency error, introduced by Christiansen and Johnson in 2001, quantifies the distance between the composition of the mappings from each image to the other, produced by the registration procedure, and the identity function, and is used as a regularisation constraint in the loss function of many registration algorithms to enforce consistent mappings. Inverse consistency is necessary for good image registration but it is not sufficient, since a mapping can be perfectly consistent but not register the images at all. == Definition == Image registration is the process of establishing a common coordinate system between two images, and given two images I 1 : Ω 1 → R I 2 : Ω 2 → R {\displaystyle {\begin{aligned}I_{1}:\Omega _{1}\to \mathbb {R} \\I_{2}:\Omega _{2}\to \mathbb {R} \end{aligned}}} registering a source image I 1 {\displaystyle I_{1}} to a target image I 2 {\displaystyle I_{2}} consists of determining a transformation f 1 : Ω 2 → Ω 1 {\displaystyle f_{1}:\Omega _{2}\to \Omega _{1}} that maps points from the target space to the source space. An ideal registration algorithm should not be sensitive to which image in the pair is used as source or target, and the registration operator should be antisymmetric such that the mappings f 1 : Ω 2 → Ω 1 f 2 : Ω 1 → Ω 2 {\displaystyle {\begin{aligned}f_{1}:\Omega _{2}\to \Omega _{1}\\f_{2}:\Omega _{1}\to \Omega _{2}\end{aligned}}} produced when registering I 1 {\displaystyle I_{1}} to I 2 {\displaystyle I_{2}} and I 2 {\displaystyle I_{2}} to I 1 {\displaystyle I_{1}} respectively should be the inverse of each other, i.e. f 2 = f 1 − 1 {\displaystyle f_{2}=f_{1}^{-1}} and f 1 = f 2 − 1 {\displaystyle f_{1}=f_{2}^{-1}} or, equivalently, f 2 ∘ f 1 = id Ω 2 {\displaystyle f_{2}\circ f_{1}=\operatorname {id} _{\Omega _{2}}} and f 1 ∘ f 2 = id Ω 1 {\displaystyle f_{1}\circ f_{2}=\operatorname {id} _{\Omega _{1}}} , where ∘ {\displaystyle \circ } denotes the function composition operator. Real algorithms are not perfect, and when swapping the role of source and target image in a registration problem the so obtained transformations are not the inverse of each other. Inverse consistency can be enforced by adding to the loss function of the registration a symmetric regularisation term that penalises inconsistent transformations ∫ Ω 2 ‖ f 2 ( f 1 ( x ) ) − x ‖ 2 d x + ∫ Ω 1 ‖ f 1 ( f 2 ( x ) ) − x ‖ 2 d x . {\displaystyle \int _{\Omega _{2}}\left\Vert f_{2}(f_{1}(x))-x\right\Vert ^{2}\mathrm {d} x+\int _{\Omega _{1}}\left\Vert f_{1}(f_{2}(x))-x\right\Vert ^{2}\mathrm {d} x.} Inverse consistency can be used as a quality metric to evaluate image registration results. The inverse consistency error ( I C E {\displaystyle ICE} ) measures the distance between the composition of the two transforms and the identity function, and it can be formulated in terms of both average ( I C E a {\displaystyle ICE_{a}} ) or maximum ( I C E m {\displaystyle ICE_{m}} ) over a region of interest Ω {\displaystyle \Omega } of the image: I C E a = 1 ∫ Ω d x ∫ Ω ‖ f 2 ( f 1 ( x ) ) − x ‖ d x I C E m = max x ∈ Ω ‖ f 2 ( f 1 ( x ) ) − x ‖ . {\displaystyle {\begin{aligned}ICE_{a}&={\frac {1}{\int _{\Omega }\mathrm {d} x}}\int _{\Omega }\left\Vert f_{2}(f_{1}(x))-x\right\Vert \mathrm {d} x\\ICE_{m}&=\max _{x\in \Omega }\left\Vert f_{2}(f_{1}(x))-x\right\Vert .\end{aligned}}} While inverse consistency is a necessary property of good registration algorithms, inverse consistency error alone is not a sufficient metric to evaluate the quality of image registration results, since a perfectly consistent mapping, with no other constraint, may be not even close to correctly register a pair of images.

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  • ECML PKDD

    ECML PKDD

    ECML PKDD, the European Conference on Machine Learning Principles and Practice of Knowledge Discovery in Databases, is one of the leading academic conferences on machine learning and knowledge discovery, held in Europe every year. == History == ECML PKDD is a merger of two European conferences, European Conference on Machine Learning (ECML) and European Conference on Principles and Practice of Knowledge Discovery in Databases (PKDD). ECML and PKDD have been co-located since 2001; however, both ECML and PKDD retained their own identity until 2007. For example, the 2007 conference was known as "the 18th European Conference on Machine Learning (ECML) and the 11th European Conference on Principles and Practice of Knowledge Discovery in Databases (PKDD)", or in brief, "ECML/PKDD 2007", and both ECML and PKDD had their own conference proceedings. In 2008 the conferences were merged into one conference, and the division into traditional ECML topics and traditional PKDD topics was removed. The history of ECML dates back to 1986, when the European Working Session on Learning was first held. In 1993 the name of the conference was changed to European Conference on Machine Learning. PKDD was first organised in 1997. Originally PKDD stood for the European Symposium on Principles of Data Mining and Knowledge Discovery from Databases. The name European Conference on Principles and Practice of Knowledge Discovery in Databases was used since 1999. The conference remains highly competitive, consistently maintaining an average acceptance rate of around 25% for the main research track. == Upcoming conferences == == List of past conferences ==

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  • International Olympiad in Artificial Intelligence

    International Olympiad in Artificial Intelligence

    The International Olympiad in Artificial Intelligence (IOAI) is an annual International Science Olympiad in the field of artificial intelligence (AI) for secondary education students under the age of 20. The first IOAI was held in Burgas, Bulgaria, in 2024. Each country or territory may send up to two teams, each consisting of up to four students supported by one leader. Participants are selected through a multi-stage National Olympiad in Artificial Intelligence (NOAI) and/or a Regional Olympiad such as the NAOAI or APOAI. Participants at the IOAI compete on an individual basis. As of 2025, there were 61 countries and territories participating in the IOAI. Three hundred students participated in IOAI 2025. As of 2026, 130 countries and territories are accredited for participation in the IOAI. == Competition Structure == The IOAI consists of three contests: the Individual Contest, the Team Challenge, and the GAITE contest. Medals are awarded based solely on the Individual Contest. === Individual Contest === The Individual Contest is the main competition of the IOAI in which contestants compete individually on separate computers and are not permitted to communicate during the contest. Medals are awarded solely on the basis of the total score from the two-day Individual Contest. The Individual Contest consists of two on-site contest days (six hours per day), preceded by an at-home practice round and an on-site practice session. In IOAI 2025, three at-home problems were released for preparation approximately one month before the on-site contest. Results from this at-home round do not affect final results. The first on-site contest day (Individual Contest 1) comprises three tasks as extensions and continuations of the at-home tasks, while the second day (Individual Contest 2) comprises two or three tasks which are novel and different from the at-home tasks. The Individual Contest tasks span various AI domains such as machine learning, natural language processing, and computer vision. The IOAI 2025 contest rules describe tasks as requiring typical machine-learning workflows, including writing code, fitting models on training data, and running inference on test data, using identical local machines and GPU resources (minimum 24 GB RAM). Tasks, datasets, and submissions are handled through a contest platform (Bohrium), including a web-based Jupyter notebook environment for GPU access. Internet access is restricted to a whitelist of documentation sites and an integrated compact large language model accessible within the platform. The use of external APIs are prohibited unless a task explicitly allows them. In IOAI 2025, each contest task was scored up to 100 points and could include multiple subtasks. Scores are normalized using a baseline solution and a maximum score derived from either a Scientific Committee solution or the best contestant submission. Contestants can view only their own scores during the contest; a live scoreboard may be available publicly outside the contest hall but is not permitted to be viewed by contestants during the contest. For non-English-speaking teams, the IOAI hold a translation session beginning three hours before each contest day in which team leaders review and may amend machine-translated task statements; translations must match the English original and are published after the contest. The IOAI committee also enforces quarantine restrictions during these translation sessions, where neither contestants or team leaders may not use cell phones, laptops, and other communication devices. === Team Challenge === The Team Challenge is a team-based component of the IOAI. The results of this part do not affect the distribution of medals. The IOAI 2025 rules describe it as a “creative and AI-oriented challenge” in which a team's contestants sit together and cooperate, with the format varying by year. In IOAI 2024, teams worked with existing AI image and video generation tools to produce a visual result. In IOAI 2025, teams were assigned to program a robot to complete various tasks. === GAITE Contest === The GAITE (Global AI Talent Empowerment) contest is a simplified version of the individual contest with a separate scoreboard, where participants may ask for hints. It is designed for countries and territories with limited International Science Olympiads history, and it awards alternative prizes instead of medals. == Awards Distribution == The top 50% of the participants in the individual contest receive gold, silver and bronze medals in ratio of 1:2:3, respectively. The top three individuals receive honorary trophies. As in other International Science Olympiads, if an individual is in the top 50% on one of the days, but does not receive a medal, they receive an honorary mention during the awards ceremony. The GAITE contest has similar cutoff logic, but receives a reward instead of a medal. The top three teams in the Team Challenge receive trophies. == National selection and regional competitions == National delegations are selected through country-level qualification processes referred to as National Olympiads in Artificial Intelligence (NOAI) or equivalent, which are widely known for their low success rates. Although the total number of participants worldwide is not published, available data indicate exceptionally competitive national pools; for example, Brazil reports over 716,000 competitors, while Russia reports more than 72,000. In addition, Regional Olympiads (for example, APOAI or NAOAI) provide continent-level competition and preparation platforms in most regions. === National Selection (National Olympiads in Artificial Intelligence) === Participating countries and territories select their students for the IOAI through a National Olympiad in Artificial Intelligence (NOAI) or an equivalent process. The names of these selection processes differ by country, but almost all of them (excluding newer countries participating in the GAITE contest) have in common that the process comprises multiple and/or extremely rigorous selection stages. United States / Canada – The USA–North America AI Olympiad (USAAIO) is a three-round process including an invitational in-person round and a subsequent selection camp, after which a national delegation is selected for IOAI. Russia – The Russian Olympiad in Artificial Intelligence is organized as a multi-stage process (training, qualification, main round, final). Organizers reported 72,316 registrations for the training round and 52,260 registrations for the qualifying round in one season, with tasks spanning mathematics, algorithms/programming, and machine learning; 977 students were disqualified following plagiarism checks. Japan – Japan's national selection consists of multiple stages, beginning with the Japan Olympiad in Artificial Intelligence (JOAI), a large-scale Kaggle-style competition. High-performing participants advance through additional assessment stages, including written solution reports and technical interviews. From this process, eight students are selected for the APOAI team, with four ultimately chosen to represent Japan at the IOAI. Brazil – Brazil's National Olympiad in Artificial Intelligence (ONIA) is conducted as a large competition which consists of progressive rounds of evaluation. It identifies 28 top students from over 716,000 competitors, four of which are selected for the IOAI. The competition is held in four phases across two cycles, including a two-step third phase and a final training-and-evaluation phase that selects a four-student national team. Singapore – Singapore's national Olympiad consists of two rounds: an online preliminary round (300 MCQs in 3 hours) selects the top 150 performers to advance to the final assessment, which includes both theory questions and Python programming tasks. Additional training and selection may follow the finals for top performers. Poland – The Polish AI Olympiad adopts a two-stage structure: an open online first stage (at-home tasks) and a second-stage competitive camp with 30 selected participants competing for a four-person IOAI team. France – The Olympiades Françaises d'Intelligence Artificielle (OFIA), organized by France-IOI, follow a three-stage structure consisting of an open online qualification round, a second selection round, and a multi-day national training camp and final in Paris. Bangladesh – The Bangladesh AI Olympiad (BdAIO) selects competitors in three rounds: the online preliminary round, the national finals, and the team selection camp. In 2025, 406 participants competed in the national finals. Norway – The Norwrgian AI Olympiad (NOKI) is a three-stage selection system; however, unlike other countries, its first two rounds are shared with the Norwegian Informatics Olympiad. The national Olympiad reports 1,180 participants in the first round. Hong Kong – The national Olympiad reported more than 800 preliminary-round entrants, narrowing through multiple rounds to 25 finalists, with a subsequent

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  • Padre Pio (2022 film)

    Padre Pio (2022 film)

    Padre Pio is a 2022 biographical drama film co-written and directed by Abel Ferrara. It stars Shia LaBeouf as the titular role of Padre Pio, a Capuchin Franciscan priest who receives the stigmata, in the background of the World War I in Italy. The film is a co-production of Italy, Germany and the United Kingdom. During its production, LaBeouf converted to Catholicism as result of his spiritual experiences in character as Pio, who is venerated as a saint by the Catholic Church. The film had its world premiere in the Giornate degli Autori section of the 79th Venice International Film Festival on 2 September 2022. It was released theatrically in the United Kingdom on 26 January 2024 by Dazzler Media and in Italy on 18 July 2024 by RS Productions. == Plot == It is the year 1920. Italian WWI veterans have returned to their impoverished villages. Padre Pio arrives at San Giovanni Rotondo after living with his family in Pietrelcina for a number of years. While still sick, he continues to encounter Satan. Satan reveals himself as the instigator of the war and the sociopolitical problems of San Giovanni. While having little contact with the people of this town, Padre Pio learns what the poor are suffering from in the Sacrament of Confession and the Holy Mass, such as when a crippled man walks again because of Padre Pio's prayer. Besides the effects of war, such as medical inadequacy, health conditions and labourers dying from the effects of mustard gas, the people suffer from corrupt, wealthy landowners. Gerardo, a militaristic anti-socialist, threatens to kill any communal labourers tending his land. Many of them join the socialist party as a way to improve their lives. However, after they win the first free election in San Giovanni, Gerardo's forces massacre many of them. Padre Pio asks God that he may become a suffering servant for their salvation. He receives the wounds of Jesus Christ. The stigmata disrupts Satan's influence on San Giovanni Rotondo. == Cast == Shia LaBeouf as Padre Pio Marco Leonardi as Gerardo Salvatore Ruocco as Vincenzo Cristina Chiriac as Giovanna Brando Pacitto as Renato Luca Lionello as Silvestro Asia Argento as Tall Man == Production == According to Abel Ferrara, actor Willem Dafoe suggested that Shia LaBeouf should be cast for the film's leading role. After Ferrara held several Zoom calls with LaBeouf, the latter agreed to join the film, even though very little money was raised (the film was almost never made) and LaBeouf did the project for free. LaBeouf arrived at Old Mission Santa Inés in July 2021 to learn about Padre Pio with the Capuchin Franciscan friars. Thanks to Father Bobby Barbato and Brother Jude Quinto, Br. Alexander Rodriguez met LaBeouf while he attended Mass every day. He learned about the Catholic Church and the Capuchins while living in his truck or spending a few nights in the Capuchin's guest room. He was immersing himself in the Catholic faith. He enrolled in RCIA, revised the script with Rodriguez and trained to do the Latin Mass. Rodriguez traveled with LaBeouf as his spiritual adviser and catechist and was in the film as Padre Pio's companion. Filming occurred in Apulia, Italy, in December 2021. The first place was at the Capuchin friary in San Marco la Catola. Padre Pio exchanged letters with his provincial and spiritual director while living in Pietrelcina with his family. The time was around 1909–1916. Both directors were living in San Marco during these years. Padre Pio expressed in his letters his deep and mysterious relationship with God and health difficulties. This event is in the film. While filming, LaBeouf slept in Padre Pio's bedroom. After San Marco, filming continued outside the Sanctuary of Saint Michael the Archangel in Monte Sant'Angelo. Traditionally, St. Michael appeared here in the late 400s. LaBeouf stayed and filmed for a few weeks at the Abbey of Saint Mary of Pulsano. It is near the sanctuary. The rest of the filming took place outside the sanctuary. Ferrara said in 2024 that he used AI for the Italian dub of this film. == Release == Padre Pio had its world premiere in the Giornate degli Autori section of the 79th Venice International Film Festival on 2 September 2022. It received a four-minute ovation. It also competed at the Rio de Janeiro International Film Festival. At the Lisbon & Estoril Film Festival, it was chosen to compete for the "Best Film Award." During its North American premiere at the Mammoth Film Festival, it won the "Achievement for Filmmaking" award for cinematography. At the Taormina Film Festival, it premiered worldwide in Italian. In March 2023, Gravitas Ventures acquired North American rights to the film. It was released in select theaters and on video on demand in the United States on 2 June 2023. The film was released in the United Kingdom and Ireland on 26 January 2024 by Dazzler Media. RS Productions released it in Italy on 18 July 2024. == Reception == On the review aggregator website Rotten Tomatoes, the film holds an approval rating of 30% based on 43 reviews, with an average rating of 4.5/10. The website's critics consensus reads, "Tonally unbalanced and burdened with a distracting Shia LaBeouf performance, Padre Pio is one of Abel Ferrara's less divine works." Metacritic, which uses a weighted average, assigned the film a score of 45 out of 100, based on 6 critics, indicating "mixed or average" reviews.. Jordan Mintzer of The Hollywood Reporter gave the film a negative review, describing it as "clunky" and criticizing its political themes for possessing "the subtlety of a cartoon for preschoolers." Brian Tallerico of RogerEbert.com gave the film one and a half stars out of four, describing it as a "dull slog". Journalist Glenn Kenny of The New York Times found the film "occasionally rank" and panned LaBeouf's performance, though complimented Ferrara's "sometimes Brechtian consideration of the nodes of political history and spirituality." Film critic Armond White of National Review also criticized the film, describing it as "a work of deluded, semi-improvisational navel-gazing". Film critic Peter Bradshaw of The Guardian gave the film a positive review, with three out of five stars, writing that it is "a weird film...with an undeveloped, improvised feel, like a fragment or shard of something else. Yet there is a background hum there...an awareness of something dark and malign. It is a minor film but interesting." Writing for The New Yorker, Richard Brody considered that "in its hectic, scattershot way, Padre Pio feels very much of the desperate present day," describing it as "a historical drama without historical distance" and "a wild effort to reach the immediate experience of the past and its furies." Faith-based reviews for the film were generally negative. It received negative reviews from Catholic Answers, The Catholic World Report, The Catholic Weekly, The Catholic Thing, and Crisis Magazine. Conversely, it received a mixed review from The Catholic Review, as well as a positive review from America. Criticisms were generally aimed at the film's sexual content and perceived support of left-wing politics.

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  • C-RAN

    C-RAN

    C-RAN (Cloud-RAN), also referred to as Centralized-RAN, is an architecture for cellular networks. C-RAN is a centralized, cloud computing-based architecture for radio access networks that supports 2G, 3G, 4G, 5G and future wireless communication standards. Its name comes from the four 'C's in the main characteristics of C-RAN system, "Clean, Centralized processing, Collaborative radio, and a real-time Cloud Radio Access Network". == Background == Traditional cellular, or Radio Access Networks (RAN), consist of many stand-alone base stations (BTS). Each BTS covers a small area, whereas a group BTS provides coverage over a continuous area. Each BTS processes and transmits its own signal to and from the mobile terminal, and forwards the data payload to and from the mobile terminal and out to the core network via the backhaul. Each BTS has its own cooling, back haul transportation, backup battery, monitoring system, and so on. Because of limited spectral resources, network operators 'reuse' the frequency among different base stations, which can cause interference between neighboring cells. There are several limitations in the traditional cellular architecture. First, each BTS is costly to build and operate. Moore's law helps reduce the size and power of an electrical system, but the supporting facilities of the BTS are not improved quite as well. Second, when more BTS are added to a system to improve its capacity, interference among BTS is more severe as BTS are closer to each other and more of them are using the same frequency. Third, because users are mobile, the traffic of each BTS fluctuates (called 'tide effect'), and as a result, the average utilization rate of individual BTS is pretty low. However, these processing resources cannot be shared with other BTS. Therefore, all BTS are designed to handle the maximum traffic, not average traffic, resulting in a waste of processing resources and power at idle times. == Evolution of base station architecture == === All-in-one macro base station === In the 1G and 2G cellular networks, base stations had an all-in-one architecture. Analog, digital, and power functions were housed in a single cabinet as large as a refrigerator. Usually the base station cabinet was placed in a dedicated room along with all necessary supporting facilitates such as power, backup battery, air conditioning, environment surveillance, and backhaul transmission equipment. The RF signal is generated by the base station RF unit and propagates through pairs of RF cables up to the antennas on the top of a base station tower or other mounting points. This all-in-one architecture was mostly found in macro cell deployments. === Distributed base station === For 3G, a distributed base station architecture was introduced by Ericsson, Nokia, Huawei, and other leading telecom equipment vendors. In this architecture the radio function unit, also known as the remote radio head (RRH), is separated from the digital function unit, or baseband unit (BBU) by fiber. Digital baseband signals are carried over fiber, using the Open Base Station Architecture Initiative (OBSAI) or Common Public Radio Interface (CPRI) standard. The RRH can be installed on the top of tower close to the antenna, reducing the loss compared to the traditional base station where the RF signal has to travel through a long cable from the base station cabinet to the antenna at the top of the tower. The fiber link between RRH and BBU also allows more flexibility in network planning and deployment as they can be placed a few hundred meters or a few kilometers away. Most modern base stations now use this decoupled architecture. === C-RAN/Cloud-RAN === C-RAN may be viewed as an architectural evolution of the above distributed base station system. It takes advantage of many technological advances in wireless, optical and IT communications systems. For example, it uses the latest CPRI standard, low cost Coarse or Dense Wavelength Division Multiplexing (CWDM/ DWDM) technology, and mmWave to allow transmission of baseband signal over long distance thus achieving large scale centralised base station deployment. It applies recent Data Centre Network technology to allow a low cost, high reliability, low latency and high bandwidth interconnect network in the BBU pool. It utilizes open platforms and real-time virtualization technology rooted in cloud computing to achieve dynamic shared resource allocation and support multi-vendor, multi-technology environments. == Architecture overview == C-RAN architecture has the following characteristics that are distinct from other cellular architectures: Large scale centralized deployment: Allows many RRHs to connect to a centralized BBU pool. The maximum distance can be 20km in fiber link for 4G (LTE/LTE-A) systems, and even longer distances (40~80km) for 3G (WCDMA/TD-SCDMA) and 2G (GSM/CDMA) systems. Native support to Collaborative Radio technologies: Any BBU can talk with any other BBU within the BBU pool with very high bandwidth (10 Gbit/s and above) and low latency (10 μs level). This is enabled by the interconnection of BBUs in the pool. This is one major difference from BBU Hotelling, or base station Hotelling; in the latter case, the BBUs of different base stations are simply stacked together and have no direct link between them to allow physical layer co-ordination. Real-time virtualization capability based on open platform: This is different from traditional base stations built on proprietary hardware, where the software and hardware are close-sourced and provided by single vendors. In contrast, a C-RAN BBU pool is built on open hardware, like x86/ARM CPU based servers, and interface cards that handle fiber links to RRHs and inter-connections in the pool. Real-time virtualization ensures that resources in the pool can be allocated dynamically to base station software stacks, say 4G/3G/2G function modules from different vendors, according to network load. However, to satisfy the strict timing requirements of wireless communication systems, the real-time performance for C-RAN is at the level of tens of microseconds, which is two orders of magnitude better than the millisecond level 'real-time' performance usually seen in Cloud Computing environments. == Similar architecture and systems == KT, a telecom operator in the Republic of Korea, introduced a Cloud Computing Center (CCC) system in their 3G (WCDMA/HSPA) and 4G (LTE/LTE-A) network in 2011 and 2012. The concept of CCC is basically the same as C-RAN. SK Telecom has also deployed Smart Cloud Access Network (SCAN) and Advanced-SCAN in their 4G (LTE/LTE-A) network in Korea no later than 2012. In 2014, Airvana (now CommScope) introduced OneCell, a C-RAN-based small cell system designed for enterprises and public spaces. == Competing architectures in cellular network evolution == === All-in-one BTS === One major alternative solution that is addressing similar challenges of RAN, is the small size, all-in-one outdoor BTS. Thanks to the achievements in the semiconductor industry, all the functionality of a BTS, including RF, baseband processing, MAC processing and package level processing, can now be implemented in a volume of <50 liters. This makes the system small and weatherproof, reduces the difficulty of BTS site choice and construction, eliminates the air conditioning requirement, and thus reduces operational costs. However, because each BTS is still working on its own, it cannot readily make use of the collaboration algorithms to reduce the interference between neighboring BTSs. It is also relatively hard to upgrade or repair because the all-in-one BTS units are usually mounted near the antenna. More processing units in less-protected environments also implies a higher failure rate compared to C-RAN, which only has the RRU deployed outdoors. The advantage of Cloud RAN lies in its ability to implement LTE-Advanced features such as Coordinated MultiPoint (CoMP) with very low latency between multiple radio heads. However, the economic benefit of improvements such as CoMP can be negated by the higher backhaul costs for some operators. === Small cell === The main competition between small cell and C-RAN occurs in two deployment scenarios: outdoor hotspot coverage and indoor coverage. == Academic research and publications == As one of the promising evolution paths for future cellular network architecture, C-RAN has attracted high academic research interest. Meanwhile, because the native support of cooperative radio capability built into the C-RAN architecture, it also enables many advanced algorithms that were hard to implement in cellular networks, including Cooperative Multi-Point Transmission/Receiving, Network Coding, etc. In October 2011, Wireless World Research Forum 27 was hosted in Germany, when China Mobile was invited to give a C-RAN presentation. In August 2012, IEEE C-RAN 2012 workshop was hosted in Kunming, China. CRC Press published a book, "Green Communications: Theore

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  • The Future of Truth (Rosenbaum book)

    The Future of Truth (Rosenbaum book)

    The Future of Truth: How AI Reshapes Reality is a 2026 book by American filmmaker and author Steven Rosenbaum about how artificial intelligence affects the concept of truth. It was published by Matt Holt Books on May 12, 2026, to positive media attention; on May 19, in response to an inquiry from The New York Times, Rosenbaum acknowledged that the book itself contains multiple misattributed or false quotes that were hallucinated by AIs. == Synopsis == == Development == Rosenbaum has said that he developed the book using AI chatbots as research tools, indicating in his notes what information came from AI and sending those claims to a fact-checker affiliated with the publisher. He has said that he did not use AI tools to write the book itself. He has described AI tools as "a delightful writing companion ... strangely creative and crafty and unusual in all these ways", while acknowledging that sometimes "then it betrays you in ways that are just really quite horrible". Journalist and Nobel laureate Maria Ressa wrote the book's foreword. Taylor Lorenz, Michael Wolff, and Nicholas Thompson wrote blurbs promoting it. == Release and reception == The Future of Truth was published by Matt Holt Books, an imprint of BenBella Books, and distributed by Simon & Schuster. The book's release on May 12, 2026, was described by Futurism as "buzzy" and by The New York Times as "to great fanfare". On May 14, an excerpt was published in Wired under the title "Gen Z Is Pioneering a New Understanding of Truth". On May 17, the Times contacted Rosenbaum regarding a number of quotes that appeared to be falsified or misattributed; the following evening he confirmed that they were the result of AI hallucinations:As I disclosed in the book's acknowledgments, I used AI tools ChatGPT and Claude during the research, writing and editing process. That does not excuse these errors, of which I take full responsibility. I am now working with the editors to thoroughly review and quickly correct any affected passages; any future editions will be corrected. The Times documented several of the errors, including a quote from Kara Swisher that Swisher described as making it "sound like I have a stick up my butt" and a quote from Lisa Feldman Barrett that Barrett described as misrepresenting her views on the nature of emotions, social signals, and truth. The book also misattributed a quote by Meredith Broussard from an interview with Marketplace Tech as having been from her book Artificial Unintelligence and hallucinated several words in a quote from Lee McIntyre, although according to McIntyre it did not misrepresent his views. Wired's editors, in an addendum to the excerpt they published, said that all quotes included in it had been verified as part of their fact-checking process. Rosenbaum told the Times that the series of errors "serves as a warning about the risks of AI-assisted research and verification, that is why I wrote the book. These AI errors do not, in fact, diminish the larger questions that the book raises about truth, trust and AI and its impact on society, democracy and editorial." Maggie Harrison Dupré in Futurism expressed skepticism, writing "The risk of AI hallucinations ... is well-known. If you're going to literally write the book on post-AI truth, you should probably put some more elbow grease into fact-checking your AI-assisted research." Kyle Orland in Ars Technica, responding to Rosenbaum's statement that his error "demonstrates the problem more vividly than any abstract argument could", was similarly skeptical, writing that "if we accept this take, every avoidably obvious mess in the world might be a disguised good because it really helps illuminate the huge mistake. And that can't be right; sometimes 'negligence' is just that." Subsequent comments by Rosenbaum placed more blame on the chatbots, which he told The Atlantic "fucked up the book". Rosenbaum told Ars Technica that fact-checking occurred "incredibly effectively, but not a hundred percent"; Orland observed that "it's worth noting that most writers manage to include zero made-up quotes when they write a book". Rosenbaum said that he had "learned a lesson" and would be "much more suspicious" of AI in the future, but would continue to use AI in his research. Orland responded to Rosenbaum's characterization of AI as "magical" by comparing it to the One Ring from The Lord of the Rings, in that it "convinces many of those who use it that they can control its power properly" when many cannot. Orland highlighted the limits of traditional fact-checking regarding AI, given that fact-checkers are used to assuming that direct quotes are copied word-for-word from the source. Rosenbaum told Orland that the future of fact-checking for AI-researched works "probably includes mandatory source tracing for quotations, better provenance tracking, clearer standards around AI-assisted research, and potentially (more irony here) AI tools that audit citations against primary materials". Patrick Redford in Defector criticized Rosenbaum, alongside other artists tricked by AI, for failing to recognize AI as "the enemy". Will Oremus in The Atlantic described Redford's approach of stigmatizing AI writing as "reasonable", noting the presence of low-quality, seemingly AI-generated verbiage in The Future of Truth—a claim denied by Rosenbaum—before saying that the greater issue is finding the line at which AI assistance in writing becomes a problem. Oremus concluded, "The scandal can't just be that [Rosenbaum] used AI while working on his book, because he acknowledged that up front. He got in trouble because he had used AI badly, failing to check its work on a task at which it is famously unreliable."

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  • ECML PKDD

    ECML PKDD

    ECML PKDD, the European Conference on Machine Learning Principles and Practice of Knowledge Discovery in Databases, is one of the leading academic conferences on machine learning and knowledge discovery, held in Europe every year. == History == ECML PKDD is a merger of two European conferences, European Conference on Machine Learning (ECML) and European Conference on Principles and Practice of Knowledge Discovery in Databases (PKDD). ECML and PKDD have been co-located since 2001; however, both ECML and PKDD retained their own identity until 2007. For example, the 2007 conference was known as "the 18th European Conference on Machine Learning (ECML) and the 11th European Conference on Principles and Practice of Knowledge Discovery in Databases (PKDD)", or in brief, "ECML/PKDD 2007", and both ECML and PKDD had their own conference proceedings. In 2008 the conferences were merged into one conference, and the division into traditional ECML topics and traditional PKDD topics was removed. The history of ECML dates back to 1986, when the European Working Session on Learning was first held. In 1993 the name of the conference was changed to European Conference on Machine Learning. PKDD was first organised in 1997. Originally PKDD stood for the European Symposium on Principles of Data Mining and Knowledge Discovery from Databases. The name European Conference on Principles and Practice of Knowledge Discovery in Databases was used since 1999. The conference remains highly competitive, consistently maintaining an average acceptance rate of around 25% for the main research track. == Upcoming conferences == == List of past conferences ==

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