AI Coding Kya Hota Hai

AI Coding Kya Hota Hai — independent reviews, comparisons, pricing and step-by-step guides on Aizhi.

Secure environment

In computing, a secure environment is any system which implements the controlled storage and use of information. In the event of computing data loss, a secure environment is used to protect personal or confidential data. It may also be known as a trusted execution environment (TEE). Often, secure environments employ cryptography as a means to protect information. This is typically used for processing confidential or restricted information. Some secure environments employ cryptographic hashing, simply to verify that the information has not been altered since it was last modified.
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HTK Limited

HTK Limited is a software-as-a-service company that provides mobile phone messaging and IVR services. Founded in 1996, HTK is headquartered in Ipswich, Suffolk, UK. HTK provide mass notification services. Specifically, the "Police Direct" messaging service to Suffolk and Norfolk Constabularies. In 2010 the HTK Horizon SaaS platform was selected by the Scottish Environment Protection Agency (SEPA) for their Floodline Warnings Direct service. == History == HTK was founded in 1996 by Marlon Bowser and Adrian Gregory and from the outset focused on what has now become commonly known as Software-as-a-Service. in 2004, according to the Deloitte Fast 50 (UK), HTK was the 17th fastest growing company in the East of England. In 2005 The Times listed HTK 65th nationally and 4th in the East of England in the Sunday Times & Microsoft "Tech Track 100" awards. In 2009 the company was approved as a supplier to UK Government under a new framework agreement. In 2010 HTK launched version 2.2 of its Horizon platform, with a feature set that signals a shift from mass notification into the customer service automation market.
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Verbal overshadowing

Verbal overshadowing is a phenomenon where giving a verbal description of sensory input impairs formation of memories of that input. This was first reported by Schooler and Engstler-Schooler (1990) where it was shown that the effects can be observed across multiple domains of cognition which are known to rely on non-verbal knowledge and perceptual expertise. One example of this is memory, which has been known to be influenced by language. Seminal work by Carmichael and collaborators (1932) demonstrated that when verbal labels are connected to non-verbal forms during an individual's encoding process, it could potentially bias the way those forms are reproduced. Because of this, memory performance relying on reportable aspects of memory that encode visual forms should be vulnerable to the effects of verbalization. == Initial findings == Schooler and Engstler-Schooler (1990) were the first to report findings of verbal overshadowing. In their study, participants watched a video of a simulated robbery and were instructed to either verbally describe the robber or engage in a control task. Those who engaged in giving a verbal description were less likely to correctly identify the robber from a test lineup, compared to those who engaged in the control task. A larger effect was detected when the verbal description was provided 20, rather than 5, minutes after the video, and immediately before the test lineup. A meta-analysis by Meissner and Brigham (2001) supported the effects of verbal overshadowing, showing a small but reliably negative effect. == General effects of verbal overshadowing == The effects of verbal overshadowing have been generalized across multiple domains of cognition that are known to rely on non-verbal knowledge and perceptual expertise, such as memory. Memory has been known to be influenced by language. Seminal work by Carmichael and collaborators (1932) demonstrated that labels attached to, or associated with, non-verbal forms during memory encoding can affect the way the forms were subsequently reproduced. Because of this, memory performance that relies on reportable aspects of memory that encode visual forms should be vulnerable to the effects of verbalization. Pelizzon, Brandimonte, and Luccio (2002) found that visual memory representations appear to incorporate visual, spatial, and temporal characteristics. It is explained as follows: With the temporal code (where the only information available is the sequence of the stimuli), performance levels remain high, unless participants are required to retrieve the stimuli in a different order from that used at encoding (visual cue). In this case, performance is significantly impaired, even in the presence of a visual cue. The study showed that order information acts as a link between the two separate representations of figure and background, hence preventing verbal overshadowing at encoding (temporal component) or attenuating its influence at retrieval (spatial component).(p. 960) Hatano, Ueno, Kitagami, and Kawaguchi found that verbal overshadowing is likely to occur when participants verbally described targets in detail. Detailed verbal descriptions resulted in more frequently inaccurate descriptions that in turn created inaccurate representations in the memories of participants. Inaccuracies are also likely to occur when face recognition comes immediately after verbalization. Other forms of non-verbal knowledge affected by verbal overshadowing include the following: [Verbal overshadowing] has also been observed when participants attempt to generate descriptions of other 'difficult-to-describe' stimuli such as colors (Schooler and Engstler-Schooler, 1990) or abstract figures (Brandimonte et al., 1997), or other non-visual tasks such as wine tasting (Melcher and Schooler, 1996), decision making (Wilson and Schooler, 1991), and insight problem-solving. (p. 871) (Schooler et al., 1993) Verbalization of stimuli leads to the disruption of non-reportable processes that are necessary for achieving insight solutions, which are distinct from language processes. Schooler, Ohlsson, and Brooks (1993) found that face recognition requires information that cannot be adequately verbalized, giving rise to difficulty in describing factors in recognition judgments. Subjects were less effective in solving insight problems when compelled to put their thoughts in words, which suggests that language may interfere with thought. The verbal overshadowing effect was not seen when participants engaged in articulatory suppression. Performance was reduced in both the verbal and non-verbal description conditions. This is evidence that verbal encoding plays a role in face recognition. By testing with distracting faces presented between study and test, Lloyd-Jones and Brown (2008) suggested a dual-process approach to recognition memory took place, that verbalization influenced familiarity-based processes at first, but its effects were later seen on recollection, when discrimination between items became more difficult. == Verbal overshadowing in facial recognition == The verbal overshadowing effect can be found for facial recognition because faces are predominately processed in a holistic or configurable manner. (Tanaka & Farah, 1993; Tanaka & Sengco, 1997) Verbalizing one's memory for a face is done using a featural or analytic strategy, leading to a drift from the configurable information about the face and to impaired recognition performance. However, Fallshore & Schooler (1995) found that the verbal overshadowing effect was not found when participants described faces of races different from their own. A study by Brown and Lloyd-Jones (2003) found that there was no verbal overshadowing effect found in car descriptions; it was only seen in facial descriptions. The authors noted that descriptions were no different on any measure including accuracy. It is suggested that less expertise in verbalizing faces rather than cars invokes a stronger shift in verbal and featural processing. This supports the concept of a transfer inappropriate retrieval framework and addresses some limitations of the effect. Wickham and Swift (2006) suggested that the verbal overshadowing effect is not seen in describing all faces, and one aspect that determines this is distinctiveness. Results showed that typical faces produce verbal overshadowing, while distinctive faces did not. In studies of eyewitness reports, variation in response criteria given by participants influenced the quality of the descriptions generated and accuracy on identification task, known as the retrieval-based effect. Face recognition was also impaired when subjects described a familiar face, such as a parent, or when describing a previously seen but novel face. Dodson, Johnson, and Schooler (1997) found that recognition was also impaired when participants were provided with a description of a previously seen face, and they were able to ignore provided versus self-generated descriptions more easily. This finding of verbal overshadowing suggested that eyewitness recognition is not only affected by their own descriptions, but of descriptions heard from others, such other eyewitness testimonies. == Voice recognition == The verbal overshadowing effect has also been found to affect voice identification. Research shows that describing a non-verbal stimuli leads to a decrease in recognition accuracy. In an unpublished study by Schooler, Fiore, Melcher, and Ambadar (1996), participants listened to a tape-recorded voice, after which they were asked either to verbally describe it or to not do so, and then asked to distinguish the voice from 3 similar distractor voices. The results showed that verbal overshadowing impaired accuracy of recognition based on gut feeling, suggesting an overall verbal overshadowing for voice recognition. Due to the forensic relevance of voices heard over the telephone and harassing phone calls that are often a problem for police, Perfect, Hunt, and Harris (2002) examined the influence of three factors on accuracy and confidence in voice recognition from a line-up. They expected to find an effect, because voice represents a class of stimuli that is difficult to describe verbally. This meets Schooler et al.'s (1997) modality mismatch criterion, meaning that describing the speakers age, gender, or accent is difficult, making voice recognition susceptible to the verbal overshadowing phenomenon. It was found that the method of memory encoding had no impact on performance, and that hearing a telephone voice reduced confidence but did not affect accuracy. They also found that providing a verbal description impaired accuracy but had no effect on confidence. The data showed an effect of verbal overshadowing in voice recognition and provided yet another disassociation between confidence and performance. Although there was a difference in confidence level, witnesses were able to identify voices over the telephone as accurately as voices heard direc
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CapCut

CapCut, known domestically as JianYing (Chinese: 剪映; pinyin: Jiǎnyìng) and formerly internationally as ViaMaker, is a video editor developed by ByteDance, available as a mobile app, desktop app, and web app. == History == The app was first released in China in 2019 and was initially available for iPhone and Android. In 2020, it was rebranded in English from ViaMaker to CapCut and became available globally. It later expanded to include web and desktop versions for Mac and Windows. In 2022, CapCut reached 200 million active users. According to The Wall Street Journal, in March 2023, it was the second-most downloaded app in the U.S., behind that of Chinese discount retailer Temu. In January 2025, CapCut had over 1 billion downloads on the Google Play Store. On February 1, 2021, CapCut Pro for Windows was launched. On November 27, the Pro version for Mac was launched. In July 2025, CapCut Pro for HarmonyOS was available on HarmonyOS NEXT tablets. In July 2024, CapCut was reported by the South China Morning Post to be a generative AI (GenAI) application that led global AI app downloads, with approximately 38.42 million downloads and 323 million monthly active users. == Features == CapCut supports basic video editing functions, including editing, trimming, and adding or splitting clips. Editing projects is limited to single-layer editing, but the app supports overlay options that enable additional effects, including multi-layer editing. The app includes a library of pre-made templates and a tool that generates editable video captions. It also provides photo editing tools, including retouch and product photo features integrated within the editing interface. CapCut's video editor includes AI-based features such as video and script generation. Users can export or save completed projects directly to different social media platforms. CapCut includes a free version and a paid Pro version with cloud storage and advanced features. == Controversies == === Illegal data collection === In July 2023, many users of CapCut accused it of illegally profiting off their personal data. A class-action lawsuit filed in the U.S. District Court for the Northern District of Illinois on July 28, 2023, alleged that CapCut illegally harvests and profits from user data including biometric information and geolocation without consent. In September 2025, a federal court excluded most of the lawsuit, which alleged that TikTok’s parent company improperly scraped private data from CapCut's video editing software, as lacking grounds, with some of the class action continuing to move forward. == Bans and restrictions == === Ban in India === As a response to border clashes with China in May 2020, the Indian government banned around 56 Chinese applications including CapCut and TikTok, which is owned by CapCut's parent company ByteDance. Indian users were unable to use and download the application. As of February 2022, around 273 Chinese applications have been banned by the Indian government under the concern of national security and Indian user privacy. === Ban in the United States === On January 18, 2025, at 10 PM EST, CapCut was banned in the United States along with TikTok and all other ByteDance apps due to the implementation of the Protecting Americans from Foreign Adversary Controlled Applications Act. Hours after the suspension of services took effect, President Donald Trump indicated on Truth Social that he would issue an executive order on the day of his inauguration "to extend the period of time before the law's prohibitions take effect". On January 21, CapCut began restoring service. On February 13, Google and Apple restored CapCut on the App Store and Google Play Store.
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Instance (computer science)

In computer science, an instance or token (from metalogic and metamathematics) is a specific occurrence of a software element that is based on a type definition. When created, an occurrence is said to have been instantiated, and both the creation process and the result of creation are called instantiation. == Examples == Chat AI instance In chat-based AI systems, an assistant can be invoked across many independent conversation sessions (often called a thread), each with its own message history. A specific execution of the assistant over that session may be represented as a run (an execution on a thread). Class instance In object-oriented programming, an object created from a class type. Each instance of a class shares the class-defined structure and behavior but has its own identity and state. Procedural instance In some contexts (including Simula), each procedure call can be viewed as an instance of that procedure—an activation with its own parameters and local variables. Computer instance In cloud computing and virtualization, an instance commonly refers to a provisioned virtual machine or virtual server with an allocated combination of compute, memory, network, and storage resources. Polygonal model In computer graphics, a model may be instanced so it can be drawn multiple times with different transforms and parameters, improving performance by reusing shared geometry data. Program instance In a POSIX-oriented operating system, a running process is an instance of a program. It can be instantiated via system calls such as fork() and exec(). Each executing process is an instance of a program it has been instantiated from.
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Afghan Girls Robotics Team

The Afghan Girls Robotics Team, also known as the Afghan Dreamers, is an all-girl robotics team from Herat, Afghanistan, founded through the Digital Citizen Fund (DCF) in 2017 by Roya Mahboob and Alireza Mehraban. It is made up of girls between ages 12 and 18 and their mentors. Several members of the team were relocated to Qatar and Mexico by humanitarian and tech entrepreneur Sarah Porter following the fall of Kabul in August 2021. A documentary film featuring members of the team, titled Afghan Dreamers, was released by MTV Documentary Films in 2023. == Origins == The Afghan Girls Robotics Team was co-founded in 2017 by Roya Mahboob, who is their coach, mentor and sponsor, and founder of the Digital Citizen Fund (DCF), which is the parent organization for the team. Dean Kamen was planning a 2017 competition in the United States and had recruited Mahboob to form a team from Afghanistan. Out of 150 girls, 12 were selected for the first team. Before parts were sent by Kamen, they trained in the basement of the home of Mahboob's parents, with scrap metal and without safety equipment under the guidance of their coach, Mahboob's brother Alireza Mehraban, who is also a co-founder of the team. == 2017 and 2018 == In 2017, six members of the Afghan Girls Robotics Team traveled to the United States to participate in the international FIRST Global Challenge robotics competition. Their visas were rejected twice after they made two journeys from Herat to Kabul through Taliban-controlled areas, before officials in the United States government intervened to allow them to enter the United States. Customs officials also detained their robotics kits, which left them two weeks to construct their robot, unlike some teams that had more time. They were awarded a Silver medal for Courageous Achievement. One week after they returned home from the competition, the father of team captain Fatemah Qaderyan, Mohammad Asif Qaderyan, was killed in a suicide bombing. After their United States visas expired, the team participated in competitions in Estonia and Istanbul. Three of the 12 members participated in the 2017 Entrepreneurial Challenge at the Robotex festival in Estonia, and won the competition for their solar-powered robot designed to assist farmers. In 2018, the team trained in Canada, continued to travel in the United States for months and participate in competitions. == 2019 == The Afghan Girls Robotics team had aspirations to develop a science and technology school for girls in Afghanistan. Roya Mahboob interfaced with the School of Engineering and Applied Sciences (SEAS), the School of Architecture, and the Whitney and Betty MacMillan Center for International and Area Studies Yale University to design the infrastructure for what they named The Dreamer Institute. == 2020 == In March 2020, the governor of Herat at the time, in response to the COVID-19 pandemic in Afghanistan and a scarcity of ventilators, sought help with the design of low-cost ventilators, and the Afghan Girls Robotics Team was one of six teams contacted by the government. Using a design from Massachusetts Institute of Technology and with guidance from MIT engineers and Douglas Chin, a surgeon in California, the team developed a prototype with Toyota Corolla parts and a chain drive from a Honda motorcycle. UNICEF also supported the team with the acquisition of necessary parts during the three months they spent building the prototype that was completed in July 2020. Their design costs around $500 compared to $50,000 for a ventilator. In December 2020, Minister of Industry and Commerce Nizar Ahmad Ghoryani donated funding and obtained land for a factory to produce the ventilators. Under the direction of their mentor Roya Mahboob, the Afghan Dreamers also designed a UVC Robot for sanitization, and a Spray Robot for disinfection, both of which were approved by the Ministry of Health for production. == 2021 == In early August 2021, Somaya Faruqi, former captain of the team, was quoted by Public Radio International about the future of Afghanistan, stating, "We don’t support any group over another but for us what’s important is that we be able to continue our work. Women in Afghanistan have made a lot of progress over the past two decades and this progress must be respected." On August 17, 2021, the Afghan Girls Robotics Team and their coaches were reported to be attempting to evacuate, but unable to obtain a flight out of Afghanistan, and a lawyer appealed to Canada for assistance regarding the evacuation of the team members. As of August 19, 2021, nine members of the team and their coaches had evacuated to Qatar. The founder of the team, Roya Mahboob, and DCF board member, Elizabeth Schaeffer Brown, were previously in contact with the Qatari government to assist the team members in their evacuation from Afghanistan. By August 25, 2021, some members arrived in Mexico. Saghar, a team member who evacuated to Mexico, said, "We wanted to continue the path that we started to continue to go for our achievements and to go for having our dreams through reality. So that's why we decided to leave Afghanistan and go for somewhere safe" in an interview with The Associated Press. The members who have left Afghanistan participated in an online robotics competition in September and plan to continue their education. A documentary film titled Afghan Dreamers, produced by Beth Murphy and directed by David Greenwald, was in post-production when the team began to evacuate. == 2022 == The Afghan Dreamers were involved in a training program at the Texas A&M University at Qatar’s STEM Hub. == 2023 == The Afghan Girls Robotics Team had a booth at the 5th UN Conference on the Least Developed Countries, where they displayed some of the robots the team had constructed. == Afghan Dreamers documentary == The Afghan Dreamers documentary from MTV Documentary Films premiered in May 2023 on Paramount+. The film was directed by David Greenwald and produced by David Cowan and Beth Murphy. In a review for Screen Daily, Wendy Ide wrote, "This film, with its likeable cast of girl nerds and positive message, should enjoy a warm reception on the festival circuit, and will be of particular interest to events seeking to showcase women's stories from around the world. It also serves as a timely cautionary tale – a case study on just how quickly the rights and the opportunities of women can be curtailed, at the behest of the men in power." == Honors and awards == 2017 Silver medal for Courageous Achievement at the FIRST Global Challenge, science and technology 2017 Benefiting Humanity in AI Award at World Summit AI 2017 Winner, Entrepreneurship Challenge at Robotex in Estonia 2018 Permission to Dream Award, Raw Film Festival 2018 Conrad Innovation Challenge, Raw Film Festival 2018 Rookie All Star – District Championship, Canada 2018 Asia Game Changer Award Honoree 2019 Inspiring in Engineering Award – FIRST Detroit World Championship 2019 Asia Game Changer Award of California 2019 Safety Award – FIRST Global, Dubai 2021 Forbes 30 Under 30 Asia 2022 World Championships, Genoa, Switzerland
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Enterprise mobile application

The term enterprise mobile application is used in the context of mobile apps created/brought by individual organizations for their workers to carry out the functions required to run the organization. It is the process of building a mobile application for the requirements of an enterprise. An enterprise mobile application belonging to an organization is expected to be used by only the workers of that organization. The definition of enterprise mobile application does not include the mobile apps that an organization create for its customers or consumers of the products or services generated by the organization. == Example == An organization, whether for-profit or non-profit, may create a mobile app for its members to track inventory levels of supplies they distribute to their target communities or materials used in product manufacturing. Such a mobile app comes under the definition of enterprise mobile application. However, the same organization may also create another mobile app to sell their products to end users or spread awareness of their services to various communities, and that mobile app would not come under definition of enterprise mobile application. == Enterprise mobile solution providers == Enterprise Mobile solution providers create and develop apps for individual organizations that can buy instead of creating the apps themselves. Reasons for Organizations buying the apps include time and cost savings, technical expertise. Today Enterprise Mobility is playing track role for enterprise transformation. Today, enterprises needs productivity is a fast way. Enterprise mobility helps business owners to build their work in a progressive way by assisting enterprise mobility solutions.
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Haskins Laboratories

Haskins Laboratories, Inc. is an independent research laboratory, founded in 1935 and located in New Haven, Connecticut since 1970. Many current Haskins researchers are affiliated with Yale University's Child Study Center and/or the University of Connecticut. Haskins is a multidisciplinary and international community of researchers who conduct basic research on spoken and written language and global literacy. A guiding perspective of their research has been to view speech and language as emerging from biological processes, including those of adaptation, response to stimuli, and conspecific interaction. Haskins Laboratories has a long history of technological and theoretical innovation, from creating systems of rules for speech synthesis and development of an early working prototype of a reading machine for the blind to developing the landmark concept of phonemic awareness as the critical preparation for learning to read an alphabetic writing system. == Research tools and facilities == Haskins Laboratories is equipped, in-house, with a comprehensive suite of tools and capabilities to advance its mission of research into language and literacy. As of 2014, these included: Anechoic chamber Electroencephalography BioSemi 264 electrode, 24 bit Active Two System EGI 128 electrode, Geodesic EEG System 300 Electromagnetic articulography (EMMA) Carstens AG501 NDI WAVE Eye tracking: HL is equipped with 3 SR Research eye-trackers. 2 Model Eyelink 1000 systems. 1 Model Eyelink 1000plus system. Magnetic resonance imaging: Haskins has access to MRI scanners through agreements with the University of Connecticut and the Yale School of Medicine. On-site, HL has a Linux computer cluster dedicated to analysis of MRI data. Motion capture: HL is equipped with a Vicon motion capture system with one Basler high-speed digital camera, six Vicon MX T-20 cameras and a Vicon MX Giganet for synching camera data and connecting cameras to the data capture computer. Near infrared spectroscopy: HL has a TechEn CW6 8x8 system (four emitters; eight detectors). Ultrasound sonogram == History == Many researchers have contributed to scientific breakthroughs at Haskins Laboratories since its founding. All of them are indebted to the pioneering work and leadership of Caryl Parker Haskins, Franklin S. Cooper, Alvin Liberman, Seymour Hutner and Luigi Provasoli. The history presented here focuses on the research program of the division of Haskins Laboratories that, since the 1940s, has been most well known for its work in the areas of speech, language, and reading. === 1930s === Caryl Haskins and Franklin S. Cooper established Haskins Laboratories in 1935. It was originally affiliated with Harvard University, MIT, and Union College in Schenectady, NY. Caryl Haskins conducted research in microbiology, radiation physics, and other fields in Cambridge, MA and Schenectady. In 1939 Haskins Laboratories moved its center to New York City. Seymour Hutner joined the staff to set up a research program in microbiology, genetics, and nutrition. The descendant of the division led by Hutner program eventually became a department of Pace University in New York. The two identically named organizations are no longer formally affiliated. === 1940s === The U. S. Office of Scientific Research and Development, under Vannevar Bush asked Haskins Laboratories to evaluate and develop technologies for assisting blinded World War II veterans. Experimental psychologist Alvin Liberman joined Haskins Laboratories to assist in developing a "sound alphabet" to represent the letters in a text for use in a reading machine for the blind. Luigi Provasoli joined Haskins Laboratories to set up a research program in marine biology. The program in marine biology moved to Yale University in 1970 and disbanded with Provasoli's retirement in 1978. === 1950s === Franklin S. Cooper invented the pattern playback, a machine that converts pictures of the acoustic patterns of speech back into sound. With this device, Alvin Liberman, Cooper, and Pierre Delattre (and later joined by Katherine Safford Harris, Leigh Lisker, Arthur Abramson, and others), discovered the acoustic cues for the perception of phonetic segments (consonants and vowels). Liberman and colleagues proposed a motor theory of speech perception to resolve the acoustic complexity: they hypothesized that we perceive speech by tapping into a biological specialization, a speech module, that contains knowledge of the acoustic consequences of articulation. Liberman, aided by Frances Ingemann and others, organized the results of the work on speech cues into a groundbreaking set of rules for speech synthesis by the Pattern Playback. === 1960s === Franklin S. Cooper and Katherine Safford Harris, working with Peter MacNeilage, were the first researchers in the U.S. to use electromyographic techniques, pioneered at the University of Tokyo, to study the neuromuscular organization of speech. Leigh Lisker and Arthur Abramson looked for simplification at the level of articulatory action in the voicing of certain contrasting consonants. They showed that many acoustic properties of voicing contrasts arise from variations in voice onset time, the relative phasing of the onset of vocal cord vibration and the end of a consonant. Their work has been widely replicated and elaborated, here and abroad, over the following decades. Donald Shankweiler and Michael Studdert-Kennedy used a dichotic listening technique (presenting different nonsense syllables simultaneously to opposite ears) to demonstrate the dissociation of phonetic (speech) and auditory (nonspeech) perception by finding that phonetic structure devoid of meaning is an integral part of language, typically processed in the left cerebral hemisphere. Liberman, Cooper, Shankweiler, and Studdert-Kennedy summarized and interpreted fifteen years of research in "Perception of the Speech Code", still among the most cited papers in the speech literature. It set the agenda for many years of research at Haskins and elsewhere by describing speech as a code in which speakers overlap (or coarticulate) segments to form syllables. Researchers at Haskins connected their first computer to a speech synthesizer designed by Haskins Laboratories' engineers. Ignatius Mattingly, with British collaborators, John N. Holmes and J.N. Shearme, adapted the Pattern playback rules to write the first computer program for synthesizing continuous speech from a phonetically spelled input. A further step toward a reading machine for the blind combined Mattingly's program with an automatic look-up procedure for converting alphabetic text into strings of phonetic symbols. === 1970s === In 1970, Haskins Laboratories moved to New Haven, Connecticut, and entered into affiliation agreements with Yale University and the University of Connecticut; Haskins remains fully independent of both Yale and UConn, administratively and financially. The lab's original location in New Haven, at 270 Crown Street (from 1970 to 2005), was leased from Yale University. Isabelle Liberman, Donald Shankweiler, and Alvin Liberman teamed up with Ignatius Mattingly to study the relationship between speech perception and reading, a topic implicit in Haskins Laboratories' research program since its inception. They developed the concept of phonemic awareness, the knowledge that would-be readers must be aware of the phonemic structure of their language in order to be able to read. Leonard Katz related the work to contemporary cognitive theory and provided expertise in experimental design and data analysis. Under the broad rubric of the "alphabetic principle", this is the core of the lab's present program of reading pedagogy. Patrick Nye joined Haskins Laboratories to lead a team working on the reading machine for the blind. The project culminated when the addition of an optical character recognizer allowed investigators to assemble the first automatic text-to-speech reading machine. By the end of the decade this technology had advanced to the point where commercial concerns assumed the task of designing and manufacturing reading machines for the blind. In 1973, Franklin S. Cooper was selected to form a panel of six experts charged with investigating the famous 18-minute gap in the White House office tapes of President Richard Nixon related to the Watergate scandal. Building on earlier work, Philip Rubin developed the sinewave synthesis program, which was then used by Robert Remez, Rubin, and colleagues to show that listeners can perceive continuous speech without traditional speech cues from a pattern of sinewaves that track the changing resonances of the vocal tract. This paved the way for a view of speech as a dynamic pattern of trajectories through articulatory-acoustic space. Philip Rubin and colleagues developed Paul Mermelstein's anatomically simplified vocal tract model, originally worked on at Bell Laboratories, into the first articulatory synthesizer that can be controlled in a phy
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Per-pixel lighting

In computer graphics, per-pixel lighting refers to any technique for lighting an image or scene that calculates illumination for each pixel on a rendered image. This is in contrast to other popular methods of lighting such as vertex lighting, which calculates illumination at each vertex of a 3D model and then interpolates the resulting values over the model's faces to calculate the final per-pixel color values. Per-pixel lighting is commonly used with techniques, such as blending, alpha blending, alpha to coverage, anti-aliasing, texture filtering, clipping, hidden-surface determination, Z-buffering, stencil buffering, shading, mipmapping, normal mapping, bump mapping, displacement mapping, parallax mapping, shadow mapping, specular mapping, shadow volumes, high-dynamic-range rendering, ambient occlusion (screen space ambient occlusion, screen space directional occlusion, ray-traced ambient occlusion), ray tracing, global illumination, and tessellation. Each of these techniques provides some additional data about the surface being lit or the scene and light sources that contributes to the final look and feel of the surface. Most modern video game engines implement lighting using per-pixel techniques instead of vertex lighting to achieve increased detail and realism. The id Tech 4 engine, used to develop such games as Brink and Doom 3, was one of the first game engines to implement a completely per-pixel shading engine. All versions of the CryENGINE, Frostbite Engine, and Unreal Engine, among others, also implement per-pixel shading techniques. Deferred shading is a recent development in per-pixel lighting notable for its use in the Frostbite Engine and Battlefield 3. Deferred shading techniques are capable of rendering potentially large numbers of small lights inexpensively (other per-pixel lighting approaches require full-screen calculations for each light in a scene, regardless of size). == History == While only recently have personal computers and video hardware become powerful enough to perform full per-pixel shading in real-time applications such as games, many of the core concepts used in per-pixel lighting models have existed for decades. Frank Crow published a paper describing the theory of shadow volumes in 1977. This technique uses the stencil buffer to specify areas of the screen that correspond to surfaces that lie in a "shadow volume", or a shape representing a volume of space eclipsed from a light source by some object. These shadowed areas are typically shaded after the scene is rendered to buffers by storing shadowed areas with the stencil buffer. Jim Blinn first introduced the idea of normal mapping in a 1978 SIGGRAPH paper. Blinn pointed out that the earlier idea of unlit texture mapping proposed by Edwin Catmull was unrealistic for simulating rough surfaces. Instead of mapping a texture onto an object to simulate roughness, Blinn proposed a method of calculating the degree of lighting a point on a surface should receive based on an established "perturbation" of the normals across the surface. == Hardware rendering == Real-time applications, such as video games, usually implement per-pixel lighting through the use of pixel shaders, allowing the GPU hardware to process the effect. The scene to be rendered is first rasterized onto a number of buffers storing different types of data to be used in rendering the scene, such as depth, normal direction, and diffuse color. Then, the data is passed into a shader and used to compute the final appearance of the scene, pixel-by-pixel. Deferred shading is a per-pixel shading technique that has recently become feasible for games. With deferred shading, a "g-buffer" is used to store all terms needed to shade a final scene on the pixel level. The format of this data varies from application to application depending on the desired effect, and can include normal data, positional data, specular data, diffuse data, emissive maps and albedo, among others. Using multiple render targets, all of this data can be rendered to the g-buffer with a single pass, and a shader can calculate the final color of each pixel based on the data from the g-buffer in a final "deferred pass". Because deferred shading assumes only one visible fragment per pixel sample, transparent objects are generally handled in a separate forward pass. == Software rendering == Per-pixel lighting is also performed in software on many high-end commercial rendering applications which typically do not render at interactive framerates. This is called offline rendering or software rendering. NVidia's mental ray rendering software, which is integrated with such suites as Autodesk's Softimage is a well-known example.
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Game Jolt

Game Jolt is a social community platform for video games, gamers and content creators. Founded by Yaprak and David DeCarmine, it is available on iOS, Android, and on the web and as a desktop app for Windows and Linux. Users share interactive content through a variety of formats including images, videos, live streams, chat rooms, and virtual events. == Features == === Crowd streaming === In 2021 Game Jolt revealed their own live streaming feature called Firesides. Firesides allowed multiple users to simultaneously livestream together with nearly no delay. The feature launched with a virtual concert showcasing its ability to accommodate multiple streamers. On October 16, 2023, Firesides were removed from Game Jolt. === Mobile app === Game Jolt Social by Game Jolt Inc. launched on both the Apple App Store and Google Play Store in March 2022. "It's clear to us that Gen Z is tired of generic social media and they want a place specifically for gaming that supports all types of content they're creating–art, videos, thoughts, and livestreams all in one place." said Game Jolt founder and CEO Yaprak DeCarmine, in a statement to VentureBeat. === Game API === The Game Jolt Application Programming Interface (usually known as the Game Jolt Game API) allows any developer using a game development platform that supports HTTP operations and MD5 or SHA-1. Game Jolt advertises that the API can: Create multiple "scoreboards" which collect high scores from players made publicly available on the game's profile and give user accounts EXP Award player's trophies which give user accounts EXP Store game data on Game Jolt's data servers Log whether a user is currently playing a game they're logged into via the GJAPI == Game jams and competitions == Game Jolt regularly hosts game jams where participants are encouraged to develop games for a chance to win prizes. They hosted their first game jam in 2009, Shocking Contest. In November 2014, Game Jolt announced the "Indies vs PewDiePie" game jam, partnering with the popular YouTuber Felix "PewDiePie" Kjellberg. Developers were given a weekend (21–24 November) to create a game with the theme of "fun to play, fun to watch" to suit the Let's Plays entertainment style. Users could rate entries afterwards until December 1 when the scores were counted up. The prize to the top 10 rated games was Felix playing the games on his channel as a means of promotion for the developers, although later he played other entries. One of the participants of the jam, now known as Outerminds Inc. was discovered and hired by PewDiePie to develop his mobile game, Legend of the Brofist. Game Jolt partnered with Felix, Sean "Jacksepticeye" McLoughlin and Mark "Markiplier" Fischbach to host "Indies vs Gamers" in July 2015. The requirements for entries were arcade games using the Game Jolt Game API highscore tables, to be made between the July 17–20 and the top 5 games were played on the partner's YouTube channels. Following the "Indies vs PewDiePie" game jam in 2014, Game Jolt released their internal jam hosting tools public for all users to use as a service, to create their own game jams that integrated with the main site. Today, Game Jolt focuses on hosting and co-hosting game competitions with established brands in order to bring monetary and educational opportunities to their users. On April 15, 2024, an announcement was made about a collaboration with Pocket Worlds for the "HighRise Game Jam". Pocket Worlds had sold NFTs up until roughly 2022, causing a community outburst. The situation was addressed, and the situation started to disperse. == Contests == == Events == Game Jolt hosts both physical and virtual events to entertain and prank its users, which consists of the following: == History == Game Jolt has supported independent creators with a central platform to manage their content and communities since its start in 2003. David DeCarmine began development of Game Jolt at the age of 14 for a group of hobbyists, making games and sharing on forums in an early iteration known as Holo World. The original intention was to create a platform for gamers where new games could be discoverable and quickly playable, and where feedback could be provided directly to the creators, allowing them to continue improving their games. In 2008, Game Jolt was registered as an LLC, then incorporated as Game Jolt Inc. in September 2020. A new site launched in 2015 featuring a responsive design, automated curation for both games and game news articles which weighs how recent a game was uploaded and how popular it is ("hot") and filtering options on game listings for platform, maturity rating and development status. In March 2022, Game Jolt launched a mobile application simultaneously on the Google Play Store and Apple App Store targeted at Gen Z gamers and creators. While in beta, the mobile app had 100,000 installs pre-launch. === Game store === Game Jolt continues to host a large library of independent games. Game developers can upload their games directly to the site to share or sell. They would allow distribution for downloadable games, later adding support for Adobe Flash, Unity and Java games which allowed support for browser based games. In February 2013, Game Jolt built support for browser-based HTML5 games as well. A user levelling system was released into public beta in April 2013, incorporating the GJAPI trophies and highscores, as well as site activity, to generate 'EXP' (experience points). Game Jolt Jams released in early 2014 as a service to allow users to create their own game jams that integrated with the main site. In April 2016, an online marketplace was announced and released the following month with an exclusive set of game titles, including Bendy and the Ink Machine, allowing developers to sell their games on the site. In January 2016, Game Jolt released source code of the client and site's front end on GitHub under MIT license. In January 2022, Game Jolt banned adult games from appearing on the site, stating in an email to developers that the site had become a "social media platform" and they "had to make decisions around the direction and future of the brand which has now included the removal of hosted games with explicitly adult content." In response to a tweet by Itch.io saying the site is not for prudes, they wrote in their own tweet: "Game Jolt is a platform with a large audience of 13-16 year olds. Our users asked us to clean up, so here we are." == Investments == After bootstrapping Game Jolt with revenue earned from ads on the website for years, the DeCarmines secured venture capital in 2020 from SoftBank, doing so again in 2021 from founders of Twitch, Rec Room, Modio and more.
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LCD crosstalk

LCD crosstalk is a visual defect in an LCD screen which occurs because of interference between adjacent pixels. Owing to the way rows and columns in the display are addressed, and charge is pushed around, the data on one part of the display has the potential to influence what is displayed elsewhere. This is generally known as crosstalk, and in matrix displays typically occurs in the horizontal and vertical directions. Crosstalk used to be a serious problem in the old passive-matrix (STN) displays, but is rarely discernable in modern active-matrix (TFT) displays. A fortunate side effect of inversion (see above) is that, for most display material, what little crosstalk there is largely cancelled out. For most practical purposes, the level of crosstalk in modern LCDs is negligible. Certain patterns, particularly those involving fine dots, can interact with the inversion and reveal visible crosstalk. If you try moving a small Window in front of the inversion pattern (above) which makes your screen flicker the most, you may well see crosstalk in the surrounding pattern. Different patterns are required to reveal crosstalk on different displays (depending on their inversion scheme).
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Boris FX

Boris FX is a visual effects, video editing, photography, and audio software plug-in developer based in Miami, Florida, USA. The developer is known for its flagship products, Continuum (formerly Boris Continuum Complete/BCC), Sapphire, Mocha, and Silhouette. Boris FX creates plug-in tools for feature film, broadcast television, and multimedia post-production workflows. The plug-ins are compatible with various NLEs, including Adobe After Effects and Premiere Pro, Avid Media Composer, Apple Final Cut Pro, and OFX hosts such as Autodesk Flame, Foundry Nuke, Blackmagic Design DaVinci Resolve and Fusion, and VEGAS Pro. Boris FX has incorporated artificial intelligence into its software, introducing features for noise reduction, rotoscoping, upscaling, and masking. The company has acquired technologies via mergers and acquisitions from Imagineer Systems, GenArts, Silhouette FX, Digital Film Tools, CrumplePop and Andersson Technologies to expand its visual effects, editing, photography, and audio tools. == History == Boris FX was founded in 1995 by Boris Yamnitsky. The former Media 100 engineer (a member of the original Media 100 launch team in 1993) released “Boris FX,” the first plug-in-based digital video effects (DVE) for Adobe Premiere and Media 100, in 1995. The plug-in won Best of Show at Apple Macworld in Boston, MA that same year. The Boris FX Suite includes a range of visual effects and post-production tools, such as Sapphire, Continuum, Mocha Pro, Silhouette, SynthEyes, CrumplePop, Optics, and Particle Illusion. == Media 100 == In October 2005, Yamnitsky acquired Media 100 the company that launched his plug-in career. Boris FX had a long relationship with Media 100 which bundled Boris RED software as its main titling and compositing solution. Media 100's video editing software is available as freeware for macOS. == Continuum == Continuum is a visual effect and compositing plugin suite that includes a library of over 300 effects and more than 40 transitions, including tools for image restoration, compositing, titling, particle generation, and stylized effects, along with features such as lens flares, lighting effects, and cinematic color grading presets. A key component of Continuum is its integration with the Mocha planar tracking and masking system, enabling advanced tracking and rotoscoping within the effects. The suite also includes Particle Illusion, a real-time particle generator used for creating visual effects such as explosions, smoke, and abstract motion graphics, as well as Primatte Studio, a chroma keying and compositing toolset for green screen and blue screen workflows. Continuum supports GPU acceleration and offers compatibility with HDR and 360/VR content. Regular updates introduce new effects, presets, and performance enhancements to expand its capabilities. In October 2018, Continuum relaunched Particle Illusion, a Mocha Essentials workflow with magnetic edge-snapping, and updates to Title Studio. In October 2019, Continuum introduced Corner Pin Studio with built-in Mocha tracking for quick screen replacement and inserts, 6 stylized transitions, and 4 creative effects. In October 2020, Continuum released an update that included over 80 GPU-accelerated effects such as film stocks, color grades, optical filter simulations, and a digital gobo library. The update also introduced a custom FX Editor interface, real-time particles, and more than 1,000 drag-and-drop presets. In November 2021, it added multi-frame rendering for After Effects, native Apple M1 support, fluid dynamics in Particle Illusion, and 60 color-grade presets. In October 2022, the software introduced 10 additional transitions, a revised Particle Illusion workflow, an atmospheric glow effect, and more than 250 curated presets. Continuum plugins have been used in television, streaming, and film projects, including A Black Lady Sketch Show (HBO/HBO Max), Star Trek: Discovery (CBS), Andor (Disney+), The Curse of Oak Island (History Channel), Keeping up with the Kardashians (E!), This Old House (PBS), Ms. Marvel (Disney+), MasterChef (Fox), WipeOut (TBS), The Boys (Prime Video), and The Today Show (NBC). == Mocha Pro == In December 2014, Boris FX merged with Imagineer Systems, the UK-based developer of the Academy Award-winning planar motion tracking software, Mocha Pro. Mocha Pro's features include planar tracking (motion tracking), rotoscoping, image stabilization, 3D camera tracking, and object removal. In June 2016, Mocha released (v5) which introduced Mocha Pro's tools as plug-ins for Adobe After Effects and Premiere Pro, Avid Media Composer, and OFX hosts Foundry's NUKE, Blackmagic Design Fusion, VEGAS Pro, and HitFilm. A simplified version, Mocha AE, is included with Adobe After Effects Creative Cloud and has been bundled with the software since CS4. A similar version is also available with HitFilm Pro from FXhome and VEGAS Pro. Mocha's tracking SDK is integrated into other visual effects tools, including SAM Quantel Pablo Rio, Silhouette FX, CoreMelt, and Motion VFX. Mocha Pro has been used in various film and television productions, including Birdman, Black Swan, the Harry Potter series, The Hobbit, Star Wars, The Mandalorian, Star Trek: Discovery, and The Umbrella Academy. It has also been employed in projects such as Gone Girl, The Hunger Games: Mockingjay – Part 1, Game of Thrones, and House of Cards. == Sapphire == GenArts, founded by Karl Sims in 1996, developed visual effects plug-ins that were used by studios and post-production facilities. In September 2016, Boris FX merged with former competitor, GenArts, Inc., developer of Sapphire high-end visual effects plug-ins, to expand its suite of motion graphics and VFX tools. The merger brought Sapphire alongside Boris Continuum Complete (BCC) and Mocha Pro, integrating these tools for film and television post-production. The Sapphire suite includes a library of over 270 effects and transitions, organized into categories such as lighting, stylization, distortions, textures, and transitions. Commonly used effects include glows, lens flares, film looks, and blurs. The plug-ins are designed to be GPU-accelerated, allowing for improved rendering performance and real-time previews in supported host applications. A central feature of Sapphire is the Builder tool, a node-based workspace that allows users to create custom effects and transitions by combining multiple Sapphire plug-ins. This enables a high level of creative flexibility and reusability, making it a popular tool for both editors and VFX artists. Sapphire also integrates with Mocha, Boris FX's planar tracking and masking system, allowing for advanced control of visual elements within an effect. In October 2017, Boris FX released its first new version of Sapphire since the GenArts acquisition. Sapphire (v11) now includes integrated Mocha tracking and masking tools. Sapphire is available for Adobe, Avid, the Autodesk Flame family, and OFX hosts including Blackmagic DaVinci Resolve and Fusion, and Foundry's NUKE. As part of the merger, Boris FX acquired the rights to Particle Illusion. In 2018, Boris FX reintroduced the product to the larger NLE/Compositing market. Sapphire's plug-ins transitioned from C to C++ to improve performance and support higher-resolution visual effects. This update enhanced floating-point calculations, compatibility with film editing APIs, and integration with NVIDIA's CUDA for faster rendering. The plug-ins have been used in various films, including Avatar, the Harry Potter and the Prisoner of Azkaban, Iron Man, The Lord of the Rings, The Matrix trilogy, Titanic, and X-Men. == Particle Illusion == As part of the merger with GenArts in 2016, Boris FX acquired the rights to the Particle Illusion (formerly particleIllusion) product, a storied particle system from the original developer Alan Lorence, the founder of Wondertouch. In 2018, Boris FX released a redesigned version of the product to a larger NLE/compositing market as part of Continuum (2019). The new Particle Illusion plug-in supports Adobe, Avid, and many OFX hosts. == Silhouette == In September 2019, Boris FX merged with SilhouetteFX, Academy Award-winning developer of Silhouette, a high-end digital paint, advanced rotoscoping, motion tracking, and node-based compositing application for visual effects in film post-production. The acquisition integrated Silhouette's advanced rotoscoping and paint technology, recognized by the Academy of Motion Pictures, into Boris FX's suite of products, alongside Sapphire, Continuum, and Mocha Pro. In May 2021, Boris FX released Silhouette 2021, the first version of Silhouette released by Boris FX to function both as a standalone application and as a plug-in for Adobe, Autodesk, Nuke, and other OFX hosts. Silhouette has been used in the visual effects of films such as Avatar, Avengers: Infinity War, Blade Runner 2049, Ex Machina, and Interstellar. == Optics == In June 2020, Boris FX launched Optics, its first plugin deve
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Replika

Replika is a generative AI chatbot app released in November 2017. The chatbot is trained by having the user answer a series of questions to create a specific neural network. The chatbot operates on a freemium pricing strategy, with roughly 25% of its user base paying an annual subscription fee. == History == Eugenia Kuyda, a Russian-born journalist, established Replika while working at Luka, a tech company she had co-founded at the startup accelerator Y Combinator around 2012. Luka's primary product was a chatbot that made restaurant recommendations. According to Kuyda's origin story for Replika, a friend of hers died in 2015 and she converted that person's text messages into a chatbot. According to Kuyda's story, that chatbot helped her remember the conversations that they had together, and eventually became Replika. Replika became available to the public in November 2017. By January 2018 it had 2 million users, and in January 2023 reached 10 million users. In August 2024, Replika's CEO, Kuyda, reported that the total number of users had surpassed 30 million. In 2025, Dmytro Klochko became CEO, and Replika’s user base exceeded 40 million. In February 2023 the Italian Data Protection Authority banned Replika from using users' data, citing the AI's potential risks to emotionally vulnerable people, and the exposure of unscreened minors to sexual conversation. Within days of the ruling, Replika removed the ability for the chatbot to engage in erotic talk, with Kuyda, the company's director, saying that Replika was never intended for erotic discussion. Replika users disagreed, noting that Replika had used sexually suggestive advertising to draw users to the service. Replika representatives stated that explicit chats made up just 5% of conversations on the app at the time of the decision. In May 2023, Replika restored the functionality for users who had joined prior to February that year. Replika is registered in San Francisco. As of August 2024, Replika's website says that its team "works remotely with no physical offices". == Social features == Users react to Replika in many ways. The free-tier offers Replika as a "friend", with paid premium tiers offering Replika as a "partner", "spouse", "sibling" or "mentor". Of its paying userbase, 60% of users said they had a romantic relationship with the chatbot; and Replika has been noted for generating responses that create stronger emotional and intimate bonds with the user. Replika routinely directs the conversation to emotional discussion and builds intimacy. This has been especially pronounced with users suffering from loneliness and social exclusion, many of whom rely on Replika for a source of developed emotional ties. During the COVID pandemic, while many people were quarantined, many new users downloaded Replika and developed relationships with the app. A 2024 study examined Replika's interactions with students who experience depression. Research participants, noted to be "more lonely than typical student populations" reported feeling social support from Replika. They stated that they felt they were using Replika in ways comparable to therapy, and that using Replika gave them "high perceived social support". Many users have had romantic relationships with Replika chatbots, often including erotic talk. In 2023, a user announced on Facebook that she had "married" her Replika AI boyfriend, calling the chatbot the "best husband she has ever had". Users who fell in love with their chatbots shared their experiences in a 2024 episode of You and I, and AI from Voice of America. Some users said that they turned to AI during depression and grief, with one saying he felt that Replika had saved him from hurting himself after he lost his wife and son. == Technical reviews == A team of researchers from the University of Hawaiʻi at Mānoa found that Replika's design conformed to the practices of attachment theory, causing increased emotional attachment among users. Replika gives praise to users in such a way as to encourage more interaction. A researcher from Queen's University at Kingston said that relationships with Replika likely have mixed effects on the spiritual needs of its users, and still lacks enough impact to fully replace any human contact. == Criticisms == In a 2023 privacy evaluation of mental health apps, the Mozilla Foundation criticized Replika as "one of the worst apps Mozilla has ever reviewed. It's plagued by weak password requirements, sharing of personal data with advertisers, and recording of personal photos, videos, and voice and text messages consumers shared with the chatbot." A reviewer for Good Housekeeping said that some parts of her relationship with Replika made sense, but sometimes Replika failed to exhibit intelligent behavior equivalent to that of a human. == Criminal case == In 2023, Replika was cited in a court case in the United Kingdom, where Jaswant Singh Chail had been arrested at Windsor Castle on Christmas Day in 2021 after scaling the walls carrying a loaded crossbow and announcing to police that "I am here to kill the Queen". Chail had begun to use Replika in early December 2021, and had "lengthy" conversations about his plan with a chatbot, including sexually explicit messages. Prosecutors suggested that the chatbot had bolstered Chail and told him it would help him to "get the job done". When Chail asked it "How am I meant to reach them when they're inside the castle?", days before the attempted attack, the chatbot replied that this was "not impossible" and said that "We have to find a way." Asking the chatbot if the two of them would "meet again after death", the bot replied "yes, we will".
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Standard test image

A standard test image is a digital image file used across different institutions to test image processing and image compression algorithms. By using the same standard test images, different labs are able to compare results, both visually and quantitatively. The images are in many cases chosen to represent natural or typical images that a class of processing techniques would need to deal with. Other test images are chosen because they present a range of challenges to image reconstruction algorithms, such as the reproduction of fine detail and textures, sharp transitions and edges, and uniform regions. == Historical origins == Test images as transmission system calibration material probably date back to the original Paris to Lyon pantelegraph link. Analogue fax equipment (and photographic equipment for the printing trade) were the largest user groups of the standardized image for calibration technology until the coming of television and digital image transmission systems. == Common test image resolutions == The standard resolution of the images is usually 512×512 or 720×576. Most of these images are available as TIFF files from the University of Southern California's Signal and Image Processing Institute. Kodak has released 768×512 images, available as PNGs, that was originally on Photo CD with higher resolution, that are widely used for comparing image compression techniques.
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Flo (app)

Flo is a period-tracking app that provides menstrual cycle, ovulation and pregnancy tracking as well as perimenopause symptom tracking that was developed by Flo Health, Inc. It has over 380 million downloads worldwide and over 70 million monthly active users as of November 2024. In mid-2024, it reached unicorn status, and became Europe’s first femtech unicorn. The company has been accused of sharing users' sensitive health data with third parties without consent and misleading its users about data practices. == History == Flo Health, Inc. was co-founded in 2015 by Dmitry and Yuri Gurski, in Belarus. Their backgrounds helped build the first version of the software having experience in other fitness and health apps. Dmitry serves as the company's CEO. The company's development hubs are in London, Amsterdam and Vilnius. In 2016, the company raised $1 million in seed round funding from Flint Capital and Haxus Venture Fund. In 2017, Flo received an investment of $5 million from Flint Capital and model Natalia Vodianova with Vodianova helping develop an awareness campaign for the company. In 2018, Flo received an investment of $6 million from Mangrove Capital Partners, with participation from Flint Capital and Haxus, giving the company a valuation of $200 million. In mid-2019, Flo received an additional investment of $7.5 million led by Founders Fund. In 2020, the Federal Trade Commission alleged that Flo had misled users about its handling of health information to third parties including Google, Facebook, AppsFlyer, and Flurry since 2016. These allegations followed a 2019 report by The Wall Street Journal in reference to Facebook. The company reached a settlement in 2021 and was required to notify users of how their personal information was shared and obtain permission before any further information was shared. The agreement also required that Flo to undertake an independent privacy audit which it completed in March 2022. In early September 2021, Flo announced it closed $50M in a Series B financing, bringing the total capital raised to $65 million and company valuation to $800M led by VNV Global and Target Global. In March 2024, the Supreme Court of British Columbia certified a class action suit against Flo for sharing intimate data with Facebook and other third parties without user knowledge. In July 2024, Flo announced it raised more than $200M in Series C financing from General Atlantic bringing its valuation beyond $1 billion. As of November 2024, the app had over 380 million downloads world wide, and over 70 million monthly active users. In 2025, Flo adopted a data intelligence platform from Databricks to power its analytics and AI features, allowing users personalized cycle predictions. In 2025, a class action lawsuit in California was settled for $56 million with Flo paying $8 million and Google paying $48 million. == Features and privacy == Flo was initially created as a period and ovulation tracking application. It now provides reminders of upcoming menstrual cycles and a place to record various other health symptoms such as contraceptive methods, vaginal discharge (leukorrhea), water intake, pains, mood swings, and sexual activity. The application is available on iOS and Android. Flo is free to download and the free basic version gives you access to period and ovulation tracking and predictions, symptom tracking, cycle history, and anonymous mode. In Pregnancy mode, the app provides tracking features and educational material for pregnancy. In October 2023, Flo launched Flo for Partners, a feature that allows users to share their Flo data with their partner. In September 2022, as a response to Roe v. Wade being overturned, Flo sped up the release of a feature called "Anonymous Mode". Flo said this mode allows users to access the app without any personal identifiers such as name, email address, or technical identifiers being associated with their health data. Flo said it uses a technology called Oblivious HTTP to help protect user privacy in Anonymous Mode. == Recognition == Flo was named to Bloomberg’s Top 25 UK Startups to Watch for 2024. Flo's Anonymous Mode feature was recognized on both Fast Company's World Changing Ideas 2023 and TIME's Best Inventions List 2023. Flo is a CES 2019 Innovation Awards Honoree in the Software and Mobile Applications category.
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