VistaCreate (formerly Crello) is an online graphic design platform for non-designers, launched in 2016. As of 2022, it has more than 10 million users in 192 countries. == Overview == VistaCreate (then known as Crello) was launched in 2016 as a part of Depositphotos. In 2019, the product hit a milestone of 1 million registered users and also launched mobile apps. In 2020, the library of templates and objects became free. A music library and a background remover tool were added to the platform. In May 2021, Moufflons Basketball, in collaboration with VistaCreate, organized a poster design competition in support of gender equality in sports. In October 2021, Vistaprint acquired Crello and its parent company, Depositphotos, for a total price of $85 million. After the acquisition, Crello was rebranded to VistaCreate. Along with Vistaprint and 99designs, it became part of the new Vista parent brand. After Russia started a full-scale war on the territory of Ukraine in February 2022, VistaCreate suspended all business in Russia and Belarus. VistaCreate's team and Depositphotos gathered collections of images and templates dedicated to the war in Ukraine.
Kuaishou
Kuaishou Technology is a Chinese publicly traded partly state-owned holding company based in Haidian District, Beijing, that was founded in 2011 by Hua Su (Chinese: 宿华) and Cheng Yixiao (Chinese: 程一笑). The company, listed on the Hong Kong Stock Exchange, is known for developing a mobile app for sharing users' short videos, a social network, and video special effects editor. The app is known as Kwai in many countries outside of China. It is also known as Snack Video in India, Pakistan and Indonesia. == Ownership and governance == Kuaishou's overseas team is led by the former CEO of the application 99, and staff from Google, Facebook, Netflix, and TikTok were recruited to lead the company's international expansion. The China Internet Investment Fund, a state-owned enterprise controlled by the Cyberspace Administration of China, holds a golden share ownership stake in Kuaishou. == History == Kuaishou is China's first short video platform that was developed in 2011 by engineer Hua Su and Cheng Yixiao. Prior to co-founding Kuaishou, Su Hua had worked for both Google and Baidu as a software engineer. The company is headquartered in Haidian District, Beijing. Kuaishou's predecessor "GIF Kuaishou" was founded in March 2011. GIF Kuaishou was a mobile app with which users could make and share GIF pictures. In 2013, Kuaishou became a short-video social platform. By 2013, the app had reached 100 million daily users. By 2019, it had exceeded 200 million active daily users. In March 2017, Kuaishou closed a US$350 million investment round that was led by Tencent. In January 2018, Forbes estimated the company's valuation to be US$18 billion. In April 2018, Kuaishou's app was briefly banned from Chinese app stores after China Central Television (CCTV) reported on the platform popularizing videos of teenage mothers. In 2019, the company announced a partnership with the People's Daily, an official newspaper of the Central Committee of the Chinese Communist Party, to help it experiment with the use of artificial intelligence in news. In June 2020, following the start of the 2020–2021 China–India skirmishes, the Government of India banned Kwai along with 58 other apps, citing "data and privacy issues". In January 2021, Kuaishou announced it was planning an initial public offering (IPO) to raise approximately US$5 billion. Kuaishou's stock completed its first day of trading at $300 Hong Kong dollars (HKD) (US$38.70), more than doubling its initial offer price, and causing its market value to rise to over $1 trillion HKD (US$159 billion). In February 2021, Kuaishou made a debut on the Hong Kong Stock Exchange, with its shares soaring by 194% at the opening. The company subsequently encountered major setbacks as a result of heightened regulatory restrictions on Chinese internet firms, which contributed to its share price falling by nearly 80% from its post-IPO peak. By December 2021, Kuaishou announced a major reorganization, including the layoff of 30% of its staff, primarily targeting mid-level employees earning an annual salary of $157,000 or more. This restructuring aimed to cut costs and mitigate financial losses. In October 2022, state-owned Beijing Radio and Television Station took a minority ownership stake in Kuaishou. In April 2024, a Financial Times article citing current and former Kuaishou employees stated that the company has been running an ageist redundancy programme known internally as "Limestone", culling workers in their mid-30s. In June 2024, Kuaishou and the Sichuan international communication center launched a branch center in São Paulo, Brazil. In June 2024, Kuaishou released its diffusion transformer text-to-video model, Kling, which they claimed could generate two minutes of video at 30 frames per second and in 1080p resolution. The model has been compared to that of OpenAI's Sora text-to-video model. It is accessible to the public on Kuaishou's video editing app KwaiCut via signing up for a waitlist with a Chinese phone number. In December 2025, Kuaishou came under a cyberattack which led to a temporary influx of violent and pornographic content. == Popularity == As of 2019, it had a worldwide user base of over 200 million, leading the "Most Downloaded" lists of the Google Play and Apple App Store in eight countries, such as Brazil, where it was introduced in 2019. Its main short-video platform competitor was Douyin, which is known as TikTok outside China. Compared to Douyin, Kuaishou is more popular with older users living outside China's Tier 1 cities. Its initial popularity came from videos of Chinese rural life. The app is particularly well known for its "rustic" aesthetic and is popular among rural people. Kuaishou also relied more on e-commerce revenue than on advertising revenue compared to its main competitor. == Reception == Kwai (as the app is called outside of China) was banned in India in 2020 along with other short video apps like TikTok. Kuaishou then released the clone SnackVideo, which was subsequently also banned. The app is one of the most popular social media platforms in Brazil, where Kuaishou partnered with creators to make telenovela style content, and appeals to football fans by working with football teams CR Flamengo and Santos FC and sponsoring the tournament Copa América. Kwai was notable in Brazil for spreading information (and misinformation) about the COVID-19 vaccine and political misinformation. === Manjiao Wenhua === "Manjiao wenhua" (慢脚文化) is a sarcasm term on Chinese internet on the unethical or illegal contents on Kuaishou. State broadcaster China Central Television (CCTV) reported that many contents are about child pregnancy. "Dating, pregnancy, bearing a child...these are strictly prohibited in the real time by a minor, but these contents can easily shown to audiences here." In addition, many students from primary or secondary schools make a pose of smoking. Wang Zhenhui (王贞会) from CUPSL stated that these kinds of bad values will give negative effects to the minors.
REEM
REEM is a prototype humanoid robot built by PAL Robotics in Spain. It is a 1.70 m high humanoid robot with 22 degrees of freedom, with a mobile base with wheels, allowing it to move at 4 km/hour. The upper part of the robot consists of a torso with a touch screen, two motorized arms, which give it a high degree of expression, and a head, which is also motorized. REEM-A and REEM-B are the first and second prototypes of humanoid robots created by PAL Robotics. REEM-B can recognize, grasp and lift objects and walk by itself, avoiding obstacles through simultaneous localization and mapping. The robot accepts voice commands and can recognize faces. == Specifications ==
Plinian Core
Plinian Core is a set of vocabulary terms that can be used to describe different aspects of biological species information. Under "biological species Information" all kinds of properties or traits related to taxa—biological and non-biological—are included. Thus, for instance, terms pertaining descriptions, legal aspects, conservation, management, demographics, nomenclature, or related resources are incorporated. == Description == The Plinian Core is aimed to facilitate the exchange of information about the species and upper taxa. What is in scope? Species level catalogs of any kind of biological objects or data. Terminology associated with biological collection data. Striving for compatibility with other biodiversity-related standards. Facilitating the addition of components and attributes of biological data. What is not in scope? Data interchange protocols. Non-biodiversity-related data. Occurrence level data. This standard is named after Pliny the Elder, a very influential figure in the study of the biological species. Plinian Core design requirements includes: ease of use, to be self-contained, able to support data integration from multiple databases, and ability to handle different levels of granularity. Core terms can be grouped in its current version as follows: Metadata Base Elements Record Metadata Nomenclature and Classification Taxonomic description Natural history Invasive species Habitat and Distribution Demography and Threats Uses, Management and Conservation associatedParty, MeasurementOrFact, References, AncillaryData == Background == Plinian Core started as a collaborative project between Instituto Nacional de Biodiversidad and GBIF Spain in 2005. A series of iterations in which elements were defined and implanted in different projects resulted in a "Plinian Core Flat" [deprecated]. As a result, a new development was impulse to overcome them in 2012. New formal requirements, additional input and a will to better support the standard and its documentation, as well as to align it with the processes of TDWG, the world reference body for biodiversity information standards. A new version, Plinian Core v3.x.x was defined. This provides more flexibility to fully represent the information of a species in a variety of scenarios. New elements to deal with aspects such as IPR, related resources, referenced, etc. were introduced, and elements already included were better-defined and documented. Partner for the development of Plinian Core in this new phase incorporated the University of Granada (UG, Spain), the Alexander von Humboldt Institute (IAvH, Colombia), the National Commission for the Knowledge and Use of Biodiversity (Conabio, Mexico) and the University of São Paulo (USP, Brazil). A "Plinian Core Task Group" within TDWG "Interest Group on species Information" was constituted and currently working on its development. == Levels of the standard == Plinian Core is presented in to levels: the abstract model and the application profiles. The abstract model (AM), comprising the abstract model schema(xsd) and the terms' URIs, is the normative part. It is all comprehensive, and allows for different levels of granularity in describing species properties. The AM should be taken as a "menu" from which to choose terms and level of detail needed in any specific project. The subsets of the abstract model intended to be implemented in specific projects are the "application profiles" (APs). Besides containing part of the elements of the AM, APs can impose additional specifications on the included elements, such as controlled vocabularies. Some examples of APs in use follow: Application profile CONABIO Application profile INBIO Application profile GBIF.ES Application profile Banco de Datos de la Naturaleza.Spain Application profile SIB-COLOMBIA == Relation to other standards == Plinian incorporates a number of elements already defined by other standards. The following table summarizes these standards and the elements used in Plinian Core:
RealSense
RealSense is an American technology company that develops depth cameras and computer-vision systems used in robotics, access control, industrial automation and healthcare. The company’s stereoscopic 3D cameras and software are marketed as a perception platform for “physical AI”, particularly for humanoid robots and autonomous mobile robots (AMRs). RealSense was incubated for more than a decade inside Intel’s perceptual computing and depth-sensing group before being spun out as an independent company in July 2025 with a US$50 million Series A round backed by a semiconductor-focused private equity firm and strategic investors including Intel Capital and the MediaTek Innovation Fund. Following the spin-out, RealSense announced a strategic collaboration with Nvidia to integrate its AI depth cameras with the Nvidia Jetson Thor robotics platform, the Isaac Sim simulation environment and the Holoscan Sensor Bridge for low-latency sensor fusion. In November 2025, Swiss access-solutions provider dormakaba acquired a minority stake in RealSense and formed a partnership to develop AI-powered biometric access-control and security systems for data centres, airports and other critical infrastructure. == History == === Origins in Intel Perceptual Computing === Intel began developing depth-sensing and perceptual-computing technologies in the early 2010s under the Perceptual Computing brand, with research spanning gesture control, facial recognition and eye-tracking systems. The work led to a series of 3D cameras and developer challenge programmes intended to stimulate software ecosystems for natural-user interfaces. In 2014 Intel rebranded the effort as Intel RealSense, positioning the technology as a family of depth cameras and vision processors for PCs, mobile devices and embedded systems. Early devices such as the F200 and R200 were integrated into laptops and tablets from OEMs including Asus, HP, Dell, Lenovo and Acer, and were also sold as standalone webcams by partners such as Razer and Creative. === Refocus on robotics and near-closure === By the late 2010s Intel had steered RealSense away from mainstream PC peripherals toward robotics, industrial and embedded applications, adding stereo and lidar-based depth cameras to the portfolio. In August 2021, trade publication CRN reported that Intel planned to wind down the RealSense business as part of a broader restructuring, raising questions about the future of the product line. Despite that announcement, Intel continued to invest in new custom silicon for depth cameras, and RealSense remained widely used in mobile robots and automation projects. === Spin-out as RealSense Inc. (2025) === On 11 July 2025, Intel completed the spin-out of its RealSense 3D-camera business into a new privately held company, RealSense Inc., and the new entity announced a US$50 million Series A funding round. The round was led by a semiconductor-focused private equity investor with participation from Intel Capital, MediaTek Innovation Fund and other strategics. Independent coverage described RealSense as serving more than 3,000 active customers and supplying depth cameras to a large share of global AMR and humanoid robot platforms. The company stated that it would continue to support the existing Intel RealSense product roadmap while accelerating development of AI-enabled cameras and perception software. === Strategic partnerships and investments === In October 2025 RealSense and Nvidia announced a strategic collaboration centered on integrating RealSense AI depth cameras with Nvidia’s Jetson Thor robotics compute modules, the Isaac Sim simulation environment and the Holoscan Sensor Bridge for multi-sensor streaming. The collaboration is positioned as enabling “physical AI” workloads such as whole-body humanoid control, real-time mapping and safety-critical human–robot interaction. On 19 November 2025, dormakaba announced that it had acquired a minority stake in RealSense and entered into a partnership to co-develop intelligent access-control solutions, including biometric gates for airports and enterprise facilities. The partnership aims to combine RealSense’s depth and facial-authentication technology with dormakaba’s installed base of sensors, doors and turnstiles. == Products == === Depth-camera families === RealSense’s products are sold as modular components (depth modules, vision processors and complete cameras) and as integrated systems with on-device AI. The company continues to offer and support the Intel RealSense D400 family of active-stereo depth cameras (including the D415, D435 and D455), which are widely used in robotics and automation. These devices combine a RealSense Vision Processor from the D4 family with dual infrared imagers and, on some models, an RGB camera. Earlier generations of Intel RealSense cameras, including the F200, R200, SR300 and the L515 lidar camera, remain in use in niche and legacy applications but are no longer the focus of the independent company’s roadmap. === D555 PoE depth camera === The first new hardware platform announced after the spin-out was the RealSense Depth Camera D555, a ruggedised stereo-depth device aimed at industrial and robotics deployments. The D555 uses the longer-range D450 optical module with a global shutter and integrates RealSense’s Vision SoC V5, a new generation of vision processor optimised for neural-network inference and depth computation. Key features highlighted in technical coverage include: Power over Ethernet (PoE), allowing power and data to be delivered over a single cable and supporting both RJ45 and ruggedised M12 connections; an IP-rated enclosure designed for harsh indoor and outdoor environments; a built-in inertial measurement unit (IMU) to support simultaneous localisation and mapping (SLAM) and motion tracking; native support for ROS 2 and integration with the open-source RealSense SDK. According to independent reporting, the D555 is used in AI-enabled embedded-vision applications in mobile robots and fixed industrial systems, and was among the first RealSense products to be tightly integrated with Nvidia’s Jetson Thor and Holoscan platforms for low-latency sensor fusion. === Software and SDK === RealSense cameras are supported by a cross-platform, open-source software stack historically branded as Intel RealSense SDK 2.0. The SDK provides device drivers, depth and point-cloud processing, tracking and calibration tools, and bindings for languages such as C++, Python and C#. The independent company has continued to maintain and extend the SDK for new hardware, including D555 and other Vision SoC V5-based devices, and publishes reference integrations for ROS 2 and industrial-automation frameworks. === Biometrics and access-control products === In addition to general-purpose depth cameras, RealSense offers facial-authentication hardware and software, commonly referred to as RealSense ID, for biometric access control and identity verification. These products combine an active depth sensor with a dedicated neural-network pipeline running on embedded processors, aimed at applications such as secure doors, turnstiles and kiosks. Use-case material published by partners describes deployments of RealSense-based biometric readers in school lunch programmes, agricultural biosecurity checkpoints and enterprise facilities. The dormakaba partnership announced in 2025 extends this portfolio to integrated biometric gates and sensor-equipped doors in airports and data centres. == Applications == === Robotics and automation === RealSense depth cameras are used in autonomous mobile robots, humanoid robots, drones and industrial automation systems for tasks such as obstacle avoidance, navigation and manipulation. Reuters reported in 2025 that RealSense cameras were embedded in around 60 percent of the world’s AMRs and humanoid robots, citing customers including Unitree Robotics and ANYbotics. Developers and integrators use RealSense systems with platforms such as Nvidia Jetson, ROS and proprietary motion-planning stacks. === Biometrics and security === RealSense technology is also applied in biometric access control and surveillance, where depth and infrared imaging are used to improve anti-spoofing performance for facial recognition. The dormakaba investment and collaboration is aimed at integrating these capabilities into boarding gates, staff entrances and secure facilities, with RealSense providing perception hardware and algorithms and dormakaba providing access-control infrastructure and global distribution. == Reception == Early coverage of Intel RealSense for consumer PCs noted that the technology’s impact would depend on the availability of compelling software and use cases for depth-sensing cameras. Later reporting on the spin-out has characterised the new company as part of a broader wave of investment in robotics and physical AI, with some analysts suggesting that RealSense’s installed base and patent portfolio give it an advantage as dep
Clips (software)
Clips is a discontinued mobile video editing software application created by Apple Inc. It was released onto the iOS App Store on April 6, 2017, for free. Initially, it was only available on 64-bit devices running iOS 10.3 or later; as of version 3.1.3, it requires iOS 16.0 or later. Apple describes it as an app for "making and sharing fun videos with text, effects, graphics, and more.". Its final release was on May 9, 2024 before was removed from the App Store on October 10, 2025. == Features == After launching of the app, the user sees the view of the front-facing camera. The app allows the user to create a new clip by tapping on a red record button, or use photos or videos from the device's photo library. Once a clip is recorded, it can be added to a project timeline shown at the bottom of the screen. The user can share their project on social media platforms. The user can also add filters and effects to the project. "Live Titles" (available in several styles) can also be created by dictating to the device.
Lighthill report
Artificial Intelligence: A General Survey, commonly known as the Lighthill report, is a scholarly article by James Lighthill, published in Artificial Intelligence: a paper symposium in 1973. It was compiled by Lighthill for the British Science Research Council as an evaluation of academic research in the field of artificial intelligence (AI). The report gave a very pessimistic prognosis for many core aspects of research in this field, stating that "In no part of the field have the discoveries made so far produced the major impact that was then promised". It "formed the basis for the decision by the British government to end support for AI research in most British universities", contributing to an AI winter in the United Kingdom. == Publication history == It was commissioned by the SRC in 1972 for Lighthill to "make a personal review of the subject [of AI]". Lighthill completed the report in July. The SRC discussed the report in September, and decided to publish it, together with some alternative points of view by Stuart Sutherland, Roger Needham, Christopher Longuet-Higgins, and Donald Michie. The SRC's decision to invite the report was partly a reaction to high levels of discord within the University of Edinburgh's Department of Artificial Intelligence, one of the earliest and biggest centres for AI research in the UK. On May 9, 1973, Lighthill debated several leading AI researchers (Donald Michie, John McCarthy, Richard Gregory) at the Royal Institution in London concerning the report. == Content == While the report was supportive of research into the simulation of neurophysiological and psychological processes, it was "highly critical of basic research in foundational areas such as robotics and language processing". The report stated that AI researchers had failed to address the issue of combinatorial explosion when solving problems within real-world domains. That is, the report states that whilst AI techniques may have worked within the scope of small problem domains, the techniques would not scale up well to solve more realistic problems. The report represents a pessimistic view of AI that began after early excitement in the field. The report divides AI research into three categories: Advanced Automation ("A"): applications of AI, such as optical character recognition, mechanical component design and manufacture, missile perception and guidance, etc. Computer-based Central Nervous System research ("C"): building computational models of human brains (neurobiology) and behavior (psychology). Bridge, or Building Robots ("B"): research that combines categories A and C. This category is intentionally vague. Projects in category A had had some success, but only in restricted domains where a large quantity of detailed knowledge was used in designing the program. This was disappointing to researchers who hoped for generic methods. Due to the issue of the combinatorial explosion, the amount of detailed knowledge required by the program quickly grew too large to be entered by hand, thus restricting projects to restricted domains. Projects in category C had had some measure of success. Artificial neural networks were successfully used to model neurobiological data. SHRDLU demonstrated that human use of language, even in fine details, depends on the semantics or knowledge, and is not purely syntactical. This was influential in psycholinguistics. Attempts to extend SHRDLU to larger domains of discourse was considered impractical, again due to the issue of the combinatorial explosion. Projects in category B were held to be failures. One important project, that of "programming and building a robot that would mimic human ability in a combination of eye-hand co-ordination and common-sense problem solving", was considered entirely disappointing. Similarly, chess playing programs were no better than human amateurs. Due to the combinatorial explosion, the run-time of general algorithms quickly grew impractical, requiring detailed problem-specific heuristics. The report stated that it was expected that within the next 25 years, category A would simply become applied technologies engineering, C would integrate with psychology and neurobiology, while category B would be abandoned.