AI Generator Zdjec Za Darmo

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

AppyStore

AppyStore is a comprehensive learning videos and games app for kids up to the age of 8 years. The platform developed by Mauj Mobile, a mobile value-added services (VAS) provider curates content to help in child development by leveraging technology. Mauj is funded by Sequoia Capital, Westbridge Capital and Intel Capital. == Background == AppyStore was launched in 2014 as a platform providing content for kids between the ages of 1.5 and 6 years. AppyStore subsequently extended its services for kids up to 8 years of age. The company operates on a subscription-based model and claims to have 5,000 learning games and videos segregated in 18 learning areas developed to help children gain optimal skills and qualities. According to an article published in Business Standard, the application is claimed to be one of the top 5 apps that help to enhance the logical and imaginative capabilities of children. AppyStore was awarded the Best app for kids by Google Play in December 2017. == Service == The company provides content via a website and an Android app. The website and android app provide learning games, rhymes, phonics, reading, stories, science, numbers, maths, logic videos comprising puzzles, worksheets, videos and fun activities and the premium subscription also includes physical worksheets which are home delivered. This content is educational and has been handpicked by teachers and experts with an understanding of the major areas of child development milestones for children up to 8 years of age. The mobile application also allows parents to track the progress of their child on the basis of the number of videos viewed.
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Dropbox Carousel

Dropbox Carousel was a photo and video management app offered by Dropbox. The third-party native app, available on Android and iOS, allowed users to store, manage, and organize photos. Photos were organized by date, time and event and backed up on Dropbox. It competed in this space against other online photo storage services such as Google's Google Photos, Apple's iCloud, and Yahoo's Flickr. Chris Lee, Dropbox's head of product development for Carousel described the app as an add-on to Dropbox, a “dedicated experience for photos and videos” and a space for “reliving personal memories”. == History == Mailbox founder, Gentry Underwood unveiled Carousel at a gathering in San Francisco on April 9, 2014. Much of the features in Carousel come from Snapjoy, a photo start-up, that Dropbox acquired on December 19, 2012. When Carousel was launched, it marked amongst many others, a series of acquisitions made by Dropbox to prep up before opening its stock for public offering. The acquisitions would help demonstrate its expansive product offerings pitching potential profitability to investors. In December 2015, Dropbox announced that Carousel would be shut down and some Carousel features would be integrated into the primary Dropbox application. On March 31, 2016, Carousel was deactivated. == Features == Carousel prompted users to free local storage once it had synced and backed-up local photos to the cloud. Flashback was a feature (enabled by default) that showed past photos or videos taken the same day, a year, or some years back. Flashback used an algorithm designed to identify human faces - resulting in greater likelihood of the user's picture or people in the user's close circle appearing. A scrollable timeline, which was earlier a scroll wheel, at the bottom let the user scroll to photo(s) at a specific date with a finger swipe.
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Write or Die

Write or Die is an online web application designed to combat writer's block by letting users of the application punish themselves if they slow down or stop typing in the application's window. How severe the punishments are depends on the mode the user chooses, which ranges from "Gentle" to "Kamikaze". It was reviewed by publications PCWorld, the Los Angeles Times and The Guardian, and it was most notably used by writers Helen Oyeyemi and David Nicholls. The creator, Jeff Printy, explained that he wrote the application because he wants "to be published and make a living as a writer."
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Azure Maps

Azure Maps is a suite of cloud-based, location-based services provided by Microsoft as part of the company's Azure platform. The platform provides geospatial and location-based services via REST APIs and software development kits (SDKs). The service is typically used to integrate maps or geospatial data into applications. Azure Maps differs from Microsoft's other enterprise mapping service, Bing Maps, in its pricing model, focus on privacy, and its level of integration into the broader Azure cloud ecosystem. == History == Azure Maps was first introduced in public preview mode under the name "Azure Location Based Services" in 2017, primarily as an enterprise solution. The services was intended to add mapping and location-based functionality onto the existing Azure cloud services suite, seen as a critical part of Microsoft's broader Internet-of-Things (IoT) strategy. The preview version included APIs which could be used to develop location aware apps for use cases such as logistics and mobility. In 2018, the software was renamed "Azure Maps," and became generally available to the public, and a number of new functions were added, including route calculation, travel time calculation, and incorporation of real-time traffic data and incident information. Azure Maps was integrated with Azure IoT Central in 2018, which added tracking, monitoring, and geofencing capabilities. A set of mobility APIs on were added in 2019, with applications such as use in public transport apps and shared bicycle fleet management. “Azure Maps Creator,” which converts private facility floor plans into indoor map data, was also introduced in 2019. Some commentators linked these services to Microsoft's broader development of augmented reality products. In 2020, Azure Maps Visual for Power BI was released, integrating location-based features and mapping capabilities into Microsoft's business intelligence software. An elevation API (which was later retired), geolocation services, and an iOS and Android software development kit were introduced in 2021. In 2022, support for historical weather, air quality, and tropical storm data was made generally available and custom styling for indoor maps was also introduced. In 2023, Azure Maps was certified as HIPAA compliant in a move to target healthcare and health insurance companies. == Functionality == === Geocoding === Geocoding is one of the core functionalities of Azure Maps, converting addresses or place names into geographic coordinates. Batch geocoding is used to process large amounts of address data, a function used for route optimization and spatial analysis. === Reverse geocoding === Reverse geocoding derives human-readable information from geographic coordinates like longitude and latitude, used in navigation and by geographic information systems. === Routing === Azure Maps uses map data and routing algorithms to calculate the shortest or fastest routes between locations based on factors like vehicle size and type, traffic conditions, and distance. Routing also supports multi-modal routing, which include multiple modes of transport in a single trip, including cycling, walking, and ferries. This functionality is used for location-based searches and route optimization in applications like fleet management, proximity marketing, and emergency services as well as logistics and delivery, urban planning, ride sharing apps, and outdoor activities. === Map visualization === The platform supports map visualizations that can be modified to reflect real-time data (including from IoT sensors) as well as historical data patterns. Visualizations include heat maps, street maps, satellite imagery and other custom data layers. Maps are rendered using raster or vector tiles which reduce the load of displaying large data sets or complex maps. This can be used in various applications in areas like transportation, smart cities, retail and marketing, public health, and environmental monitoring. For example, it can be used for tracking the spread of diseases or measuring the impact of changing climatic patterns. === Geofencing and spatial analytics === Azure Maps supports polygonal geofencing, which enables the definition of custom geographic boundaries. Geofenced areas can be monitored in real-time for events of interest. For example, an application could send an alert when equipment or persons enter or leave a defined area. Tools for analyzing historical geofencing data are also available via the APIs for optimization purposes. == Industry usage == Azure Maps' geofencing function has seen usage in the construction industry, designating hazardous areas for safety purposes and sending alerts if anyone enters the area. Private facility maps are used by construction companies for monitoring large construction sites to increase productivity and prevent accidents or damage. In emergency management, New Zealand based company Beca has used Azure Maps to provide analysis on the impact of earthquakes to users, including information on the severity and location of an earthquake and the impact on affected properties. Alaska's Department of Transportation uses Azure Maps as part of an information system providing weather-related warnings and analytics to road crews. Airmap, an airspace management platform for drones, uses Azure Maps. Azure Maps has also been used in conjunction with Azure Monitor for risk monitoring by an insurance company. Other companies that use or have used Azure Maps include BMW, Banco Santander, Jvion, MV Transportation, C.H. Robertson, Wise Skulls, Tata Consultancy Services, Providence Health and Services, Gas Brasiliano Distribuidora S.A., Shell plc, Persistent Systems, Phase 2 Dining and Entertainment, Symbio, HID, Globant, and Insight Enterprises. == Partnerships == Azure Maps and TomTom have been partners since 2016, and TomTom provides location data to Azure Maps and can process data from Azure Maps for mapping purposes. In 2021, Azure Maps partnered with AccuWeather to make climatic data available via its APIs, making weather data along all parts of calculated routes available for mobility and logistics purposes. Microsoft has partnered with Esri, the developer of ArcGIS, and there is cross-compatibility between Azure and ArcGIS so that data from Azure Maps can be integrated into ArcGIS and vice versa. Azure Maps partnered with Moovit in 2019, a startup providing software that interfaces with public transport data. Moovit's database on global public transit networks, including information on which stations and facilities are wheelchair accessible, was linked to Azure Maps. This service was noted for its use increasing accessibility to public transport for the visually impaired by means of voice activated route planning assistance. NORAD has used some Azure Maps functions for their NORAD Tracks Santa website during Christmas holidays. == Components == === REST APIs === Various APIs cover the major functionalities across Azure Maps: Data registry API Geolocation API Render API Route API Search API Spatial API Time zone API Traffic API Weather API === SDKs === Azure Maps SDKs uses MapLibre-style specifications and open source MapLibre GL-based libraries as a rendering engine. The Web SDK is used for developing web apps with maps and location-based data and functionality. It includes a map control module as well as modules with drawing tools. It also supports Azure Maps Creator and various spatial data formats. The platform also includes a set of REST SDKs for developers integrating Azure Maps REST APIs into Python, C#, Java or JavaScript applications. Azure Maps also includes Android and iOS SDKs used for developing applications for Android and Apple devices. === Azure Maps Creator === Azure Maps Creator is a tool for generating custom maps for locations like large office complexes, construction sites, or university campuses. These maps can then be integrated into applications and used with other Azure Maps functions for purposes such as wayfinding and maintenance and security in building automation contexts. === Azure Maps Visual for Power BI === Azure Maps is integrated with Microsoft Power BI, a graphical tool for producing data visualizations. Since July 2020, Power BI can be used in conjunction with Azure Maps for developing map-based data visualizations. This functionality entered general availability in May 2023.
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Universal IR Evaluation

In computer science, Universal IR Evaluation (information retrieval evaluation) aims to develop measures of database retrieval performance that shall be comparable across all information retrieval tasks. == Measures of "relevance" == IR (information retrieval) evaluation begins whenever a user submits a query (search term) to a database. If the user is able to determine the relevance of each document in the database (relevant or not relevant), then for each query, the complete set of documents is naturally divided into four distinct (mutually exclusive) subsets: relevant documents that are retrieved, not relevant documents that are retrieved, relevant documents that are not retrieved, and not relevant documents that are not retrieved. These four subsets (of documents) are denoted by the letters a, b, c, d respectively and are called Swets variables, named after their inventor. In addition to the Swets definitions, four relevance metrics have also been defined: Recall refers to the fraction of relevant documents that are retrieved (a/(a+b)), and Precision refers to the fraction of retrieved documents that are relevant (a/(a+c)). These are the most commonly used and well-known relevance metrics found in the IR evaluation literature. Two less commonly used metrics include the Fallout, i.e., the fraction of not relevant documents that are retrieved (b/(b+d)), and the Miss, which refers to the fraction of relevant documents that are not retrieved (c/(c+d)) during any given search. == Universal IR evaluation techniques == Universal IR evaluation addresses the mathematical possibilities and relationships among the four relevance metrics Precision, Recall, Fallout and Miss, denoted by P, R, F and M, respectively. One aspect of the problem involves finding a mathematical derivation of a complete set of universal IR evaluation points. The complete set of 16 points, each one a quadruple of the form (P, R, F, M), describes all the possible universal IR outcomes. For example, many of us have had the experience of querying a database and not retrieving any documents at all. In this case, the Precision would take on the undetermined form 0/0, the Recall and Fallout would both be zero, and the Miss would be any value greater than zero and less than one (assuming a mix of relevant and not relevant documents were in the database, none of which were retrieved). This universal IR evaluation point would thus be denoted by (0/0, 0, 0, M), which represents only one of the 16 possible universal IR outcomes. The mathematics of universal IR evaluation is a fairly new subject since the relevance metrics P, R, F, M were not analyzed collectively until recently (within the past decade). A lot of the theoretical groundwork has already been formulated, but new insights in this area await discovery.
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Magisto

Magisto provided an online video editing tool (both as a web application and a mobile app) for automated video editing and production. In 2019, the company was acquired by Vimeo for an estimated US$200 million. The Magisto app contained a library of music. The music, largely by independent artists, was sorted by mood and is licensed for in-app use. Magisto had a freemium business model where users can create basic video clips for free. In addition, advanced business, professional and personal service tiers are available via various subscription plans, unlocking more features; such as longer videos, HD, premium themes, customization, and control features. == History == Magisto was founded in 2009 as SightEra (LTD) by Oren Boiman (CEO) and Alex Rav-Acha (CTO). Boiman, frustrated with the amount of time it took editing together videos of his daughter, wanted an easier to use application to capture and share videos. Boiman, a computer scientist that graduated from Tel Aviv University, followed with graduate work in computer vision at the Weizmann Institute of Science. Boiman developed several patent-pending image analysis technologies that analyze unedited videos to identify the most interesting parts. The system recognized faces, animals, landscapes, action sequences, movements and other important content within the video, as well as analyzing speech and audio. These scenes are then edited together, along with music and effects. Magisto was launched publicly on September 20, 2011, as a video editing software web application through which users could upload unedited video footage, choose a title and soundtrack and have their video edited for them automatically. On the following day, Magisto was added to YouTube Create's collection of video production applications. The Magisto iPhone app was launched publicly at the 2012 International Consumer Electronics Show (CES) in Las Vegas. At CES, the company was also awarded first place in the 2012 CES Mobile App Showdown. In August 2012, Magisto launched the Android app on Google Play. In September 2012, Magisto launched a Google Chrome App and announced Google Drive integration. In March 2013, Magisto claimed it had 5 million users. Google listed Magisto as an "Editors’ Choice" on its list of "Best Apps of 2013". In September 2013, the company claimed that 10 million users had downloaded the App. In February 2014, Magisto claimed that they had 20 million users, with 2 million new users per month. The company also confirmed investment from Mail.Ru. In September 2014, Magisto rolled out a feature called 'Instagram Ready' which allowed users to upload 15 second clips that are automatically formatted for Instagram. In the same month, Magisto launched a feature for iOS and Android users, called 'Surprise Me', which created video from still photography on users’ smartphones. In October 2014, Magisto was placed 9th on the 2014 Deloitte Israel Technology Fast 50 list and named as a finalist in the Red Herring's Top 100 Europe award. In July 2015, Magisto released an editing theme dedicated to Jerry Garcia. In April 2019, the company was acquired by Vimeo, the IAC-owned platform for hosting, sharing and monetizing streamed video, for an estimated $200 million. === Financing === In 2011, the company received more than $5.5 million in a Series B venture round funding from Magma Venture Partners and Horizons Ventures. In September 2011, at the same time as the public launch of their web application, Magisto announced a $5.5 million Series B funding round led by Li Ka-shing’s Horizons Ventures. Li Ka-Shing is known for making early-stage investments in companies like Facebook, Spotify, SecondMarket and Siri. In October 2013, the company received $13 million in funding from Qualcomm and Sandisk. In 2014, the company received $2 million in Venture Funding from Magma Venture Partners, Qualcomm Ventures, Horizons Ventures and the Mail.Ru Group. == Awards == Magisto won first place at Technonomy3, an annual Internet Technology start-up competition in Israel. Judges of the competition included Jeff Pulver, TechCrunch editor Mike Butcher, investor Yaron Samid, Bessemer Venture Partners Israel partner Adam Fisher and Brad McCarty of The Next Web. Magisto won first place at CES 2012 Mobile app competition, during the launch of Magisto iOS mobile app. Magisto was awarded twice the Google Play Editor's Choice and was part of iPhone App Store Best App awards for 2013 and 2014, and Wired Essential iPad Apps. Magisto was declared by Deloitte as the 7th fastest growing company in Europe, the Middle East, and Africa in 2016.
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Charge-coupled device

A charge-coupled device (CCD) is an integrated circuit containing an array of linked, or coupled, capacitors. Under the control of an external circuit, each capacitor can transfer its electric charge to a neighboring capacitor. CCD sensors are a major technology used in digital imaging. In a CCD image sensor, pixels are represented by p-doped metal–oxide–semiconductor (MOS) capacitors. These MOS capacitors, the basic building blocks of a CCD, are biased above the threshold for inversion when image acquisition begins, allowing the conversion of incoming photons into electron charges at the semiconductor-oxide interface; the CCD is then used to read out these charges. Although CCDs are not the only technology to allow for light detection, CCD image sensors are widely used in professional, medical, and scientific applications where high-quality image data are required. In applications with less exacting quality demands, such as consumer and professional digital cameras, active pixel sensors, also known as CMOS sensors (complementary MOS sensors), are generally used. However, the large quality advantage CCDs enjoyed early on has narrowed over time and since the late 2010s CMOS sensors are the dominant technology, having largely if not completely replaced CCD image sensors. == History == The basis for the CCD is the metal–oxide–semiconductor (MOS) structure, with MOS capacitors being the basic building blocks of a CCD, and a depleted MOS structure used as the photodetector in early CCD devices. In the late 1960s, Willard Boyle and George E. Smith at Bell Labs were researching MOS technology while working on semiconductor bubble memory. They realized that an electric charge was the analog of the magnetic bubble and that it could be stored on a tiny MOS capacitor. As it was fairly straightforward to fabricate a series of MOS capacitors in a row, they connected a suitable voltage to them so that the charge could be stepped along from one to the next. This led to the invention of the charge-coupled device by Boyle and Smith in 1969. They conceived of the design of what they termed, in their notebook, "Charge 'Bubble' Devices". The initial paper describing the concept in April 1970 listed possible uses as memory, a delay line, and an imaging device. The device could also be used as a shift register. The essence of the design was the ability to transfer charge along the surface of a semiconductor from one storage capacitor to the next. The first experimental device demonstrating the principle was a row of closely spaced metal squares on an oxidized silicon surface electrically accessed by wire bonds. It was demonstrated by Gil Amelio, Michael Francis Tompsett and George Smith in April 1970. This was the first experimental application of the CCD in image sensor technology, and used a depleted MOS structure as the photodetector. The first patent (U.S. patent 4,085,456) on the application of CCDs to imaging was assigned to Tompsett, who filed the application in 1971. The first working CCD made with integrated circuit technology was a simple 8-bit shift register, reported by Tompsett, Amelio and Smith in August 1970. This device had input and output circuits and was used to demonstrate its use as a shift register and as a crude eight pixel linear imaging device. Development of the device progressed at a rapid rate. By 1971, Bell researchers led by Michael Tompsett were able to capture images with simple linear devices. Several companies, including Fairchild Semiconductor, RCA and Texas Instruments, picked up on the invention and began development programs. Fairchild's effort, led by ex-Bell researcher Gil Amelio, was the first with commercial devices, and by 1974 had a linear 500-element device and a 2D 100 × 100 pixel device. Peter L. P. Dillon, a scientist at Kodak Research Labs, invented the first color CCD image sensor by overlaying a color filter array on this Fairchild 100 x 100 pixel Interline CCD starting in 1974. Steven Sasson, an electrical engineer working for the Kodak Apparatus Division, invented a digital still camera using this same Fairchild 100 × 100 CCD in 1975. The interline transfer (ILT) CCD device was proposed by L. Walsh and R. Dyck at Fairchild in 1973 to reduce smear and eliminate a mechanical shutter. To further reduce smear from bright light sources, the frame-interline-transfer (FIT) CCD architecture was developed by K. Horii, T. Kuroda and T. Kunii at Matsushita (now Panasonic) in 1981. The first KH-11 KENNEN reconnaissance satellite equipped with charge-coupled device array (800 × 800 pixels) technology for imaging was launched in December 1976. Under the leadership of Kazuo Iwama, Sony started a large development effort on CCDs involving a significant investment. Eventually, Sony managed to mass-produce CCDs for their camcorders. Before this happened, Iwama died in August 1982. Subsequently, a CCD chip was placed on his tombstone to acknowledge his contribution. The first mass-produced consumer CCD video camera, the CCD-G5, was released by Sony in 1983, based on a prototype developed by Yoshiaki Hagiwara in 1981. Early CCD sensors suffered from shutter lag. This was largely resolved with the invention of the pinned photodiode (PPD). It was invented by Nobukazu Teranishi, Hiromitsu Shiraki and Yasuo Ishihara at NEC in 1980. They recognized that lag can be eliminated if the signal carriers could be transferred from the photodiode to the CCD. This led to their invention of the pinned photodiode, a photodetector structure with low lag, low noise, high quantum efficiency and low dark current. It was first publicly reported by Teranishi and Ishihara with A. Kohono, E. Oda and K. Arai in 1982, with the addition of an anti-blooming structure. The new photodetector structure invented at NEC was given the name "pinned photodiode" (PPD) by B.C. Burkey at Kodak in 1984. In 1987, the PPD began to be incorporated into most CCD devices, becoming a fixture in consumer electronic video cameras and then digital still cameras. Since then, the PPD has been used in nearly all CCD sensors and then CMOS sensors. In January 2006, Boyle and Smith were awarded the National Academy of Engineering Charles Stark Draper Prize, and in 2009 they were awarded the Nobel Prize for Physics for their invention of the CCD concept. Michael Tompsett was awarded the 2010 National Medal of Technology and Innovation, for pioneering work and electronic technologies including the design and development of the first CCD imagers. He was also awarded the 2012 IEEE Edison Medal for "pioneering contributions to imaging devices including CCD Imagers, cameras and thermal imagers". == Basics of operation == In a CCD for capturing images, there is a photoactive region (an epitaxial layer of silicon), and a transmission region made out of a shift register (the CCD, properly speaking). An image is projected through a lens onto the capacitor array (the photoactive region), causing each capacitor to accumulate an electric charge proportional to the light intensity at that location. A one-dimensional array, used in line-scan cameras, captures a single slice of the image, whereas a two-dimensional array, used in video and still cameras, captures a two-dimensional picture corresponding to the scene projected onto the focal plane of the sensor. Once the array has been exposed to the image, a control circuit causes each capacitor to transfer its contents to its neighbor (operating as a shift register). The last capacitor in the array dumps its charge into a charge amplifier, which converts the charge into a voltage. By repeating this process, the controlling circuit converts the entire contents of the array in the semiconductor to a sequence of voltages. In a digital device, these voltages are then sampled, digitized, and usually stored in memory; in an analog device (such as an analog video camera), they are processed into a continuous analog signal (e.g. by feeding the output of the charge amplifier into a low-pass filter), which is then processed and fed out to other circuits for transmission, recording, or other processing. == Detailed physics of operation == === Charge generation === Before the MOS capacitors are exposed to light, they are biased into the depletion region; in n-channel CCDs, the silicon under the bias gate is slightly p-doped or intrinsic. The gate is then biased at a positive potential, above the threshold for strong inversion, which will eventually result in the creation of an n channel below the gate as in a MOSFET. However, it takes time to reach this thermal equilibrium: up to hours in high-end scientific cameras cooled at low temperature. Initially after biasing, the holes are pushed far into the substrate, and no mobile electrons are at or near the surface; the CCD thus operates in a non-equilibrium state called deep depletion. Then, when electron–hole pairs are generated in the depletion region, they are separated by the electric field, the elec
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Site-specific browser

A site-specific browser (SSB) is a software application dedicated to accessing pages from a single source (site) on a computer network such as the Internet or a private intranet. SSBs typically simplify the more complex functions of a web browser by excluding the menus, toolbars and browser graphical user interface associated with functions that are external to the workings of a single site. Modern site-specific browsers range from simple browser windows without navigation controls to sophisticated desktop applications built with frameworks like Electron that bundle entire browser engines. This evolution has enabled many popular desktop applications to be built using web technologies, effectively making them advanced site-specific browsers. == History == === Early development === One of the earliest examples of an SSB was MacDICT, a Mac OS 9 application that accessed various websites to define, translate, or find synonyms for words typed into a text box. However, the first general-purpose SSB is considered to be Bubbles, which launched in late 2005 on the Windows platform. Bubbles introduced the term "Site Specific Extensions" for SSB userscripts and created the first SSB JavaScript API. In 2007, Mozilla announced Prism (originally called WebRunner), a project to integrate web applications with the desktop. That same year, Todd Ditchendorf, a former Apple Dashboard engineer, released Fluid for macOS. On 2 September 2008, Google Chrome was released with a built-in "Create application shortcut" feature, bringing SSB functionality to mainstream users. This feature allowed any website to be launched in a separate window without the browser interface. === Modern era === The landscape of site-specific browsers changed dramatically with the introduction of Electron in 2013 (originally called Atom Shell). Electron combined Chromium and Node.js into a single runtime, enabling developers to build desktop applications using web technologies. This framework has since powered applications used by hundreds of millions of users, including Visual Studio Code, Slack, Discord, and Microsoft Teams. In 2015, the concept of Progressive Web Apps (PWAs) was introduced by Google engineers Alex Russell and Frances Berriman, representing a parallel evolution in web-to-desktop technology. While PWAs share similar goals with SSBs, they follow web standards and can be installed directly from browsers. More recently, alternative frameworks like Tauri have emerged, offering significantly smaller application sizes by using the system's native web renderer instead of bundling Chromium. == Technical implementation == Site-specific browsers can be implemented through various approaches: === Browser-based SSBs === The simplest form of SSB is created through browser features that allow websites to run in separate windows without the standard browser interface. Modern Chromium-based browsers offer "Install as app" or "Create shortcut" functionality that creates a dedicated window for a specific website. These SSBs share the browser's underlying engine and resources but operate in isolated windows. === Framework-based SSBs === More sophisticated SSBs are built using application frameworks: Electron: Bundles a complete Chromium browser with Node.js, resulting in applications of 85MB or larger. Each Electron application runs its own browser instance, providing full access to system APIs but consuming significant resources. Tauri: Uses the operating system's native web rendering engine (WebView2 on Windows, WebKit on macOS, and WebKitGTK on Linux), resulting in applications typically 2.5-10MB in size. Other frameworks: Include Neutralino.js (ultra-lightweight using system browser), Wails (Go-based), and the Chromium Embedded Framework (CEF). == Comparison with Progressive Web Apps == While site-specific browsers and Progressive Web Apps (PWAs) share the goal of bringing web content to the desktop, they differ in several key aspects: == Applications == Site-specific browsers have become the foundation for many popular desktop applications: Communication and collaboration: Many modern communication tools are built as SSBs, including Slack, Discord, Microsoft Teams, and WhatsApp Desktop. These applications benefit from web-based development while providing desktop integration. Development tools: Visual Studio Code, used by 73.6% of developers according to Stack Overflow's 2024 survey, is built with Electron, as are Atom and GitHub Desktop. Productivity software: Applications like Notion, Obsidian, and various project management tools use SSB technology to provide consistent experiences across platforms. Security and Privacy: Web browsers can be modified to only have access to a single site, in order to protect the security and privacy of the user via compartmentalization == Security and performance == === Memory usage === Framework-based SSBs, particularly those using Electron, are known for high memory consumption. Studies show Electron applications typically use 120-300MB at baseline, with complex applications consuming significantly more. This is approximately 5-10 times more memory than equivalent native applications. === Security considerations === SSBs can provide security benefits through process isolation, where each application runs in its own sandboxed environment. However, bundling an entire browser engine also means each application must be updated independently to patch security vulnerabilities. Research presented at the Network and Distributed System Security (NDSS) Symposium has identified various security challenges specific to Electron applications. === Bundle sizes === The choice of framework significantly impacts application size: Electron applications: 85MB+ (includes full Chromium) Tauri applications: 2.5-10MB (uses system WebView) Browser-based SSBs: No additional download (uses existing browser) == Software == === Browser support === Most modern browsers provide some form of SSB functionality: Chromium-based browsers (Google Chrome, Microsoft Edge, Brave, Opera, Vivaldi): "Install as app" or "Create shortcut" feature Safari: "Add to Dock" feature in macOS Sonoma (2023) Firefox: Removed SSB support in December 2020 (version 85) GNOME Web: "Install Site as Web Application" feature === Standalone tools === ==== Active ==== WebCatalog (Windows, macOS, Linux) – Manages multiple SSBs with isolated storage Fluid (macOS) – Pioneering SSB creator for Mac Unite (macOS) – Creates SSBs with customization options Coherence X (macOS) – Advanced SSB creation tool Pake (cross-platform) – Open-source SSB creator Wavebox (cross-platform) – Workspace browser with SSB features ==== Discontinued ==== Mozilla Prism – Cross-platform SSB creator (discontinued 2011) Nativefier – Command-line SSB creator (discontinued 2023) Epichrome – macOS SSB creator (discontinued 2021) === Development frameworks === Electron – Most popular framework, bundles Chromium and Node.js Tauri – Rust-based framework using system WebView Chromium Embedded Framework (CEF) – C++ library for embedding Chromium Neutralino.js – Lightweight framework using system browser Wails – Go-based framework for web frontends
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Concurrent MetateM

Concurrent MetateM is a multi-agent language in which each agent is programmed using a set of (augmented) temporal logic specifications of the behaviour it should exhibit. These specifications are executed directly to generate the behaviour of the agent. As a result, there is no risk of invalidating the logic as with systems where logical specification must first be translated to a lower-level implementation. The root of the MetateM concept is Gabbay's separation theorem; any arbitrary temporal logic formula can be rewritten in a logically equivalent past → future form. Execution proceeds by a process of continually matching rules against a history, and firing those rules when antecedents are satisfied. Any instantiated future-time consequents become commitments which must subsequently be satisfied, iteratively generating a model for the formula made up of the program rules. == Temporal Connectives == The Temporal Connectives of Concurrent MetateM can divided into two categories, as follows: Strict past time connectives: '●' (weak last), '◎' (strong last), '◆' (was), '■' (heretofore), 'S' (since), and 'Z' (zince, or weak since). Present and future time connectives: '◯' (next), '◇' (sometime), '□' (always), 'U' (until), and 'W' (unless). The connectives {◎,●,◆,■,◯,◇,□} are unary; the remainder are binary. === Strict past time connectives === ==== Weak last ==== ●ρ is satisfied now if ρ was true in the previous time. If ●ρ is interpreted at the beginning of time, it is satisfied despite there being no actual previous time. Hence "weak" last. ==== Strong last ==== ◎ρ is satisfied now if ρ was true in the previous time. If ◎ρ is interpreted at the beginning of time, it is not satisfied because there is no actual previous time. Hence "strong" last. ==== Was ==== ◆ρ is satisfied now if ρ was true in any previous moment in time. ==== Heretofore ==== ■ρ is satisfied now if ρ was true in every previous moment in time. ==== Since ==== ρSψ is satisfied now if ψ is true at any previous moment and ρ is true at every moment after that moment. ==== Zince, or weak since ==== ρZψ is satisfied now if (ψ is true at any previous moment and ρ is true at every moment after that moment) OR ψ has not happened in the past. === Present and future time connectives === ==== Next ==== ◯ρ is satisfied now if ρ is true in the next moment in time. ==== Sometime ==== ◇ρ is satisfied now if ρ is true now or in any future moment in time. ==== Always ==== □ρ is satisfied now if ρ is true now and in every future moment in time. ==== Until ==== ρUψ is satisfied now if ψ is true at any future moment and ρ is true at every moment prior. ==== Unless ==== ρWψ is satisfied now if (ψ is true at any future moment and ρ is true at every moment prior) OR ψ does not happen in the future.
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GCube system

gCube is an open source software system specifically designed and developed to enact the building and operation of a Data Infrastructure providing their users with a rich array of services suitable for supporting the co-creation of Virtual Research Environments and promoting the implementation of open science workflows and practices. It is at the heart of the D4Science Data Infrastructure. == Overview == It is primarily organised in a number of web service called to offer functionality supporting the phases of knowledge production and sharing. In addition, it consists of a set of software libraries supporting service development, service-to-service integration, and service capabilities extension, and a set of portlets dedicated to realise user interface constituents facilitating the exploitation of one or more services. It is designed and conceived to enact system of systems. In fact, its gCube services rely on standards and mediators to interact with other services as well as are made available by standard and APIs to make it possible for clients to use them. For instance, the DataMiner service implements the Web Processing Service protocol to facilitate clients to execute processes. The set of components dealing with Identity and Access Management rely on Keycloak and federates other IDMs thus making the overall Authentication and the Authorization management compliant with open standards such as OAuth2, User-Managed Access (UMA), and OpenID Connect (OIDC)protocols. The Catalogue relies on DCAT, OAI-PMH, and Catalogue Service for the Web to collect contents from other catalogues and data sources and offers its content by DCAT, OAI-PMH, and a proprietary REST API (gCat REST API). Its Continuous Integration/Continuous Delivery pipeline implemented by Jenkins represents an innovative approach to software delivering conceived to be scalable and easy to maintain and upgrade at a minimal cost. == History == gCube has been developed in the context of the D4Science initiative with the support of several EU projects.
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Radek Maneuver

The Radek Maneuver is a scale-up-then-scale-down tactic used in the administration of web services, specifically those deployed under a cloud computing paradigm (by a provider e.g. Amazon Elastic Compute Cloud or Microsoft Azure). == History == Developed by Olivier "Radek" Dabrowski in the mid-2010s, the Radek Maneuver was originally conceived of in using and maintaining applications running on a PaaS system. == Execution == The Radek Maneuver consists of a series of steps, usually executed via the PaaS or web portal interface. The tactic should be used when a service is misbehaving or otherwise experiencing errors, and the suspected cause is the underlying cloud layer, rather than the application layer. This includes networking issues and other "bad box" problems. The steps are as follows: Identify the application or service which is misbehaving. Increase the compute resource (number of CPU cores, amount of ram) for the instance on which the application is running. This is also known as scaling up. Wait for the application to re-deploy and stabilize. Scale back down to the original instance size. == Principle of action == This scale-up-scale-down method is understood to shift the application to a different physical machine underlying the PaaS service or application virtual machine. While this layer of the cloud computing stack is generally out of the access of an application developer (instead in the hands of the cloud provider), the maneuver allows troubleshooting and dodging errors in that layer.
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Cloud Security Alliance

Cloud Security Alliance (CSA) is a not-for-profit organization with the mission to "promote the use of best practices for providing security assurance within cloud computing, artificial intelligence and to provide education on the uses of cloud computing to help secure all other forms of computing." The CSA has over 80,000 individual members worldwide. The CSA gained significant reputability in 2011 when the American Presidential Administration selected the CSA Summit as the venue for announcing the federal government’s cloud computing strategy. == History == The CSA was formed in December 2008 as a coalition by individuals who saw the need to provide objective enterprise user guidance on the adoption and use of cloud computing. Its initial work product, Security Guidance for Critical Areas of Focus in Cloud Computing, was put together in a Wiki-style by dozens of volunteers. In 2014, the Chairman of the Board of the CSA was Dave Cullinane, VP of Global Security and Privacy for Catalina Marketing, St. Petersburg, Florida, and former CISO for eBay. Cullinane has said, "If you have an application exposed to the Internet that will allow people to make money, it will be probed." == Profile == In 2009, the Cloud Security Alliance incorporated in Nevada as a Corporation and achieved US Federal 501(c)6 non-profit status. It is registered as a Foreign Non-Profit Corporation in Washington. == Policy maker support == The CSA works to support a number of global policy makers in their focus on cloud security initiatives including the National Institute of Standards and Technology (NIST), European Commission, Singapore Government, and other data protection authorities. In March 2012, the CSA was selected to partner with three of Europe’s largest research centers (CERN, EMBL and ESA) to launch Helix Nebula – The Science Cloud. == Size == The Cloud Security Alliance employs roughly sixty full-time and contract staff worldwide. It has several thousand active volunteers participating in research, working groups and chapters at any time. == Membership == According to CSA, they are a member-driven organization, chartered with promoting the use of best practices for providing security assurance within Cloud Computing, and providing education on the uses of Cloud Computing to help secure all other forms of computing. === Individuals === Individuals who are interested in cloud computing and have experience to assist in making it more secure receive a complimentary individual membership based on a minimum level of participation. === Chapters === The Cloud Security Alliance has a network of chapters worldwide. Chapters are separate legal entities from the Cloud Security Alliance, but operate within guidelines set down by the Cloud Security Alliance In the United States, Chapters may elect to benefit from the non-profit tax shield that the Cloud Security Alliance has. Chapters are encouraged to hold local meetings and participate in areas of research. Chapter activities are coordinated by the Cloud Security Alliance worldwide. === International scope === There are separate legal entities in Europe and Asia Pacific, called Cloud Security Alliance (Europe), a Scottish company in the United Kingdom, and Cloud Security Alliance Asia Pacific Ltd, in Singapore. Each legal entity is responsible for overseeing all Cloud Security Alliance-related activities in their respective regions. These legal entities operate under an agreement with Cloud Security Alliance that give it oversight power and have separate Boards of Directors. Both are companies Limited By Guarantee. The Managing Directors of each are members of the Executive Team of Cloud Security Alliance. == Areas of research == The Cloud Security Alliance has 25+ active working groups. Key areas of research include cloud standards, certification, education and training, guidance and tools, global reach, and driving innovation. Security Guidance for Critical Areas of Focus in Cloud Computing. Foundational best practices for securing cloud computing. Top Threats to Cloud Computing. Helps organizations make educated risk management decisions regarding their cloud adoption strategies. GRC (Governance, Risk and Compliance) Stack. A toolkit for key stakeholders to instrument and assess clouds against industry established best practices, standards and critical compliance requirements. Cloud Controls Matrix (CCM). Security controls framework for cloud provider and cloud consumers. CloudTrust Protocol. The mechanism by which cloud service consumers ask for and receive information about the elements of transparency as applied to cloud service providers. Consensus Assessments Initiative Research. Tools and processes to perform consistent measurements of cloud providers. Software Defined Perimeter. A proposed security framework that can be deployed to protect application infrastructure from network-based attacks. It will incorporate standards from organizations such as OASIS and NIST and security concepts from organizations like the U.S. DoD into an integrated framework. == Working groups and initiatives == Mobile Working Group Big Data Working Group Security as a Service Working Group Trusted Cloud Initiative CloudAudit CloudCERT CloudSIRT Cloud Metrics Security, Trust and Assurance Registry (STAR) Cloud Data Governance Turbot (business) Blockchain/Distributed Ledger
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PowerBuilder

PowerBuilder is an integrated development environment owned by SAP since the acquisition of Sybase in 2010. On July 5, 2016, SAP and Appeon entered into an agreement whereby Appeon, an independent company, would be responsible for developing, selling, and supporting PowerBuilder. Over the years, PowerBuilder has been updated with new standards. In 2010, a major upgrade of PowerBuilder was released to provide support for the Microsoft .NET Framework. In 2014, support was added for OData, dockable windows, and 64-bit native applications. In 2019 support was added for rapidly creating RESTful Web APIs and non-visual .NET assemblies using the C# language and the .NET Core framework. And PowerScript client app development was revamped with new UI technologies and cloud architecture. In 2025 the IDE was revamped with new code editor and ultra-fast compiler. Appeon has been releasing new features every 6-12 month cycles, which per the product roadmap focus on four key focus areas: sustaining core features, modernizing application UI, improving developer productivity, and incorporating more Cloud technology. == Features == PowerBuilder has a native data-handling component called a DataWindow, which can be used to create, edit, and display data from a database. This object gives the programmer a number of tools for specifying and controlling user interface appearance and behavior, and also provides simplified access to database content and JSON or XML from Web services. To some extent, the DataWindow frees the programmer from considering the differences between Database Management Systems from different vendors. DataWindow can display data using multiple presentation styles and can connect to various data sources. == Usage == PowerBuilder is used primarily for building business-oriented CRUD applications. Although new software products are rarely built with PowerBuilder, many client-server ERP products and line-of-business applications built in the late 1980s to early 2000s with PowerBuilder still provide core database functions for large enterprises in government, higher education, manufacturing, insurance, banking, energy, and telecommunications. == History == === Early history === PowerBuilder originated from Computer Solutions Inc. (CSI), a software consulting firm founded in 1974 by Mitchell Kertzman in Massachusetts. CSI developed GrowthPower, an MRP II software package with integrated financial modules released in 1981, which ran exclusively on the HP 3000 platform and achieved over 1,000 customer installations at its peak. In the late 1980s, as demand increased for graphical user interfaces amid the rise of Microsoft Windows, Kertzman partnered with Dave Litwack, former executive vice president of product development at Cullinet Software (acquired by Computer Associates in 1989). Litwack joined the company in 1988 as head of research and development to develop a client/server GUI tool, leading to its rebranding as Powersoft Corporation in 1990. PowerBuilder 1.0 was released in July 1991 as a rapid application development tool featuring the DataWindow and PowerScript language. Powersoft went public on February 3, 1993, with shares closing at $38 from an initial $20 price. Sybase announced its acquisition of Powersoft on November 15, 1994, in a stock swap valued at approximately $940 million; the merger closed on February 14, 1995, at a revised value of about $904 million due to Sybase's stock fluctuations. === Recent history === In December 2013 SAP announced the new version going directly to number 15 and released a beta version. Key features included support for the .NET Framework v4.5, SQL Server 2012, Oracle 12, Windows 8, OData and Dockable Windows. SAP later released this as version 12.6. On May 31, 2019, PowerBuilder 2019 was released by Appeon. This release supports C# development. It provides a new C# IDE, .NET data access objects, C# migration solution, Web API client, and UI themes. On April 3, 2020, PowerBuilder 2019 R2 was launched by Appeon. This release includes a first-ever PowerScript-to-C# code converter, which can automatically migrate 80-95% of PowerBuilder business logic and DataWindows to C#. Interoperability between PowerScript and .NET programming languages is also now supported. Many existing features have also been enhanced. On January 22, 2021, PowerBuilder 2019 R3 was launched by Appeon. This release provides a groundbreaking new app deployment technology called PowerClient, which securely automates the installation and update of client apps over HTTPS. C# Web API development has been greatly enhanced with asynchronous programming and support for Amazon Aurora and Azure cloud databases. Aside from many other new features, PowerBuilder 2019 R3 is a long-term support (LTS) version that replaces previous LTS versions On August 6, 2021, PowerBuilder 2021 was launched by Appeon. The Cloud deployment capability of the PowerBuilder 2021 IDE, in conjunction with the matching PowerServer 2021 runtime, was revamped, bringing PowerBuilder up-to-date with the latest .NET technologies. The presentation layer now executes PowerScript natively on Windows devices. The middle-tier has been rebuilt around REST API standard with a pure .NET Core implementation. A new CI/CD utility that integrates with Git/SVN and Jenkins, witch compiles all PowerBuilder projects using the command-line interface, was added alongside other features. On September 4, 2022, PowerBuilder 2022 was launched by Appeon. This release brings enhancements to the productivity of developing both client/server & installable cloud apps and more security measures to safeguard your apps. It includes many new features, including Windows 11 support, introducing time-saving functionalities to the IDE, such as Tabbed Code Editor, Jump to Objects, and Quick Code Search, and supports the latest HTTP/2 and TLS 1.3 protocols and two-way TLS authentication. On August 4, 2023, PowerBuilder 2022 R2 was launched by Appeon. This release introduces a range of new features aimed at helping developers build powerful, feature-rich, and secure client/server and installable cloud apps more efficiently, including tabbed windows, fillable PDFs, and SMTP client. On January 8, 2024, PowerBuilder 2022 R3 was launched by Appeon. This release is a long-term support version. Features previously released in earlier releases have been enhanced and/or corrected. On May 7, 2025, PowerBuilder 2025 was launched by Appeon. This release delivers a revamped IDE that boosts developer productivity throughout the SLDC—from writing and extending code to debugging, automating builds, and deploying applications. It features a new-generation code editor, ultra-fast compiler, automatic REST API creation, faster GIT operations, and codeless UI modernization features. == Features == PowerBuilder is an object-oriented programming language. Nearly all of the visual and non-visual objects support inheritance, polymorphism, and encapsulation. The programmer may utilize a common code framework such as PowerBuilder Foundation Classes, also known as PFC, to inherit objects from and leverage pre-existing code. The DataWindow is the key component (and selling point) of PowerBuilder. The DataWindow offers a visual SQL painter which supports outer joins, unions and subquery operations. It can convert SQL to visual representation and back, so the developer can use native SQL if desired. DataWindow updates are automatic — it produces the proper SQL at runtime based on the DBMS to which the user is currently connected. This feature makes it easier for developers who are not experienced with SQL. The DataWindow also has the built-in ability to both retrieve data and update data via stored procedures or REST Web APIs as well as import/export JSON data. The RESTClient object introduced in PowerBuilder 2017 facilitates bridging the DataWindow with REST Web APIs and requiring minimal coding. === RDBMS interfaces === PowerBuilder offers native interfaces to all major databases, as well as ODBC and OLE-DB, in the Enterprise version. There are many connectivity options that allow performance monitoring and tuning, such as: Integrated security Tracing of all SQL Isolation level Password expiration dialog Blocking factor Number of SQL statements to cache Use connection pool Thread safety Trace ODBC API calls Due to the information about the database schema (such as primary key information) that are stored in PowerBuilder's data dictionary, the code required to implement data display and browsing is greatly simplified, because the dictionary information allows generation of the appropriate SQL behind the scenes. PowerBuilder supports the following ways of interacting with a database: DataWindow this is the simplest approach, relying on automatically generated SQL. Embedded SQL Embedded SQL supports SELECT, INSERT, UPDATE, DELETE and cursors. This option is used when the developer desires more control than is available with the
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Flutter (software)

Flutter is an open-source UI software development kit created by Google. It can be used to develop cross platform applications from a single codebase for the web, Fuchsia, Android, iOS, Linux, macOS, and Windows. First described in 2015, Flutter was released in May 2017. Flutter is used internally by Google in apps such as Google Pay and Google Earth as well as by other software developers including ByteDance and Alibaba. Flutter ships applications with its own rendering engine which directly outputs pixel data to the screen. This is in contrast to many other UI frameworks that rely on the target platform to provide a rendering engine, such as native Android apps which rely on the device-level Android SDK or iOS SDK which use the target platform's built-in UI stack. Flutter's control of its rendering pipeline simplifies multi-platform support as identical UI code can be used for all target platforms.One of Flutter’s key features is hot reload, which allows developers to see code changes instantly without restarting the application. == Architecture == The basic component in a Flutter program is a "widget", which can in turn consist of other widgets. A widget describes the logic, interaction, and design of a UI element with an implementation similar to React. Unlike other cross-platform toolkits such as React Native and Xamarin which draw widgets using native platform components, Flutter renders widgets itself on a per-pixel basis. Flutter has two types of widgets: stateless and stateful. Stateless widgets only update if their inputs change, meaning they otherwise won't need to be rebuilt when other elements of the screen change, while stateful widgets can call the setState() method to update an internal state and redraw. Although widgets are the primary method of constructing Flutter applications, they can also be bypassed in favor of directly drawing on a canvas. This feature has been occasionally used to implement game engines in Flutter. The Flutter framework contains two sets of widgets that conform to specific design languages: Material Design widgets implement Google's design language of the same name, and Cupertino widgets implement Apple's iOS Human interface guidelines. Flutter allows the developer to use either set of widgets on either platform. Developers can use Cupertino widgets on Android. Flutter apps are written in the Dart language. Release versions of Flutter apps on all platforms use ahead-of-time (AOT) compilation except for on the Web where code is transpiled to JavaScript or WebAssembly. Flutter inherits Dart's Pub package manager and software repository, which allows users to publish and use custom packages as well as Flutter-specific plugins. The Foundation library, written in Dart, provides basic classes and functions that are used to construct applications using Flutter, such as APIs to communicate with the engine. Flutter's engine, written primarily in C++, provides low-level rendering support using either Google's Skia graphics library or the custom "Impeller" graphics layer, which is enabled by default on iOS and Android API 29 and higher. The engine interfaces with platform-specific SDKs such as those provided by Android and iOS to implement features like accessibility, file and network I/O, native plugin support, etc. == History == The first version of Flutter was known as "Sky" and ran on the Android operating system. It was unveiled at the 2015 Dart developer summit with the stated intent of being able to render consistently at 120 frames per second. On December 4, 2018, Flutter 1.0 was released at the Flutter conference in London. On May 6, 2020, the Dart software development kit (SDK) version 2.8 and Flutter 1.17.0 were released, adding support for the Metal API. On March 3, 2021, Google released Flutter 2 during an online Flutter Engage event. It added a Canvas-based renderer for web in addition to the HTML-based renderer and early-access desktop application support for Windows, macOS, and Linux. It also shipped with Dart 2.0 which included support for null-safety. Null safety was initially optional as it was a breaking change and was made mandatory in Dart 3 released in 2023. On May 12, 2022, Flutter 3 and Dart 2.17 were released with support for all desktop platforms as stable. On October 27, 2024, a number of Flutter community developers announced Flock, a fork of Flutter intended to be easier to contribute to while still keeping in sync with all changes made in the upstream code base. In 2025, Google continued Flutter's evolution with enhanced modular architecture, foldable device support, and ARM IoT optimizations as outlined in the updated roadmap. === Major releases in Flutter === Prior to the Flutter 2.0 release in March of 2021, the Flutter framework was centered on mobile development. The developers of Flutter were primarily focused on the two main platforms, IOS and Android. Specifically, they wanted to deliver strong performance and improve access to native API and platform features and expand the widget system. With the release of Flutter 2.0, the framework moved beyond mobile and introduced support for the web platform. This marked a shift into a broader cross platform development environment. With this release, developers could produce applications for Web, Android and IOS from the same codebase. This release also brought the desktop platform closer to stable. There have been a number of improvements since then that have broadened platform support. They introduced enhancements to performance and workflow, redefined the developer’s toolkit, and added an improved rendering engine. "Flutter 2.10.0 release notes". docs.flutter.dev. Retrieved 2025-11-11.
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Likewise, Inc.

Likewise, Inc., is an American technology startup company which provides a social networking service for finding and saving content recommendations for movies, TV shows, books, and podcasts. A team of ex-Microsoft employees founded Likewise in October 2017 with financial investment from Microsoft co-founder Bill Gates. The company is led by CEO Ian Morris and as of 2020 had a team of about 35 employees. Its headquarters operates in Bellevue, Washington. As of July 2020, 1 million users had joined the platform. == History == === Ideation (October 2017) === In 2017, former Microsoft Communications Chief Larry Cohen came up with the idea for Likewise in Bill Gates’ private office, Gates Ventures. Cohen currently serves as Gates Ventures’ CEO and managing partner. Cohen collaborated with colleagues Michael Dix and Ian Morris to co-found what would become Likewise, with Morris as its CEO. Gates funded the company's early development. The company developed its platform in stealth mode before launching publicly in October 2018. === Release (October 2018) === Likewise officially released its platform in the US and Canada on October 3, 2018. === Growth (2020 COVID-19 pandemic) === Likewise experienced accelerated growth alongside the COVID-19 pandemic. From March 2020 to July 2020, the platform's monthly active users tripled in numbers. The company reached one million users in July 2020. == Applications == === Mobile === Likewise is available as a mobile app for the Android and iOS mobile operating systems. Users receive recommendations from the Likewise algorithm, people they follow, and the Likewise editorial team. === Likewise TV === In October 2019, the company launched its Apple TV app called Likewise TV. The television app organizes shows across streaming services under one watchlist. On July 20, 2020, Likewise TV expanded to Android TV and Amazon Fire TV users.
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