The Portable Format for Analytics (PFA) is a JSON-based predictive model interchange format conceived and developed by Jim Pivarski. PFA provides a way for analytic applications to describe and exchange predictive models produced by analytics and machine learning algorithms. It supports common models such as logistic regression and decision trees. Version 0.8 was published in 2015. Subsequent versions have been developed by the Data Mining Group. As a predictive model interchange format developed by the Data Mining Group, PFA is complementary to the DMG's XML-based standard called the Predictive Model Markup Language or PMML. == Release history == == Data Mining Group == The Data Mining Group is a consortium managed by the Center for Computational Science Research, Inc., a nonprofit founded in 2008. == Examples == reverse array: # reverse input array of doubles input: {"type": "array", "items": "double"} output: {"type": "array", "items": "double"} action: - let: { x : input} - let: { z : input} - let: { l : {a.len: [x]}} - let: { i : l} - while : { ">=" : [i,0]} do: - set : {z : {attr: z, path : [i] , to: {attr : x ,path : [ {"-":[{"-" : [l ,i]},1]}] } } } - set : {i : {-:[i,1]}} - z Bubblesort input: {"type": "array", "items": "double"} output: {"type": "array", "items": "double"} action: - let: { A : input} - let: { N : {a.len: [A]}} - let: { n : {-:[N,1]}} - let: { i : 0} - let: { s : 0.0} - while : { ">=" : [n,0]} do : - set : { i : 0 } - while : { "<=" : [i,{-:[n,1]}]} do : - if: {">": [ {attr: A, path : [i]} , {attr: A, path:[{+:[i,1]}]} ]} then : - set : {s : {attr: A, path: [i]}} - set : {A : {attr: A, path: [i], to: {attr: A, path:[{+:[i,1]}]} } } - set : {A : {attr: A, path: [{+:[i,1]}], to: s }} - set : {i : {+:[i,1]}} - set : {n : {-:[n,1]}} - A == Implementations == Hadrian (Java/Scala/JVM) - Hadrian is a complete implementation of PFA in Scala, which can be accessed through any JVM language, principally Java. It focuses on model deployment, so it is flexible (can run in restricted environments) and fast. Titus (Python 2.x) - Titus is a complete, independent implementation of PFA in pure Python. It focuses on model development, so it includes model producers and PFA manipulation tools in addition to runtime execution. Currently, it works for Python 2. Titus 2 (Python 3.x) - Titus 2 is a fork of Titus which supports PFA implementation for Python 3. Aurelius (R) - Aurelius is a toolkit for generating PFA in the R programming language. It focuses on porting models to PFA from their R equivalents. To validate or execute scoring engines, Aurelius sends them to Titus through rPython (so both must be installed). Antinous (Model development in Jython) - Antinous is a model-producer plugin for Hadrian that allows Jython code to be executed anywhere a PFA scoring engine would go. It also has a library of model producing algorithms.
AppBlock
AppBlock is a software tool for managing screen time that limits access to selected mobile applications and websites. Developed by the Czech studio MobileSoft, it is distributed for Android and iOS devices as well as through browser extensions for Google Chrome, Microsoft Edge and Brave, and as desktop solutions. The application is used primarily to restrict time spent on social media and similar distracting services while working and studying. By 2025, the application reported 700,000 monthly active users, with the domestic Czech market accounting for less than one percent of its total user base and revenue. == History == === Origins === AppBlock was created by the Czech software studio MobileSoft, based in Hradec Králové. The studio was founded in 2012 by Miroslav Novosvětský, who remains the sole owner. The idea for the application arose from the use of browser-based website blockers on desktop computers. AppBlock was conceived as a way to reduce the time spent on mobile devices. === Early releases === In its early phase, AppBlock was available only for phones running on Android. Early versions allowed users to limit access to selected applications and websites during specified periods. From the outset, the application was distributed internationally rather than only within the Czech market, and early coverage reported a multi-million number of downloads worldwide. === Expansion of functionality === Over time, AppBlock has expanded beyond basic application blocking to include additional functions related to limiting procrastination and managing attention. The development of AppBlock accelerated during the COVID-19 pandemic. Following a reduction in external client orders, the studio reallocated resources from contract development to the application. Increased digital content consumption during lockdowns contributed to a rise in the application's usage and revenue. As the application developed, it became the company's product with the largest user base. Novosvětský described an increase in downloads over a twelve-month period, which he linked in part to the company's activities abroad, including participation in events focused on mobile marketing in the United States. These activities were an important factor in the further development of AppBlock. === Internationalization and market expansion === Within roughly the first eight years of the company's existence, MobileSoft became active both in the domestic Czech market and in the United States, supported among other things by participation in the CzechAccelerator program, which is intended to help Czech firms enter foreign markets. In mid-August 2021 the developers launched a version for iOS, which soon began to attract paying users. The expansion to iOS was accompanied by plans for cooperation with the Procrastination.com platform, intended to complement the blocking functions with educational content related to digital media use, sleep and work habits. By 2025, AppBlock was localised into 15 languages, with the largest share of users in the United States, the United Kingdom, Germany, and France, with recent growth in Brazil, and usage extending across several continents. AppBlock has reached more than 10 million installations. In the same period its creators announced plans to refine existing functions and to expand support beyond mobile phones to desktop use, including through support for additional web browsers. == Features == === Supported platforms === AppBlock is distributed as a mobile application for Android and iOS users through Google Play and the Apple App Store. Browser extensions for desktop systems are available for Google Chrome, Microsoft Edge and Brave. === Functionality === AppBlock's core function is to restrict access to selected applications and websites. The mobile application shows a list of installed apps and lets the user select which ones to block. It also includes tools to block specific websites and, on iOS, to block certain phrases entered in the Safari browser. AppBlock can mute notifications from selected applications, so alerts from those apps do not appear while blocking is active. In addition to choosing which apps or content to block, the software also offers an allowlist mode, where only selected applications remain accessible and all others are blocked. Blocking rules are organized into configurable schedules, called profiles. Users can create profiles that define time periods when selected apps and websites are unavailable. Newer versions also allow profiles to be activated automatically based on the time of day, days of the week, the device's location, or connection to specific Wi-Fi networks. The iOS version lets users set limits on how often or how long certain apps can be used before they are blocked, and it can track and restrict screen time for individual apps. In addition to these recurring rules, AppBlock includes a Quick Block feature that temporarily blocks selected apps and websites with a single action, without requiring a separate long-term schedule. Strict Mode is an optional setting that limits the ability to change blocking once it is active. For a specified period, it prevents editing AppBlock's rules and can be configured to stop the app from being uninstalled during that time. While Strict Mode is enabled, users cannot modify or disable the restrictions they have set. Deactivation requires specific verification steps, such as connecting the device to a charger or obtaining approval from a designated contact person. The mobile application also includes statistical and reporting features. In addition to blocking, AppBlock lets users view statistics and data about their use of applications and websites, including screen-time summaries and focus sessions that silence notifications and enforce blocking during defined work or study periods. Browser extensions for desktop environments apply AppBlock's website-blocking functions on Windows and macOS systems through supported web browsers. == Business model == AppBlock uses a freemium revenue model. The basic version of the application is available free of charge and allows blocking of up to three applications at the same time. The premium version removes this limit and adds further configuration options. In 2020, the application shifted from a one-time payment structure to a subscription model. By 2021, AppBlock had more than seven thousand paying users and annual revenue of about four million Czech crowns. By 2025, annual revenue reached approximately 4 million US dollars (80 million CZK) before taxes and platform fees, with roughly 20 percent of active users subscribing to the paid version. == Usage == AppBlock limits access to selected applications and websites in order to reduce smartphone overuse and digital distraction. It is used to block social media, games and other services considered addictive, with the aim of reducing frequent checking of mobile devices and creating time intervals in which these services are unavailable. Reported use cases of AppBlock cover work, students, parents, ADHD, mental health, well-being and business. The application is used both by individual users and within workplace initiatives in which employees install it to reduce digital distractions during working hours.
DVD
DVD (digital video disc or digital versatile disc) is a digital optical disc data storage format. It was invented and developed in 1995 and first released on November 1, 1996, in Japan. The medium can store any kind of digital data and has been widely used to store video programs (watched using DVD players), software and other computer files. DVDs offer significantly higher storage capacity than compact discs (CD) while having the same dimensions. A standard single-layer DVD can store up to 4.7 GB of data, a dual-layer DVD up to 8.5 GB. Dual-layer, double-sided DVDs can store up to a maximum of 17.08 GB. Prerecorded DVDs are mass-produced using molding machines that physically stamp data onto the DVD. Such discs are a form of DVD-ROM because data can only be read and not written or erased. Blank recordable DVD discs (DVD-R and DVD+R) can be recorded once using a DVD recorder and then function as a DVD-ROM. Rewritable DVDs (DVD-RW, DVD+RW, and DVD-RAM) can be recorded and erased many times. DVDs are used in DVD-Video consumer digital video format and less commonly in DVD-Audio consumer digital audio format, as well as for authoring DVD discs written in a special AVCHD format to hold high definition material (often in conjunction with AVCHD format camcorders). DVDs containing other types of information may be referred to as DVD data discs. == Etymology == The Oxford English Dictionary comments that, "In 1995, rival manufacturers of the product initially named digital video disc agreed that, in order to emphasize the flexibility of the format for multimedia applications, the preferred abbreviation DVD would be understood to denote digital versatile disc." The OED also states that in 1995, "The companies said the official name of the format will simply be DVD. Toshiba had been using the name 'digital video disc', but that was switched to 'digital versatile disc' after computer companies complained that it left out their applications." "Digital versatile disc" is the explanation provided in a DVD Forum Primer from 2000 and in the DVD Forum's mission statement, which the purpose is to promote broad acceptance of DVD products on technology, across entertainment, and other industries. Because DVDs became highly popular for the distribution of movies in the 2000s, the term DVD became popularly used in English as a noun to describe specifically a full-length movie released on the format; for example the phrase "to watch a DVD" describes watching a movie on DVD. == History == === Development and launch === Released in 1987, CD Video used analog video encoding on optical discs matching the established standard 120 mm (4.7 in) size of audio CDs. Video CD (VCD) became one of the first formats for distributing digitally encoded films in this format, in 1993. In the same year, two new optical disc storage formats were being developed. One was the Multimedia Compact Disc (MMCD), backed by Philips and Sony (developers of the CD and CD-i), and the other was the Super Density (SD) disc, supported by Toshiba, Time Warner, Matsushita Electric, Hitachi, Mitsubishi Electric, Pioneer, Thomson, and JVC. By the time of the press launches for both formats in January 1995, the MMCD nomenclature had been dropped, and Philips and Sony were referring to their format as Digital Video Disc (DVD). On May 3, 1995, an ad hoc industry technical group formed from five computer companies (IBM, Apple, Compaq, Hewlett-Packard, and Microsoft) issued a press release stating that they would only accept a single format. The group voted to boycott both formats unless the two camps agreed on a single, converged standard. They recruited Lou Gerstner, president of IBM, to pressure the executives of the warring factions. In one significant compromise, the MMCD and SD groups agreed to adopt proposal SD 9, which specified that both layers of the dual-layered disc be read from the same side—instead of proposal SD 10, which would have created a two-sided disc that users would have to turn over. Philips/Sony strongly insisted on the source code, EFMPlus, that Kees Schouhamer Immink had designed for the MMCD, because it makes it possible to apply the existing CD servo technology. Its drawback was a loss from 5 to 4.7 Gigabytes of capacity. As a result, the DVD specification provided a storage capacity of 4.7 GB (4.38 GiB) for a single-layered, single-sided disc and 8.5 GB (7.92 GiB) for a dual-layered, single-sided disc. The DVD specification ended up similar to Toshiba and Matsushita's Super Density Disc, except for the dual-layer option. MMCD was single-sided and optionally dual-layer, whereas SD was two half-thickness, single-layer discs which were pressed separately and then glued together to form a double-sided disc. Philips and Sony decided that it was in their best interests to end the format war, and on September 15, 1995 agreed to unify with companies backing the Super Density Disc to release a single format, with technologies from both. After other compromises between MMCD and SD, the group of computer companies won the day, and a single format was agreed upon. The computer companies also collaborated with the Optical Storage Technology Association (OSTA) on the use of their implementation of the ISO-13346 file system (known as Universal Disk Format) for use on the new DVDs. The format's details were finalized on December 8, 1995. In November 1995, Samsung announced it would start mass-producing DVDs by September 1996. The format launched on November 1, 1996, in Japan, mostly with music video releases. The first major releases from Warner Home Video arrived on December 20, 1996, with four titles being available. The format's release in the U.S. was delayed multiple times, from August 1996, to October 1996, November 1996, before finally settling on early 1997. Players began to be produced domestically that winter, with March 24, 1997, as the U.S. launch date of the format proper in seven test markets. Approximately 32 titles were available on launch day, mainly from the Warner Bros., MGM, and New Line libraries, with the notable inclusion of the 1996 film Twister. However, the launch was planned for the following day (March 25), leading to a distribution change with retailers and studios to prevent similar violations of breaking the street date. The nationwide rollout for the format happened on August 22, 1997. DTS announced in late 1997 that they would be coming onto the format. The sound system company revealed details in a November 1997 online interview, and clarified it would release discs in early 1998. However, this date would be pushed back several times before finally releasing their first titles at the 1999 Consumer Electronics Show. In 2001, blank DVD recordable discs cost the equivalent of $27.34 US dollars in 2022. === Adoption === Movie and home entertainment distributors adopted the DVD format to replace the ubiquitous VHS tape as the primary consumer video distribution format. Immediately following the formal adoption of a unified standard for DVD, two of the four leading video game console companies (Sega and The 3DO Company) said they already had plans to design a gaming console with DVDs as the source medium. Sony stated at the time that they had no plans to use DVD in their gaming systems, despite being one of the developers of the DVD format and eventually the first company to actually release a DVD-based console. Game consoles such as the PlayStation 2, Xbox, and Xbox 360 use DVDs as their source medium for games and other software. Contemporary games for Windows were also distributed on DVD. Early DVDs were mastered using DLT tape, but using DVD-R DL or +R DL eventually became common. TV DVD combos, combining a standard definition CRT TV or an HD flat panel TV with a DVD mechanism under the CRT or on the back of the flat panel, and VCR/DVD combos were also available for purchase. For consumers, DVD soon overtook VHS as the favored choice for home movie releases. In 2001, DVD players outsold VCRs for the first time in the United States. At that time, one in four American households owned a DVD player. By 2007, about 80% of Americans owned a DVD player, a figure that had surpassed VCRs; it was also higher than personal computers or cable television. == Specifications == The DVD specifications created and updated by the DVD Forum are published as so-called DVD Books (e.g. DVD-ROM Book, DVD-Audio Book, DVD-Video Book, DVD-R Book, DVD-RW Book, DVD-RAM Book, DVD-AR (Audio Recording) Book, DVD-VR (Video Recording) Book, etc.). DVD discs are made up of two discs; normally one is blank, and the other contains data. Each disc is 0.6 mm thick, and they are glued together to form a DVD disc. The gluing process must be done carefully to make the disc as flat as possible to avoid both birefringence and "disc tilt", which is when the disc is not perfectly flat, preventing it from being read. Some specifications for mechanical, physical and optical characteristics of DV
SitePal
SitePal is a speaking avatar platform for small and medium-sized businesses developed by Oddcast. SitePal allows users to deploy "virtual employees" on websites that can welcome visitors, guide them around the site and answer questions. The use of SitePal on commercial websites has been controversial because many visitors report finding them annoying. Some research has shown that they can increase sales in comparison to using static photographs. == Development == The technology used was the result of more than 4 years of research at Stanford University. The research was based on a literature review and other previous work in the field of artificial intelligence research. The SitePal AI option uses the AIML programming language, which is partially editable by users. This allows web designers to simulate normal human conversation by using keywords or key phrases that the bot can respond to. == Features == The company provides web designers with options to customize the chosen avatar. A large selection of faces, clothing, hair, backgrounds, voices and other details are available. If a web designer wants to use a particular face, Sitepal can create one from a photo. Thus, a mascot or a known face can be simulated. == Speech == Sitepal avatars talk through text-to-speech (tts) software. A short paragraph can be written (up to 900 characters) and the text-to-speech engine will compile the actual speech, which can be reproduced and edited. The tts engine is not perfect, but it comes close to actual speech and is easy to understand. Tts can be further enhanced by some commands, like /laugh and /loud which make the avatar laugh or talk loud. Even pronunciation is possible. The web designer can record and upload his or her own audio messages. Alternatively Sitepal offers professional voice acting service at extra cost. == User interaction == The company provides 5 options for visitor interaction: No interaction. The avatar simply says a pre-fixed message. FAQ mode. Questions can be configured, which are clickable and the user can hear the answer. Lead mode. The avatar prompts the user to type his email and short message, so it can be sent to the webmaster (usually used on a "contact us" page) Chatbot mode. The avatar greets the user, and he can type his questions and have a conversation with the bot. With predetermined replies, this can work as an FAQ as well. API customization. Experienced programmers can make their avatar interact with their website, making it talk when the user clicks on a link or when other triggers occur. Even dual avatar conversations can be created, like a talk show. == Posting options == The company provides five options for posting the avatar: Embed in webpage (via javascript) Embed in HTML Send by email Publish to eBay Embed in Flash == Criticism == Early reviews, such as one by Troy Dreier published in PC World in 2002 were positive and described SitePal as: "an engagingly simple and personal tool, and the price is reasonable for what it adds to a site". Although Dreier did note that the program had "bugs that suggested it hadn't been tested thoroughly". In more recent years, reaction to SitePal has been much more negative with reviews such as Tom Spring writing in a PC World review citing SitePal ads and described his reaction as "Not so nice". Paul Bissex, writing in E-Scribe News described SitePal as "heinous... and embarrassing if anyone is within earshot...they creep me out" == Research on effectiveness == In one single-website research project Anita Campbell had half the visitors to Small Business Trends see a SitePal and the other half see just a static photograph. Over 11,000 visitors the SitePal avatar improved sign-up for a newsletter 144% over the control condition.
Content reference identifier
A content reference identifier or CRID is a concept from the standardization work done by the TV-Anytime forum. It is or closely matches the concept of the Uniform Resource Locator, or URL, as used on the World-Wide Web: A unit of content, in a broadcast stream, can be referred to by its globally unique CRID in the same way that a webpage can be referred to by its globally unique URL on the web. The concept of CRID permits referencing contents unambiguously, regardless of their location, i.e., without knowing specific broadcast information (time, date and channel) or how to obtain them through a network, for instance, by means of a streaming service or by downloading a file from an Internet server. The receiver must be capable of resolving these unambiguous references, i.e. of translating them into specific data that will allow it to obtain the location of that content in order to acquire it. This makes it possible for recording processes to take place without knowing that information, and even without knowing beforehand the duration of the content to be recorded: a complete series by a simple click, a program that has not been scheduled yet, a set of programs grouped by a specific criterion... This framework allows for the separation between the reference to a given content (the CRID) and the necessary information to acquire it, which is called a “locator”. Each CRID may lead to one or more locators which will represent different copies of the same content. They may be identical copies broadcast in different channels or dates, or cost different prices. They may also be distinct copies with different technical parameters such as format or quality. It may also be the case that the resolution process of a CRID provides another CRID as a result (for example, its reference in a different network, where it has an alternative identifier assigned by a different operator) or a set of CRIDs (for instance, if the original CRID represents a TV series, in which case the resolution process would result in the list of CRIDs representing each episode). From the above it can be concluded that provided that a given content can belong to many groups (each possibly defined by distinctive qualities), it is possible that many CRIDs carry the same content. That is, several CRIDs may be resolved into the same locator. A CRID is not exactly a universal, unique and exclusive identifier for a given content. It is closely related to the authority that creates it, to the resolution service provider, and to the content provider in such a way that the same content may have different CRIDs depending on the field in which they are used (for example, a different one for each television operator that has the rights to broadcast the content). == Format == A CRID is specified much like URLs. In fact, a CRID is a so-called URI. Typically, the content creator, the broadcaster or a third party will use their DNS-names in a combination with a product-specific name to create globally unique CRIDs. That is, the syntax of a CRID is: crid://authority/data The authority field represents the entity that created the CRID and its format is that of a DNS name. The data field represents a string of characters that will unambiguously identify the content within the authority scope (it is a string of characters assigned by the authority itself). As an example, let's assume that BBC wanted to make a CRID for (all the programs of) the Olympics in China. It may have looked something like this crid://bbc.co.uk/olympics/2008/ This would be a group CRID, that is, a CRID representing a group of contents. Then, to refer to a specific event – such as the women's shot-put final – they could have used the following inside their metadata. crid://bbc.co.uk/olympics/2008/final/shotput/women Currently, four types of CRIDs are playing a major role in some unidirectional television networks: programme CRID, series CRID, group CRID, and recommendation CRID. One of the most important applications of CRIDs is the so-called series link recording function (SL) of modern digital video recorders (DVR, PVR). In turn, a locator is a string of characters that contains all the necessary information for a receiver to find and acquire a given content, whether it is received through a transport stream, located in local storage, downloaded as a file from an Internet server, or through a streaming service. For example, a DVB locator will include all the necessary parameters to identify a specific content within a transport stream: network, transport stream, service, table and/or event identifiers. The locators' format, as established in TV-Anytime, is quite generic and simple, and corresponds to: [transport-mechanism]:[specific-data] The first part of the locator's format (the transport mechanism) must be a string of characters that is unique for each mechanism (transport stream, local file, HTTP Internet access...). The second part must be unambiguous only within the scope of a given transport mechanism and will be standardized by the organism in charge of the regulation of the mechanism itself. For instance, a DVB locator to identify a content within the transport stream of networks that follow this standard would be: dvb://112.4a2.5ec;2d22~20121212T220000Z—PT01H30M which would indicate a content (identified by the string “2d22”) that airs on a channel available on a DVB network identified by the address “112.4a2.5ec” (network “112”, transport stream “4a2” and service “5ec”), on 12 December 2012 at 10 p.m. and with a duration of 90 minutes. == The location resolution process == The location resolution process is the procedure by which, starting from the CRID of a given content, one or several locators of that content are obtained. Resolving a CRID can be a direct process, which leads immediately to one or many locators, or it may also happen that in the first place one or many intermediate CRIDs are returned, which must undergo the same procedure to finally obtain one or several locators. This procedure involves some information elements, among which we find two structures named resolving authority record (RAR) and ContentReferencingTable, respectively. Consulting them repeatedly will take the receiver from a CRID to one or many locators that will allow it to acquire the content. The RAR table The RAR table is one or many data structures that provide the receiver, for each authority that submits CRIDs, information on the corresponding resolution service provider. Among other things, it informs about which mechanism is used to provide information to resolve the CRIDs from each authority. That is, one or many RAR records must exist for each authority that indicate the receiver where it has to go to resolve the CRIDs of that particular authority. For example, in the record of the figure (expressed by means of a XML structure, according to the XML Schema defined in the TV-Anytime) there is an authority called “tve.es”, whose resolution service provider is the entity “rtve.es”, available on the URL "http://tva.rtve.es/locres/tve", which means there is resolution information in that URL. These RAR records will have reached the receiver in an indefinite form, unimportant for the TV-Anytime specification, which will depend on the specific transport mechanism of the network to which the receiver is connected. Each family of standards that regulates distribution networks (DVB, ATSC, ISDB, IPTV...) will have previously defined such procedure, which will be used by devices certified according to those standards. The ContentReferencingTable table The second structure involved in the location resolution process is a proper resolution table which, given a content's CRID, returns one or several locators that enable the receiver to access an instance of that content, or one or many CRIDs that allow it to move forward in the resolution process. The figure shows an example of this second structure, an XML document according to the specifications of the XML Schema defined in TV-Anytime. In it, several sections are included (
Artificial general intelligence
Artificial general intelligence (AGI) is a hypothetical type of artificial intelligence that matches or surpasses human capabilities across virtually all cognitive tasks. Beyond AGI, artificial superintelligence (ASI) would outperform the best human abilities across every domain by a wide margin. Unlike artificial narrow intelligence (ANI), whose competence is confined to well‑defined tasks, an AGI system can generalise knowledge, transfer skills between domains, and solve novel problems without task‑specific reprogramming. Creating AGI is a stated goal of technology companies such as OpenAI, Google, xAI, and Meta. A 2020 survey identified 72 active AGI research and development projects across 37 countries. AGI is a common topic in science fiction and futures studies. Contention exists over whether AGI represents an existential risk. Some AI experts and industry figures have stated that mitigating the risk of human extinction posed by AGI should be a global priority. Others find the development of AGI to be in too remote a stage to present such a risk. == Terminology == AGI is also known as strong AI, full AI, human-level AI, human-level intelligent AI, or general intelligent action. The term "artificial general intelligence" was used in 1997 by Mark Gubrud in a discussion of the implications of fully automated military production and operations. A mathematical formalism of AGI named AIXI was proposed in 2000 by Marcus Hutter, who defines intelligence as "an agent’s ability to achieve goals or succeed in a wide range of environments". This type of AGI has also been called "universal artificial intelligence". The term AGI was re-introduced and popularized by Shane Legg and Ben Goertzel around 2002. Some academic sources reserve the term "strong AI" for computer programs that will experience sentience or consciousness. In contrast, weak AI (or narrow AI) can solve a specific problem but lacks general cognitive abilities. Some academic sources use "weak AI" to refer more broadly to any programs that neither experience consciousness nor have a mind in the same sense as humans. Related concepts include artificial superintelligence and transformative AI. An artificial superintelligence (ASI) is a hypothetical type of AGI that is much more generally intelligent than humans, while the notion of transformative AI relates to AI having a large impact on society, for example, similar to the agricultural or industrial revolution. A framework for classifying AGI was proposed in 2023 by Google DeepMind researchers. They define five performance levels of AGI: emerging, competent, expert, virtuoso, and superhuman. For example, a competent AGI is defined as an AI that outperforms 50% of skilled adults in a wide range of non-physical tasks, and a superhuman AGI (i.e., an artificial superintelligence) is similarly defined but with a threshold of 100%. They consider large language models like ChatGPT or LLaMA 2 to be instances of emerging AGI (comparable to unskilled humans). Regarding the autonomy of AGI and associated risks, they define five levels: tool (fully in human control), consultant, collaborator, expert, and agent (fully autonomous). == Characteristics == There is no single agreed-upon definition of intelligence as applied to computers. Computer scientist John McCarthy wrote in 2007: "We cannot yet characterize in general what kinds of computational procedures we want to call intelligent." === Intelligence traits === Researchers generally hold that a system is required to do all of the following to be regarded as an AGI: reason, use strategy, solve puzzles, and make judgments under uncertainty, represent knowledge, including common sense knowledge, plan, learn, communicate in natural language, if necessary, integrate these skills in completion of any given goal. Many interdisciplinary approaches (e.g. cognitive science, computational intelligence, and decision making) consider additional traits such as imagination (the ability to form novel mental images and concepts) and autonomy. Computer-based systems exhibiting these capabilities are now widespread, with modern large language models demonstrating computational creativity, automated reasoning, and decision support simultaneously across domains. === Physical traits === Other capabilities are considered desirable in intelligent systems, as they may affect intelligence or aid in its expression. These include: the ability to sense (e.g. see, hear, etc.), and the ability to act (e.g. move and manipulate objects, change location to explore, etc.) This includes the ability to detect and respond to hazard. === Tests for human-level AGI === Several tests meant to confirm human-level AGI have been considered. ==== Turing test ==== The Turing test was proposed by Alan Turing in his 1950 paper "Computing Machinery and Intelligence". This test involves a human judge engaging in natural language conversations with both a human and a machine designed to generate human-like responses. The machine passes the test if it can convince the judge that it is human a significant fraction of the time. Turing proposed this as a practical measure of machine intelligence, focusing on the ability to produce human-like responses rather than on the internal workings of the machine. The idea of the test is that the machine has to try and pretend to be a man, by answering questions put to it, and it will only pass if the pretence is reasonably convincing. A considerable portion of a jury, who should not be experts about machines, must be taken in by the pretence. In 2014, a chatbot named Eugene Goostman, designed to imitate a 13-year-old Ukrainian boy, reportedly passed a Turing Test event by convincing 33% of judges that it was human. However, this claim was met with significant skepticism from the AI research community, who questioned the test's implementation and its relevance to AGI. A 2025 pre‑registered, three‑party Turing‑test study by Cameron R. Jones and Benjamin K. Bergen showed that GPT-4.5 was judged to be the human in 73% of five‑minute text conversations—surpassing the 67% humanness rate of real confederates and meeting the researchers' criterion for having passed the test. ==== Ikea test ==== The "Ikea test", also known as the Flat Pack Furniture Test, involves an AI controlling a robot which attempts to assemble an Ikea flat-pack furniture product after having been shown the parts and instructions. As early as 2013, MIT's IkeaBot demonstrated fully autonomous multi-robot assembly of an IKEA Lack table in ten minutes, with no human intervention and no pre-programmed assembly instructions. The robots inferred the assembly sequence from the geometry of the parts alone. ==== Coffee test ==== Steve Wozniak proposed a test where a machine is required to enter an average American home and figure out how to make coffee. It must find the coffee machine, find the coffee, add water, find a mug, and brew the coffee by pushing the proper buttons. This test has been substantially approached across multiple systems. In January 2024, Figure AI's Figure 01 humanoid learned to operate a Keurig coffee machine autonomously after watching video demonstrations, using end-to-end neural networks to translate visual input into motor actions. In 2025, researchers at the University of Edinburgh published the ELLMER framework in Nature Machine Intelligence, demonstrating a robotic arm that interprets verbal instructions, analyses its surroundings, and autonomously makes coffee in dynamic kitchen environments — adapting to unforeseen obstacles in real time rather than following pre-programmed sequences. ==== Suleyman's test ==== Mustafa Suleyman's test proposes giving an AI model US$100,000 and asking it to obtain US$1 million. ==== Use of video-games ==== Adams, et al. propose that the ability to learn and succeed in a wide range of video games can be used to test AI intelligence. This range would include games unknown to the AGI developers before the test is administered. === AI-complete problems === A problem is informally called "AI-complete" or "AI-hard" if it is believed that AGI would be needed to solve it, because the solution is beyond the capabilities of a purpose-specific algorithm. == History == === Classical AI === Modern AI research began in the mid-1950s. The first generation of AI researchers were convinced that artificial general intelligence was possible and that it would exist in just a few decades. AI pioneer Herbert A. Simon wrote in 1965: "machines will be capable, within twenty years, of doing any work a man can do". Their predictions were the inspiration for Stanley Kubrick and Arthur C. Clarke's fictional character HAL 9000, who embodied what AI researchers believed they could create by the year 2001. AI pioneer Marvin Minsky was a consultant on the project of making HAL 9000 as realistic as possible according to the consensus predictions of the time. He said in 1967, "Within a generation... the problem of
Pull technology
Pull coding or client pull is a style of network communication, where the initial request for data originates from the client, and then is responded to by the server. The reverse is known as push technology, where the server pushes data to clients. Pull requests form the foundation of network computing, where many clients request data from centralized servers. Pull is used extensively on the Internet for HTTP page requests from websites. A push can also be simulated using multiple pulls within a short amount of time. For example, when pulling POP3 email messages from a server, a client can make regular pull requests, every few minutes. To the user, the email then appears to be pushed, as emails appear to arrive close to real-time. A trade-off of this system is that it places a heavier load on both the server and network to function correctly. Many web feeds, such as RSS are technically pulled by the client. With RSS, the user's RSS reader polls the server periodically for new content; the server does not send information to the client unrequested. This continual polling is inefficient and has contributed to the shutdown or reduction of several popular RSS feeds that could not handle the bandwidth. For solving this problem, the WebSub protocol, as another example of a push code, was devised. Podcasting is specifically a pull technology. When a new podcast episode is published to an RSS feed, it sits on the server until it is requested by a feed reader, mobile podcasting app, or directory. Directories such as Apple Podcasts (iTunes), The Blubrry Directory, and many apps' directories request the RSS feed periodically to update the Podcast's listing on those platforms. Subscribers to those RSS feeds via app or reader will get the episodes when they request the RSS feed next time, independent of when the directory listing updates.