Artificial development, also known as artificial embryogeny or machine intelligence or computational development, is an area of computer science and engineering concerned with computational models motivated by genotype–phenotype mappings in biological systems. Artificial development is often considered a sub-field of evolutionary computation, although the principles of artificial development have also been used within stand-alone computational models. Within evolutionary computation, the need for artificial development techniques was motivated by the perceived lack of scalability and evolvability of direct solution encodings (Tufte, 2008). Artificial development entails indirect solution encoding. Rather than describing a solution directly, an indirect encoding describes (either explicitly or implicitly) the process by which a solution is constructed. Often, but not always, these indirect encodings are based upon biological principles of development such as morphogen gradients, cell division and cellular differentiation (e.g. Doursat 2008), gene regulatory networks (e.g. Guo et al., 2009), degeneracy (Whitacre et al., 2010), grammatical evolution (de Salabert et al., 2006), or analogous computational processes such as re-writing, iteration, and time. The influences of interaction with the environment, spatiality and physical constraints on differentiated multi-cellular development have been investigated more recently (e.g. Knabe et al. 2008). Artificial development approaches have been applied to a number of computational and design problems, including electronic circuit design (Miller and Banzhaf 2003), robotic controllers (e.g. Taylor 2004), and the design of physical structures (e.g. Hornby 2004).
Multi-agent reinforcement learning
Multi-agent reinforcement learning (MARL) is a sub-field of reinforcement learning. It focuses on studying the behavior of multiple learning agents that coexist in a shared environment. Each agent is motivated by its own rewards, and does actions to advance its own interests; in some environments these interests are opposed to the interests of other agents, resulting in complex group dynamics. Multi-agent reinforcement learning is closely related to game theory and especially repeated games, as well as multi-agent systems. Its study combines the pursuit of finding ideal algorithms that maximize rewards with a more sociological set of concepts. While research in single-agent reinforcement learning is concerned with finding the algorithm that gets the biggest number of points for one agent, research in multi-agent reinforcement learning evaluates and quantifies social metrics, such as cooperation, reciprocity, equity, social influence, language and discrimination. == Definition == Similarly to single-agent reinforcement learning, multi-agent reinforcement learning is modeled as some form of a Markov decision process (MDP). Fix a set of agents I = { 1 , . . . , N } {\displaystyle I=\{1,...,N\}} . We then define: A set S {\displaystyle S} of environment states. One set A i {\displaystyle {\mathcal {A}}_{i}} of actions for each of the agents i ∈ I = { 1 , … , N } {\displaystyle i\in I=\{1,\dots ,N\}} . P a → ( s , s ′ ) = Pr ( s t + 1 = s ′ ∣ s t = s , a → t = a → ) {\displaystyle P_{\vec {a}}(s,s')=\Pr(s_{t+1}=s'\mid s_{t}=s,{\vec {a}}_{t}={\vec {a}})} is the probability of transition (at time t {\displaystyle t} ) from state s {\displaystyle s} to state s ′ {\displaystyle s'} under joint action a → {\displaystyle {\vec {a}}} . R → a → ( s , s ′ ) {\displaystyle {\vec {R}}_{\vec {a}}(s,s')} is the immediate joint reward after the transition from s {\displaystyle s} to s ′ {\displaystyle s'} with joint action a → {\displaystyle {\vec {a}}} . In settings with perfect information, such as the games of chess and Go, the MDP would be fully observable. In settings with imperfect information, especially in real-world applications like self-driving cars, each agent would access an observation that only has part of the information about the current state. In the partially observable setting, the core model is the partially observable stochastic game in the general case, and the decentralized POMDP in the cooperative case. == Cooperation vs. competition == When multiple agents are acting in a shared environment their interests might be aligned or misaligned. MARL allows exploring all the different alignments and how they affect the agents' behavior: In pure competition settings, the agents' rewards are exactly opposite to each other, and therefore they are playing against each other. Pure cooperation settings are the other extreme, in which agents get the exact same rewards, and therefore they are playing with each other. Mixed-sum settings cover all the games that combine elements of both cooperation and competition. === Pure competition settings === When two agents are playing a zero-sum game, they are in pure competition with each other. Many traditional games such as chess and Go fall under this category, as do two-player variants of video games like StarCraft. Because each agent can only win at the expense of the other agent, many complexities are stripped away. There is no prospect of communication or social dilemmas, as neither agent is incentivized to take actions that benefit its opponent. The Deep Blue and AlphaGo projects demonstrate how to optimize the performance of agents in pure competition settings. One complexity that is not stripped away in pure competition settings is autocurricula. As the agents' policy is improved using self-play, multiple layers of learning may occur. === Pure cooperation settings === MARL is used to explore how separate agents with identical interests can communicate and work together. Pure cooperation settings are explored in recreational cooperative games such as Overcooked, as well as real-world scenarios in robotics. In pure cooperation settings all the agents get identical rewards, which means that social dilemmas do not occur. In pure cooperation settings, oftentimes there are an arbitrary number of coordination strategies, and agents converge to specific "conventions" when coordinating with each other. The notion of conventions has been studied in language and also alluded to in more general multi-agent collaborative tasks. === Mixed-sum settings === Most real-world scenarios involving multiple agents have elements of both cooperation and competition. For example, when multiple self-driving cars are planning their respective paths, each of them has interests that are diverging but not exclusive: Each car is minimizing the amount of time it's taking to reach its destination, but all cars have the shared interest of avoiding a traffic collision. Zero-sum settings with three or more agents often exhibit similar properties to mixed-sum settings, since each pair of agents might have a non-zero utility sum between them. Mixed-sum settings can be explored using classic matrix games such as prisoner's dilemma, more complex sequential social dilemmas, and recreational games such as Among Us, Diplomacy and StarCraft II. Mixed-sum settings can give rise to communication and social dilemmas. == Social dilemmas == As in game theory, much of the research in MARL revolves around social dilemmas, such as prisoner's dilemma, chicken and stag hunt. While game theory research might focus on Nash equilibria and what an ideal policy for an agent would be, MARL research focuses on how the agents would learn these ideal policies using a trial-and-error process. The reinforcement learning algorithms that are used to train the agents are maximizing the agent's own reward; the conflict between the needs of the agents and the needs of the group is a subject of active research. Various techniques have been explored in order to induce cooperation in agents: Modifying the environment rules, adding intrinsic rewards, and more. === Sequential social dilemmas === Social dilemmas like prisoner's dilemma, chicken and stag hunt are "matrix games". Each agent takes only one action from a choice of two possible actions, and a simple 2x2 matrix is used to describe the reward that each agent will get, given the actions that each agent took. In humans and other living creatures, social dilemmas tend to be more complex. Agents take multiple actions over time, and the distinction between cooperating and defecting is not as clear cut as in matrix games. The concept of a sequential social dilemma (SSD) was introduced in 2017 as an attempt to model that complexity. There is ongoing research into defining different kinds of SSDs and showing cooperative behavior in the agents that act in them. == Autocurricula == An autocurriculum (plural: autocurricula) is a reinforcement learning concept that's salient in multi-agent experiments. As agents improve their performance, they change their environment; this change in the environment affects themselves and the other agents. The feedback loop results in several distinct phases of learning, each depending on the previous one. The stacked layers of learning are called an autocurriculum. Autocurricula are especially apparent in adversarial settings, where each group of agents is racing to counter the current strategy of the opposing group. The Hide and Seek game is an accessible example of an autocurriculum occurring in an adversarial setting. In this experiment, a team of seekers is competing against a team of hiders. Whenever one of the teams learns a new strategy, the opposing team adapts its strategy to give the best possible counter. When the hiders learn to use boxes to build a shelter, the seekers respond by learning to use a ramp to break into that shelter. The hiders respond by locking the ramps, making them unavailable for the seekers to use. The seekers then respond by "box surfing", exploiting a glitch in the game to penetrate the shelter. Each "level" of learning is an emergent phenomenon, with the previous level as its premise. This results in a stack of behaviors, each dependent on its predecessor. Autocurricula in reinforcement learning experiments are compared to the stages of the evolution of life on Earth and the development of human culture. A major stage in evolution happened 2-3 billion years ago, when photosynthesizing life forms started to produce massive amounts of oxygen, changing the balance of gases in the atmosphere. In the next stages of evolution, oxygen-breathing life forms evolved, eventually leading up to land mammals and human beings. These later stages could only happen after the photosynthesis stage made oxygen widely available. Similarly, human culture could not have gone through the Industrial Revolution in the 18th century without the resources and insights gaine
Virtual DOM
A virtual DOM is a lightweight JavaScript representation of the Document Object Model (DOM) used in declarative web frameworks such as React, Vue.js, and Elm. Since generating a virtual DOM is relatively fast, any given framework is free to rerender the virtual DOM as many times as needed relatively cheaply. The framework can then find the differences between the previous virtual DOM and the current one (diffing), and only makes the necessary changes to the actual DOM (reconciliation). While technically slower than using just vanilla JavaScript, the pattern makes it much easier to write websites with a lot of dynamic content, since markup is directly coupled with state. Similar techniques include Ember.js' Glimmer and Angular's incremental DOM. == History == The JavaScript DOM API has historically been inconsistent across browsers, clunky to use, and difficult to scale for large projects. While libraries like jQuery aimed to improve the overall consistency and ergonomics of interacting with HTML, it too was prone to repetitive code that didn't describe the nature of the changes being made well and decoupled logic from markup. The release of AngularJS in 2010 provided a major paradigm shift in the interaction between JavaScript and HTML with the idea of dirty checking. Instead of imperatively declaring and destroying event listeners and modifying individual DOM nodes, changes in variables were tracked and sections of the DOM were invalidated and rerendered when a variable in their scope changed. This digest cycle provided a framework to write more declarative code that coupled logic and markup in a more logical way. While AngularJS aimed to provide a more declarative experience, it still required data to be explicitly bound to and watched by the DOM, and performance concerns were cited over the expensive process of dirty checking hundreds of variables. To alleviate these issues, React was the first major library to adopt a virtual DOM in 2013, which removed both the performance bottlenecks (since diffing and reconciling the DOM was relatively cheap) and the difficulty of binding data (since components were effectively just objects). Other benefits of a virtual DOM included improved security since XSS was effectively impossible and better extensibility since a component's state was entirely encapsulated. Its release also came with the advent of JSX, which further coupled HTML and JavaScript with an XML-like syntax extension. Following React's success, many other web frameworks copied the general idea of an ideal DOM representation in memory, such as Vue.js in 2014, which used a template compiler instead of JSX and had fine-grained reactivity built as part of the framework. In recent times, the virtual DOM has been criticized for being slow due to the additional time required for diffing and reconciling DOM nodes. This has led to the development of frameworks without a virtual DOM, such as Svelte, and frameworks that edit the DOM in-place such as Angular 2. == Implementations == === React === React pioneered the use of a virtual DOM to make components declaratively. Virtual DOM nodes are constructed using the createElement() function, but are often transpiled from JSX to make writing components more ergonomic. In class-based React, virtual DOM nodes are returned from the render() function, while in functional hook-based components, the return value of the function itself serves as the page markup. === Vue.js === Vue.js uses a virtual DOM to handle state changes, but is usually not directly interacted with; instead, a compiler is used to transform HTML templates into virtual DOM nodes as an implementation detail. While Vue supports writing JSX and custom render functions, it's more typical to use the template compiler since a build step isn't required that way. === Svelte === Svelte does not have a virtual DOM, with its creator Rich Harris calling the virtual DOM "pure overhead". Instead of diffing and reconciling DOM nodes at runtime, Svelte uses compile-time reactivity to analyze markup and generate JavaScript code that directly manipulates the DOM, drastically increasing performance.
Digital signal
A digital signal is a signal that represents data as a sequence of discrete values; at any given time it can only take on, at most, one of a finite number of values. This contrasts with an analog signal, which represents continuous values; at any given time it represents a real number within an infinite set of values. Simple digital signals represent information in discrete bands of levels. All levels within a band of values represent the same information state. In most digital circuits, the signal can have two possible valid values; this is called a binary signal or logic signal. They are represented by two voltage bands: one near a reference value (typically termed as ground or zero volts), and the other a value near the supply voltage. These correspond to the two values zero and one (or false and true) of the Boolean domain, so at any given time a binary signal represents one binary digit (bit). Because of this discretization, relatively small changes to the signal levels do not leave the discrete envelope, and as a result are ignored by signal state sensing circuitry. As a result, digital signals have noise immunity; electronic noise, provided it is not too great, will not affect digital circuits, whereas noise always degrades the operation of analog signals to some degree. Digital signals having more than two states are occasionally used; circuitry using such signals is called multivalued logic. For example, signals that can assume three possible states are called three-valued logic. In a digital signal, the physical quantity representing the information may be a variable electric current or voltage, the intensity, phase or polarization of an optical or other electromagnetic field, acoustic pressure, the magnetization of a magnetic storage media, etcetera. Digital signals are used in all digital electronics, notably computing equipment and data transmission. == Definitions == The term digital signal has related definitions in different contexts. === In digital electronics === In digital electronics, a digital signal is a pulse amplitude modulated signal, i.e., a sequence of fixed-width electrical pulses or light pulses, each occupying one of a discrete number of levels of amplitude. A special case is a logic signal or a binary signal, which varies between a low and a high signal level. The pulse trains in digital circuits are typically generated by metal–oxide–semiconductor field-effect transistor (MOSFET) devices, due to their rapid on–off electronic switching speed and large-scale integration (LSI) capability. In contrast, bipolar junction transistors more slowly generate signals resembling sine waves. === In signal processing === In digital signal processing, a digital signal is a representation of a physical signal that is sampled and quantized. A digital signal is an abstraction that is discrete in time and amplitude. The signal's value only exists at regular time intervals, since only the values of the corresponding physical signal at those sampled moments are significant for further digital processing. The digital signal is a sequence of codes drawn from a finite set of values. The digital signal may be stored, processed or transmitted physically as a pulse-code modulation (PCM) signal. === In communications === In digital communications, a digital signal is a continuous-time physical signal, alternating between a discrete number of waveforms, representing a bitstream. The shape of the waveform depends on the transmission scheme, which may be either a line coding scheme allowing baseband transmission; or a digital modulation scheme, allowing passband transmission over long wires or over a limited radio frequency band. Such a carrier-modulated sine wave is considered a digital signal in literature on digital communications and data transmission, but considered as a bit stream converted to an analog signal in specific cases where the signal will be carried over a system meant for analog communication, such as an analog telephone line. In communications, sources of interference are usually present, and noise is frequently a significant problem. The effects of interference are typically minimized by filtering off interfering signals as much as possible and by using data redundancy. The main advantages of digital signals for communications are often considered to be noise immunity, and the ability, in many cases such as with audio and video data, to use data compression to greatly decrease the bandwidth that is required on the communication media. == Logic voltage levels == A waveform that switches representing the two states of a Boolean value (0 and 1, or low and high, or false and true) is referred to as a digital signal or logic signal or binary signal when it is interpreted in terms of only two possible digits. The two states are usually represented by some measurement of an electrical property: Voltage is the most common, but current is used in some logic families. Two ranges of voltages are typically defined for each logic family, which are frequently not directly adjacent. The signal is low when in the low range and high when in the high range, and in between the two ranges the behavior can vary between different types of gates. The clock signal is a special digital signal that is used to synchronize many digital circuits. The image shown can be considered the waveform of a clock signal. Logic changes are triggered either by the rising edge or the falling edge. The rising edge is the transition from a low voltage (level 1 in the diagram) to a high voltage (level 2). The falling edge is the transition from a high voltage to a low one. Although in a highly simplified and idealized model of a digital circuit, we may wish for these transitions to occur instantaneously, no real-world circuit is purely resistive, and therefore no circuit can instantly change voltage levels. This means that during a short, finite transition time, the output may not properly reflect the input, and will not correspond to either a logically high or low voltage. == Modulation == To create a digital signal, a signal must be modulated with a control signal to produce it. The simplest modulation, a type of unipolar encoding, is simply to switch on and off a DC signal so that high voltages represent a '1' and low voltages are '0'. In digital radio schemes, one or more carrier waves are amplitude, frequency or phase modulated by the control signal to produce a digital signal suitable for transmission. Asymmetric Digital Subscriber Line (ADSL) over telephone wires, does not primarily use binary logic; the digital signals for individual carriers are modulated with different-valued logics, depending on the Shannon capacity of the individual channel. == Clocking == Digital signals may be sampled by a clock signal at regular intervals by passing the signal through a flip-flop. When this is done, the input is measured at the clock edge and the signal from that time. The signal is then held steady until the next clock. This process is the basis of synchronous logic. Asynchronous logic also exists, which uses no single clock, and generally operates more quickly, and may use less power, but is significantly harder to design.
Facebook is an American social networking service owned by the American technology conglomerate Meta Platforms. It was founded in 2004 by Mark Zuckerberg, along with his Harvard College roommates and fellow students Eduardo Saverin, Andrew McCollum, Dustin Moskovitz, and Chris Hughes. The name Facebook derives from the face book directories often given to American university students. The service was initially limited to Harvard students before gradually expanding to other universities in North America. Since 2006, Facebook has permitted registration by individuals aged 13 and older, with the exception of South Korea, Spain, and Quebec, where the minimum age is 14. As of December 2023, Facebook reported approximately 3.07 billion monthly active users worldwide. As of July 2025, it was ranked as the third-most-visited website in the world, with 23 percent of its traffic originating from the United States. It was the most downloaded mobile application of the 2010s. Facebook can be accessed from devices with Internet connectivity, such as personal computers, tablets and smartphones. After registering, users can create a profile revealing personal information about themselves. They can post text, photos and multimedia which are shared either publicly or exclusively with other users who have agreed to be their friend, depending on privacy settings. Users can also communicate directly with each other with Messenger, edit messages (within 15 minutes after sending), join common-interest groups, and receive notifications on the activities of their Facebook friends and the pages they follow. Facebook has often been criticized over issues such as user privacy (as with the Facebook–Cambridge Analytica data scandal), political manipulation (as with the 2016 U.S. elections) and mass surveillance. The company has also been subject to criticism over its psychological effects such as addiction and low self-esteem, and over content such as fake news, conspiracy theories, copyright infringement, and hate speech. Commentators have accused Facebook of willingly facilitating the spread of such content, as well as overemphasizing its number of users to appeal to advertisers. == History == The history of Facebook traces its growth from a college networking site to a global social networking service. While attending Phillips Exeter in the early 2000s, Zuckerberg met Kris Tillery. Tillery, a one-time project collaborator with Zuckerberg, would create a school-based social networking project called Photo Address Book. Photo Address Book was a digital face book, created through a linked database composed of student information derived from the official records of the Exeter Student Council. The database contained linkages such as name, dorm-specific landline numbers, and student headshots. Mark Zuckerberg built a website called "Facemash" in 2003 while attending Harvard University. The site was comparable to Hot or Not and used photos from online face books, asking users to choose the 'hotter' person". Zuckerberg was reported and faced expulsion, but the charges were dropped. A "face book" is a student directory featuring photos and personal information. In January 2004, Zuckerberg coded a new site known as "TheFacebook", stating, "It is clear that the technology needed to create a centralized Website is readily available ... the benefits are many." Zuckerberg met with Harvard student Eduardo Saverin, and each agreed to invest $1,000. On February 4, 2004, Zuckerberg launched "TheFacebook". Membership was initially restricted to students of Harvard College. Dustin Moskovitz, Andrew McCollum, and Chris Hughes joined Zuckerberg to help manage the growth of the site. It became available successively to most universities in the US and Canada. In 2004, Napster co-founder Sean Parker became company president and the company moved to Palo Alto, California. PayPal co-founder Peter Thiel gave Facebook its first investment. In 2005, the company dropped "the" from its name after purchasing the domain name Facebook.com. In 2006, Facebook opened to everyone at least or only 13 years old with a valid email address. Facebook introduced key features like the News Feed, which became central to user engagement. By late 2007, Facebook had 100,000 pages on which companies promoted themselves. Facebook had surpassed MySpace in global traffic and became the world's most popular social media platform. Microsoft announced that it had purchased a 1.6% share of Facebook for $240 million ($373 million in 2025 dollars), giving Facebook an implied value of around $15 billion ($23.3 billion in 2025 dollars). Facebook focused on generating revenue through targeted advertising based on user data, a model that drove its rapid financial growth. In 2012, Facebook went public with one of the largest IPOs in tech history. Acquisitions played a significant role in Facebook's dominance. In 2012, it purchased Instagram, followed by WhatsApp and Oculus VR in 2014, extending its influence beyond social networking into messaging and virtual reality. The Facebook–Cambridge Analytica data scandal in 2018 revealed misuse of user data to influence elections, sparking global outcry and leading to regulatory fines and hearings. Facebook's role in global events, including its use in organizing movements like the Arab Spring and its impact on events like the Rohingya genocide in Myanmar, highlighted its dual nature as a tool for both empowerment and harm. In 2021, Facebook rebranded as Meta, reflecting its shift toward building the "metaverse" and focusing on virtual reality and augmented reality technologies. == Features == Facebook does not officially publish a maximum character limit for posts; however, user posts can be lengthy, with unofficial sources suggesting a high character limit. Posts may also include images and videos. According to Facebook's official business documentation, videos can be up to 240 minutes long and 10 GB in file size, with supported resolutions up to 1080p. Users can "friend" users, both sides must agree to being friends. Posts can be changed to be seen by everyone (public), friends, people in a certain group (group) or by selected friends (private). Users can join groups. Groups are composed of persons with shared interests. For example, they might go to the same sporting club, live in the same suburb, have the same breed of pet or share a hobby. Posts posted in a group can be seen only by those in a group, unless set to public. Users are able to buy, sell, and swap things on Facebook Marketplace or in a Buy, Swap and Sell group. Facebook users may advertise events, which can be offline, on a website other than Facebook, or on Facebook. == Website == === Technical aspects === The site's primary color is blue as Zuckerberg is red–green colorblind, a realization that occurred after a test taken around 2007. Facebook was initially built using PHP, a popular scripting language designed for web development. PHP was used to create dynamic content and manage data on the server side of the Facebook application. Zuckerberg and co-founders chose PHP for its simplicity and ease of use, which allowed them to quickly develop and deploy the initial version of Facebook. As Facebook grew in user base and functionality, the company encountered scalability and performance challenges with PHP. In response, Facebook engineers developed tools and technologies to optimize PHP performance. One of the most significant was the creation of the HipHop Virtual Machine (HHVM). This significantly improved the performance and efficiency of PHP code execution on Facebook's servers. The site upgraded from HTTP to the more secure HTTPS in January 2011. ==== 2012 architecture ==== Facebook is developed as one monolithic application. According to an interview in 2012 with Facebook build engineer Chuck Rossi, Facebook compiles into a 1.5 GB binary blob which is then distributed to the servers using a custom BitTorrent-based release system. Rossi stated that it takes about 15 minutes to build and 15 minutes to release to the servers. The build and release process has zero downtime. Changes to Facebook are rolled out daily. Facebook used a combination platform based on HBase to store data across distributed machines. Using a tailing architecture, events are stored in log files, and the logs are tailed. The system rolls these events up and writes them to storage. The user interface then pulls the data out and displays it to users. Facebook handles requests as AJAX behavior. These requests are written to a log file using Scribe (developed by Facebook). Data is read from these log files using Ptail, an internally built tool to aggregate data from multiple Scribe stores. It tails the log files and pulls data out. Ptail data are separated into three streams and sent to clusters in different data centers (Plugin impression, News feed impressions, Actions (plugin + news feed)). Puma is used to manage periods of high data
Relational data mining
Relational data mining is the data mining technique for relational databases. Unlike traditional data mining algorithms, which look for patterns in a single table (propositional patterns), relational data mining algorithms look for patterns among multiple tables (relational patterns). For most types of propositional patterns, there are corresponding relational patterns. For example, there are relational classification rules (relational classification), relational regression tree, and relational association rules. There are several approaches to relational data mining: Inductive Logic Programming (ILP) Statistical Relational Learning (SRL) Graph Mining Propositionalization Multi-view learning == Algorithms == Multi-Relation Association Rules: Multi-Relation Association Rules (MRAR) is a new class of association rules which in contrast to primitive, simple and even multi-relational association rules (that are usually extracted from multi-relational databases), each rule item consists of one entity but several relations. These relations indicate indirect relationship between the entities. Consider the following MRAR where the first item consists of three relations live in, nearby and humid: “Those who live in a place which is near by a city with humid climate type and also are younger than 20 -> their health condition is good”. Such association rules are extractable from RDBMS data or semantic web data. == Software == Safarii: a Data Mining environment for analysing large relational databases based on a multi-relational data mining engine. Dataconda: a software, free for research and teaching purposes, that helps mining relational databases without the use of SQL. == Datasets == Relational dataset repository: a collection of publicly available relational datasets.
Infone
Infone was a service launched by Metro One Telecommunications in 2003. The service was discontinued effective December 14, 2005. == How it worked == Infone included directory assistance and other services via a toll-free phone number. A user could call 888-411-1111 to request directory assistance, directions, traffic information, movie times, call completion, dinner reservation assistance and other services. Infone provided a number of innovative 411 'concierge'-like services, including movie listings from a live operator, and offered a feature where they could provide information from a linked Microsoft Outlook calendar when set up in advance. For a period of time they advertised heavily on U.S. television, featuring ads with then Governor of Minnesota Jesse Ventura, emphasizing their use of all U.S. based operators. The price offered was $0.89 per call up to 15 minutes (for use when the operator connects you to the requested number, as well as for additional information requests afterwards), with $0.05 for each additional minute, making Infone also a competitively priced long-distance service. New users received 5–10 free calls. Infone identified a registered user (along with billing information; the service was only payable by credit card) by caller ID (numbers were registered on signing up) and by an advanced voiceprint recognition system (VPRS) from SpeechWorks that identified the user when the user called from an unregistered telephone number (or no caller ID) through the use of a personal phrase spoken by the user (e.g., "Hello Infone!") after the welcome tone.