AI Coding Kiro

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

Avid Free DV

Avid Free DV is a non-linear editing video editing software application developed by Avid Technology. Avid introduced Free DV in January 2003 at the 2003 MacWorld Expo; the company discontinued it in September 2007. Free DV was intended to give editors a sample of the Avid interface to use in deciding whether or not to purchase Avid software, so when compared with other Avid products its features were relatively minimal. When it was available it was not limited by time or watermarking, so it could be used as a non-linear editor for as long as desired. == Comparisons == When compared with other consumer-end non-linear editors such as iMovie and Windows Movie Maker, it sported more powerful video processing tools, but lacked the ease-of-use and shallow learning curve emphasized in similar programs because it had the full interface of the professional Avid system. However, Avid did offer a number of flash-based tutorials to help new users learn how to use the program for capturing, editing, clipping, processing, and outputting audio/video, among other things. == Limitations == The limitations of Avid Free DV included that it allowed only two video and audio tracks, had fewer editing tools than other Avid products, had few import and export formats, and allowed capture and output of standard-definition DV only, via FireWire. Avid Free DV projects and media were not compatible with other Avid systems. As the name implied, Avid Free DV was available as a free download, although users were required to complete a short survey on the Avid website before they were given a download link and key. In addition to using Free DV to evaluate Avid prior to purchase, it could also act as a stepping stone for people wishing to learn to use Avid's other editing products, such as Xpress Pro, Media Composer and Symphony. While additional skills and techniques are necessary to use these professionally geared systems, the basic operation remains the same. == Operating systems == Avid Free DV was available for Windows XP and Mac OS X. The officially supported Mac OS X versions were Panther versions up to 10.3.5, and Tiger versions up to 10.4.3 only. == Supported formats == Avid Free DV supported QuickTime (MOV) and DV AVIs. == Reception == John P. Mello Jr. of The Boston Globe gave Free DV a negative review, finding the user interface obfuscatory and the process of ingesting video error-prone. He summarized: "Professional video editors who use an Avid competitor may jump at the chance to take a free look at how Avid does things. But for the merely curious, this software is a nightmare". Video Systems's Steve Mullen opined that its lack of interoperability with Avid's professional editing software contracted Avid's stated goal to entice budding video editors into buying into the company's software ecosystem.
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Media Auxiliary Memory

Media Auxiliary Memory or Medium Auxiliary Memory (MAM) refers to a chip embedded into a digital media device (usually a tape cartridge) that stores a small amount of data or metadata that a computer can read without having to read the actual tape. MAMs can be used by the tape driver to increase efficiency, or by custom software to store & retrieve custom data. Some examples of MAM's are Cartridge Memory (HP/Seagate/IBM LTO) and MIC (Sony AIT).
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Event cinema

Event cinema sometimes called alternative content cinema or livecasts refers to the use of movie theaters to display a varied range of live and recorded entertainment excluding traditional films, such as sport, opera, musicals, ballet, music, one-off TV specials, current affairs, comedy and religious services. == History and development == Event Cinema was set up at the start of the century with rock concerts by Bon Jovi (2001), David Bowie (2003), and Robbie Williams (2005) bringing non-film audiences into cinemas that had newly installed digital equipment. The Metropolitan Opera in New York through their partnership with Fathom Events is acknowledged as the trailblazer in this area, aggressively seeking out new markets and setting high standards for live broadcasts via satellite. Emulated by other opera houses worldwide such as the Royal Opera House following a close second, Glyndebourne, La Scala and the Sydney Opera House the genre of opera within the 'Event Cinema' industry has been a huge success, and has brought new, younger audiences into cash-strapped opera houses depended on state funding and wealthy benefactors for the first time - an unforeseen and happy consequence of digitisation. Ballet and theater have also been very successful, as have rock concerts, both live and recorded. The UK's National Theatre has been a huge success here with their season of live broadcasts under the banner 'NT Live', featuring big name casts such as Helen Mirren, whose recent turn as Queen Elizabeth II in The Audience was a sell out everywhere. (This was in partnership with another West End theatre and the NT are keen to help other theatres maximise their potential through live broadcasts). The Globe and the Royal Shakespeare Company are also producing work for live broadcast and recorded exhibition. As digitisation of cinemas matures, the Event Cinema industry is growing. The strongest territory is the US, followed by the UK and mainland European territories. Latin America is also a very strong market. Recent additions include Pompeii Live, a unique exhibition by the UK's British Museum, featuring celebrities and curators taking the audience on a live tour around the recreated set of Pompeii within the museum itself, and they are also exploring the schools market for the first time, following the live broadcast on June 18 with a daytime broadcast aimed at UK schools for the first time. If successful this will no doubt prove a model for future museums to emulate. An added incentive for exhibitors is the ability to show alternative content, i.e. alternative to mainstream, studio-driven content, such as live special events, sports, pre-show advertising and other digital or video content. In industry terms this has become known as 'Alternative Content', but has recently become known more widely as 'Event Cinema'. === Expanding markets === Some low-budget films that would normally not have a theatrical release because of distribution costs might be shown in smaller engagements than the typical large release studio pictures. The cost of duplicating a digital "print" is very low, so adding more theaters to a release has a small additional cost to the distributor. Movies that start with a small release could scale to a much larger release quickly if they were sufficiently successful, opening up the possibility that smaller movies could achieve box office success previously out of their reach. ==== Technical specifications ==== Event Cinema is also finding a market in 3rd world countries in which the higher costs and quality of DCI equipment are not yet affordable, as crucially there are no DCI specifications for Alternative Content as there is in mainstream [studio] content. This has led to an explosion in the variety of content on offer, but a lack of standardisation has led to questionable quality at times. As the industry matures, this lack of regulation is expected to change and there are moves afoot to introduce codes of practice and technical specifications. Recorded content complements mainstream studio content by maximising the 'downtime' that plagues the cinema industry, where screens worldwide spend a large proportion of their time in darkness and cinemas empty. Some cinema chains have targeted pensioners in particular, offering free tea and coffee for afternoon matinees of recorded opera, for example. Digital Cinema Packages (DCPs) have been useful to cinemas not yet equipped with satellite broadcasting capability and has enabled exhibitors to build their Event Cinema audience, which is not generally the 18-24 demographic that multiplexes are targeting. ==== New Audiences ==== Event Cinema has seen a return of an older, affluent audience, previously turned off by the multiplex experience, and cinemas are starting to capitalise on this by offering waiter-serviced, high class finger food and alcoholic beverages, complete with bars and restaurants, a world away from the traditional popcorn/soft drink model; art house cinemas are increasingly marketing themselves as 'destination' venues for an evening's entertainment, somewhere to spend an entire evening, rather than just a couple of hours. As exhibition admissions have plateau'd in recent years due to the explosion in VOD, tablet and mobile content technology, this new revenue stream has been a surprise and welcome addition to the cinema industry, though the US studios have been cautious in embracing the change as yet. The thrill of Live broadcasts means they are generally regarded as more popular than recorded events, but there are exceptions; artists with a loyal cult or teenage following tend to do particularly well in this area, as concert films featuring artists such as the Grateful Dead, Pearl Jam, JLS, Led Zeppelin and the Rolling Stones have shown. ==== The Future ==== As more and more distributors are emerging, offering an increasingly broad range of content to cinemas worldwide, the landscape itself is shifting: screen advertising companies, technical providers, and exhibitors themselves are reinventing themselves as Alternative Content or Event Cinema distributors, and the industry is witnessing a re-evaluation of business models and practices worldwide. Predictions are that this industry could be work in excess of US$1bn by 2015. An illustration of the growth of this industry is the news the establishment of a European trade association promoting the industry to the general public and supporting those involved in it and the Event Cinema Association.
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Digital data

Digital data or digital information, in information theory and information systems, is data or information represented as a string of discrete symbols, each of which can take on one of only a finite number of values from some alphabet, such as letters or digits. An example is a text document, which consists of a string of alphanumeric characters. The most common form of digital data in modern information systems is binary data, which is represented by a string of binary digits (bits) each of which can have one of two values, either 0 or 1. Digital data can be contrasted with analog data, which is represented by a value from a continuous range of real numbers. Analog data is transmitted by an analog signal, which not only takes on continuous values but can vary continuously with time, a continuous real-valued function of time. An example is the air pressure variation in a sound wave. Data requires interpretation to become information. In modern (post-1960) computer systems, all data is digital. The word digital comes from the same source as the words digit and digitus (the Latin word for finger), as fingers are often used for counting. Mathematician George Stibitz of Bell Telephone Laboratories used the word digital in reference to the fast electric pulses emitted by a device designed to aim and fire anti-aircraft guns in 1942. The term is most commonly used in computing and electronics, especially where real-world information is converted to binary numeric form as in digital audio and digital photography. == Symbol to digital conversion == Since symbols (for example, alphanumeric characters) are not continuous, representing symbols digitally is rather simpler than conversion of continuous or analog information to digital. Instead of sampling and quantization as in analog-to-digital conversion, such techniques as polling and encoding are used. A symbol input device usually consists of a group of switches that are polled at regular intervals to see which switches are switched. Data will be lost if, within a single polling interval, two switches are pressed, or a switch is pressed, released, and pressed again. This polling can be done by a specialized processor in the device to prevent burdening the main CPU. When a new symbol has been entered, the device typically sends an interrupt, in a specialized format, so that the CPU can read it. For devices with only a few switches (such as the buttons on a joystick), the status of each can be encoded as bits (usually 0 for released and 1 for pressed) in a single word. This is useful when combinations of key presses are meaningful, and is sometimes used for passing the status of modifier keys on a keyboard (such as shift and control). But it does not scale to support more keys than the number of bits in a single byte or word. Devices with many switches (such as a computer keyboard) usually arrange these switches in a scan matrix, with the individual switches on the intersections of x and y lines. When a switch is pressed, it connects the corresponding x and y lines together. Polling (often called scanning in this case) is done by activating each x line in sequence and detecting which y lines then have a signal, thus which keys are pressed. When the keyboard processor detects that a key has changed state, it sends a signal to the CPU indicating the scan code of the key and its new state. The symbol is then encoded or converted into a number based on the status of modifier keys and the desired character encoding. A custom encoding can be used for a specific application with no loss of data. However, using a standard encoding such as ASCII is problematic if a symbol such as 'ß' needs to be converted but is not in the standard. It is estimated that in the year 1986, less than 1% of the world's technological capacity to store information was digital and in 2007 it was already 94%. The year 2002 is assumed to be the year when humankind was able to store more information in digital than in analog format (the "beginning of the digital age"). == States == Digital data come in these three states: data at rest, data in transit, and data in use. The confidentiality, integrity, and availability have to be managed during the entire lifecycle from 'birth' to the destruction of the data. === Data at rest === Data at rest in information technology means data that is housed physically on computer data storage in any digital form (e.g. cloud storage, file hosting services, databases, data warehouses, spreadsheets, archives, tapes, off-site or cloud backups, mobile devices etc.). Data at rest includes both structured and unstructured data. This type of data is subject to threats from hackers and other malicious threats to gain access to the data digitally or physical theft of the data storage media. To prevent this data from being accessed, modified or stolen, organizations will often employ security protection measures such as password protection, data encryption, or a combination of both. The security options used for this type of data are broadly referred to as data-at-rest protection (DARP). Definitions include: "...all data in computer storage while excluding data that is traversing a network or temporarily residing in computer memory to be read or updated." "...all data in storage but excludes any data that frequently traverses the network or that which resides in temporary memory. Data at rest includes but is not limited to archived data, data which is not accessed or changed frequently, files stored on hard drives, USB thumb drives, files stored on backup tape and disks, and also files stored off-site or on a storage area network (SAN)." While it is generally accepted that archive data (i.e. which never changes), regardless of its storage medium, is data at rest and active data subject to constant or frequent change is data in use. “Inactive data” could be taken to mean data which may change, but infrequently. The imprecise nature of terms such as “constant” and “frequent” means that some stored data cannot be comprehensively defined as either data at rest or in use. These definitions could be taken to assume that Data at Rest is a superset of data in use; however, data in use, subject to frequent change, has distinct processing requirements from data at rest, whether completely static or subject to occasional change. ==== Security ==== Because of its nature data at rest is of increasing concern to businesses, government agencies and other institutions. Mobile devices are often subject to specific security protocols to protect data at rest from unauthorized access when lost or stolen and there is an increasing recognition that database management systems and file servers should also be considered as at risk; the longer data is left unused in storage, the more likely it might be retrieved by unauthorized individuals outside the network. Data encryption, which prevents data visibility in the event of its unauthorized access or theft, is commonly used to protect data in motion and increasingly promoted for protecting data at rest. The encryption of data at rest should only include strong encryption methods such as AES or RSA. Encrypted data should remain encrypted when access controls such as usernames and password fail. Increasing encryption on multiple levels is recommended. Cryptography can be implemented on the database housing the data and on the physical storage where the databases are stored. Data encryption keys should be updated on a regular basis. Encryption keys should be stored separately from the data. Encryption also enables crypto-shredding at the end of the data or hardware lifecycle. Periodic auditing of sensitive data should be part of policy and should occur on scheduled occurrences. Finally, only store the minimum possible amount of sensitive data. Tokenization is a non-mathematical approach to protecting data at rest that replaces sensitive data with non-sensitive substitutes, referred to as tokens, which have no extrinsic or exploitable meaning or value. This process does not alter the type or length of data, which means it can be processed by legacy systems such as databases that may be sensitive to data length and type. Tokens require significantly less computational resources to process and less storage space in databases than traditionally encrypted data. This is achieved by keeping specific data fully or partially visible for processing and analytics while sensitive information is kept hidden. Lower processing and storage requirements makes tokenization an ideal method of securing data at rest in systems that manage large volumes of data. A further method of preventing unwanted access to data at rest is the use of data federation especially when data is distributed globally (e.g. in off-shore archives). An example of this would be a European organisation which stores its archived data off-site in the US. Under the terms of the USA PATRIOT Act the American authorities can demand
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Artificial intelligence in fraud detection

Artificial intelligence is used by many different businesses and organizations. It is widely used in the financial sector, especially by accounting firms, to help detect fraud. In 2022, PricewaterhouseCoopers reported that fraud has impacted 46% of all businesses in the world. The shift from working in person to working from home has brought increased access to data. According to an FTC (Federal Trade Commission) study from 2022, customers reported fraud of approximately $5.8 billion in 2021, an increase of 70% from the year before. The majority of these scams were imposter scams and online shopping frauds. Furthermore, artificial intelligence plays a crucial role in developing advanced algorithms and machine learning models that enhance fraud detection systems, enabling businesses to stay ahead of evolving fraudulent tactics in an increasingly digital landscape. == Tools == === Expert systems === Expert systems were first designed in the 1970s as an expansion into artificial intelligence technologies. Their design is based on the premise of decreasing potential user error in decision-making and emulating mental reasoning used by experts in a particular field. They differentiate themselves from traditional linear reasoning models by separating identified points in data and processing them individually at the same time. Though, these systems do not rely purely on machine-learned intelligence. Information regarding rules, practices, and procedures in the form of "if-then" statements are implemented into the programming of the system. Users interact with the system by feeding information into the system either through direct entry or import of external data. An inference system compares the information provided by the user with corresponding rules that are believed to specifically apply to the situation. Using this information and the corresponding rules will be used to create a solution to the user's query. Expert systems will generally not operate properly when the common procedures for a specified situation are ambiguous due to the need for well-defined rules. Implementation of expert systems in accounting procedures is feasible in areas where professional judgment is required. Situations where expert systems are applicable include investigations into transactions that involve potential fraudulent entries, instances of going concern, and the evaluation of risk in the planning stages of an audit. === Continuous auditing === Continuous auditing is a set of processes that assess various aspects of information gathered in an audit to classify areas of risk and potential weaknesses in financial Internal controls at a more frequent rate than traditional methods. Instead of analyzing recorded transactions and journal entries periodically, continuous auditing focuses on interpreting the character of these actions more frequently. The frequency of these processes being undertaken as well as highlighting areas of importance is up to the discretion of their implementer, who commonly makes such decisions based on the level of risk in the accounts being evaluated and the goals of implementing the system. Performance of these processes can occur as frequently as being nearly instantaneous with an entry being posted. The processes involved with analyzing financial data in continuous auditing can include the creation of spreadsheets to allow for interactive information gathering, calculation of financial ratios for comparison with previously created models, and detection of errors in entered figures. A primary goal of this practice is to allow for quicker and easier detection of instances of faulty controls, errors, and instances of fraud. === Machine learning and deep learning === The ability of machine learning and deep learning to swiftly and effectively sort through vast volumes of data in the forms of various documents relevant to companies and documents being audited makes them applicable to the domains of audit and fraud detection. Examples of this include recognizing key language in contracts, identifying levels of risk of fraud in transactions, and assessing journal entries for misstatement. == Applications == === 'Big 4' Accounting Firms === Deloitte created an Al-enabled document-reviewing system in 2014. The system automates the method of reviewing and extracting relevant information from different business documents. Deloitte claims that this innovation has made a difference by reducing time spent going through lawful contract documents, invoices, money-related articulations, and board minutes by up to 50%. Working with IBM's Watson, Deloitte is developing cognitive-technology-enhanced commerce arrangements for its clients. LeasePoint is fueled by IBM TRIRIGA (this product evolved into IBM Maximo Real Estate and Facilities) and uses Deloitte's industrial information to create an end-to-end leasing portfolio. Automated Cognitive Resource Assessment employs IBM's Maximo innovation to progress the proficiency of asset inspection. Ernst and Young (EY) connected Al to the investigation of lease contracts. EY (Australia) has also received Al-enabled auditing technology. Collaborating with H20.ai, PwC developed an Al-enabled framework (GL.ai) capable of analyzing reports and preparing reports. PwC claims to have made a significant investment in normal dialect processing (NLP), an Al-enabled innovation to process unstructured information efficiently. KPMG built a portfolio of Al instruments, called KPMG Ignite, to upgrade trade decisions and forms. Working with Microsoft and IBM Watson, KPMG is creating instruments to coordinate Al, data analytics, Cognitive Technologies, and RPA. == Advantages == === Efficiency === The process of auditing an entity in an attempt to detect fraudulent activity requires the repeating of investigatory processes until an error or misstatement may be identified. Under traditional methods, these processes would be carried out by a human being. Proponents of artificial intelligence in fraud detection have stated that these traditional methods are inefficient and can be more quickly accomplished with the aid of an intelligent computing system. A survey of 400 chief executive officers created by KPMG in 2016 found that approximately 58% believed that artificial intelligence would play a key role in making audits more efficient in the future. === Data interpretation === Higher levels of fraud detection entail the use of professional judgement to interpret data. Supporters of artificial intelligence being used in financial audits have claimed that increased risks from instances of higher data interpretation can be minimized through such technologies. One necessary element of an audit of financial statements that requires professional judgement is the implementation of thresholds for materiality. Materiality entails the distinction between errors and transactions in financial statements that would impact decisions made by users of those financial statements. The threshold for materiality in an audit is set by the auditor based on various factors. Artificial intelligence has been used to interpret data and suggest materiality thresholds to be implemented through the use of expert systems. === Decreased costs === Those in favor of using artificial intelligence to complete investigations of fraud have stated that such technologies decrease the amount of time required to complete tasks that are repetitive. The claim further states that such efficiencies allow for lowered resource requirements, which can then be further spent on tasks that have not been fully automated. The audit firm Ernst & Young has posited these claims by declaring that their deep learning systems have been used to reduce time spent on administrative tasks by analyzing relevant audit documents. According to the firm, this has allowed their employees to focus more on judgement and analysis. == Disadvantages == === Job Displacement === The inescapable reception of computer based intelligence and robotization advancements might prompt critical work relocation across different enterprises. As artificial intelligence frameworks become more equipped for performing undertakings customarily completed by people, there is a worry that specific work jobs could become out of date, prompting joblessness and financial imbalance. === Initial investment requirement === Along with a knowledge of coding and building systems through computer programs, we are seeing the advantages of these systems, but since they are so new, they require a large investment to start building such a system. Any firm that is planning on implementing an AI system to detect fraud must hire a team of data scientists, along with upgrading their cloud system and data storage. The system must be consistently monitored and updated to be the most efficient form of itself, otherwise the likelihood of fraud being involved in those transactions increases. If one does not initially invest in such a syst
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False answer supervision

False answer supervision (FAS) refers to VoIP fraud where the billed duration for the caller is more than the duration of the actual connection duration. The FAS is usually performed by VoIP wholesalers in their softswitches for randomly selected calls. Adding a small amount of extra billed seconds for many calls results in significant revenue for the VoIP wholesaler. == Implementation of FAS == The FAS fraud can be implemented in a softswitch in many different ways. These include: False billing of party A without calling a party B. Usually a fake ringback tone, loopback audio or voicemail message is played Start of billing before actual answer of party B Extra billing after disconnection of party B == Detection of FAS == The FAS can be detected and blocked in a softswitch. Common methods are: Manual verification of call detail records: listening to voice recordings Identification of FAS types and using algorithms to automatically detect the FAS RTP audio signal processing: detection of voice RTP audio signal processing: detection of silence RTP audio signal processing: detection of ringback tone
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InteLex Past Masters

InteLex Past Masters is a collection of full-text web-based scholarly editions of classic works in the humanities. InteLex Corporation was founded in 1989 by its current chief executive officer, Mark Rooks, to produce electronic versions of the works of the great philosophers, based on existing scholarly editions. The company is located in Charlottesville, Virginia. Its databases are marketed to academic institutions, with pricing based on the individual collections purchased. Content is provided in XML and searchable image format and is accessed through the InteLex Corporation website. In addition to philosophy, subject coverage includes religious studies, English literature, women's writing, social science, and history of science. InteLex databases are found in institutions in over 65 countries around the world.
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Digital goods

Digital goods or e-goods are intangible goods that exist in digital form. Examples are Wikipedia articles; digital media, such as e-books, downloadable music, internet radio, internet television and streaming media; fonts, logos, photos and graphics; digital subscriptions; online ads (as purchased by the advertiser); internet coupons; electronic tickets; electronically treated documentation in many different fields; downloadable software (Digital Distribution) and mobile apps; cloud-based applications and online games; virtual goods used within the virtual economies of online games and communities; community access; workbooks; worksheets; planners; e-learning (online courses); webinars, video tutorials, blog posts; cards; patterns; website themes and templates. == Legal concerns about digital goods == Special legal concerns regarding digital goods include copyright infringement and taxation. Also the question of the ownership (versus licensed use or service only) of purely digital goods is not finally resolved. For instance, the software installers of the digital software distributor gog.com are technically independent to the account but are still subject to the EULA, where a "licensed, not sold" formulation is used. Therefore, it is not clear if the software can be legally used after a hypothetical loss of the account; a question which was also raised before in practice for the similar service Steam. In July 2012, the European Court of Justice ruled in the case UsedSoft GMbH v. Oracle International Corp. that the sale of a software product, either through a physical support or download, constituted a transfer of ownership in EU law, thus the first sale doctrine applies; the ruling thereby breaks the "licensed, not sold" legal theory, but leaves open numerous questions. Therefore, it is also permissible to resell software licenses even if the digital good has been downloaded directly from the Internet, as the first-sale doctrine applied whenever software was originally sold to a customer for an unlimited amount of time, thus prohibiting any software maker from preventing the resale of their software by any of their legitimate owners. The court requires that the previous owner must no longer be able to use the licensed software after the resale, but finds that the practical difficulties in enforcing this clause should not be an obstacle to authorizing resale, as they are also present for software which can be installed from physical supports, where the first-sale doctrine is in force. In several cases, content providers have faced criticism for revoking access to digital goods due to expired licenses or the discontinuation of a product, such as ebooks (which resulted in a lawsuit against Amazon.com, Inc.), digital video (with Sony Interactive Entertainment revoking access to purchased StudioCanal content from its now-defunct PlayStation video store; a similar move involving Warner Bros. Discovery content was averted by an updated license agreement), and video games (such as Ubisoft discontinuing and revoking access to its game The Crew without providing refunds or the ability to redownload the game) In September 2024, the U.S. state of California implemented a consumer protection law that prohibits the use of terms such as "buy" or "purchase" during transactions involving digital goods if there is no way to obtain the purchases in a manner that cannot be revoked by the seller (such as allowing it to be downloaded for permanent, offline access), and requires a disclaimer to be displayed to the customer at the time of purchase.
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Zolostays

Zolostays is a real-tech co-living focused startup that provides ready-to-move rooms/beds. It was founded in 2015 by Nikhil Sikri, Akhil Sikri and Sneha Choudhry. == Overview == During the pandemic, Zolo provided 75 of rent-free accommodation to those who lost their jobs. Zolo uses bulk inventory in usually residential township and ties up with real estate companies to make the rooms/beds available. Zolostays has both revenue sharing and leased model. == History == Zolostays was founded in 2015 to solve the problem of students and young professionals who would move to temporarily go to other cities to study and work and look for affordable housing. In 2020, it was operating in 10 Indian cities. It has four round of funding, with total $98 million.
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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.
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Webedia

Webedia S.A. is a company specializing in online media, a subsidiary of the Fimalac group based in Levallois-Perret, France. Webedia is active in more than twenty countries including France (AlloCiné, Jeuxvideo.com, MGG, Puremédias, Ode, Pureshopping, Volum, Terrafemina, 750g, easyVoyage, l’Automobile Magazine, Le 10 Sport), Brazil (AdoroCinema, Tudo Gostoso, Minhavida), Germany (Filmstarts, Moviepilot, GameStar), Spain and Latin America (Xataka, SensaCine, Raiser Games), Poland (Gry-Online and GetHero) and the United States (Boxoffice Pro). == History == === Early years (2007-2013) === Webedia was created in France in 2007, following the successive launches of the websites Purepeople, Puretrend and Purefans. Webedia bought the comparison shopping website Shopoon in 2008 and renamed it Pureshopping, and the website Ozap (media news) from M6 group in 2011 and renamed it Puremédias. Webedia was acquired by Fimalac in May 2013 and became its Internet media subsidiary. === Growth (2013-2016) === In 2013, Fimalac acquired AlloCiné, the websites Newsring and Youmag, the cooking website 750g and the cultural platform Exponaute. In 2014, Webedia acquired OverBlog, Jeuxvideo.com (through L'Odyssée Interactive and moved to Paris in 2015), Moviepilot (Germany), and Gameo Consulting (owner of Millenium, electronic sports), In December 2014, Webedia announced a license agreement with Ziff Davis to launch sites under the IGN franchise in Brazil and France at the beginning of 2015. The French version of IGN was launched on 2, it targets the general public and casual gamers. In 2015, Webedia acquired Côté Ciné Group (technological solutions for movie theaters and specialized press magazines: BoxOffice Pro in the United States and Côté Ciné in France), 57% of Easyvoyage group (online travel comparators Easyvol and Alibabuy, Mixicom (website JeuxActu and multi-channel network), 50% of the Brazilian network Paramaker, and West World Media (digital marketing company for the film industry). In 2016, Webedia bought Scimob (mobile video game studio), Surprizemi (home-delivered surprise boxes), Eklablog (blogging platform) Oxent (eSports World Convention), and Bang Bang Management (sports PR agency). In addition, an agreement is made with Paris Saint-Germain for Webedia to recruit and manage e-sports players on behalf of Paris Saint-Germain eSports. On November 15, 2016, the LFP announced that it had reached an agreement with beIN Sports and Webedia for the broadcasting of the first edition of the e-League 1. The competition is renewed for two additional seasons on July 26, 2017, the broadcasting agreements are renewed. On December 8, 2016, Webedia joined forces with Chronopost to launch Pourdebon, a home delivery service that connects Internet users and labeled producers (AOC, organic AB, etc.). Webedia has a slight majority (53%) in this new platform. === 2017 === On January 19, 2017, Webedia announced the acquisition of the English company Peach Digital, specializing in web development and digital marketing for movie theaters. In February 2017, Le Figaro announced that Webedia had invested 10 million euros in Illico Fresco, a home delivery service for baskets of recipes. The same month, FDJ and Webedia announced a partnership for the creation of eSports competitions: a professional one (FDJ Masters League) and another one for amateur gamers (FDJ Open Series) starting in March 2017. They are broadcast on Webedia's Web TV. At the end of February 2017, the media group finalized the acquisition of MyPoseo, a SaaS publisher specialized on SEO analytics. On March 8, 2017, Webedia launched LeStream, a Twitch Web TV dedicated to video games, the result of two years of development, in the company of several YouTubers including Cyprien and Squeezie,. On March 29, 2017, Webedia bought the Brazilian web publisher Minha Vida, a website devoted to health, nutrition, beauty and fitness, which attracts 14.3 million unique monthly visitors. Webedia reaches 44 million unique visitors in Brazil, and thus becomes the leading publisher on entertainment themes. In June 2017, the company made its largest international acquisition, with the American agency 3BlackDot, a media and marketing agency focused on videogamers. The agency, based in Los Angeles, manages 36 YouTubers followed by millions of subscribers on their channels which total 700 million videos viewed per month. In July 2017, Webedia bought IDZ, an audiovisual production company, and thus strengthened its production activities and its leadership on the YouTube channel networks in France. That year, Webedia was the first French media group to use the measurement of their global audiences by Comscore. It represents deduplicated coverage on desktops, laptops, smartphones and tablets, and includes audiences for websites, mobile applications and videos. This new measure allows Webedia to establish a deduplicated global audience of 177 million unique visitors in April 2017. In October 2017, Webedia announced its intention to launch a TV channel dedicated to electronic sports, called ES1. The channel was officially launched on January 10, 2018, on Orange TV and on February 6, 2018, on Free and Bouygues Telecom. In November 2017, Webedia, with the support of CDC International Capital, entered into exclusive negotiations with the Saudi company Uturn Entertainment, specializing in online entertainment, particularly on YouTube, and the production of digital content for the region's youth, with a view to merging it with Diwanee, a Webedia subsidiary in the Middle East, for an amount close to $100 million. In December 2017, Webedia acquired a majority stake in the United States–based company called Creators Media, which brings together social and video production platforms specializing in popular culture and entertainment. That same month, Webedia joined forces with Elephant, Emmanuel Chain's audiovisual production company, to create a new content production label aimed at Millennials. === 2018-2019 === In January 2018, Webedia launched a sports marketing agency: Only Sports & Passions. That same month, Illico Fresco, specialist in the delivery of kit meals belonging to Webedia, joined forces with Weight Watchers, the world leader in slimming products. In April 2018, Webedia published new audience figures in partnership with Comscore, 188 million unique monthly visitors in December 2017, an increase of 6.2% compared to the previous measure dating from April 2017. The same month, Webedia unveils its ambitions concerning content production, as a partnership with the video game studio Focus Home Interactive is signed with a title "Fear the Wolves" already planned for 2018, co-production projects of films, cartoons or series are announced. In July 2018, Webedia bought the American authors company Full Fathom Five, a company that helps authors produce books, TV series, films and video games. In October 2018, Webedia announced that it was focusing on both esports clubs PSG Esports and LeStream Esport. The first one being geared towards international competitions and the second devoted mainly to the French esports scene. The "Millenium" brand is thus refocusing around its media activities and esports merchandising products, and the "Millenium esport club" being gradually closed. The same month, the company announced the acquisition of Weblogs, a Spanish-speaking website publisher, thereby strengthening its activity in Spain and Latin America. On October 22, 2018, Webedia announced the merger of BoxOffice magazine with Film Journal International. On November 13, 2018, Groupe SEB announced the acquisition from Webedia of 750g International, the international branch of the French recipe site 750g (the original French website 750g.com being retained by Webedia). The group is thus separating from Gourmandize (United States and United Kingdom), HeimGourmet (Germany), Rebañando (Spain), Receitas Sem Fronteiras (Brazil / Portugal) and Tribù Golosa (Italy). The same month, Webedia joined forces with Riot Games to launch the French League of League of Legends (LFL), the first French professional league on the League of Legends game, which will bring together the 8 best teams on the French scene. In March 2019, Webedia bought 51% of the audiovisual production company Elephant. The new set will weigh 500 million euros, a quarter of which will be made outside France. The same month, Webedia purchased a majority stake in the company Partoo, which publishes a SaaS platform specializing in local marketing for brands and merchants. On March 14, 2019, a new measurement of the international audience of Webedia sites was produced by Comscore, posting 250 million unique visitors in December 2018, up 9.2% compared to December 2017. In June 2019, the group joined forces with Michel Cymes, a famous doctor and French TV host by taking a majority stake in his company Club Santé Débat, in order to develop a health platform around the Dr. Good! Brand. In Sep
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Open Rights Group

The Open Rights Group (ORG) is a UK-based organisation that works to preserve digital rights and freedoms by campaigning on digital rights issues and by fostering a community of grassroots activists. It campaigns on numerous issues including mass surveillance, internet filtering and censorship, and intellectual property rights. == History == The organisation was started by Danny O'Brien, Cory Doctorow, Ian Brown, Rufus Pollock, James Cronin, Stefan Magdalinski, Louise Ferguson and Suw Charman after a panel discussion at Open Tech 2005. O'Brien created a pledge on PledgeBank, placed on 23 July 2005, with a deadline of 25 December 2005: "I will create a standing order of 5 pounds per month to support an organisation that will campaign for digital rights in the UK but only if 1,000 other people will too." The pledge reached 1000 people on 29 November 2005. The Open Rights Group was launched at a "sell-out" meeting in Soho, London. == Work == The group has made submissions to the All Party Internet Group (APIG) inquiry into digital rights management and the Gowers Review of Intellectual Property. The group was honoured in the 2008 Privacy International Big Brother Awards alongside No2ID, Liberty, Genewatch UK and others, as a recognition of their efforts to keep state and corporate mass surveillance at bay. In 2010 the group worked with 38 Degrees to oppose the introduction of the Digital Economy Act, which was passed in April 2010. The group opposes measures in the draft Online Safety Bill introduced in 2021, that it sees as infringing free speech rights and online anonymity. The group campaigns against the Department for Digital, Culture, Media and Sport's plan to switch to an opt-out model for cookies. The group spokesperson stated that "[t]he UK government propose to make online spying the default option" in response to the proposed switch. == Areas of interest == The organisation, though focused on the impact of digital technology on the liberty of UK citizens, operates with an apparently wide range of interests within that category. Its interests include: === Access to knowledge === Copyright Creative Commons Free and open source software The public domain Crown copyright Digital Restrictions Management Software patents === Free speech and censorship === Internet filtering Right to parody s. 127 Communications Act 2003 === Government and democracy === Electronic voting Freedom of information legislation === Privacy, surveillance and censorship === Automatic Vehicle Tracking Communications data retention Identity management Net Neutrality NHS patients' medical database Police DNA Records RFID == Structure == ORG has a paid staff, whose members include: Jim Killock (executive director) Former staff include Suw Charman-Anderson and Becky Hogge, both executive directors, e-voting coordinator Jason Kitcat, campaigner Peter Bradwell, grassroots campaigner Katie Sutton and administrator Katerina Maniadaki. Neil Gaiman was previously the group's patron. As of October 2022, the group had over 43,000 supporters. == ORGCON == ORGCON was the first ever conference dedicated to digital rights in the UK, marketed as "a crash course in digital rights". It was held for the first time in 2010 at City University in London and included keynote talks from Cory Doctorow, politicians and similar pressure groups including Liberty, NO2ID and Big Brother Watch. ORGCON has since been held in 2012, 2013, 2014, 2017, and 2019 where the keynote was given by Edward Snowden.
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Comparison of machine learning software

The following tables are a comparison of machine learning software such as software frameworks, libraries, and computer programs used for machine learning. == Machine learning software == == Other comparisons == == Machine learning helper libraries and platforms == Apache OpenNLP — natural language processing toolkit CUDA — GPU computing platform used to accelerate machine learning and deep learning workloads Horovod — distributed training framework for deep learning Hugging Face Transformers — library of pretrained transformer models built on other machine learning frameworks Kubeflow — machine learning platform for Kubernetes Mallet — toolkit for natural language processing and text analysis NumPy — numerical computing library used in machine learning OpenCV — computer vision library with machine learning functions ONNX — open format for representing machine learning models pandas — data analysis and data preparation library used in machine learning PlaidML — tensor compiler and backend for machine learning frameworks Polars — Dataframe library used for machine learning data preparation and analysis PyArrow — columnar data library used in machine learning data processing ROOT (TMVA) — data analysis framework with machine learning tools SciPy — scientific computing and optimization library used in machine learning == Online development environments for machine learning == Google Colab — hosted Jupyter Notebook environment commonly used for machine learning and deep learning JupyterLab — notebook-based development environment for machine learning and data science Jupyter Notebook — interactive notebook environment used for machine learning and data science Kaggle — online data science and machine learning platform
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Video game

A video game, computer game, or simply game is an electronic game that involves interaction with a user interface or input device (such as a joystick, controller, keyboard, or motion sensing device) to generate visual feedback from a display device, most commonly shown in a video format on a television set, computer monitor, flat-panel display or touchscreen on handheld devices, or a virtual reality headset. Most modern video games are audiovisual, with audio complement delivered through speakers or headphones, and sometimes also with other types of sensory feedback (e.g., haptic technology that provides tactile sensations). Some video games also allow microphone and webcam inputs for in-game chatting and livestreaming. Video games are typically categorized according to their hardware platform, which traditionally includes arcade video games, console games, and computer games (which includes LAN games, online games, and browser games). More recently, the video game industry has expanded onto mobile gaming through mobile devices (such as smartphones and tablet computers), virtual and augmented reality systems, and remote cloud gaming. Video games are also classified into a wide range of genres based on their style of gameplay and target audience. The first video game prototypes in the 1950s and 1960s were simple extensions of electronic games using video-like output from large, room-sized mainframe computers. The first consumer video game was the arcade video game Computer Space in 1971, which took inspiration from the earlier 1962 computer game Spacewar!. In 1972 came the now-iconic video game Pong and the first home console, the Magnavox Odyssey. The industry grew quickly during the "golden age" of arcade video games from the late 1970s to early 1980s but suffered from the crash of the North American video game market in 1983 due to loss of publishing control and saturation of the market. Following the crash, the industry matured, was dominated by Japanese companies such as Nintendo, Sega, and Sony, and established practices and methods around the development and distribution of video games to prevent a similar crash in the future, many of which continue to be followed. In the 2000s, the core industry centered on "AAA" games, leaving little room for riskier experimental games. Coupled with the availability of the Internet and digital distribution, this gave room for independent video game development (or "indie games") to gain prominence into the 2010s. Since then, the commercial importance of the video game industry has been increasing. The emerging Asian markets and proliferation of smartphone games in particular are altering player demographics towards casual and cozy gaming, and increasing monetization by incorporating games as a service. Today, video game development requires numerous skills, vision, teamwork, and liaisons between different parties, including developers, publishers, distributors, retailers, hardware manufacturers, and other marketers, to successfully bring a game to its consumers. As of 2020, the global video game market had estimated annual revenues of US$159 billion across hardware, software, and services, which is three times the size of the global music industry and four times that of the film industry in 2019, making it a formidable heavyweight across the modern entertainment industry. The video game market is also a major influence behind the electronics industry, where personal computer component, console, and peripheral sales, as well as consumer demands for better game performance, have been powerful driving factors for hardware design and innovation. == Origins == Early video games used interactive electronic devices with various display formats. The earliest example dates to 1947—a "cathode-ray tube amusement device" was filed for a patent on 25 January 1947, by Thomas T. Goldsmith Jr. and Estle Ray Mann, and issued on 14 December 1948, as U.S. Patent 2455992. Inspired by radar display technology, it consisted of an analog device allowing a user to control the parabolic arc of a dot on the screen to simulate a missile being fired at targets, which were paper drawings fixed to the screen. Other early examples include the Nimrod computer at the 1951 Festival of Britain; Christopher Strachey's Checkers, possibly the first game to display visuals on an electronic screen in 1952; OXO, a tic-tac-toe computer game by Alexander S. Douglas for the EDSAC in 1952; Tennis for Two, an electronic interactive game engineered by William Higinbotham in 1958; and Spacewar!, written by Massachusetts Institute of Technology students Martin Graetz, Steve Russell, and Wayne Wiitanen's on a DEC PDP-1 computer in 1962. Each game had different means of display: NIMROD had a panel of lights to play the game of Nim, OXO had a graphical display to play tic-tac-toe, Tennis for Two had an oscilloscope to display a side view of a tennis court, and Spacewar! had the DEC PDP-1's vector display to have two spaceships battle each other. These inventions laid the foundation for modern video games. In 1966, while working at Sanders Associates, Ralph H. Baer devised a system to play a basic table tennis game on a television screen. With the company's approval, Baer created the prototype known as the "Brown Box". Sanders patented Baer's innovations and licensed them to Magnavox, which commercialized the technology as the first home video game console, the Magnavox Odyssey, released in 1972. Separately, Nolan Bushnell and Ted Dabney, inspired by seeing Spacewar! running at Stanford University, devised a similar version running in a smaller coin-operated arcade cabinet using a less expensive computer. This was released as Computer Space, the first arcade video game, in 1971. Bushnell and Dabney went on to form Atari, Inc., and with Allan Alcorn, created their second arcade game in 1972, the hit ping pong-style Pong, which was directly inspired by the table tennis game on the Odyssey. Atari made a home version of Pong, which was released by Christmas 1975. The success of the Odyssey and Pong, both as an arcade game and home machine, launched the video game industry. Both Baer and Bushnell have been titled "Father of Video Games" for their contributions. == Terminology == The term "video game" was developed to describe electronic games played on a video display rather than on a teletype printer, audio speaker, or similar device. This also distinguished from handheld electronic games such as Merlin, which commonly used LED lights for indicators not in combination for imaging purposes. "Computer game" may also be used as a descriptor, as all these types of games essentially require the use of a computer processor; in some cases, it is used interchangeably with "video game". Particularly in the United Kingdom and Western Europe, this is common due to the historic relevance of domestically produced microcomputers. Other terms used include digital game, for example, by the Australian Bureau of Statistics. The term "computer game" can also refer to PC games, which are played primarily on personal computers or other flexible hardware systems, to distinguish them from console games, arcade games, or mobile games. Other terms, such as "television game", "telegame", or "TV game", had been used in the 1970s and early 1980s, particularly for home gaming consoles that rely on connection to a television set. However, these terms were also used interchangeably with "video game" in the 1970s, primarily due to "video" and "television" being synonymous. In Japan, where consoles like the Odyssey were first imported and then made within the country by the large television manufacturers such as Toshiba and Sharp Corporation, such games are known as "TV games", "TV geemu", or "terebi geemu". The term "TV game" is still commonly used into the 21st century. "Electronic game" may also be used to refer to video games, but this also incorporates devices like early handheld electronic games that lack any video output. The first appearance of the term "video game" emerged around 1973. The Oxford English Dictionary cited a 10 November 1973 BusinessWeek article as the first printed use of the term. Though Bushnell believed the term came from a vending magazine review of Computer Space in 1971, a review of the major vending magazines Vending Times and Cashbox showed that the term may have come even earlier, appearing first in a letter dated July 10, 1972. In the letter, Bushnell uses the term "video game" twice. Per video game historian Keith Smith, the sudden appearance suggested that the term had been proposed and readily adopted by those in the field. Around March 1973, Ed Adlum, who ran Cashbox's coin-operated section until 1972 and then later founded RePlay Magazine, covering the coin-op amusement field, in 1975, used the term in an article in March 1973. In a September 1982 issue of RePlay, Adlum is credited with first naming these games as "video games": "RePlay
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Ambient awareness

Ambient awareness (AmA) is a term used by social scientists to describe a form of peripheral social awareness through social media. This awareness is propagated from relatively constant contact with one's friends and colleagues via social networking platforms on the Internet. The term essentially defines the sort of omnipresent knowledge one experiences by being a regular user of these media outlets that allow a constant connection with one's social circle. According to Clive Thompson of The New York Times, ambient awareness is "very much like being physically near someone and picking up on mood through the little things; body language, sighs, stray comments". Academic Andreas Kaplan defines ambient awareness as "awareness created through regular and constant reception, and/or exchange of information fragments through social media". Two friends who regularly follow one another's digital information can already be aware of each other's lives without actually being physically present to have had a conversation. == Social == Socially speaking, ambient awareness and social media are products of the new generations who are being born or growing up in the digital age, starting circa 1998 and running to current times. Social media is personal media (what you're doing in the moment, how you feel, a picture of where you are) combined with social communication. Social media is the lattice work for ambient awareness. Without social media the state of ambient awareness cannot exist. Artificial Social Networking Intelligence (ASNI) refers to the application of artificial intelligence within social networking services and social media platforms. It encompasses various technologies and techniques used to automate, personalize, enhance, improve, and synchronize user's interactions and experiences within social networks. ASNI is expected to evolve rapidly, influencing how we interact online and shaping their digital experiences. Transparency, ethical considerations, media influence bias, and user control over data will be crucial to ensure responsible development and positive impact. A significant feature of social media is that it is created by those who also consume it. Mostly, those participating in this phenomenon are adolescents, college age, or young adult professionals. According to Dr. Mimi Ito, a cultural anthropologist and Professor in Residence at the University of California at Irvine, the mobile device is the greatest proxy device used to create and distribute Social Media. She reportedly states that "teenagers capture and produce their own media, and stay in constant ambient contact with each other..." using mobile devices. Usually while doing this they are consuming other forms of media such as music or video content via their smart phones, tablets, or other similar devices. Effectively this has led social scientists to believe that learning and multitasking will have a new face as the products of the digital generation enter the work force and begin to integrate their learning methods into the standard preexisting business models of today. Professors Kaplan and Haenlein see ambient awareness as one of the major reasons for the success of such microblogging sites as Twitter. == Origins == The earliest available technology that could be used for constant social contact is the cell phone. For the first time, people could be contacted readily and at will beyond the confines of their work or homes. Then later, with the additional service of texting, one can see the somewhat primitive form of the status update. Since the text message only allows for 160 characters to transmit pertinent information it paved the way for the status update as we know it today. The transition from only having a few points of regular long distance contact, to being constantly available via cell phone, is what primed society for social networking websites. Perhaps the first instance where these websites created the possibility of larger scale ambient awareness was when Facebook installed the news feed. The news feed automatically sends compiled information on all of a users contacts activities directly to them so that they can access all of the happenings in their world from one location. For the first time, becoming someone's Facebook friend was the equivalent of subscribing to a feed of their daily minutiae. Since this innovation, a new wave of micro-blogging services have emerged, such as Twitter or Tumblr. Although these services have often been criticized as containing seemingly meaningless snippets of information, when a follower gathers a certain amount of information, they begin to obtain an ambient understanding of who they are following. This has led to the mass usage of social media as not only a social tool but also as a marketing and business tool. == Uses in marketing == Websites such as Twitter, YouTube, Facebook, and Myspace, among many others, have been used by people in all forms of business to create a closer digital/ambient bond with their clientele base. This is most notably seen in the music industry where social media networking has become the mainstay of all advertising for independent and major artists. The effect of this type of ambient marketing is that the consumer begins to get a sense of the artist's life style and personality. In this way social media outlets and ambient awareness have managed to tighten the gap between consumers and producers in all areas of business. == Uses in business processes == As web-based collaboration tools and social project management suites proliferate, the addition of activity streams to those products help to create business context-specific ambient awareness, and produce a new class of products, such as social project management platforms.
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