RTX Video Super Resolution (RTX VSR) is a video scaling feature by Nvidia. It was released on February 28, 2023. == History == The feature was first unveiled during CES 2023 as RTX Video Super Resolution. It uses the on-board Tensor Cores to upscale browser video content in real time. Video Super Resolution was initially only available on RTX 30 and 40 series GPUs, while support for 20 series GPUs was added afterwards; it is now available on all Nvidia RTX-branded GPUs. The feature supports input resolutions from 360p to 1440p and a max output of 4K and comes without support for HDR content although that could be likely added in the future. Nvidia released RTX Video Super Resolution 1.5 with improved video quality and RTX 20 series support on October 17, 2023. == Reception == According to ComputerBase, although "the algorithm is not yet working flawlessly", the feature is "overall recommendable".
MetroHero
MetroHero is a semi-defunct real-time transit tracking and performance analysis application for the Washington Metro rapid transit system. Originally available on iOS, Android, and the web, it allows users to view live maps of all trains on a specific line, summary statistics relating to real-time system performance, and user feedback on current Metro conditions. The app launched in 2015, followed by ARIES for Transit, a related project from the same developers, and continued functioning until its original developers shut it down in 2023. Afterwards, forks of the application went live to allow for its continued public use, and the Washington Metropolitan Area Transit Authority (WMATA), Metro's operator, announced that it would launch a similar app. The app has been described by local news media as popular and well-liked among Washington, D.C.-area residents. == History and main development == MetroHero was initially developed by James and Jennifer Pizzurro, who both attended George Washington University and studied computer science. They said that they were inspired to create the app after experiencing train delays and searching for an app to track a train after boarding; such an app did not exist for the Washington Metro. The development of the app was not endorsed by WMATA, but it did use publicly available data from the agency. MetroHero launched as an Android application in September 2015, followed by the release of an iOS-compatible web app in December of that year. A standalone iOS app launched in April 2018, but the web app remained supported. By April 2018, MetroHero had approximately 13,000 monthly active users. James Pizzurro has stated that the app's intended audience was regular Metro commuters who wanted to communicate with each other about active problems, as opposed to tourists and riders who only wanted train time data. Throughout the application's development, the Pizzurros had been advocates for Metro's transparency with riders and the community by providing more high-quality data and taking on the feedback of developers. In particular, they criticized Metro's reluctance to uniquely identify individual train trips and its decision to obscure data under certain circumstances, which have posed problems for MetroHero's data collection. In addition to their work on MetroHero, the app's developers led or participated in other initiatives related to transit in the Greater Washington area. In 2019, MetroHero partnered with a local transit group to analyze Metrobus data and publish a "Metrobus Report Card", along with proposed goals and recommendations based on the report's findings. Based on this experience, MetroHero's developers began a sister project, the Adherence + Reliability + Integrity Evaluation System for Transit (ARIES for Transit), which displays data and issues grades for Washington- and Baltimore-area transit systems. Separately, James Pizzurro used MetroHero data to inform Rail Transit OPS, an independent Metro oversight group, and assist in its documentation of Metro system incidents. == Application == The MetroHero application uses several interfaces, including an overall dashboard and a live map, to display data to its users. On the dashboard, system-wide train summary data, such as the number of operating trains and headway adherence, is visible. The map offers a visual representation of all trains' positions throughout the system, filtered by line. Individual stations and trains can be selected to see ratings and comments provided by other users, including both positive and negative notes like cleanliness and crowdedness. Additionally, a list of train wait times is given, along with aggregate data like average wait time. Any train delays or service incidents are visible in the app. MetroHero uses several data sources for the various components of its application. Train positions and other operational data are provided by WMATA as part of its initiative to release open data for third-party developers. However, MetroHero's developers noted that the Metro-provided information is sometimes inaccurate and incomplete, thereby limiting the accuracy of MetroHero. The app also collects crowdsourced data from its users, who can report conditions in train cars and stations and add to reports sent by other people. Additionally, MetroHero parses data from Twitter feeds to learn about system incidents, including delays and fires. In addition to the web app, Android app, and iOS app, MetroHero's initial developers maintained automated social media accounts that alerted customers about Metro service; these accounts were discontinued upon the original app's eventual shutdown. MetroHero also hosts archived performance data for later review, a feature that is sometimes used after major incidents. == Shutdown and future == In February 2023, James Pizzurro announced that MetroHero would be shut down on July 1, 2023, citing "positive changes ... in the app landscape and in WMATA's data management and communication" and the costs and time associated with maintaining the app. Shortly before the application's end date, the Pizzurros shared MetroHero's source code on GitHub, which prompted others to fork the code and begin maintaining new instances of MetroHero to succeed the original app. The original website went offline on July 1, as planned. Historically, WMATA has not offered its own real-time map or similar service, citing other apps from third parties which accomplished the same task. However, on June 30, 2023, Randy Clarke, WMATA's general manager, announced that Metro would begin offering a similar service as MetroHero did. The app, initially named MetroMeter, was planned to begin operating in early July and would provide real-time information on trains, headways, and service schedules. Metro also noted its intentions to extend this service to Metrobus and MetroAccess. On July 20, Metro announced that the app had been renamed to MetroPulse and launched it in beta. MetroHero's other project, ARIES for Transit, was not affected by the shutdown. == Reception == MetroHero was generally well-received and has been recognized for its usage among Washington-area commuters. DCist called it one of the "most praised" Metro tracking apps, and WMATA publicly acknowledged its popularity when announcing its decision to establish MetroPulse. Chris Barnes, a member of the Metro Riders' Advisory Council, said that the app is considered important among riders because it fulfills a need for riders to have reliable and transparent transit information, albeit somewhat hindered by flaws in WMATA's data.
Downloadable content
Downloadable content (DLC) is additional content created for an already released video game, distributed through the Internet by the game's publisher. It can be added for no extra cost or as a form of video game monetization, enabling the publisher to gain additional revenue from a title after it has been purchased, often using a microtransaction system. DLC can range from cosmetic content, such as skins, to new in-game content, like characters, levels, modes, and larger expansions that may contain a mix of such content as a continuation of the base game. In some games, multiple DLCs (including future DLC not yet released) may be bundled as part of a "season pass"—typically at a discount rather than purchasing each DLC individually. While the Dreamcast was the first home console to support DLC (albeit in a limited form due to hardware and internet connection limitations), Microsoft's Xbox helped popularize the concept. Since the seventh generation of video game consoles, DLC has been a prevalent feature of major video game platforms with internet connectivity. == Etymology == Since the popularization of microtransactions in online distribution platforms such as Steam, the term DLC has become a synonymous for any form of paid content in video games, regardless of whether they constitute the download of new content. Furthermore, this led to the creation of the oxymoronic term "on-disc DLC" for content included on the game's original files but locked behind a paywall. == History == === Precursors to DLC === The earliest form of downloadable content were offerings of full games, such as on the Atari 2600's GameLine service, which allowed users to download games using a telephone line. A similar service, Sega Channel, allowed for the downloading of games to the Sega Genesis over a cable line. While the GameLine and Sega Channel services allowed for the distribution of entire titles, they did not provide downloadable content for existing titles. Expansion packs were sold at retail for some PC games, which featured content such as additional levels, characters, or maps for a base game. They often required an installation of the original game in order to function, but some games (such as Half-Life) had "standalone" expansions, which were essentially spin-off games that reused engine code and assets from the original game. === On consoles === The Dreamcast was the first console to feature online support as a standard; DLC was available, though limited in size due to the narrowband connection and the 200 block limit of the Visual Memory Unit memory card. These online features were still considered a breakthrough in video games. With the release of the Xbox, Microsoft was the second company to implement downloadable content. Many Xbox titles, including Splinter Cell, Halo 2, and Ninja Gaiden, offered varying amounts of extra content, available for download through the Xbox Live service. Most of this content was available free. With the advent of the GameCube, Nintendo was the third company to implement downloadable content. Many GameCube titles offered varying amounts of extra content from Game Boy Advance titles with the GameCube – Game Boy Advance link cable. All of this content was available free. The Xbox 360 (2005) included more robust support for digital distribution, including DLC downloads and purchases, via its Xbox Live Marketplace service. Microsoft believed that publishers would benefit by offering small pieces of content at a small cost ($1 to $5), rather than full expansion packs (~$20), as this would allow players to pick and chose what content they desired, providing revenue to the publishers. Microsoft also utilized a digital currency known as "Microsoft Points" for transactions, which could also be purchased through physical gift cards to avoid the banking fees associated with the small price points. The PlayStation 3 (2006) adopted the same approach with their downloadable hub, the PlayStation Store. Sony planned on having the bulk of its content be purchased separately via many separate online microtransactions for PlayStation Network titles, including Gran Turismo HD Concept and Gran Turismo 5 Prologue. The Wii (2006) featured a sparser amount of downloadable content on their Wii Shop Channel, the bulk of which is accounted for by digital distribution of emulated Nintendo titles from previous generations. Music video games, such as titles from the Guitar Hero and Rock Band franchises, took significant advantage of downloadable content as a means of offering new songs to be played in-game. Harmonix claimed that Guitar Hero II would feature "more online content than anyone has ever seen in a game to this date." Rock Band features the largest number of downloadable items of any console video game, with a steady number of new songs that were added weekly between 2007 and 2013. Acquiring all the downloadable content for Rock Band would, as of July 12, 2012, cost $5,880.10. === On personal computers === As the popularity and speed of internet connections rose, so did the popularity of using the internet for digital distribution of media. User-created game mods and maps were distributed exclusively online, as they were mainly created by people without the infrastructure capable of distributing the content through physical media. In 1997, Cavedog offered a new unit every month as free downloadable content for their real-time strategy computer game Total Annihilation. Later PC digital distribution platforms, such as Games for Windows Marketplace and Steam, would add support for DLC in a similar manner to consoles. === On handhelds === Nokia phones of the late 1990s and early 2000s shipped with side-scrolling shooter Space Impact, available on various models. With the introduction of WAP in 2000, additional downloadable content for the game, with extra levels, became available. The Nintendo Wi-Fi Connection service on the Nintendo DS could be used to obtain a form of DLC for certain games, such as Picross DS—where players could download puzzle "packs" of classic puzzles from previous Picross series games (such as Mario's Picross). as well as downloadable user generated content. Due to the Nintendo DS's use of cartridges and lack of dedicated storage, most "DLC" for DS games was limited in scope, or in some cases (such as Professor Layton and the Curious Village and Moero! Nekketsu Rhythm Damashii Osu! Tatakae! Ouendan 2), was already part of the game's data on the cartridge, and merely unlocked. Its successor, the Nintendo 3DS, natively supported the purchase of DLC for supported titles via Nintendo eShop. Starting with iPhone OS 3, downloadable content became available for the platform via applications bought from the App Store. While this ability was initially only available to developers for paid applications, Apple eventually allowed for developers to offer this in free applications as well in October 2009. == On-disc DLC == In some cases, a purchased DLC may not actually download new content to the device, but merely consists of data used to enable associated content that is already present within the game's data. DLC of this nature revealed via data mining is typically referred to as "on-disc DLC" or PULC (premium unlockable content). This practice has sometimes been considered controversial, with publishers being accused of using what is effectively a microtransaction to lock access to content that was already contained within the game as sold at retail. Data relating to future DLC may be included on-disc or downloaded during updates for technical reasons as well, either to ensure online multiplayer compatibility for existing content between players who have not yet purchased the new DLC, or as dormant support code for planned content that is still in development at the time of the release. == Monetization == Downloadable content is often offered for a price. Since Facebook games popularized the business model of microtransactions, some have criticized downloadable content as being overpriced and an incentive for developers to leave items out of the initial release, with The Elder Scrolls IV: Oblivion's horse armor DLC having faced a mixed reception upon its release for that reason. However, by 2009, the Horse Armor DLC was one of the top ten content packs that Bethesda had sold, which justified the DLC model for future games. Where a normal software disc may allow its license sold or traded, DLC is generally locked to a specific user's account and does not come with the ability to transfer that license to another user. In addition to individual content downloads, video game publishers sometimes offer a "season pass", which allows users to pre-order a selection of upcoming content over a specific time period, and ensuring the customer's ability to immediately obtain the content upon release. As users do not have the ability to fully preview the content before their purchase, there is a chance that the content of a season
Contact cleaner
Contact cleaner, also known as switch-cleaner, is any of various chemicals, or mixtures of chemicals, intended to remove or prevent the build-up of oxides or other unwanted substances on the conductive surfaces of connectors, switches, and other electronic components with moving surface-contacts, and thus reduce the contact resistance encountered. The use of contact cleaner can help to minimize the wetting current across a pair of contacts. An example of a simple contact cleaner is isopropyl alcohol Some contact cleaners are designed to evaporate completely and rapidly, leaving no residue. Others may contain lubricants. Lubricants themselves should not necessarily be used as contact cleaners, especially if they are designed to leave an unsuitable residue. However, appropriate lubricants may work well as contact cleaners.
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.
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
Texas House Bill 20
An Act Relating to censorship of or certain other interference with digital expression, including expression on social media platforms or through electronic mail messages, also known as Texas House Bill 20 (HB20), is a Texas anti-deplatforming law enacted on September 9, 2021. It prohibits large social media platforms from removing, moderating, or labeling posts made by users in the state of Texas based on their "viewpoints", unless considered illegal under federal law or otherwise falling into exempted categories. It also requires them to make various public disclosures relating to their business practices (including the impact of algorithmic and moderation decisions on the content that is delivered to users). The bill is part of a wider array of Republican-backed legislation seeking to prohibit the censorship of political speech, based on allegations that the moderation policies of large social media platforms are not politically neutral. It has been challenged in NetChoice, LLC v. Paxton, and is currently the subject of a circuit split between the Fifth Circuit, and a decision by the Eleventh Circuit that struck down a similar bill in the state of Florida. In September 2023, the U.S. Supreme Court agreed to hear NetChoice v. Paxton jointly with NetChoice v. Moody on questions of whether the Florida and Texas state laws are in compliance with the 1st Amendment. == Content == The law applies to "social media platforms" that serve users in the state of Texas, and have more than 50 million monthly active users in the United States. They are defined as any public internet website or application that allows users to "communicate with other users for the primary purpose of posting information, comments, messages, or images", excluding internet service providers, electronic mail, and services where communication features are "incidental to, directly related to, or dependent on" content that is pre-selected by the operator. In the bill, to "censor" is defined as to "block, ban, remove, deplatform, demonetize, de-boost, restrict, deny equal access or visibility to, or otherwise discriminate against" expression. The law prohibits social media platforms from "censoring on the basis of user viewpoint, user expression, or the ability of a user to receive the expression of others", or on the basis of a user's geographic location in Texas. This includes removal or labeling posts with warnings and disclaimers. Social media platforms may only censor content if it is unlawful, they are "specifically authorized" to do so by federal law, based on requests from "an organization with the purpose of preventing the sexual exploitation of children or protecting survivors of sexual abuse from ongoing harassment", or "directly incites" criminal activity or contains threats of violence against persons based on protected categories. It is disputed over whether this provision is actually enforceable, as it may be preempted by Section 230 of the Communications Decency Act (which states that the operators of interactive computer services are not responsible for the actions of their users). Social media platforms must make public disclosures regarding the algorithmic techniques and moderation polices that are used to determine the content provided to users, must publish a compliant acceptable use policy (AUP), and must publish a biannual transparency report containing specific details on all actions made by the service regarding the moderation of users and content. The law also prohibits email providers from "intentionally imped[ing] the transmission of another person's electronic mail message based on the content." == Legislative history == Texas Governor Greg Abbott signed the bill into law on September 9, 2021. Democrat-proposed amendments excluding Holocaust denial, terrorism content, and vaccine misinformation from the bill were rejected. Following a suit by the industry groups Computer & Communications Industry Association (CCIA) and NetChoice, NetChoice, LLC v. Paxton, the bill was blocked by U.S. District Judge Robert Pitman in December 2021, on First Amendment grounds. Texas appealed to the United States Court of Appeals for the Fifth Circuit. Judges Edith Jones, Andrew Oldham, and Leslie H. Southwick, lifted the injunction on May 11, 2022, but the decision was appealed to the Supreme Court which suspended the bill pending a full review in the Fifth Circuit. On September 16, 2022, the Fifth Circuit reversed the injunction, allowing the bill to take effect; Judge Oldham stated that the bill "chills censorship" and "does not chill speech", and accused the plaintiffs of "attempt[ing] to extract a freewheeling censorship right from the Constitution's free speech guarantee. The Platforms are not newspapers. Their censorship is not speech." Southwick dissented, stating that "we are in a new arena, a very extensive one, for speakers and for those who would moderate their speech. None of the precedents fit seamlessly." The CCIA and NetChoice requested a stay on the ruling and that the case be taken to the Supreme Court, arguing that the reversal conflicts with an Eleventh Circuit decision in NetChoice v. Moody which struck down a similar anti-moderation bill imposed by the state of Florida. On October 12, 2022, the Fifth Circuit granted the stay.