Chatbot - Knowledge

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gives chatbot-style techniques a potentially useful role in interactive systems that need to elicit information from users, as long as that information is relatively straightforward and falls into predictable categories. Thus, for example, online help systems can usefully employ chatbot techniques to identify the area of help that users require, potentially providing a "friendlier" interface than a more formal search or menu system. This sort of usage holds the prospect of moving chatbot technology from Weizenbaum's "shelf ... reserved for curios" to that marked "genuinely useful computational methods".

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while 6% had heard of a health chatbot and 3% had experience of using it, 67% perceived themselves as likely to use one within 12 months. The majority of participants would use a health chatbot for seeking general health information (78%), booking a medical appointment (78%), and looking for local health services (80%). However, a health chatbot was perceived as less suitable for seeking results of medical tests and seeking specialist advice such as sexual health.

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only seeking a doctor when experiencing a health problem and 65% thought that a chatbot was a good idea. 30% reported dislike about talking to computers, 41% felt it would be strange to discuss health matters with a chatbot and about half were unsure if they could trust the advice given by a chatbot. Therefore, perceived trustworthiness, individual attitudes towards bots, and dislike for talking to computers are the main barriers to health chatbots.

1807:, an AI chatbot designed to learn from previous interaction, caused major controversy due to it being targeted by internet trolls on Twitter. Soon after its launch, the bot was exploited, and with its "repeat after me" capability, it started releasing racist, sexist, and controversial responses to Twitter users. This suggests that although the bot learned effectively from experience, adequate protection was not put in place to prevent misuse. 1959: 1945: 1973: 81: 1197:

responding to any input that contains the word 'MOTHER' with 'TELL ME MORE ABOUT YOUR FAMILY'). Thus an illusion of understanding is generated, even though the processing involved has been merely superficial. ELIZA showed that such an illusion is surprisingly easy to generate because human judges are so ready to give the benefit of the doubt when conversational responses are

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The observer says to himself "I could have written that". With that thought, he moves the program in question from the shelf marked "intelligent", to that reserved for curios. The object of this paper is to cause just such a re-evaluation of the program about to be "explained". Few programs ever needed it more.

1146:’. When humans use and apply chatbot content contaminated with hallucinations, this results in ‘botshit’. Given the increasing adoption and use of chatbots for generating content, there are concerns that this technology will significantly reduce the cost it takes humans to generate, spread and consume botshit. 4845:

reports how he was initially fooled by a chatterbot posing as an attractive girl in a personal ad he answered on a dating website. In the ad, the girl portrayed herself as being in Southern California and then soon revealed, in poor English, that she was actually in Russia. He became suspicious after

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The analysis of attitudinal variables showed that most participants reported their preference for discussing their health with doctors (73%) and having access to reliable and accurate health information (93%). While 80% were curious about new technologies that could improve their health, 66% reported

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can pass itself off as a human instead of a chatbot, its message would be more credible. Therefore, human-seeming chatbots with well-crafted online identities could start scattering fake news that seems plausible, for instance making false claims during an election. With enough chatbots, it might be

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is an Internet-connected version of the doll that uses a chatbot provided by the company ToyTalk, which previously used the chatbot for a range of smartphone-based characters for children. These characters' behaviors are constrained by a set of rules that in effect emulate a particular character and

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techniques can be incorporated into chatbot applications to allow them to map conversations between users and customer service agents, especially in social media. Research has shown that methods incorporating deep learning can learn writing styles from a brand and transfer them to another, promoting

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is one of the major concerns of chatbot technologies. Security threats and system vulnerabilities are weaknesses that are often exploited by malicious users. Storage of user data and past communication, that is highly valuable for training and development of chatbots, can also give rise to security

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Interface designers have come to appreciate that humans' readiness to interpret computer output as genuinely conversational—even when it is actually based on rather simple pattern-matching—can be exploited for useful purposes. Most people prefer to engage with programs that are human-like, and this

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threats. Chatbots operating on third-party networks may be subject to various security issues if owners of the third-party applications have policies regarding user data that differ from those of the chatbot. Security threats can be reduced or prevented by incorporating protective mechanisms. User

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unveiled that Messenger would allow chatbots into the app. In large companies, like in hospitals and aviation organizations, IT architects are designing reference architectures for Intelligent Chatbots that are used to unlock and share knowledge and experience in the organization more efficiently,

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In artificial intelligence, machines are made to behave in wondrous ways, often sufficient to dazzle even the most experienced observer. But once a particular program is unmasked, once its inner workings are explained, its magic crumbles away; it stands revealed as a mere collection of procedures.

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Chatbots have been used at different levels of government departments, including local, national and regional contexts. Chatbots are used to provide services like citizenship and immigration, court administrations, financial aid, and migrants’ rights inquiries. For example, EMMA answers more than

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Certain patient groups are still reluctant to use chatbots. A mixed-methods study showed that people are still hesitant to use chatbots for their healthcare due to poor understanding of the technological complexity, the lack of empathy, and concerns about cyber-security. The analysis showed that

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sequence. Such sequences can be triggered by user opt-in or the use of keywords within user interactions. After a trigger occurs a sequence of messages is delivered until the next anticipated user response. Each user response is used in the decision tree to help the chatbot navigate the response

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Chatbots are increasingly present in businesses and often are used to automate tasks that do not require skill-based talents. With customer service taking place via messaging apps as well as phone calls, there are growing numbers of use-cases where chatbot deployment gives organizations a clear

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Chatbots have great potential to serve as an alternate source for customer service. Many high-tech banking organizations are looking to integrate automated AI-based solutions such as chatbots into their customer service in order to provide faster and cheaper assistance to their clients who are

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ELIZA's key method of operation (copied by chatbot designers ever since) involves the recognition of clue words or phrases in the input, and the output of the corresponding pre-prepared or pre-programmed responses that can move the conversation forward in an apparently meaningful way (e.g. by

1187:, published in 1966, which seemed to be able to fool users into believing that they were conversing with a real human. However Weizenbaum himself did not claim that ELIZA was genuinely intelligent, and the introduction to his paper presented it more as a debunking exercise: 1364:. Despite criticism of its accuracy and tendency to “hallucinate”—that is, to confidently output false information and even cite non-existent sources—ChatGPT has gained attention for its detailed responses and historical knowledge. Another example is BioGPT, developed by 1615:

launched their chatbot called SoBot in March 2018. While 80% of users of the SoBot expressed their satisfaction after having tested it, Société Générale deputy director Bertrand Cozzarolo stated that it will never replace the expertise provided by a human advisor.

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As it happens usually with technology-led changes in existing services, some consumers, more often than not from older generations, are uncomfortable with chatbots due to their limited understanding, making it obvious that their requests are being dealt with by

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written conversation with a human judge to the extent that the judge is unable to distinguish reliably—on the basis of the conversational content alone—between the program and a real human. The notoriety of Turing's proposed test stimulated great interest in

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Chatbots are also appearing in the healthcare industry. A study suggested that physicians in the United States believed that chatbots would be most beneficial for scheduling doctor appointments, locating health clinics, or providing medication information.

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Chatbot developers create, debug, and maintain applications that automate customer services or other communication processes. Their duties include reviewing and simplifying code when needed. They may also help companies implement bots in their operations.

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Chatbots require a large amount of conversational data to train. Generative models, which are based on deep learning algorithms to generate new responses word by word based on user input, are usually trained on a large dataset of natural-language

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so as to target specific tasks or applications (i.e., simulating human conversation, in the case of chatbots). Chatbots can also be designed or customized to further target even more specific situations and/or particular subject-matter domains.

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predicted that by 2021, 15% of all customer service interactions globally will be handled completely by AI. A study by Juniper Research in 2019 estimates retail sales resulting from chatbot-based interactions will reach $ 112 billion by 2023.

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Since 2016, when Facebook allowed businesses to deliver automated customer support, e-commerce guidance, content, and interactive experiences through chatbots, a large variety of chatbots were developed for the Facebook Messenger platform.

1690:(made by Nick Gerritsen of Touchtech) – has been developed. It is designed to share its political thoughts, for example on topics such as climate change, healthcare and education, etc. It talks to people through Facebook Messenger. 1586:

the brand's image on social media platforms. Chatbots can create new ways of brands and user interactions, which can help improve the brand's performance and allow users to gain "social, information, and economic benefits".

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that optimize their ability to communicate based on each conversation held. Still, there is currently no general purpose conversational artificial intelligence, and some software developers focus on the practical aspect,

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Luo, Renqian; Sun, Liai; Xia, Yingce; Qin, Tao; Zhang, Sheng; Poon, Hoifung; Liu, Tie-Yan; et al. (2022). "BioGPT: generative pre-trained transformer for biomedical text generation and mining".

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In 2016, Facebook Messenger allowed developers to place chatbots on their platform. There were 30,000 bots created for Messenger in the first six months, rising to 100,000 by September 2017.

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with spam and advertisements by mimicking human behavior and conversations or to entice people into revealing personal information, such as bank account numbers. They were commonly found on

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Many banks, insurers, media companies, e-commerce companies, airlines, hotel chains, retailers, health care providers, government entities, and restaurant chains have used chatbots to

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becoming increasingly comfortable with technology. In particular, chatbots can efficiently conduct a dialogue, usually replacing other communication tools such as email, phone, or

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and reduce the errors in answers from expert service desks significantly. These Intelligent Chatbots make use of all kinds of artificial intelligence like image moderation and

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Gertner, Jon. (2023) "Knowledge's Moment of Truth: Can the online encyclopedia help teach A.I. chatbots to get their facts right — without destroying itself in the process?"

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Sajani Senadheera, et al. (2024) Understanding Chatbot Adoption in Local Governments: A Review and Framework, Journal of Urban Technology, DOI: 10.1080/10630732.2023.2297665

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Several studies report significant reduction in the cost of customer services, expected to lead to billions of dollars of economic savings in the next ten years. In 2019,

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Chatbots sometimes provide plausible-sounding but incorrect or nonsensical answers. They can make up names, dates, historical events, and even simple math problems.

4082: 1712:, the state government has launched a chatbot for its Aaple Sarkar platform, which provides conversational access to information regarding public services managed. 3482: 4706: 3176: 1218: 972: 4389: 3059: 1360:, which provides a solid foundation for the model to perform well on downstream tasks with limited amounts of task-specific data. An example of a GPT chatbot is 5556: 4514: 1758:

mobile app to recognize the child's speech and have a conversation. Like the Hello Barbie doll, it attracted controversy due to vulnerabilities with the doll's

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Bird, Jordan J.; Ekart, Aniko; Faria, Diego R. (June 2018). "Learning from Interaction: An Intelligent Networked-Based Human-Bot and Bot-Bot Chatbot System".

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launched a chatbot called MyGov Corona Helpdesk, that worked through Whatsapp and helped people access information about the Coronavirus (COVID-19) pandemic.

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2006). While ELIZA and PARRY were used exclusively to simulate typed conversation, many chatbots now include other functional features, such as games and

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In 2016, Russia-based Tochka Bank launched the world's first Facebook bot for a range of financial services, including a possibility of making payments.

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a couple of months of email exchanges, sent her an email test of gibberish, and she still replied in general terms. The dating website is not named.

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architecture, have become common to build sophisticated chatbots. The "pre-training" in its name refers to the initial training process on a large

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fields employ specialized software or programming languages created specifically for the narrow function required. For example, A.L.I.C.E. uses a

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parliamentary election, and was built by the artist collective Computer Lars. Leader Lars differed from earlier virtual politicians by leading a

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both announced their participation in the testing; both airlines had previously launched customer services on the Facebook Messenger platform.

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and by not pretending to be an objective candidate. This chatbot engaged in critical discussions on politics with users from around the world.

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techniques without any reasoning capabilities, the same technique ELIZA was using back in 1966. This is not strong AI, which would require

1159: 949: 712: 247: 1579:. In banking, their major application is related to quick customer service answering common requests, as well as transactional support. 3681: 6131: 3274: 1460:

A 2017 study showed 4% of companies used chatbots. According to a 2016 study, 80% of businesses said they intended to have one by 2020.

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A chatbot's efficiency highly depends on language processing and is limited because of irregularities, such as accents and mistakes.

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the meaning of their responses, this means they can produce coherent-sounding but inaccurate or fabricated content, referred to as ‘

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The advantages of using chatbots for customer interactions in banking include cost reduction, financial advice, and 24/7 support.

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Dandapani, Arundati (30 April 2020). "Redesigning Conversations with Artificial Intelligence (Chapter 11)". In Sha, Mandy (ed.).

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and The Chatterbox Challenge (the latter has been offline since 2015, however, materials can still be found from web archives).

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Other companies explore ways they can use chatbots internally, for example for Customer Support, Human Resources, or even in

1108: 1005: 665: 486: 4891:. Advances in Intelligent Systems and Computing. Vol. 840 (1st ed.). Nottingham, UK: Springer. pp. 179–190. 5997: 5718: 5263: 1997: 876: 578: 354: 4991:

Hasal, Martin; Nowaková, Jana; Ahmed Saghair, Khalifa; Abdulla, Hussam; Snášel, Václav; Ogiela, Lidia (10 October 2021).

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protocols. There has also been a published report of a chatbot used in a fake personal ad on a dating service's website.

5690: 5241: 3474: 1280: 833: 770: 680: 658: 501: 491: 2883: 1612: 6035: 6020: 5992: 5857: 5852: 5427: 4381: 3051: 2446:(January 1966), "ELIZA – A Computer Program For the Study of Natural Language Communication Between Man And Machine", 2052: 1559: 1276: 1058: 984: 896: 881: 342: 164: 4504: 871: 4960: 6172: 5772: 5743: 5521: 3823: 3801: 3417: 1868:

Chatbots are unable to deal with multiple questions at the same time and so conversation opportunities are limited.

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the dialogue from the ICCC, which took place 24–26 October 1972, whereas this session is from 18 September 1972.)

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Mauldin, Michael (1994), "ChatterBots, TinyMuds, and the Turing Test: Entering the Loebner Prize Competition",

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Chatbots have difficulty managing non-linear conversations that must go back and forth on a topic with a user.

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As the input/output database is fixed and limited, chatbots can fail while dealing with an unsaved query.

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is able to answer user queries related to health promotion and disease prevention such as screening and

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staff with a chatbot but had to take it offline after users reported receiving harmful advice from it.

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Chatbot competitions focus on the Turing test or more specific goals. Two such annual contests are the

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Parts of this article (those related to everything, particularly sections after the intro) need to be

6115: 5791: 5767: 5620: 5379: 5120: 5046: 3229: 2563: 2002: 1518: 1383: 1261: 636: 586: 1476:'s virtual customer service agent which launched in 2011. The newer generation of chatbots includes 6095: 6025: 5982: 5938: 5710: 5700: 5695: 5583: 5079:; Jacques, Richard (2019), "Chatbots, Humbots, and the Quest for Artificial General Intelligence", 3980:

Palanica, Adam; Flaschner, Peter; Thommandram, Anirudh; Li, Michael; Fossat, Yan (3 January 2019).

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Chatbots have also been incorporated into devices not primarily meant for computing, such as toys.

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The bots usually appear as one of the user's contacts, but can sometimes act as participants in a

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questions. In November 2023, Amazon announced a new chatbot, called Q, for people to use at work.

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and simulating the way a human would behave as a conversational partner. Such chatbots often use

717: 641: 427: 222: 4568:"Maharashtra government launches Aaple Sarkar chatbot to provide info on 1,400 public services" 2672:

Kolodner, Janet L. (1 October 1983). "Maintaining organization in a dynamic long-term memory".

6167: 6110: 5822: 5630: 5541: 5355: 5345: 5208: 5140: 5092: 5022: 4900: 4869: 4240: 4178:"In focus: Mumbai-based Haptik which developed India's official WhatsApp chatbot for Covid-19" 4063: 4055: 4013: 3599: 3557: 3245: 2833: 2740: 2691: 2443: 2386: 2360: 2072: 2032: 1798: 1766: 1399: 1304: 1180: 1124: 1093: 1081: 810: 653: 566: 362: 332: 277: 272: 227: 169: 73: 5309: 4858:"Automation, Algorithms, and Politics| Talking to Bots: Symbiotic Agency and the Case of Tay" 3266: 5987: 5872: 5847: 5648: 5551: 5386: 5321: 5132: 5084: 5012: 5004: 4892: 4230: 4222: 4087: 4047: 4003: 3993: 3591: 3547: 3539: 3301: 3235: 2825: 2732: 2681: 2599: 2595: 2501: 2457: 2423: 2352: 2221: 2188: 2042: 1992: 1852: 1786: 1563: 1453:, for promotion, and to offer additional ways to order from them. Chatbots are also used in 1296: 1171: 1120: 1116: 1089: 1050: 838: 591: 541: 451: 435: 405: 267: 262: 212: 202: 100: 4258: 3824:"Gagner du Temps avec le Chatbot Bancaire pour Gagner en Intelligence avec les Conseillers" 2317: 1933:’s GPT series (which still contain notable flaws and limitations, as previously outlined). 1847:

The creation and implementation of chatbots is still a developing area, heavily related to

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Since September 2017, this has also been as part of a pilot program on WhatsApp. Airlines

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500,000 inquiries monthly, regarding services on citizenship and immigration in the US.

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Please help update this article to reflect recent events or newly available information.

5807: 5787: 5511: 4992: 4842: 4235: 4210: 4008: 3981: 3590:. CHI '17. New York, NY, USA: Association for Computing Machinery. pp. 3506–3510. 3532:"What Makes Users Trust a Chatbot for Customer Service? An Exploratory Interview Study" 2099: 2062: 1832: 1513:, for one, has reportedly launched a chatbot named Mila to automate certain simple yet 1410: 1345: 1249: 1034: 886: 417: 154: 5081:

Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems – CHI '19

3982:"Physicians' Perceptions of Chatbots in Health Care: Cross-Sectional Web-Based Survey" 3658: 2686: 1468:

Previous generations of chatbots were present on company websites, e.g. Ask Jenn from

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has been used as the basis for chatbot-based educational toys for companies such as

6050: 2471: 2318:"2017 Messenger Bot Landscape, a Public Spreadsheet Gathering 1000+ Messenger Bots" 2067: 2037: 1816: 1698: 1534: 1167: 1038: 5136: 3240: 3109:"Podrás hacer 'check in' y consultar tu vuelo con Aeroméxico a través de WhatsApp" 80: 4896: 4815:"From Russia With Love: How I got fooled (and somewhat humiliated) by a computer" 3543: 3530:

Følstad, Asbjørn; Nordheim, Cecilie Bertinussen; Bjørkli, Cato Alexander (2018).

2736: 2356: 6007: 5887: 5600: 5516: 5493: 5441: 5305: 4784:"Elemental's smart connected toy taps IBM's Watson supercomputer for its brains" 4441:[Danes want to enter the political scene with artificial intelligence]. 2655: 2411: 2304:"GPT-4 takes the world by storm - List of companies that integrated the chatbot" 1958: 1904: 1642: 1542: 1357: 1253: 1222: 1163: 1155: 611: 105: 4209:

Nadarzynski, Tom; Miles, Oliver; Cowie, Aimee; Ridge, Damien (1 January 2019).

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also launched a Facebook chatbot, making it the first bank to do so in Africa.

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Xu, Anbang; Liu, Zhe; Guo, Yufan; Sinha, Vibha; Akkiraju, Rama (2 May 2017).

2780: 2695: 2390: 2364: 2345:"Beware of botshit: How to manage the epistemic risks of generative chatbots" 5478: 5088: 4572: 4476: 4115:"India's Coronavirus Chatbot on WhatsApp Crosses 1.7 Crore Users in 10 Days" 3923: 3595: 3588:

Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems

3392:"Rare Carat's Watson-powered chatbot will help you put a diamond ring on it" 1811: 1804: 1759: 1439: 1365: 1127:. Companies spanning a wide range of industries have begun using the latest 1077: 919: 700: 5186:"Eating disorder helpline fires AI for harmful advice after sacking humans" 4244: 4067: 4017: 2837: 5374: 3583: 2829: 2462: 2101:

Proceedings of the Eleventh National Conference on Artificial Intelligence

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company Rare Carat to provide information to prospective diamond buyers.

1480:-powered "Rocky", introduced in February 2017 by the New York City-based 1318: 1300: 1292: 5017: 3793: 1291:, and has since been adopted by various other developers of, so-called, 5948: 5928: 5802: 5546: 5461: 5201:"US eating disorder helpline takes down AI chatbot over harmful advice" 4743: 3199:"Better believe the bot boom is blowing up big for B2B, B2C businesses" 2343:

Hannigan, Timothy R.; McCarthy, Ian P.; Spicer, André (20 March 2024).

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Used by marketers to script sequences of messages, very similar to an

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systems that are capable of maintaining a conversation with a user in

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doll was marketed as a line of 18-inch (46 cm) dolls which uses

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In 2022, the chatbot "Leader Lars" or "Leder Lars" was nominated for

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processes when requesting sick leave. Other large companies such as

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through text or voice interactions. Modern chatbots are typically

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technologies to power more advanced developments in such areas.

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chatbot business ecosystem has been steadily growing since the

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Although chatbots have existed since the late 1960s, the field

5943: 1755: 1576: 1428: 1418: 1414: 31: 4676:"Conversational Toys – The Latest Trend in Speech Technology" 2165:

Caldarini, Guendalina; Jaf, Sardar; McGarry, Kenneth (2022).

1907:

workers may be particularly at risk from AI-driven chatbots.

1773:

intended to interact with children for educational purposes.

1762:

stack and its use of data collected from the child's speech.

1037:

application or web interface that is designed to mimic human

2908: 2621:– Transcript of a session between Parry and Eliza. (This is 1248:

From 1978 to some time after 1983, the CYRUS project led by

1264:, and updated its database daily by parsing wire news from 1213:

Among the most notable early chatbots are ELIZA (1966) and

3052:"KLM claims airline first with WhatsApp Business Platform" 2656:

Memory organization for natural language data-base inquiry

3768:"Absa launches 'world-first' Facebook Messenger banking" 978:

List of datasets in computer vision and image processing

5264:"How chatbots are killing jobs (and creating new ones)" 4288:

Wellington, Victoria University of (15 December 2017).

3951:"AI chatbots have a future in healthcare, with caveats" 1162:" was published, which proposed what is now called the 3651:"How to Manage Customer Service Technology Innovation" 1310:

Jabberwacky learns new responses and context based on

1115:

A major area where chatbots have long been used is in

5047:"Meet 11 of the Most Interesting Chatbots in Banking" 4146:"COVID-19: Govt of India launches a WhatsApp chatbot" 3855:"Meet 11 of the Most Interesting Chatbots in Banking" 2723:

Dennett, Daniel C. (2004), Teuscher, Christof (ed.),

1533:

are now using automated online assistants instead of

4997:

Concurrency and Computation: Practice and Experience

3708:"Facebook launches Messenger platform with chatbots" 3584:"A New Chatbot for Customer Service on Social Media" 2167:"A Literature Survey of Recent Advances in Chatbots" 1295:. Nevertheless, A.L.I.C.E. is still purely based on 1287:

called AIML, which is specific to its function as a

6124: 6079: 6034: 6006: 5966: 5911: 5833: 5821: 5752: 5709: 5681: 5629: 5492: 5434: 5342:

Designing bots: Creating conversational experiences

4669: 4667: 3475:"Facebook opens its Messenger platform to chatbots" 2484:Güzeldere, Güven; Franchi, Stefano (24 July 1995), 1537:with humans to provide a first point of contact. A 1497:sequences to deliver the correct response message. 5344:(First ed.). Sebastopol, CA: O'Reilly Media. 5234:"How talking machines are taking call center jobs" 3083:"Aeroméxico te atenderá por WhatsApp durante 2018" 2884:"Amazon announces Q, an AI chatbot for businesses" 2731:, Berlin, Heidelberg: Springer, pp. 295–316, 4930:"How Twitter bots get people to spread fake news" 4321:"This virtual politician wants to run for office" 3231:The Essential Role of Language in Survey Research 2210:"Chatbots: History, technology, and applications" 2208:Adamopoulou, Eleni; Moussiades, Lefteris (2020). 1061:, but simpler chatbots have existed for decades. 2414:(1950), "Computing Machinery and Intelligence", 1611:The France's third-largest bank by total assets 1241:was published, allegedly written by the chatbot 2729:Alan Turing: Life and Legacy of a Great Thinker 2379:"Transcript: Ezra Klein Interviews Gary Marcus" 1781:Malicious chatbots are frequently used to fill 4889:Advances in Computational Intelligence Systems 3738:"Российский банк запустил чат-бота в Facebook" 3445:"Chatbots Are Your Newest, Dumbest Co-Workers" 3418:"10 ways you may have already used IBM Watson" 3326: 3324: 3169:"She is the company's most effective employee" 2298: 2296: 1858:The most common limitations are listed below: 1066:gained widespread attention in the early 2020s 973:List of datasets for machine-learning research 5412: 4736:Oren Jacob, the co-founder and CEO of ToyTalk 4505:"This Danish Political Party Is Led by an AI" 3919:"Baidu is bringing AI chatbots to healthcare" 3332:"A Virtual Travel Agent With All the Answers" 2708:: CS1 maint: DOI inactive as of March 2024 ( 2438: 2436: 1682:Government by algorithm § AI politicians 1217:(1972). More recent notable programs include 1170:. This criterion depends on the ability of a 1006: 8: 4961:"Five Potential Malicious Uses For Chatbots" 1686:In New Zealand, the chatbot SAM – short for 4856:Neff, Gina; Nagy, Peter (12 October 2016). 4631:"Maharashtra launches Aaple Sarkar chatbot" 4290:"Meet the world's first virtual politician" 3882: 3880: 5830: 5626: 5419: 5405: 5397: 4382:"AI-Politicians: A Revolution In Politics" 3794:"The Biggest French Banks by Total Assets" 2659:. Advanced Research Projects Agency, 1978. 1013: 999: 91: 5040: 5038: 5036: 5016: 4234: 4007: 3997: 3551: 3297:"80% of businesses want chatbots by 2020" 3239: 3139:"Building for People, and Now Businesses" 2939:"Meet the DBpedia Chatbot | DBpedia" 2819: 2685: 2635:The Policeman's Beard is Half Constructed 2603: 2461: 2225: 2192: 2182: 1317:, rather than being driven from a static 1239:The Policeman's Beard is Half Constructed 2090: 1988:Applications of artificial intelligence 1421:customer service, sales and marketing. 99: 23:. For bots on Internet Relay Chat, see 4862:International Journal of Communication 3032:from the original on 22 September 2017 3026:"Facebook Messenger Hits 100,000 bots" 2701: 2586:"RFC 439, PARRY Encounters the DOCTOR" 1275:One pertinent field of AI research is 4986: 4984: 4982: 4967:from the original on 24 February 2023 4940:from the original on 27 November 2018 4763:from the original on 12 December 2021 4757:"Artificial intelligence script tool" 4610:from the original on 16 December 2020 4548:from the original on 22 December 2022 4331:from the original on 1 September 2019 4269:from the original on 1 September 2019 4029: 4027: 3577: 3575: 3573: 2975:from the original on 2 September 2019 2949:from the original on 2 September 2019 2919:from the original on 8 September 2019 2851:Bastian, Matthias (29 January 2023). 2667: 2665: 2612:from the original on 20 February 2008 2112:from the original on 13 December 2007 1888:National Eating Disorders Association 1629:Artificial intelligence in healthcare 7: 5878:Simple Knowledge Organization System 4831:from the original on 19 October 2010 4782:Takahashi, Dean (23 February 2015). 4517:from the original on 13 October 2022 3986:Journal of Medical Internet Research 3718:from the original on 26 October 2019 3511:from the original on 15 January 2019 3149:from the original on 9 February 2018 3062:from the original on 5 February 2020 2863:from the original on 7 February 2023 2324:from the original on 2 February 2019 2160: 2158: 2156: 2141:from the original on 2 November 2010 1815:even possible to achieve artificial 1464:As part of company apps and websites 1382:of 2017. It can communicate through 1160:Computing Machinery and Intelligence 4928:Temming, Maria (20 November 2018). 4484:from the original on 22 August 2022 4392:from the original on 10 August 2019 4300:from the original on 3 January 2020 4036:"Role of Chat GPT in Public Health" 3931:from the original on 3 January 2020 3688:from the original on 2 January 2020 3534:. In Bodrunova, Svetlana S. (ed.). 3424:from the original on 22 August 2017 3398:from the original on 22 August 2017 3362:"Chatbot vendor directory released" 2644:. everything2.com. 13 November 1999 1457:to collect short survey responses. 1350:generative pre-trained transformers 1076:, followed by alternatives such as 968:Glossary of artificial intelligence 19:For the bot-creation software, see 16:Program that simulates conversation 5083:, ACM CHI 2020, pp. 209–219, 4717:from the original on 15 March 2015 4536:Hearing, Alice (14 October 2022). 4380:Prakash, Abishur (8 August 2018). 4361:from the original on 4 August 2019 4081:Ahaskar, Abhijit (27 March 2020). 3961:from the original on 23 March 2023 3917:Larson, Selena (11 October 2016). 3443:Greenfield, Rebecca (5 May 2016). 3372:from the original on 23 April 2017 3209:from the original on 3 August 2017 3179:from the original on 23 March 2023 2882:Novet, Jordan (28 November 2023). 2214:Machine Learning with Applications 2023:Generative artificial intelligence 1750:technology in conjunction with an 1237:abilities. In 1984, a book called 1129:generative artificial intelligence 1047:generative artificial intelligence 14: 5893:Thesaurus (information retrieval) 5270:from the original on 1 April 2019 5244:from the original on 1 April 2019 5125:Bulletin of the Atomic Scientists 5119:Stover, Dawn (3 September 2023). 5057:from the original on 1 April 2019 4643:from the original on 23 July 2020 4580:from the original on 23 July 2020 4451:from the original on 20 June 2022 4437:Sternberg, Sarah (20 June 2022). 4294:Victoria University of Wellington 4190:from the original on 23 July 2020 4158:from the original on 23 July 2020 4125:from the original on 21 June 2020 4095:from the original on 23 July 2020 3898:from the original on 1 April 2019 3865:from the original on 1 April 2019 3834:from the original on 1 April 2019 3774:from the original on 1 April 2019 3748:from the original on 1 April 2019 3631:from the original on 1 April 2019 3485:from the original on 23 June 2017 3455:from the original on 6 April 2017 3342:from the original on 15 June 2017 3309:from the original on 8 March 2018 3277:from the original on 8 March 2018 3115:. 27 October 2017. Archived from 1979:Human–computer interaction portal 1252:constructed a chatbot simulating 5385: 5373: 5158:Crimmins, Tricia (30 May 2023). 4813:Epstein, Robert (October 2007). 4794:from the original on 20 May 2015 4629:Aggarwal, Varun (5 March 2019). 4503:Xiang, Chloe (13 October 2022). 4470:Diwakar, Amar (22 August 2022). 4418:from the original on 11 May 2021 4319:Wagner, Meg (23 November 2017). 4040:Annals of Biomedical Engineering 3804:from the original on 9 July 2017 3505:"Chatbot Reference Architecture" 3394:. TechCrunch. 15 February 2017. 3267:"The AI Revolution is Underway!" 3265:Capan, Faruk (18 October 2017). 3089:from the original on 2 July 2018 3081:Forbes Staff (26 October 2017). 2522:Computer History Museum (2006), 2018:Friendly artificial intelligence 1971: 1957: 1943: 1409:Many companies' chatbots run on 1258:United States Secretary of State 1227:Agence Nationale de la Recherche 36: 5199:Aratani, Lauren (31 May 2023). 4705:Nagy, Evie (13 February 2015). 4144:Kurup, Rajesh (21 March 2020). 3234:. RTI Press. pp. 221–230. 3006:from the original on 3 May 2019 2971:. dbpedia.org. 22 August 2018. 2781:"What is ChatGPT? - MagicBuddy" 2591:Internet Engineering Task Force 2241:Hu, Krystal (2 February 2023). 5474:Natural language understanding 5184:Knight, Taylor (31 May 2023). 3420:. VentureBeat. 10 March 2017. 2767:"Chat Robots Simiulate People" 2584:Network Working Group (1973), 1556:natural-language understanding 388:Relevance vector machine (RVM) 1: 5998:Optical character recognition 5314:Behavioral and Brain Sciences 5137:10.1080/00963402.2023.2245247 5045:Marous, Jim (14 March 2018). 4259:"Sam, the virtual politician" 4034:Biswas, Som S. (1 May 2023). 3853:Marous, Jim (14 March 2018). 3241:10.3768/rtipress.bk.0023.2004 2687:10.1016/S0364-0213(83)80001-9 2562:, nettime.org, archived from 2260:Hines, Kristi (4 June 2023). 1998:Conversational user interface 1378:created a chatbot during the 1368:, which focuses on answering 877:Computational learning theory 441:Expectation–maximization (EM) 5691:Multi-document summarization 5310:"Minds, Brains and Programs" 4897:10.1007/978-3-319-97982-3_15 3544:10.1007/978-3-030-01437-7_16 2994:Beaver, Laurie (July 2016). 2737:10.1007/978-3-662-05642-4_12 2357:10.1016/j.bushor.2024.03.001 1199:capable of being interpreted 1174:to impersonate a human in a 834:Coefficient of determination 681:Convolutional neural network 393:Support vector machine (SVM) 6021:Latent Dirichlet allocation 5993:Natural language generation 5858:Machine-readable dictionary 5853:Linguistic Linked Open Data 5428:Natural language processing 4738:interviewed on the TV show 2524:"Internet History – 1970's" 2486:"Constructions of the Mind" 2053:Natural language processing 1560:natural-language generation 1277:natural-language processing 1059:natural language processing 985:Outline of machine learning 882:Empirical risk minimization 6199: 5773:Explicit semantic analysis 5522:Deep linguistic processing 4052:10.1007/s10439-023-03172-7 2969:"Meet the DBpedia Chatbot" 2690:(inactive 29 March 2024). 2490:Stanford Humanities Review 2227:10.1016/j.mlwa.2020.100006 1679: 1626: 1501:Company internal platforms 1397: 1342:artificial neural networks 1266:United Press International 622:Feedforward neural network 373:Artificial neural networks 18: 5616:Word-sense disambiguation 5469:Computational linguistics 5326:10.1017/S0140525X00005756 4822:Scientific American: Mind 3888:"Chatbots: Boon or Bane?" 3680:Smith, Sam (8 May 2019). 3366:www.hypergridbusiness.com 2556:Sondheim, Alan J (1997), 2449:Communications of the ACM 2028:Hybrid intelligent system 1688:Semantic Analysis Machine 1651:World Health Organization 1472:which debuted in 2008 or 1068:due to the popularity of 605:Artificial neural network 6183:Natural language parsing 6142:Natural Language Toolkit 6066:Pronunciation assessment 5968:Automatic identification 5798:Latent semantic analysis 5754:Distributional semantics 5639:Compound-term processing 5537:Named-entity recognition 5121:"Will AI make us crazy?" 4959:Epp, Len (11 May 2016). 4674:Amy (23 February 2015). 4227:10.1177/2055207619871808 2996:"The Chatbots Explainer" 2428:10.1093/mind/lix.236.433 1123:, with various sorts of 914:Journals and conferences 861:Mathematical foundations 771:Temporal difference (TD) 627:Recurrent neural network 547:Conditional random field 470:Dimensionality reduction 218:Dimensionality reduction 180:Quantum machine learning 175:Neuromorphic engineering 135:Self-supervised learning 130:Semi-supervised learning 6046:Automated essay scoring 6016:Document classification 5683:Automatic summarization 5294:New York Times Magazine 5089:10.1145/3290605.3300439 3596:10.1145/3025453.3025496 2640:4 February 2010 at the 2532:Computer History Museum 1849:artificial intelligence 1843:Limitations of chatbots 1649:has teamed up with the 1447:answer simple questions 1323:evolutionary algorithms 323:Apprenticeship learning 5903:Universal Dependencies 5596:Terminology extraction 5579:Semantic decomposition 5574:Semantic role labeling 5564:Part-of-speech tagging 5532:Information extraction 5517:Coreference resolution 5507:Collocation extraction 3798:Banks around the World 1903:return on investment. 1791:Windows Live Messenger 1523:Royal Bank of Scotland 1194: 1138:responses rather than 872:Bias–variance tradeoff 754:Reinforcement learning 730:Spiking neural network 140:Reinforcement learning 89: 77: 6178:Interactive narrative 5664:Sentence segmentation 5340:Shevat, Amir (2017). 2725:"Can Machines Think?" 2463:10.1145/365153.365168 2266:Search Engine Journal 1837:End-to-end encryption 1795:AOL Instant Messenger 1739:produce a storyline. 1662:The Indian Government 1388:Master of Code Global 1352:(GPT), which use the 1328:information retrieval 1189: 1105:Gemini language model 1097:large language models 708:Neural radiance field 530:Structured prediction 253:Structured prediction 125:Unsupervised learning 83: 71: 6116:Voice user interface 5827:datasets and corpora 5768:Document-term matrix 5621:Word-sense induction 5382:at Wikimedia Commons 4357:. 25 November 2017. 4221:: 2055207619871808. 3684:. Juniper Research. 3305:. 15 December 2016. 2194:10.3390/info13010041 2131:"What is a chatbot?" 2003:Dead Internet theory 1519:Lloyds Banking Group 1417:. They are used for 1289:conversational agent 1262:case-based reasoning 1134:As chatbots work by 897:Statistical learning 795:Learning with humans 587:Local outlier factor 6096:Interactive fiction 6026:Pachinko allocation 5983:Speech segmentation 5939:Google Ngram Viewer 5711:Machine translation 5701:Text simplification 5696:Sentence extraction 5584:Semantic similarity 5391:Conversational bots 5051:The Financial Brand 4686:on 21 February 2018 3859:The Financial Brand 3661:on 11 December 2019 3619:Hingrajia, Mirant. 3271:www.PM360online.com 3002:. BI Intelligence. 2830:10.1093/bib/bbac409 2653:Kolodner, Janet L. 2538:on 21 February 2008 2498:Stanford University 1890:replaced its human 1695:The Synthetic Party 1566:and deep learning. 1451:customer engagement 1158:'s famous article " 740:Electrochemical RAM 647:reservoir computing 378:Logistic regression 297:Supervised learning 283:Multimodal learning 258:Feature engineering 203:Generative modeling 165:Rule-based learning 160:Curriculum learning 120:Supervised learning 95:Part of a series on 6106:Question answering 5978:Speech recognition 5843:Corpus linguistics 5823:Language resources 5606:Textual entailment 5589:Sentiment analysis 5240:. 23 August 2018. 4824:. pp. 16–17. 4680:Virtual Agent Chat 4604:The Economic Times 3894:. 9 January 2018. 3507:. 1 January 2019. 3336:The New York Times 3175:. September 2017. 3056:www.phocuswire.com 2945:. 22 August 2018. 2769:. 11 October 2015. 2444:Weizenbaum, Joseph 2385:. 6 January 2023. 2383:The New York Times 2048:Multi-agent system 1965:Programming portal 1951:Linguistics portal 1927:Prompt Engineering 1886:In 2023, US-based 1810:If a text-sending 1748:speech recognition 1507:Internet-of-Things 1384:Facebook Messenger 1201:as "intelligent". 1166:as a criterion of 1125:virtual assistants 308: • 223:Density estimation 90: 78: 6173:Instant messaging 6155: 6154: 6111:Virtual assistant 6036:Computer-assisted 5962: 5961: 5719:Computer-assisted 5677: 5676: 5669:Word segmentation 5631:Text segmentation 5569:Semantic analysis 5557:Syntactic parsing 5542:Ontology learning 5378:Media related to 5351:978-1-4919-7482-7 5098:978-1-4503-5970-2 4906:978-3-319-97982-3 4510:Vice: Motherboard 3714:. 12 April 2016. 3605:978-1-4503-4655-9 3563:978-3-030-01437-7 3481:. 12 April 2016. 3251:978-1-934831-24-3 3028:. 18 April 2017. 2909:"DBpedia Chatbot" 2746:978-3-662-05642-4 2674:Cognitive Science 2349:Business Horizons 2073:Stochastic parrot 2033:Intelligent agent 1898:Chatbots and jobs 1799:instant messaging 1488:Chatbot sequences 1400:Virtual assistant 1340:Chatbots may use 1315:user interactions 1305:logical reasoning 1181:Joseph Weizenbaum 1023: 1022: 828:Model diagnostics 811:Human-in-the-loop 654:Boltzmann machine 567:Anomaly detection 363:Linear regression 278:Ontology learning 273:Grammar induction 248:Semantic analysis 243:Association rules 228:Anomaly detection 170:Neuro-symbolic AI 74:virtual assistant 66: 65: 6190: 6132:Formal semantics 6081:Natural language 5988:Speech synthesis 5970:and data capture 5873:Semantic network 5848:Lexical resource 5831: 5649:Lexical analysis 5627: 5552:Semantic parsing 5421: 5414: 5407: 5398: 5389: 5377: 5363: 5336: 5280: 5279: 5277: 5275: 5266:. 18 June 2017. 5260: 5254: 5253: 5251: 5249: 5230: 5224: 5223: 5221: 5219: 5196: 5190: 5189: 5181: 5175: 5174: 5172: 5170: 5155: 5149: 5148: 5116: 5110: 5109: 5077:Grudin, Jonathan 5073: 5067: 5066: 5064: 5062: 5042: 5031: 5030: 5020: 5009:10.1002/cpe.6426 4988: 4977: 4976: 4974: 4972: 4956: 4950: 4949: 4947: 4945: 4925: 4919: 4918: 4884: 4878: 4877: 4853: 4847: 4840: 4838: 4836: 4830: 4819: 4810: 4804: 4803: 4801: 4799: 4779: 4773: 4772: 4770: 4768: 4753: 4747: 4733: 4727: 4726: 4724: 4722: 4702: 4696: 4695: 4693: 4691: 4682:. Archived from 4671: 4662: 4659: 4653: 4652: 4650: 4648: 4626: 4620: 4619: 4617: 4615: 4596: 4590: 4589: 4587: 4585: 4576:. 5 March 2019. 4564: 4558: 4557: 4555: 4553: 4533: 4527: 4526: 4524: 4522: 4500: 4494: 4493: 4491: 4489: 4467: 4461: 4460: 4458: 4456: 4434: 4428: 4427: 4425: 4423: 4408: 4402: 4401: 4399: 4397: 4377: 4371: 4370: 4368: 4366: 4347: 4341: 4340: 4338: 4336: 4316: 4310: 4309: 4307: 4305: 4285: 4279: 4278: 4276: 4274: 4255: 4249: 4248: 4238: 4206: 4200: 4199: 4197: 4195: 4186:. 7 April 2020. 4174: 4168: 4167: 4165: 4163: 4141: 4135: 4134: 4132: 4130: 4119:NDTV Gadgets 360 4111: 4105: 4104: 4102: 4100: 4078: 4072: 4071: 4031: 4022: 4021: 4011: 4001: 3977: 3971: 3970: 3968: 3966: 3955:AI in Healthcare 3947: 3941: 3940: 3938: 3936: 3914: 3908: 3907: 3905: 3903: 3884: 3875: 3874: 3872: 3870: 3850: 3844: 3843: 3841: 3839: 3830:. 19 June 2018. 3828:Marketing Client 3820: 3814: 3813: 3811: 3809: 3790: 3784: 3783: 3781: 3779: 3770:. 19 July 2016. 3764: 3758: 3757: 3755: 3753: 3744:. 13 July 2016. 3734: 3728: 3727: 3725: 3723: 3704: 3698: 3697: 3695: 3693: 3677: 3671: 3670: 3668: 3666: 3657:. Archived from 3647: 3641: 3640: 3638: 3636: 3616: 3610: 3609: 3579: 3568: 3567: 3555: 3536:Internet Science 3527: 3521: 3520: 3518: 3516: 3501: 3495: 3494: 3492: 3490: 3471: 3465: 3464: 3462: 3460: 3440: 3434: 3433: 3431: 3429: 3414: 3408: 3407: 3405: 3403: 3388: 3382: 3381: 3379: 3377: 3368:. October 2011. 3358: 3352: 3351: 3349: 3347: 3338:. 4 March 2008. 3328: 3319: 3318: 3316: 3314: 3302:Business Insider 3293: 3287: 3286: 3284: 3282: 3262: 3256: 3255: 3243: 3225: 3219: 3218: 3216: 3214: 3205:. 24 July 2016. 3195: 3189: 3188: 3186: 3184: 3165: 3159: 3158: 3156: 3154: 3135: 3129: 3128: 3126: 3124: 3119:on 10 March 2018 3105: 3099: 3098: 3096: 3094: 3078: 3072: 3071: 3069: 3067: 3048: 3042: 3041: 3039: 3037: 3022: 3016: 3015: 3013: 3011: 3000:Business Insider 2991: 2985: 2984: 2982: 2980: 2965: 2959: 2958: 2956: 2954: 2943:wiki.dbpedia.org 2935: 2929: 2928: 2926: 2924: 2913:chat.dbpedia.org 2905: 2899: 2898: 2896: 2894: 2879: 2873: 2872: 2870: 2868: 2848: 2842: 2841: 2823: 2803: 2797: 2796: 2794: 2792: 2777: 2771: 2770: 2763: 2757: 2756: 2755: 2753: 2720: 2714: 2713: 2707: 2699: 2689: 2669: 2660: 2651: 2645: 2632: 2626: 2620: 2619: 2617: 2607: 2605:10.17487/RFC0439 2596:Internet Society 2581: 2575: 2574: 2573: 2571: 2553: 2547: 2546: 2545: 2543: 2534:, archived from 2519: 2513: 2512: 2511: 2509: 2500:, archived from 2481: 2475: 2474: 2465: 2440: 2431: 2430: 2422:(236): 433–460, 2408: 2402: 2401: 2399: 2397: 2375: 2369: 2368: 2340: 2334: 2333: 2331: 2329: 2314: 2308: 2307: 2306:. 21 March 2023. 2300: 2291: 2290: 2283: 2277: 2276: 2274: 2272: 2257: 2251: 2250: 2238: 2232: 2231: 2229: 2205: 2199: 2198: 2196: 2186: 2162: 2151: 2150: 2148: 2146: 2127: 2121: 2120: 2119: 2117: 2095: 2043:List of chatbots 1993:Autonomous agent 1981: 1976: 1975: 1974: 1967: 1962: 1961: 1953: 1948: 1947: 1853:machine learning 1787:Yahoo! Messenger 1637:The GPT chatbot 1613:Société Générale 1570:Customer service 1564:machine learning 1545:Conference when 1509:(IoT) projects. 1297:pattern matching 1172:computer program 1117:customer service 1051:natural language 1015: 1008: 1001: 962:Related articles 839:Confusion matrix 592:Isolation forest 537:Graphical models 316: 315: 268:Learning to rank 263:Feature learning 101:Machine learning 92: 61: 58: 52: 40: 39: 32: 6198: 6197: 6193: 6192: 6191: 6189: 6188: 6187: 6158: 6157: 6156: 6151: 6120: 6100:Syntax guessing 6082: 6075: 6061:Predictive text 6056:Grammar checker 6037: 6030: 6002: 5969: 5958: 5924:Bank of English 5907: 5835: 5826: 5817: 5748: 5705: 5673: 5625: 5527:Distant reading 5502:Argument mining 5488: 5484:Text processing 5430: 5425: 5370: 5352: 5339: 5304: 5296:(18 July 2023) 5289: 5287:Further reading 5284: 5283: 5273: 5271: 5262: 5261: 5257: 5247: 5245: 5232: 5231: 5227: 5217: 5215: 5198: 5197: 5193: 5183: 5182: 5178: 5168: 5166: 5157: 5156: 5152: 5118: 5117: 5113: 5099: 5075: 5074: 5070: 5060: 5058: 5044: 5043: 5034: 4990: 4989: 4980: 4970: 4968: 4958: 4957: 4953: 4943: 4941: 4927: 4926: 4922: 4907: 4886: 4885: 4881: 4855: 4854: 4850: 4834: 4832: 4828: 4817: 4812: 4811: 4807: 4797: 4795: 4781: 4780: 4776: 4766: 4764: 4755: 4754: 4750: 4734: 4730: 4720: 4718: 4704: 4703: 4699: 4689: 4687: 4673: 4672: 4665: 4660: 4656: 4646: 4644: 4628: 4627: 4623: 4613: 4611: 4598: 4597: 4593: 4583: 4581: 4566: 4565: 4561: 4551: 4549: 4535: 4534: 4530: 4520: 4518: 4502: 4501: 4497: 4487: 4485: 4469: 4468: 4464: 4454: 4452: 4444:Jyllands-Posten 4436: 4435: 4431: 4421: 4419: 4410: 4409: 4405: 4395: 4393: 4379: 4378: 4374: 4364: 4362: 4349: 4348: 4344: 4334: 4332: 4318: 4317: 4313: 4303: 4301: 4287: 4286: 4282: 4272: 4270: 4263:Tuia Innovation 4257: 4256: 4252: 4208: 4207: 4203: 4193: 4191: 4183:Hindustan Times 4176: 4175: 4171: 4161: 4159: 4143: 4142: 4138: 4128: 4126: 4113: 4112: 4108: 4098: 4096: 4080: 4079: 4075: 4033: 4032: 4025: 3979: 3978: 3974: 3964: 3962: 3949: 3948: 3944: 3934: 3932: 3916: 3915: 3911: 3901: 3899: 3886: 3885: 3878: 3868: 3866: 3852: 3851: 3847: 3837: 3835: 3822: 3821: 3817: 3807: 3805: 3792: 3791: 3787: 3777: 3775: 3766: 3765: 3761: 3751: 3749: 3736: 3735: 3731: 3721: 3719: 3706: 3705: 3701: 3691: 3689: 3679: 3678: 3674: 3664: 3662: 3655:www.gartner.com 3649: 3648: 3644: 3634: 3632: 3618: 3617: 3613: 3606: 3581: 3580: 3571: 3564: 3529: 3528: 3524: 3514: 3512: 3503: 3502: 3498: 3488: 3486: 3473: 3472: 3468: 3458: 3456: 3442: 3441: 3437: 3427: 3425: 3416: 3415: 3411: 3401: 3399: 3390: 3389: 3385: 3375: 3373: 3360: 3359: 3355: 3345: 3343: 3330: 3329: 3322: 3312: 3310: 3295: 3294: 3290: 3280: 3278: 3264: 3263: 3259: 3252: 3227: 3226: 3222: 3212: 3210: 3197: 3196: 3192: 3182: 3180: 3167: 3166: 3162: 3152: 3150: 3137: 3136: 3132: 3122: 3120: 3113:Huffington Post 3107: 3106: 3102: 3092: 3090: 3080: 3079: 3075: 3065: 3063: 3050: 3049: 3045: 3035: 3033: 3024: 3023: 3019: 3009: 3007: 2993: 2992: 2988: 2978: 2976: 2967: 2966: 2962: 2952: 2950: 2937: 2936: 2932: 2922: 2920: 2907: 2906: 2902: 2892: 2890: 2881: 2880: 2876: 2866: 2864: 2850: 2849: 2845: 2808:Brief Bioinform 2805: 2804: 2800: 2790: 2788: 2779: 2778: 2774: 2765: 2764: 2760: 2751: 2749: 2747: 2722: 2721: 2717: 2700: 2671: 2670: 2663: 2652: 2648: 2642:Wayback Machine 2633: 2629: 2615: 2613: 2583: 2582: 2578: 2569: 2567: 2566:on 13 June 2008 2555: 2554: 2550: 2541: 2539: 2521: 2520: 2516: 2507: 2505: 2504:on 11 July 2007 2483: 2482: 2478: 2442: 2441: 2434: 2410: 2409: 2405: 2395: 2393: 2377: 2376: 2372: 2342: 2341: 2337: 2327: 2325: 2316: 2315: 2311: 2302: 2301: 2294: 2285: 2284: 2280: 2270: 2268: 2259: 2258: 2254: 2240: 2239: 2235: 2207: 2206: 2202: 2177:(1). MDPI: 41. 2164: 2163: 2154: 2144: 2142: 2129: 2128: 2124: 2115: 2113: 2097: 2096: 2092: 2087: 2082: 2013:Eugene Goostman 2008:Dialogue system 1977: 1972: 1970: 1963: 1956: 1949: 1942: 1939: 1900: 1845: 1825: 1779: 1767:Watson computer 1744:My Friend Cayla 1727: 1718: 1703:political party 1684: 1678: 1631: 1625: 1606:Barclays Africa 1572: 1551:Mark Zuckerberg 1503: 1490: 1470:Alaska Airlines 1466: 1455:market research 1407: 1402: 1396: 1348:. For example, 1285:markup language 1211: 1152: 1019: 990: 989: 963: 955: 954: 915: 907: 906: 867:Kernel machines 862: 854: 853: 829: 821: 820: 801:Active learning 796: 788: 787: 756: 746: 745: 671:Diffusion model 607: 597: 596: 569: 559: 558: 532: 522: 521: 477:Factor analysis 472: 462: 461: 445: 408: 398: 397: 318: 317: 301: 300: 299: 288: 287: 193: 185: 184: 150:Online learning 115: 103: 62: 56: 53: 50: 41: 37: 28: 17: 12: 11: 5: 6196: 6194: 6186: 6185: 6180: 6175: 6170: 6160: 6159: 6153: 6152: 6150: 6149: 6144: 6139: 6134: 6128: 6126: 6122: 6121: 6119: 6118: 6113: 6108: 6103: 6093: 6087: 6085: 6083:user interface 6077: 6076: 6074: 6073: 6068: 6063: 6058: 6053: 6048: 6042: 6040: 6032: 6031: 6029: 6028: 6023: 6018: 6012: 6010: 6004: 6003: 6001: 6000: 5995: 5990: 5985: 5980: 5974: 5972: 5964: 5963: 5960: 5959: 5957: 5956: 5951: 5946: 5941: 5936: 5931: 5926: 5921: 5915: 5913: 5909: 5908: 5906: 5905: 5900: 5895: 5890: 5885: 5880: 5875: 5870: 5865: 5860: 5855: 5850: 5845: 5839: 5837: 5828: 5819: 5818: 5816: 5815: 5810: 5808:Word embedding 5805: 5800: 5795: 5788:Language model 5785: 5780: 5775: 5770: 5765: 5759: 5757: 5750: 5749: 5747: 5746: 5741: 5739:Transfer-based 5736: 5731: 5726: 5721: 5715: 5713: 5707: 5706: 5704: 5703: 5698: 5693: 5687: 5685: 5679: 5678: 5675: 5674: 5672: 5671: 5666: 5661: 5656: 5651: 5646: 5641: 5635: 5633: 5624: 5623: 5618: 5613: 5608: 5603: 5598: 5592: 5591: 5586: 5581: 5576: 5571: 5566: 5561: 5560: 5559: 5554: 5544: 5539: 5534: 5529: 5524: 5519: 5514: 5512:Concept mining 5509: 5504: 5498: 5496: 5490: 5489: 5487: 5486: 5481: 5476: 5471: 5466: 5465: 5464: 5459: 5449: 5444: 5438: 5436: 5432: 5431: 5426: 5424: 5423: 5416: 5409: 5401: 5395: 5394: 5383: 5369: 5368:External links 5366: 5365: 5364: 5350: 5337: 5320:(3): 417–457, 5301: 5300: 5288: 5285: 5282: 5281: 5255: 5225: 5191: 5176: 5150: 5131:(5): 299–303. 5111: 5097: 5068: 5032: 4978: 4951: 4920: 4905: 4879: 4848: 4843:Robert Epstein 4805: 4774: 4748: 4728: 4697: 4663: 4654: 4621: 4591: 4559: 4528: 4495: 4462: 4429: 4403: 4372: 4342: 4311: 4280: 4250: 4215:Digital Health 4201: 4169: 4136: 4121:. April 2020. 4106: 4073: 4046:(5): 868–869. 4023: 3972: 3942: 3909: 3876: 3845: 3815: 3785: 3759: 3729: 3699: 3672: 3642: 3611: 3604: 3569: 3562: 3522: 3496: 3466: 3435: 3409: 3383: 3353: 3320: 3288: 3257: 3250: 3220: 3190: 3160: 3130: 3100: 3073: 3043: 3017: 2986: 2960: 2930: 2900: 2874: 2843: 2798: 2772: 2758: 2745: 2715: 2680:(4): 243–280. 2661: 2646: 2627: 2576: 2548: 2514: 2476: 2432: 2403: 2370: 2335: 2320:. 3 May 2017. 2309: 2292: 2278: 2252: 2233: 2200: 2152: 2135:techtarget.com 2122: 2089: 2088: 2086: 2083: 2081: 2080: 2075: 2070: 2065: 2063:Software agent 2060: 2055: 2050: 2045: 2040: 2035: 2030: 2025: 2020: 2015: 2010: 2005: 2000: 1995: 1990: 1984: 1983: 1982: 1968: 1954: 1938: 1935: 1899: 1896: 1884: 1883: 1880: 1876: 1873: 1869: 1866: 1863: 1844: 1841: 1833:authentication 1824: 1821: 1778: 1775: 1726: 1723: 1717: 1714: 1697:to run in the 1677: 1674: 1624: 1621: 1604:In July 2016, 1571: 1568: 1515:time-consuming 1502: 1499: 1489: 1486: 1465: 1462: 1413:or simply via 1411:messaging apps 1406: 1405:Messaging apps 1403: 1395: 1392: 1346:language model 1250:Janet Kolodner 1210: 1207: 1151: 1148: 1144:hallucinations 1021: 1020: 1018: 1017: 1010: 1003: 995: 992: 991: 988: 987: 982: 981: 980: 970: 964: 961: 960: 957: 956: 953: 952: 947: 942: 937: 932: 927: 922: 916: 913: 912: 909: 908: 905: 904: 899: 894: 889: 887:Occam learning 884: 879: 874: 869: 863: 860: 859: 856: 855: 852: 851: 846: 844:Learning curve 841: 836: 830: 827: 826: 823: 822: 819: 818: 813: 808: 803: 797: 794: 793: 790: 789: 786: 785: 784: 783: 773: 768: 763: 757: 752: 751: 748: 747: 744: 743: 737: 732: 727: 722: 721: 720: 710: 705: 704: 703: 698: 693: 688: 678: 673: 668: 663: 662: 661: 651: 650: 649: 644: 639: 634: 624: 619: 614: 608: 603: 602: 599: 598: 595: 594: 589: 584: 576: 570: 565: 564: 561: 560: 557: 556: 555: 554: 549: 544: 533: 528: 527: 524: 523: 520: 519: 514: 509: 504: 499: 494: 489: 484: 479: 473: 468: 467: 464: 463: 460: 459: 454: 449: 443: 438: 433: 425: 420: 415: 409: 404: 403: 400: 399: 396: 395: 390: 385: 380: 375: 370: 365: 360: 352: 351: 350: 345: 340: 330: 328:Decision trees 325: 319: 305:classification 295: 294: 293: 290: 289: 286: 285: 280: 275: 270: 265: 260: 255: 250: 245: 240: 235: 230: 225: 220: 215: 210: 205: 200: 198:Classification 194: 191: 190: 187: 186: 183: 182: 177: 172: 167: 162: 157: 155:Batch learning 152: 147: 142: 137: 132: 127: 122: 116: 113: 112: 109: 108: 97: 96: 64: 63: 44: 42: 35: 15: 13: 10: 9: 6: 4: 3: 2: 6195: 6184: 6181: 6179: 6176: 6174: 6171: 6169: 6166: 6165: 6163: 6148: 6145: 6143: 6140: 6138: 6137:Hallucination 6135: 6133: 6130: 6129: 6127: 6123: 6117: 6114: 6112: 6109: 6107: 6104: 6101: 6097: 6094: 6092: 6089: 6088: 6086: 6084: 6078: 6072: 6071:Spell checker 6069: 6067: 6064: 6062: 6059: 6057: 6054: 6052: 6049: 6047: 6044: 6043: 6041: 6039: 6033: 6027: 6024: 6022: 6019: 6017: 6014: 6013: 6011: 6009: 6005: 5999: 5996: 5994: 5991: 5989: 5986: 5984: 5981: 5979: 5976: 5975: 5973: 5971: 5965: 5955: 5952: 5950: 5947: 5945: 5942: 5940: 5937: 5935: 5932: 5930: 5927: 5925: 5922: 5920: 5917: 5916: 5914: 5910: 5904: 5901: 5899: 5896: 5894: 5891: 5889: 5886: 5884: 5883:Speech corpus 5881: 5879: 5876: 5874: 5871: 5869: 5866: 5864: 5863:Parallel text 5861: 5859: 5856: 5854: 5851: 5849: 5846: 5844: 5841: 5840: 5838: 5832: 5829: 5824: 5820: 5814: 5811: 5809: 5806: 5804: 5801: 5799: 5796: 5793: 5789: 5786: 5784: 5781: 5779: 5776: 5774: 5771: 5769: 5766: 5764: 5761: 5760: 5758: 5755: 5751: 5745: 5742: 5740: 5737: 5735: 5732: 5730: 5727: 5725: 5724:Example-based 5722: 5720: 5717: 5716: 5714: 5712: 5708: 5702: 5699: 5697: 5694: 5692: 5689: 5688: 5686: 5684: 5680: 5670: 5667: 5665: 5662: 5660: 5657: 5655: 5654:Text chunking 5652: 5650: 5647: 5645: 5644:Lemmatisation 5642: 5640: 5637: 5636: 5634: 5632: 5628: 5622: 5619: 5617: 5614: 5612: 5609: 5607: 5604: 5602: 5599: 5597: 5594: 5593: 5590: 5587: 5585: 5582: 5580: 5577: 5575: 5572: 5570: 5567: 5565: 5562: 5558: 5555: 5553: 5550: 5549: 5548: 5545: 5543: 5540: 5538: 5535: 5533: 5530: 5528: 5525: 5523: 5520: 5518: 5515: 5513: 5510: 5508: 5505: 5503: 5500: 5499: 5497: 5495: 5494:Text analysis 5491: 5485: 5482: 5480: 5477: 5475: 5472: 5470: 5467: 5463: 5460: 5458: 5455: 5454: 5453: 5450: 5448: 5445: 5443: 5440: 5439: 5437: 5435:General terms 5433: 5429: 5422: 5417: 5415: 5410: 5408: 5403: 5402: 5399: 5392: 5388: 5384: 5381: 5376: 5372: 5371: 5367: 5361: 5357: 5353: 5347: 5343: 5338: 5335: 5331: 5327: 5323: 5319: 5315: 5311: 5307: 5303: 5302: 5299: 5295: 5291: 5290: 5286: 5269: 5265: 5259: 5256: 5243: 5239: 5235: 5229: 5226: 5214: 5210: 5206: 5202: 5195: 5192: 5187: 5180: 5177: 5165: 5164:The Daily Dot 5161: 5154: 5151: 5146: 5142: 5138: 5134: 5130: 5126: 5122: 5115: 5112: 5108: 5104: 5100: 5094: 5090: 5086: 5082: 5078: 5072: 5069: 5056: 5052: 5048: 5041: 5039: 5037: 5033: 5028: 5024: 5019: 5014: 5010: 5006: 5002: 4998: 4994: 4987: 4985: 4983: 4979: 4966: 4962: 4955: 4952: 4939: 4935: 4931: 4924: 4921: 4916: 4912: 4908: 4902: 4898: 4894: 4890: 4883: 4880: 4875: 4871: 4867: 4863: 4859: 4852: 4849: 4844: 4841:Psychologist 4827: 4823: 4816: 4809: 4806: 4793: 4789: 4785: 4778: 4775: 4762: 4758: 4752: 4749: 4745: 4741: 4740:Triangulation 4737: 4732: 4729: 4716: 4712: 4708: 4701: 4698: 4685: 4681: 4677: 4670: 4668: 4664: 4658: 4655: 4642: 4638: 4637: 4636:Business Line 4632: 4625: 4622: 4609: 4605: 4601: 4595: 4592: 4579: 4575: 4574: 4569: 4563: 4560: 4547: 4543: 4539: 4532: 4529: 4516: 4512: 4511: 4506: 4499: 4496: 4483: 4479: 4478: 4473: 4466: 4463: 4450: 4446: 4445: 4440: 4433: 4430: 4417: 4413: 4412:"SAM website" 4407: 4404: 4391: 4387: 4383: 4376: 4373: 4360: 4356: 4352: 4346: 4343: 4330: 4326: 4322: 4315: 4312: 4299: 4295: 4291: 4284: 4281: 4268: 4264: 4260: 4254: 4251: 4246: 4242: 4237: 4232: 4228: 4224: 4220: 4216: 4212: 4205: 4202: 4189: 4185: 4184: 4179: 4173: 4170: 4157: 4153: 4152: 4151:Business Line 4147: 4140: 4137: 4124: 4120: 4116: 4110: 4107: 4094: 4090: 4089: 4084: 4077: 4074: 4069: 4065: 4061: 4057: 4053: 4049: 4045: 4041: 4037: 4030: 4028: 4024: 4019: 4015: 4010: 4005: 4000: 3999:10.2196/12887 3995: 3992:(4): e12887. 3991: 3987: 3983: 3976: 3973: 3960: 3956: 3952: 3946: 3943: 3930: 3926: 3925: 3920: 3913: 3910: 3897: 3893: 3889: 3883: 3881: 3877: 3864: 3860: 3856: 3849: 3846: 3833: 3829: 3825: 3819: 3816: 3803: 3799: 3795: 3789: 3786: 3773: 3769: 3763: 3760: 3747: 3743: 3739: 3733: 3730: 3717: 3713: 3709: 3703: 3700: 3687: 3683: 3676: 3673: 3660: 3656: 3652: 3646: 3643: 3630: 3626: 3622: 3615: 3612: 3607: 3601: 3597: 3593: 3589: 3585: 3578: 3576: 3574: 3570: 3565: 3559: 3554: 3553:11250/2571164 3549: 3545: 3541: 3537: 3533: 3526: 3523: 3510: 3506: 3500: 3497: 3484: 3480: 3476: 3470: 3467: 3454: 3450: 3449:Bloomberg.com 3446: 3439: 3436: 3423: 3419: 3413: 3410: 3397: 3393: 3387: 3384: 3371: 3367: 3363: 3357: 3354: 3341: 3337: 3333: 3327: 3325: 3321: 3308: 3304: 3303: 3298: 3292: 3289: 3276: 3272: 3268: 3261: 3258: 3253: 3247: 3242: 3237: 3233: 3232: 3224: 3221: 3208: 3204: 3200: 3194: 3191: 3178: 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