- Also known as:
- chatterbot
- Related Topics:
- Amazon Alexa
- ChatGPT
- Siri
- Claude AI
- Eliza
chatbot
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What is a chatbot?
A chatbot is a computer program designed to simulate conversation with humans through automated interaction. The concept of chatbots dates back to the mid-to-late 20th century. One of the earliest examples was ELIZA, developed in 1966, which simulated conversation by using pattern-recognition algorithms to generate responses. Chatbots became more advanced in the 2000s and 2010s, with the release of programs such as SmarterChild on AOL Instant Messenger. Today, chatbots are used in various applications, from virtual assistants like Siri and Alexa to generative AI models like ChatGPT.
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How does a chatbot work?
A chatbot is a computer program designed to simulate conversation with humans through automated interactions. Modern chatbots use natural language processing (NLP) to process and parse language in a way that is similar to how humans do. NLP models use computational linguistics, statistics, machine learning, and deep-learning models.
Large language models (LLM) employ AI and statistics to predict the final form of a sentence based on existing portions. These models use parameters, or variables and weights, to influence the prediction outcome. Modern NLP systems use deep-learning models and techniques that help them to "learn" as they process information.
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What are some common uses for chatbots?
Chatbots are computer programs designed for automated conversation with humans. They have become more advanced with the rise of artificial intelligence (AI).
Common uses for chatbots:
* Virtual assistants like Siri and Alexa perform simple tasks through voice commands, such as setting alarms and searching the Internet.
* Generative AI chatbots, like ChatGPT, can draft articles and computer code, and respond to emails.
* AI chatbots can teach users about financial concepts and provide best practices to improve spending habits. They can generate summaries, guides, and tutorials tailored for different expertise levels.2 Britannica SourcesCreated from Britannica articles using AI. AI can make mistakes, so verify using Britannica articles. -
How do chatbots understand what people say?
Chatbots use natural language processing (NLP) to understand human language through computational linguistics, statistics, machine learning, and deep-learning models. Modern NLP systems utilize deep-learning techniques to learn while processing information. These systems predict sentence structure using AI and statistical methods. Large language models (LLM) use parameters, variables, and weights to predict outcomes based on vast amounts of data.
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What is the difference between a rule-based and an AI chatbot?
Chatbots use varied methods to engage in conversations. Rule-based chatbots use pre-programmed rules to answer questions, but they don't account for the nuances of language. AI chatbots use natural language processing (NLP) to parse language in a way that mirrors human ability, using computational linguistics, statistics, machine learning, and deep-learning models.
AI chatbots can predict the final form of a sentence on the basis of existing portions. Modern NLP systems also use deep-learning models and techniques that help them to learn as they process information.
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How can chatbots improve their responses over time?
Chatbots enhance their responses through natural language processing (NLP), which enables them to process and parse language in a human-like manner. Modern NLP systems use deep-learning models to "learn" from the data they process, improving accuracy over time.
One method to combat inaccuracies involves prompt engineering, where specific prompts are designed to extract optimal outputs from the model. An example of this is the chain-of-thought approach, which uses a carefully worked-out answer to show the large language model (LLM) how to proceed.
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chatbot, computer program designed to have interactive or automated conversation with humans. Rudimentary chatbots were first developed in the mid-to-late 20th century and became more technically sound and widely available in the late 2010s and early 2020s, especially as artificial intelligence (AI) gained prominence in the technology sphere.
The first chatbots
The idea for the technology that preceded chatbot programs was first conceptualized by British mathematician and logician Alan Turing. In 1950 Turing proposed a set of criteria to determine whether a computer was sentient. The premise of the test was that a remote human interrogator, within a fixed time frame, must distinguish between a computer and a human subject based on their replies to various questions posed by the interrogator. Turing suggested that the computer’s sentience could be measured by whether or how often the human interrogator misidentified the computer as human. This theoretical test of AI became known as the Turing test.
The first software program to be recognized as a chatbot was developed in 1966 by computer scientist Joseph Weizenbaum. The program, named Eliza, was capable of simulating conversation with a computer user. By using an electric typewriter connected to a mainframe, a user could type in a conversational phrase, which Eliza would then review using a pattern-recognition algorithm. The algorithm compared the user’s input against a set of rules, which would generate appropriate sentences as typewritten responses. While this was considered a historic development in the field of computer science, Eliza’s abilities were too limited to pass the Turing test, as Eliza sometimes produced incoherent responses.
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A.L.I.C.E. and Jabberwacky
In 1995 a chatbot known as A.L.I.C.E. (Artificial Linguistic Internet Computer Entity) was released by developer Richard Wallace. In creating A.L.I.C.E., Wallace improved upon the AI used by Eliza after monitoring its conversations. After A.L.I.C.E. was presented with a sentence or phrase that it could not recognize, Wallace would add a response for the chatbot to use in the future rather than letting it repeatedly produce an incorrect response; this allowed for greater flexibility. As A.L.I.C.E. became more popular, other software designers could add their own responses to the chatbot’s spin-off software. Thus, the bot was capable of answering even more varied inquiries.
The chatbot Jabberwacky was released by computer scientist Rollo Carpenter in 1997 after he had spent more than a decade on its development. When it first launched, Jabberwacky used a similar rule-based approach to response generation as older chatbots like Eliza. Jabberwacky has been the subject of continuous development since it first debuted, and in 2008 the program was renamed Cleverbot. Cleverbot is notable for having the ability to save human responses to questions, which, unlike A.L.I.C.E., allows it to learn without intervention from a developer.
Later developments
Chatbot technology continued to proliferate in the 2000s and 2010s. In 2001 the development team at AI startup ActiveBuddy released the chatbot SmarterChild for use on AOL Instant Messenger (AIM). AIM was a popular chat room and instant messaging app, and its users could add SmarterChild to their friends list and converse with it. ActiveBuddy released its second chatbot, named GooglyMinotaur, through AIM as well. Created in collaboration with the rock band Radiohead, GooglyMinotaur was meant to be an unconventional promotional tool, as it was released alongside the band’s 2001 album Amnesiac. AIM users could interact with GooglyMinotaur by chatting with it and could even play games such as hangman with the bot.
In 2011 Apple released its virtual voice assistant program, Siri, on the iPhone 4S. Siri is a built-in chatbot that accepts voice commands from users to perform simple tasks. In 2014 Amazon followed suit by releasing its own virtual voice assistant program, named Alexa, on its Amazon Echo devices. Neither of these chatbots were developed with the goal of creating convincing conversations with users. Rather, the virtual assistants were designed to follow voice commands to perform simple tasks such as searching for information online, setting alarms, sending text messages, playing music, and adding events to calendars. Both virtual assistants proved to be immensely popular and brought chatbot technology into mainstream use.
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In 2022 OpenAI introduced the generative AI chatbot ChatGPT. ChatGPT is based on a natural language processing model that uses probability to predict words or sentences that its user is expecting. This allows ChatGPT to respond to users in a way that is sometimes indistinguishable from human communication. ChatGPT is capable of writing articles, responses to emails, and even computer code. While the widespread adoption of ChatGPT has proven useful in some sectors, the chatbot does have a reputation for responding in ways that are biased toward the expectations of the user. This leads ChatGPT to occasionally respond with false or misleading data (termed hallucinations) or to potentially even plagiarize information.