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It is made possible by natural language processing (NLP), a field of AI that allows computers to understand and process human language and Google’s foundation models that power new generative AI capabilities. Google Cloud offers conversational AI as part of Vertex AI platform offerings like Vertex AI Conversation and Vertex AI solutions like Contact Center AI.
What is an example of conversational AI?
A few application examples of conversational AI technology are:
- Generative AI agents: these virtual agents use generative AI to power text or voice conversations
- Chatbots: often used in customer service applications to answer questions and provide support
- Virtual assistants: often voice-activated and can be used on mobile devices and smart speakers
- Text-to-speech software: used to create audiobooks, or spoken directions
- Speech recognition software: used to transcribe lectures, phone calls, captions, and more
What technology uses conversational AI?
Conversational AI uses a combination of natural language processing (NLP), foundation models, and machine learning (ML). Conversational AI systems are trained on large amounts of data, such as text and speech. This data is used to teach the system how to understand and process human language. The system then uses this knowledge to interact with humans in a natural way. It’s constantly learning from its interactions and improving its response quality over time.
What is the difference between AI and conversational AI?
AI is a general term that refers to a broad set of technologies that allows software and machines to perform ‘human-like’ reasoning and interactions. One of the defining characteristics of AI is its ability to convince humans that they are interacting with a human-like thinking entity. Another defining characteristic of AI is its ability to ‘learn’ independently from its initial programming and adapt to new environments.
Conversational AI is a subset of AI that focuses on natural language conversations. Conversational AI uses various technologies, such as NLP, ML, and speech recognition, to understand, process, and generate human-like responses. Conversational AI is especially useful for applications that require human-like interactions, such as customer service, personal assistants, and entertainment.
What are the features of conversational AI?
Some of the features of conversational AI are:
- Natural language understanding: The ability to comprehend the meaning and intention of human language inputs
- Natural language generation: The ability to produce natural and appropriate responses in human language
- Dialogue management: The ability to maintain a coherent and relevant conversation flow
- Context awareness: The ability to consider the situational and historical information of the conversation
- Personalization: The ability to tailor the responses according to the user’s preferences, needs, and behavior
- Emotion recognition: The ability to detect and respond to the user’s emotions and moods.
What is the purpose of conversational AI?
The purpose of conversational AI is to provide a more natural, engaging, and convenient way for humans to interact with machines. Conversational AI can help humans achieve various goals, such as:
- Reduce costs, and increase productivity and operational efficiency through automation.
- Deliver better customer experience, achieve higher customer engagement and satisfaction.
- Provide 24/7 service across all channels
- Offer personalized product recommendations
- Enable hands-free operation
- Access information and entertainment easily
What was the first conversational AI?
The first conversational AI was ELIZA, a computer program created by Joseph Weizenbaum in 1966. ELIZA simulated a psychotherapist and used pattern matching and substitution to respond to user inputs. ELIZA was one of the first programs to demonstrate the illusion of natural language understanding, and it inspired many subsequent conversational AI projects.
What is another name for conversational AI?
Some other names for conversational AI are:
- Conversational agents
- Conversational interfaces
- Conversational systems
- Conversational platforms
- Conversational applications
- Conversational computing
What is the best conversational AI platform?
There is no definitive answer to this question, as different conversational AI platforms may have different features, capabilities, and use cases. However, some of the popular and widely used conversational AI platforms are:
- Google Cloud’s Vertex AI Conversation: a basic developer platform with simple user interface to help enterprises quickly create and deploy generative AI powered chat and voice bots
- IBM Watson Assistant: an advanced platform for building conversational AI agents that can integrate with various channels and data sources
- Amazon Lex: a platform for building conversational AI agents that can leverage the power of Amazon Alexa and AWS services
- Microsoft Azure Bot Service: a platform for building conversational AI agents that can connect to various channels and Microsoft services
- Rasa: an open source platform for building conversational AI agents that can handle complex and contextual conversations
What is the most powerful conversational AI?
This is also a subjective question, as different conversational AI systems may have different strengths and weaknesses. However, some of the conversational AI systems that are considered to be very powerful and impressive are:
- Google Duplex: a conversational AI system that can make phone calls on behalf of users to book appointments, make reservations, or get information
- OpenAI GPT-3: a generative AI system that can produce natural and coherent texts on various topics and tasks, such as writing essays, creating chatbots, or generating code
- Facebook Blender: a conversational AI system that can engage in open-domain conversations with humans on various topics, such as movies, sports, or hobbies
- Alibaba’s AliMe: a conversational AI system that can provide customer service, product recommendations, and transaction support for millions of users on Alibaba’s e-commerce platforms
- Microsoft XiaoIce: a conversational AI system that can provide social and emotional companionship for millions of users across various platforms and languages.
Examples
Some of the examples of conversational AI and their track record are:
- Apple Siri: one of the first and most popular virtual assistants that can perform various tasks and answer questions on iOS devices. Siri has over 500 million monthly active users and can support 21 languages.
- Google Assistant: a virtual assistant that can help users with various tasks and information on Android devices, smart speakers, and other platforms. Google Assistant has over 500 million monthly active users and can support 30 languages.
- Amazon Alexa: a virtual assistant that can provide various services and skills on Amazon Echo devices and other platforms. Alexa has over 200 million active users and can support 8 languages.
- Netflix: a streaming service that uses conversational AI to provide personalized recommendations and content discovery for its users. Netflix has over 200 million subscribers and can support 26 languages.
- Spotify: a music streaming service that uses conversational AI to provide personalized playlists and music discovery for its users. Spotify has over 345 million monthly active users and can support 60 languages.
- Domino’s Pizza: a pizza delivery service that uses conversational AI to enable customers to order pizzas and track their delivery status via voice or text. Domino’s Pizza has over 17,000 stores in 90 countries and can support 40 languages.
Related Terms
Some of the terms related to conversational AI are:
- Artificial intelligence: a broad set of technologies that allows software and machines to perform ‘human-like’ reasoning and interactions
- Natural language processing: a field of AI that allows computers to understand and process human language
- Machine learning: a branch of AI that uses algorithms and data sets to improve operations
- Speech recognition: a technology that helps convert pure phonetic input from a human speaker into recognizable words
- Speech synthesis: a technology that helps convert text into speech
- Voicebot: a conversational AI agent that uses voice as the main mode of interaction
- Chatbot: a conversational AI agent that uses text as the main mode of interaction
- Virtual assistant: a conversational AI agent that can perform various tasks and services for users
- Generative AI: a type of AI that can produce new and original content, such as texts, images, or music
- Semantic search: a type of search that considers the meaning and context of the query, rather than just the keywords
Conclusion
Conversational AI is a powerful and promising technology that enables natural and intuitive interaction between humans and machines using speech and text. It has many applications and benefits in various domains, such as customer service, education, finance, and more. Conversational AI is based on the combination of natural language processing, machine learning, and foundation models, which allow the system to understand, process, and generate human language. Conversational AI is constantly learning and improving from its data and feedback, and strives to achieve trustworthiness, reliability, and fairness. Conversational AI is one of the key areas of research and development at Google Cloud, which offers various tools and solutions for building and deploying conversational AI agents and systems.
References
- What is conversational AI: examples and benefits | Google Cloud
- What is conversational AI? | IBM
- What is Artificial Intelligence (AI)? - Definition from Techopedia
- Conversational AI: The Future of Customer Service
- ELIZA - Wikipedia
- What is Conversational Artificial Intelligence? - Definition from Techopedia
- Top 10 Conversational AI Platforms in 2023
- The 10 Most Powerful Conversational AI Platforms in 2023
- Siri - Wikipedia
- Google Assistant - Wikipedia
- Alexa Internet - Wikipedia
- Netflix - Wikipedia
- Spotify - Wikipedia