🤖 Gemini: Conversational AI — Annotated Reference List
Key sources defining Conversational AI, its core components, and its relationship with NLP, ML, and Generative AI.
The following sources support the definition, core components, and architecture of Conversational AI, including its relationship with Natural Language Processing (NLP), Machine Learning (ML), and Generative AI.
Amazon Web Services (AWS). (2025). What is conversational AI? - Conversational AI chatbots explained.
https://aws.amazon.com/what-is/conversational-ai/
Annotation: Provides a comprehensive overview defining Conversational AI, explaining its operation using NLP, NLU, and NLG, and detailing its evolution from rule-based systems to modern LLM-powered assistants.
https://aws.amazon.com/what-is/conversational-ai/
Annotation: Provides a comprehensive overview defining Conversational AI, explaining its operation using NLP, NLU, and NLG, and detailing its evolution from rule-based systems to modern LLM-powered assistants.
Appian. (2024, September 19). Generative AI vs Large Language Models (LLMs): What's the Difference?
https://appian.com/blog/acp/process-automation/generative-ai-vs-large-language-models
Annotation: Differentiates between Generative AI (broad category) and LLMs (subset), showing how LLMs power text generation—core to modern Conversational AI.
https://appian.com/blog/acp/process-automation/generative-ai-vs-large-language-models
Annotation: Differentiates between Generative AI (broad category) and LLMs (subset), showing how LLMs power text generation—core to modern Conversational AI.
beconversive. (2025, February 17). What is Conversational AI? Definition, Components, Examples, and Use Cases.
https://www.beconversive.com/blog/conversational-ai
Annotation: Outlines the four-step process of Conversational AI—Input, Intent Understanding, Response Generation, Output Delivery—detailing technologies such as ASR, NLP/NLU, and TTS.
https://www.beconversive.com/blog/conversational-ai
Annotation: Outlines the four-step process of Conversational AI—Input, Intent Understanding, Response Generation, Output Delivery—detailing technologies such as ASR, NLP/NLU, and TTS.
Conversation Design Institute. (n.d.). What are Generative AI and LLMs (Large Language Models)?
https://www.conversationdesigninstitute.com/topics/generative-ai-and-llm
Annotation: Defines Generative AI and LLMs, explaining how they generate original content and perform diverse language tasks, functioning as the “brain” of modern Conversational AI.
https://www.conversationdesigninstitute.com/topics/generative-ai-and-llm
Annotation: Defines Generative AI and LLMs, explaining how they generate original content and perform diverse language tasks, functioning as the “brain” of modern Conversational AI.
Google Cloud. (n.d.). Conversational AI.
https://cloud.google.com/conversational-ai
Annotation: Defines Conversational AI as a system simulating human dialogue powered by NLP, ML, and generative models; includes examples of enterprise applications.
https://cloud.google.com/conversational-ai
Annotation: Defines Conversational AI as a system simulating human dialogue powered by NLP, ML, and generative models; includes examples of enterprise applications.
IBM. (n.d.). What Is NLP (Natural Language Processing)?
https://www.ibm.com/think/topics/natural-language-processing
Annotation: Defines NLP as combining computational linguistics and machine learning to enable computers to understand and generate human language.
https://www.ibm.com/think/topics/natural-language-processing
Annotation: Defines NLP as combining computational linguistics and machine learning to enable computers to understand and generate human language.
LivePerson. (n.d.). What is Conversational AI? Your Complete Guide.
https://www.liveperson.com/resources/reports/what-is-conversational-ai/
Annotation: Offers a foundational definition and traces Conversational AI’s reliance on AI, ML, and NLP for context-aware dialogue.
https://www.liveperson.com/resources/reports/what-is-conversational-ai/
Annotation: Offers a foundational definition and traces Conversational AI’s reliance on AI, ML, and NLP for context-aware dialogue.
Maya Research – Veena AI. (2025, September 1). Conversational AI: What It Is and How It Works.
https://mayaresearch.ai/blog/conversational-ai-what-it-is-and-how-it-works
Annotation: Maps the full technical stack—ASR, NLP (NLU/Intent/Entity), Dialogue/LLM layer, NLG, and TTS—clarifying architecture and function.
https://mayaresearch.ai/blog/conversational-ai-what-it-is-and-how-it-works
Annotation: Maps the full technical stack—ASR, NLP (NLU/Intent/Entity), Dialogue/LLM layer, NLG, and TTS—clarifying architecture and function.
Mosaicx. (n.d.). Generative AI vs. Conversational AI: Differences & How They Work Together.
https://www.mosaicx.com/blog/generative-ai-vs-conversational-ai
Annotation: Explains how Generative AI creates content and Conversational AI manages dialogue—complementary technologies in advanced systems.
https://www.mosaicx.com/blog/generative-ai-vs-conversational-ai
Annotation: Explains how Generative AI creates content and Conversational AI manages dialogue—complementary technologies in advanced systems.
SAP. (2024, June 10). What is conversational AI: Benefits and applications.
https://www.sap.com/resources/what-is-conversational-ai
Annotation: Emphasizes Conversational AI’s ability to process and respond to natural language, addressing nuances and context challenges.
https://www.sap.com/resources/what-is-conversational-ai
Annotation: Emphasizes Conversational AI’s ability to process and respond to natural language, addressing nuances and context challenges.
Scribd. (n.d.). 1.6 - Components of A Conversational AI System.
https://www.scribd.com/document/918034644/1-6-Components-of-a-Conversational-AI-System
Annotation: Lists and defines the five essential components—ASR, NLU, DM, NLG, TTS—and details NLU’s key tasks of intent recognition and entity extraction.
https://www.scribd.com/document/918034644/1-6-Components-of-a-Conversational-AI-System
Annotation: Lists and defines the five essential components—ASR, NLU, DM, NLG, TTS—and details NLU’s key tasks of intent recognition and entity extraction.
SmythOS. (n.d.). Conversational Agents and Natural Language Processing: Bridging Human Communication and AI.
https://smythos.com/developers/agent-development/conversational-agents-and-natural-language-processing/
Annotation: Structures the core capabilities around NLU, Dialogue Management, and NLG—illustrating how they identify intent, maintain context, and generate human-like responses.
https://smythos.com/developers/agent-development/conversational-agents-and-natural-language-processing/
Annotation: Structures the core capabilities around NLU, Dialogue Management, and NLG—illustrating how they identify intent, maintain context, and generate human-like responses.
Softobotics. (2024, January 10). Developing Chatbots with NLP in AI & ML.
https://www.softobotics.com/blogs/building-conversational-chatbots-with-natural-language-processing-in-ai-ml/
Annotation: Highlights Machine Learning’s critical role in enabling Conversational AI to learn continuously and improve context awareness.
https://www.softobotics.com/blogs/building-conversational-chatbots-with-natural-language-processing-in-ai-ml/
Annotation: Highlights Machine Learning’s critical role in enabling Conversational AI to learn continuously and improve context awareness.
SquadStack. (n.d.). Natural Language Understanding in AI Voice Agents.
https://www.squadstack.ai/voicebot/natural-language-processing-in-ai-voice-bots
Annotation: Presents the “Three Pillars” of an NLP-based voice bot—NLU, NLG, and Continuous Learning—underscoring synthesis and contextual understanding.
https://www.squadstack.ai/voicebot/natural-language-processing-in-ai-voice-bots
Annotation: Presents the “Three Pillars” of an NLP-based voice bot—NLU, NLG, and Continuous Learning—underscoring synthesis and contextual understanding.
Tavus. (2024, December 19). 13+ Best Conversational AI Solutions [2025].
https://www.tavus.io/post/conversational-ai-solutions
Annotation: Defines Conversational AI as systems using NLP and ML to replicate human dialogue by understanding context and intent.
https://www.tavus.io/post/conversational-ai-solutions
Annotation: Defines Conversational AI as systems using NLP and ML to replicate human dialogue by understanding context and intent.
Yada, V. (2025, January 5). How Natural Language Processing is Transforming Conversational AI. Medium.
https://medium.com/@vaishnaviyada/how-natural-language-processing-is-transforming-conversational-ai-da720ce78ba9
Annotation: Details NLP’s role in user intent detection, sentiment analysis, and contextual understanding within Conversational AI systems.
https://medium.com/@vaishnaviyada/how-natural-language-processing-is-transforming-conversational-ai-da720ce78ba9
Annotation: Details NLP’s role in user intent detection, sentiment analysis, and contextual understanding within Conversational AI systems.
Webio. (n.d.). What is the Difference Between Generative AI and Conversational AI?
https://www.webio.com/faq/difference-between-generative-ai-and-conversational-ai
Annotation: Highlights distinctions between Generative and Conversational AI, noting dialogue-specific dataset training for realistic interactions.
https://www.webio.com/faq/difference-between-generative-ai-and-conversational-ai
Annotation: Highlights distinctions between Generative and Conversational AI, noting dialogue-specific dataset training for realistic interactions.
Zendesk. (n.d.). What is conversational AI? How it works, examples, and more.
https://www.zendesk.com/blog/customers-really-feel-conversational-ai/
Annotation: Defines Conversational AI and its reliance on ML and NLP (NLU and NLG) to form intent-based replies grounded in knowledge bases.
https://www.zendesk.com/blog/customers-really-feel-conversational-ai/
Annotation: Defines Conversational AI and its reliance on ML and NLP (NLU and NLG) to form intent-based replies grounded in knowledge bases.
Zendesk. (n.d.). What are NLP chatbots and how do they work?
https://www.zendesk.com/blog/nlp-chatbot/
Annotation: Explains NLP chatbot mechanics—normalization, tokenization, intent classification, and entity recognition—and how Generative AI enhances personalization and context.
https://www.zendesk.com/blog/nlp-chatbot/
Annotation: Explains NLP chatbot mechanics—normalization, tokenization, intent classification, and entity recognition—and how Generative AI enhances personalization and context.
🧩 Compiled for AI Library — Collaboration with Gemini