// MODEL OPTIMIZATION AND PROMPT SYNTAX TERM
Multi-Turn
Refers to a conversation with an AI model that involves several back-and-forth exchanges, where the AI remembers previous parts of the discussion.
TECHNICAL DEFINITION
Multi-turn interaction describes a conversational exchange with a large language model (LLM) that spans multiple user inputs and model responses, where the LLM maintains context and coherence across the dialogue history to provide relevant follow-up.
BACKGROUND
Prompt engineering is the process of structuring natural language inputs to produce specified outputs from a generative artificial intelligence (GenAI) model. Context engineering is the related area of software engineering that focuses on the management of non-prompt contexts supplied to the GenAI model, such as metadata, API tools, and tokens.
READ MORE ON WIKIPEDIASYNONYMS & ALIASES
- Conversational AI
- Dialogue history
- Stateful conversation
USAGE NOTE
Multi-turn capabilities are fundamental for building engaging and helpful chatbots and virtual assistants.
DEVELOPERS
Organizations developing technology related to Multi-Turn.
Develops leading large language models like GPT-3 and GPT-4, which inherently support complex multi-turn conversations through advanced context management and are heavily influenced by effective prompt engineering for sequential interactions.
Pioneers in conversational AI, developing models such as LaMDA and Gemini that power multi-turn interactions in products like Bard and Google Assistant, leveraging sophisticated dialogue management and prompt design techniques.
Offers Azure AI services and integrates multi-turn conversational AI into products like Copilot and Bing Chat, emphasizing robust dialogue capabilities for productivity and search, often requiring detailed prompt engineering for optimal performance.
Develops large language models such as Claude, which are designed with a focus on safety and a large context window, enabling complex and extended multi-turn conversations and advanced prompt chaining for intricate tasks.
Develops the Alexa voice assistant, a prominent example of a multi-turn conversational agent, and offers services like Amazon Lex on AWS for building custom multi-turn chatbots and virtual assistants, emphasizing dialogue flow and state management.
Provides enterprise-grade LLMs and tools for building AI applications, where robust multi-turn conversational capabilities are crucial for complex business workflows and require careful AI engineering and prompt design to maintain context and achieve desired outcomes.
A long-standing leader in enterprise AI, offering Watson Assistant for building multi-turn conversational agents with advanced dialogue management, natural language understanding (NLU) capabilities, and tools for designing effective conversational flows.