LLM-Supported End-User Application
(Redirected from LLM-based application)
An LLM-Supported End-User Application is an AI-supported application that is a LLM-supported system (that uses LLMs).
- Context:
- It can (typically) be characterized by direct interaction with non-technical users, providing services such as automated content generation, customer support, or decision-making assistance.
- It can (typically) employ natural language interfaces, allowing users to communicate with the application through conversational AI, chatbots, or command-line instructions.
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- It can range from a Past LLM-Supported Application to being a Present LLM-Supported Application to being a Future LLM-Supported Application.
- It can range from being a Natural Language Understanding (NLU)-focused LLM-Supported End-User Application to being a Natural Language Generation(NLG)-focused LLM-Supported End-User Application
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- It can reference an LLM-based Application Architecture (and an LLM-based system arch).
- It can make use of an LLM Application Framework.
- It can be evaluated with an LLM Application Evaluation Task.
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- Example(s):
- LLM-supported Professional End-User Tools (professional end-user tools), such as:
- LLM-supported Software Development Application, such as: Github Copilot, which assists software developers in writing code by providing suggestions and code completion.
- LLM-supported System Configuration Application, such as: LLM-Supported Clinical Trial Configuration Application, used to configure and manage clinical trials based on structured and unstructured data.
- LLM-based Medical Diagnosis System, which aids medical professionals in diagnosing diseases by analyzing patient symptoms and medical history using large language models.
- LLM-supported Legal End-User Applications, such as:
- LLM-supported Legal Document Analysis Application (legal document analysis system), such as LLM-supported contract analysis application (contract analysis system).
- LLM-supported Legal Document Generation Application (legal document generation system), such as LLM-supported contract drafting application (contract drafing system).
- LLM-based Clinical Trial Application, which helps researchers design and manage clinical trials by automating protocol generation and data analysis, improving efficiency in the process.
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- Content and Communication:
- LLM-based Customer Support System, a customer support system where LLMs assist in answering customer queries and resolving issues in real-time, improving customer satisfaction and reducing response times.
- LLM-Supported Content Creation Application, such as: Jasper AI, which assists content creators by generating blog posts, articles, and marketing materials based on user prompts, accelerating the content creation process.
- LLM-Supported Language Learning Application, such as: Duolingo's AI Chatbots, which help users practice conversations in different languages by simulating real-life language interactions, providing personalized feedback and adaptive learning.
- LLM-Supported Creative Writing Application, such as: Sudowrite, an AI tool for writers that provides suggestions for plot development, dialogue, and creative writing enhancement, aiding in overcoming writer’s block and enhancing creativity.
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- Personal Assistance and Planning:
- LLM-Supported Personal Assistant Application, such as: Google Assistant, which assists users with tasks like setting reminders, managing calendars, and answering questions by understanding natural language inputs, offering seamless daily task management.
- LLM-Supported Financial Planning Application, such as: Wealthfront's AI Advisor, which helps users create and manage personalized investment plans using natural language recommendations and insights, enabling smarter investment decisions and financial planning.
- LLM-Supported Travel Planning Application, such as: Kayak’s AI Trip Planner, which assists users in organizing travel itineraries, suggesting flights, accommodations, and activities based on user preferences and budgets.
- LLM-Supported Health Management Application, such as: MyFitnessPal's AI Nutrition Coach, which helps users track dietary intake, exercise routines, and provide recommendations for healthier living using natural language insights.
- LLM-Supported Smart Home Management Application, such as: Amazon Alexa, which allows users to control smart home devices, manage household schedules, and interact with connected systems through voice commands powered by LLMs.
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- LLM-supported Professional End-User Tools (professional end-user tools), such as:
- Counter-Example(s):
- an LLM-based Back-End System, accessible via APIs.
- an ML-Supported Application.
- See: LangChain, Conversational AI-based Application.