LLM-based AI Task
An LLM-based AI Task is an AI-based task that makes use of an LLM model.
- Context:
- input: LLM Prompt.
- It can (often) require substantial computational resources due to the complexity of the LL model.
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- It can be used in various applications, including content creation, customer support, and data analysis.
- It can involve training, fine-tuning, or using a pre-trained LLM to achieve the desired outcomes.
- It can be implemented through various frameworks and platforms that support LLMs, such as OpenAI, Hugging Face, and others.
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- Example(s):
- LLM-based ... Text-absed Tasks, such as:
- LLM-based Text Generation Task using an LLM to create marketing copy for a new product.
- LLM-based Summarization Task where an LLM condenses a lengthy article into key points.
- LLM-based Translation Task leveraging an LLM to translate a document from English to Spanish.
- LLM-based Question Answering Task using an LLM to provide detailed responses to user queries in a knowledge base.
- LLM-based Content Creation Task where an LLM generates blog posts based on given topics.
- LLM-based Chatbot Interaction Task using an LLM to engage in natural language conversations with users.
- Industry-Specific LLM-based Tasks, such as:
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- LLM-based ... Text-absed Tasks, such as:
- Counter-Example(s):
- Rule-Based Task which relies on predefined rules rather than a large language model.
- Statistical Machine Translation (SMT) Task which uses statistical models instead of neural networks.
- Simple Text Parsing Task which involves basic text processing without the complexity of an LLM.
- Traditional Machine Learning Task that employs algorithms like decision trees or SVMs instead of LLMs.
- Hand-Crafted Dialogue System which does not use an LLM for generating responses but relies on manually written scripts.
- See: LLM-based System, ML-based Task, Natural Language Processing (NLP), Transformer Models.