Since LLMs are natural evolutionary step of NLP (natural language programming) models – they can perform exceptionally well text-related tasks.

NLP is a subfield of artificial intelligence that focuses on the interaction between computers and humans through natural language. It involves the ability of a computer program to understand, interpret, and generate human language. Common NLP tasks include text classification, sentiment analysis, named entity recognition (NER), machine translation, speech recognition, and more.

LLM are a type of AI model, often based on deep learning architectures like transformers, designed to understand and generate human language at a very large scale. These models are trained on vast amounts of text data. LLMs can perform a wide range of NLP tasks and often surpass previous models in terms of performance and versatility. They can generate coherent and contextually relevant text, translate languages, answer questions, summarize text, and many many more.

LLMs are characterized by their large scale, both in terms of the number of parameters and the volume of training data. This scale allows them to capture more nuances of language and perform better on a variety of tasks.

These are typical tasks for Large Language Models (LLMs):

1. Text Generation and Writing

• Creative writing (stories, poems, scripts)
• Professional writing (emails, reports, documentation)
• Content summarization
• Translation between languages

2. Analysis and Problem-Solving

• Data analysis and pattern recognition
• Critical analysis of text
• Mathematical calculations and problem-solving
• Logical reasoning and step-by-step analysis

3. Programming and Technical Tasks

• Code writing and debugging
• Code explanation and documentation
• Converting requirements into code
• Suggesting code optimizations

4. Education and Knowledge

• Explaining complex concepts
• Answering questions across various domains
• Breaking down topics into simpler components
• Creating educational content and exercises

5. Conversation and Assistance

• Engaging in dialogue
• Providing recommendations
• Answering questions
• Role-playing for practice scenarios

6. Text Processing

• Information extraction
• Classification and categorization
• Sentiment analysis
• Format conversion

However, LLMs also have important limitations. They:

• May occasionally provide incorrect information
• Cannot directly interact with external systems