What are large language models (LLMs)?
Large language models (LLMs) are a class of artificial intelligence (AI) algorithms leveraging deep learning methodologies and vast datasets to comprehend, condense, produce, and forecast fresh content.
Associated closely with LLMs is the concept of generative AI, as they are intricately designed to aid in generating text-based material.
Why are LLMs becoming important to businesses?
Large language models (LLMs) are gaining importance in the business landscape due to the expanding role of AI. Their relevance is highlighted alongside machine learning tools. The research underscores the significance of simplicity and consistency in crafting and deploying machine learning models. Pinpointing critical challenges, understanding historical data, and ensuring precision are pivotal factors in this process.
What are large language models used for?
LLMs have become increasingly popular because they have broad applicability for a range of NLP tasks, including the following:
- Text generation: LLMs can generate text on a wide range of topics they have been trained on.
- Translation: LLMs trained on multiple languages can translate between languages.
- Content summarization: They can condense blocks or pages of text into shorter summaries.
- Content rewriting: LLMs can rewrite sections of text while maintaining the original meaning.
- Classification and categorization: LLMs can classify and categorize content based on predefined criteria.
- Sentiment analysis: They can analyze the sentiment of text to discern the emotional tone.
- Conversational AI and chatbots: LLMs enable natural-language interactions with users, enhancing conversational AI and chatbot functionalities.
One of the most prevalent applications of conversational AI is through chatbots, which operate on a query-and-response model for user interaction. Among these, ChatGPT stands out as one of the most extensively used LLM-based AI chatbots, developed by OpenAI.
