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Understanding Key Terminologies in Large Language Model (LLM) Universe
Are you interested in learning about large language models (LLMs) and the technical terms associated with them? Understanding these terms is the first step to unraveling the powerful algorithms that drive modern AI language systems. In this article, we explore 25 essential terms to enhance your technical vocabulary and provide insights into the mechanisms that make LLMs transformative.
1. LLM (Large Language Model)
Large Language Models (LLMs) are advanced AI systems trained on extensive text datasets to understand and generate human-like text. They mark a significant advancement in natural language processing.
2. Training
Training refers to teaching a language model to understand and generate text by exposing it to a large dataset. This process is foundational for developing any AI that handles language tasks.
3. Fine-tuning
Fine-tuning is a process where a pre-trained language model is further trained on a smaller, specific dataset to specialize in a particular domain or task.
25. Autoregressive Models
Autoregressive models in language modeling predict subsequent words based on previous ones in a sequence. This approach is fundamental in models like GPT.
Practical AI Solutions
If you want to evolve your company with AI, stay competitive, and use AI to your advantage, consider leveraging the understanding of key terminologies in the LLM universe.
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