LLMs 101: Your Smart (but also silly) Second Brain
Large Language Models (LLMs) have incredible potential to revolutionize how we access and utilize our data. However, like a student who needs focused study sessions, LLMs require careful fine-tuning to be truly reliable within a knowledge management system. Let’s dive into the science behind this process.
At the heart of LLMs, or large language models, lie deep learning algorithms, especially a kind called transformers. These are complex artificial neural networks loosely inspired by the human brain. Transformers are built from layers containing interconnected nodes, and information flows through these layers. During training, the LLM is exposed to massive amounts of text data. As it processes this data, the connections between nodes are strengthened or weakened, allowing the LLM to learn the patterns and relationships between words. Essentially, it learns the language by encountering vast examples of how it’s used.
Pattern recognition: Identifies and learns how words and phrases are used together.
Statistical modeling: Derives rules of language from massive amounts of data.
This ability to learn language patterns allows LLMs to perform a variety of tasks. They can generate text, like poems or code, by predicting the most likely word to follow a sequence of previous ones. They can…
