Generative AI LLMs (Part 2)
Key Takeaways
⇨ Large Language Models (LLMs) power advanced natural language processing by leveraging vast datasets and neural network architectures, enabling applications such as text generation, translation, and summarization.
⇨ Fine-tuning customizes pre-trained LLMs for specific tasks or industries, while Prompt Engineering enhances user interactions by structuring input queries effectively to generate precise responses.
⇨ Embeddings play a crucial role in LLMs by converting text into numerical representations, allowing AI models to understand context, semantics, and relationships between words for more accurate outputs.
In the second part of this series, we unpack Large Language Model components such as fine-tuning and prompt engineering.
Premium
