• Definition of Generative AI:Generative AI is a type of artificial intelligence focused on creating content or synthetic data, such as videos, pictures, text, and sound.
• AI and Machine Learning:AI is a broad field that includes machine learning, which is a subset focusing on algorithms that enable systems to learn from data and make predictions.
• Discriminative vs. Generative Models: Discriminative models classify or predict specific properties of input data, while generative models create new data that resembles the input data.

• Definition: Large language models (LLMs) are generative AI models that excel at understanding and generating human-like text based on the input they receive, known as prompts.
• Capabilities: LLMs can answer questions, solve problems, provide coding and writing assistance, summarize text, and translate languages.
• Training: They are trained on massive amounts of diverse text data, which helps them capture the nuances of language usage and perform a wide range of tasks effectively.

Transfer Learning: Large language models can be trained as general-purpose models and then fine-tuned for specific tasks using transfer learning.

Categories of LLMs:four main categories of large language models:

• Generic Language Models: Pre-trained on diverse texts and used with prompt design.
• Instruction-Tuned Models: Fine-tuned to generate text based on specific instructions or prompts.
• Dialogue-Tuned Models: Designed for interactive conversations and dialogue.
• Domain-Specific Models: Fine-tuned for tasks in specific domains like medical text analysis or legal document processing.