Generative AI and Large Language Models (LLMs) are at the forefront of AI innovation, capable of evolving from simple assistants into agents that can take actions. These technologies are revolutionizing various industries, particularly education.
Definition of LLMs
LLMs are advanced AI models that can understand and generate human-like text. Beyond text, they can also generate images from textual descriptions.
Applications of LLMs
LLMs have diverse applications, including:
- Text Generation: Creating various forms of written content.
- Chat Applications: Powering conversational AI systems.
- Image Generation: Producing images from text prompts (e.g., DALL-E, Midjourney).
- Search Applications: Enabling semantic search through embeddings, providing highly relevant results even for complex queries. For example, a search application can "return a list of YouTube videos that are relevant to the question, and better still, the search application will return a link to the place in the video where the answer to the question is located."
- AI Agents: Allowing LLMs to perform actions by providing them "access to tools and state management," enhancing visibility into their planned actions.
Types of LLMs
There are various types of LLMs, including proprietary and open-source models. Understanding the differences is crucial for selecting the right model for a specific use case. Hugging Face and Azure AI Studio are platforms for exploring open-source models.
Deployment
LLMs can be deployed in environments like Azure.