[1hr Talk] Intro to Large Language Models

Step-by-Step Tutorial:

1. Understanding Large Language Models:

• Large language models consist of two main files: parameters file and a run file that executes those parameters.
• Parameters file contains the weights of the neural network, stored as float16 numbers.
• The run file is a piece of code that runs the neural network, typically written in C, Python, or any other programming language.

2. Running the Model:

• Compile the C code to create a binary file that can be pointed at the parameters file.
• Use the compiled binary to interact with the language model by sending it text prompts.
• For example, you can ask the model to generate text like a poem about a specific topic.

3. Obtaining Parameters:

• Large language models are trained on massive datasets, typically comprising internet text.
• Training such models involves compressing a large chunk of text into parameters that represent the model's knowledge.
• Obtaining parameters requires specialized GPU clusters and can be a multi-million dollar process.

4. Fine-Tuning the Model:

• Fine-tuning involves customizing the base model for specific tasks or domains.
• By providing high-quality conversational data or Q&A documents, the model can be fine-tuned to become an assistant model.
• Fine-tuning helps in creating more specialized models for specific tasks.

5. Future Directions and Challenges:

• Researchers are exploring concepts like system one vs. system two thinking in large language models.
• Self-improvement, customization, and multimodal capabilities are areas of interest for enhancing language models.
• Challenges such as jailbreak attacks, prompt injection attacks, data poisoning, and backdoor attacks pose security risks that need to be addressed.

6. Security Measures:

• Stay informed about potential security threats and attacks on large language models.
• Regularly update models with security patches and defenses to mitigate vulnerabilities.
• Keep track of ongoing research and developments in the field to stay ahead of emerging security challenges.

By following these steps and staying informed about the latest advancements and security measures in the field of large language models, you can effectively utilize and safeguard your interactions with these powerful AI systems.