About this Video

• Video Title: How I use LLMs
• Channel: Andrej Karpathy
• Speakers: Andrej Karpathy
• Duration: 02:11:12

Introduction

This video provides a practical guide to using Large Language Models (LLMs), focusing on real-world applications and various settings. Andrej Karpathy demonstrates his workflow, showcasing different LLMs and their features, including tool use, thinking models, and multimodality interactions.

Key Takeaways

1. LLM Ecosystem: The LLM ecosystem is vast and diverse, with various providers offering different models and pricing tiers. Choosing the right model depends on specific needs and budget.
2. Basic Interactions: Basic LLM interaction involves providing text input and receiving text output. Understanding the underlying tokenization process helps in optimizing interactions.
3. Thinking Models: Thinking models, trained with reinforcement learning, enhance accuracy on complex problems, particularly in math and code, but require more processing time.
4. Tool Use: LLMs can be enhanced with tools like internet search, deep research capabilities, and Python interpreters to access external information and perform calculations.
5. Multimodality: LLMs are increasingly incorporating multimodality, enabling interaction through speech, audio, images, and video. This opens up new possibilities for applications.
6. Quality of Life Features: Features like chat memory, custom instructions, and custom GPTs significantly improve user experience and workflow efficiency.

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