Free guide for training AI from basics to modern techniques
A new open-source guide teaches how to train AI using human feedback. It covers both old and new methods to help people build better digital assistants.
This curriculum reached 2,800 stars on GitHub in just two months. It focuses on Reinforcement Learning, where software learns by trying different actions and getting rewards. The guide specifically explains RLHF, which is the method used to make models follow human instructions accurately. By learning these steps, you can build AI agents that are more reliable and easier to control. Well-trained agents require shorter prompts to work correctly, which helps save money on compute costs and tokens.
Key points
- A free guide covering the full process of training smart AI.
- Teaches the latest methods for making AI follow human rules.
- Helps build efficient AI agents that cost less to operate.
- Provides step-by-step instructions from basic concepts to real use.
Quick term guide
- open-source
- Software whose code is shared publicly so others can inspect, use, or change it.
- feedback
- A response that tells a user what they did well or should fix.
- digital
- Work or products that can be made and delivered online.
- Reinforcement Learning
- A type of AI training where the machine learns by trial and error to get the best result.
- software
- Programs or apps that run on a computer or smartphone.
- AI agents
- AI agents are AI tools that can carry out steps toward a goal, not just answer once.
- AI agent
- An AI program that can inspect information and suggest what to do next.
- compute
- The server power and chips needed to run AI systems.