Comparison
Instruction Tuning vs Reinforcement Learning from Human Feedback
Instruction Tuning and Reinforcement Learning from Human Feedback are both common AI/LLM terms but cover different ideas. Here is a quick side-by-side.
When you would reach for Instruction Tuning
Instruction Tuning comes up when the question is fundamentally about training.
FLAN tuning Google's T5 to follow instructions.
When you would reach for Reinforcement Learning from Human Feedback
Reinforcement Learning from Human Feedback comes up when the question is fundamentally about training.
ChatGPT trained with RLHF to refuse unsafe requests.
Frequently asked
What is the difference between Instruction Tuning and Reinforcement Learning from Human Feedback?
Instruction Tuning: Instruction tuning is fine-tuning on examples of (instruction, desired response) pairs so a base model learns to follow natural-language directions. Reinforcement Learning from Human Feedback: RLHF fine-tunes an LLM to maximize a reward model that was itself trained on human preference judgments between candidate responses.
When should I use Instruction Tuning vs Reinforcement Learning from Human Feedback?
Instruction Tuning is the right concept when you are focused on training. Reinforcement Learning from Human Feedback applies when you are focused on training.
Are Instruction Tuning and Reinforcement Learning from Human Feedback the same thing?
No. Instruction Tuning is training; Reinforcement Learning from Human Feedback is training. They are related but address different parts of the AI stack.