RLHF — Reinforcement learning from human feedback — training a model to prefer answers humans rate as better, which turns a raw text predictor into a usable assistant.
alignment — The work of making AI systems actually pursue what their builders and users intend, rather than something subtly or dangerously different.
fine-tuning — Taking a trained model and training it a bit more on your own examples so it gets better at one specific job.
Why it matters
A deep dive into the mechanics of high-quality human annotation and RLHFReinforcement learning from human feedback — training a model to prefer answers humans rate as better, which turns a raw text predictor into a usable assistant.Full definition → labeling — covering rater agreement, aggregation, and quality-control techniques that directly affect the data your alignmentThe work of making AI systems actually pursue what their builders and users intend, rather than something subtly or dangerously different.Full definition → and fine-tuningTaking a trained model and training it a bit more on your own examples so it gets better at one specific job.Full definition → pipelines depend on.
Key quotes
“High-quality data is the fuel for modern data deep learning model training.”
“Everyone wants to do the model work, not the data work”
