Part 2/11:
Historically, training AI models has required extensive human involvement. Developers typically employ Reinforcement Learning from Human Feedback (RLHF), where humans evaluate and guide the AI's responses, steering it toward desired behaviors. While effective, RLHF is resource-intensive, slow, and increasingly impractical as models grow more complex. Over time, the need to reannotate data to fix biases or accommodate new training standards further hampers scalability.