The article explores the RLHF method as a way to enrich language models with a deeper understanding of complex concepts. It highlights the challenges related to accessibility and costs of gathering expert-labeled data. It also discusses how RLHF significantly improved ChatGPT compared to the original GPT-3.

Zero-shot models are helpful for prototyping machine learning projects because they generally do not need additional training to operate. CLIP, a popular model from OpenAI, does particularly well.