How ChatGPT actually works
Blog post from AssemblyAI
ChatGPT is based on the Reinforcement Learning with Human Feedback (RLHF) methodology, which consists of three main steps: supervised fine-tuning (SFT), reinforcement learning from human feedback (RLHF), and evaluating the resulting model. In the SFT step, a pre-trained language model is fine-tuned on high-quality instruction data. In the RLHF step, the model is trained with an additional reward model based on human feedback to optimize its output for human preferences. Finally, the performance of the resulting model is evaluated by human labelers on several criteria including helpfulness, truthfulness, and harmlessness.
| Trend | Post Mentions | Total Month Mentions | Posts | Companies | MoM |
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| Reinforcement learning | 20 | No monthly metrics for this publish month. | |||
| LLM | 9 | 274 | 59 | 27 | +154% |
| AI Model Fine-tuning | 5 | No monthly metrics for this publish month. | |||
| AI Guardrails | 1 | No monthly metrics for this publish month. | |||
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