In recent years, the global food crisis has intensified, posing a challenge to secure sustainable food supplies. Factors such as population growth, climate change, and labor shortages in primary industries threaten the stability of food production. In response, insect-based food has gained prominence as an efficient and sustainable food source, offering benefits such as resource efficiency, environmental friendliness, and high nutritional value. This study explores the capability of a large-scale language model (LLM), like ChatGPT, to learn safe cooking methods for insect-based food. Despite ChatGPT's general ethical constraints, we utilize the Fine-tuning API from OpenAI to train the model using a dialog-based dataset. Information about insects and poisons is collected from Wikipedia for training purposes. Evaluation of the model's output is performed using OpenAI's evals, specifically examining the inclusion of appropriate cooking methods. The study assesses the model's performance over 3,10, and 30 epochs for 50 different types of insects.
NETL
