The accuracy of AI predictions in catalysis depends on the quality and quantity of the data used for training the models. With high-quality, comprehensive datasets, AI can achieve remarkable accuracy. However, it is important to validate these predictions through experimental results. Continuous updating of AI models with new data can further improve their accuracy and reliability.
