Accurate prediction of protein properties is an essential task in many areas of biotechnology, including enzyme engineering and protein-hybrid optoelectronics. In recent publications, approaches based on protein language models have shown superior performance both in predicting protein function and structure and in generating novel sequences. In this talk, we will show the benefits of large language models for predicting protein thermophilicity and thermostability, and give an outlook on how these models will revolutionize the design of synthetic proteins.