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Rough (energy, or free energy, or fitness) landscapes are ubiquitous in disordered systems, from material science to biology. These landscapes feature a multitude of local energy minima, separated by barriers and transition paths, with highly heterogeneous properties. I will first review some applications of these ideas in glass physics. I will discuss in particular how quantitative calculations for glass-forming particle systems can be performed using a mean-field approach in large spatial dimensions. Next, I will discuss how rough landscapes emerge in the inference of statistical models for protein sequences. Such models can be extremely useful in understanding the emergence of protein structure and function, generating new artificial proteins with desired properties, and modeling dynamical (natural or in vitro) evolution. I will discuss the validation of some of these models against two recent "in vitro evolution" experiments, and an ongoing experimental collaboration with the Tokuriki lab, to generate functional intermediates between natural antibiotic-resistance proteins.