Thermodynamics has been a historical concern in the engineering of conventional computing systems due to its role in power consumption, scaling, and device performance. Today, we see thermodynamics re-emerging in a new role as an algorithmic technique in areas such as machine learning, annealing, quantum, and neuromorphic systems. Recent theoretical developments in non-equilibrium thermodynamics suggest thermodynamics may become the basis of a new “thermodynamic computing” paradigm. For example, it may lead to computing systems that self-organize in response to external input.