NON-TECHNICAL SUMMARY The history of spin glasses is a fascinating study into the intellectual power of statistical physics and its far-reaching consequences, especially for the understanding of complex materials. Once devised as an abstraction of some rare materials with peculiar magnetic properties, they have become a foundation for the study of complexity in some of the hardest computational problems in the sciences and engineering: from memory and learning in neural networks such as the brain or in artificial intelligence, to the structure and dynamics of a very broad range of real amorphous materials – granular, colloidal, polymeric, or magnetic. Their wide-ranging importance has been recognized with the 2021 Nobel Prize in Physics. An "Ising" spin glass is a simple model in which the spin variables can take on merely two values, up or down (+/-), similar to a bit (0/1) in a computer. By coupling each pair of these variables with a randomly selected positive (enhancing) or negative (suppressing) bond, it becomes an elementary model of a glass, i.e., a disordered amorphous material that fails to condense into a regularly ordered, crystalline state on cooling. Since finding such ground states is among the hardest known computational problems in science, their low-temperature properties are still poorly understood. While a mean-field theory of spin glasses that is mathematically tractable but ignores spatial embedding is well developed, results for real glasses that