This past May marked the beginning of our return to face-to-face events after almost three years of pandemic-forced virtual-only interactions. The first attempt was the 2022 ICASSP! Planning for large international events in the era of postpandemic uncertainty is not an easy undertaking. Of course, signal processing is all about dealing with uncertainty—and who would be better at planning than IEEE Signal Processing Society (SPS) people?

As humans, we cannot be indifferent to the increasing number of dramatic events taking place in the world: fires, tornadoes, floods, and - recently - the collapse of a huge block of the Marmolada glacier in the Italian Alps. All are clear evidence to the global warming of the Earth.

Fourier theory is the backbone of signal processing (SP) and communication engineering. It has been widely used in almost all branches of science and engineering in numerous applications since its inception. However, Fourier representations such as Fourier series (FS) and Fourier transform (FT) may not exist for some signals that fail to fulfill a predefined set of Dirichlet conditions (DCs). 

This article discusses the contradiction between the exploding energy demand of artificial intelligence (AI) and the information and communication (ICT) industry as a whole and the parallel strong request for energy sobriety imposed by the need to mitigate the impact of climate change and the anticipated collapse of civilization as we know it.