Lectures potser interessants d’aquests darrers dies.
Our main result is to show that proper treatment of scientific uncertainties dissolves the Fermi paradox by showing that it is not at all unlikely ex ante for us to be alone in the Milky Way, or in the observable universe.
Our second result is to show that, taking account of observational bounds on the prevalence of other civilizations, our updated probabilities suggest that there is a substantial probability that we are alone.
We can take any arbitrary image (e.g. “panda”) and classify it as whatever class we want (e.g. “ostrich”) by adding tiny, imperceptible noise patterns… But in fact the core flaw extends to many other domains (e.g. speech recognition systems) and, most importantly, also to Linear Classifiers. It is in fact this linear nature that is problematic. And because Deep Learning models use linear functions to build up the architecture, they inherit their flaw.