The frenzy is not limited to the Valley: a cloud of somewhat overlapping concepts — big data, data science, machine learning, Artificial Intelligence, deep learning— have become mainstream in recent years; serious business people went as far as claiming that data scientist is “the Sexiest Job of the 21st Century”, partially vindicating my failed attempt to become an NBA superstar (for some clear photographic evidence, compare this life with the one below).Still, not as sexy as the life of a data scientist.To many old(ish) practitioners, it may seem like the world finally caught up with what we knew all along: building smart machines is pretty f*%$ing cool!.On the other side, there seems to be some terrible confusion on what A.I..means, what A.I..promises and what A.I..can actually deliver.As an old(ish) practitioner and founder of “yet another San Francisco startup with an AI domain”, I find myself fully immersed in an ecosystem where optimism is often only matched by genuine ignorance of basic facts in A.I..history: I cannot help but wonder, are we at the beginning of an era, or instead at the end of one?In what follows, I submit my deeply subjective overview of A.I. — yesterday, today, tomorrow — and shall commit the ultimate (nerd) sin: decoupling the scienc-y hype from the business value.Disclaimer: in what follows, we won’t make particularly original claims from a scholarly perspective; even just considering non-academic stuff, some of our considerations are shared. More details