In the context of computational learning, the concept of 'probably approximately correct' (PAC) learning provides a framework for understanding the efficiency and feasibility of learning algorithms.
"We are all alone, born alone, die alone, and—in spite of True Romance magazines—we shall all someday look back on our lives and see that, in spite of our company, we were alone the whole way."
