How do infants learn their first words in a noisy environment? How do they progress from being slow incremental learners to rapid learners who appropriately generalize categories and concepts from minimal experience. In this talk, I will present evidence that the answer to these questions lies in the structure of the learning environment itself, which is not like that assumed by most theorists of early word learning and not like that used in language learning experiments. We have used head cameras to collect egocentric views (and parent talk) in the home from the perspective of infants and toddlers (8 month olds to 30 month olds, with no experimenters present, 500 hours of head camera video) and in a naturalistic toy room environment in the laboratory (about 200 hours of head-mounted eye tracking yielding both the ego-centric view and the gaze within that view). Our analyses of the everyday experiences indicate four principles we believe to be key to learning to becoming a rapid learner of object names and a robust learner across domains more generally. The four principles are: (1) Learn a massive amount about very few individual entities (and little bit about lots of other individual things); (2) Learn a massive amount about a very few categories (and a little bit about lots of other categories); (3) Learn about small selective sets at different points in time; (4) Self-generate the data for learning (with some help from mom and dad).