there  could  be  snakes  in  here

to red team (US military v.): to attack your own side, to test the soundness of their defence. See also pentest . rah (UK n.) or Rah-Rah (US n.): brash upper-class young man. A preppy boor. the Real Book (70s, US n.): illicit book of jazz scores, including melody lines, photocopied by generations of American music students. A phenomenal playlist . The biggest jazz sheet book ever. manel (n.): Man panel; public speaking session with no women. (Not including the chair, for some reason.) People are angry about this, because they take manels to constitute a claim that no women know anything about the topic. This is a bit strong. government name (US gang n.): birth name; source of embarrassment for thugs with edgy nicknames. See also (UK) Sunday name : "Aye, ma name's Bet - oh bit ma Sunday name's Elizabeth.". the note (cinema n.): the impression a character gives in their first scene, setting the tone for them. By analogy with a tuning fork. H

thought vector (ML n.): digital representation of an idea ; a series of numbers produced by embedding e.g. the words "cow", "heifer", and "Aberdeen Angus" in several languages, but also ( speculative ) all these images . if you can convert each sentence in a document into a vector, then you can take that sequence of vectors and [try to model] natural reasoning. And that was something that old fashioned AI could never do. If we can read every English document on the web, and turn each sentence into a thought vector, you've got plenty of data for training a system that can reason like people do. (Now, you might not want it to reason like people do, but at least we can see what they would think.) What I think is going to happen over the next few years is this ability to turn sentences into thought vectors is going to rapidly change the level at which we can understand documents. A big ass deal. Of course, it is not computationally pos