It's a bit of an anthropomorphism ation. I don't believe it has any formal meaning here. The idea is that there are certain kinds of underlying signals and patt

It's a bit of an anthropomorphism ation. I don't believe it has any formal meaning here. The idea is that there are certain kinds of underlying signals and patterns which are common to a wide range of time series data. So if a model is able to learn those signals and patterns, it can look at any time series and, with enough historical data, predict future data, without actually updating any model weights. Those signals constitute a "grammar" of sorts.