The crucial insight of the distributional hypothesis is that the knowledge that we acquire through this process can be brought to bear during language processing long after its initial acquisition in novel contexts. We saw in Chapter 6 that embeddings (static word representations) can be learned from text and then employed for other purposes like measuring word similarity or studying meaning change over time.