Jason Edge discusses the implications of the growing proliferation of unstructured data for the way in which we ascribe meaning to data. Increasingly we have to draw the meaning of data from its context and the way in which it is used. This then points to the growing sophistication of natural language processing and the ability to draw semantic information out of unstructured data.
Jason argues that in order to be able to cope with the need to draw meaning out of unstructured data, we have to look to further advances in AI and natural language processing and that this process will be further democratised through the growth of open source projects. Additionally, the more that we can move things into a public cloud, the better as with this comes the ability to scale, thus enabling machine learning to happen in the cloud.