Natural Language Processing
Natural language processing uses statistical methods to generate data representations from text (natural language) without supervision.
Statistical
Neural Methods
Machine Learning
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Generative language using AI
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Text generated from this description of the exhibition's background.
Artificial intelligence can in theory generate an 'average' representation of a place. Current methods cannot render three-dimensional environments with parametric atmospheres, temporality, geometries, and spatial relationships. Such analyses flatten the diversity that defines 'place'. An unsupervised analysis of the shape of the data will reveal that this data is composed of a vast but finite collection of data on 'place' and not the true environment it is based on. However, this is no more than a 'thrilling' description of the data's composition of a space—it shows that many structures of a given type (e.g., objects, spatial relations, and interactions) have not been represented by the same number of 'places'. This will show that there are many many different kinds of objects from which to create new locations.
A single set of 'places' is certainly possible based on this. (This is even assuming that the 'place' representation can be represented on a different set of data points in relation to it's 'baseline'. In most situations, the initial map of a place doesn't change as one takes in the location information as it comes across the land, but it will be the area, rather than the place itself, which is affected by the data as it is collected.) However, if the 'place' representations are so simple that it is difficult (which it should be), then the map is likely to be much more complicated
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