Feeding the Cuckoo
/0 Comments/by Jörg LehmannLarge Language Models (LLMs) combine words that frequently appear in similar contexts in the training dataset; on this basis, they predict the most probable word or sentence. The larger the training dataset, the more possible combinations there are, and the more ‘creative’ the model appears. The sheer size of models such as GPT-4 already provides […]
Human-Machine-Cognition
/0 Comments/by Jörg LehmannHumans search for themselves in non-human creatures and inanimate artefacts. Apes, the “next of kin”, or dogs, the “most faithful companions” are good examples of the former, robots are good examples of the latter: A human-like design of the robots’ bodies and a humanising linguistic framing of their capabilities supports, according to a common hypothesis, […]
On the Tyranny of the Majority
/0 Comments/by Jörg LehmannLarge Language Models (LLMs) predict the statistically most probable word when they generate texts. The fact that the predicted word or sentence is the most probable does on the one hand not mean that it is true or false. On the other hand, the prediction of probabilities leads to a favouring of the majority opinion. […]