Large Language Models and their WEIRD Consequences

In his book “The Weirdest People in the World“, evolutionary psychologist Joseph Henrich focuses on a particular species that he calls “WEIRD people”. This play on words can be resolved because WEIRD stands for “white, educated, industrialised, rich, democratic”. Henrich wonders how it was possible for a small section of the population, most of whom […]

Power Hungry Magic

“Any sufficiently advanced technology is indistinguishable from magic”, Arthur C. Clarke already knew, and it is part of the magic of new technologies that their downsides are systematically concealed. This is also the case with the energy consumption of large language models (LLMs): As with the schnitzel that ends up on consumers’ plates and makes […]

Feeding the Cuckoo

Large 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 […]