Using less than $8 and 13 hours of training time, researchers from the United Nations were able to develop a program that could craft realistic-seeming speeches for the United Nations’ General Assembly.
The study, first reported by MIT’s Technology Review, is another indication that the age of deepfakes is here and that faked texts could be just as much of a threat as fake videos. Perhaps more, given how cheap they are to produce.
For their experiment, Joseph Bullock and Miguel Luengo-Oroz created a taxonomy for the machine learning algorithms using English language transcripts of speeches given by politicians at the UN General Assembly between 1970 and 2015.
The goal was to train