One billion public-facing Instagram photos were used to train an algorithm created by Facebook to learn to recognise images by itself.
Traditionally, algorithms were trained on datasets already categorised by humans – labelled cats, dogs or flowers, for example. But the Instagram photos were presented to the algorithm without the labelling.
Afterwards it was able to correctly identify images with 84.5% accuracy.
Facebook has called its system Seer, an abbreviation of self-supervised.
AI expert Calum Chase said the system “could be an important step towards the holy grail of computers with common sense” if it proved effective in the long term.
There are other firms also working on similar processes.
Facebook said while this sort of technique has already seen success in algorithms dealing with processing language, images present a different challenge. That’s because individual words are easier to identify than the different parts of a picture.