> Typically, AI models start with a blank slate and are trained on data with many different examples, from which the model constructs knowledge. But research on infants suggests this is not what babies do. Instead of building knowledge from scratch, infants start with some principled expectations about objects [...] The exciting finding by Piloto and colleagues is that a deep-learning AI system modelled on what babies do, outperforms a system that begins with a blank slate and tries to learn based on experience alone
The interesting thing is that the author of the paper you linked is currently reviewing the paper, or was at the time of writing:
>> New research by Luis Piloto and colleagues at Princeton University – which I’m reviewing for an article in Nature Human Behaviour – takes a step towards filling this gap.
I don't reckon I've seen this kind of article before: "here's some new research I'm reviewing and I think it's rad". That just sounds so... dodgy. You're supposed to maintain at least the facace of being impartial and having some sort of integrity when making reviews, even when reviewing a DeepMind paper for Nature.
https://theconversation.com/researchers-trained-an-ai-model-...
> Typically, AI models start with a blank slate and are trained on data with many different examples, from which the model constructs knowledge. But research on infants suggests this is not what babies do. Instead of building knowledge from scratch, infants start with some principled expectations about objects [...] The exciting finding by Piloto and colleagues is that a deep-learning AI system modelled on what babies do, outperforms a system that begins with a blank slate and tries to learn based on experience alone