Deep *and* Broad ... Hodges' model is no blank slate ...

"Beyond deep learning

Steeper than expected

Different researchers have different ideas about how to try to improve things. One idea is to widen the scope, rather than the volume, of what machines are taught. Christopher Manning, of Stanford University's AI Lab, points out that biological brains learn from far richer data-sets than machines. Artificial language models are trained solely on large quantities of text or speech. But a baby, he says, can rely on sounds, tone of voice or tracking what its parents are looking at, as well as a rich physical environment to help it anchor abstract concepts in the real world. This shades into an old idea in AI research called "embodied cognition", which holds that if minds are to understand the world properly, they need to be fully embodied in it, not confined to an abstracted existence as pulses of electricity in a data-centre.

Biology offers other ideas, too. Dr Brooks argues that the current generation of AI researchers "fetishise" models that begin as blank slates, with no hand-crafted hints built in by their creators. But "all animals are born with structure in their brains," he says. 'That's where you get instincts from.'" p.11.

The Economist, Technology Quarterly: Artificial intelligence and its limits. The Economist, June 13 2020, 435:9198. [and image source].

'Deep and Broad' - as required.