SOURCE-LINKED INTELLIGENCE

Why do infants learn language so fast? A reverse engineering approach

CORDIS · observation · Publication date unknown

? The popular yet controversial 'statistical learning hypothesis' posits that they learn by gradually collecting statistics over their language inputs. This is strickingly similar to how current AI's Large Language Models (LLMs) learn and shows that simple statistical mechanisms may be sufficient to attain adult-like language competence. But does it? Estimates of language inputs to children show that by age 3, they have received 2 or 3 orders of magnitude less data than LLMs of similar performance. And the gap grows exponentially larger with children's age. Worse, when models are fed with speech instead of text they learn even slower. How are infants so efficient learners? This project tests the hypothesis that in addition to statistical learning, infants benefit from 3 mechanisms that accelerate their learning rate. (1) They are born with a \textit{vocal tract} which helps them understand the link between abstract motor commands and speech sounds, and decode noisy speech inputs more efficiently. (2) They have an \textit{episodic memory} enabling them to learn from unique events, i

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recordType

award

status

SIGNED

region

EU

value

2494625

unit

EUR