AI that can learn the patterns of human language

Recommendable! Impressive! This is still only the beginning!

"... This model can also automatically learn higher-level language patterns that can apply to many languages, enabling it to achieve better results. ...
This system could be used to study language hypotheses and investigate subtle similarities in the way diverse languages transform words. ..."

From the abstract:

"Automated, data-driven construction and evaluation of scientific models and theories is a long-standing challenge in artificial intelligence. We present a framework for algorithmically synthesizing models of a basic part of human language: morpho-phonology, the system that builds word forms from sounds. We integrate Bayesian inference with program synthesis and representations inspired by linguistic theory and cognitive models of learning and discovery. Across 70 datasets from 58 diverse languages, our system synthesizes human-interpretable models for core aspects of each language’s morpho-phonology, sometimes approaching models posited by human linguists. Joint inference across all 70 data sets automatically synthesizes a meta-model encoding interpretable cross-language typological tendencies. Finally, the same algorithm captures few-shot learning dynamics, acquiring new morphophonological rules from just one or a few examples. These results suggest routes to more powerful machine-enabled discovery of interpretable models in linguistics and other scientific domains."

AI that can learn the patterns of human language | MIT News | Massachusetts Institute of Technology On its own, a new machine-learning model discovers linguistic rules that often match up with those created by human experts.

Synthesizing theories of human language with Bayesian program induction (open access)