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While the federal government has introduced proposed legislation to outline rules and standards to guide the development of AI moving forward, a debate persists as to what those guidelines should look like, or even what they should be trying to achieve.
Most machine-learning models rely on mountains of data to replicate human text, but new research suggests the recipe for learning language might be simpler
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Researchers from MIT and elsewhere developed a machine-learning model that can automatically learn the rules and patterns of human languages on its own, and also learn some inductive biases that are applicable across many languages. This work could pave the way for AI systems that could automatically learn a model from a collection of interrelated datasets.