>"But a pair of new studies by artificial intelligence researchers at Stanford find that advanced AI systems can figure out linguistic principles on their own,

>"But a pair of new studies by artificial intelligence researchers at Stanford find that advanced AI systems can figure out linguistic principles on their own, without first practicing on sentences that humans have labeled for them. It’s much closer to how human children learn languages long before adults teach them grammar or syntax. Even more surprising, however, the researchers found that the AI model appears to infer “universal” grammatical relationships that apply to many different languages. That has big implications for natural language processing, which is increasingly central to AI systems that answer questions, translate languages, help customers and even review resumes. It could also facilitate systems that learn languages spoken by very small numbers of people. [PDS: Or are no longer spoken! So-called "dead" / ancient languages... important for understanding the histories of historic people and groups who have now faded into the proverbial "Sands of Time"...] The key to success? It appears that machines learn a lot about language just by playing billions of fill-in-the-blank games that are reminiscent of “Mad Libs.” In order to get better at predicting the missing words, the systems gradually create their own models about how words relate to each other. “As these models get bigger and more flexible, it turns out that they actually self-organize to discover and learn the structure of human language,” says Christopher Manning, the Thomas M. Siebel Professor in Machine Learning and professor of linguistics and of computer science at Stanford, and an associate director of Stanford’s Institute for Human-Centered Artificial Intelligence (HAI)."