Policy Indications: India’s Impending Growth in Education and Skills Market: A Report  |  Technology Inceptions: Strong Soft Materials are on the Move!  |  Rajagiri Round Table: Learning Through Games-Art and Science of Serious Games  |  Science Innovations: How Nucleoli Exist as Stable Droplets within the Nucleus?  |  Career News: Indian School of Business Inviting application for Aspiring Entrepreneurs  |  Health Monitor: Early Diagnosis and Treatment of Autism Spectrum Disorder Effective  |  Health Monitor: “School Meal Coalition” an Initiative by the UN  |  Policy Indications: WHO’s #HealthyAtHome Challenge for Students  |  Science Innovations: Another Planet Discovery!  |  Higher Studies: Hebrew University of Jerusalem's International Med-Tech Innovation MBA  |  Higher Studies: University of Birmingham Dubai invites applications for M.Sc. Urban Planning  |  Leadership Instincts: UNICEF’s comprehensive statistical analysis finds that nearly 240 million childr  |  Technology Inceptions: Quantum Dots can be Improvised in Tracking Biochemical Pathways of a Drug  |  Technology Inceptions: MIT promotes ‘Back to Bicycles’ with Artificial Intelligence  |  Policy Indications: Cambridge’s New Curriculum matches NEP 2020  |  
October 26, 2021 Tuesday 11:15:08 AM IST

Human Brain Uses Next-Word Prediction to Drive Language Processing

Technology Inceptions

MIT neuroscientists suggests the underlying function of the models resembles the function of language-processing centers in the human brain. Computer models that perform well on other types of language tasks do not show this similarity to the human brain, offering evidence that the human brain may use next-word prediction to drive language processing. Joshua Tenenbaum and  Evelina Fedorenko are the senior authors of the study, which appears this week in the Proceedings of the National Academy of Sciences. Martin Schrimpf, an MIT graduate student who works in CBMM, is the first author of the paper.

Most notably, the artificial intelligence excel at predicting the next word in a string of text; this technology helps search engines and texting apps predict the next word people are going to type. The most recent generation of predictive language models appears to learn something about the underlying meaning of language. These models can not only predict the word that comes next, but also perform tasks that seem to require some degree of genuine understanding, such as question answering, document summarization, and story completion. 

Comments