Much work has been done within artificial intelligence (AI) to better understand how the human brain works to make AI more efficient. When you use a search on Google or Amazon, or you type on a phone or tablet, a piece of technology known as predictive language model is being used. This AI-driven functionality is what allows technology to be able to predict the next word within a string of text. The most recent generation of these predictive language models also learns the underlying meaning of languages, such as question answering or story completion. Could these AI next-word prediction models provide insight into how the brain processes language? This is what a team of cognitive neuroscientists from MIT wanted to explore.

The most recent generation of predictive language models also 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. Such models were designed to optimize performance for the specific function of predicting text, without attempting to mimic anything about how the human brain performs this task or understands language. But a new study from MIT neuroscientists suggests the underlying function of these 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.

Neuroscientists find the internal workings of next-word prediction models resemble those of language-processing centers in the brain. In the past few years, artificial intelligence models of language have become very good at certain tasks. Most notably, they excel at predicting the next word in a string of text; this technology helps search engines and texting apps predict the next word you are going to type. The most recent generation of predictive language models also 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.

In the past few years, artificial intelligence models of language have become very good at certain tasks. Most notably, they excel at predicting the next word in a string of text; this technology helps search engines and texting apps predict the next word you are going to type. The most recent generation of predictive language models also 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. Such models were designed to optimize performance for the specific function of predicting text, without attempting to mimic anything about how the human brain performs this task or understands language.

Summary: Artificial intelligence sheds new light on how the brain processes language. Researchers report the human brain may use next word prediction to drive language processing. In the past few years, artificial intelligence models of language have become very good at certain tasks. Most notably, they excel at predicting the next word in a string of text; this technology helps search engines and texting apps predict the next word you are going to type. The most recent generation of predictive language models also appears to learn something about the underlying meaning of language.

In the past few years, artificial intelligence models of language have become very good at certain tasks. Most notably, they excel at predicting the next word in a string of text; this technology helps search engines and texting apps predict the next word you are going to type. The most recent generation of predictive language models also 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. Such models were designed to optimize performance for the specific function of predicting text, without attempting to mimic anything about how the human brain performs this task or understands language.

Lauded by hippies, music heads and fans of all things psychedelic, acid has been used to blur the boundaries of reality and perception for decades. Experts have drawn parallels between the dissociative effects caused by the drug on the brain and psychiatric illnesses, with hope it could potentially be explored as a treatment. Now researchers have shown how the drug affects language and speech, reveal it may even enable users to be more creative. In the trials, participants took between 40 to 80 micrograms of the drug intravenously, which would be in the same range as the average tab of acid (illustrated). Researchers in Germany and the UK carried out trials in which participants were asked to name a number of pictures, either under the influence of acid or taking a placebo.