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Researchers from MIT have made significant progress in enhancing the automatic understanding in AI models.

Algorithms, Artificial Intelligence, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, Computer vision, Electrical Engineering & Computer Science (eecs), Language, Machine learning, MIT Schwarzman College of Computing, MIT-IBM Watson AI Lab, National Science Foundation (NSF), Research, School of Engineering, UncategorizedJuly 24, 202434Views0Likes0Comments
As AI models become increasingly integrated into various sectors, understanding how they function is crucial. By interpreting the mechanisms underlying these models, we can audit them for safety and biases, potentially deepening our understanding of intelligence. Researchers from MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL) have been working to automate this interpretation process, specifically…

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The cognitive abilities of extensive linguistic models are frequently exaggerated.

Algorithms, Artificial Intelligence, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, Electrical Engineering & Computer Science (eecs), Language, Machine learning, MIT Schwarzman College of Computing, MIT-IBM Watson AI Lab, National Science Foundation (NSF), Quest for Intelligence, Research, School of Engineering, UncategorizedJuly 12, 202445Views0Likes0Comments
Artificial intelligence (AI) and particularly large language models (LLMs) are not as robust at performing tasks in unfamiliar scenarios as they are positioned to be, according to a study by researchers from MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL). The researchers focused on the performance of models like GPT-4 and Claude when handling “default tasks,”…

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Assisting beginners in creating sophisticated generative AI models

Algorithms, Artificial Intelligence, Electrical Engineering & Computer Science (eecs), Language, Machine learning, MIT Schwarzman College of Computing, School of Engineering, UncategorizedJune 22, 202429Views0Likes0Comments
Artificial intelligence (AI) models today have become increasingly complex with billions of parameters. Existing AI models are largely inaccessible to many due to a lack of widespread knowledge of how to create and control them. MosaicML, a company co-founded by Jonathan Frankle PhD '23 and MIT Associate Professor Michael Carbin, strives to overcome this issue.…

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This method enhances the problem-solving abilities of extensive language models.

Artificial Intelligence, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, Electrical Engineering & Computer Science (eecs), Language, Machine learning, MIT Schwarzman College of Computing, Programming, Research, School of Engineering, UncategorizedJune 14, 202432Views0Likes0Comments
A new technique has been proposed by researchers from the Massachusetts Institute of Technology (MIT) and other institutions that allows large language models (LLMs) to solve tasks involving natural language, math and data analysis, and symbolic reasoning by generating programs. Known as natural language embedded programs (NLEPs), the approach enables a language model to create…

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The brain’s language network has to exert more effort when dealing with complicated and unfamiliar sentences.

Artificial Intelligence, Brain and cognitive sciences, Computer science and technology, Language, Machine learning, McGovern Institute, MIT Schwarzman College of Computing, MIT-IBM Watson AI Lab, Neuroscience, Research, School of Engineering, School of Science, UncategorizedMay 3, 202443Views0Likes0Comments
Researchers from MIT, led by neuroscience associate professor Evelina Fedorenko, have used an artificial language network to identify which types of sentences most effectively engage the brain’s language processing centers. The study showed that sentences of complex structure or unexpected meaning created strong responses, while straightforward or nonsensical sentences did little to engage these areas.…

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The brain’s language network has to exert more effort when dealing with sentences that are intricate and unknown.

Artificial Intelligence, Brain and cognitive sciences, Computer science and technology, Language, Machine learning, McGovern Institute, MIT Schwarzman College of Computing, MIT-IBM Watson AI Lab, Neuroscience, Research, School of Engineering, School of Science, UncategorizedMay 2, 202440Views0Likes0Comments
Researchers from MIT have been using a language processing AI to study what type of phrases trigger activity in the brain's language processing areas. They found that complex sentences requiring decoding or unfamiliar words triggered higher responses in these areas than simple or nonsensical sentences. The AI was trained on 1,000 sentences from diverse sources,…

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The brain’s language network has to put in more effort when dealing with complex and unfamiliar sentences.

Artificial Intelligence, Brain and cognitive sciences, Computer science and technology, Language, Machine learning, McGovern Institute, MIT Schwarzman College of Computing, MIT-IBM Watson AI Lab, Neuroscience, Research, School of Engineering, School of Science, UncategorizedMay 2, 202439Views0Likes0Comments
Scientists from MIT have used an artificial language network to investigate the types of sentences likely to stimulate the brain's primary language processing areas. The research shows that more complicated phrases, owing to their unconventional grammatical structures or unexpected meanings, generate stronger responses in these centres. However, direct and obvious sentences prompt barely any engagement,…

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Intricate and unfamiliar phrases require more effort from the brain’s language processing system.

Artificial Intelligence, Brain and cognitive sciences, Computer science and technology, Language, Machine learning, McGovern Institute, MIT Schwarzman College of Computing, MIT-IBM Watson AI Lab, Neuroscience, Research, School of Engineering, School of Science, UncategorizedMay 1, 202435Views0Likes0Comments
With the assistance of an artificial language network, MIT neuroscientists have discovered what types of sentences serve to stimulate the brain's primary language processing regions. In a study published in Nature Human Behavior, they revealed that these areas respond more robustly to sentences that display complexity, either due to unconventional grammar or unexpected meaning. Evelina Fedorenko,…

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The language network of our brain has to exert more effort when dealing with intricate and unfamiliar sentences.

Artificial Intelligence, Brain and cognitive sciences, Computer science and technology, Language, Machine learning, McGovern Institute, MIT Schwarzman College of Computing, MIT-IBM Watson AI Lab, Neuroscience, Research, School of Engineering, School of Science, UncategorizedApril 30, 202441Views0Likes0Comments
Neuroscientists at MIT, with the aid of an artificial language network, have determined the type of sentences that most likely activate the brain's main language processing centers. The recently published study demonstrates that sentences which are more complex, either due to exceptional grammar or unexpected meanings, stimulate stronger responses in these regions. On the other…

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Intricate and unfamiliar phrases cause the brain’s language system to exert more effort.

Artificial Intelligence, Brain and cognitive sciences, Computer science and technology, Language, Machine learning, McGovern Institute, MIT Schwarzman College of Computing, MIT-IBM Watson AI Lab, Neuroscience, Research, School of Engineering, School of Science, UncategorizedApril 30, 202438Views0Likes0Comments
In collaboration with an artificial language network, neuroscientists at Massachusetts Institute of Technology (MIT) have revealed what type of sentences most significantly engage the brain’s primary language processing areas. The study indicates that sentences featuring unusual grammar or unexpected meaning trigger a heightened response in these language-oriented regions, as opposed to more straightforward phrases, which…

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