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Scientists improve the side vision capabilities in artificial intelligence models.

Artificial Intelligence, Autonomous vehicles, Brain and cognitive sciences, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, Computer vision, Electrical Engineering & Computer Science (eecs), Machine learning, MIT Schwarzman College of Computing, Research, School of Engineering, School of Science, UncategorizedJune 16, 202471Views0Likes0Comments
Peripheral vision, most humans' mechanism to see objects not directly in their line of sight, although with less detail, does not exist in AI. However, researchers at MIT have made significant progress towards this by developing an image dataset to simulate peripheral vision in machine learning models. The research indicated that models trained with this…

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Scientists improve sideline sight in AI prototypes.

Artificial Intelligence, Autonomous vehicles, Brain and cognitive sciences, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, Computer vision, Electrical Engineering & Computer Science (eecs), Machine learning, MIT Schwarzman College of Computing, Research, School of Engineering, School of Science, UncategorizedJune 16, 202470Views0Likes0Comments
MIT researchers are replicating peripheral vision—a human's ability to detect objects outside their direct line of sight—in AI systems, which could enable these machines to more effectively identify imminent dangers or predict human behavior. By equipping machine learning models with an extensive image dataset to imitate peripheral vision, the team found these models were better…

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Scientists improve sideline viewing capabilities in AI systems.

Artificial Intelligence, Autonomous vehicles, Brain and cognitive sciences, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, Computer vision, Electrical Engineering & Computer Science (eecs), Machine learning, MIT Schwarzman College of Computing, Research, School of Engineering, School of Science, UncategorizedJune 15, 202470Views0Likes0Comments
Peripheral vision, the ability to see objects outside of our direct line of sight, has been simulated by researchers at MIT to be used with AI technology. Unlike human vision, AI lacks the capability to perceive peripherally. Enhancing AI with this ability could greatly enhance its proactivity in identifying threats, and could even predict if…

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Scientists improve side vision capabilities in AI systems.

Artificial Intelligence, Autonomous vehicles, Brain and cognitive sciences, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, Computer vision, Electrical Engineering & Computer Science (eecs), Machine learning, MIT Schwarzman College of Computing, Research, School of Engineering, School of Science, UncategorizedJune 15, 202474Views0Likes0Comments
A team from MIT has created an image dataset aimed at simulating peripheral vision in machine learning models, a characteristic which AI typically lacks. This could improve the models' ability to recognise approaching threats and predict whether a human driver would spot an oncoming object. In experiments, these models improved in terms of hazard detection,…

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The conference emphasizes the magnitude of the mental health issue and innovative approaches to identifying and treating it.

Alzheimer's, Artificial Intelligence, Behavior, Biology, Brain and cognitive sciences, Depression, Digital technology, Disease, Health, Health care, Health sciences and technology, Machine learning, McGovern Institute, Mental health, Mobile devices, Neuroscience, Office of Open Learning, Parkinson's, Pharmaceuticals, School of Science, Special events and guest speakers, UncategorizedJune 13, 202479Views0Likes0Comments

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A methodology for enhancing the efficiency of versatile robots.

Aeronautical and astronautical engineering, Artificial Intelligence, Brain and cognitive sciences, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, Data, Electrical Engineering & Computer Science (eecs), Machine learning, Mechanical engineering, MIT Schwarzman College of Computing, National Science Foundation (NSF), Research, Robotics, Robots, School of Engineering, UncategorizedJune 3, 202462Views0Likes0Comments
MIT researchers have developed a technique to train robots on multiple tasks by combining and optimising data from a variety of sources. At the core of their work is a type of generative AI known as a 'diffusion model', which learns from a specific dataset to complete a task. However, the particular innovation here lies…

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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, 202475Views0Likes0Comments
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, 202477Views0Likes0Comments
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, 202485Views0Likes0Comments
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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Improved coding, planning, and robotics performance can be attributed to the enhancement brought about by natural language.

Artificial Intelligence, Brain and cognitive sciences, Center for Brains Minds and Machines, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, Computer vision, Defense Advanced Research Projects Agency (DARPA), Department of Defense (DoD), Electrical Engineering & Computer Science (eecs), Human-computer interaction, MIT Schwarzman College of Computing, MIT-IBM Watson AI Lab, National Science Foundation (NSF), Natural language processing, Programming, Programming languages, Quest for Intelligence, Research, Robotics, School of Engineering, School of Science, UncategorizedMay 2, 202479Views0Likes0Comments
Researchers at the MIT Computer Science and Artificial Intelligence Laboratory (CSAIL) presented three papers at the International Conference on Learning Representations, indicating breakthroughs in Large Language Models' (LLMs) abilities to form useful abstractions. The team used everyday words for context in code synthesis, AI planning, and robotic navigation and manipulation. The three frameworks, LILO, Ada,…

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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, 202473Views0Likes0Comments
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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