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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, 202439Views0Likes0Comments
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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An improved, more efficient method to inhibit AI chatbots from delivering harmful responses.

Algorithms, Artificial Intelligence, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, Defense Advanced Research Projects Agency (DARPA), Electrical Engineering & Computer Science (eecs), Human-computer interaction, Machine learning, MIT Schwarzman College of Computing, MIT-IBM Watson AI Lab, Research, School of Engineering, UncategorizedApril 10, 202434Views0Likes0Comments

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A novel computational method may simplify the process of engineering beneficial proteins.

Artificial Intelligence, Biological engineering, Brain and cognitive sciences, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, Defense Advanced Research Projects Agency (DARPA), DNA, Electrical Engineering & Computer Science (eecs), MIT Schwarzman College of Computing, National Institutes of Health (NIH), National Science Foundation (NSF), Proteins, Research, School of Engineering, School of Science, UncategorizedApril 3, 202434Views0Likes0Comments

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An algorithm developed at MIT aids in predicting the occurrence of severe weather events.

Algorithms, Artificial Intelligence, Climate, Climate change, Computer modeling, Defense Advanced Research Projects Agency (DARPA), Disaster response, Earth and atmospheric sciences, Environment, Fluid dynamics, Hurricanes, Machine learning, Mechanical engineering, Natural disasters, Planetary science, Research, School of Engineering, Uncategorized, WeatherMarch 27, 202434Views0Likes0Comments
Assessing a community’s risk of extreme weather events – such as catastrophic storms and catastrophic flooding – is a key task for policymakers who are trying to prepare for the potential impacts of global climate change. Despite major advancements in technology and modeling techniques, however, these forecasts leave a lot to be desired. Now, a…

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Numerous AI systems assist robots in carrying out intricate strategies with greater clarity.

Algorithms, Artificial Intelligence, Computer science and technology, Computer vision, Data, Defense Advanced Research Projects Agency (DARPA), Electrical Engineering & Computer Science (eecs), Machine learning, MIT Schwarzman College of Computing, MIT-IBM Watson AI Lab, National Science Foundation (NSF), Research, Robotics, School of Engineering, UncategorizedMarch 7, 202437Views0Likes0Comments
MIT's Improbable AI Lab has developed a novel multimodal framework for artificial intelligence (AI) called the Compositional Foundation Models for Hierarchical Planning (HiP). The aim of this system is to help robots conduct complex tasks that involve numerous smaller steps, from household chores to more elaborate industrial processes. Traditionally, AI systems have required paired visual,…

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AI-based risk prediction provides fresh optimism for timely intervention in pancreatic cancer.

Algorithms, Artificial Intelligence, Cancer, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, Data, Defense Advanced Research Projects Agency (DARPA), Diagnostics, Electrical Engineering & Computer Science (eecs), Health sciences and technology, Machine learning, Medicine, MIT Schwarzman College of Computing, National Science Foundation (NSF), Research, School of Engineering, Technology and society, UncategorizedMarch 7, 202440Views0Likes0Comments
MIT Computer Science and Artificial Intelligence Laboratory (CSAIL) scientists, in collaboration with Limor Appelbaum, a scientist in the Department of Radiation Oncology at Beth Israel Deaconess Medical Center (BIDMC), have developed two machine-learning models for the early detection of pancreatic cancer. The two models PRISM and the logistic regression model both surpassed current diagnostic methods.…

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