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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, 202433Views0Likes0Comments
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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Startup advances the journey towards computing at the speed of light.

Alumni/ae, Artificial Intelligence, Computer science and technology, Data, Electrical Engineering & Computer Science (eecs), Electronics, Innovation and Entrepreneurship (I&E), Machine learning, MIT $100K competition, Photonics, School of Engineering, Startups, Sustainability, Sustainable computing, UncategorizedJune 13, 202436Views0Likes0Comments
In today's digital era, the demand for ever-increasing computing power has been overwhelmingly huge, driven primarily by advancements in artificial intelligence. However, the constant innovation in computing technology is facing obstacles, primarily due to the limitations in the shrinking size of transistors used in chips. This imposes a strict limit on Moore's Law and Dennard's…

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Researchers utilize extensive language models to assist robots with navigation.

Artificial Intelligence, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, Computer vision, Data, Electrical Engineering & Computer Science (eecs), Machine learning, MIT Schwarzman College of Computing, MIT-IBM Watson AI Lab, Research, Robotics, Robots, School of Engineering, UncategorizedJune 12, 202430Views0Likes0Comments
Researchers from MIT and the MIT-IBM Watson AI Lab have developed a language-based navigational strategy for AI robots. The method uses textual descriptions instead of visual information, effectively simplifying the process of robotic navigation. Visual data traditionally requires significant computational capacity and detailed hand-crafted machine-learning models to function effectively. The researchers' approach involves converting a…

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A new AI model has the potential to enhance procedures in a robot-operated warehouse.

Algorithms, Artificial Intelligence, Civil and environmental engineering, Computer science and technology, IDSS, Laboratory for Information and Decision Systems (LIDS), Machine learning, MIT Schwarzman College of Computing, Research, Robots, School of Engineering, UncategorizedJune 10, 202433Views0Likes0Comments
MIT researchers have developed a deep-learning model to improve the efficiency of warehouse robots. The team used a neural network architecture to encode features including the robots' paths, tasks, and obstacles in the warehouse. This enabled the model to predict where congestion was most likely to occur and take measures to counteract it. The groundbreaking method…

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A new AI model has the potential to improve efficiency in automated warehouse processes.

Algorithms, Artificial Intelligence, Civil and environmental engineering, Computer science and technology, IDSS, Laboratory for Information and Decision Systems (LIDS), Machine learning, MIT Schwarzman College of Computing, Research, Robots, School of Engineering, UncategorizedJune 10, 202433Views0Likes0Comments
MIT researchers have designed an artificial intelligence solution to help robotic warehouses operate more efficiently. Automated warehouses, which employ hundreds of robots to pick and deliver goods, are becoming more commonplace, especially in industries such as e-commerce and automotive production. However, coordinating this robot workforce to avoid collisions, while also maintaining a high operational pace,…

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