3-D

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AI agents create virtual playgrounds to help robots get crucial training data

3-D, ai, AI (Artificial Intelligence), Artificial Intelligence, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, Electrical engineering and computer science (EECS), Machine Learning, MIT Schwarzman College of Computing, National Science Foundation (NSF), Research, Robotics, School of Engineering, Simulation

Robots walking down the street, surrounded by astounded onlookers, is an increasingly common sight. But these machines aren’t yet the do-it-all assistants you’d want working in a kitchen or factory, and a major bottleneck is data. Much like humans, robots learn best by experience. The challenge is that it’s labor-intensive and time-consuming to physically teach […]

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Deep-learning model predicts how fruit flies form, cell by cell

3-D, Animals, Artificial Intelligence, Biology, Cells, Computer vision, Imaging, Machine Learning, Mechanical engineering, National Institutes of Health (NIH), Research, School of Engineering, Self-assembly

During early development, tissues and organs begin to bloom through the shifting, splitting, and growing of many thousands of cells.A team of MIT engineers has now developed a way to predict, minute by minute, how individual cells will fold, divide, and rearrange during a fruit fly’s earliest stage of growth. The new method may one

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New AI agent learns to use CAD to create 3D objects from sketches

3-D, Artificial Intelligence, automation, Computer modeling, Design, Machine Learning, Mechanical engineering, Research, School of Engineering, Software

Computer-Aided Design (CAD) is the go-to method for designing most of today’s physical products. Engineers use CAD to turn 2D sketches into 3D models that they can then test and refine before sending a final version to a production line. But the software is notoriously complicated to learn, with thousands of commands to choose from.

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