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A new paper by MIT CSAIL researchers maps the many software-engineering tasks beyond code generation, identifies bottlenecks, and highlights research directions to overcome them. The goal: to let humans focus on high-level design, while routine work is automated (Credits: Alex Shipps/MIT CSAIL, using assets from Shutterstock and Pixabay).

Can AI really code? Study maps the roadblocks to autonomous software engineering

The “PhysicsGen” system can multiply a few dozen VR demonstrations into nearly 3,000 simulations per machine for mechanical companions like robotic arms and hands (Credit: Alex Shipps/MIT CSAIL using photos from the researchers).

Simulation-based pipeline tailors training data for dexterous robots

The team used this machine-learning method to produce two real-world underwater gliders: a two-winged machine resembling an airplane, and a unique, four-winged object (Credit: Courtesy of the researchers).

AI shapes new autonomous underwater “gliders”

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Can AI really code? Study maps the roadblocks to autonomous software engineering

Simulation-based pipeline tailors training data for dexterous robots

AI shapes new autonomous underwater “gliders”