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Researchers from MIT CSAIL and EECS evaluated how closely language models could keep track of objects that change position rapidly. They found that they could steer the models toward or away from particular approaches, improving the system’s predictive capabilities (Credits: Image designed by Alex Shipps, using assets from Shutterstock and Pixabay).

The unique, mathematical shortcuts language models use to predict dynamic scenarios

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

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The unique, mathematical shortcuts language models use to predict dynamic scenarios

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

Simulation-based pipeline tailors training data for dexterous robots