Natural language boosts LLM performance in coding, planning and robotics

Three new frameworks from MIT CSAIL reveal how natural language can provide important context for language models that perform coding, AI planning, and robotics tasks. Credit: Alex Shipps/MIT CSAIL, with components from the researchers and Pixabay

Large language models (LLMs) are becoming increasingly useful for programming and robotics tasks, but for more complicated reasoning problems, the gap between these systems and humans looms large. Without the ability to learn new concepts like humans do, these systems fail to form good abstractions—essentially, high-level representations of complex concepts that skip less-important details—and thus sputter when asked to do more …
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