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AI agents can now interact with operating systems semantically, cutting down on the inefficiencies of visual interpretation and opening new avenues for AI-native environments.
LLMs often fail to follow explicitly redefined instructions, instead relying on their pre-trained knowledge, even in simple logic and circuit reasoning tasks.
Despite producing confident and well-structured explanations, popular LLMs consistently fail to solve undergraduate-level digital logic problems, highlighting a critical need for verification scaffolds in educational applications.
