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Today's AI agents are surprisingly inept at navigating the messy reality of digital workspaces, failing to reach even 70% accuracy on tasks that require understanding file dependencies.
LLMs can now cook up database-native functions with 34% higher accuracy, even creating entirely new functions missing from current database versions.
Current image editing models stumble when domain-specific knowledge is required, as revealed by a new benchmark spanning disciplines from natural science to social science.
LLMs can now more accurately answer questions on complex documents thanks to a new system that understands layout and hierarchical relationships between document components.
A principled framework for General World Models reveals the limitations of current systems and the architectural requirements for future progress.
