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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.
AI research agents can now reliably trace method evolution topologies thanks to a new methodological evolution graph, Intern-Atlas, that captures structured relationships between research methods.
A principled framework for General World Models reveals the limitations of current systems and the architectural requirements for future progress.
