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Researchers set out a system-level framework for work agents, dividing digital work into categories and identifying capability groups that they say are needed for reliable execution.
The researchers built a fleet-learning system that pulls supervision from deployed robots’ own executions, a sign policy improvement can continue without new expert demonstrations.
Google researchers said a late-2025 workshop in New York City produced a report on privacy and security challenges for autonomous agents, including a call for standardized multi-agent benchmarks.