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Wrapping standard CLI coding agents in a state-persisting orchestration layer beats unconstrained autonomous agents at research completeness without altering the underlying model.
LLMs still struggle to apply public policy knowledge in real-world scenarios, even when they can memorize facts and understand concepts.
Training massive LLMs on a single GPU is now possible, potentially democratizing access to large-scale model development.
