AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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Large language model agents are increasingly deployed for long-horizon task execution, raising a central granularity question for trajectory evaluation: whole-trajectory verification is too coarse to capture concrete failures and their associated evidence in long trajectories, while atomic-step scoring is too fine-grai...
Envs-FORGE is presented, a prompting policy that converts verifier rewards into per-seed environment-synthesis actions and solves a per-seed mixed-integer linear program (MILP) to choose the action that conditions generation.
The DataFoundry is introduced, a framework for evolving data preparators through recursive self-improvement before large-scale data production, and it is found that recursively evolved preparators produce training data with higher downstream utility than baselines.
LazyTrain is proposed, an optimization layer over a layer-streaming executor that formulates checkpoint selection, activation placement, recomputation, and CPU-GPU-NVMe communication overlap as a mixed-integer scheduling problem, then executes the solved policy during training.
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