AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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Pretrained macro-placement policies can reduce repeated optimization across circuits, but deployment often exposes them to unfamiliar designs when the original training data are unavailable. Repeatedly fine-tuning a single serving model can overwrite earlier improvements, while simply saving checkpoints does not determ...
LACE is presented, an LLM-aided multi-agent workflow that translates natural-language ISAX intents into a compact two-level IR, performs retrieval-guided localized RTL edits over large repositories, and closes the loop with a compiler-agnostic riscv-formal checking flow.
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