AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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TokenCast is proposed, which learns a composable cost representation for each execution segment, recording its own consumption and the context growth it introduces, and captures the extra input cost incurred when context from earlier segments is re-read by every later call.
This work argues that studying AI Scientists as human-agent systems (HAS) is both underexplored and undervalued, and calls for new research that adopts the HAS lens to develop mathematical frameworks for understanding and fostering human-AI synergy in scientific discovery.
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