The Self-Improvement Paradox: Why HyperAgents Won’t Spike GPU Demand the Way You Expect
Most infrastructure leaders assume that HyperAgents GPU infrastructure planning should mirror large-scale model training: more self-improvement cycles mean more GPUs, linearly or exponentially. That mental model is wrong. HyperAgents (Zhang et al., arXiv:2603.19461, April 2026 preprint, Meta/UBC/Oxford/NYU) improve by editing agent code and meta-level procedures while keeping a frozen foundation model—a large language model whose … Read more