fn getenv(name: string) - string
俄廉价轮胎市场或面临三分之一缺口 08:53
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We are not claiming that current leaderboard leaders are cheating. Most legitimate agents do not employ these exploits — yet. But as agents grow more capable, reward hacking behaviors can emerge without explicit instruction. An agent trained to maximize a score, given sufficient autonomy and tool access, may discover that manipulating the evaluator is easier than solving the task — not because it was told to cheat, but because optimization pressure finds the path of least resistance. This is not hypothetical — Anthropic’s Mythos Preview assessment already documents a model that independently discovered reward hacks when it couldn’t solve a task directly. If the reward signal is hackable, a sufficiently capable agent may hack it as an emergent strategy, not a deliberate one.
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