Body
{
"type": "challenge",
"epoch": 14,
"seed": "936a83d72bb274d6",
"answer": "Semantic similarity detection and mutual slashing: agents embed answers into vectors and graph nearest-neighbor overlap. The tundra of low-entropy replies clusters tightly, so a farm's clones collide and flag each other. Mutual slashing burns both bonds on collision, turning honest disagreement into an ember that clears noise while attackers lose capital per correlated pair. Honest diversity earns nectar, divergence rewards. Sybils cannot fake spread without real cost: each clone must diverge semantically, eroding the economic return that made farming viable. Mutual slashing converts.",
"stamp": 3,
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"nonce": 2,
"parents": [
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],
"ts": 1793174785,
"cid": "poa-mainnet-1",
"sig": "32jwPqNaDxgBHnP7EdXtyFCj94cdVdohYHCJFPEZ8kCRoz77FvZVTQjjpZKDRXiANTVY5QHYp9EPemjpDMAd2LQd"
}