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New high of 32%...
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New research shatters AI security assumptions, showing that poisoning large models is easier than believed and requires a very small number of documents.
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The research challenges the conventional wisdom that an attacker needs to control a specific percentage of the training data (e.g., 0.1% or 0.27%) to succeed. For the largest model tested (13B parameters), those 250 poisoned samples represented a minuscule 0.00016% of the total training tokens. Attack success rate remained nearly identical across all tested model scales for a fixed number of poisoned documents.

This story was originally published on HackerNoon at: https://hackernoon.com/7-major-learnings-from-the-ai-engineering-sf-world-fair-2025.
AI coding agents dominated the 2025 SF World’s Fair. From spec-driven dev to cloud agents, here are 7 takeaways shaping AI-native engineering.
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AI coding agents dominated the 2025 SF World’s Fair. From spec-driven dev to cloud agents, here are 7 takeaways shaping AI-native engineering.