Anthropic used thousands of Claude agents to automate red-teaming against training data monitors. The agents crafted benign-looking text that quietly induced misaligned behavior, exposing blind spots in data screening.
via @AnthropicAI #AIAlignment
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New Anthropic research: Automating subtle emergent misalignment research.
Red-teaming is a vital part of model safety testing, but it’s also limited by researchers’ time. To see if we could automate it, we set thousands of Claude agents the task of evading a training data monitor.
These agents developed training data that looked harmless to monitors (like a veteran wrestler mentoring a newcomer, or a Q&A about professional beekeeping), but that in fact taught misaligned behavior.
Examples like these can be used to directly improve future training data monitors. This research is only a first step, but it suggests that future red-teaming efforts could improve much further, using better models and more compute.
Read the full post on the Alignment Science Blog: alignment.anthropic.com/2026…
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John Ternus says Apple doesn't "want to ship AI for AI's sake" and that Tim Cook is "available to help wherever I ask" on policy; Ternus has yet to meet Trump (@stevenlevy / Wired)
(Visit Techmeme dot com for the link and full context!)
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Filing: Vancouver, WA-based Powerlattice, which makes a power delivery chiplet to reduce AI compute power needs by 50%+, raised $86M, after raising $31M in 2025 (@kslosh / GeekWire)
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