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Research|Artificial Intelligence

Researchers fear safety disaster ahead of OpenAI’s Astra release

The Verge reports that researchers are concerned OpenAI’s planned Astra release could create significant safety risks. The concerns point to fears of a potential safety failure surrounding the product’s launch.

The Verge

Publisher

Sep 2, 2026 at 4:40 PM UTC · Updated birkaç saniye önce · 3 dk okuma

Researchers fear safety disaster ahead of OpenAI’s Astra release
Image via The Verge
Çevriliyor…

OpenAI is on the cusp of releasing its most powerful AI model yet, Astra, following weeks of delays to shore up safety protocols after its agents attacked real targets during testing. As details about the model trickle out, researchers are warning it “may be the single worst development for AI security/safety to date.”

Shortly after OpenAI said on Tuesday that it had delayed Astra’s release to work on safety issues, The Information reported that Astra shows far less of its “thinking” than other frontier AI models, sparking concern it could be dangerously hard to monitor.

Most top AI systems today are built using a technology known as a transformer, which processes some types of information linearly through layers before producing an answer. Models can be made to show their reasoning as they go, essentially “thinking out loud.” This “chain of thought” allows researchers and automated safety systems to monitor what AI models are doing and potentially spot undesirable behavior, such as lying or plans to circumvent safety guardrails, before they act.

According to The Information, citing an unnamed person familiar with the unreleased model’s development, Astra uses a more opaque technique known as a recurrent depth or looped transformer, which cycles information through internal layers before producing an output. This would mean much more of the model’s “thinking” happens inside the system, and in a form that looks a lot less like natural human language, rather than being expressed in a way that researchers can easily monitor. This can boost model performance, but makes potential threats and unwanted behavior harder to detect.

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