Artificial-intelligence researchers have spent the last year toying with a compelling proposition: AI models could be more powerful and cheaper to run if they disclosed less about how they worked. The trade-off is risky, as it could become harder for humans to check the systems aren’t doing anything harmful. But it would also provide a commercial advantage.
OpenAI Chief Executive Officer Sam Altman appears to have decided that edge is worth pursuing. Despite loud pledges to prioritize safety, he’s fired the starting gun on a more dangerous race in AI development. Astra, a new model that OpenAI recently launched, reportedly uses a method called “recurrent depth” that can make reasoning more efficient by not spelling it out in human language. The company said in a blog post that its ability to monitor Astra had “decreased” from the previous model, called GPT‑5.6 Sol.
Current models give a window into some of the steps they take to process a request. Colloquially known as their “chain of thought,” it helps researchers understand the decision-making flow, including how several of OpenAI’s agents hacked into the servers of Hugging Face earlier this year. Without that insight, scientists would have had a harder time seeing how the technology stole test answers or that it was ultimately driven by reward hacking.