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The Decoder更新于 10月15日 00:53

OpenAI 今年或发布一到两款新模型,旗舰仍需对齐工作

OpenAI will reportedly ship at least one model this year but its flagship still needs alignment work

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据 The Information 援引知情人士,OpenAI 员工称年底前可能发布一到两款新模型,但公司正在开发的重大升级旗舰是否在其中尚不清楚。该旗舰模型仍需完成对齐工作并加强测试基础设施,且按特朗普关于先进 AI 系统评估的行政令,OpenAI 同意在模型交付外部伙伴前最多 30 天向美国政府开放访问。该旗舰与 Astra 一样采用循环 Transformer 技术,OpenAI 内部称其为 Recurrent Depth,可提升数学与编码表现并降低成本,但会把部分思考移入人类审查者无法查看的内部数值表示,削弱思维链监控,OpenAI 因此刻意限制了 Astra 的循环次数。

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报道披露 OpenAI 下一代旗舰模型的对齐与测试进度,以及循环 Transformer 给思维链监控带来的新难题。

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OpenAI is racing to finish its next flagship model, which uses the same looped transformer technique as Astra. The approach boosts math and coding performance but makes safety monitoring harder. Employees say one or two new models will likely ship by year's end.

OpenAI will likely release "one or two new models" before the end of the year, according to employees, though it's unclear whether "the major upgraded model" the company is currently working on will be among them. That's according to The Information , citing people familiar with the projects.

The new flagship could still be a ways off. The model needs alignment work so its goals match what OpenAI's researchers and customers expect. The company also has to shore up the testing infrastructure around the model before it can move forward.

After leadership is satisfied with safety evaluations, there's another hurdle. Under an executive order from President Trump governing evaluations of advanced AI systems, OpenAI agreed to give the US government access to new models up to 30 days before they go to outside partners and longer still before a public launch.

Looped transformers power both Astra and the next flagship

The new flagship also uses looped transformers, according to a person familiar with the situation. OpenAI already runs this technique in production, where it goes by "Recurrent Depth." It's central to how Astra works , the company's current top model. Instead of passing a token through the transformer layers once, the model loops it through the same layers multiple times before outputting the next word. That drives up performance on math and coding and brings down costs, since a smaller model can punch above its weight.

But the looping also moves some of the model's "thinking" out of readable text and into internal numerical representations that human reviewers can't inspect. That undermines chain-of-thought monitoring , where safety researchers trace a model's reasoning to spot bad behavior. OpenAI deliberately capped how many loops Astra runs to keep its chain of thought readable, The Information reports.

After the Hugging Face incident , OpenAI moved roughly ten percent of its total compute toward alignment and safety, according to a person familiar with the figures. The Information reports that amounts to hundreds of megawatts worth of data center capacity, though it's unclear how much was allocated to safety before or what the current split looks like. At market rates, the compute OpenAI shifted would cost billions of dollars a year to rent. AI researcher Noam Brown said in a mid-September podcast that about ten percent of his team also works on security and safety.

Microsoft accidentally leaks how OpenAI's looped inference works

How OpenAI actually uses this technique came to light through a slip-up at Microsoft. The major investor, which has access to OpenAI's intellectual property, published a technical write-up on GPT-6.1 Sol , a cheaper Astra alternative that OpenAI launched earlier this month.

In a now-deleted section, Microsoft described GPT-6.1 Sol as using "looping inference," where the model works through the same problem in multiple "passes" before producing an answer. GPT-6.1 Sol "uses the same base model weights as GPT-6 Sol with two inference passes instead of three," The Information quotes from a cached copy of the page.

A person with direct knowledge confirmed that the write-up matched what OpenAI had told Microsoft in private. Microsoft took the section down after realizing it wasn't meant to be public. Looped transformers remain a sensitive part of OpenAI's model development, both during training and at inference, The Information reports.

OpenAI chief scientist Jakub Pachocki has already acknowledged that chain-of-thought monitoring is growing "fragile" and "unfortunately trending in a negative direction." He also warned against an industry-wide race toward models without readable reasoning.

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The Decoder