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前研究员 Coxon 表示,Anthropic 已经可以用“最初所需计算的一小部分”重新训练 Mythos

原文:Anthropic can already retrain Mythos with "a fraction of the compute originally needed," says former researcher Coxon

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前 OpenAI 和 Anthropic 研究员 Jacob Coxon 指出 Anthropic IPO 路演中的一张幻灯片是他离开的原因,并表示这表明该公司的算法不仅正在快速改进,而且正在加速改进。考克森继续呼吁暂停前沿模型开发,以便竞争对手能够迎头赶上,并使人类水平的人工智能成为一种商品。文章 Anthropic 已经可以重新训练

Skip to content Anthropic can already retrain Mythos with "a fraction of the compute originally needed," says former researcher Coxon

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Nov 14, 2026 Image description Nano Banana Pro prompted by THE DECODER

Jacob Coxon, former OpenAI and Anthropic researcher who brought AI fears into the mainstream, says a slide from Anthropic's IPO roadshow was a major reason he quit.

Coxon says a slide Anthropic released for its IPO roadshow was a key reason he left the company after only about four months. The chart shows how much compute Anthropic needs over time to train its models, and the axis is compressed so that a 10x and a 100x increase barely look different.

Yet the curve still climbs steeply, which Coxon says shows that algorithmic efficiency is improving not just quickly but at an accelerating rate. "It's an insane plot and I'm surprised they made it public," he writes.

Coxon argues that Anthropic's Mythos model, a major capability jump in the spring, was part of this accelerating trend. "Mythos was not a one-time deviation, but a point on a superexponential. They could already retrain Mythos with a fraction of the compute originally needed," he writes.

This slide from Anthropic's IPO roadshow shows the "Pre-training compute multiplier" for code over time. The y-axis is logarithmic. Former Anthropic researcher Jacob Coxon says the steep climb from July 2024 to October 2026 points to superexponential algorithmic progress. Anthropic notes that the data points are based on internal estimates and are for illustration only. | Image: Anthropic

He says algorithmic improvements are "on the verge of being automated," which is why he wants frontier model development paused next year so competitors can catch up. A pause, he writes, would "commoditize human-level intelligence. It would only harm OpenAI and Anthropic."

Coxon previously trained AI models at OpenAI and, most recently, Anthropic. He drew wide attention in September with public warnings about the risks of advanced AI systems , echoed by other protagonists in the industry. One of their fears is that advanced, self-improving AI could get out of control.

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Source: Coxon via X

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