전 OpenAI 및 Anthropic 연구원 Jacob Coxon은 Anthropic의 IPO 로드쇼 슬라이드를 퇴사 이유로 언급하며, 이 슬라이드가 Anthropic이 Mythos를 "당초 필요했던 컴퓨팅의 일부"만으로 이미 재훈련할 수 있음을 보여준다고 말했다.

Jacob Coxon, a former OpenAI and Anthropic researcher who helped bring AI fears into the mainstream, says a slide from Anthropic's IPO roadshow was a major reason he left the company after only about four months.

The slide shows how much compute Anthropic needs over time to pre-train its models, specifically the "pre-training compute multiplier" for code. The y-axis is logarithmic, so a 10x and a 100x increase look barely different. Anthropic notes that the data points are based on internal estimates and are for illustration only. Even so, the curve climbs steeply from July 2024 to October 2026. Coxon reads this as evidence 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.

He also 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, at Anthropic. In September he drew wide attention with public warnings about the risks of advanced AI systems, which other industry figures echoed. One of their shared fears is that advanced, self-improving AI could get out of control.