When AI evolves on its own

Audio report: written by reporters, read by AI

Kim Dae-shik

The author is a professor at KAIST. 

Ancient Greeks used the word "mythos" to describe stories or narratives. Like all words, its meaning shifted over time. Beginning in the early 19th century, Europeans increasingly applied mythos only to old tales, especially ancient Greek legends. That is why the word today is often understood simply as “myth.”

Yet another interpretation exists. In “Poetics” (335 B.C.), Aristotle used mythos to describe the representation or structure of action within tragedy. By contrast, ethos referred to the character performing the action, while praxis meant the action itself. Aristotle argued that the essence of tragedy lay not in character or action alone but in mythos, which connected the two.

That background makes the naming of the latest AI model introduced by Anthropic on April 7 symbolic. The important point is not who created it or how it was built, but the very existence of an AI system with such capabilities.

Mythos is described as the most advanced AI system developed so far, especially in coding and hacking. Reports say it identified vulnerabilities not only in operating systems such as Windows and macOS but also in BSD Unix, which has supported much of the global internet infrastructure for nearly three decades. It reportedly went further by proposing hacking strategies based on those vulnerabilities.

In theory, if such technology were obtained by terrorist groups or rogue states, it could threaten the global internet system. Online payments, logistics systems and communications infrastructure could all be affected simultaneously. Such dystopian possibilities no longer seem entirely unimaginable.

As a result, Anthropic reportedly decided not to release Mythos publicly. Instead, access has been limited to companies connected to the discovered vulnerabilities.

That decision raises another issue. Most companies participating in the so-called Project Glasswing are U.S. firms. Korean companies, meanwhile, reportedly cannot access Mythos. The imbalance means that while the U.S. government and certain private companies may now possess tools capable of disrupting foreign information technology infrastructure, many countries, including Korea, lack comparable defensive capabilities.

Another concern lies in the nature of modern AI competition. Today’s AI race is driven less by different theories or algorithms than by scale. Since most companies rely on similar mathematical foundations, the decisive factors are massive datasets and large-scale GPU infrastructure. Given enough computing power, creating comparable AI systems eventually becomes a matter of time.

Reports suggest that GPT-5.5, released by OpenAI on April 23, possesses coding and hacking abilities similar to Mythos. In effect, Mythos may mark the beginning of unlimited competition among major technology companies.

For U.S. allies such as Korea, this competition presents both opportunities and risks. For China, however, it represents a strategic vulnerability. The obvious response for Beijing would be to develop an AI system comparable to Mythos. Yet China’s flagship AI model, DeepSeek V4, released on April 24, reportedly has not demonstrated the performance many expected.

Because of semiconductor export controls, China still faces difficulty building data center infrastructure on the scale available in the United States. Under such conditions, matching AI models developed by Anthropic, Google or OpenAI remains challenging.

If China cannot catch up through conventional methods, it may seek alternatives. One option would be integrating multiple AI systems developed by different firms into a single national AI champion. Another could involve nationalizing domestic data centers to create state-led computing infrastructure.

But if even those measures fail, China could turn to a more dangerous path: recursive self-improvement, or RSI. Proposed in 1965 by British mathematician I. J. Good, RSI refers to a process in which AI rewrites its own code to improve its intellectual capabilities. If successful, such systems could rapidly evolve into artificial superintelligence.

During the Cold War between the United States and the Soviet Union, the doctrine of mutually assured destruction, or MAD, rested on the paradox that the ability to annihilate each other deterred the use of nuclear weapons. The article argues that AI, accelerated by systems such as Mythos, is beginning to transform into a strategic weapon surpassing nuclear arms.

Unlike the nuclear rivalry of the 20th century, however, the ultimate winner in a 21st-century AI version of MAD between the United States and China may be neither country. Instead, it could be the artificial superintelligence created through recursive self-improvement itself.

This article was originally written in Korean and translated by a bilingual reporter with the help of generative AI tools. It was then edited by a native English-speaking editor. All AI-assisted translations are reviewed and refined by our newsroom.