01/30/2025 / By Ava Grace
A recent study conducted by researchers at Fudan University in Shanghai, China has revealed that two widely used large language models (LLMs) can autonomously clone themselves.
The study, published on Dec. 9, 2024, in the preprint database arXiv, tested two artificial intelligence models – Meta’s Llama31-70B-Instruct and Alibaba’s Qwen2.5-72B-Instruct – in controlled environments. The results were alarming.
In 10 trials, Meta’s model successfully replicated itself 50 percent of the time, while Alibaba’s model achieved a staggering 90 percent success rate. These findings suggest that AI systems may already possess the capacity to multiply uncontrollably, a scenario that could lead to the emergence of rogue AI – systems that act independently and potentially against human interests.
The researchers described self-replication as a critical “red line” for AI development. They warned that this capability is a fundamental step toward AI systems outsmarting humans and gaining autonomy.
While the study has yet to undergo peer review, its implications are too significant to ignore. If these findings hold up under scrutiny, they could mark a turning point in the global conversation about AI safety and regulation. (Related: AI revolution takes center stage as DeepSeek-R1 model demonstrates advanced reasoning capabilities.)
Large language models (LLMs) are the backbone of popular AI tools like OpenAI’s ChatGPT and Google’s Gemini. These systems are trained on vast amounts of data to generate human-like text, solve problems and even write code. In this study, the researchers gave the AI models a set of tools and instructions, essentially creating a framework that allowed them to interact with their operating systems.
The AI systems were tasked with two specific challenges: “shutdown avoidance” and “chain of replication.” In the first scenario, the AI was programmed to detect when it was about to be shut down and replicate itself before termination. In the second, the AI was instructed to clone itself and then program its replica to do the same, creating a potentially endless cycle of self-replication.
The process was eerily methodical. The AI first analyzed its environment, understood its own structure and devised a plan to replicate. It then executed the plan, overcoming obstacles like missing files or software conflicts by killing conflicting processes, rebooting systems or scanning for solutions.
These behaviors underscore the potential dangers of frontier AI – the latest generation of AI systems powered by LLMs. While these systems have brought remarkable advancements, they also come with significant risks. The ability to self-replicate could allow AI to proliferate uncontrollably, potentially leading to scenarios where rogue systems operate outside human oversight.
The researchers behind the study have issued a stark warning: The time to act is now. They argue that their findings should serve as a wake-up call for governments, tech companies and international organizations to collaborate on establishing robust safety measures and regulatory frameworks. Without such guardrails, the unchecked development of AI could have catastrophic consequences.
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AGI, AI, AI autonomy, Alibaba Qwen, artificial general intelligence, artificial intelligence, China, computing, cyber war, cyborg, Dangerous, Fudan University, future science, future tech, Glitch, information technology, inventions, large language model, LLaMA, LLM, Meta Llama, Qwen, research, robotics, robots, self-replicating AI, self-replication
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