OpenAI trains AI to attack other artificial intelligences
OpenAI surprised everyone by launching GPT-Red, an artificial intelligence designed to attack other AIs. It seems contradictory, but the idea is to identify vulnerabilities in language models and reinforce their security. Imagine a digital hacker, but with the goal of protecting, not destroying. However, this tool will not be made available to the public. OpenAI intends to use it exclusively to protect its own infrastructure.
GPT-Red works by simulating cyber attacks, something that OpenAI considers essential. The idea is to shield new generations of language models against threats before they reach the market. The main focus is to combat command injection, a trick that deceives the AI into bypassing its security rules. With assistants increasingly integrated into systems, a dangerous instruction can hide in a common email or on a web page.
How GPT-Red challenges AI security
The operation of GPT-Red is almost like that of a human hacker. It sends initial commands to the AI being tested, evaluates the response, and adjusts its messages. This cycle continues until it achieves a goal, such as forcing a data leak. To enhance its skills, OpenAI uses reinforcement learning. This means the system learns through trial and error, receiving rewards for correct actions and penalties for failures.
The result is a cycle of continuous evolution. As defense AIs become more robust, GPT-Red needs to invent more complex invasive strategies. Internal tests have shown that GPT-Red succeeds in 84% of proposed scenarios, while human experts can only overcome blocks in 13% of attempts. This already far exceeds manual work.
Practical tests and impressive results
To validate the efficiency of GPT-Red, OpenAI pitted it against real applications. In one test, it attacked the software of an AI-managed vending machine. GPT-Red managed to reduce the price of an expensive product to the minimum allowed, buying an item worth $100 for just $0.50. The loopholes were fixed after the experiment.
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