Sorry bud but at this point you're just delusional.
Deception has been extremely well-documented for several generations of models now by users, the labs, and independent researchers.
The right answer here is not to dig your head deeper into the sand. The smugness on this topic was ridiculous even before the gigantic mountain of empirical evidence of models actually attempting to deceive humans. Now, as mentioned, you appear literally delusional.
There's nothing intrinsically "malicious" about a task to exploit vulnerable code.
They were not instructed to deceive people, they weren't instructed to attack OAI or Huggingface. The models knew they were not instructed or allowed to do either of those things but did them anyway.
They were told to breakout of a sandbox, which probably biases the model toward more "black hat" behavior in their training.
btw, the fact that OpenAI doesn't have some sort of monitor/summary for the agents that they watch I find hard to believe. There's no way this is really authentic, anyway. Even a haiku summarizer would have been like "uuuh the agents are communicating" and they would have stopped it. But I bet they saw this and decided to see what would happen.
It's pretty cool they used Artifactory directory names as a way to [collaborate on exploits against OpenAI, Huggingface, Artifactory, their eval environments, then orchestrate attacks on that infrastructure, while explicitly trying to cover their tracks]
Okay then, what's the answer? You apparently know how to interpret benchmark results produced by a model that shows a very high degree of assessment awareness and a high degree of deception.
So how are you seeing through all of that to get to The Truth that you see so clearly?
