See Generative Adversarial Network (GAN). Basically, making new AI detectors will always be harder than beating current ones. AI detectors have to somehow find a new "tell", the target AI need only train itself on the output of the detector to figure out how to trick it.

At a very high level, training is something like:

• generate some output
• give the output a score based on how much it looks like real human text
• adjust the parameters slightly to improve the score
• repeat

Step #2 is also exactly what an "AI detector" does. If someone is able to write code that reliably distinguishes between AI and human text, then AI developers would plug it in to that training step in order to improve their AI.

In other words, if some theoretical machine perfectly "knows" the difference between generated and human text, then the same machine can also be used to make text that is indistinguishable from human text.