No, its even more fundamental than that: the entire goal of broad reasoning over input data makes it impossible to have a sharp instruction/data division.

The structured input that every modern chat-focussed model expects makes it very clear that they can be trained to distinguish different kinds of input, and some of those patterns now include different priority levels of instruction.

That really isn't true. There's no law of physics preventing you from having separate data and instruction inputs to models. The model's transcript format generally distinguishes between prompts and instructions and tool output and such. This isn't a solved problem, and it's possible it's entire unsolvable, but it probably is possible (in general, not with current models) to reject prompt injection to several nines.

This is a lot like making the same statement about CPUs, "the von Neumann architecture doesn't distinguish between code and data so it's impossible to reject malicious instructions." There's actually a lot you can do to reject malicious instructions, you can prevent execution in certain pages, you can prevent certain privileged instructions from being executed in certain pages, you can employ stack cookies, et cetera. Do they prevent all exploitation in all circumstances? No. But each component does function in it's lane and it is possible to create programs with high (though not absolute) guarantees against unauthorized code execution by composing them.

Similarly, you could prevent certain tokens from appearing in the prompt portions of a transcript, you can have a model with multiple input heads only one of which is trusted, etc. I'm not saying those techniques will necessarily work, but it is more complex than "models can only possibly take a single and undifferentiated input stream".

Speculation: I think we must accept that prompt injection happens, and structure the security of the rest of the system around that. Data given to an LLM becomes an agent, so maybe we must give permissions to this data, instead of to the LLM. Not sure exactly how this would look like in practice!

...

Oh wait.

Yes, the above was referring to programming languages. Which is what prompts are, essentially. It's just a different (and more verbose) way of instructing the computer on what to do. It also has a solution space of infinity and is ambiguous enough that there is no way to secure it because there are infinite combinations of saying anything imaginable. All prompt injections do is prove this point, over and over and over again, and "prompting" an LLM is just reverse-engineering programming languages in the worst possible way. I suspect that we will eventually have no other choice but to revert to using programming languages because they are the only way to get the kind of protections that people are trying to come up with with all these containerization and virtualization systems (which inevitably fail).

As in real life it wouldn't be any good at doing anything but it'd be able to see fault in others and deny actions.

As a loose comparison, hardware bit errors happen probabilistically, yet they’re so rare that we can effectively ignore them in day-to-day use assuming no specialized application (e.g. defense, space, critical infrastructure).

LLMs aren’t there yet, but it’s entirely plausible that structures may can be developed to solve the problem, and those structures aren’t known or commonly conceived of in the present.