And the second llm is running on the same basic principles as the first, so it might be 2 or 4 times harder, but it’s unlikely to be 1000x. But here we are.
You’re welcome to prove me wrong, but I expect if this problem was as easy to solve as you seem to think, it would be more solved by now.
Moving goalposts, you are the one who said even 1000x would not matter.
The second one does not run on the same principles, and the same exploits would not work against it, e g. it does not accept user commands, it uses different training data, maybe a different architecture even.
You need a prompt that not only exploits two completely different models, but exploits them both at the same time. Claiming that is a 2x increase in difficulty is absurd.
1st, I didn’t just say 1000x harder is still easy, I said 10 or 1000x would still be easy compared to multiple different jailbreaks on this thread, a reference to your saying it would be “orders of magnitude harder”
2nd, the difficulty of seeing the system prompt being 1000x harder only makes it take 1000x longer of the difficulty is the only and biggest bottleneck
3rd, if they are both LLMs they are both running on the principles of an LLM, so the techniques that tend to work against them will be similar
4th, the second LLM doesn’t need to be broken to the extent that it reveals its system prompt, just to be confused enough to return a false negative.
Obviously the 2nd LLM does not need to reveal the prompt. But you still need an exploit to make it both not recognize the prompt as being suspicious, AND not recognize the system prompt being on the output. Neither of those are trivial alone, in combination again an order of magnitude more difficult. And then the same exploit of course needs to actually trick the 1st LLM. That’s one pompt that needs to succeed in exploiting 3 different things.
LLM litetslly just means “large language model”. What is this supposed principles that underly these models that cause them to be susceptible to the same exploits?
And the second llm is running on the same basic principles as the first, so it might be 2 or 4 times harder, but it’s unlikely to be 1000x. But here we are.
You’re welcome to prove me wrong, but I expect if this problem was as easy to solve as you seem to think, it would be more solved by now.
Moving goalposts, you are the one who said even 1000x would not matter.
The second one does not run on the same principles, and the same exploits would not work against it, e g. it does not accept user commands, it uses different training data, maybe a different architecture even.
You need a prompt that not only exploits two completely different models, but exploits them both at the same time. Claiming that is a 2x increase in difficulty is absurd.
1st, I didn’t just say 1000x harder is still easy, I said 10 or 1000x would still be easy compared to multiple different jailbreaks on this thread, a reference to your saying it would be “orders of magnitude harder”
2nd, the difficulty of seeing the system prompt being 1000x harder only makes it take 1000x longer of the difficulty is the only and biggest bottleneck
3rd, if they are both LLMs they are both running on the principles of an LLM, so the techniques that tend to work against them will be similar
4th, the second LLM doesn’t need to be broken to the extent that it reveals its system prompt, just to be confused enough to return a false negative.
Obviously the 2nd LLM does not need to reveal the prompt. But you still need an exploit to make it both not recognize the prompt as being suspicious, AND not recognize the system prompt being on the output. Neither of those are trivial alone, in combination again an order of magnitude more difficult. And then the same exploit of course needs to actually trick the 1st LLM. That’s one pompt that needs to succeed in exploiting 3 different things.
LLM litetslly just means “large language model”. What is this supposed principles that underly these models that cause them to be susceptible to the same exploits?