Comment by crooked-v
7 hours ago
I doubt it's possible, regardless of specific architecture, because if you want an AI that can do general purpose tasks like "look at my calendar and find a restaurant for the lunch meeting that the other people also like, but make sure nobody has to travel more than 20 minutes to get there, and it can't be too cold inside", then it has to ingest and understand a bunch of data to do that. The whole point is that the decision-making process is reading everything. The only "fix" is to make an AI smart enough that it can understand context for each item, which is a tall order.
> The only "fix" is to make an AI smart enough that it can understand context for each item, which is a tall order.
Impossible as you said. Context isn’t static, it’s continuous, analog, and a conglomeration of viewpoints.
AI cannot create useful context for itself because it is a machine with no desires. It doesn’t have a point of view, it has historical records. It moves forward in time by walking backwards (if that makes sense?)
This is especially true because so much of that data comes from outside of your organization. I receive Google Calendar invites from scammers a couple of times a week and those show up in my invitation list just like anything else. If LLMs start screening things, that kind of thing will become even more popular but most of us can’t just ignore everyone outside of our employer’s directory.
Humans are vulnerable to prompt injection as well. We usually call it something like "social engineering."
Yes, it's a serious problem. It's why we remove humans from these systems whenever possible!
Right, and add controls to limit the damage they can do where possible. Avoiding prompt injection looks to require superhuman intelligence.