| ▲ | nater5000 9 hours ago | ||||||||||||||||||||||||||||
>Who will find this useful? It's worth reading past the opening paragraph before asking these kinds of questions: >When a user sends a request to an AI model, today they have no way of knowing for certain that the model they selected is the one that generated the response. For everyday uses, in which users mostly care about the output and not necessarily which specific model produced it, this is a less pressing concern. But there are several cases where such assurance would be useful. For example, independent evaluators who test AI models before and after release need to know that the model they are evaluating is the model being served. Clients who use a model through a third-party routing service want assurance that the tokens came from the model they paid for. And if a cyberattacker modifies the token stream while pretending to be a given model, a user has no way to detect it from the output alone. This is from the first paragraph in the Introduction. | |||||||||||||||||||||||||||||
| ▲ | grey-area 9 hours ago | parent [-] | ||||||||||||||||||||||||||||
I didn't find any of it compelling, perhaps you do. That's what I was asking really, which of these use-cases is valuable for you? For me if you use a routing service you have to trust it, it sees all your inputs and outputs. If a cyberattacker can modify the token stream (i.e. man in the middle your traffic), you should be worried about a lot more than which model you're using! | |||||||||||||||||||||||||||||
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