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Generative AI for Beginners

microsoft.github.io

51–60 of 104 posts

Re: Generative AI for Beginners

#51

Earlier quoted context omitted.

Everyone + dog is adding "AI" to their products and "nobody ever got fired by buying Microsoft" so...

Why would someone be fired over what company they bought an LLM from?

Because if your product sucks and can be traced to using an unproven LLM, you will get the blame for betting on an unknown.

Re: Generative AI for Beginners

#52
post #48

Andrej Karpathy's "Zero to Hero" series on YouTube is the ultimate guide to building LLMs. Extremely information-dense but as complete as it gets: https://www.youtube.com/playlist?list=PLAqhIrjkxbuWI23v9cThs... Also, an amazing high-level overview of LLMs, including extensive discussion about attack vectors, that he published a couple days ago: https://www.youtube.com/watch?v=zjkBMFhNj_g

[deleted]

Re: Generative AI for Beginners

#53

Earlier quoted context omitted.

Why would someone be fired over what company they bought an LLM from?

Because if your product sucks and can be traced to using an unproven LLM, you will get the blame for betting on an unknown.

It is trivial to swap LLM considering most LLM are compatible with the OpenAPI API.

Re: Generative AI for Beginners

#54
post #35

Earlier quoted context omitted.

I diagree. Structured output may look like it helps address prompt injection, but it doesn't protect against the more serious implications of the prompt injection vulnerability class. My favourite example is still the personal AI assistant with access to your email, which has access to tools like "read latest emails" or "forward an email" or "send a reply". Each of those tools requires valid JSON output saying how th…

I'm trying to understand the vulnerability you are pointing out; in the example of an AI assistant w/ access to your email, is that AI assistant also reading it's instructions from your email?

Yes. You can't guarantee that the assistant won't ever consider the text of an incoming email as a user instruction, and there is a lot of incentive to find ways to confuse an assistant in that specific way.

BTW, I find it weird that the Von Neumann vs. Harvard architecture debate (ie. whether executable instructions and data should even exist in the same computer memory) is now resurfacing in this form, but even weirder that so many people don't even see the problem (just like so many couldn't see the problem with MS Word macros being Turing-complete).

Re: Generative AI for Beginners

#56
post #35

Earlier quoted context omitted.

I diagree. Structured output may look like it helps address prompt injection, but it doesn't protect against the more serious implications of the prompt injection vulnerability class. My favourite example is still the personal AI assistant with access to your email, which has access to tools like "read latest emails" or "forward an email" or "send a reply". Each of those tools requires valid JSON output saying how th…

I'm trying to understand the vulnerability you are pointing out; in the example of an AI assistant w/ access to your email, is that AI assistant also reading it's instructions from your email?

The key problem is that an LLM can't distinguish between instructions from a trusted source and instructions embedded in other text it is exposed to.

You might build your AI assistant with pseudo code like this:

    prompt = "Summarize the following messages:"
    emails = get_latest_emails(5)
    for email in emails:
        prompt += email.body
    response = gpt4(prompt)
That first line was your instruction to the LLM - but there's no current way to be 100% certain that extra instructions in the bodies of those emails won't be followed instead.
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