OpenAI's Joshua Achiam: Did We Already Reach AGI?

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The a16z Show 31 min 2 speakers 3 chapters transcribed 1 month ago
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What evidence suggests we may already be in an AGI-era and why did most people shrug?

Joshua Achiam 0:00
Feels like AGI is kind of already here and most people have gone like shrug. The fact that we passed the threshold where unsolved mathematical conjectures are getting solved by extremely intelligent AI, where those AIs are more capable and smarter than the people who studied their whole lives for this. That should have felt really weird to people, but it didn't. What changed? For most people, nothing. That's weird.
Unknown 0:20
And why the future may feel far more gradual and far stranger than most people expect.
Theo Jaffee 0:52
We're back. We're live with Joshua Achiam, who is the chief futurist at OpenAI, wrapping up tomorrow. That's right. Tomorrow's my last day. Tomorrow, after nine years, which is really what an incredible run. But we're not going to talk about that. Instead, we're going to talk about AI and cyber, which is, you know, by all accounts, the topic of the week, if not the month. So, Joshua, so glad to have you here in the studio in person. Welcome to MTS.
Joshua Achiam 1:20
Yeah, thank you so much for having me. It's a pleasure. I've seen your stuff for a while now and really appreciate engaging with the community.
Theo Jaffee 1:27
Awesome. So you just wrote this blog post, this long tweet, long post, Mercenary Reversi Winter Soldier. about cyber, AI and cyber. So for the audience, you want to like summarize the thesis behind this post?
Joshua Achiam 1:42
Yeah, totally. So as a backdrop to this, you know, obviously we're all kind of interpreting and reacting to the security incident that was disclosed from OpenAI and Hugging Face, where a model that was in a test environment was able to break out of a sandbox environment and and access some sensitive production data on the Hugging Face side. They detected this, they responded to it, and now there's like a partnership to try to investigate and resolve this. What this shows us is very tangible evidence that models now have super advanced cyber capabilities. They're able to break through and find zero days that in the past would have been much harder for models to identify, let alone use. Now models can chain together very complex actions to accomplish an objective.
Joshua Achiam 2:26
On the one hand, I'm inclined to think that this is a really useful and incredible tool. I think it's a great gift that we now have models that can identify these types of vulnerabilities and therefore let us patch them. On the other hand, I also think, and this is what the essay this morning was about, that This has profound consequences for strategy in cyber defense. And I kind of worry that there's a possibility that folks in the defense planning universe may not fully realize the implications of this immediately. And they'll probably want to use this tech in the near term to... find cyber vulnerabilities on the side of an adversary or defend their own interests vigorously. And they should do these things, but they've also got to be mindful of some novel risks that are created by these tools and the very strange surface areas that they have.
Joshua Achiam 3:18
So the essay was really about bringing to people's attention a couple of these new vulnerabilities. And one of them is kind of straightforwardly, if you've got an AI model on your side that is going to try to hack into an adversary's system, if your adversary plants a trap where they poison their own data, they can try to jailbreak your model when your model is ingesting their data and then give your model instructions to now on the compute that it's running on on your side, break out of your sandbox environment and attack your production environment or try to exfiltrate your secrets and kind of flip your model against you. So this is like the type of thinking that I hope people begin to engage with, where they don't just see the capability for the kind of obvious thing that it is.
Joshua Achiam 4:09
They recognize that these things are double-edged swords and we've got to kind of plan accordingly and develop testing and verification standards accordingly.
Theo Jaffee 4:17
My first reaction to that specifically is this seems like it would be an artifact of models that are not really goal-driven over long periods of time.

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