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Common misconceptions about OpenAI — LessWrong

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Comment by paulfchristiano - I think almost all of the acceleration comes from either products that generate $ and hype and further investment, or more directly from scaleup to more powerful models. I think "We have powerful AI systems but haven't deployed them to do stuff they are capable of" is a very short-term kind of situation and not particularly desirable besides. I'm not sure what you are comparing RLHF or WebGPT to when you say "paradigm of AIs that are much harder to align." I think I probably just think this is wrong, in that (i) you are comparing to pure generative modeling but I think that's the wrong comparison point barring a degree of coordination that is much larger than what is needed to avoid scaling up models past dangerous thresholds, (ii) I think you are wrong about the dynamics of deceptive alignment under existing mitigation strategies and that scaling up generative modeling to the point where it is transformative is considerably more likely to lead to deceptive alignment than using RLHF (primarily via involving much more intelligent models).

x Common misconceptions about OpenAI — LessWrong OpenAI AI Frontpage 228 Common misconceptions about OpenAI by Jacob_Hilton 25th Aug 2022 AI Alignment Forum 6 min read 154 228 Ω 64 I have recently encountered a number of people with misconceptions about OpenAI. Some common impressions are accurate, and others are not. This post is intended to provide clarification on some of these points, to help people know what to expect from the organization and to figure out how to engage with it. It is not intended as a full explanation or evaluation of OpenAI's strategy. The post has three sections: Comm

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