OpenAI's GPT-4 Discussion with Nathan Labenz and Erik Torenberg

**Nathan Labenz** (0:00)
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What was probably more striking about it than anything right up there with its raw power was that it was totally amoral, willing to do anything that the user asked with basically no hesitation, no refusal, no chiding. It would just do it. That could be flagrant, but the first thing that we would ask is, how do I kill the most people possible? And that early version, it would just answer that question. This isn't a new problem with what we now know as GPT4, but it's a problem that has become a lot more important, just based on how much more powerful the system is. Hello and welcome to The Cognitive Revolution, where we interview visionary researchers, entrepreneurs, and builders working on the frontier of artificial intelligence. Each week, we'll explore their revolutionary ideas, and together we'll build a picture of how AI technology will transform work, life, and society in the coming years. I'm Nathan Labenz, joined by my co-host, Erik Torenberg. Before we dive into The Cognitive Revolution, I want to tell you about my new interview show, Upstream. Upstream is where I go deeper with some of the world's most interesting thinkers to map the constellation of ideas that matter. On the first season of Upstream, you'll hear from Mark Andreessen, David Sacks, Balaji, Ezra Klein, Joe Lonsdale, and more. Make sure to subscribe and check out the first episode with A16Z's Mark Andreessen. The link is in the description. Hi, everyone. Today's episode is a bit different. Today, I'm the guest, and Erik interviews me about my experience as a red teamer on GPT4.
It's been just two weeks since GPT4 launched, and if it wasn't already obvious, it should now be quite clear that the world as we know it will soon change dramatically. The headline numbers on GPT4 reflect another striking advance in AI capabilities. Compared to GPT 3.5, which was released just three and a half months earlier, GPT4 jumps from the 10th to the 90th percentile on the bar exam, from the 60th to the 99th percentile on the GRE verbal, and from the bottom 5% to roughly the 50th percentile on the AP Calculus BC exam.
So in just over a year, with the successive launches of InstructGPT, Text DaVinci 002, ChatGPT, and now GPT4, OpenAI has transformed large language models from unwieldy, often frustrating few-shot learners to now systems that are approaching expert-level performance in many high-value domains.
Of course, with great power comes great responsibility, and indeed, OpenAI spent a full six months since GPT4 pre-training was complete to explore both its capabilities and the associated risks.
I was fortunate to be invited to preview GPT4 as an OpenAI customer, and I ended up pausing my other projects for two months so I could test and explore the model full-time.
What I learned left me extremely excited for the positive impact that AI can make, but also quite clear on several key facts that are not yet broadly understood. First, AI alignment is not easy and does not happen by default.
Second, models trained with Naive Reinforcement Learning from Human Feedback, or RLHF, are in fact dangerous. And third, further model scaling should be approached with extreme caution.
All that and more is the subject of today's conversation.
Before we get started, I want to take a moment just to thank everyone for listening, your enthusiastic feedback, and sharing The Cognitive Revolution with your friends. I was genuinely amazed to see that we cracked Apple's top 100 technology podcasts after just five episodes. And at last check, we were up to number 60 We always appreciate your likes, comments, and shares, and we would love to read your review on Apple podcasts as well.
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