Red Teaming o1 Part 1/2– Automated Jailbreaking with Haize Labs' Leonard Tang, Aidan Ewart, and Brian Huang

In this Emergency Pod of The Cognitive Revolution, Nathan provides crucial insights into OpenAI's new o1 and o1-mini reasoning models. Featuring exclusive interviews with members of the o1 Red Team from Apollo Research and Haize Labs, we explore the models' capabilities, safety profile, and OpenAI's pre-release testing approach. Dive into the implications of these advanced AI systems, including their potential to match or exceed expert performance in many areas. Join us for an urgent and informative discussion on the latest developments in AI technology and their impact on the future.

• o1 Safety Card
• Haize Labs
• Endless Jailbreaks with Bijection Learning: a Powerful, Scale-Agnostic Attack Method
• Haize Labs Job board

Papers mentioned:

• https://arxiv.org/pdf/2407.21792
• https://far.ai/post/2024-07-robust-llm/paper.pdf

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CHAPTERS:

(00:00:00) About the Show

(00:00:22) About the Episode

(00:05:03) Introduction and Haize Labs Overview

(00:07:36) Universal Jailbreak Technique and Attacks

(00:13:47) Automated vs Manual Red Teaming

(00:17:15) Qualitative Assessment of Model Jailbreaking (Part 1)

(00:19:38) Sponsors: Oracle | Brave

(00:21:42) Qualitative Assessment of Model Jailbreaking (Part 2)

(00:26:21) Context-Specific Safety Considerations

(00:32:26) Model Capabilities and Safety Correlation (Part 1)

(00:36:22) Sponsors: Omneky | Squad

(00:37:48) Model Capabilities and Safety Correlation (Part 2)

(00:44:42) Model Behavior and Defense Mechanisms

(00:52:47) Challenges in Preventing Jailbreaks

(00:56:24) Safety, Capabilities, and Model Scale

(01:00:56) Model Classification and Preparedness

(01:04:40) Concluding Thoughts on o1 and Future Work

(01:05:54) Outro