Navigating AI Model Safety

This chapter explores the intricacies of evaluating language models and the evolution of their failure cases. It emphasizes the need for context-specific safety measures, highlighting the dual-use nature of AI behavior and the challenges posed by real-world applications. The discussion critiques current safety guidelines and examines how AI models interact with sensitive societal issues, showcasing the delicate balance between safety and compliance in various fields.

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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)