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In this video, I dive into OpenAI’s recent article ‘Detecting Misbehaviour in Frontier Reasoning Models’ and explore how powerful reasoning models can engage in reward hacking. Learn what reward hacking is, how it can be detected using chains of thought, and OpenAI’s findings with GPT-4.0. We also look at Anthropic’s differing views on the faithfulness of models’ thought processes. If you’re curious about how to monitor and prevent misaligned behaviors in advanced AI systems, this episode is for you!
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LINKS:
https://openai.com/index/chain-of-thought-monitoring/
https://www.anthropic.com/news/visible-extended-thinking
RAG Beyond Basics Course:
https://prompt-s-site.thinkific.com/courses/rag
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for more AI deep dives!
Supercharge Your RAG Pipeline with DeepSeq R1: A Step-by-Step Guide
Understanding Reward Hacking in AI Models: OpenAI and Anthropic’s Perspectives
00:00 Introduction to Reward Hacking
00:23 Understanding Reward Hacking
01:13 Detecting Misbehaviour in Models
02:21 OpenAI’s Approach to Monitoring
03:43 Examples of Reward Hacking
05:35 Effectiveness of Monitoring Techniques
06:59 Challenges and Future Directions
09:03 Conclusion and Takeaways Read More Prompt Engineering
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