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What will be the biggest challenge in implementing OpenAI's Rule-Based Rewards by the end of 2024?
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Resolution / Starting Odds
Technical complexity • 25%
Regulatory hurdles • 25%
Adoption by developers • 25%
Public perception and trust • 25%
Reports and publications from OpenAI or credible news sources
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OpenAI Introduces Rule-Based Rewards to Enhance AI Safety
Jul 24, 2024, 04:31 PM
OpenAI has introduced Rule-Based Rewards (RBRs) as a key component of its safety stack to align AI model behavior with desired safe behavior without extensive human data collection. This new method leverages RBRs to provide reinforcement learning signals based on a set of safety rubrics, making it easier to adapt to changing safety policies. The RBRs enable AI models to rank their own safety, thereby automating safety scoring and allowing developers to create clear-cut safety instructions for AI model fine-tuning. This approach aims to make AI systems safer and more reliable for everyday use.
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Achieves a breakthrough in natural language processing • 25%
Reaches a new level of general AI • 25%
Other • 25%
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Federal regulations • 25%
Other state or local regulations • 25%
Level 2: Reasoners • 25%
Level 3: Agents • 25%
Level 4: Innovators • 25%
Level 5: Organizations • 25%
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Partnerships with other organizations • 25%
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Robustness • 25%
Transparency • 25%
Privacy • 25%
Data Security • 25%
Algorithmic Bias • 25%
Transparency • 25%
Other • 25%
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GPT-4 • 25%
Claude 2.0 • 25%
Other • 25%
Increased security measures • 25%
Revised participant agreements • 25%
Limited access to sensitive models • 25%
No changes announced • 25%