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Updated at: 4/22/2025, 10:30:27 PM

The "Era of Experience" paper discusses the emergence of a new phase in artificial intelligence (AI) characterized by agents that learn primarily from their own experiences rather than relying on human-generated data. It highlights the limitations of current AI systems that depend heavily on large datasets created by humans. The authors emphasize that future AI agents will develop superhuman capabilities by interacting with their environments, allowing for continual learning and adaptation throughout their lifetimes. Key advancements in reinforcement learning (RL) are anticipated, including improved reward functions grounded in real-world observations, enhanced methods for long-term reasoning, and the capacity for agents to autonomously explore and learn new behaviors. The paper predicts that experiential data will surpass human-generated data in scale and quality, leading to novel capabilities in AI that could fundamentally transform various domains. Ultimately, the authors argue that reconciling self-discovery with task generality will be crucial for realizing the full potential of AI in this new era.

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