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131.6
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Knut Jägersberg
KnutJaegersberg
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jagersbergknut
AI & ML interests
NLP, opinion mining, narrative intelligence
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Evolution and The Knightian Blindspot of Machine Learning The paper discusses machine learning's limitations in addressing Knightian Uncertainty (KU), highlighting the fragility of models like reinforcement learning (RL) in unpredictable, open-world environments. KU refers to uncertainty that can't be quantified or predicted, a challenge that RL fails to handle due to its reliance on fixed data distributions and limited formalisms. ### Key Approaches: 1. **Artificial Life (ALife):** Simulating diverse, evolving systems to generate adaptability, mimicking biological evolution's robustness to unpredictable environments. 2. **Open-Endedness:** Creating AI systems capable of continuous innovation and adaptation, drawing inspiration from human creativity and scientific discovery. 3. **Revising RL Formalisms:** Modifying reinforcement learning (RL) models to handle dynamic, open-world environments by integrating more flexible assumptions and evolutionary strategies. These approaches aim to address ML’s limitations in real-world uncertainty and move toward more adaptive, general intelligence. https://arxiv.org/abs/2501.13075
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DeepSeek R1 on how to build conscious AGI
4 days ago
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So, what is general intelligence?
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**Intelligence Potentiation: An Evolutionary Perspective on AI Agent Designs**
Dec 19, 2024
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Practical Consciousness Theory for AI System Design
Dec 5, 2024
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Perspectives for first principles prompt engineering
Aug 18, 2024
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Towards actively reasoning LLM systems
Mar 10, 2024
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