Qwen2.5-1M
Collection
The long-context version of Qwen2.5, supporting 1M-token context lengths
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2 items
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NIONGOLO Chrys Fé-Marty PRO
Svngoku
AI & ML interests
African Culture, LLM, Fine-tuning & Quantization and i love experimenting RAGs & building synthetic datas
Recent Activity
liked
a dataset
about 8 hours ago
MaziyarPanahi/synthetic-medical-conversations-deepseek-v3-chat
new activity
about 11 hours ago
OpenLLM-France/Lucie-7B-Instruct-gguf:Misunderstandings of press about this model
reacted
to
KnutJaegersberg's
post
with 👀
about 13 hours ago
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
Organizations
Svngoku's activity
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3 days ago
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6 days ago
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11 days ago
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12 days ago
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14 days ago
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17 days ago
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17 days ago
Article
Use Models from the Hugging Face Hub in LM Studio
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20 days ago
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papers
23 days ago
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26 days ago
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about 1 month ago
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**Intelligence Potentiation: An Evolutionary Perspective on AI Agent Designs**
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2 months ago
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2 months ago
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2 months ago
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3 months ago