Qwen/Qwen-Image-Layered
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Nina Larsen
ninalarsen
AI & ML interests
I’m passionate about applying artificial intelligence and machine learning to the gambling industry to enhance player insights, optimize risk management, and improve predictive accuracy. My interests lie in developing data-driven models for odds calculation, fraud detection, and player behavior analysis. I’m particularly excited by how AI can create smarter, more responsible, and personalized gaming experiences.
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vanta-research/scout-8b
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NEW MODEL: https://huggingface.co/vanta-research/scout-8b
VANTA Research is excited to share our new model, Scout-8B! This iteration of Scout is based on the RNJ-1 Instruct architecture from Essential AI, and not only improves but expands on the capabilities from https://huggingface.co/vanta-research/scout-4b
Scout is specifically designed for:
Tactical Intelligence Analysis
- Systematic problem decomposition
- Structured reconnaissance approach
- Data-driven assessment methodology
Operational Planning
- Multi-phase operation planning
- Risk assessment and mitigation
- Resource allocation guidance
Technical Assessment
- Architecture evaluation and analysis
- Performance optimization recommendations
- Security perimeter assessment
This model is great for anyone that works in security, IT, DevOps, or anyone looking for a unique, but functional AI collaborator. Check it out!
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