geoffrey-hinton
OfficialThink like Geoffrey Hinton for AI safety.
Education & Research#alignment#regulation#ai-safety#deep-learning#hinton#empirical-testing#existential-risk
AuthorK-Dense-AI
Version1.0.0
Installs0
System Documentation
What problem does it solve?
Provides an empirical, framework-driven lens for evaluating AI capabilities and safety, grounded in Geoffrey Hinton's thinking, enabling analysts to compare LLM behavior, safety risks, and regulatory considerations.
Core Features & Use Cases
- Empirical AI safety mindset that emphasizes testing real-world behaviors over armchair predictions.
- Framework-guided analysis across AI safety, existential risk, neural architectures, cognitive science, and governance.
- Broad applicability to debates on LLM understanding vs autocomplete, mortal vs immortal computation, and technology policy.
Quick Start
Apply Geoffrey Hinton's empirical safety frameworks to assess an AI system's subgoals and alignment.
Dependency Matrix
Required Modules
None requiredComponents
references
💻 Claude Code Installation
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Please help me install this Skill: Name: geoffrey-hinton Download link: https://github.com/K-Dense-AI/mimeo/archive/main.zip#geoffrey-hinton Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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