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AI Research
arXiv CS.AI·Jun 29·5 min read
Odyssey: Constructing Verifiable Local Truth-Preserving Foundation Models
TL;DR
Foundation models in AI often struggle with verifiability and truth preservation, leading to trust issues. Odyssey is a framework designed to construct verifiable local truth-preserving foundation models that ensure reliable outputs.
✦ Why It Matters
Engineers can leverage Odyssey to build AI models that ensure output verifiability and enhance user trust.
Key Takeaways
- Investigate the use of foundries for modular AI model construction.
- Utilize Universal Foundry Learning for structured model integration.
- Implement Foundry SQL for effective artifact management.
- Adopt TICKET certification for external model compatibility.
How It Works
ODYSSEY employs a categorical framework where foundries serve as modular components that encapsulate local contexts and knowledge types. By using Kan extensions, it integrates local artifacts into a cohesive model while ensuring that necessary conditions for reasoning and argumentation are met.
This structured approach allows for the preservation of local truths and supports complex reasoning tasks.