Global Model
A consolidated AI model trained on aggregated data from multiple sources, as opposed to localized or personalized models.
Centralized models that learn from all available data - often achieving high overall accuracy but potentially under-serving specific subpopulations. Global-model governance involves evaluating per-segment performance, assessing fairness across regions or demographics, and deciding when localized or personalized models (e.g., federated variants) are more appropriate for sensitive applications.
A ride-hailing company deploys a global demand-forecasting model trained on city data worldwide. While it predicts London and New York trends well, it underperforms in emerging markets. The team then implements regional fine-tuning on local data to create hybrid models that blend global knowledge with local behavior patterns.
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What problem does Enzai solve?
Enzai provides enterprise-grade infrastructure to manage AI risk and compliance. It creates a centralized system of record where AI systems, models, datasets, and governance decisions are documented, assessed, and auditable.
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