Part 9/12:
Model Reliability and Hallucinations: LLMs can generate plausible but false information. Incorporating verifiable sources and grounding models against trusted repositories (e.g., internal codebases, Stack Overflow) mitigates this.
Platform Maturity and API Management: Creating adaptive, scalable platforms requires significant effort—starting small, iterating in agile sprints, and gradually expanding scope.
Enterprise Readiness: Complying with standards like encryption, auditability, and certification involves aligning AI deployment with organizational security policies and regulatory requirements.
Google exemplifies addressing these challenges by open-sourcing models like Gemini and deploying robust security and compliance measures, ensuring enterprise-grade reliability.