The AI Infrastructure Gap in Life Sciences
Key takeaway:
Life sciences organizations have enormous datasets but lack the infrastructure required for AI deployment.
Topics:
• heterogeneous research data
• pipeline complexity
• scientific reproducibility
• metadata and lineage tracking
Hallucination Risk in Clinical AI Systems
Hallucinations are not just a model problem—they are a system design problem.
Topics:
• context retrieval
• grounding models in structured data
• query constraints
• validation pipelines
How to Deploy AI in Regulated Environments (Engineering Considerations)
AI deployment in healthcare requires architecture designed for compliance and observability.
Topics:
• controlled data access
• deterministic pipelines
• monitoring and audit logs
• incremental deployment strategies