Healthcare, life sciences and consumer health are undergoing a quiet revolution in generative AI. Early applications are showing promise on everything from speeding up preclinical drug discovery and development by better predicting molecular behavior to augmenting how physicians and providers provide care to their patients.
Given the potential harms and regulatory risks intrinsic to applying AI in healthcare, having robust LLM evaluation and LLM observability is critical.
How can teams deploy generative AI reliably and responsibly – and what should they look for when assessing partners?
Dive into details on essentials like:
- Healthcare Use Cases for LLMs
- LLM System Evaluations
- LLM Traces and Spans
- Prompt Engineering
- Retrieval Augmented Generation
- Fine-Tuning
- Embeddings Analysis
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