Everything on LLM Limitations

LLMs excel at general knowledge retrieval but fail at precise molecular design tasks, such as generating ligands with specific atom counts and binding constraints.

Impact: Relying solely on LLMs for design risks errors; hybrid workflows requiring expert validation are essential to maintain quality and reliability in molecular engineering.

— from AI in Materials Science: Discovery, Data Gaps, and Active Learning · Latent Space: The AI Engineer Podcast· Mar 24, 2026