  We envision "AI scientists" as systems capable of skeptical learning and
reasoning that empower biomedical research through collaborative agents that
integrate AI models and biomedical tools with experimental platforms. Rather
than taking humans out of the discovery process, biomedical AI agents combine
human creativity and expertise with AI's ability to analyze large datasets,
navigate hypothesis spaces, and execute repetitive tasks. AI agents are poised
to be proficient in various tasks, planning discovery workflows and performing
self-assessment to identify and mitigate gaps in their knowledge. These agents
use large language models and generative models to feature structured memory
for continual learning and use machine learning tools to incorporate scientific
knowledge, biological principles, and theories. AI agents can impact areas
ranging from virtual cell simulation, programmable control of phenotypes, and
the design of cellular circuits to developing new therapies.
