about beneficial innovation in human technology.
Currently, numerous efforts in various specialized domains aim to overcome this challenge [437; 438;
439]. Experts from the computer field make full use of the agent’s powerful code comprehension
and debugging abilities [398; 397]. In the fields of chemistry and materials, researchers equip agents
with a large number of general or task-specific tools to better understand domain knowledge. Agents
evolve into comprehensive scientific assistants, proficient in online research and document analysis to
fill data gaps. They also employ robotic APIs for real-world interactions, enabling tasks like material
synthesis and mechanism discovery [110; 354; 399].
The potential of LLM-based agents in scientific innovation is evident, yet we do not expect their
exploratory abilities to be utilized in applications that could threaten or harm humans. Boiko et
al. [110] study the hidden dangers of agents in synthesizing illegal drugs and chemical weapons,
TheRiseandPotentialofLargeLanguageModel BasedAgents