Core Viewpoint - The article discusses the ambitious vision of creating Artificial Intelligence Virtual Cells (AIVC) to model and predict cellular behavior, leveraging advancements in AI and omics technologies [3][5][7]. Group 1: AI Virtual Cell Development - Multiple research teams are competing to develop AI models for cellular behavior prediction [4]. - The Chan-Zuckerberg Initiative (CZI) plans to invest hundreds of millions over the next decade to create virtual cells [10]. - The development of AI protein structure prediction tools like AlphaFold is contributing to virtual cell projects [10]. Group 2: Current Progress and Challenges - The efforts to create virtual cells are still in the early stages, generating significant interest in academic and industrial labs [8]. - Despite the excitement, some scientists express skepticism about the hype surrounding virtual cells, noting a lack of concrete results and clear success pathways [11]. - Current virtual cell models primarily focus on single-cell RNA sequencing data, which provides snapshots of gene activity and cellular states [16]. Group 3: Data Utilization and Future Directions - CZI plans to release sequencing data from 1 billion cells, while Arc Institute has released data from 100 million cancer cells treated with various drugs [16]. - Researchers are beginning to develop single-cell AI models, with Arc Institute launching its first virtual cell model called "State" [16]. - There is a need for integrating other data forms, such as optical and electron microscopy images, to enhance virtual cell models [17]. Group 4: Definition and Consensus - The concept of virtual cells lacks a clear definition, and there is no consensus among researchers on what constitutes a virtual cell [18]. - Stephen Quake emphasizes that the transition to using virtual cell models in biology will take time, as both the models and the scientists are not yet fully prepared [19].