The field of biomedical research is moving towards increased adoption of general-purpose artificial intelligence (GPAI) to accelerate scientific discovery. However, the practical limits of GPAI in biomedicine remain unclear, with potential speed increases ranging from 2x to 100x, depending on the task. Despite the potential benefits, achieving these gains may be limited by factors such as irreducible biological constraints, research infrastructure, data access, and the need for human oversight. Moreover, the assimilation of new tools by the scientific community is a critical bottleneck that must be addressed through targeted investment in shared automation infrastructure and systemic reforms to research and publication practices. Noteworthy papers in this area include: Making AI Inevitable: Historical Perspective and the Problems of Predicting Long-Term Technological Change, which highlights the subjective and philosophical disagreements over the future of AI. Deep Hype in Artificial General Intelligence: Uncertainty, Sociotechnical Fictions and the Governance of AI Futures, which conceptualizes AGI as sustained by deep hype and highlights the critical implications for the governance of technological futures.