Benjamin Lee on why AI needs better infrastructure, not just bigger models

Benjamin Lee, a professor of Electrical and Systems Engineering at the University of Pennsylvania, emphasizes that the rapid growth of AI requires smarter infrastructure and energy-aware design rather than just bigger models. Lee’s expertise spans hardware design, infrastructure strategy, and energy policy, and he highlights the unsustainable pace at which data centers are expanding—often outstripping the availability of clean energy. He stresses that energy consumption must be treated as a core design metric in AI development, not an afterthought, to ensure long-term sustainability. Lee traces his career motivation back to an undergraduate course on computer organization that revealed the complexities of hardware-software interaction, leading him to focus on energy efficiency in computing. He points out a common misconception among engineers and policymakers: the belief that current AI applications like chatbots justify massive infrastructure investments. Instead, he argues that tech companies are building energy and data center infrastructure with future, yet-to-be-imagined AI capabilities in mind. While there was initial optimism about powering data centers with renewables