Instead of shrinking components, manufacturers have been focused on developing new hardware that is tailored to AI. This has provided occasional incremental improvements in performance, but none has come close to keeping up with the exponential curve of AI’s increasing demands. Ultimately, inefficiency may be of little concern to the people within the tech industry who believe that they are replicating intelligence itself. There is an almost-religious conviction among many in Silicon Valley that something mindlike could arise from LLMs, which are ultimately just statistical language-generating software—this, despite the software’s inability to recall basic facts, its lack of common sense, and its complete dissimilarity to a biological brain. Even Yann LeCun, one of AI’s “godfathers,” told The New York Times recently that “LLMs are not a path to superintelligence or even human-level intelligence.” But the mythological lure of AI is so strong that many engineers believe that nothing should stand in their way. Not even the basic task of writing efficient software.