According to Greg Brockman (@gdb), inference is emerging as the most valuable software category in artificial intelligence, driven by increasingly sophisticated and economically impactful models (Source: Twitter/@gdb). As AI solutions become more advanced, the demand for compute resources to perform inference—drawing samples from models—will surge, presenting significant business opportunities. Brockman highlights that optimizing inference encompasses tasks like enhancing the model forward pass, leveraging techniques such as speculative decoding and workload-aware load balancing, and managing large-scale infrastructure. These areas offer fertile ground for innovation and operational efficiency, especially for enterprises scaling AI deployments. Companies and professionals with expertise in inference and large-scale system optimization are well-positioned to capitalize on these trends as AI permeates more business sectors.