The most expensive word in inference is "now"

The text explores the concept of asynchronous inference in computing, highlighting how it alters the economic and operational dynamics compared to synchronous systems. It discusses the notion that urgency in processing tasks, often driven by human wait times, incurs higher costs and resource inefficiencies. By decoupling tasks from immediate human oversight, systems can leverage batch processing and smart scheduling to optimize resource utilization and reduce costs. The piece emphasizes the importance of categorizing tasks based on their urgency and suggests that many operations traditionally considered real-time can be shifted to more cost-effective asynchronous processing. It also touches on the historical precedence of this approach in infrastructure, drawing parallels to practices like batch processing in databases and job queues. The author suggests that advancements in scheduling and routing will further enhance these efficiencies, ultimately shifting the competitive advantage from hardware to orchestration and task management.

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