Frontier AI compute usually combines large clusters of current-generation accelerators with fast networking, storage and optimized software. The word frontier is relative because the performance threshold rises as hardware and model techniques improve.
Usable frontier capacity depends on more than the nominal number of chips. Hardware age, power efficiency, cluster reliability and the ability to keep accelerators supplied with data all affect the effective compute available to a laboratory.
ELI5
Frontier AI compute is the high-end computing capacity used for the most capable AI models available at a particular time. It combines current accelerators with fast networking, storage, power and optimized software.
For example, owning thousands of advanced chips does not guarantee full frontier capacity if power limits or network bottlenecks leave many idle. The frontier also moves as new hardware and techniques make yesterday's leading cluster less competitive.
