MLCommons, an international artificial intelligence (AI) standards body formed in 2018, launched MLPerf Tiny, their first benchmark targeted at the inference capabilities of edge and embedded devices, or what they call "intelligence in everyday devices". The new benchmark is now part of the overall MLPerf benchmark suite, which measures AI training and inference performance on a wide variety of workloads, including natural language processing and image recognition. The benchmark covers four machine learning (ML) tasks focused on camera and microphone sensors as inputs: keyword spotting, visual wake words, tiny image classification, and anomaly detection. Some important use cases include smart home security, virtual assistants, and predictive maintenance.

Late last month, US Department of Defense (DOD) leadership explored the potential to inculcate artificial intelligence (AI) processes into its overall military operations, signaling a fundamental change in how information and data are used to increase the decision space for leaders both in military and civilian domains. Delivered during the third and most recent iteration of the Global Information Dominance Experiment (GIDE 3), which included representatives from all 11 combatant commands, NORTHCOM Commander Gen. Glen D. VanHerck's remarks on AI were aimed at progressing the ability to maintain domain awareness, achieve information dominance, and provide decision superiority in both competition and crisis.