Japan’s AIST Adds NVIDIA System to Further QC-Classical Computing Research Efforts

The August 2021 issue of the International Research Journal of Engineering and Technology (IRJET), a peer-reviewed research journal, included a paper based on the work of three researchers from India's St. Francis Institute of Technology (SFIT) summarizing their use of artificial intelligence (AI) and machine learning (ML) methods to help alleviate water shortages in India caused by population growth, urbanization, and climate change. Verlekar, Shah, and Kulkarni used a machine learning model to create a proactive scheme for managing local water resources, work that was prompted by a 2019 drought that impacted the Chennai area of India.

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.