Data science has been recognized as an attractive approach for scientific discovery and has been applied in all kinds of research fields such as computational biology, physics and engineering. These data science applications read large amounts of data, analyze and extract features using data mining methods, and also learn and infer data features and trends using AI techniques. The High Performance Big Data Research Team at RIKEN Center for Computational Science (RIKEN R-CCS) has been researching and developing system software to facilitate such big data processing, machine learning and deep learning for high performance computing (HPC) systems towards convergence of AI/Big Data and HPC. In this talk, Kento Sato introduces several R&D activities for accelerating AI/Big data applications on HPC systems (HPC for AI/Big data) as well as ones for resolving HPC challenges by using these AI/Big data techniques (AI/Big data for HPC).