Most Artificial Intelligence (AI) applications are about having the right data at the right time, but also about being able to process them in intelligent ways. The global leaders on AI are already collecting, aggregating, processing and managing very large volume of data. In the future, a proliferating number of enterprises will have to manage very large datasets, as a means of empowering their AI-based processes. This has already a significant impact on the databases of these organizations, which must be more scalable and more intelligent than ever before. However, the relationship between AI systems and modern databases is a two-way one. On the one hand, the quality of the data management infrastructure of an enterprise is a decisive factor for its ability to adopt and fully leverage AI.

Though it's still several years away from widespread deployment, 5G is a key component in the evolution of cloud-computing ecosystems toward more distributed environments. Between now and 2025, the networking industry will invest about $1 trillion worldwide on 5G, supporting rapid global adoption of mobile, edge, and embedded devices in practically every sphere of our lives. It will be a proving ground for next-generation artificial intelligence (AI), offering an environment within which data-driven algorithms will guide every cloud-centric process, device, and experience. Just as significant, AI will be a key component in ensuring that 5G networks are optimized from end to end, 24 7. AI will live at every edge in the hybrid clouds, multiclouds, and mesh networks of the future. Already, we see prominent AI platform vendors--such as NVIDIA--making significant investments in 5G-based services for mobility, Internet of Things (IoT) and other edge environments.