The discipline of data science has come into its own since the appearance of big data more than a decade ago. Just as the universe is growing, so too does big data keep getting even bigger. In parallel, the importance of the data scientist has risen within organizations. Jens Graupmann, SVP of product and innovation at Exasol, expects investments in artificial intelligence (AI) to soar from $122 billion in 2022 to more than $300 billion in 2026. What's more, Infosys estimates that companies can generate over $460 billion in incremental profit if they are able to optimize AI and data science practices.

Welcome to Azure Hybrid, Multicloud, and Edge Day--please join us for the digital event. Today, we're sharing how Azure Arc extends Azure platform capabilities to datacenters, edge, and multicloud environments through an impactful, 90-minute lineup of keynotes, breakouts, and technical sessions available live and on-demand. Now you can build, train, and deploy your machine learning models right where the data lives, such as your new or existing hardware and IoT devices. When I talk with customers, one of the things I hear most frequently is how new cloud-based applications drive business forward. And as these new applications are built, they need to take full advantage of the agility, efficiency, and speed of cloud innovation. However, not all applications and infrastructure they run on can physically reside in the cloud.

The financial services industry is a dynamic space that is constantly testing and pushing novel use cases of information technology. Many of its members must balance immense demands--from the pressures to unlock continuous innovation in a landscape with cloud-native entrants, to responding to unexpected surges in demand and extend services to new regions--all while managing risk and combatting financial crime. At the same time, financial regulations are also constantly evolving. In the face of the current pandemic, we have seen our customers accelerate in their adoption of new technologies, including public cloud services, to keep up with evolving regulations and industry demands. Hand in hand with growing cloud adoption, we've also seen growing regulatory concerns over concentration risk (check out our recent whitepaper on this), which have resulted in new recommendations for customers to increase their overall operational resiliency, address vendor lock-in risks and require effective exit plans.

Amid the imperative of digital transformation and the enterprise adoption of multicloud, network agility and flexibility are prized. The right network-automation tools can help, contributing to agile operations while enabling the portability of applications and data between on-premises datacenters and clouds. With the rise of cloud operating models and multicloud environments, there's no question that network professionals are compelled to forgo manual processes, inherently inefficient and error prone, in deference to automated processes that are more efficient and verifiable. IDC foresees network-automation tools evolving in lockstep with cloud-driven requirements to enable efficient and relevant connectivity of network service/functions within multicloud environments. Given the nature of multicloud, automation tools should work across a range of cloud services from different cloud service providers.

The cloud wars are rapidly separating public cloud leaders from the rest of the pack. Where does IBM Corp. stand now in the cloud market? Considering how far behind its public cloud is against Amazon Web Services Inc. and Microsoft Corp. in market share, the technology giant has wisely chosen to step up its focus on hybrid and multicloud management as its next best hope for deep differentiation. At this stage in the development of the cloud economy, it's not clear whether enterprises will adopt multicloud as a long-term architectural end-state, or simply as a way station on the road to reliance on strategic public cloud providers. Nevertheless, the multicloud option is becoming more prominent in enterprise information technology strategies, as we've seen recently in moves by VMware Inc., Cisco Systems Inc. and others in this arena.

Its impact on customer experiences, business processes and models, and workforce innovations was undeniable. We saw more and more use cases where customers started leveraging multiple clouds to enable innovation than ever before. But the landscape continues to change. Here are my thoughts about what's ahead for cloud in 2019. The Kubernetes ecosystem will grow and enable more innovation.

IBM has recently announced that it plans to incorporate the new RAPIDS open source software into its enterprise-grade data science platform for on-premises, hybrid, and multicloud environments. 'IBM has a long collaboration with NVIDIA that has shown demonstrable performance increases leveraging IBM technology, like the IBM POWER9 processor, in combination with NVIDIA GPUs,' said Bob Picciano, senior vice president of IBM Cognitive Systems. 'We look to continue to aggressively push the performance boundaries of AI for our clients as we bring RAPIDS into the IBM portfolio.' RAPIDS will help bring GPU acceleration capabilities to IBM offerings that take advantage of open source machine learning software including Apache Arrow, Pandas and scikit-learn. Immediate, wide ecosystem support for RAPIDS comes from key open-source contributors including Anaconda, BlazingDB, Graphistry, NERSC, PyData, INRIA, and Ursa Labs.