The “cloud” as a metaphor applied to computing dates back to the mid 1990’s when companies like Compaq Computer Corporation launched “cloud computing-enabled applications” and the viability of online consumer file storage. It gained prominence as a acceptable means of offloading IT application and storage management as vendors like Amazon, Google and Microsoft launched their respective services between 2000 and 2010. NASA even launched the first open-source software for deploying private and hybrid clouds in 2008 and the world of computing was forever changed.
As security, privacy and cost no longer became issues for enterprises, more of an organization’s IT dependences began to be offloaded to public as well as hybrid cloud solutions for primarily cost-effective scales of compute power and storage. As generative AI (GenAI) becomes more mainstream, the inevitable marriage of cloud and AI is spawning the concept of an intelligent cloud
Put most simply, an intelligent cloud is a cloud computing model/platform that leverages to power of AI to enhance its capabilities. What was once a platform for pure application processing power and storage can now leverage new GenAI technologies to extend functionality into the realm of contextualized data ingestion, advanced omni-channel analytics and proactive/predictive engines to forecast future states based on variables correlated from both within as well as outside the enterprise.
While the promise of AI is still in its infancy, the value realized for specific use cases such as enhancing cloud operations are generating measurable results. But the true value of an intelligent cloud can only be realized by establishing a technology stack that not only creates new content but learns as it processes. This is where the marriage of GenAI with Reinforcement Learning steps in to deliver on the promise of an intelligent cloud.
The biggest fear in using AI today is not the Hollywood premonitions of Hal 9000, Skynet or even Agent Smith. It is the challenges that manifest for:
The ignition spark for an intelligent cloud initiative can range from enterprise-wide digital transformation project to a more targeted mainframe modernization initiative forced by the end-of-support announcement of a beloved application. In any case the difference between success and failure will be dependent upon the process you undertake.
To that end, we would offer these 5 steps to deliver on the promise of an intelligent cloud:
One final recommendation would be to select experienced partners who understand the nuances of an intelligent cloud adapted you your specific requirements with an eye to future enhancements that don’t require proprietary tools or resources.
At the core of UBIX is a highly scalable and flexible cloud architecture that leverages the best-in-class cloud technologies to support modern data workloads, including analytics, AI, and ML. This architecture is designed to adapt to the varying demands of clients, allowing them to scale up or down based on their specific requirements.
UBIX transforms the way cloud environments are managed, ensuring that each step of the process—whether provisioning, scaling, securing, or customizing—works seamlessly to drive business outcomes. The platform’s holistic design positions it as a future-proof solution that adapts to the evolving needs of its clients and maximizes the potential of cloud-based data operations powered by GenAI and Reinforcement Learning.
Learning how GenAI and emerging advancements like Reinforcement Learning can deliver on the promise of an intelligent cloud has never been easier. Download our free eBook titled “5 Steps to AI Business Transformation Success” to help better understand the nuances of emerging AI concepts and technologies and offer a set of best practices for consideration to ensure digital transformation and business-led AI success. Or if you can spare 22 minutes for a mini–AI Readiness Workshop, you can contact one of our AI experts today.