Without Virtualization technology, the evolution of generative AI and AI agents wouldn’t have been possible. That’s because Virtualization is the foundation on which cloud computing is built, and cloud, in turn, powers the widespread rise of generative AI. As generative AI dominates today’s landscape, the next evolution already emerging is AI agents.
If you are hearing the term virtualization for the first time, let me make it clear to you in the simplest possible way. Virtualization means creating virtual versions of computers so that one physical machine can run many separate systems at the same time, each acting like its own computer. The software that implements virtualization are called hypervisors. If you want to experience it, try VirtualBox on your personal computer.
Brief history of Virtualization
It all started in the late 1960s. That’s when IBM began a project named CP/CMS. It was an operating system that could run multiple virtual machines in a single computer. This was when in desktop virtualization was born. IBM researchers introduced the Hypervisor concept by partitioning physical resources.
IBM discontinued it as they couldn’t convert it into a long-term commercial platform. Many experiments were conducted, and several organizations failed. In 1999, VMware emerged as the first company to successfully commercialize hypervisors. Till now, it stands as the largest player in the virtualization market.
The current market
With almost half the market share, VMware powers both public and private cloud. VMware Player and VMware Fusion are free software that you can use for desktop virtualization. Its ESXi is the most commonly used bare metal hypervisor.
Along with VMware, Microsoft and Citrix are the ones holding the top positions. IBM is stepping in with its PowerVM project maintaining the legacy.
Where are we heading
Modern AI/ML training and inference workloads are computationally heavy. They require GPUs (Graphics Processing Units), which are optimized for parallel processing—ideal for deep learning models like CNNs, RNNs, and Transformers.
As cloud and AI evolve, virtualization remains essential—bridging traditional systems with modern innovation and shaping the future of digital transformation. I believe the one who develops the most effective way to virtualize GPUs will own the future.