In 2016, Klaus Schwab, the Founder and Executive Chairman of the World Economic Forum, described how the world stood on the brink of a technological revolution that would fundamentally alter the way in which we live, work, and relate to one another. Just as history has shown, each revolution has had a massive impact on society and the Fourth Revolution, characterized by tech innovation at great speed across physical, digital, and cyber spheres, will undoubtedly create a seismic shift in how we do business.
We currently sit on an avalanche of data at global scale where the ability to access, mine and apply insights in a structured way to drive both innovation and novel approaches has become business critical, all against the backdrop of cost cutting. With new tech like artificial intelligence and machine learning, more data is being required to train AI models to deliver extremely intelligent algorithms which support core business processes today, from operations to customer experience.
As organizations evaluate their tech stacks, questions over the cloud are brewing.
The cloud offers scalability, flexibility, and speed that traditional on-premises deployments can lack. Organizations can scale their IT systems to increase or decrease performance, workloads, and costs in line with changing computing, processing, and application needs. This on-demand nature of cloud computing can be a perfect solution for some organizations.
But is it enough?
While cloud computing has democratized the way in which organizations can mine data, in particular by giving those organizations without on-premise access the level of compute power needed, the question that remains is whether the cloud has actually been designed to cope with this explosive level of data?
High performance applications and workloads continue to increase, and most organizations now find themselves in need of powerful compute capabilities – specifically high-performance computing resources to succeed. Data-intensive organizations face an even greater challenge in the current volatile economic market where their portfolio of workloads must accomplish more for less, at speed and performance.
This is where HPCaaS (High-Performance Computing as a Service) comes into play, delivering both the capacity needed for large compute and the privacy and security to manage confidential company data and intelligence in a safe way without the need for public cloud environments. HPCaaS provides a smart solution that incorporates the scale and flexibility of the cloud with safety and security top of mind, increasing resilience, reducing costs, and boosting output in a more sustainable and efficient way. Workloads can no longer be pigeonholed into the cloud – organizations need to find the right time to transition from the public cloud to hybrid environments to continue to scale operations and process data at lightning speed.
Time still waits for no one.
Organizations must carefully consider the smartest, most effective infrastructure strategy for their business, and when the time is right to re-evaluate the current structure. While there are many questions to be addressed, time to market is crucial and can be the difference between success and failure.
Tech innovations like ChatGPT have posed interesting questions and have shown the immense need for business to keep pace today. HPC’s ability to drive innovation, create faster time to market, and shorten the lifecycle window is fundamental to the success of business and industry as a whole.
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We are only just touching the tip of the iceberg where organizations will need to scale, and in some cases overhaul, their data strategy as innovation continues at breakneck speed, competition continues to heat up, and the cost of doing business increases. While the cloud is an effective solution for many short, occasional, and differing workloads requests, training large language models like ChatGPT, or running data intense simulations such as weather forecasting can take weeks or even months in the public cloud, with huge and often unmanageable associated costs.