What does artificial intelligence mean for your data centre?
Artificial Intelligence has finally arrived. After years of stagnation and research, the discipline is now experiencing a true...
Artificial intelligence (AI) and machine learning (ML) technologies are advancing to the point where they can generate exceptional value for enterprises. However, such rapid evolution means infrastructures must shift – or even be restructured – to accommodate the high-performance systems that AI and ML require.
AI adoption is key for organisations working with the most demanding applications of IT, but it’s not just high-end scientific researchers who need guidance. With AI and ML entering the mainstream, new technologies are already affecting a multitude of industries. Lenovo is currently supporting customers explore AI solutions in sectors as diverse as agriculture, particle science and healthcare. Whether it’s boosting the quality of oncology diagnoses and radiology practices, or taking proactive steps to improve drought management and optimise the location of wind turbines, AI is reinforcing all these solutions.
Such a rapid uptake of AI/ML will lead to the next phase of software-defined data centre (SDDC) control – that is, ‘thinking’ and ‘learning’ data centre systems that harness the power of AI, ML and even deep-learning techniques, that all make good use of Lenovo-supported GPUs (graphics processing units) in order to forward-manage resource allocation, orchestrate future-defined workloads and automate policy application, for example.
Organisations still need to conduct their business without being hampered by constantly changing technologies that cramp their applications. That’s why customers must take advantage of expert guidance from leading technology partners who now invest in the AI/ML space. Whether it’s using vision recognition to automate warehouse packing processes, or helping businesses boost productivity through augmented intelligence capabilities, companies like Lenovo are accelerating their AI initiatives to generate new and actionable insights in the business and science sectors.
According to InfoSys, organisations that have deployed – or plan to deploy – AI technologies anticipate a revenue increase of 39 per cent by 2020 by doing so. That figure shows just how integral AI adoption will be over the new few years. And in order to exploit AI and ML to the fullest extent, enterprises must utilise the proven expertise of technology market leaders.
While applying AI to existing IT environments may realise some benefits, it is key to recognise that AI delivers the utmost when operated across AI-optimised hardware and software. This may require firms to restructure – or even rebuild from the ground up – their technology estates, but with IT departments now the leading adopters of AI (69 per cent), such an overhaul will come to be acknowledged as standard practice.
Technology leaders like Lenovo can help customers implement these restructures, and be there even earlier at the planning and adoption stage. Its Executive Briefing Centers in Stuttgart, for example, are collaboration hubs that provide an interactive environment for customers – here, people can share their business challenges and even go behind the scenes to explore new technologies. Lenovo also provides expertise on the ground floor, with customer-centric, AI-ready hardware and software. And customers can take advantage of a support team of more than 100 AI developers and data scientists, all working to engineer AI-enabled data solutions.
One such solution is Lenovo’s latest ThinkSystem SD530 Server. The ultra-dense and economical two-socket server provides the ideal 2U four-node (2UFN) platform/chassis for compute-intense enterprise and cloud workloads. ThinkSystem SD530 is a single platform designed to excel not only at AI and high-performance computing (HPC), but also at critical enterprise workload environments, such as virtualisation and hyperconverged infrastructure. The ThinkSystemSD530 can be equipped with both CPUs and GPUs, depending on the AI/ML algorithms required, and be part of a solution that can be scaled up to grow with demand.
There’s no question that IT infrastructures must stay up-to-date with advanced – and still-advancing – AI and ML technologies. But for this to occur, enterprises need to rethink their current IT infrastructures and install hardware and software that are design-optimised for the deep-learning tools and applications that are coming along.
IT managers and C-suite execs can no longer afford to let the AI revolution pass them by, especially as AI and ML are becoming critical aids in automating management of HPC-enabled, hyper-converged data centres. Lenovo is one such leading player that is poised to exploit all that AI has to offer.