Intelligent CIO Middle East Issue 47 | Page 33

+ EDITOR’S QUESTION ASSAAD EL SAADI, REGIONAL DIRECTOR – MIDDLE EAST, PURE STORAGE ///////////////// F or Middle East enterprises looking to implement AI or Machine Learning projects, the good news is that the compute bottleneck that used to hold back projects like these has largely been eliminated. In recent years advancements in deep learning, GPUs and Big Data have allowed AI to flourish. As a result, the challenge for many projects is now providing the data fast enough to feed the data analysis pipelines central to AI. Until recently, enterprises were stuck with building their own infrastructure to feed the AI pipeline. With DIY solutions, these enterprises lost months of productivity going through the painful cycle of integrating, testing and continuously maintaining both the hardware and ever-evolving software. Even when all of this is done, users often find that workloads are slow and data ends up in silos. It’s because the system is built with old, legacy components cobbled together in the system. Bringing together data into a single centralised modern data hub – as part of a deep learning architecture – enables far more efficient access to information, increasing the productivity of data scientists and making scaling and operating simpler and more agile for the data architect. Modern all-flash based data platforms are ideal candidates to act as that central data hub. It’s an effective technology capable of underpinning and releasing the full potential of projects operating in environments that demand high performance compute capabilities such as AI and deep learning. This is because modern data storage solutions encompass a parallelism that mimics the human brain and enable multiple queries or jobs to run simultaneously. They also deliver uncompromised performance across all manner of access patterns – small to large files, random to sequential and low to high concurrency – all with the ability to easily scale linearly and non-disruptively, as the business demands. By building this “ type of flash technology into the very foundation of AI projects, it vastly improves the rate at which AI and ML initiatives can develop. THE CHALLENGE FOR MANY PROJECTS IS NOW PROVIDING THE DATA FAST ENOUGH TO FEED THE DATA ANALYSIS PIPELINES CENTRAL TO AI. To cite just one example, Man AHL, a pioneer in the field of systematic quantitative investing, leverages Apache Spark on top of flash storage to create and execute computer models that make investment decisions. Roughly 50 quantitative researchers and more than 60 technologists collaborate to formulate, develop and drive new investment models and strategies that can be executed autonomously. The firm adopted flash storage to deliver the massive storage throughput and scalability required to meet its most demanding simulation applications. Whether AI is central to your company’s core competency or not, it is a tool all organisations should be looking at using to bring efficiency and accuracy to their data-heavy projects. Those who don’t could be leaving their business at a severe competitive disadvantage. n INTELLIGENTCIO 33