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With the proliferation of applications, organisations need underlying databases that allow for scalability, speed, and security. Developer productivity is tied to...

More and more articles, blogs and videos mention natural language processing (NLP) as a tool to get information from vast amount of text. What they rarely mention is that NLP can also be used to increase diversity and reduce the bias of text analysis.

AI continues to garner interest across industries, demonstrating clear benefits to cost savings, decision-making speed, and customer insights. However, fully realising benefits in a measurable way can prove difficult. Unsurprisingly, a return on investment (ROI) is top of mind for organisations and is vital to securing budget for further AI initiatives.

A successful, cost-effective AI journey is built on high performance hardware. Analysing vast amounts of data quickly and accurately, a key mechanism in AI, relies on specialist technology with capable compute features. Including highly threaded workloads that demand numerous cores, high bandwidth memory, and AI-specific instruction sets – all while keeping a lid on power demands.

Understanding the data your business your collects is crucial to its success. Acting on insights and transforming historical interactions into predictive analysis are key to successful business models.AI – a popular buzzword among industry professionals and employees, still has a long way to go before it is in widespread use and organisations are maximising the value of their data.

Across industries, organisations are looking to use AI to enhance decision-making, automate processes, and gain crucial insights. However, adoption still has a long way to go, with many only just beginning to embark on their journey to establishing a culture led by advanced data analytics.

AI advancements transform organisations across every industry to make more intelligent business decisions, faster and with greater confidence. However, even intelligent solutions will not succeed if employees are not motivated to use them. Amidst the long-standing problems surrounding talent acquisition and retention, organisations must strive to scale with the talent they have and build a culture driven by advanced data analytics.