EXPERT OPINION ecosystem much easier to integrate and deploy at the edge .
Touch it twice ? Automate it
More than 59 zettabytes ( ZB ) of data will be created , captured , copied and consumed in the world this year , according to IDC . For IT teams to keep afloat amid this explosion of data and the complexity of diverse workloads , automation is essential for success .
On one hand , automation is a way of relieving the pressure from IT staff and freeing their time to more important projects . However , automation is also key in helping AI take on more functions in the data centre by removing tasks that rely on close human interaction . Automation is what will help data centres make the journey to AI and move from being reactive to preventative , and ultimately , predictive .
Increasing efficiency with AI chips
Using general-purpose chips for largescale AI processes can be outrageously expensive . As AI demands such enormous computational power , many businesses opt for specialised AI chips , which are designed to perform complex mathematical and computational tasks in a more efficient way . With most AI use cases today being very narrow , AI chips can be configured for a specific task such as pattern recognition , natural language processing , network security , robotics and / or automation .
As AI continues to mature , capabilities will not only expand , but the cost of implementation will also decrease . This trend will advance even further with the RISC-V initiative and other open-source technologies , lowering the barriers to purpose-built ‘ building blocks ’ that can focus on efficiency , performance and scalability like never before .
ORGANISATIONS MUST BUILD UNIFIED INFRASTRUCTURE THAT IS DEVOTED TO AI PROJECTS .
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