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The edge and AI – a partnership in smarter computing

The advent of artificial intelligence (AI) and its continued proliferation has seen technology changing the functionality of computers by making them infinitely smarter and adept to meeting our daily requirements.

George Senzere.

A recent article by Scientific American provides examples where AI can deliver solutions to issues such as the world’s current nickel shortage. Through AI, says the article, four alternative materials were identified that could replace nickel, undoubtedly a significant discovery.

However, for the world to harness the full potential of AI, ensuring its outcomes remain relevant, data and the computation and transmission thereof is crucial. Organisational decision-makers must ensure that data complexity and data silos are mitigated and the right tools or platforms are in place before deploying AI.

Edge computing pushes AI to do more

A fundamental part of fully utilising AI is the space where data processing occurs. Findings from IBM’s Global AI Adoption Index 2021 demonstrated that almost 90% of IT professionals believe data location is critical to the resultant success of AI projects. This is where edge computing’s importance becomes evident. AI requires a robust edge data centre which focuses on keeping data on location for faster processing, higher security and more efficient performance.

Edge computing offers much-needed speed for organisations that can be burdened with large volumes of raw data from AI. Processing is done on-site while the system’s speed allows for timely output of analysis. Latency is reduced significantly, allowing for real-time decision making.

In an industrial or large-scale edge computing setting, the availability of real-time decision-making saves money, effort and mitigates potential unplanned downtime. Accurate data also gives industrial players the ability to predict machine failures and implement predictive maintenance without disrupting the production capabilities – a major plus.

The combined power of AI and edge computing leads to:

• Faster computing and insights.

• Improved data security.

• More efficient control over operations.

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