How AI points the way to a new gold standard for big data analytics

If data is the new gold, then today’s “gold” comes in the form of priceless insights into trends and customer behaviors for growth-seeking organizations. But possessing an abundance of data — though fortunate — remains problematic, at least for now.

Why?

Most organizations have a tremendous amount of data available at their fingertips, yet don’t have the infrastructure or equipment to process all of it. 2.5 quintillion bytes of data are currently being generated daily, and it’s accelerating alongside the proliferation of IoT technologies on one end, and centralized cloud services catering to billions of daily users on the other end. today’s standard computer chips — central processing units (CPUs) — have reached a performance ceiling where the cost of computing outweighs the benefits.

As illustrated by the famous gold rush of the 19th century, there is a natural tendency to follow familiar paths, even at the cost of climbing a steep slope and achieving less-than-ideal results. Many gold miners may have fared far better by creating new paths. Similarly, forging a new path toward data analysis is essential in finding the ideal path to the “new” gold.

Make no mistake – data has already led to countless breakthroughs and provided incredible benefits. But if we are to truly squeeze all of the value out of this new gold, now is the time to move beyond CPUs and explore next-gen alternatives that unlock a whole universe of insights at unprecedented speeds.

To truly understand where and how big data processing is falling short, a look at the evolution of artificial intelligence (AI) can be extremely enlightening.

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