Pitting artificial intelligence vs. big data is like comparing a pick to a shovel. Although the two complement...
each other in important ways, they are distinctively different in both nature and purpose.
AI refers to a type of intelligence that makes it possible for a machine to perform cognitive functions similar to those attributed to humans. Compare this to a traditional system, which reacts according to how it's been programmed to act; the AI-enabled machine can analyze and interpret data and then problem solve based on those interpretations. It is always learning from the data, evolving as the data evolves and reacting to what it learns. In this way, the AI system is constantly improving and adjusting its behavior to accommodate change.
Big data refers to a much different phenomenon. Not only does it describe large sets of data, but also data that can be extremely varied, moves at a high velocity and has meaning within a defined context, with a goal toward analytics that lead to specific results.
For example, data produced by social networks or the internet of things by itself is not enough to qualify as big data in the strictest sense. The data must also be part of a larger analytics strategy that can lead to process automation, enhanced decision-making or other specific results. The difference is this: The ability of a machine to learn to act like a human is artificial intelligence vs. big data, which is a large volume of data that, when analyzed, produces usable data.
Artificial intelligence vs. big data use cases
That said, AI and big data work well together. The characteristics that define big data -- volume, velocity and variety -- have quickly overwhelmed the capabilities of traditional analytics, which is where AI comes in. AI thrives on data. The greater the amount of data, the more effectively an AI system can analyze, learn and evolve. An AI system can help find significant trends and patterns in big data that might otherwise be misinterpreted or go undiscovered.
At the same time, big data makes it possible for AI to reach its fullest potential. AI has made relatively little progress, in part because of the lack of technologies to handle massive sets of data. But the proliferation of the internet and the influx of unprecedented amounts of information have forced these technologies to evolve more quickly, particularly when it comes to storage.
Today's storage systems, especially solid-state flash arrays, can handle greater capacities and support faster I/O operations than ever. Although AI in itself doesn't warrant these capacity and performance levels, its hunger for large data sets does, creating a symbiotic relationship between AI and big data that is realized in part through today's storage technologies. Consequently, as large data sets have become more available and manageable, AI technologies have also evolved. In fact, big data might turn out to be the greatest single influence on AI's imminent rise. So, although there is a difference between artificial intelligence vs. big data, the two go hand in hand.