Can we properly compare artificial intelligence and Big Data?
A survey of Big Data and artificial intelligence carried out by NewVantage Partners’ revealed that 97.2% of executives said their companies were investing, building, or launching Big Data and AI initiatives.
According to Alan Morrison, senior researcher at PriceWaterhouse Coopers, “many people do not really know what Big Data is or Big Data analysis.” They talk about AI and Big Data together because artificial intelligence needs very distinct data to build intelligence and make it automatic.
Although they are two different concepts, they accomplish the same task. But can you define them?
Artificial Intelligence versus Big Data: Some differences.
The major difference is that Big Data is raw data that needs to be cleaned, structured and integrated before it becomes useful, while artificial intelligence is the output, the intelligence that results the processed data. This makes the two intrinsically different.
Artificial intelligence is a form of calculation who allows machines to perform cognitive functions, such as acting or reacting in the same way as humans. Traditional IT applications also respond to data, but they have to be hand-coded. AI systems change their behavior to better adapt to changes. It acts on the decision-making and performs tasks of a human being, but faster and with fewer mistakes.
When it comes to Big Data, it’s more archaic. It does not act directly on the results, but it simply looks for them. It defines very large data sets, but also extremely variable data.
One thing is certain in all the existing confusion is that there is no artificial intelligence without Big Data.