Machine learning is all about faster processing of massive amounts of data, no? Take the new iPhone camera for example. It has an image signal processor (ISP) enhanced by machine learning that makes editing photos more intelligent.
An intelligent program should read historical data, analyze it for patterns, and be able to classify what it sees. Without a database to learn from and then call upon this information to match with new data, a program cannot really “learn”.
Google G Suite and IBM Watson are both examples of machine learning that depend on analytics. In fact, many see Microsoft’s acquisition of Linkedin as an attempt at the same – acquire massive amounts of data that can feed productivity tools of Microsoft.
While we have been looking at artificial intelligence as a new domain that will override existing set ups. But chances are it is AI will evolve from current ecosystems, not just Google and Microsoft but also Salesforce and any other such system that has access to massive amounts of data.
Because, Artificial Intelligence is all about data.