Here’s some background on this critical area of AI.
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Machine learning is one of those buzz words that gets thrown around as a synonym for AI (Artificial Intelligence). But this really is not accurate. Note that machine learning is a subset of AI.
This field has also been around for quite some time, with the roots going back to the late 1950s. It was during this period that IBM’s Arthur L. Samuel created the first machine learning application, which played chess.
So how was this different from any other program? Well, according to Venkat Venkataramani, who is the co-founder and CEO of Rockset, machine learning is “the craft of having computers make decisions without providing explicit instructions, thereby allowing the computers to pattern match complex situations and predict what will happen.”
To pull this off, there needs to be large amounts of quality data as well as sophisticated algorithms and high-powered computers. Consider that when Samuel built his program such factors were severely limited. So it was not until the 1990s that machine learning became commercially viable.
“Current trends in machine learning are mainly driven by the structured data collected by enterprises over decades of transactions in various ERP systems,” said Kalyan Kumar B, who is the Corporate Vice President and Global CTO of HCL Technologies . “In addition, the plethora of unstructured data generated by social media is also a contributing factor to new trends.
