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Wednesday, March 06, 2019

What You Need To Know About Machine Learning | Entrepreneurs - Forbes

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, as Forbes reports. 

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Photo: Getty
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.”...

But machine learning – supercharged by deep learning neural networks -- is also making strides in the enterprise. Here are just a few examples:
  • Mist has built a virtual assistant, called Marvis, that is based on machine learning algorithms that mine insights from Wireless LANs. A network administrator can just ask it questions like “How are the wi-fi access points in the Baker-Berry Library performing?” and Marvis will provide answers based on the data. More importantly, the system gets smarter and smarter over time.
  • Barracuda Networks is a top player in the cybersecurity market and machine learning is a critical part of the company’s technology. “We've found that this technology is exponentially better at stopping personalized social engineering attacks,” said Asaf Cidon, who is the VP of Email Security for Barracuda Networks. “The biggest advantage of this technology is that it effectively allows us to create a ‘custom’ rule set that is unique to each customer's environment. In other words, we can use the historical communication patterns of each organization to create a statistical model of what a normal email looks like in that organization. For example, if the CFO of the company always sends emails from certain email addresses, at certain times of the day, and logs in using certain IPs and communicates with certain people, the machine learning will absorb this data. We can also learn and identify all of the links that would be ‘typical’ to appear in an organization's email system. We then use that knowledge and apply different machine learning classifiers that compare employee behavior with what a normal email would be like in the organization.”
Of course, machine learning has drawbacks – and the technology is far from achieving true AI.

Source: Forbes