Will machine learning advances spur cross-platform data set deployment?

Q:

Will machine learning advances spur cross-platform data set deployment?

A:

What are we talking about when we talk about machine learning and AI in business?

Lots of different people have different opinions – and it really depends on the context of what the business is doing. However, when you talk about artificial intelligence capabilities overall, it's possible to clear up some of the confusion and ambiguity about how businesses tend to use these brand-new technologies.


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In an article on Venture Beat called “Don’t Believe the Hype About AI in Business,” writer Vivek Wadhwa offers a rather strong indictment of the idea that modern AI systems are easy to incorporate into business processes.

“Most business problems can't be turned into a game,” Wadhwa writes. “You have more than two players, and no clear rules. The outcomes of business decisions are rarely a clear win or loss, and there are far too many variables … Today's AI systems do their best to emulate the functioning of the human brain's neural networks, but they do this in a very limited way.”

Pointing out that “AI is only as good as the data it receives,” Wadhwa makes a very salient point. Artificial intelligence is not “thinking like a human.” Rather it's replicating aspects of human thought through the more sophisticated use of information. It's still structured around input and output.

However, Wadhwa also makes an interesting caveat in talking about one of the most promising aspects of artificial intelligence in today's business world.

Wadhwa uses mega-retailer Amazon as an example. Talking about how the Amazon company takes data from various silos and ports it to interactive destinations, Wadhwa suggests that consolidating all of this data across departments can innovate in the realms of customer service, business intelligence and much more.

“Amazon is solving a problem many companies have – disconnected islands of data,” Wadhwa writes.

In other words, taking data sets across platforms and applying them throughout an architecture is one of the biggest current roles of artificial intelligence software, and it may constitute some of the best use cases for business within the next few years. An artificial intelligence entity might not be able to fully behave and act like a human – but it does have very powerful capabilities related to data crunching and insight development.

Businesses are also talking a lot these days about unified commerce and unified communications. There is the idea that by consolidating all of their channels and helping them become interactive, businesses are positioning themselves for agile competition throughout the next decade. This is again something that artificial intelligence can help with. It can handle the various data sets and deploy them where they are needed in a somewhat automated and self-driven way. At a very broad level, artificial intelligence takes the burden off of human handlers and directs its own operations in various compelling ways.

With that in mind, machine learning advances are certain to promote the use of data sets across platforms in order to innovate. Although other big roles and processes may be coming down the pike, this is probably going to be a major aspect of machine learning and AI in the short term.

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Written by Justin Stoltzfus
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Justin Stoltzfus is a freelance writer for various Web and print publications. His work has appeared in online magazines including Preservation Online, a project of the National Historic Trust, and many other venues.
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