Artificial intelligence (AI) is frequently the focus of technology news. There is a marked tendency, however, to treat AI as if it were a singular thing.

The Varieties of AI
It isn't. A recent article in Wired points out that there are many varieties of artificial intelligence. If you hear of deep neural networks, for example, you are reading about a pattern recognition system. Facebook, Microsoft, and Google all use neural networks.

Another form of AI uses probabilistic programming. This type of AI uses the hypotheses of programmers, and then use data generated by AI to test and refine those hypotheses.

Probabilistic programming can be used in translation, for example. It can also be used to cull meaning from raw data. Ben Vigoda, the chief executive officer and founder of Gamalon, a probabilistic programming AI company, believes that form of AI crunches information and data more rapidly than neural networks. It can also learn from much smaller data streams.

Other AIs?

Evolutionists try to replicate the rules of natural selection.

Symbolists code knowledge and the rules with which that knowledge can be assimilated by machines.

The unifying element, and the intriguing advantage of AI is the ability for the systems to learn and continually improve over time. The future likely belongs to AI blends.

Using probabilistic programming allows scientists to create algorithms to more accurately predict outcomes, based on future events or inputs. It can also provide researchers with insight into why and how an AI system makes the decision it does. As a result, they can refine its decision-making processes.

Neural networks excel at speech and image recognition. Those processes are not in competition with the kind of research into decision-making that probabilistic programming allows. Companies are increasingly combining the two.

What Businesses Use AI For
How do businesses use AI? A recent Forbes article pinpointed four ways in which organizations will deploy AI, both now and in the future.

The first is chatbots used for customer service. Chatbots are already operating in the websites of many companies and can be particularly useful for frequently asked customer questions.

The second is crunching of data. This can be specifically created databases, such as responses to customer surveys.

Intriguingly, though, AI can also be used to crunch data for specific purposes. A company looking for energy sources, for example, may have tons of data on drilling sites, practices, and history. But the data may exist in far-flung locations and sources, like technical manuals and maps long out of use. AI can be fed this data to find usable information and patterns.

The third is automation of manual processes. Factories, which are increasingly using robots, are often given as examples. Forbes observes that the first demarcation is likely to be routine work versus nonroutine work. Box scores and financial summaries in journalism, for example, are routine - they involve reporting facts and figures on what has happened. Analysis and reporting are nonroutine work unlikely to be done by robots.

The fourth is using unstructured data. Customer service centers, for example, may collect data on customer and employee personalities with the eventual aim of matching customers with employees who suit their own personalities.

As you can see, AI comes in many forms and has many practical uses for business. In the future, we expect to see an increased use of a combination of AI technologies driving innovation and research across a variety of industries. Consider the likely impact AI will have in your industry, both directly and indirectly in the next two years and beyond.