The AI revolution: Is the future finally now?

With so much support from these titans of industry, it’s no wonder that the latest burst of AI interest seems to be gaining momentum rather than losing it. But are the techniques used today truly what is meant by AI?

As is typically the case in questions of technology and business, the answer is yes and no. Just like there are varying levels of complexity in other areas of technology (consider the range of databases from simple to complex; from SQL to NoSQL; or the range of programming languages LOGO, BASIC, C, Perl, Swift, R) there are many technologies and techniques that naturally fall under the moniker ‘AI’.

AI as a technology is nebulous. Would machine learning be possible without access to large amounts of data from a traditional SQL or a cutting-edge NoSQL environment? Could an AI package be effectively used without modern concepts of APIs and REST services?

In my opinion, all of the tools commonly covered and discussed today are a part of the larger AI family of technologies that are going to drive the next generation of consumer, corporate and government solutions.

On the other hand, you have to remember that true “artificial intelligence” won’t happen anytime soon–at least no examples that can act independently of human intervention. A true AI system has the ability to learn on its own, making connections and improving on past scenarios without relying on programmed algorithms to improve capabilities.  This is thankfully, still the realm of Science Fiction.

What is called AI even today is in fact, the leveraging of machines with minimal–though not zero–human intelligence to solve specific, narrow problems. Humans still have the upper hand as machines cannot think on their own and rely on human intervention (through code) and past data to be able to work. They can be better at finding patterns that humans can miss and find similarities between objects, but this is possible only through sheer horsepower.  With today’s state-of-the-art they will never be able to invent something totally new or independently address a problem that they have never come across before.

Most of what passes for AI today is the sophisticated application of statistical techniques to data invented in the past four-to-five decades, not ‘real’ intelligence. Please note however, that this designation does not detract from the immense capabilities afforded by the newfound resurgence of AI.  It may not be fundamentally “intelligent” but is no less useful and impressive.

While the core technologies of AI are similar to those of prior years and the term AI has become somewhat of a catchall for a variety of different techniques, the biggest difference–and perhaps what will spur future cycles of interest–is the thirst for and commitment to more from both corporations and consumers.  With continued funding, research and interest in AI and with advances in the tools and techniques needs to capitalize on them, perhaps one day we will finally witness the emergence of true, independent AI.


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