Is 2017 the Year of AI?

Data CenterArtificial Intelligence is making enormous leaps and in 2016 produced several results that were unimaginable a few years ago. The year started with Google’s AlphaGo beating the world champion in Go. The year ended up with an announcement by Google that its translation software using artificial intelligence had achieved the same level of competency as human translators.

This has all come about through applying the new techniques of machine learning. The computers are not yet intelligent in any sense of being able to pass the Turing test (a computer being able to simulate human conversation), but the new learning software builds up competency in specific fields of endeavor using trial and error, in much the same manner as people learn something new.

It is the persistent trials and errors that enable software like that used at Facebook to be getting eerily good at identifying people and places in photographs. The computer software can examine every photograph posted to Facebook or the open internet. The software then tries to guess what it is seeing, and its guess is then compared to what the photograph is really showing. Over time, the computer makes more and more refined guesses and the level of success climbs. It ‘learns’ and in a relatively short period of time can pick up a very specific competence.

2017 might be the year where we finally start seeing real changes in the world due to this machine learning. Up until now, each of the amazing things that AI has been able to do (such as beat the Go champion) were due to an effort by a team aimed at a specific goal. But the main purpose of these various feats was to see just how far AI could be pushed in terms of competency.

But this might be the year when AI computing power goes commercial. Google has developed a cloud product they are calling the Google Brain Team that is going to make Google’s AI software available to others. Companies of all sorts are going to be able, for the first time, to apply AI techniques to what they do for a living.

And it’s hard to even imagine what this is going to mean. You can look at the example of Google Translate to see what is possible. That service has been around for a decade, and was more of an amusement than a real tool. It was great for translating individual words or short phrases but could not handle the complicated nuances of whole sentences. But within a short time after applying the Google Brain Team software to the existing product it leaped forward in the competence of translating. The software can now accurately translate sentences between eight languages and is working to extend that to over one hundred languages. Language experts already predicted that this is likely to put a lot of human translators out of business. But it will also make it easier to converse and do business between those using different languages. We are on the cusp of having a universal human translator through the application of machine learning.

Now companies in many industries will unleash AI on their processes. If AI can figure out how to play Go at a championship level then it can learn a whole lot of other things that could be of great commercial importance. Perhaps it can be used to figure out the fastest way to create vaccines for new viruses. There are firms on Wall Street that have the goal of using AI to completely replace human analysts. It could be used to streamline manufacturing processes to make it cheaper to make almost anything.

The scientists and engineers working on Google Translate said that AI improved their product far more within a few months than what they had been able to do in over a decade. Picture that same kind of improvements popping up in every industry and within just a few years we could be looking at a different world. A lot of companies have already figured out that they need to deploy AI techniques or fall behind competitors that use them. We will be seeing a gold rush in AI and I can’t wait to see what this means in our daily lives.

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