2019 – The Year of Machine Learning?

While the phrase “artificial intelligence” has traditionally brought to mind killer robots and conversational supercomputers, its progression into everyday use has steadily been growing. Machine learning, a much less loaded phrase but meaning pretty much the same thing, has taken its place, and has found a host of applications in a variety of situations.

The likelihood is that you’ve already used some machine learning today without even realising it. With industry giants like Google and Facebook pushing its development, machine learning is integrated across app and mobile development, search engines and social media in a big way. The use of algorithms to massively speed up data crunching and decision making can be applied to pretty much any situation where accurate solutions are needed from a wide array of variables.

Bots X Humans

Many software developers are looking at ways to introduce machine learning in new and innovative ways; a major use is in the development of bots and human-like interactions on websites and services. In a way, this should be the least obvious use of machine learning of all, as if it works as it should, the results should be indistinguishable from interacting with a real human.

Who’s on the phone?

Devices you can talk to are now commonplace, and that trend is only going to continue as it becomes more acceptable – and practical – to talk to machines rather than input all commands manually. Last year Google showcased an example of this, with one of their bots making a phone call to an unsuspecting hairdresser to book an appointment.

While it seems inevitable that this sort of interaction will be monitored and controlled more closely in the future, it certainly highlights the possibilities that AIs and machine learning software can bring; to a large extent, it will be the social acceptability of these sorts of applications which drive them, or hold them back.

Who’s in the driving seat?

Machine learning is also a major force in the development of automated controls, on devices as varied as home hubs and cars. The automotive industry is forever keen to find new technologies, and assisted driving systems are already commonplace on our roads. While it can be seen as little more than a logical progression from things like anti lock braking systems and adjustable suspension, the introduction of truly automatic personal vehicles will no doubt herald a new age in motoring – with the accompanying race for best use of the technology at the same time. Laws have already been passed in many countries to ease the introduction of driverless cars, and many products are already in the final stages of development. Automatic cars use machine learning to better understand conditions and make choices on the road. Equally, companies like Uber are investing heavily in self-driving technology, perhaps with the aim of taking car ownership right out the equation.

While the development of machine learning systems at big companies will make the headlines for now, it seems likely that the most significant developments in machine learning will come from an unanticipated source. The world seems ready for the rise of the robots, and now it’s up to the developers to make it happen.

John Morris
John Morrishttps://www.tenoblog.com
John Morris is a self-motivated person, a blogging enthusiast who loves to peek into the minds of innovative entrepreneurs. He's inspired by emerging tech & business trends and is dedicated to sharing his passion with readers.


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