A couple of days back, I came across this application which scans your face and automatically adds dynamics – it makes you look older, younger, can add or modify your smile and even show how you’d look if you were of the opposite gender. A novelty app at best, FaceApp does bring about the big question: Can AI actually power the next generation of consumer technology?
Artificial Intelligence is, without a doubt, turning out to be the game changer as far as interaction with consumer electronics and tech devices is considered. Throw a little bit of machine learning and other complex algorithms into the mix, and you’re looking at a full fledged ecosystem with a plethora of possibilities.
And this shall be the crux of my article here – can Artificial Intelligence, with a little bit of machine learning, bring the next revolution as far as contextual interactions with tech devices go?
A BEVY OF APPLICATIONS
AI by itself has a very vivid scope. Deep Learning and Neural Networks are composed of AI, and it can therefore be applied to a lot of things, not merely studying user inputs. Data Mining and Machine Learning, needless to say, are right up there with the possible use cases.
In fact, the statistics speak for themselves. According to Statista, the revenue from the Artificial Intelligence market worldwide is estimated to be at $1.2 billion U.S. Dollars this year, with the number estimated to rise five-fold to $6 billion in 2020 and thirty-fold to $36 billion in 2025.
But specifically, I believe that AI in terms of consumer technology can make it big in the following spheres (for a start).
When it comes to healthcare, the biggest use cases for artificial intelligence can come in the form of predictive medicine and personal genomics. Personal genomics would lead to better disease identification and management, which would in turn lead to better predictive medicine.
I’ve already spoken at length about genomics, and I’ve mentioned there that the human body is a veritable pool of data. The human body generates data on an every moment basis, and tapping into this data leads to more information, more insight and in turn, more informed decisions.
But here’s the thing when it comes to genomics: even though scientists have made tremendous headway in sequencing the human genome, it’s still hard to pin point what exactly is happening. This is due to genes constantly acting out of combination with external variables. Think of a computer program, that has multiple, random alternative measures depending on what the user input is going to be.
Artificial Intelligence is already being used (in the form of Google’s Deep Mind program and IBM’S Watson program) to study massive silos of data – in the form of patient clinical records, diagnostic images and treatment plans – to look for a pattern in all the observations. This is paving the way for a better system which will not only study the genetic variations at a molecular level, but will also give rise to personal genetics – genetics and gene types which are intricately designed according to different body types.
And not just genetics. The future will also include specialised drugs designed to target specific diseases, wearable trackers which will pick up intricate factors and sensors which will constantly monitor your health. All this, to develop more personalised and effective healthcare systems. And all this, can be achieved in a shorter time span through, you guessed it, Artificial Intelligence.
Self driving cars have been the rage for a couple of years now, and Artificial Intelligence will only make things better in this regard. The best examples of this were seen at CES 2017, with major car manufacturers teaming up with OEMs and software providers to deliver vehicle systems that can predict obstacles and prevent accidents in a more quantified way.
The market for self driving cars is expected to grow at a massive rate in the next few years, and this will in turn create new avenues for Artificial Intelligence as well. With a larger share of cars connected to the internet (it’s estimated that 17% of all the cars on the streets worldwide will be connected to the internet in 2018), AI can only bring more use cases to the mix.
Artificial Intelligence has made its way to handheld tech – and no, I’m not talking about just smartphones. CES 2017 saw some downright weird innovations, such as AI powered toothbrushes, hair brushes, shoes and fridges.
A big factor in all these gadgets has been the inclusion of voice-guided commands, which enables users to interact with their devices through voice. Think of Alexa, but on your fridge. Booking a cab, ordering a pizza, turning off the lights – all this can be accomplished through voice commands (Internet of Things, ladies and gentlemen).
But with AI, the need for voice commands can itself be minimised. What if a software could study your schedule for the day, and ask you a couple of hours ahead whether you wanted to book a cab to go for the movies, the ticket for which was brought by your personal assistant software. Needless to say, the scope is endless, and the future holds big things when AI and IoT come together.
Finally, one of the biggest aspects of the Artificial Intelligence revolution has been deep learning – which involves analysing the data collected by smart devices to make them more useful. Understanding language, recognising faces, making use of cloud services – all these factors constitute just a speck of what AI can achieve.
The best place to start would be assessing micro-problems and driving growth accordingly. Assessing external factors, studying what would be the appropriate ‘human’ response, and delivering it through a machine – that is what AI will be about, and that is what will drive the next wave of innovation for consumer technology.
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