The Penetration of Machine Learning in Today’s Tech-Driven World

Speak about the term “Machine Learning” and chances are, thoughts of a sentient race of robotic overlords spring to mind. But instead of a world where Skynet is determining your value as a person, we needn’t look so far to see examples of how intrinsically deep machine learning and artificial intelligence impacts our day to day life and potentially our future.

From simple games that seem to eerily know what we are thinking of just by answering 21 questions, to assistants in our pockets who seemingly know our usage habits of our mobile devices right up to a self-driving car, potentially ferrying us to our destination sans idle chit-chat; Artificial Intelligence and subsequently Machine Learning is everywhere.

Different processes in machine learning

Different processes in machine learning

Machine Learning is the act of making a computer smarter through attaining thought processes and decision-making abilities similar to that of a human being.  Put simply, via a series of algorithms and an artificial neural network, a computer or a program will be easily able to learn in the example of the video above, what a dog looks like and how to identify one in a photo.


You don’t have to look too far to find that several companies are doing amazing things with Machine Learning-driven products. One of the first examples that come to mind are chatbots and most famously, Facebook’s iteration that seemingly developed their own language and had to be prematurely terminated. These days businesses are also hopping on board the Messenger Chatbot bandwagon to bring a better customer experience, without the manpower needed to run the helplines.

On the flip side, a company has also developed Woebot, a chatbot therapist that was created by a team of Stanford psychologists and AI experts. It uses daily conversations and mood tracking to help people manage mental health without the exorbitant fees associated with a traditional approach. Of course, this is in no way a replacement for a real medical solution but it’s certainly an interesting way to apply a mix of a neural network and traditional know-how.



On the other end of the spectrum, Singapore has been making waves with a self driving car system from Nutonomy, similar to other autonomous motor vehicles in the US from Google and is definitely an advancement in technology that will revolutionize the way we travel and commute. Granted Nutonomy is only accessible and testing in a small area for now, with more data and a more refined neural network, the sky is the limit and before long, I’m sure driverless cars will a service island wide.

What all these have in common are the requirement of a vast amount of data to make each neural network a lot more accurate and facilitate testing. The greater the data the better prepared and learned the algorithm becomes. At Supahands we provide the workforce that will help your company prepare the necessary datasets and take the hassle out of training your computer or application for the foreseeable future. With the added benefits of predictive routing, we also ensure that we only produce quality data sets. Let us help you create both our visions of the future together.

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