Trends in machine learning

The sheer number of devices prompting us today to connect to the internet and exchange data is endless. These devices have brought smart solutions to everyday problems we encounter at our homes and workplace or even both simultaneously.

Trends in machine learning

Trends in machine learning

The sheer number of devices prompting us today to connect to the internet and exchange data is endless. These devices have brought smart solutions to everyday problems we encounter at our homes and workplace or even both simultaneously. While the IoT scene has exploded with a plethora of offerings such as rapid disease screening biochips to wearable body vital sensors, one thing that has remain unchanged is the need for crunching the vast amounts of data available.

The sheer number of devices prompting us today to connect to the internet and exchange data is endless. These devices have brought smart solutions to everyday problems we encounter at our homes and workplace or even both simultaneously. While the IoT scene has exploded with a plethora of offerings such as rapid disease screening biochips to wearable body vital sensors, one thing that has remain unchanged is the need for crunching the vast amounts of data available.

The manufacturing of cheaper and easily relatable sensors has been driven by recent developments in material sciences. We are looking at a combination of great technology being matched with equally clever and efficient manufacturing coming together in what can be called as the modern day techno-Industrial revolution. The expansion of devices and sensors crunching data and making available great insights, all connected via Internet of Things is good. However, the mind boggling amount of data generated needs careful curation and self-learning systems which would make these tacit learning more inclusive.

The speed at which we are facing a deluge of data makes it even more important to create such systems which can quickly accumulate and assimilate learning outcomes and apply them correctly. This may sound easy but in real world scenario, it is the toughest challenge being faced by the industry and computer scientists today.

Here is the point where Big data analytics and machine learning should join hands to come to our rescue. Machine learning can be defined as “..construction and study of systems that can learn from data, rather than follow only explicitly programmed instructions”. It is not science fiction anymore, where customer shopping trends and music choices help the companies shape the ‘recommended’ lists and suggested items on their websites. We have even made computers dream where the Google deep dream project took a random set of images and let its Deep dream AI work its magic to generate learned image patterns from memory.

TAnother big challenge which Facebook is trying to tackle with the help of machine learning and AI is busting fake news. The culpability of today’s news sources that have mushroomed in the webs sphere needs to be put to the ultimate test. Whether or not these news are factually correct. Facebook and many other independent researchers with Universities such as Carnegie Mellon are trying to take the big data analysis approach. Here they are trying to feed their AI with metadata sets, which in turn help in creating machine learning exercises. Simply put the large news data sets are learnt and understood by the AI to successfully discern between real news and fake news. At least this is what the scientists are hoping to create in their pursuit of busting circulating fake news.

Machine learning and big data analytics will mean that the Fitbit you are wearing would soon get a brother which would tune to the internet on its own. Then go on to let your physician know about your vitals and possible ailments which might be affecting you. Internet of Things has opened up a whole new dimension for big data analytics and machine learning to conquer. And conquer it will, largely due to our readiness and swift response within the recent years to tackle the issues. For these issues transcend the boundaries of mere scientific and technological interest and have meandered into the zone of touching our innate needs.

We hope to bring you many more such articles pertaining to the developments, needs and discoveries from the world of machine learning, AI and IoT.

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