Best upcoming Smartphone technologies in 2017
Best upcoming Smartphone technologies in 2017 Technology is evolving, adapting and progressing. There is always something new on the horizon, and we can’t help but wait and wonder what technological marvels are coming next. Machine Learning is on the horizon that is going to change your life.
What is Machine Learning
Machine learning is an analysis of data that automates analytical solution. Using algorithms that iteratively learn from data, machine learning allows processing units to capture hidden insights without being explicitly programmed. With volumes of data available, faster computational power at affordable cost, machine learning has a brighter future than ever to change our day to day interaction with technology.
Deloitte Global TMT 2017 predicts over 300 MM smartphones to have built-in machine learning capabilities which will significantly transform the way we interact with technology. It states that over one fifth (300 MM) of the total smartphones sold in the year 2017 will have Machine Learning Capability that can operate without the network connectivity.
The AI (artificial intelligence) will drive our day to day tasks, augmented reality and much more. The biggest challenge for implementing Machine Learning is the need for raw processing power; it was earlier done from the cloud, however, it’ll change in 2017 with the influx of better processing units in the current generation smartphones.
Existing AI Capabilities
Facebook and Google use Machine Learning in their voice recognition and image processing which is currently being done in the cloud and is displayed on the smartphones. With the processing expected to be executed in the smartphones itself means lower latency and better privacy.
Google launched a prototype technology RAISR to reduce data required for high-resolution images by up to 75%. It achieved so by making low-resolution images appear more detailed. Google is applying this technique to more than a billion images every week and has reduced user’s total bandwidth by about a third.
Paypal (Fraud Detection)
Paypal is using machine learning algorithms through various tools to flag fraudulent transactions. Machine Learning processes millions of transactions which are available for learning and using unsupervised and supervised techniques; machine learning can assist in distinguishing between legitimate and fraudulent activities.
As per IBM’s survey, 74% of the top auto executives believe to have smart cars on roads by 2025. It will use unsupervised learning by through its environment and integrate into the internet of things. Self-driving cars are being tested by Tesla who (if the reports are to be believed) would be closer to self-driving by 3-6 months.
It’s most famous and known algorithm which is evolving over time. Google and other competitors are working to improve the way we search. It learns from our behavior when we search for a string. If we open one link and then either change the search criteria or open multiple more links it gets to learn that the first link did not solve the purpose and likewise.
Last year, Twitter bought UK AI startup Magic Pony which does the same as Google, using machine learning techniques to improve the resolution of low-quality Videos. This will provide tangible benefits to the consumers by lowering the data requirements.
Qualcomm’s Zeroth is another initiative from Qualcomm releasing its Software development kit for organizations to design deep learning programs on devices – Smartphones, Drones, etc. which will be supported by Qualcomm chips.