In the last week of February 2019, over 55,000 white-collar executives from all over the world converged at the Mobile World Congress in Barcelona. The broad consensus influencing the showcased and proposed innovations at the event was that the future belongs to personalized, inter-connected experiences, accessible whenever needed. This would become a reality when we create an all-encompassing Internet of Things singularity!
The concept of IoT is to embed objects and gadgets with sensors and other such forms of hardware. These objects will then be able to interact with each other using the internet. It will facilitate remote monitoring and controlling of such smart devices.
The key to creation of a better and ‘Smart’ world is to bring machine learning and cloud computing together. Equipped with artificial intelligence powered by cloud, the IoT devices will be able to seamlessly and autonomously deliver the desired results. Until now, concerns like cyber security, data theft, international regulations, etc. affected the adoption of Cloud computing. However, things are changing now as more and more people discover the scope offered by cloud, especially in implementation of the IoT and smart cities globally. Soon, Cloud will evolve from being a support system to becoming a production tool by facilitating machine learning.
Machine learning in the Cloud
Paired with Cloud computing, machine learning will create an ‘intelligent cloud’. This would take machine learning to the level where machines will be able to operate independent of human inputs. The intelligent Cloud gains knowledge by accessing the humongous volumes of data stored on the cloud. It would analyse and predict with great accuracy, leading to a more efficient business operation.
There are two essential pre-requisites for running any AI system optimally and viably: scalable and low-cost computing/storage and the power to analyse mind-boggling data volumes. That’s why the merger between Cloud and machine learning is a great ‘marriage of convenience’. The most far-reaching benefits of machine learning on Cloud will be as follows.
The vast ocean of data stored on cloud serves as the source of information for machine learning. Hundreds of millions of people use Cloud for computing, storage of data and connecting to other users, resulting in millions of processes at any given time, all of which enhance machine learning. Platforms like Watson from IBM, GCP from Google and Microsoft Azure, etc. have already made it an evolving and competitive ecosystem. Despite being in its infancy, the cognitive Cloud-based computing systems will be greatly involved in healthcare, public utilities, hospitality, sales and even personal lives in the future.
Smart Home Devices/Digital Assistants
Machine learning has led to the creation of voice controlled devices that independently connect with various smart home products and perform a number of tasks. Amazon Echo, Google Home and Apple’s HomePod are among the most reputed products in this category.
Similarly, there are voice operated digital personal assistants from Google for Android based devices and Siri in case of Apple phones. These smart devices/personal assistants have a 3-stage operational process: speech to text, text to purpose and purpose to execution. When a command is given, the machine breaks the sound into text and searches for the relevant data in its ever-expanding database. Once it understands the communication, it takes the next step of carrying out the instructed task. The integration of machine learning with cloud storage will give the devices, access to virtually unlimited information and enhance their knowledge as well as operational capabilities immensely.
The integration of cloud and machine learning is going to be a game-changer in the way the machines work around us. Whether it be driver-less cars, aircrafts on auto-pilot, predicting the weather, sen