The future of life: Machine Learning....
Published: 2020-06-01 15:22:26

Back in the day, machine experiences were a drag. Hit a button, pull a lever, and get the task done. Decades later, with subsequent computing innovation, machines have transformed into their ultra-smart, self-learning, automated versions that are sweeping the human landscape.
The underlying technology that’s reinventing machines to personalize human experiences is Machine Learning (ML), a branch of Artificial Intelligence and a strong buzzword in today’s digital-first world. In essence, it’s about programming machines to infuse the ability of self-learning by leveraging Big Data. Information extracted from various touch points is analyzed and used to predict intentions for actionable intelligence.
And, the good news is, Latest technology is advancing consistently and revolutionizing every facet of our routines. Humans had their first brush-up with Machine Learning when voice-controlled personal assistants — Amazon’s Echo and Alexa — were launched. These devices are a new normal with the trend of smart homes picking up. Driverless cars, which were a quintessential sci-fi fantasy, aren’t something of the far-off future now. These new-age vehicles, aimed at cutting down human labor, are tested across the world for their utility benefits.
Initially, the idea of intelligent machines was preposterous. Machines that act on behalf of humans weren’t a norm. However, with enablement and evolution of Machine Learning in our daily lives, the human landscape is radically changing and how.
A few part of the machine learning that is being a inspeprabale part of our dailylife are:
Health
Currently, Machine Learning is applied for swift patient diagnosis and accelerated healthcare delivery. Though these machines come under the scrutiny of not being ‘human enough’, the accuracy and precision offered by them are unparalleled.
From administration, record-keeping to fully fledged diagnosis and treatments, ML has the capability to analyze the crisis at hand and compare it with numerous other scenarios for the right treatment and procedure. This comparison saves time and paves a strategic path for the decisive medical approach.
Moreover, Machine Learning can empower surgical robots to help doctors in medical procedures while ensuring minimal invasion and high precision. This achievement can improve the success rates of surgical procedures and accelerate turnaround time with cost benefits. In the context of healthcare, ML can be a critical enabler to efficient diagnosis, research, and treatment, thereby underlining the holistic transformation of the sector.
As per a McKinsey Report, the stagnation of the pharmaceutical industries will end, and the healthcare industry will embark on a transitional journey, mustering savings up to $100 billion in the U.S alone.
Transportation
Today’s transportation industry is highly influenced by Machine Learning. The technology has been instrumental in eradicating the threat posed by reckless driving through the deployment of sensory management and automation. This has intelligized vehicles to understand the surrounding parameters and take precautionary action whenever required to ensure passenger safety.
China is testing driverless buses for its city while Google and Rolls Royce have collaborated to design and launch the world’s first self-driving ship by 2020. The ship will be leveraging Google’s Cloud Machine Learning Engine to understand the sea and objects surrounding it. This will enable the remote controlling of the vessel and end up reducing the resources involved in the transportation.
Beyond vehicles, Machine Learning can soon by deployed for traffic management and preventing traffic congestions on roads. China and Singapore, at the moment, are leading the innovation and creating algorithms that can help drivers choose routes cleared off traffic.
Social Media Services
From personalizing your news feed to better ads targeting, social media platforms are utilizing machine learning for their own and user benefits. Here are a few examples that you must be noticing, using, and loving in your social media accounts, without realizing that these wonderful features are nothing but the applications of ML.
•	People You May Know: Machine learning works on a simple concept: understanding with experiences. Facebook continuously notices the friends that you connect with, the profiles that you visit very often, your interests, workplace, or a group that you share with someone etc. On the basis of continuous learning, a list of Facebook users are suggested that you can become friends with.
•	Face Recognition: You upload a picture of you with a friend and Facebook instantly recognizes that friend. Facebook checks the poses and projections in the picture, notice the unique features, and then match them with the people in your friend list. The entire process at the backend is complicated and takes care of the precision factor but seems to be a simple application of ML at the front end.
•	Similar Pins: Machine learning is the core element of Computer Vision, which is a technique to extract useful information from images and videos. Pinterest uses computer vision to identify the objects (or pins) in the images and recommend similar pins accordingly.
Education
It’s true that teachers cannot be replaced by bots, but they sure can be assisted by the diversity that Machine Learning can provide to their methods of teaching and education on a whole. ML capabilities are being used to assess the child’s academic understanding, analyze the way he/she perceives knowledge, and create a customized academic plan that can help focus on the wholesome attribute of that specific student.
The algorithms analyze test results and create a unique grading system that can free up the teachers’ time and help refine the education modules for children. Not to mention, ML can be extremely helpful for students with disabilities and learning gaps. ML, in addition to teaching, is simplifying administrative duties and help educational institutions create an organized means of administering students and staff via its automated responses, customized software and more. It’s all about breaking down the processes and making organizing an institution less of a burden.
CONCLUSION
Machine Learning, in a nutshell, is addressing the complexities of all the sectors, and if we go as per the numerous statistics, it’s highly plausible that almost all industries will embrace the algorithm-based working and streamline their processing. Machine Learning is the future and those who choose to skip this evolutionary element can be well assured of their impending decline.