Last year in the year 2019, the value of the Machine Learning market was valued at USD 8.43 billion which is likely to exhibit a CAGR of 39.2% to reach USD 117.19 billion by 2027.
One of the biggest innovations for businesses and also for mankind, technologies like AI, ML, AR, VR has entered the market and brought us fruitful and accurate results. Among these top technologies, Machine Learning technology is made to make the work processes of everyday life easier, smoother, and error-free.
The technology has reinvented machines to personalize human experiences by integrating the ability to self-learn and work by leveraging big data into consideration. Various information is gathered and analyzed that are extracted from different touchpoints for predicting the actions thoroughly. By this, it becomes easier to present better results instantly.
Machine learning technology today is revolutionizing the way we work and interact and is advancing consistently and has entered almost every facet of the routines. Humans had their first experience with ML when voice controller personal assistants came into existence in the form of Amazon Echo and Alexa. Driverless cars, more like a sci-fi fantasy, are not far from reality. The technology in short is cutting down human labor, costing parts, and others to bring accurate results.
There are more ways machine learning is making the work-life and everyday life of humans easier, smarter, and efficient. Here are a few examples stating how machine learning technology is swiftly impacting our life-
Top Ways Machine Learning Impacting Our Life
Health
Machine learning technology has entered the healthcare domain and is used for diagnosing patients. The accuracy, precision, and results offered by them are just unparalleled and slightly different from the human version of bringing results.
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Moving it, ML is highly used for administration purposes, record-keeping along with diagnosis, and treatments. ML has the capability of analyzing and comparing them with numerous scenarios for the right treatment and procedure. The method of analyzing and comparing further helps in saving time while paving a strategic path for a decisive medical approach.
Other than that, ML also empowers surgical robots for helping doctors in medical processes all the while ensuring invasion and precision. This in result helps in the success rate of surgical procedures.
A report by McKinsey stated that the healthcare industry will begin its transitional journey, saving up to $100 billion in the U.S alone.
Transportation
The transportation industry is also taking the leverage of Machine learning technology, eradicating several reckless driving threats by deploying sensory automation and management. Vehicles integrated with technology can understand the surrounding environment and take precautions for the safety of passengers.
Other than that, ML can also be deployed for traffic management, helping in traffic congestion.
Education
Though teachers can never be replaced by artificial intelligence, they can certainly be assisted by Machine learning technology for the purpose of teaching and educating. ML can be used for assessing the child’s academic understanding along with analyzing his/her knowledge and further creating an academic plan as per the requirements.
It is one of the best technologies for students with disabilities too. The technology simplifies administration duties while helping the educational system and the staff with automated responses, customized software, processes, etc.
Law
Machine learning technology automates the day-to-day activities of the lawyers freeing their everyday tasks and giving them space to focus on other major liable solutions.
The technology simply augments various data, documents, processes, and then analyzes them for serving as proofs, research, and other crucial information. Other than that, ML can systemize the operational tasks while keeping all the notes of the cases and reports.
Financial Industry
Today a major number of banks, financial institutions, and others are using ML-based complex algorithms to analyze & predict loan and related risks. Apart from that, the technology assesses the quality of the loan based application and offers information as per the requirements. Also, it helps in detecting frauds, scams, or any sort of threat.
The support system in the form of chatbots, voice recognition, and predictive analysis makes the customer experience even more smoother with timely processing of various tasks.
Environmental Preservation
With the help of big data, AI, one can store an ample amount of data, information, statistics, trends, and clothes to bring out the solution to the persisting issue.
According to IBM’s Green Horizon Project, it analyzed that environmental data taken from thousands of sources and sensors helps in producing accurate, right, and evolving weather and pollution based forecasts. This further helps city planners and other people working on the project to come up with solutions to mitigate environmental impact.
Elderly Care
As elderly care is a concern for many families and taking care of them majorly requires someone to rely upon.
To this, in-home robots are taking their place for elderly care and assisting them with everything. This gives relaxation and flexibility to the family members for managing the care of their loved ones.
The AI researchers and medical practitioners are piloting systems based on infrared cameras for detecting the elderly person’s activity. Other than that, the technology can also help in monitoring food consumption, alcohol is taken, fever, urinary frequency, bed & chair comfort, restlessness, eating, sleeping, and declining mobility criteria, and others.
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Endnote
These are some of the ways through which Machine learning technology is impacting the everyday life of the users, businesses, and ultimately the society. With the passage of time and advancement in technology, ML soon is going to take over the major areas and easing the process of working, interacting, and others efficiently.
FAQs
Machine Learning technology is basically made up of three parts-
– Computation algorithm for making determinations
– Features and variables meant for decision making
– Base knowledge through which the system learns
There are 4 types of machine learning technology
– Supervised learning
– Unsupervised learning
– Semi-supervised learning
– Reinforcement learning
Each and every machine learning technology got three major components-
1. Representation- This is meant for representing knowledge. The examples include- graphical models, neural networks, model ensembles, and more
2. Evaluation- It is meant for evaluating candidates’ programs. The example here include- prediction and recall, posterior probability, cost, margin, and others
3. Optimization- This revolves around the way of generating candidate programs through the searching process. The example of it includes- combinatorial optimization, constrained optimization, convex optimization
