Thursday 26 March 2020

Top 5 ways Machine Learning will Impact in Your Everyday Life




Artificial intelligence (AI) and machine learning are now considered one of the greatest innovations since the chip. AI was a bizarre concept from science fiction, but now it's becoming a daily reality. Neural networks (which mimic the process of real neurons in the brain) pave the way for breakthroughs in machine learning, known as deep learning.

Machine learning can help us live happier, healthier, and more productive lives ... if we know how to use its power.

Some say that AI marks the beginning of another “industrial revolution”. While the previous industrial revolution used physical and mechanical forces, this new revolution will take advantage of mental and cognitive skills. One day computers will not only replace manual work, but also intellectual work. But how exactly will it happen? And is that happening already?

Here are 5 ways artificial intelligence and machine learning will impact your everyday life.

1.      Gaming intelligence


Some of you may remember 1997 when IBM's deep blue defeated Gary Kasparov in chess. But if you weren't old enough, you may remember when another computer program, AlphaGo from Google DeepMind, defeated Lee world champion Go in 2016.
Go is an ancient Chinese game that is much more difficult to master than computer chess. However, AlphaGo was trained specifically to play Go by not only analyzing the movements of the best players, but also learning to play the game better by practicing against yourself a million times.

2.      Self-Driving Cars and Automated Transportation


Did you fly recently? In this case you have already seen the automation of the transport to work. These modern commercial aircraft use the FMS (Flight Management System), a combination of GPS, motion sensors and computer systems to track their position during the flight. For example, a Boeing 777 pilot spends an average of seven minutes manually steering the aircraft, and many of these minutes are spent on takeoff and landing.

The jump in autonomous cars is more complicated. There are more cars on the road, obstacles that need to be avoided, and limits to consider in terms of traffic patterns and rules. Nevertheless, autonomous cars are already a reality. According to a study of 55 Google vehicles that have covered a total of more than 1.3 million kilometers, these AI-powered cars have even surpassed the safety of human-powered cars.
The question of navigation has long been solved. Google Maps already provides location data from your smartphone. Comparing the location of a device from one point to another can determine the speed at which the device is moving. Simply put, it can determine slow traffic in real time. This data can be combined with user-reported incidents to create a picture of traffic at a specific point in time. Maps can recommend the fastest route due to traffic jams, construction, or accidents between you and your destination.

But what about the ability to drive a car? Machine learning enables autonomous cars to adapt immediately to changing road conditions and at the same time learn new driving situations. Through the continuous analysis of a flow of visual data and sensors, on-board computers can make decisions in fractions of a second even faster than well-trained drivers.

It is not magic. It is based on the same basic principles of machine learning that are used in other industries. They have input functions (i.e. visual and real-time sensor data) and outputs (i.e. a decision from the universe of possible next "actions" for a car).

Of course, these autonomous cars already exist, but are they ready for prime time? Perhaps not yet, because vehicles currently have to have a driver for safety reasons. Despite exciting developments in this new area of ​​automated transport, the technology is not yet perfect. But give it a few months or years and you will probably want to own one of these cars.

3.      Taking over dangerous jobs


One of the most dangerous tasks is bomb disposal. Today robots (or technically drones) take care of these risky professions. Most of these drones currently require a human to control them. As machine learning technology improves in the future, these tasks will be completely done by robots with AI. This technology alone has saved thousands of lives.
Another job outsourced to robots is welding. This type of work creates noise, intense heat, and toxic substances that are present in the fumes. Without automatic learning, these welding robots should be pre-programmed to weld at a specific point. Advances in image processing and deep learning, however, have allowed greater flexibility and accuracy.

4.      Banking Innovation


Think about how many people have a bank account. Now also consider the number of credit cards in circulation. How many hours would it take employees to view the thousands of transactions that take place every day? If you notice an anomaly, your bank account may be empty or your credit card may have reached its maximum.

Using location data and buying patterns, AI can also help banks and lenders identify fraudulent behavior as it happens. These anomaly detection models based on machine learning monitor transaction requests. You can spot trends in your transactions and alert users to suspicious activity.

They can even confirm with you that the purchase was yours before proceeding with the payment. It may seem annoying if you only eat out on vacation, but it could save you thousands of dollars a day.

5.      Enhancement in Healthcare


Hospitals could soon put their wellbeing in the hands of an AI, and that's good news. Hospitals that use machine learning to treat patients see fewer accidents and fewer hospital-related illnesses, such as sepsis. AI is also addressing some of the most difficult problems to solve in medicine, such as: B. the ability to better understand genetic diseases using predictive models.
Healthcare professionals previously had to manually review a variety of data before diagnosing or treating a patient. Today, high-performance computing GPUs have become key tools for deep learning and AI platforms. Deep learning models quickly deliver real-time information and, in conjunction with the explosion in computing power, help medical professionals diagnose patients faster and more accurately and develop new and innovative medicines and treatments. Reduce medical and diagnostic errors, predict and predict adverse events lower healthcare costs for providers and patients.

There are other area as well where machine learning will impact in your daily life. Here I have mentioned only top 5 ways. You can observe other areas as well in your daily life.

Conclusion


I hope you have understood that how machine learning is impacting in our daily life. There are other areas as well where machine learning is impacting in our daily life. You can comment area in the below section where you think that machine learning is impacting more.
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