How is Machine Learning Making Sci-Fi a Reality?

Machine Learning & its Uses in the Human World: The Future

Do you also hear new technological terminology every year? The answer is certainly yes. The pace at which new forms of technology are entering the world is unimaginable. The world is moving into an era where every aspect of our life involves technology.

One such form of technology is Machine Learning. The fundamental question is “What is Machine Learning?” In layman’s terms, it is the application of Artificial Intelligence that allows learning and improvement of systems with experience without being programmed explicitly.

It is witnessed that with each passing day, computational data is getting more voluminous, and it is cumbersome to manage and analyze that data. That’s where Machine Learning comes into the picture.

Machine Learning generates models to analyze the massive data quickly to deliver precise results.

So, broadly, we will look into its applications in the tech world and daily life.

11 Machine Learning Uses in Real Life Voice recognition:

Alexa play this song!! When we instruct Alexa, and it gives us desirable results. It is the voice recognition feature that is possible all due to Machine Learning.

Also, algorithms convert our speech into text in google voice assistant and Siri and look for the asked data to give us accurate results. The Voice recognition feature has made it more convenient for users.

Google Maps:

Whenever we are traveling, we usually use google maps which gives us the shortest route. Apart from it, it also foresees the traffic conditions like whether it is congested or semi-congested.

Machine Learning models help to make traffic predictions. Besides this, when we book a cab, with just one click, we get the fare charges for the trip. The fantastic feature has become a reality through ML algorithms.

Product Recommendations:

We often get product recommendations from Amazon, Flipkart, etc., while surfing on google. These advertisements are done by companies using ML.

Search engines also use ML algorithms to facilitate us with product suggestions when we browse on google. Apart from this, Netflix also resorts to ML to give us movies and web series recommendations.

Self-driving cars:

Elon Musk has made it clear that self-driving cars, which we have only read in science fiction, are soon going to be a reality. Tesla has started directing its effort towards making self-driving cars.

Machine Learning algorithms will give instructions to a car in any situation to make it drive itself. The models will allow cars to collect data on their surroundings through cameras and evaluate their action.

What seems like a fantasy is soon materializing into reality.

Online Fraud detection:

Cybersecurity has become a crucial issue we are grappling with today. People often face the problem of fraudulent online transactions and breaches of their data.

To detect whether the transaction goes smoothly, ML provides a neural network. Also, it establishes a specific pattern after the transaction, which becomes an input for the next one.

The technology keeps a strict vigil on data intruders and fake ids.

Language translation:

Nowadays, the language barrier has been eradicated by technology as we can communicate to a person from any part of the country through Machine Learning. It converts our text into our native language.

The technology which works behind the picture is a sequence to sequence learning algorithm which translates the text into a known language.

Image recognition:

The infamous face detection lock-in smartphones these days are provided by ML. The algorithm helps us to recognize our faces through inbuilt sensors.

Image recognition is also used to recognize digital images, objects, places, etc. Moreover, it foretells the output of every pixel in the digital image.

Video surveillance:

Machine Learning has expanded to security applications also. ML technology in CCTV cameras can detect the uncanny behavior of individuals in public places. In this way, they can keep an eagle’s eye on a possible crime before it happens.

It helps to make the police officers and national security teams before any unusual happening.

Healthcare:

ML models analyze and interpret huge volumes of data to provide conspicuous results. The Healthcare sector uses ML to forecast which patients will be sick the earliest by analyzing their data.

It helps the doctors to interfere and take action as early as possible to save potential lives.

Credit Worthiness:

People often get loans on their credit score these days. But a new credit cardholder has no credit card history, therefore, no credit score. So, credit card companies use ML algorithms to come at the metric of credit score.

The algorithm takes financial habits, financial goals, and current financial health into consideration to arrive at a credit score.

Social Media:

Last but not least, you often have noticed that we often get the content we spend the lion’s share of time on our feed, stories, etc. Behind the curtains, it’s the Machine Learning algorithm that works.

Social Media giants use ML to keep track of all our activities on social media. ML helps them present us with our likable content to make us spend more time on social media, owing to which they make exorbitant amounts of money.

Conclusion:

To recapitulate, We are witnessing the alluring features in our mundane technology use, which are all a product of Machine Learning and its models.

The subtle changes it is making gradually in different applications astound us with the amazing features the apps provide.

ML gives the system a freehand to adapt to the situations independently without being programmed every time. It means that the sky’s the limit. The technological devices have their own will to create something fresh.

All the new technologies coming in this age are equipped with ML models to create a first-hand customer experience. We can not help but wonder that like self-driving cars, what is coming next.

The day is not far that we will see revolutionary developments in industries like healthcare, finance, etc., which would make our lives easier just through Machine learning and its easy interpretation of colossal amounts of data.