We are sure you weren’t waiting for us to tell you that machine learning is all around us. Machine learning and artificial intelligence (AI) may have been part of the Sci-Fi world up until a couple of years ago, but they have become integral parts of every tech-savvy person’s life. Kids are spending time at home with smart AI assistants at home. People are leveraging voice assistants, self-driving cars and smart assistants at every step of their lives.
A report by IBM shows that around 90% of the data in the existing world has come from interactions in the last two years only. While it is impossible for human beings to process or manage the huge volumes of data, machine learning can effectively help with the management and utilization of the data.
You may have heard people use the terms machine learning and AI interchangeably, but these are two separate technologies that can work together. You can think of machine learning as a subset of AI that can make computer algorithms by automatically upgrading them according to the patterns in the data without human intervention.
If you use social media, shopping applications and gaming applications, you must have come in contact with machine learning. Retail, mobile app development, healthcare, and robotics are only some of the many industries that have utilized machine learning to perfect their customer experience.
Here are ten instances from the everyday lives of our customers, who have experienced a touch of machine learning –
Upselling and cross-selling products
If you shop from Amazon (or an ecommerce giant), you may have noticed the range of different products the interface suggests during the purchase process. These are usually related to items you have purchased recently or have added to your wish-list.
Shopping online has become blissful thanks to product recommendations. The websites always seem to know what we need and at what time. It saves a lot of time and money (and makes a lot of money for the e-retailers!).
Product recommendation is a function of machine learning and it is one of the most common ways machine learning touches the lives of almost everyone in the digital age.
Have you ever used a GPS navigation while driving to and from work? A majority of smartphone users and voice assistant users have used GPS navigation services. When people use similar services their locations and speeds are saved at the central server that manages traffic. Later, the same data is used to map the traffic.
Ride-sharing applications like Uber and Lyft use traffic prediction dedicatedly for real-time traffic updates and route suggestions to divers. It helps with congestion analysis, traffic predictions and prediction of waiting time at each main crossing. The only challenge to traffic predictions right now is the limitation of cars equipped with GPS.
Virtual personal assistants
We have all heard of or used virtual personal assistants to find the nearest restaurant, movie timings or even recipes. Siri, Alexa, Cortana and Google Now are all examples of personal assistants who can yield information when the user asks a question. They can find pertinent information against questions like “what are my appointments for today?” or “what movies are playing at XYZ theater?” To find the answers, the assistant has to comb through a person’s calendar, phone apps, related Google queries and collect information, which would be impossible without machine learning.
Social media suggestions
Social media platforms have been using machine learning for quite a while now. From personalizing the news feed to finding appropriate ads based on recent queries; social media services have been trying to perfect machine learning algorithms for user benefits. Some of the products of machine learning you may have already come across include “people you may know”, “face recognition” and “similar pins” or “boards you may like” (Pinterest).
Malware filtering by email clients
Today, email clients use multiple spam filtering approaches that are fueled by machine learning. In 2019, over 325,000 malware threats were detected from programs with 90 to 98% similarity in their codes. Machine learning has become instrumental in predicting and preventing such malware attacks on PDAs and other electronic devices.
Online customer support on websites
Websites offer 24/7 customer support with the help of chatbots. They can answer your queries quite effectively by leveraging machine learning. It allows the chatbots to learn more about the customer’s navigation trends, buying habits and search trends. It helps them to serve the customers better with accurate answers.
Almost all the shopping mall, movie theater and brand stores you visit today are armed with a flurry of surveillance cameras. It is quite impossible to monitor these cameras manually.
Software engineers have been trying for years to train computers to do the surveillance job for humans. The AI fueled by machine learning can now track unnatural behavior that may precede a crime, including standing in front of a display for extended periods or napping on the benches inside stores.
Search engine result optimization
Google has almost perfected the art of offering the right search results to users. Depending on a user’s past searches, general search trends and other demographics, Google can present a list of search results that cater to your interest. Every time you browse a search list, the search engine keeps a tab on your responses. All future results will depend upon your reactions. Google uses machine learning to improve user experience every day.
Financial services and fraud detection
The applications of Machine learning has several benefits and online fraud detection is one of the most significant ones. Tracking monetary frauds has become considerably easier than five years ago thanks to machine learning and AI.
Payment platforms and vendors like PayPal are using machine learning to detect telltale signs of money laundering and other forms of fraud. When a company has to go through millions of transactions, having a foolproof method to tell the difference between legitimate and illegitimate transactions is imperative.
Not everyone has experienced this side of machine learning, but experts from different fields are working together to leverage machine learning in the fields of diagnosis of diseases. A combination of analytical tests, comparison of symptoms and analysis of the medical history of patients can help in the early detection of many tests before the primary symptoms even present themselves.
Machine learning is gradually becoming an indispensable part of our lives in many ways. Whether we want to reach office on time, or we want to find matching drapes to the bedcovers we bought for home; machine learning has been helping us out in every way possible without us realizing it. AI and machine learning are no longer parts of nebulous dreams of Sci-Fi authors. They have entered our homes holding the hands of smartphones, smart speakers, and wearable technologies.
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