How Deep Learning Algorithms are Transforming Our Everyday Lives?

Deep learning and AI have become the latest trend in the tech industry. But what’s their impact? And how are they influencing our day-to-day lives? 

Deep learning applications are responsible for many changes in the world today, a majority of which have far-reaching implications on the way we live in the world. In this article, we’ll be discussing different deep learning algorithms and their use cases. You’d be surprised to see some of those uses.

Many companies now rely on deep learning and AI to provide quality services to their customers. Here are some ways how:

Real-Life Use Cases of Deep Learning Algorithms

App Store Recommendations

Both Google’s Play Store and Apple’s App Store use deep learning techniques for giving download recommendations to its users. They track user activity, see which apps the user installs, and which apps the user neglects. According to the data received, they recommend the apps to the user.

While it might seem simple, there are a lot of factors at play here. These algorithms also consider the recent trends, such as the apps which get the most downloads. They also compare the user’s activity with other similar users and recommend the apps accordingly. That’s why their recommendations are so accurate.

Suppose, you installed an English-learning app. The algorithms will now start recommending you other learning apps as well as apps related to English. Due to these algorithms, every person’s Play Store (or App Store) is unique to them. It’s personalized and offers a fantastic user experience.

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Dynamic Pricing

Ride-hailing services such as Uber and Ola have plenty of things in common. One of them is their dynamic pricing. Dynamic pricing is another excellent result of deep learning. They use it to calculate the price of a particular ride, which depends on a lot of factors such as distance, demand, etc.

You must’ve experienced this pricing first-hand while booking a cab. Try booking a taxi during free-time when there’s less traffic then compare the prices with ones during rush hour.

They rely on this pricing model to make sure that the cabs remain affordable while generating a profit for the company. Dynamic pricing isn’t limited to Uber or Ola. Many other industries, such as hospitality and travel, are also using these techniques.

Google Maps

Google Maps is an excellent example of using machine learning and AI to deliver quality results. It uses deep learning algorithms for calculating the time a particular trip will take.

It is constantly improving. Due to its deep learning implementations, its calculations of every trip’s estimated time requirement are becoming more accurate.

It can calculate the distance, consider the traffic in the route, suggest different ways, and even give directions to the user. Google Maps determines the perfect route for the user by considering a lot of factors. It uses numerous deep learning algorithms for that purpose.

Another feature of Google Maps, which uses machine learning algorithms is its ‘Explore Nearby’ option. It lets you find nearby ATMs, hospitals, spas, etc. It must go through a lot of data to produce such accurate results.

AI Assistants (Siri, Alexa, etc.)

Google Assistant, Siri, and other AI assistants are a great example of artificial neural networks. They use machine learning algorithms for speech recognition.

Through speech recognition, these AI-powered assistants can recognize your commands and act accordingly. So, if you’d tell your Google Assistant to play a specific track on YouTube, it would.

These assistants also use natural language processing (NLP) to enhance their performance with time. You must’ve noticed how your experience with Siri or Alexa must’ve improved over time.

Google had created the Google Brain project for the sole purpose of using deep learning AI better. And their Google Assistant is a product of the same. These assistants can also use other interesting deep learning algorithms for a variety of tasks, including text-to-speech, image recognition, etc.

Google’s Search Engine

Google’s search engine is the most popular and the most significant example of deep learning algorithms and their application. It’s vast, accurate, and powerful. Although we can’t pinpoint which deep learning algorithms they use, we’re confident that the number is vast. Moreover, Google has some of its algorithms that enhance the searching experience for its users too.

For example, its most potent tool Google uses is PageRank. Google uses this algorithm for ranking web pages according to its relevance. Google has enhanced its algorithms substantially in the past years. In fact, in the year 2018 alone, Google rolled out 3,234 updates for its search engine algorithm.

This means they released around nine updates every day. Its search algorithms are now far more complex and diverse. However, they are also a great example of how deep learning has become a vital part of our day-to-day lives.

Facebook Recommendations

Have you ever wondered how Facebook can recommend to you people who you know in life? Like all the examples we’ve discussed in this article, Facebook also uses deep learning algorithms for this task. They take loads of data from each use and use it to refine their experience.

That’s why you begin to more of those cat videos you like before and the blazers you had clicked on once. Not only Facebook but other social media platforms also use these algorithms for optimizing your feed. For example, for the ‘People you may know’ section, Facebook’s algorithms check your profile and then find other profiles that are similar to yours. The criteria could be very different based on each profile.

After checking other profiles, it recommends the profiles which match yours the most. They use the Recommender System Algorithm for this task.

Deep Learning Algorithms are Everywhere

There are countless examples of deep learning’s applications. From social media platforms to search engines, they are everywhere. The uses of deep learning algorithms are also expanding. Apart from the applications we mentioned above, deep learning also finds uses in image enhancements, logistics, finance, and security. Know more about Deep Learning and Dive into the World of Machine Learning!

Industries are finding new ways to implement this technology for facilitating growth and improving user experience.  

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