How Spotify uses AI and ML to stand out in the crowd of music streaming services in the market?
FILE PHOTO: A smartphone is seen in front of a screen projection of Spotify logo, in this picture illustration taken April 1, 2018. REUTERS/Dado Ruvic/Illustration/File Photo

How Spotify uses AI and ML to stand out in the crowd of music streaming services in the market?

What is AI?

AI is a branch of computer science that focuses on replicating human intelligence and their thinking capacity and decision making power. AI has made it possible for the machines to learn from the experiences according to the provided data and information about the real world and think like a real brain. Humans are the most intelligent creature we know so far.

Humans can communicate with their languages see with their eyes and perceive things accordingly and process them for a conclusive result. Humans can move around and do gestures understand the environment better in their own way. Humans observe the things going on as a pattern or sequence of things and then make a conclusion out of it.

We as humans can remember the past and predict the future and they possess decisive powers and decision-making capabilities which makes them more intelligent than any other creature in this world we know.

Let me elaborate Artificial Intelligence a little bit in the context of human beings.There is there are two main ways by which artificial intelligence works one is is symbolic learning and other one is machine learning.

The way we as humans learn from our experiences and sequence of activities and incidents and by identifying that pattern we can also predict and make assumptions about what is going to happen in future and replicating this feature of a human being in machines are what we call as Machine learning.for this we need to feed lots of data to our machine for it to understand and learn from the pattern and experiences that the information we gave is following.

We can plot and make a graph out of of the given data to observe the trend or pattern that it is following to make predictions but the machines are so advanced that they can learn from the same pattern in so many different dimensions and in much less time than human beings and make predictions trends which we as humans many times won’t be possible to predict.

Artificial intelligence under two broad categories.

1. Narrow AI

2. Artificial General Intelligence (AGI)

Narrow AI is a type of artificial intelligence that remains in a specific context but more focused on a specific task l. The machines are very intelligent and good at that specific job and have intelligence like human beings. It is nowadays being used in chatbots and assistants.

In artificial general Intelligence, the machines are much more like human beings that they can apply the technologies and their intelligence as we humans do. Sounds amazing so far, right?

Applications of AI

Artificial intelligence is much more interesting than one could ever think of but every technology comes with the advantage and a drawback too.

Artificial intelligence nowadays is being used as a new tool for businesses to provide the customers more user-friendly and much more in hands experience than ever.

Applications of AI now a day has really grown-up and expanded in the business world. Machine learning algorithms in Businesses are being used for data analytics and management to serve their customers better and most efficiently, and it is way more reliable.

AI is being used in manufacturing as the programmed robots can perform multiple tasks at one time and do the job much quicker than human workers.

AI and machine learning are two such technologies that are widely being used in the security world as well. Organisations are using machine learning to identify malicious or suspicious activities going on and indicate threats. And again this all is done in a much quicker time than an average human being can do. It is much more reliable and gives a lot of time to counteract.

How big is the pool of songs we now have and how it is a challenge for the music streaming services?

Music has become a huge part of our lives ever since it entered our lives. Almost every age group is listening to some or the other kind of music. There are so many different kinds of songs that are available out there. Considering each of us at least likes to listen to one song and we are such a huge population that makes it millions of songs altogether.

We all have different tastes and preferences which makes us all apart from each other. Music keeps on changing so quickly like everything new comes up in an unexpected time and we all start liking it. So there is a high demand for a service which provides us with all the songs at one place and makes you aware of what the music industry has to offer.

Who is winning the market in the pool of these music streaming services?

There are many music services running around the world but the most famous and the biggest on-demand music service across the globe is Spotify.

We as a user we all like to listen to what we prefer not just any random song that is available and in this huge volume of music genres and millions of songs. It gets very hard to discover what we like in a bunch of different categories and genres, where you have too much to choose from.

Spotify was launched in 2008 and now has over 159 million+ active users across the globe. In the market of music streaming services, Spotify stands out as it is more user-friendly and helps the users to discover music based on their preferences and give them a really personalized experience. For all this Spotify uses machine learning as a strategy to attract customers and provide the best of experience out of all the music streaming services available.

How Spotify uses Artificial Intelligence and Machine Learning to build up user experience?

Spotify uses artificial intelligence, machine learning and data science to improve their user’s experience and provides them with personalised playlists every week. Spotify is a data-driven company and the most important key for their customer satisfaction is the data they use and how efficiently they use it for recommendations.

Spotify’s home screen uses BaRT. BaRT is a machine learning algorithm that Spotify uses for recommending tracks and a personalized homepage based on the others the user has listened to.

If a specific amount of time if you listen to a song, let’s say 30 seconds then this algorithm considers it into your interests. BaRT not only looks at your interests of songs, artists or albums, but it also looks at the device being used and the timings too to make the system aware of the user’s complete account activity.

Why Spotify recommendations are the main attraction of users?

Discover Weekly data flow chart :source

One of the most trending features of Spotify is “Discover weekly”. It offers you a list of 30 tracks every week which according to their ML engines is best for you based on your search history, browsing history and preferences.

And these recommendations keep on getting better every time making the users reach out for Spotify instead of other services. Discover weekly tracklist is made by the combination of three models. It tries to collect as much data as it is required to predict the recommendations for a particular user.

These three models are what Spotify uses for The Discover weekly playlist

1.collaborative filtering: This collaborative filtering algorithm looks up on the personalized created playlists by the users and looks at their personal choice and the number of times a user is reaching out for a song, artist or album. And after collecting all this data it provides the user with some personalized recommendations based on others that they have surfed.

2. Natural language processing (NLP): Spotify’s AI tracks for the description about a specific artist or a song on the internet. It looks for blog posts, articles based on the kind of music and the language, and tries to categorise under some description or keyword associated with that song to identify a particular song’s description for a better recommendation.

3. Convolutional neural networks (CNN): This model is is configured by Spotify for not so popular audio files that often gets un noticed by NLP. In this model each song is converted in a waveform and is processed and is then categorised accordingly under certain parameters known as tempo in beats per minute, loudness and many more things that the users prefer.

 This way Spotify provides a user with customised playlist every week, totally based on their recommendations they predicted using Machine learning models.


Spotify is not only famous amongst the users but also it serves as a platform for newbies in the music industry. And that’s how Spotify became one of the world’s biggest and the most user-friendly on-demand music streaming service.

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