Tag Archives: NLP

How AI Revolutionizes Music Streaming


In 2020, worldwide music streaming revenue hit 11.4 billion dollars, a 2800% growth over the course of a decade. Three hundred forty-one million paid online streaming subscribers get their music from top services like Apple Music, Spotify, and Tidal. The competition for listeners is fierce. Each company looks to leverage every advantage they can in pursuit of higher market share.

Like all major tech conglomerates, music streaming services collect an exceptional amount of user data through their platforms and are creating elaborate AI algorithms designed to improve user experience on a number of levels. Spotify has emerged as the largest on-demand music service active today and bolstered its success through the innovative use of AI.

Here are the top ways in which AI has changed music streaming:


AI has the ability to sift through a plenitude of implicit consumer data, including:

  • Song preferences
  • Keyword preferences
  • Playlist data
  • Geographic location of listeners
  • Most used devices

AI algorithms can analyze user trends and identify users with similar tastes. For example, if AI deduces that User 1 and User 2 have similar tastes, then it can infer that songs User 1 has liked will also be enjoyed by User 2. Spotify’s algorithms will leverage this information to provide recommendations for User 2 based on what User 1 likes, but User 2 has yet to hear.

The result is not only improved recommendations, but greater exposure for artists that otherwise may not have been organically found by User 2.


Natural Language Processing is a burgeoning field in AI. Previously in our blog, we covered GPT-3, the latest Natural Language Processing (NLP) technology developed by OpenAI. Music streaming services are well-versed in the technology and leverage it in a variety of ways to enhance UI.


Algorithms scan a track’s metadata, in addition to blog posts, discussions, and news articles about artists or songs on the internet to determine connections. When artists/songs are mentioned alongside artists/songs the user likes, algorithms make connections that fuel future recommendations.

GPT-3 is not perfect; its ability to track sentiments lacks nuance. As Sonos Radio general manager Ryan Taylor recently said to Fortune Magazine: “The truth is music is entirely subjective… There’s a reason why you listen to Anderson .Paak instead of a song that sounds exactly like Anderson .Paak.”

As NLP technology evolves and algorithms extend their grasp of the nuances of language, so will the recommendations provided to you by music streaming services.



AI can study audio models to categorize songs exclusively based on their waveforms. This scientific, binary approach to analyzing creative work enables streaming services to categorize songs and create recommendations regardless of the amount of coverage a song or artist has received.


Artist payment of royalties on streaming services poses its own challenges, problems, and short-comings. Royalties are deduced from trillions of data points. Luckily, blockchain is helping to facilitate a smoother artist’s payment process. Blockchain technology can not only make the process more transparent but also more efficient. Spotify recently acquired blockchain company Mediachain Labs, which will, many pundits are saying, change royalty payments in streaming forever.


While AI has vastly improved streaming ability to keep their subscribers compelled, a long road of evolution lies ahead before it can come to a deep understanding of what motivates our musical tastes and interests. Today’s NLP capabilities provided by GPT-3 will probably become fairly archaic within three years as the technology is pushed further. One thing is clear: as streaming companies amass decades’ worth of user data, they won’t hesitate to leverage it in their pursuit of market dominance.

How Artificial Intelligence Has Revolutionized Digital Marketing

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Last week, we explored the real power of Artificial Intelligence. AI’s ability to comprehend complex data sets and form patterns enables infinite new possibilities for personalization through the analysis of digital activity. Within the digital marketing industry, AI has been nothing short of a revolution. Here are the top ways in which Artificial Intelligence is impacting digital marketing:


Natural Language Processing (NLP) is a field that focuses on the ability for computers to process human language to the point where it can generate replies based on inferred meaning. Machine Learning has sharply increased the ability for machines to generate sentiments designed to not only seem as if they were written by a human, but that are optimized based on data to elicit a specific action or emotional response.

Digital marketers fret over when to reach out, what to say, and what channel is most appropriate. AI’s NLP abilities mean that the guessing game has come to an end. AI can analyze big data to decide upon what the best method, channel, and timing will be in order to foster growth, engagement, and sales.

NLP as a trend is on the rise. Angel.co recently valued the average NLP start-up at $4.8 million.


In days of yore, Google search rankings were determined by human-created metrics and social media feeds showed posts in chronological order. Now, programs like RankBrain are vital to deciding the criteria for Google’s search rankings while Facebook’s DeepText creates your newsfeed.


Artificial Intelligence drives programmatic purchasing, which is when AI determines who to show ads to and when to show them. Removing the burden of purchasing analysis leaves marketers room to focus on crafting powerful messages.

NLP enables AI to understand (through numbers and sentiment analysis) the abstract criterion of “context” and to match individuals with ads based on context to maximize the chances of generating a click or purchase.

According to Ad Exchange, programmatic purchasing accounted for 67% of all global display ads in 2017.


Perhaps the most anxiety-inducing example of Artificial Intelligence impacts not only digital marketing, but politics.

Psychographic profiles are data-driven psychological profiles of consumers designed to shed light on why they do what they do. Firms like CaliberMind and Cambridge Analytica have turned this into a multi-million dollar industry. Insights gleaned from psychographic profiles are intended to optimize the messaging of both political and commercial ads to induce a desired action from the viewer.

Cambridge Analytica has taken credit for influencing both the Brexit vote and the 2016 presidential election; however, many (including the New York Times) cast a shadow of doubt over the extent of their impact. Regardless, as long as there are insights to be gleaned from digital activity, psychographic profiles will only continue to develop.


That’s right, AI has become adept enough to design websites based on data. Wix ADI created this personal trainer’s website and Grid has been designing websites since 2014.


Every application of artificial intelligence in digital marketing is relatively new. While these applications are increasing in popularity, expect them to also increase in efficiency and effectiveness as technology continuously advances.