How Spotify AI plans to know what’s going on inside your head, and find the right track for it

Published

1 year ago

April 14, 2024

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With about 100 million tracks available and over 600 million subscribers, helping listeners find the music they will love has become a navigational challenge for Spotify. It’s the promise of personalization and meaningful recommendations that will give the vast catalog more meaning, and that is central to Spotify’s mission.

The streaming audio giant’s suite of recommendation tools has grown over the years: Spotify Home feed, Discover Weekly , Blend, Daylist, and Made for You Mixes. And in recent years, there have been signs that it is working. According to data released by Spotify at its 2022 Investor Day, artist discoveries every month on Spotify had reached 22 billion, up from 10 billion in 2018, “and we’re nowhere near done,” the company stated at that time.

Over the past decade or more, Spotify has been investing in AI and, in particular, in machine learning. Its recently launched AI DJ may be its biggest bet yet that technology will allow subscribers to better personalize listening sessions and discover new music. The AI DJ mimics the vibe of radio by announcing the names of songs and lead-in to tracks, something aimed in part to help ease listeners into extending out of their comfort zones. An existing pain point for AI algorithms — which can be excellent at giving listeners what it knows they already like — is anticipating when you want to break out of that comfort zone.

The AI DJ combines personalization technology, generative AI, and a dynamic AI voice, and listeners can tap the DJ button when they want to hear something new, and something less-directly-derived from their established likes. Behind the dulcet tones of an AI DJ there are people, tech experts and music experts, who aim to improve the recommendation capacity of Spotify’s tools. The company has hundreds of music editors and experts across the globe. A Spotify spokesperson said the generative AI tool allows the human experts to “scale their innate knowledge in ways never before possible.”

The data on a particular song or artist captures a few attributes: particular musical features, and which song or artist it has been typically paired with among the millions of listening sessions whose data the AI algorithm can access. Gathering information about the song is a fairly easy process, including release year, genre, and mood — from happy to danceable or melancholic. Various musical attributes, such as tempo, key, and instrumentation, are also identified. Combining this data associated with millions of listening sessions and other users’ preferences helps to generate new recommendations, and makes the leap possible from aggregated data to individual listener assumptions.

In its simplest formulation, “Users who liked Y also liked Z. We know you like Y, so you might like Z,” is how an AI finds matches. And Spotify says it’s working. “Since launching DJ, we’ve found that when DJ listeners hear commentary alongside personal music recommendations, they’re more willing to try something new (or listen to a song they may have otherwise skipped),” the spokesperson said.

If successful, it’s not just listeners that get relief from a pain point. A great discovery tool is as beneficial to the artists seeking to build connections with new fans.

Julie Knibbe, founder & CEO of Music Tomorrow — which aims to help artists connect with more listeners by understanding how algorithms work and how to better work with them — says everyone is trying to figure out how to balance familiarity and novelty in a meaningful way, and everyone is leaning on AI algorithms to help make this possible. Be she says the balance between discovering new music and staying with established patterns is a central unresolved issue for all involved, from Spotify to listeners and the artists.

“Any AI is only good at what you tell them to do,” Knibbe said. “These recommender systems have been around for over a decade and they’ve become very good at predicting what you will like. What they can’t do is know what’s in your head, specifically when you want to venture out into a new musical terrain or category.”

Spotify’s Daylist is an attempt to use generative AI to take into account established tastes, but also the varying contexts that can shape and reshape a listeners’ tastes across the course of a day, and make new recommendations that fit various moods, activities and vibes. Knibbe says it’s possible that improvements like these continue, and the AI gets better at finding the formula for how much novelty a listener wants, but she added, “the assumption that people want to discover new music all the time is not true.”

Most people still return, fairly happily, to familiar musical terrain and listening patterns.

“You have various profiles of listeners, curators, experts … people put different demands on the AI,” Knibbe said. “Experts are more difficult to surprise, but they aren’t the majority of listeners, who tend to be more casual,” and whose Spotify usage, she says, often amounts to creating a “comfortable background” to daily life.

Technology optimists often speak in terms of an era of “abundance.” With 100 million songs available, but many listeners preferring the same 100 songs a million times, it’s easy to understand why a new balance is being sought. But Ben Ratliff, a music critic and author of “Every Song Ever: Twenty Ways to Listen in an Age of Musical Plenty,” says algorithms are less solution to this problem than a further entrenching of it.

“Spotify is good at catching onto popular sensibilities and creating a soundtrack for them,” Ratliff said. “Its Sadgirl Starter Pack playlist, for instance, has a great name and about a million and a half likes. Unfortunately, under the banner of a gift, the SSP simplifies the oceanic complexity of young-adult depression into a small collection of dependably ‘yearny’ music acts, and makes hard clichés of music and sensibility form more quickly.”

Works of curation that are clearly made by actual people with actual preferences remain Ratliff’s preference. Even a good playlist, he says, might have been made without much intention and conscience, but just a developed sense of pattern recognition, “whether it’s patterns of obscurity or patterns of the broadly known,” he said.

Depending on the individual, AI may have equal chances of becoming either a utopian or dystopian solution within the 100-million track universe. Ratliff says most users should keep it more simple in their streaming music journeys. “As long as you realize that the app will never know you in the way you want to be known, and as long as you know what you’re looking for, or have some good prompts at the ready, you can find lots of great music on Spotify.”

Technology

Alibaba shares jump 19% on cloud unit acceleration, report of new AI chip

Published

1 day ago

September 1, 2025

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Alibaba shares jump 19% on cloud unit acceleration, report of new AI chip

Signage at the Alibaba Group Holding Ltd. headquarters in Hangzhou, China, on Thursday, Feb. 6, 2025.

Qilai Shen | Bloomberg | Getty Images

Alibaba‘s Hong Kong listed shares surged more than 19% on Monday as the Chinese tech giant’s cloud computing unit drove strong quarterly results, while details emerged over its new AI chip development.

It’s the highest level for the stock since March. Investors have backed the company’s improving performance in its key cloud unit and are content with the the tech giant’s investment into new areas — particularly in the so-called “instant commerce,” which has become incredibly competitive in China.

The Hong Kong rally builds on the momentum of Alibaba‘s earnings report of Friday, when the company’s New York-listed shares closed nearly 13% higher.

Alibaba last week week posted revenue for the June quarter of 247.65 billion Chinese yuan ($34.73 billion), marking a 2% year-on-year rise that nevertheless missed analyst expectations. On the upside, a 78% annual surge in net income came in ahead of forecasts.

The Chinese company’s cloud computing unit was a bright spot with revenue picking up by an annual 26%, which was a faster growth rate than seen in the previous quarter. Alibaba’s cloud growth has been accelerating over the last few quarter.

Like some of its Chinese and U.S. tech rivals, Alibaba has been investing in AI infrastructure and developing its own models, as well as selling AI services for its cloud computing unit. Investors see the division as key to the company’s efforts to monetize artificial intelligence, much like Microsoft or Google.

AI-related product revenue “maintained triple-digit year-over-year growth for the eighth consecutive quarter,” the company said Friday.

That same day, CNBC reported that Alibaba is developing a new AI chip, which also supported the share price rally on Monday.

Alibaba’s core e-commerce business has meanwhile been showing signs of revival, while the company has jumped into China’s cut-throat instant commerce space in China. This is a feature introduced this year on Taobao, one of Alibaba’s main Chinese e-commerce apps, which provides deliveries of certain products in China within an hour.

Investments in quick commerce weighed on Alibaba’s adjusted earnings for its e-commerce business. Investors have given the company some leeway to invest for now.

Technology

Global movement to protect kids online fuels a wave of AI safety tech

Published

3 days ago

August 30, 2025

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Global movement to protect kids online fuels a wave of AI safety tech

Spotify, Reddit and X have all implemented age assurance systems to prevent children from being exposed to inappropriate content.

STR | Nurphoto via Getty Images

The global online safety movement has paved the way for a number of artificial intelligence-powered products designed to keep kids away from potentially harmful things on the internet.

In the U.K., a new piece of legislation called the Online Safety Act imposes a duty of care on tech companies to protect children from age-inappropriate material, hate speech, bullying, fraud, and child sexual abuse material (CSAM). Companies can face fines as high as 10% of their global annual revenue for breaches.

Further afield, landmark regulations aimed at keeping kids safer online are swiftly making their way through the U.S. Congress. One bill, known as the Kids Online Safety Act, would make social media platforms liable for preventing their products from harming children — similar to the Online Safety Act in the U.K.

This push from regulators is increasingly causing something of a rethink at several major tech players. Pornhub and other online pornography giants are blocking all users from accessing their sites unless they go through an age verification system.

Porn sites haven’t been alone in taking action to verify users ages, though. Spotify, Reddit and X have all implemented age assurance systems to prevent children from being exposed to sexually explicit or inappropriate materials.

Such regulatory measures have been met with criticisms from the tech industry — not least due to concerns that they may infringe internet users’ privacy.

Digital ID tech flourishing

At the heart of all these age verification measures is one company: Yoti.

Yoti produces technology that captures selfies and uses artificial intelligence to verify someone’s age based on their facial features. The firm says its AI algorithm, which has been trained on millions of faces, can estimate the age of 13 to 24-year-olds within two years of accuracy.

The firm has previously partnered with the U.K.’s Post Office and is hoping to capitalize on the broader push for government-issued digital ID cards in the U.K. Yoti is not alone in the identity verification software space — other players include Entrust, Persona and iProov. However, the company has been the most prominent provider of age assurance services under the new U.K. regime.

“There is a race on for child safety technology and service providers to earn trust and confidence,” Pete Kenyon, a partner at law firm Cripps, told CNBC. “The new requirements have undoubtedly created a new marketplace and providers are scrambling to make their mark.”

Yet the rise of digital identification methods has also led to concerns over privacy infringements and possible data breaches.

“Substantial privacy issues arise with this technology being used,” said Kenyon. “Trust is key and will only be earned by the use of stringent and effective technical and governance procedures adopted in order to keep personal data safe.”

Child-safe smartphones

The wave of new tech emerging to prevent children from being exposed to online harms isn’t just limited to software.

Earlier this month, Finnish phone maker HMD Global launched a new smartphone called the Fusion X1, which uses AI to stop kids from filming or sharing nude content or viewing sexually explicit images from the camera, screen and across all apps.

The phone uses technology developed by SafeToNet, a British cybersecurity firm focused on child safety.

Finnish phone maker HMD Global’s new smartphone uses AI to prevent children from being exposed nude or sexually explicit images.

HMD Global

“We believe more needs to be done in this space,” James Robinson, vice president of family vertical at HMD, told CNBC. He stressed that HMD came up with the concept for children’s devices prior to the Online Safety Act entering into force, but noted it was “great to see the government taking greater steps.”

The release of HMD’s child-friendly phone follows heightened momentum in the “smartphone-free” movement, which encourages parents to avoid letting their children own a smartphone.

Going forward, the NSPCC’s Govender says that child safety will become a significant priority for digital behemoths such as Google and Meta.

The tech giants have for years been accused of worsening mental health in children and teens due to the rise of online bullying and social media addiction. They in return argue they’ve taken steps to address these issues through increased parental controls and privacy features.

“For years, tech giants have stood by while harmful and illegal content spread across their platforms, leaving young people exposed and vulnerable,” she told CNBC. “That era of neglect must end.”

Technology

‘AI may eat software,’ but several tech names just wrapped a huge week

Published

4 days ago

August 29, 2025

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'AI may eat software,' but several tech names just wrapped a huge week

A banner for Snowflake Inc. is displayed at the New York Stock Exchange to celebrate the company’s initial public offering on Sept. 16, 2020.

Brendan McDermid | Reuters

MongoDB’s stock just closed out its best week on record, leading a rally in enterprise technology companies that are seeing tailwinds from the artificial intelligence boom.

In addition to MongoDB’s 44% rally, Pure Storage soared 33%, its second-sharpest gain ever, while Snowflake jumped 21%. Autodesk rose 8.4%.

Since generative AI started taking off in late 2022 following the launch of OpenAI’s ChatGPT, the big winners have been Nvidia, for its graphics processing units, as well as the cloud vendors like Microsoft, Google and Oracle, and companies packaging and selling GPUs, such as Dell and Super Micro Computer.

For many cloud software vendors and other enterprise tech companies, Wall Street has been waiting to see if AI will be a boon to their business, or if it might displace it.

Quarterly results this week and commentary from company executives may have eased some of those concerns, showing that the financial benefits of AI are making their way downstream.

MongoDB CEO Dev Ittycheria told CNBC’s “Squawk Box” on Wednesday that enterprise rollouts of AI services are happening, but slowly.

“You start to see deployments of agents to automate back office, maybe automate sales and marketing, but it’s still not yet kind of full force in the enterprise,” Ittycheria said. “People want to see some wins before they deploy more investment.”

Revenue at MongoDB, which sells cloud database services, rose 24% from a year earlier to $591 million, sailing past the $556 million average analyst estimate, according to LSEG. Earnings also exceeded expectations, as did the company’s full-year forecast for profit and revenue.

MongoDB CEO Dev Ittycheria on Q2 results: The opportunity in front of us is massive

MongoDB said in its earnings report that it’s added more than 5,000 customers year-to-date, “the highest ever in the first half of the year.”

“We think that’s a good sign of future growth because a lot of these companies are AI native companies who are coming to MongoDB to run their business,” Ittycheria said.

Pure Storage enjoyed a record pop on Thursday, when the stock jumped 32% to an all-time high.

The data storage management vendor reported quarterly results that topped estimates and lifted its guidance for the year. But what’s exciting investors the most is early returns from Pure’s recent contract with Meta. Pure will help the social media company manage its massive storage needs efficiently with the demands of AI.

Pure said it started recognizing revenue from its Meta deployments in the second quarter, and finance chief Tarek Robbiati said on the earnings call that the company is seeing “increased interest from other hyperscalers” looking to replace their traditional storage with Pure’s technology.

‘Banger of a report’

Reports from MongoDB and Pure landed the same week that Nvidia announced quarterly earnings, and said revenue soared 56% from a year earlier, marking a ninth-straight quarter of growth in excess of 50%.

Nvidia has emerged as the world’s most-valuable company by selling advanced AI processors to all of the infrastructure providers and model developers.

While growth at Nvidia has slowed from its triple-digit rate in 2023 and 2024, it’s still expanding at a much faster pace than its megacap peers, indicating that there’s no end in sight when it comes to the expansive AI buildouts.

“It was a banger of a report,” said Brad Gerstner CEO of Altimeter Capital, in an interview with CNBC’s “Halftime Report” on Thursday. “This company is accelerating at scale.”