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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.” 

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How Elon Musk’s plan to slash government agencies and regulation may benefit his empire

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How Elon Musk’s plan to slash government agencies and regulation may benefit his empire

Elon Musk’s business empire is sprawling. It includes electric vehicle maker Tesla, social media company X, artificial intelligence startup xAI, computer interface company Neuralink, tunneling venture Boring Company and aerospace firm SpaceX. 

Some of his ventures already benefit tremendously from federal contracts. SpaceX has received more than $19 billion from contracts with the federal government, according to research from FedScout. Under a second Trump presidency, more lucrative contracts could come its way. SpaceX is on track to take in billions of dollars annually from prime contracts with the federal government for years to come, according to FedScout CEO Geoff Orazem.

Musk, who has frequently blamed the government for stifling innovation, could also push for less regulation of his businesses. Earlier this month, Musk and former Republican presidential candidate Vivek Ramaswamy were tapped by Trump to lead a government efficiency group called the Department of Government Efficiency, or DOGE.

In a recent commentary piece in the Wall Street Journal, Musk and Ramaswamy wrote that DOGE will “pursue three major kinds of reform: regulatory rescissions, administrative reductions and cost savings.” They went on to say that many existing federal regulations were never passed by Congress and should therefore be nullified, which President-elect Trump could accomplish through executive action. Musk and Ramaswamy also championed the large-scale auditing of agencies, calling out the Pentagon for failing its seventh consecutive audit. 

“The number one way Elon Musk and his companies would benefit from a Trump administration is through deregulation and defanging, you know, giving fewer resources to federal agencies tasked with oversight of him and his businesses,” says CNBC technology reporter Lora Kolodny.

To learn how else Elon Musk and his companies may benefit from having the ear of the president-elect watch the video.

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Why X’s new terms of service are driving some users to leave Elon Musk’s platform

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Why X's new terms of service are driving some users to leave Elon Musk's platform

Elon Musk attends the America First Policy Institute gala at Mar-A-Lago in Palm Beach, Florida, Nov. 14, 2024.

Carlos Barria | Reuters

X’s new terms of service, which took effect Nov. 15, are driving some users off Elon Musk’s microblogging platform. 

The new terms include expansive permissions requiring users to allow the company to use their data to train X’s artificial intelligence models while also making users liable for as much as $15,000 in damages if they use the platform too much. 

The terms are prompting some longtime users of the service, both celebrities and everyday people, to post that they are taking their content to other platforms. 

“With the recent and upcoming changes to the terms of service — and the return of volatile figures — I find myself at a crossroads, facing a direction I can no longer fully support,” actress Gabrielle Union posted on X the same day the new terms took effect, while announcing she would be leaving the platform.

“I’m going to start winding down my Twitter account,” a user with the handle @mplsFietser said in a post. “The changes to the terms of service are the final nail in the coffin for me.”

It’s unclear just how many users have left X due specifically to the company’s new terms of service, but since the start of November, many social media users have flocked to Bluesky, a microblogging startup whose origins stem from Twitter, the former name for X. Some users with new Bluesky accounts have posted that they moved to the service due to Musk and his support for President-elect Donald Trump.

Bluesky’s U.S. mobile app downloads have skyrocketed 651% since the start of November, according to estimates from Sensor Tower. In the same period, X and Meta’s Threads are up 20% and 42%, respectively. 

X and Threads have much larger monthly user bases. Although Musk said in May that X has 600 million monthly users, market intelligence firm Sensor Tower estimates X had 318 million monthly users as of October. That same month, Meta said Threads had nearly 275 million monthly users. Bluesky told CNBC on Thursday it had reached 21 million total users this week.

Here are some of the noteworthy changes in X’s new service terms and how they compare with those of rivals Bluesky and Threads.

Artificial intelligence training

X has come under heightened scrutiny because of its new terms, which say that any content on the service can be used royalty-free to train the company’s artificial intelligence large language models, including its Grok chatbot.

“You agree that this license includes the right for us to (i) provide, promote, and improve the Services, including, for example, for use with and training of our machine learning and artificial intelligence models, whether generative or another type,” X’s terms say.

Additionally, any “user interactions, inputs and results” shared with Grok can be used for what it calls “training and fine-tuning purposes,” according to the Grok section of the X app and website. This specific function, though, can be turned off manually. 

X’s terms do not specify whether users’ private messages can be used to train its AI models, and the company did not respond to a request for comment.

“You should only provide Content that you are comfortable sharing with others,” read a portion of X’s terms of service agreement.

Though X’s new terms may be expansive, Meta’s policies aren’t that different. 

The maker of Threads uses “information shared on Meta’s Products and services” to get its training data, according to the company’s Privacy Center. This includes “posts or photos and their captions.” There is also no direct way for users outside of the European Union to opt out of Meta’s AI training. Meta keeps training data “for as long as we need it on a case-by-case basis to ensure an AI model is operating appropriately, safely and efficiently,” according to its Privacy Center. 

Under Meta’s policy, private messages with friends or family aren’t used to train AI unless one of the users in a chat chooses to share it with the models, which can include Meta AI and AI Studio.

Bluesky, which has seen a user growth surge since Election Day, doesn’t do any generative AI training. 

“We do not use any of your content to train generative AI, and have no intention of doing so,” Bluesky said in a post on its platform Friday, confirming the same to CNBC as well.

Liquidated damages

Bluesky CEO: Our platform is 'radically different' from anything else in social media

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The Pentagon’s battle inside the U.S. for control of a new Cyber Force

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The Pentagon's battle inside the U.S. for control of a new Cyber Force

A recent Chinese cyber-espionage attack inside the nation’s major telecom networks that may have reached as high as the communications of President-elect Donald Trump and Vice President-elect J.D. Vance was designated this week by one U.S. senator as “far and away the most serious telecom hack in our history.”

The U.S. has yet to figure out the full scope of what China accomplished, and whether or not its spies are still inside U.S. communication networks.

“The barn door is still wide open, or mostly open,” Senator Mark Warner of Virginia and chairman of the Senate Intelligence Committee told the New York Times on Thursday.

The revelations highlight the rising cyberthreats tied to geopolitics and nation-state actor rivals of the U.S., but inside the federal government, there’s disagreement on how to fight back, with some advocates calling for the creation of an independent federal U.S. Cyber Force. In September, the Department of Defense formally appealed to Congress, urging lawmakers to reject that approach.

Among one of the most prominent voices advocating for the new branch is the Foundation for Defense of Democracies, a national security think tank, but the issue extends far beyond any single group. In June, defense committees in both the House and Senate approved measures calling for independent evaluations of the feasibility to create a separate cyber branch, as part of the annual defense policy deliberations.

Drawing on insights from more than 75 active-duty and retired military officers experienced in cyber operations, the FDD’s 40-page report highlights what it says are chronic structural issues within the U.S. Cyber Command (CYBERCOM), including fragmented recruitment and training practices across the Army, Navy, Air Force, and Marines.

“America’s cyber force generation system is clearly broken,” the FDD wrote, citing comments made in 2023 by then-leader of U.S. Cyber Command, Army General Paul Nakasone, who took over the role in 2018 and described current U.S. military cyber organization as unsustainable: “All options are on the table, except the status quo,” Nakasone had said.

Concern with Congress and a changing White House

The FDD analysis points to “deep concerns” that have existed within Congress for a decade — among members of both parties — about the military being able to staff up to successfully defend cyberspace. Talent shortages, inconsistent training, and misaligned missions, are undermining CYBERCOM’s capacity to respond effectively to complex cyber threats, it says. Creating a dedicated branch, proponents argue, would better position the U.S. in cyberspace. The Pentagon, however, warns that such a move could disrupt coordination, increase fragmentation, and ultimately weaken U.S. cyber readiness.

As the Pentagon doubles down on its resistance to establishment of a separate U.S. Cyber Force, the incoming Trump administration could play a significant role in shaping whether America leans toward a centralized cyber strategy or reinforces the current integrated framework that emphasizes cross-branch coordination.

Known for his assertive national security measures, Trump’s 2018 National Cyber Strategy emphasized embedding cyber capabilities across all elements of national power and focusing on cross-departmental coordination and public-private partnerships rather than creating a standalone cyber entity. At that time, the Trump’s administration emphasized centralizing civilian cybersecurity efforts under the Department of Homeland Security while tasking the Department of Defense with addressing more complex, defense-specific cyber threats. Trump’s pick for Secretary of Homeland Security, South Dakota Governor Kristi Noem, has talked up her, and her state’s, focus on cybersecurity.

Former Trump officials believe that a second Trump administration will take an aggressive stance on national security, fill gaps at the Energy Department, and reduce regulatory burdens on the private sector. They anticipate a stronger focus on offensive cyber operations, tailored threat vulnerability protection, and greater coordination between state and local governments. Changes will be coming at the top of the Cybersecurity and Infrastructure Security Agency, which was created during Trump’s first term and where current director Jen Easterly has announced she will leave once Trump is inaugurated.

Cyber Command 2.0 and the U.S. military

John Cohen, executive director of the Program for Countering Hybrid Threats at the Center for Internet Security, is among those who share the Pentagon’s concerns. “We can no longer afford to operate in stovepipes,” Cohen said, warning that a separate cyber branch could worsen existing silos and further isolate cyber operations from other critical military efforts.

Cohen emphasized that adversaries like China and Russia employ cyber tactics as part of broader, integrated strategies that include economic, physical, and psychological components. To counter such threats, he argued, the U.S. needs a cohesive approach across its military branches. “Confronting that requires our military to adapt to the changing battlespace in a consistent way,” he said.

In 2018, CYBERCOM certified its Cyber Mission Force teams as fully staffed, but concerns have been expressed by the FDD and others that personnel were shifted between teams to meet staffing goals — a move they say masked deeper structural problems. Nakasone has called for a CYBERCOM 2.0, saying in comments early this year “How do we think about training differently? How do we think about personnel differently?” and adding that a major issue has been the approach to military staffing within the command.

Austin Berglas, a former head of the FBI’s cyber program in New York who worked on consolidation efforts inside the Bureau, believes a separate cyber force could enhance U.S. capabilities by centralizing resources and priorities. “When I first took over the [FBI] cyber program … the assets were scattered,” said Berglas, who is now the global head of professional services at supply chain cyber defense company BlueVoyant. Centralization brought focus and efficiency to the FBI’s cyber efforts, he said, and it’s a model he believes would benefit the military’s cyber efforts as well. “Cyber is a different beast,” Berglas said, emphasizing the need for specialized training, advancement, and resource allocation that isn’t diluted by competing military priorities.

Berglas also pointed to the ongoing “cyber arms race” with adversaries like China, Russia, Iran, and North Korea. He warned that without a dedicated force, the U.S. risks falling behind as these nations expand their offensive cyber capabilities and exploit vulnerabilities across critical infrastructure.

Nakasone said in his comments earlier this year that a lot has changed since 2013 when U.S. Cyber Command began building out its Cyber Mission Force to combat issues like counterterrorism and financial cybercrime coming from Iran. “Completely different world in which we live in today,” he said, citing the threats from China and Russia.

Brandon Wales, a former executive director of the CISA, said there is the need to bolster U.S. cyber capabilities, but he cautions against major structural changes during a period of heightened global threats.

“A reorganization of this scale is obviously going to be disruptive and will take time,” said Wales, who is now vice president of cybersecurity strategy at SentinelOne.

He cited China’s preparations for a potential conflict over Taiwan as a reason the U.S. military needs to maintain readiness. Rather than creating a new branch, Wales supports initiatives like Cyber Command 2.0 and its aim to enhance coordination and capabilities within the existing structure. “Large reorganizations should always be the last resort because of how disruptive they are,” he said.

Wales says it’s important to ensure any structural changes do not undermine integration across military branches and recognize that coordination across existing branches is critical to addressing the complex, multidomain threats posed by U.S. adversaries. “You should not always assume that centralization solves all of your problems,” he said. “We need to enhance our capabilities, both defensively and offensively. This isn’t about one solution; it’s about ensuring we can quickly see, stop, disrupt, and prevent threats from hitting our critical infrastructure and systems,” he added.

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