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Rapper RBX has sued Spotify, alleging that the Swedish audio company has failed to stop the artificial inflation of music streams for artists like Drake and is hurting the revenue other rights holders receive through the platform.

RBX, whose real name is Eric Dwayne Collins, is seeking a class-action status and damages and restitution from Spotify. RBX, along with other rights holders, receive payment based on how often their music is streamed on Spotify, according to the lawsuit, filed in U.S. District Court in L.A. on Sunday.

Spotify pays rights holders a percentage of revenue based on the total streams attributed to them compared with total volume of streams for all songs, the lawsuit said.

The Long Beach-based rapper said that rights holders are losing money on Spotify because streams of some artists are being artificially inflated through bots powered by automated software, even though the use of such bots is prohibited on the platform, according to the lawsuit.

For example, the lawsuit notes that over a four-day period in 2024 there were at least 250,000 streams of Drake’s “No Face” song that appeared to originate in Turkey, but “were falsely geomapped through the coordinated use of VPNs to the United Kingdom in attempt to obscure their origins.”

Spotify knew or should have known “with reasonable diligence, that fraudulent activities were occurring on its platform,” states the lawsuit, describing the streamer’s policies to root out fraud as “window dressing.”

Spotify declined to comment on the pending litigation but said it “in no way benefits from the industry-wide challenge of artificial streaming.”

“We heavily invest in always-improving, best-in-class systems to combat it and safeguard artist payouts with strong protections like removing fake streams, withholding royalties, and charging penalties,” Spotify said in a statement.

Last year, a U.S. producer was accused of stealing $10 million from streaming services and Spotify said it was able to limit the theft on its platform to $60,000, touting it as evidence that its systems are working.

The platform is also making efforts to push back against AI-generated music that is made without artists’ permission. In September, Spotify announced it had removed more than 75 million AI-generated “spammy” music tracks from its platform over the last 12 months.

A representative for Drake did not immediately return a request for comment.

RBX is known for his work on Dr. Dre’s 1992 album “The Chronic” and Snoop Dogg’s 1993 album “Doggystyle.” He has multiple solo albums and has collaborated with artists including on Eminem’s “The Marshall Mathers LP” and Kris Kross’ “Da Bomb.” RBX is Snoop Dogg’s cousin.

Artificial intelligence continues to change the way that the entertainment industry operates, affecting everything from film and TV production to music. In the music industry, companies have sued AI startups, accusing the businesses of taking copyrighted music to train AI models.

At the same time, some music artists have embraced AI, using the technology to test bold ideas in music videos and in their songs.

Meta Platforms (META 0.52%) is no longer just a social media giant. It’s building one of the world’s largest AI infrastructures, recruiting elite talent, and embedding artificial intelligence into every layer of its ecosystem — from apps and ads to AR glasses.

While OpenAI and Google dominate the spotlight, Meta is quietly constructing the foundation to lead the next decade of AI development. Here’s how it plans to win.

Image source: Getty Images.

Building the backbone: A massive infrastructure bet

Meta’s AI ambitions rest on one of the biggest infrastructure buildouts in tech history. The company plans to spend $60 to 65 billion in capital expenditures this year, channeling much of that into data centers and custom AI hardware. By the end of 2025, Meta expects to operate over 1.3 million GPUs — a scale few companies can match.

This massive investment isn’t just brute force spending. It’s a strategic move to gain control. Meta is already testing its own AI chip, designed to reduce reliance on Nvidia and optimize training efficiency. Like Amazon‘s in-house silicon program, this initiative gives Meta tighter control over cost, performance, and innovation speed.

The company is also expanding a global network of data centers equipped with liquid cooling and energy-efficient designs. These facilities will train large language models such as LLaMA 3 and future generations while powering AI-driven features across Facebook, Instagram, and WhatsApp.

For Meta, infrastructure is more than a resource — it’s a moat. Every improvement in computing efficiency compounds across billions of users and trillions of interactions. That scale gives Meta a self-reinforcing infrastructure advantage.

Investing in people

Technology changes fast, but exceptional people adapt and shape the future. Meta understands that better than most. Over the past year, the company has aggressively recruited top AI researchers and engineers from DeepMind, OpenAI, and Anthropic.

In a bold move, Meta hired Alexandr Wang, the founder of Scale AI, to lead its new Superintelligence division. And that’s after investing $14.3 billion in Scale AI, the AI company Wang founded after dropping out of MIT. The hire signals Meta’s intent to compete not just in applied AI but in the broader race toward artificial general intelligence.

Zuckerberg’s philosophy is straightforward: world-class talent compounds like capital. So, it makes sense to spend heavily to acquire the best talent. This strategy is not new to Meta. Years ago, it paid a hefty sum ($16 billion) to acquire WhatsApp early on — mainly for the talent and technology.

While such a strategy does not guarantee an outcome, it has its advantages, particularly in securing the best talents — while eliminating a potential future competitor. That’s precisely what Meta did with its WhatsApp deal, and the learnings from the WhatsApp acquisition helped fuel the development of Messenger, Meta’s own messaging app.

Integration: Hardware, software, and ecosystem

Meta’s most significant edge lies in integration — uniting infrastructure, talent, and products under one ecosystem. The company’s open-source large language model, LLaMA, already powers its AI-driven functions such as real-time translation and intelligent assistants across Messenger and WhatsApp. Each deployment brings new data, which strengthens the next generation of models.

But Meta isn’t stopping at software. Its Reality Labs division is bringing AI into the physical world through devices like the Ray-Ban Meta smart glasses, which include conversational assistance, translation, and image recognition. Zuckerberg envisions a future where AI becomes ambient — invisible, intuitive, and always available.

Over time, Meta’s ecosystem could span everything from LLaMA models running on powerful clusters to lightweight AI running directly on AR glasses or smartphones. With more than 3 billion users, Meta holds an enormous testing ground for refining these systems at scale.

What does it mean for investors?

Meta’s AI strategy isn’t about racing to release the flashiest model. It’s about building the foundation of the next computing era. By investing heavily in hardware, empowering world-class talent, and integrating AI into every layer of its ecosystem, Meta aims to become the operating system of the AI age.

Execution remains the real test. Building trillion-parameter models and next-generation chips is one challenge; translating them into durable products is another. But Meta has a history of thriving when it builds patiently, at scale, and in plain sight. And that’s precisely what it’s doing right now.

Investors looking to invest in AI companies should keep the stock on watch.