Meta

If you’ve been waiting for the AI hardware story to stop being “Nvidia, Nvidia, and also Nvidia,” circle April 14, 2026. That’s when Meta and Broadcom went public with an expanded partnership to co-design multiple generations of Meta’s MTIA accelerators through 2029, anchored by a 1-gigawatt initial deployment and a path to multiple gigawatts after that. The headline spec: the first AI silicon built on TSMC’s 2nm process. This isn’t a routine vendor press release. It’s the loudest signal yet that the era of hyperscalers handing blank checks to Jensen is ending. ...

The European Commission just slapped Meta with a regulatory uppercut. On April 15, Brussels formally rejected Meta’s attempt to charge rival AI companies for access to WhatsApp’s 2 billion users — and threatened to force the tech giant to restore free access for competitors like Microsoft’s Copilot, OpenAI, and Perplexity. This isn’t just a legal skirmish. It’s the fight that decides whether you get to choose your AI assistant, or whether the company that owns your messaging app chooses for you. ...

Two deals. Two days. Two of the biggest names in AI writing checks to the same company. On Thursday, Meta committed an additional $21 billion to CoreWeave for AI cloud capacity through 2032. On Friday, Anthropic — the company behind Claude — signed a multiyear agreement to run its workloads on CoreWeave’s infrastructure. CoreWeave’s stock ripped past $103, and its total revenue backlog now exceeds $66.8 billion. For a company that started out mining Ethereum, that’s not a bad week. ...

Mark Zuckerberg spent $14.3 billion to hire the guy who trained everyone else’s AI. Now we get to see if it was worth it. Meta dropped Muse Spark this week — the first model from Superintelligence Labs, led by former Scale AI CEO Alexandr Wang. It’s proprietary. It’s consumer-focused. And it represents the most dramatic strategic pivot in Meta’s AI history: the company that championed open-source AI just went closed. ...

Mark Zuckerberg just played his most expensive hand yet. Meta unveiled Muse Spark, the first AI model from its Superintelligence Labs — the division built on a $14.3 billion Scale AI investment and a talent raid that cost hundreds of millions in individual engineer packages. After more than a year in the wilderness following the embarrassing Llama 4 launch, Meta says it’s back. But here’s the twist nobody expected: the company that championed open-source AI just went proprietary. ...

After 35 years as the Switzerland of semiconductors — licensing chip designs to anyone with a checkbook — Arm Holdings just crossed the Rubicon. It built its own chip. Not a demo. Not a reference design you’ll never see in production. A 136-core data center processor called the AGI CPU, fabricated on TSMC’s 3nm process, with Meta signed on as the debut customer. This isn’t incremental. This is tectonic. The Hardware: 136 Cores of Pure Intent The specs read like Arm had something to prove. ...

There’s a certain poetry in naming your flagship AI model after a fruit famous for going from “not ripe” to “completely rotten” in about six hours. Meta’s next-generation model, codenamed Avocado, was supposed to prove that $135 billion in annual AI spending could buy a seat at the frontier table. Instead, it’s become the most expensive guacamole in history — and the fallout is reshaping the entire tech industry. The Avocado Debacle The New York Times reported last week that Meta has delayed Avocado’s release from March to at least May. The reason: internal testing revealed the model trails leading systems from Google, OpenAI, and Anthropic in logical reasoning, programming, and writing. ...

The AI race has a new front, and it’s not about who builds the smartest model. It’s about who controls the pipes. Meta just signed a $27 billion, five-year infrastructure deal with Nebius Group — a company that, two years ago, was busy shedding its identity as Yandex’s international arm. The deal gives Meta priority access to purpose-built GPU clusters running Nvidia’s next-generation Vera Rubin chips. And it tells us something crucial about where the AI industry is actually heading. ...

Here’s a number that should stop you cold: Meta is planning to fire roughly 16,000 people — 20% of its entire workforce — while simultaneously doubling its AI spending to $135 billion in 2026. Fire the people. Fund the machines. It’s the most honest statement Big Tech has made about where things are going. The Layoffs Aren’t About Survival This isn’t 2022’s post-pandemic correction. Meta’s advertising business is still a cash machine. These cuts are proactive. The company isn’t trimming because it’s hurting — it’s reallocating capital from human labor to compute infrastructure. ...

Silicon Valley has a new business model: fire humans, hire GPUs. Meta is planning to cut roughly 20% of its workforce — about 16,000 people — to offset the staggering cost of its AI infrastructure ambitions. Reuters broke the story on March 14, citing sources who say top executives have already told senior leaders to start identifying where the axe falls. Meta spokesperson Andy Stone called it “speculative reporting about theoretical approaches.” Translation: we’re not announcing it yet. ...