Apple considers buying Mistral as Meta builds Manhattan-sized AI clusters

Apple considering Mistral acquisition as AI desperation grows. Meta announces $100B+ compute investment with 5-gigawatt clusters. Windsurf saved by Cognition after Google's brutal acqui-hire.

Apple's desperate AI shopping spree

Mark Gurman buried the lede in his latest Bloomberg piece: Apple is seriously considering acquiring Mistral, the French AI startup valued at $6 billion. This follows recent reports of Apple's interest in buying Perplexity, signaling a dramatic shift for a company historically resistant to major acquisitions. The desperation is palpable—Apple has fallen so far behind in AI that they're willing to abandon their traditional build-it-ourselves philosophy and simply buy their way into relevance.

The obstacles are massive. European regulators would scrutinize any American tech giant acquiring one of Europe's few AI champions. Mistral itself may have no interest in selling, especially to a company that's demonstrated such incompetence in AI development. But Apple's willingness to even explore these acquisitions reveals how dire their situation has become. They've watched Google dominate with Gemini, OpenAI capture mindshare with ChatGPT, and even Meta build a credible AI ecosystem while Apple fumbles with a Siri that still can't answer basic questions reliably.

The irony is thick—Apple once prided itself on patient, methodical development of perfectly integrated products. Now they're desperately shopping for AI companies like a panicked student trying to buy a term paper the night before it's due. The fact that these acquisition rumors are becoming commonplace suggests Apple is preparing for a major move, likely overpaying dramatically for whatever AI capability they can grab before it's too late.

Meta's compute arms race goes nuclear

Zuckerberg just announced Meta will invest "hundreds of billions of dollars" in AI compute, with plans that dwarf every competitor. Their Prometheus cluster coming online in 2026 will be the first 1-gigawatt facility, followed by Hyperion scaling to 5 gigawatts—each covering "a significant part of the footprint of Manhattan." For context, xAI's much-hyped Colossus operates at 250 megawatts, and OpenAI's Stargate project aims for 1 gigawatt but is already facing delays.

The scale is deliberately absurd. Meta doesn't need 5 gigawatts of compute for any practical purpose—they're building it as a recruiting tool and competitive moat. Zuckerberg explained the real strategy: "When I was recruiting people to different parts of the company, people asked 'What's my scope going to be?' Here, people say 'I want the fewest people reporting to me and the most GPUs.'" Having "by far the greatest compute per researcher" becomes the ultimate flex in the AI talent war. It's not about efficiency or need—it's about demonstrating you have unlimited resources to burn.

This compute buildup coincides with reports that Meta's super intelligence lab is considering abandoning open source entirely. The New York Times reports the team discussed ditching Llama 4's behemoth model to develop closed models from scratch, marking a complete philosophical reversal from Meta's supposed commitment to "open science." The original Llama release in 2023 positioned Meta as the open source champion against OpenAI's closed approach. Now, with their new super intelligence lab burning through billions, they're quietly admitting that open source was always just a commercial strategy, not a principle. Meta denies the shift officially, claiming they'll continue releasing open models, but the writing is on the wall—when you're spending hundreds of billions on compute, you don't give away the results for free.

The Windsurf saga's shocking conclusion

The Windsurf acquisition drama took another wild turn as Cognition, makers of Devin, swooped in to acquire the company's remains just 72 hours after Google's controversial acqui-hire. Google paid $2.4 billion to license Windsurf's technology and hire 30 engineers, leaving 200 employees in limbo with a company stripped of leadership and purpose. The consensus was these abandoned workers would split Windsurf's $100 million treasury and dissolve the company—a brutal example of how modern tech acquisitions treat non-elite employees as disposable.

Instead, Jeff Wang, thrust into the interim CEO role when executives fled to Google, orchestrated a miracle. His LinkedIn post captured the whiplash: "The last 72 hours have been the wildest roller coaster ride of my career." Cognition's acquisition ensures every remaining employee is "well taken care of," according to CEO Scott Wu, who emphasized honoring the staff's contributions rather than treating them as collateral damage. Crucially, Cognition restored Windsurf's access to Anthropic's Claude models, making the product viable again after Google's deal threatened to kill it.

This creates a fascinating new acquisition model: one company cherry-picks the founders and star engineers while another scoops up the remaining company and staff. It's a more humane approach than the typical acqui-hire that leaves most employees with nothing, but it also reveals how transactional these deals have become. The "legendary team" rhetoric masks a simple reality—AI talent is being carved up and distributed like assets in a corporate raid, with different buyers taking different pieces based on what they value most.

The Windsurf engineers who thought they were building the future of AI coding tools discovered they were actually just accumulating value to be harvested by bigger players. Google got the talent they wanted, Cognition got a product and team at a discount, early investors got paid, and somehow everyone claims victory. Welcome to the new economics of AI acquisitions, where companies are dismantled and distributed piece by piece to the highest bidders.