Apple hunts AI chip acquisitions to fix its servers


Apple built a trillion-dollar business on chips it designs itself. It cannot design the ones its AI needs fast enough, so it is going shopping.

The iPhone maker is hunting for AI chip acquisitions, The Information reported. In recent months it has talked to bankers about deals and approached chip startups to ask if they would sell. That is a rare move for a company that almost never buys big.

The reason is a problem Apple cannot hide. Its own AI servers, which run on internally designed M2 Ultra chips, are struggling. The heavy lifting behind the new, Gemini-powered Siri runs instead on Nvidia chips inside Google’s cloud. Apple tried to use its own machines for the job, and they were not up to it.

The chip that slipped

Apple has a server chip of its own in the works, codenamed Baltra. It was due this year. It slipped. Bloomberg reports that a chip powerful enough to rival Nvidia may not land until 2029, with an M5 Ultra upgrade filling the gap.

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Buying its way to the answer would break Apple’s habits. Its biggest deal ever was the $3bn Beats purchase in 2014. It built its entire chip empire off a much smaller buy: PA Semi, for $278m in 2008.

Even this year’s spending looks modest next to its rivals. Apple paid about $2bn for the Israeli AI startup Q.ai, its second-largest deal on record.

A more open wallet

Two things suggest Apple is ready to spend more. Its finance chief, Kevan Parekh, told analysts the company would drop its long-held goal of holding as much cash as debt. That frees up money, and Apple sat on $45.6bn of it at the end of March.

The other is people. Tim Cook hands the chief executive job to hardware boss John Ternus in September, and chip chief Johny Srouji now oversees all of Apple’s hardware. Both are engineers, and both may be readier to buy their way out of a bind.

Still leaning on others

Acquisitions are only one route. Apple is also in talks with PrismML, a startup that shrinks big AI models to run on an iPhone. And it just committed to $30bn of chips from Broadcom, a partnership it extended to 2031.

All of it points the same way. Apple wants off Nvidia, and clear of the wider memory and hardware squeeze reshaping the industry. Designing its own silicon is the long game. Buying someone else’s might be the shortcut. For a company that guards its independence, needing either is the real story.



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Recent Reviews


YouTube has an AI slop problem, and its crackdown is catching legitimate creators in the crossfire. Faceless channels, where no human host ever appears on screen, have existed for years and are not inherently AI-generated.

Many are run by solo creators who simply prefer to stay anonymous. The problem is that AI tools made it easy to flood the platform with low-effort faceless content at scale, and YouTube’s algorithm is now penalizing the format as a whole.

How bad is the AI slop problem on YouTube?

A Kapwing study found that roughly 21% of the first 500 videos recommended to a new YouTube account were classified as AI slop, while 33% fell into a broader brainrot category. The problem extends to children, too, as more than 40% of YouTube Shorts recommended to kids in a 15-minute session contained low-quality AI content.

YouTube’s response has been to tweak its algorithm to favor videos with real human faces on camera, which is hitting faceless creators even when their content is entirely human-made.

How is YouTube tackling its AI slop problem?

YouTube is now testing a new pop-up on mobile that asks viewers to rate whether a video feels like AI slop, on a scale from “not at all” to “extremely.” The idea sounds reasonable, but crowdsourcing AI detection has real problems. People are bad at spotting AI content, and they are getting worse at it as AI capabilities continue to improve.

There are also legitimate concerns that YouTube could use this viewer feedback as training data for its own AI models, potentially making future AI-generated content even harder to spot.

🚨 Did you just see what YouTube did?

YouTube isn’t banning AI slop.. They’re making you label it so they can train their next model to not look like slop.

Read that again…

You flag the bad AI content. YouTube collects it. Google feeds it into Veo 4… Then next year their… https://t.co/8UC2J3mjjv pic.twitter.com/mIrTChqC1b

— Tuki (@TukiFromKL) March 17, 2026

Meanwhile, faceless creators are scrambling to adapt. According to The Hollywood Reporter, some are hiring cheap on-camera hosts through platforms like Fiverr and Upwork. Others are doubling down on niche educational content, which has held up better than broad content farms.

The AI text-to-video space is still valued at enormous sums, with Higgsfield AI alone sitting at $1 billion, but on YouTube, the math for faceless creators is getting harder to work out every month.



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