Apple shows signs of making big AI acquisitions in the future


Apple knows that it needs to get really serious about AI server chips. There are signs that the company is willing to spend big under John Ternus to buy its way out of its AI problem.

We already know that Apple is looking at deals such as one with PrismML to improve its on-device processing and Siri’s capabilities. Apple also wants to further its server-based AI processing too.

According to an article published on Wednesday by The Information, Apple is showing signs it’s ready to switch acquisition tactics. Instead of deals in the hundreds of millions of dollars, it’s prepared to do more in the range of billions of dollars, rivaling the deals to get Beats and PA Semi.

So far in 2026, this has included an agreement to buy Q.Ai in January. That deal is valued at $2 billion, making it the second largest behind the $3 billion purchase of Beats in 2014.

That Q.Ai deal nets Apple a machine learning company from Israel, that specializes in interpreting speech based on a person’s facial micro-movements. PA Semi ultimately led to advancements in the A-series processor, leading to the full roll-out of Apple Silicon.

It won’t be the only big-money deal on the table. During the second quarter earnings, CFO Kevan Parekh warned that Apple was shifting from its long-term policy of being net cash neutral, balancing debt with cash reserves.

The indication means Apple is more willing to spend those cash reserves on big acquisitions.

This story is breaking. Refresh for the most current information



Source link

Leave a Reply

Subscribe to Our Newsletter

Get our latest articles delivered straight to your inbox. No spam, we promise.

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.



Source link