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Anker's new Thus chip for AI in Soundcore flagship earbuds, shown with a microchip and earbud on a circuit board.

Editorial illustration for Anker's new Thus chip powers AI in upcoming Soundcore flagship earbuds

Anker's Thus Chip Brings AI Power to Soundcore Earbuds

Anker's new Thus chip powers AI in upcoming Soundcore flagship earbuds

Updated: 4 min read

Earbuds are the ultimate proving ground for AI. They’re tiny. They’re power-starved.

And they never stop listening. That’s why most chips in wireless earbuds have been stuck running neural networks with only a few hundred thousand parameters, barely enough to untangle a voice from a coffee shop roar. Anker’s new Thus chip changes the math.

By using a compute-in-memory design, it packs several million parameters into that same sliver of space, all without draining the battery. That means the upcoming Soundcore flagship earbuds can finally do something previous designs couldn’t: lock onto your voice in any chaos. Eight MEMS microphones and two bone conduction sensors seal the deal.

The result? Call audio so clean, the world around you might as well not exist.

The model never has to move again." The first Thus chip will integrate into Soundcore's upcoming flagship earbuds. The company says it's starting with earbuds because they're the most challenging devices to put AI chips in due to size constraints. The small space limits the amount of power available, and because the chip is always active while you're wearing the earbuds, previous designs had to rely on small neural networks capable of handling a few hundred thousand parameters.

But Anker says that with the more energy-efficient compute-in-memory design, the Thus chip is capable of handling several million parameters, significantly increasing the computing power to handle things like complex world noise. Traditional call noise canceling relies on those small onboard neural networks and can have difficulty isolating your voice in very noisy environments, which results in ambient noise leaking through or voices getting highly compressed, making it difficult to hear. Anker says the larger neural network available on the Thus chip, plus eight MEMS (micro-electromechanical systems) microphones and two bone conduction sensors to focus in on your voice, in its yet-to-be-announced earbuds will have significantly cleaner call audio, regardless of the environment.

This is more than just a better noise-canceling microphone. By cracking the size-power tradeoff with a compute-in-memory architecture, Anker has pulled off something the industry has long promised but rarely delivered: genuine, on-device AI that doesn’t demand a compromise. The Thus chip’s ability to run neural networks with millions of parameters inside a tiny earbud changes the game for voice clarity, but it also signals a broader shift.

If Anker can squeeze this kind of intelligence into the most constrained form factor, every other product in its lineup becomes a candidate for the same treatment. The earbuds are just the opening act.

Common Questions Answered

How does Anker's Thus chip address the challenges of integrating AI into small earbuds?

The Thus chip is specifically designed to overcome size and power constraints in compact devices like earbuds. By using compute-in-memory neural-net capabilities, the chip can run complex audio algorithms while consuming minimal power, solving the traditional limitations of AI hardware in tiny enclosures.

What makes the Soundcore flagship earbuds unique in terms of AI processing?

The Soundcore earbuds will be the first device to feature Anker's Thus chip, which enables advanced AI processing in an extremely compact form factor. Unlike previous designs that relied on small neural networks with limited parameters, this chip can handle more sophisticated AI computations while maintaining efficient power consumption.

Why did Anker choose earbuds as the first platform for its Thus chip?

Anker selected earbuds as the initial platform because they represent the most challenging device for AI chip integration due to extreme size constraints and power limitations. The small enclosure requires a chip that can perform complex tasks while drawing minimal battery power, making it the ultimate test for their innovative neural-net technology.

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