Meta is reportedly testing an in-house chip for training AI systems, a part of a strategy to reduce its reliance on hardware makers like Nvidia.

Facebook owner Meta is testing its first in-house chip for training artificial intelligence systems, a key milestone as it moves to design more of its own custom silicon and reduce reliance on external suppliers like Nvidia ,

Any setbacks in new chips meant that companies were forced to use older chips, which might not sit well with customers. Perhaps the AI industry is learning from this, because, according to a report from Reuters,

Meta has long been one of NVIDIA's biggest customers, relying on its GPUs to train AI models. But, as the company has bet big on AI, its spending on AI

RISC-V business Meta is quietly testing RISC–V–based AI training chips to kick Nvidia out of its wallet. The social notworking outfit has rolled out a “small deployment” of in-house silicon, developed in partnership with Taiwan’s TSMC,

One of the sources said Meta’s new training chip is a dedicated accelerator, meaning it is designed to handle only AI-specific tasks. This can make it more power-efficient than the integrated graphics processing units (GPUs) generally used for AI workloads.

Meta is reportedly testing its first AI training chip, which is designed to train Meta's AI systems and reduce dependency on suppliers like Nvidia.

Meta is evaluating its AI training accelerator, which could reduce its reliance on Nvidia's AI GPUs for training.

Meta Platforms (META) is reportedly testing its first in-house AI training chip, giving it the power to design its own custom silicon and

The custom chip is designed to train Meta’s artificial intelligence systems and reduce the company’s dependency on third-party suppliers like Nvidia, with Meta aiming to use its own in-house chips by 2026.

The Facebook owner is currently one of Nvidia’s biggest customers, amassing an arsenal of GPUs to train AI models.