Meta is reportedly readying its first in-house AI training chip for deployment The dedicated AI accelerator, made with TSMC, completed tape-out Meta’s shift to custom silicon aims to reduce its dependence on Nvidia hardware Like many of Nvidia’s highest spending customers,

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 ,

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.

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.

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.

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 infrastructure has soared through the roof. Now,