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Meta Platforms on Thursday shared new details on its data center projects to better support artificial intelligence work, including a custom chip “family” being developed in-house.
The Facebook and Instagram owner said in a series of blog posts that it designed a first-generation chip in 2020 as part of the Meta Training and Inference Accelerator (MTIA) program. The aim was to improve efficiency for the recommendations models it uses to serve ads and other content in news feeds.
Reuters previously reported that the company was not planning to deploy its first in-house AI chip widely and was already working on a successor. The blog posts portrayed the first MTIA chip as a learning opportunity.
The first MTIA chip was focused exclusively on an AI process called inference, in which algorithms trained on huge amounts of data make judgments about whether to show, say, a dance video or a cat meme as the next post in a user’s feed, the posts said.
Joel Coburn, a software engineer at Meta, said during a presentation about the new chip that Meta had initially turned to graphics processing units, or GPUs, for inference tasks, but found they were not well suited to inference work.
Their efficiency is low for real models, despite significant software optimizations. This makes them challenging and expensive to deploy in practice,” Coburn said. “This is why we need MTIA.”
A Meta spokesperson declined to comment on deployment timelines for the new chip or elaborate on plans to develop chips that could train the models as well.
As a result, the company scrapped plans for a large-scale rollout of an in-house inference chip and started work on a more ambitious chip capable of performing training and inference,
SOURCE:REUTERS
