Reuters previously reported that Meta, Inc. 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.
"From this initial program, we have learned invaluable lessons that we are incorporating into our roadmap," it wrote.
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, which was aimed at improving efficiency for the recommendations models it uses to serve ads and other content in news feeds.
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.
Meta acknowledged in its blog posts that its first MTIA chip stumbled with high-complexity AI models, although it said the chip handled low- and medium-complexity models more efficiently than competitor chips.
A Meta spokesperson declined to comment on deployment timelines or elaborate on the company's plans to develop chips that could train the models as well.
Meta has been engaged in a massive project to upgrade its AI infrastructure this past year, after executives realized it lacked the hardware and software needed to support demand from product teams building AI-powered features.
In addition to detailing its chip work, Meta provided an update on plans to redesign its data centers around more modern AI-oriented networking and cooling systems, saying it would break ground on its first such facility this year.
The new design would be 31% cheaper and could be built twice as quickly as the company's current data centers, an employee said in a video explaining the changes.