Meta's new AI chips will begin production in September | TechCrunch

In a bid to lower its GPU costs amid an unprecedented component shortage, Meta is on track to start making the latest versions of its AI-specific chip in September, Reuters reported, citing an internal memo.At least one chip sailed through its testing phase in about six weeks, the memo said. Meta is working with Broadcom on the chip design, but it will use Taiwan Semiconductor Manufacturing Company (TSMC) to manufacture them. It is also buying RAM from Samsung, storage from Sandisk, and fiber-optic equipment from Sumitomo Electric, according to the report.Meta detailed the four new chips, developed under its Meta Training and Inference Accelerator (MTIA) program, in March, some of which are currently in deployment or will be this year or next. The company is taking a modular approach to designing these chips, anticipating that their needs will change as AI evolves rapidly by the time the chips are in production.“Each MTIA generation builds on the last, using modular chiplets, incorporating the latest AI workload insights and hardware technologies, and deploying on a shorter cadence,” the company wrote at the time.The chips are expected to help the company save on buying GPUs from chipmakers like Nvidia and AMD, although it still expects to spend plenty with those providers as well, Reuters reports. Meta intends to use the MTIA chips for training models for its ranking and recommendation algorithms, broader AI workloads, and inference aimed at its applications. The social media company has been producing its own AI chips since 2023.Meta has been spending massively on securing enough compute capacity to power its various AI efforts. The company in April said it expects capital expenditures between $125 billion and $145 billion this year, a lot of which is going toward its AI efforts.The company has been striking data center and power deals across the world, spending tens of billions to secure computing capacity to train and deploy its new Muse Spark series of AI models. It plans to deploy 7 gigawatts of compute this year, and double that next, according to Reuters, which cited the memo.It also signed a deal with ARM last year to secure compute for its recommendation systems, in addition to a multibillion-dollar deal with AMD for its Instinct GPUs and a multibillion-dollar deal with Amazon to use the cloud giant’s homegrown CPUs for AI-related needs.Meta isn’t the only company trying to stem the tide of capital going to Nvidia. OpenAI last month unveiled an inference processor that it is building with Broadcom, and Anthropic is said to be considering developing its own chips with Samsung. Amazon and Google both develop their own chips for AI training and inference, and there’s a host of startups building in the space to meet skyrocketing demand.Meta declined to comment.TopicsWhen you purchase through links in our articles, we may earn a small commission. This doesn’t affect our editorial independence. Editor Ram is a financial and tech reporter and editor. He covered North American and European M&A, equity, regulatory news and debt markets at Reuters and Acuris Global, and has also written about travel, tourism, entertainment and books.You can contact or verify outreach from Ram by emailing ram.iyer@techcrunch.com. Last chance to save up to $190 on TechCrunch Founder Summit. Join 1,000+ founders and VCs at all stages for real-world scaling insights and connections that move the needle.

Savings end June 26, 11:59 p.m. PT. Figma acquires team behind a vibe-coding app

If you use Google, you’re training its AI. Here’s how to opt out.

Reddit is using LLMs to solve a problem LLMs largely created

Amazon will stop accepting new customers for Mechanical Turk

5 desk gadgets that can make your workday better

New Google commercial imagines a Declaration of Independence written with help from AI

Chevy built an all-American EV truck — why is nobody buying it?