Meta to start producing in-house AI chip in September, targeting 14 gigawatts of capacity

Meta's new AI chips will begin production in September

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, however it will use Taiwan's 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 computing 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 towards 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 multi-billion deal with AMD for its Instinct GPUs, and a multi-billion 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.

EXCLUSIVE: Meta to put AI chip into production in September as it looks to double computing capacity, memo shows

NEW YORK/SAN FRANCISCO, July 9 (Reuters) - Meta Platforms (META.O), opens new tab plans to start manufacturing an artificial intelligence chip from September as part of its plan to boost overall computing power to 14 gigawatts next year, showed an internal memo reviewed by Reuters. The tech firm's data center chip, code-named "Iris", is part of a four-generation project for Meta Training and Inference Accelerators (MTIA) that it will design in-house. The plan is to use custom-built silicon to improve the AI that powers its Facebook and Instagram social media platforms. Testing the chip took only six weeks and found no major issues, the memo showed. That relatively quick progress signals positive momentum ⁠for an in-house effort that has floundered since its launch more than half a decade ago. Meta tailored the chip for its own needs and is working with Broadcom (AVGO.O), opens new tab to help design it and Taiwan Semiconductor Manufacturing Co (2330.TW), opens new tab to manufacture it. The approach is likely to help the firm lower its massive computing costs and gain more independence from chip suppliers such as Nvidia (NVDA.O), opens new tab and Advanced Micro Devices (AMD.O), opens new tab. The bug-testing completion and production timing have not been previously reported. Meta declined to comment. The chip is aimed at augmenting the large quantities of graphics processing units (GPUs) used for AI applications that Meta purchases from Nvidia and AMD. However, adopting the latest GPUs at a firm as large as Meta "has been a heavy lift, and it has cost us time," the memo showed. Meta unveiled Iris under its technical name in March ⁠along with three other AI processors. It plans to launch a chip about every six months through 2027, whereas typically firms release AI chips at intervals of a year or more. SEVEN GIGAWATTS OF COMPUTING IN 2026 Meta this year plans to deploy seven gigawatts of computing infrastructure, the memo showed. It plans to double that number in 2027, the memo said. The firm expects to spend as much as $145 billion on AI infrastructure this year, a ⁠significant portion of Big Tech's more than $700 billion projected outlay on the technology. To expand computing infrastructure, Meta has secured long-term, multi-year supply agreements, the memo showed. Those include agreements with Samsung Electronics (005930.KS), opens new tab for memory chips, Sandisk (SNDK.O), opens new tab for flash storage and Sumitomo Electric (5802.T), opens new tab for fiber-optic equipment. Such long-term agreements have ⁠become critical for data center expansion targets amid a memory chip shortage that has prompted companies such as Apple AAPL.O to raise prices. Sandisk declined to comment. Samsung Electronics and Sumitomo Electric did not respond to requests for comment. Components such as memory and AI chips have ⁠experienced a surge in demand as tech companies race to expand data centers to keep pace with AI's thirst for computing power. Memory and other chip prices have risen rapidly and substantially enough that "chipflation" has become a macroeconomic concern, Morgan Stanley analysts said. Reporting by Katie Paul in New York, and Max A. Cherney and Stephen Nellis in San Francisco; Editing by Christopher Cushing Our Standards: The Thomson Reuters Trust Principles., opens new tab * Suggested Topics: * Artificial Intelligence * ADAS, AV & Safety * Manufacturing * Products Max A. Cherney Thomson Reuters Max A. Cherney is a correspondent for Reuters based in San Francisco, where he reports on the semiconductor industry and artificial intelligence. He joined Reuters in 2023 and has previously worked for Barron's magazine and its sister publication, MarketWatch. Cherney graduated from Trent University with a degree in history.

Meta to put AI chip into production in September as it looks to double computing capacity, Reuters reports

Meta Platforms plans to start manufacturing an artificial intelligence chip from September as part of its plan to boost overall computing power to 14 gigawatts next year, according to an internal memo reviewed by Reuters. The tech firm's data center chip, code-named "Iris", is part of a four-generation project for Meta Training and Inference Accelerators (MTIA) that it will design in-house. The plan is to use custom-built silicon to improve the AI that powers its Facebook and Instagram social media platforms. Testing the chip took only six weeks and found no major issues, the memo showed. That relatively quick progress signals positive momentum for an in-house effort that has floundered since its launch more than half a decade ago. Meta tailored the chip for its own needs and is working with Broadcom AVGO.O to help design it and Taiwan Semiconductor Manufacturing Co 2330.TW to manufacture it. The approach is likely to help the firm lower its massive computing costs and gain more independence from chip suppliers such as Nvidia and Advanced Micro Devices. The bug-testing completion and production timing have not been previously reported. Meta declined to comment. The chip is aimed at augmenting the large quantities of graphics processing units (GPUs) used for AI applications that Meta purchases from Nvidia and AMD. However, adopting the latest GPUs at a firm as large as Meta "has been a heavy lift, and it has cost us time," the memo showed. Meta unveiled Iris under its technical name in March along with three other AI processors. It plans to launch a chip about every six months through 2027, whereas typically firms release AI chips at intervals of a year or more. Seven gigawatts of computing in 2026 Meta this year plans to deploy seven gigawatts of computing infrastructure, the memo showed. It plans to double that number in 2027, the memo said. The firm expects to spend as much as $145 billion on AI infrastructure this year, a significant portion of Big Tech's more than $700 billion projected outlay on the technology. To expand computing infrastructure, Meta has secured long-term, multi-year supply agreements, the memo showed. Those include agreements with Samsung Electronics for memory chips, Sandisk for flash storage and Sumitomo Electric for fiber-optic equipment. Such long-term agreements have become critical for data center expansion targets amid a memory chip shortage that has prompted companies such as Apple to raise prices. Sandisk declined to comment. Samsung Electronics and Sumitomo Electric did not respond to requests for comment. Components such as memory and AI chips have experienced a surge in demand as tech companies race to expand data centers to keep pace with AI's thirst for computing power. Memory and other chip prices have risen rapidly and substantially enough that "chipflation" has become a macroeconomic concern, Morgan Stanley analysts said.

Meta to put its own AI chip into production in September, aiming to double computing capacity

The move would deepen Meta's effort to wean its data centres off Nvidia GPUs, according to Reuters. Meta plans to put its own artificial intelligence chip into production in September and is aiming to roughly double the computing capacity across its data centres, Reuters reported on Thursday, citing people familiar with the matter. The chip belongs to Meta's in-house silicon line, the Meta Training and Inference Accelerator, or MTIA, which the company has been scaling up as part of a record spending push and a wider effort to reduce its reliance on Nvidia. Meta declined to comment on the specifics, and both the September timing and the capacity target come from anonymous sources rather than any public disclosure. If the timeline holds, it would mark another step in a programme that has moved unusually fast this year. Meta unveiled four new MTIA chips in March, the 300, 400, 450, and 500, and said it would ship them on a roughly six-month cadence rather than the annual pace common across the industry. Those chips are manufactured by TSMC and co-developed with Broadcom, whose partnership with Meta now runs through 2029 and covers several generations of custom silicon. Broadcom has said the newer MTIA parts will be among the first custom AI chips built on a 2-nanometre process. The strategic logic is straightforward. Meta remains one of Nvidia's biggest customers, buying vast numbers of GPUs to train its Llama models and to run recommendation systems for more than 3 billion daily users, and every workload it can move onto its own chips is one it does not have to buy at Nvidia's margins. For now, MTIA has largely handled inference, the day-to-day job of serving predictions once a model has been trained. The MTIA 300 is already in production for ranking and recommendation work, while the 450 and 500, aimed at generative image and video inference, are slated for mass deployment through 2027. A training-capable chip would be a harder test. Training frontier models is the workload where Nvidia's hardware and its CUDA software have proved stickiest, and where in-house alternatives from Google and Amazon have taken years to mature. The capacity ambition sits inside an enormous spending plan. Meta has guided 2026 capital expenditure to between $125bn and $145bn, with nearly all of the increase going towards data centres, GPUs, and custom silicon, and Mark Zuckerberg has floated eventual targets measured in gigawatts. That build-out has grown large enough that Meta is now looking to rent out spare compute to outside customers, echoing a model long used by cloud providers. The company has also hedged its bets on suppliers, signing deals for Amazon's Graviton5 chips and AMD accelerators alongside its standing Nvidia orders. Custom silicon is central to that hedge because it changes the underlying economics. Designing a chip for exactly the models Meta runs, rather than buying a general-purpose GPU, can cut power draw and unit costs at the scale the company operates, provided the software stack keeps pace. The catch is that in-house chips rarely displace Nvidia outright. Analysts tend to frame MTIA as a way to absorb growth and trim the GPU bill at the margins, not to replace Nvidia in the near term, and Meta itself keeps expanding its GPU commitments even as it ramps up custom parts. Reuters' report does not specify which MTIA generation enters production in September, nor how any doubling of capacity would be split between new chips and additional data-centre floor space. Meta has not published a figure that matches the framing. What is clearer is the direction of travel. After years of experiments, Meta's silicon effort has shifted from a side project into a core plank of its infrastructure strategy, and September, if the reporting proves accurate, would be the next milestone to watch. The bigger question is whether the chips can eventually reach the training workloads that still belong almost entirely to Nvidia.

Meta to start production of Iris AI chip in September 2026

Meta $META plans to begin manufacturing its in-house AI chip, code-named Iris, in September, according to an internal memo reviewed by Reuters. Falling under the umbrella of Meta's MTIA program -- short for Meta Training and Inference Accelerators -- Iris is one of four planned chip generations aimed at strengthening the AI systems running on Facebook and Instagram. According to the memo, the chip cleared its bug-testing phase in roughly six weeks without turning up any significant problems. Broadcom $AVGO is serving as Meta's design partner on the chip, while Taiwan Semiconductor Manufacturing Co. has been tapped to handle its fabrication. By building its own silicon, Meta is seeking to cut spending on compute and loosen its reliance on third-party chip vendors including Nvidia $NVDA and Advanced Micro Devices. March marked Iris's public debut, when Meta introduced it by its technical designation as part of a slate of four AI processors. That cadence -- a new chip approximately every six months until 2027 -- represents a significantly more aggressive schedule than the annual or slower release cycles common across the industry. Adopting the latest GPUs at Meta's scale "has been a heavy lift, and it has cost us time," the memo said. The Iris chip is intended to supplement -- not replace -- the large volumes of GPUs Meta buys from Nvidia and AMD $AMD. The chip production announcement is tied to a broader infrastructure push. The memo also outlined a two-step infrastructure expansion: seven gigawatts of computing capacity coming online in 2026, growing to 14 gigawatts by 2027. Meta's projected AI infrastructure spending for the year reaches as high as $145 billion. Underpinning the expansion, the memo revealed that Meta has locked in extended supply contracts across several hardware categories: memory chips from Samsung Electronics, flash storage from Sandisk, and fiber-optic equipment from Sumitomo Electric. None of the three suppliers provided comment; Sandisk explicitly declined, while Samsung Electronics and Sumitomo Electric had not responded by press time. Meta likewise declined to comment. The Iris production timeline fits into a broader custom silicon strategy Meta formalized with Broadcom earlier this year, when the two companies agreed to expand their partnership on custom AI chips through 2029, covering multiple MTIA generations. That deal included a commitment to deploy more than one gigawatt of computing capacity as an opening installment in a planned multi-gigawatt buildout. Meta has also struck a multiyear agreement with AMD to deploy up to six gigawatts of AMD Instinct GPUs, part of an effort to diversify its compute supply away from a single vendor.

Meta to put AI chip into production in September as it looks to double computing capacity, memo shows

Meta Platforms plans to manufacture its own artificial intelligence chip starting September. This initiative aims to significantly increase the company's overall computing power by next year. The custom-designed chip, code-named Iris, is part of a multi-generation project. Meta is working with Broadcom and Taiwan Semiconductor Manufacturing Co for design and production. This move seeks to reduce costs and gain independence from external chip suppliers. Meta Platforms plans to start manufacturing an artificial intelligence chip from September as part of its plan to boost overall computing power to 14 gigawatts next year, showed an internal memo reviewed by Reuters. The tech firm's data center chip, code-named "Iris", is part of a four-generation project for Meta Training and Inference Accelerators (MTIA) that it will design in-house. The plan is to use custom-built silicon to improve the AI that powers its Facebook and ⁠Instagram social ⁠media platforms. Testing the chip took only six weeks and found no major issues, the memo showed. That relatively quick progress signals positive momentum for an in-house effort that has floundered since its launch more than half a decade ago. Meta tailored the chip for its own needs and is working with Broadcom to help design it and Taiwan Semiconductor Manufacturing Co to manufacture it. The approach is likely to help the firm lower its massive computing costs and gain more independence from chip suppliers such as Nvidia and Advanced Micro Devices. The bug-testing completion ⁠and production timing have not been previously reported. Meta declined to comment. The chip is aimed at augmenting the large quantities of graphics processing units (GPUs) used for AI applications that Meta purchases from Nvidia and ⁠AMD. However, adopting the latest GPUs at a firm as large as Meta "has been a heavy lift, and it has cost us time," the memo showed. Meta unveiled Iris under its technical name in March along with three other AI processors. It plans to launch a chip about every six months through 2027, whereas typically firms release AI chips at intervals of a year or more. SEVEN GIGAWATTS OF COMPUTING IN 2026 Meta this year plans to deploy seven gigawatts of computing infrastructure, the memo showed. It plans to double that number in 2027, the memo said. The firm expects to spend as much as $145 billion on AI infrastructure this year, a significant portion of Big Tech's more than $700 billion projected outlay on the technology. To expand computing infrastructure, Meta has secured long-term, multi-year supply agreements, the memo showed. Those include agreements with Samsung ⁠Electronics for memory chips, Sandisk for flash storage and Sumitomo Electric for fiber-optic equipment. Such long-term agreements have become critical for data center expansion targets amid a memory chip shortage that has prompted companies such as Apple to raise prices. Sandisk declined to comment. Samsung Electronics and Sumitomo Electric did not respond to requests for comment. Components such as memory and AI chips have experienced a surge in demand as tech companies race to expand data centers to keep pace with AI's thirst for computing power. Memory and other chip prices have risen rapidly and substantially enough that "chipflation" has become a macroeconomic concern, Morgan Stanley analysts said.

Meta aims to make its own chips as AI giants strive for independence from strained supply chain

Mark Zuckerberg's Meta plans to design its own artificial intelligence chips in-house starting in September - part of an industry-wide effort by the biggest names in AI to start making their own chips amid ongoing high demand. Zuck's initiative, known internally as "Iris," centers on developing custom silicon to supercharge the AI systems behind Facebook and Instagram, Reuters reported Thursday. The social media giant -- which expectes to spend up to $145 billion on AI infrastructure this year -- is working with Palo Alto, Calif.-based Broadcom on design and Taiwan Semiconductor Manufacturing on production. Meta joins a growing list of technology companies seeking to handle more of their chip development internally to cut costs and reduce dependence on Nvidia, which has dominated the AI chip business with its ultra-powerful semiconductors. Even as Meta and other companies are launching their foray into chip building, the semiconductor industry remains under tremendous demand strain, and AI companies' efforts to become more autonomous provides no silver bullet to the supply chain conundrum. Demand for manufacturing, packaging and other chip production resources continues to outpace supply, while several specialized chip-making processes are controlled by a small number of companies already operating at capacity even as they invest mountains of capital to expand. Meta's latest project builds on a long-running effort to develop its own chips. Its Training and Inference Accelerators program, launched more than five years ago, has focused on in-house chip development, though progress has been slow. Development of the new chip has reportedly moved much more rapidly. Testing took just six weeks and faced no major problems, according to Reuters. Meta plans to introduce a new chip roughly every six months through 2027, compared with the typical annual-or-longer release cycle for AI chips. Meta is aiming to double its computing infrastructure in 2027, according to Reuters. The custom product is intended to complement the large number of graphics processing units, or GPUs, that Meta buys from Nvidia and AMD for AI workloads. But bringing the newest GPUs online at Meta's scale "has been a heavy lift, and it has cost us time," according to a company memo reviewed by Reuters. Developing custom chips can potentially lower costs and diversify supply chains, Axios noted. "I want something in my pocket when I'm sitting across the table from Jensen negotiating," Bernstein senior analyst Stacy Rasgon told the outlet, referring to Nvidia CEO Jensen Huang. In addition to Meta, Amazon, Google and Microsoft all have in-house chip programs. OpenAI recently introduced its first custom inference chip with Broadcom, while Anthropic is reportedly in talks with Samsung about developing its own chip. Apple announced this week that it plans to spend more than $30 billion with Broadcom over the next five years, helping the chipmaker expand a manufacturing facility in Fort Collins, Colo. The consumer tech giant already designs its own chips for the iPhone, iPad and Mac, and is reportedly developing separate processors for AI servers. Samsung manufactures advanced chips for both its own products and outside customers, while Intel is working to expand its contract manufacturing business after its production technology fell behind in recent years, Axios noted. Showing the complexity of attaining chip autonomy, those manufacturers rely on lithography equipment from Dutch company ASML -- the only supplier of the most advanced machines used to produce AI chips, per the news site. The Post has sought comment from Meta, Broadcom and Taiwan Semiconductor Manufacturing.

Benchmark reiterates Hold on Meta stock after AI infrastructure memo By Investing.com

Investing.com - Benchmark reiterated a Hold rating on Meta Platforms Inc. (NASDAQ:META) following a leaked internal memo detailing the company's artificial intelligence infrastructure plans. The stock trades at $668.69, up 8.33% over the past week, though InvestingPro analysis suggests the shares are slightly overvalued relative to its Fair Value estimate -- placing it among companies on the most overvalued list. The memo, reported by Reuters on July 9, outlined plans to deploy 7 gigawatts of computing infrastructure in 2026 and double overall capacity to 14 gigawatts in 2027. The company's 2026 spending could reach $145 billion, the top end of its April guidance range of $125 billion to $145 billion and up from the January range of $115 billion to $135 billion. Meta's financial position supports this aggressive investment, with gross profit margins of 82% and revenue growth of 26% over the last twelve months. InvestingPro subscribers can access 11 additional ProTips and a comprehensive Pro Research Report for deeper analysis. The memo disclosed multi-year supply agreements with Samsung for memory, Sandisk for flash storage, and Sumitomo Electric for fiber optics. These deals were struck during a memory shortage severe enough to lift consumer hardware prices. The memo also referenced a previously announced multi-year agreement with AMD covering up to 6 gigawatts of Instinct accelerators. Meta's in-house Iris AI accelerator enters production at TSMC in September 2026 after clearing bug validation in six weeks with no major issues. The result represents an unusually clean tape-out for the Meta Training & Inference Accelerator program, which has stumbled repeatedly since inception. Benchmark analyst Mark Zgutowicz maintained the Hold rating on the stock. In other recent news, Meta Platforms Inc. has announced the commencement of construction on a new data center in Sturgeon County, Alberta. This facility, the company's first in Canada, represents an investment of over CAD $13 billion and will be optimized for AI workloads. Approximately 3,000 construction workers are expected on-site at peak times, with the center supporting more than 300 operational jobs upon completion. Meanwhile, Piper Sandler has reiterated an Overweight rating for Meta, setting a price target of $800, highlighting the company's top-line growth and attractive valuation. BofA Securities also maintained a Buy rating with a target of $835, citing Meta's custom silicon chip development and plans to expand compute capacity significantly by 2027. Citizens has slightly adjusted its price target to $800 due to concerns over increased capital expenditures, while maintaining a Market Outperform rating. Wolfe Research continues to rate Meta as Outperform, raising its capital expenditure estimate for 2027 to $220 billion, surpassing previous estimates. These developments underscore the company's ongoing expansion and strategic investments. This article was generated with the support of AI and reviewed by an editor. For more information see our T&C.

BofA Securities reiterates Buy on Meta stock on chip development By Investing.com

Investing.com - BofA Securities reiterated a Buy rating and $835.00 price target on Meta Platforms Inc. (NASDAQ:META) following reports of the company's custom silicon chip development and capacity expansion plans. The stock currently trades at $631.48, and InvestingPro analysis suggests the company remains undervalued with a Fair Value of $658, placing it among opportunities on the most undervalued stocks list. Analyst Justin Post cited an internal memo reviewed by Reuters indicating Meta is building a custom silicon chip as part of efforts to add 14 gigawatts of total compute capacity in 2026 and 2027. The memo stated Meta has deployed 1 gigawatt of capacity so far in 2026 and expects to deploy 5.5 gigawatts in the second half of 2026. BofA Securities estimates the 2026 cost per gigawatt at approximately $22 billion based on $145 billion in capital expenditures, compared to the firm's previous estimate of $45 billion per gigawatt for 2026. The 6.5 gigawatt capacity growth cited in the memo exceeds BofA Securities' estimate of 2.6 gigawatts. The firm notes that building capacity at below $30 billion per gigawatt could offer favorable economics compared to its estimates for Amazon and Google annual cloud revenues per gigawatt at $10 billion to $16 billion. BofA Securities also referenced recent SpaceX capacity deals that could range from $40 billion to $50 billion per year per gigawatt. The analyst acknowledged that not all capacity is built the same but suggested Meta may have achieved significant cost savings in its capacity deployment strategy. These efficiency gains align with Meta's impressive gross profit margin of 82% and overall "GREAT" financial health rating. For deeper insights into Meta's capacity expansion strategy and financial outlook, investors can access the comprehensive Pro Research Report, one of 1,400+ available for top US equities. In other recent news, Meta Platforms has announced the groundbreaking of a new data center in Sturgeon County, Alberta, representing an investment of over CAD $13 billion. This facility, optimized for AI workloads, will be Meta's first in Canada and its 33rd globally. In analyst updates, Citizens reduced its price target for Meta to $800, citing concerns over increased capital expenditures, while Wolfe Research maintained its Outperform rating with the same price target, adjusting its capex estimate to $220 billion for fiscal year 2027. Additionally, Meta plans to integrate its Muse Image model into its Advantage+ creative ad tool, enhancing ad variations through visual reasoning and self-refinement capabilities. Meanwhile, Meta CEO Mark Zuckerberg has acknowledged that the development of AI agents is progressing slower than anticipated. Concerns in the AI sector have been further heightened by Michael Burry's short positions across multiple AI-infrastructure stocks. These developments come as the company continues to navigate the evolving landscape of AI and digital infrastructure. This article was generated with the support of AI and reviewed by an editor. For more information see our T&C.

Meta to produce AI chips in September, memo shows

STORY: :: A memo seen by Reuters shows that Meta plans to produce AI chips this September :: The move will likely help Meta gain more independence from chip suppliers such as Nvidia :: Katie Paul, Tech Correspondent :: Meta / Archive "In the world of AI, those who control their infrastructure and their compute costs really control their destiny. Meta has been at this a while. They want to have more control over their supply chain. Doing a chip helps them to get that cost of running compute down. If they buy a lot of chips from Nvidia and AMD, those are extremely expensive. It means that other companies are in the driver's seat, both in terms of cost and some control over the supply. And having some kind of chip that can help maximize efficiency of running compute, or running processes, helps them, puts them in the driver's seat more and it helps them control their costs. They're also trying to build out these brand-new business models to effectively compete with OpenAI and Anthropic. So, selling the AI models to developers to use, and that means rolling out an API, which they just did this morning. This is brand new for them. They're moving this direction for the first time after kind of embracing the open source ethos for a number of years. And so that means that they need to, try to compete on price with those other, players in the market and also keep their costs low enough that they can, you know, make this business model make sense. And so having a chip that can help them to run these processes in a way that is as cost-efficient as possible is a huge potential benefit for them." The tech firm's data center chip, code-named "Iris," is part of a four-generation project for Meta Training and Inference Accelerators (MTIA) that it will design in-house. The plan is to use custom-built silicon to improve the AI that powers its Facebook and Instagram social media platforms. Testing the chip took only six weeks and found no major issues, the memo showed. That relatively quick progress signals positive momentum for an in-house effort that has floundered since its launch more than half a decade ago. Meta tailored the chip for its own needs and is working with Broadcom to help design it and Taiwan Semiconductor Manufacturing Co to manufacture it. The approach is likely to help the firm lower its massive computing costs and gain more independence from chip suppliers such as Nvidia and Advanced Micro Devices.

U.S. chip stocks rebound as Meta plans to double GW capacity By Investing.com

Investing.com -- U.S. chip stocks bounced back Thursday, recovering some of the ground lost earlier in the week, after a rally in Chinese semiconductor shares helped steady investor nerves following a selloff following Samsung Electronics' latest results. Additionally, fears of an AI CapEx slowdown eased after Reuters reported that Meta Platforms plans to double its computing power to 14 gigawatts next year and expects its custom AI chip to start production in September. While stocks in the sector gained ground, they closed off their best levels. Micron Technology closed up 4.4%, Advanced Micro Devices gained 5.7%, and Broadcom gained 3.2% on the session. Elsewhere, Marvell Technology jumped 5%, SanDisk rose 7.6%, Applied Materials gained 3.2%, and Lumentum Holdings added 11%. The gains initially followed a sharp rise in Chinese semiconductor stocks, where enthusiasm is building ahead of a closely watched market debut. The CSI Semiconductor Index closed up 8.8% after Changxin Memory Technologies, a leading Chinese memory chipmaker, said it would begin book-building on July 15 for a Shanghai initial public offering that aims to raise 29.5 billion yuan, or roughly $4.34 billion. Changxin, known as CXMT, is the world's fourth-largest maker of DRAM chips, holding about 7.7% of the global market last year. Further bolstering the AI trade was the Meta news. Last week, AI chip and adjacent stocks sold off after Bloomberg reported Meta was planning to form a neocloud-like arm to sell its data center computing capacity. Initially, investors digested the news as a sign of slowing hyperscaler investment in AI. Today's news, however, shows that Meta is continuing its relentless buildout by locking in massive, long-term infrastructure commitments. The tech giant sees itself deploying 7 gigawatts of computing infrastructure in 2026, with that number doubling to 14 gigawatts in 2027. Meta expects to spend as much as $145 billion on AI infrastructure this year, the report said, a sizeable chunk of the $700+ billion tab big tech companies have projected. According to the Reuters report, citing an internal memo, Meta's custom chip, codenamed "Iris," is set to use custom-built silicon to improve Meta's AI-driven social media platforms. The chip only took 6 weeks to test and no issues were found, the report said. Meta is working with Broadcom on the design of the chip, and aiwan Semiconductor Manufacturing (NYSE:TSM) is manufacturing it. The company also secured multi-year supply agreements with Samsung for memory chips, Sandisk for flash storage, and Sumitomo Electric for fiber-optic equipment. The rebound comes just two days after a global selloff in chip stocks, sparked by an unexpected drop in Samsung Electronics shares despite the South Korean company posting forecast-beating earnings. Samsung said it expects second-quarter operating profit of 89.4 trillion won, or about $58.44 billion, nearly 19 times higher than a year earlier and greater than its combined profit over the prior three years. That figure exceeded an LSEG SmartEstimate of 87.3 trillion won, while revenue was projected to jump 129% to 171 trillion won. But despite the beat, shares in Samsung fell sharply, with some analysts attributing the reaction to the fact that much of the good news had already been priced in. The selloff also reflected broader questions about the durability of the artificial-intelligence-driven demand that has powered the chip sector's rally over the past year. Memory chip prices have risen sharply over the same period, raising questions among investors about whether demand can keep pace with elevated pricing. Luke Juricic and Frank DeMatteo contributed to this report

Meta to put AI chip into production in September as it looks to double computing capacity, memo shows

NEW YORK/SAN FRANCISCO, July 9 (Reuters) - Meta Platforms plans to start manufacturing an artificial intelligence chip from September as part of its plan to boost overall computing power to 14 gigawatts next year, showed an internal memo reviewed by Reuters. The tech firm's data center chip, code-named "Iris", is part of a four-generation project for Meta Training and Inference Accelerators (MTIA) that it will design in-house. The plan is to use custom-built silicon to improve the AI that powers its Facebook and Instagram social media platforms. Testing the chip took only six weeks and found no major issues, the memo showed. That relatively quick progress signals positive momentum for an in-house effort that has floundered since its launch more than half a decade ago. Meta tailored the chip for its own needs and is working with Broadcom to help design it and Taiwan Semiconductor Manufacturing Co to manufacture it. The approach is likely to help the firm lower its massive computing costs and gain more independence from chip suppliers such as Nvidia and Advanced Micro Devices. The bug-testing completion and production timing have not been previously reported. Meta declined to comment. The chip is aimed at augmenting the large quantities of graphics processing units (GPUs) used for AI applications that Meta purchases from Nvidia and AMD. However, adopting the latest GPUs at a firm as large as Meta "has been a heavy lift, and it has cost us time," the memo showed. Meta unveiled Iris under its technical name in March along with three other AI processors. It plans to launch a chip about every six months through 2027, whereas typically firms release AI chips at intervals of a year or more. SEVEN GIGAWATTS OF COMPUTING IN 2026 Meta this year plans to deploy seven gigawatts of computing infrastructure, the memo showed. It plans to double that number in 2027, the memo said. The firm expects to spend as much as $145 billion on AI infrastructure this year, a significant portion of Big Tech's more than $700 billion projected outlay on the technology. To expand computing infrastructure, Meta has secured long-term, multi-year supply agreements, the memo showed. Those include agreements with Samsung Electronics for memory chips, Sandisk for flash storage and Sumitomo Electric for fiber-optic equipment. Such long-term agreements have become critical for data center expansion targets amid a memory chip shortage that has prompted companies such as Apple to raise prices. Sandisk declined to comment. Samsung Electronics and Sumitomo Electric did not respond to requests for comment. Components such as memory and AI chips have experienced a surge in demand as tech companies race to expand data centers to keep pace with AI's thirst for computing power. Memory and other chip prices have risen rapidly and substantially enough that "chipflation" has become a macroeconomic concern, Morgan Stanley analysts said. (Reporting by Katie Paul in New York, and Max A. Cherney and Stephen Nellis in San Francisco; Editing by Christopher Cushing) By Katie Paul, Max A. Cherney and Stephen Nellis

Meta falls as massive AI infrastructure spending plans overshadow chip progress By Investing.com

Investing.com -- Meta Platforms (NASDAQ:META) shares declined 2.6% Thursday morning as the company's ambitious plans to double its computing capacity reminded investors of the astronomical capital expenditures required to win the artificial intelligence race. While the social media giant announced it will begin manufacturing its first in-house AI chip this September -- a move intended to eventually lower computing costs -- the sheer scale of the company's near-term spending plans triggered immediate anxiety on Wall Street. According to an internal memo reviewed by Reuters, Meta plans to start production on its data center chip, code-named "Iris," in September. The chip is part of a four-generation project for Meta Training and Inference Accelerators (MTIA) designed entirely in-house. Meta is working with Broadcom on the design and Taiwan Semiconductor Manufacturing Co. (TSMC) for fabrication, hoping to drastically reduce its dependence on expensive third-party suppliers like Nvidia and Advanced Micro Devices. However, the cost of achieving that independence is staggering. The memo revealed that Meta plans to deploy seven gigawatts of computing infrastructure this year and double that capacity by 2027. To get there, the company expects to spend as much as $145 billion on AI infrastructure this year alone. This represents a massive chunk of Big Tech's projected $700 billion industry-wide outlay, and it is this aggressive capital expenditure that weighed on the stock. Investors historically penalize tech giants when massive infrastructure bills threaten short-term margins before yielding clear revenue. Adding to the financial pressure, Meta is locking in long-term supply agreements with Samsung Electronics, Sandisk, and Sumitomo Electric to secure the components needed for this expansion. Because every tech giant is rushing to build out data centers at the same time, prices for memory and AI chips are skyrocketing. Morgan Stanley analysts recently warned that this surge has triggered "chipflation," turning skyrocketing infrastructure costs into a broader macroeconomic concern that could further squeeze Meta's bottom line in the quarters ahead.