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Chip race: Microsoft, Meta, Google, and Nvidia battle it out for AI chip supremacy

The rise of generative AI has been powered by Nvidia and its advanced GPUs. As demand far outstrips supply, the H100 has become highly sought after and extremely expensive, making Nvidia a trillion-dollar company for the first time.

It’s also prompting customers, like Microsoft, Meta, OpenAI, Amazon, and Google to start working on their own AI processors. Meanwhile, Nvidia and other chip makers like AMD and Intel are now locked in an arms race to release newer, more efficient, and more powerful AI chips.

As demand for generative AI services continues to grow, it’s evident that chips will be the next big battleground for AI supremacy.

  • OpenAI wants in on the AI chip business.

    According to The Information, OpenAI is in discussion with Broadcom and other semiconductor designers about developing its own artificial intelligence chip to address shortages in its supply chain and reduce dependency on Nvidia. OpenAI has apparently also hired former Google chip staffers.

    Bloomberg previously reported in January that OpenAI CEO Sam Altman was planning to raise billions of dollars to set up a network of chip factories.


  • Emma Roth

    Jul 10

    Emma Roth

    AMD will acquire an AI startup for $665 million.

    The Finland-based Silo AI is described as the “largest private AI lab in Europe” and has provided AI solutions for companies like Phillps, Rolls-Royce, and Unilever. In addition to Silo AI, AMD also acquired the AI startup Nod.ai last year as it aims to keep up with the likes of Nvidia.


  • a16z is trying to keep AI alive with Oxygen initiative.

    According to The Information, VC firm Andreessen Horowitz has secured thousands of AI chips, including Nvidia H100 GPUs, to dole out to its AI portfolio companies in exchange for equity. The initiative is aptly named Oxygen, because these chips are that integral to AI companies. The chips are almost impossible to secure for small startups too, because Big Tech companies hoover up all the supply.


  • Softbank is trying to borrow $10 billion for AI-related projects.

    Hey, remember the guy who’s responsible for funding WeWork’s delusional business plan? Softbank CEO Masayoshi Son is really into AI and he’s aiming to flood the area with money. His clearest targets are Nvidia chips and energy startups.


  • Apple Silicon exec joins Rain AI to develop new hardware.

    Bloomberg reports that Rain AI, which has OpenAI CEO Sam Altman as one of its backers, has hired Apple chip exec Jean-Didier Allegrucci to oversee the development of new AI processors that are supposed to reduce power consumption with “in-memory compute.”

    Rain AI:

    [Allegrucci] has worked and led silicon teams across a broad range of applications, including CPUs, GPUs, NPUs, ISPs, SoCs, and many others....At Apple, he oversaw the development of more than 30 SoCs used for flagship products, including iPhones, Macs, iPads, Apple Watch, and many more.


  • Nvidia overtakes Microsoft as the world’s most valuable company

    Vector collage of the Ndivia logo.
    Cath Virginia / The Verge

    Less than two weeks after Nvidia jumped Apple in terms of its overall valuation, the GPU maker has now passed Microsoft to stand as the world’s most valuable company based on the chips it makes that are key to powering a boom in generative AI technology.

    At the close of trading on Tuesday, its share price stood at $135.58, up $4.60 from the previous day and pushing its market cap to $3.335 trillion. That’s more than Microsoft ($3.32 trillion), Apple ($3.29 trillion), and Google ($2.17 trillion). Nvidia’s shares split 10-for-1 after June 7th, lowering the overall share price, but the spike in the company’s value has been jarring. Its share price has gone up 160 percent in 2024, and the company only passed the $2 trillion mark in February.

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  • Nvidia is the world’s most valuable company at the moment.

    Riding a valuation pumped up by generative AI and its chips that power many of the tools, Nvidia’s market cap has passed not only Apple but now Microsoft, too, at more than $3.3 trillion, as reported by Bloomberg.

    The markets are still open, but the rise has been fast — Nvidia shares are up 160 percent in 2024, passing $2 trillion in February.


    Graph showing the market cap of Apple, Microsoft, and Nvidia since 2019.
    Image: Bloomberg
  • Nvidia is now more valuable than Apple at $3.01 trillion

    Vector collage of the Ndivia logo.
    Image: Cath Virginia / The Verge

    Nvidia has become the second most valuable company in the world. On Wednesday afternoon, the chipmaking giant’s market capitalization hit $3.01 trillion, putting it just ahead of Apple at $3 trillion.

    As Nvidia dominates the AI race with its flagship H100 chip, the company’s market cap has only continued to rise. Nvidia became a $1 trillion company in May 2023, then skyrocketed past $2 trillion in February of this year, making it more valuable than both Amazon and Alphabet.

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  • Even the Raspberry Pi is getting in on AI

    Photo illustration of a computer with a brain on the screen.
    Illustration by Cath Virginia / The Verge | Photos by Getty Images

    As the AI craze continues, even the microcomputer company Raspberry Pi plans to sell an AI chip. It’s integrated with Raspberry Pi’s camera software and can run AI-based applications like chatbots natively on the tiny computer. 

    Raspberry Pi partnered with chipmaker Hailo for its AI Kit, which is an add-on for its Raspberry Pi 5 microcomputer that will run Hailo’s Hailo-8L M.2 accelerator. The kits will be available “soon from the worldwide network of Raspberry Pi-approved resellers” for $70.

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  • Emma Roth

    May 30

    Emma Roth

    Intel, Google, Microsoft, Meta, and more want to standardize the tech used in AI data centers.

    The Ultra Accelerator Link (UALink) Promoter Group, will work to create an open standard to help AI accelerators “communicate more effectively” within data centers and boost performance. Other members include AMD, HP, Broadcom, and Cisco — but not Nvidia, which has AI chip-linking tech of its own.


  • Nvidia will now make new AI chips every year

    Illustration by Alex Castro / The Verge

    Nvidia just made $14 billion worth of profit in a single quarter thanks to AI chips, and it’s hitting the gas from here on out: Nvidia will now design new chips every year instead of once every two years, according to Nvidia CEO Jensen Huang.

    “I can announce that after Blackwell, there’s another chip. We’re on a one-year rhythm,” Huang just said on the company’s Q1 2025 earnings call.

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  • Nvidia just made $14 billion of profit in a single quarter thanks to AI chips.

    Sales jumped 262 percent in Q1 2025 to hit a record $26B in revenue, of which nearly three-quarters ($19.4B) was data center compute — especially its Hopper GPUs for training LLMs and generative AI apps, says Nvidia. Gaming only accounted for $2.6 billion revenue this quarter.

    Nvidia’s expecting record revenue again next quarter — $28B. Shovels in a gold rush, people.


    Image: Nvidia
  • Wes Davis

    May 14

    Wes Davis

    Google announced Trillium, its sixth generation of Tensor processors.

    CEO Sundar Pichai just announced new Trillium chips, coming later this year, that are 4.7 times faster than their predecessors, as Google competes with everyone else building new AI chips. Pichai also highlighted Axion, Google’s first ARM-based CPU, which the company announced last month.

    Google will also be “one of the first” cloud companies to offer Nvidia’s Blackwell GPU starting in 2025.

    Correction: Axion was announced last month, not last year. Also, corrected the spelling of Axion.


    Sundar Pichai on stage at I/O.
    Image: Google
  • Apple plans to use M2 Ultra chips in the cloud for AI

    An illustration of the Apple logo.
    Illustration: The Verge

    Apple plans to start its foray into generative AI by offloading complex queries to M2 Ultra chips running in data centers before moving to its more advanced M4 chips.

    Bloomberg reports that Apple plans to put its M2 Ultra on cloud servers to run more complex AI queries, while simple tasks are processed on devices. The Wall Street Journal previously reported that Apple wanted to make custom chips to bring to data centers to ensure security and privacy in a project the publication says is called Project ACDC, or Apple Chips in Data Center. But the company now believes its existing processors already have sufficient security and privacy components.

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  • Apple’s ‘Project ACDC’ is creating AI chips for data centers.

    Apple — like Google, Meta, Microsoft, OpenAI and everyone else this side of Nvidia — is reportedly working on custom server hardware to power AI models as it prepares to introduce a slew of new features.

    Over the past decade, Apple has emerged as a leading player designing chips for iPhones, iPads, Apple Watch and Mac computers. The server project, which is internally code-named Project ACDC—for Apple Chips in Data Center—will bring this talent to bear for the company’s servers, according to people familiar with the matter.

    Apple watcher Mark Gurman followed up saying a similar-sounding project was canceled and it doesn’t make sense anyway: it would be too expensive, lack differentiation, and Apple prefers on-device AI.

    Update: Added Gurman’s rebuttal.


  • US plans $285 million in funding for ‘digital twin’ chips research

    Illustrations of a grid of processors seen at an angle with the middle one flipped over to show the pins and the rest shrouded in a green aura
    Illustration by Alex Castro / The Verge

    The Biden administration is taking applications for $285 million in federal funding — allotted from the $280 billion CHIPS and Science Act — seeking companies to “establish and operate a CHIPS Manufacturing USA institute focused on digital twins for the semiconductor industry.” The plan for the CHIPS Manufacturing USA institute to establish a “regionally diverse” network to share resources with companies developing and manufacturing both physical semiconductors and digital twins. 

    Digital twins are virtual representations of physical chips that mimic the real version and make it easier to test new processors before they’re put into production to find out how they might react to a boost in power or a different data configuration. According to the press release, digital twin-based research can also leverage tech like AI to speed up chip development and manufacturing in the US.

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  • With $1B in sales, AMD’s MI300 AI chip is its fastest selling product ever.

    AMD also says an AI PC refresh cycle will help PCs return to growth in 2024, and that 150 software vendors will be developing for AMD AI PCs by year’s end. The company’s top priority is ramping AI data center GPUs, though, which are “tight on supply.” New AI chips are coming “later this year into 2025,” too.


    AMD’s Q1 2024 earnings summary.
    AMD’s Q1 2024 earnings summary.
    Image: AMD
  • OpenAI will give you a 50 percent discount for off-peak GPT use.

    OpenAI’s Batch API now lets users upload a file of bulk queries to the AI model, like categorizing data or tagging images, with the understanding that they won’t need immediate attention. Promising results within 24 hours lets them run when there is unused compute power, and keeps those pricey GPUs humming around the clock.


  • Meta’s new AI chips run faster than before

    Image of the Meta logo and wordmark on a blue background bordered by black scribbles made out of the Meta logo.
    Illustration by Nick Barclay / The Verge

    Meta promises the next generation of its custom AI chips will be more powerful and able to train its ranking models much faster. 

    The Meta Training and Inference Accelerator (MTIA) is designed to work best with Meta’s ranking and recommendation models. The chips can help make training more efficient and inference — aka the actual reasoning task — easier. 

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  • Intel launches new AI accelerator to take on Nvidia’s H100.

    Intel first introduced its Gaudi 3 AI accelerator last year, but now the company has revealed more details on performance. When compared to the H100 GPU, Intel says its Gaudi 3 accelerator can deliver “50% faster time-to-train on average across the Llama2 models” with better efficiency.

    The company also says the Gaudi 3 AI Accelerator will be a “fraction of the cost” of Nvidia’s pricey H100. It will become available to companies like Dell, HPE, and Lenovo in the second quarter of this year.


    Image: Intel
  • The US is reportedly working on a list of restricted Chinese chipmaking factories.

    Reuters reports the list could strengthen the Commerce Department’s existing restrictions on US tech shipments to Chinese chip factories. The US government has voiced national security concerns about letting China access US technology to grow its own capabilities.

    US companies have complained it’s difficult to know which Chinese factories produce advance chips and are subject to the restrictions, Reuters says.


  • Inside TSMC’s very secretive chip training facility.

    CNN gained entry into the training facility where TSMC teaches engineers to design and operate the machines that build semiconductors. The hope is to train engineers to “seed” factories it’s building in the US, Japan, and Germany.

    TSMC told CNN that it needs “to hire thousands more” employees to staff facilities around the world as demand for advanced chips grows.


  • A $40 billion AI investment fund?

    That’s what this NYT report says a16z and Saudi Arabia’s Public Investment Fund are considering, which may explain the rumors that Elon Musk (who denied them), Sam Altman, and others looking to the Middle East to fund their AI dreams.

    It also recalls last fall’s news that the US government added an “additional licensing requirement” for Nvidia and AMD AI shipments to unspecified Middle Eastern countries.


  • Nvidia reveals Blackwell B200 GPU, the ‘world’s most powerful chip’ for AI

    The Blackwell B200 GPU.
    The Blackwell B200 GPU.
    Image: Nvidia

    Nvidia’s must-have H100 AI chip made it a multitrillion-dollar company, one that may be worth more than Alphabet and Amazon, and competitors have been fighting to catch up. But perhaps Nvidia is about to extend its lead — with the new Blackwell B200 GPU and GB200 “superchip.”

    Nvidia says the new B200 GPU offers up to 20 petaflops of FP4 horsepower from its 208 billion transistors. Also, it says, a GB200 that combines two of those GPUs with a single Grace CPU can offer 30 times the performance for LLM inference workloads while also potentially being substantially more efficient. It “reduces cost and energy consumption by up to 25x” over an H100, says Nvidia, though there’s a questionmark around cost — Nvidia’s CEO has suggested each GPU might cost between $30,000 and $40,000.

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  • Google engineer indicted over allegedly stealing AI trade secrets for China

    The FBI symbol atop a red, black and white background made of seven pointed stars.
    Illustration by Alex Castro / The Verge

    A federal grand jury has indicted a Google engineer, Linwei Ding, aka Leon Ding, for allegedly stealing trade secrets around Google’s AI chip software and hardware on March 5th, before he was arrested Wednesday morning in Newark, California. Deputy Attorney General Lisa Monaco said in a statement that Ding “stole from Google over 500 confidential files containing AI trade secrets while covertly working for China-based companies seeking an edge in the AI technology race.” 

    Much of the stolen data allegedly revolves around Google’s tensor processing unit (TPU) chips. Google’s TPU chips power many of its AI workloads and, in conjunction with Nvidia GPUs, can train and run AI models like Gemini. The company has also offered access to the chips through partner platforms like Hugging Face

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