Micron’s revenue quadrupled as AI memory demand pushes gross margins above 81 percent



TL;DR

Micron Q3 revenue hit $41bn, quadrupling year-over-year on surging AI memory demand, with gross margins above 81 percent and Q4 guidance of $50bn.

Micron Technology posted fiscal third-quarter revenue of nearly $42bn, quadrupling from just over $9bn a year earlier and beating Wall Street estimates by a wide margin. The results, reported on Tuesday, confirm that the company riding the AI memory boom hardest is the one whose stock has already climbed roughly 700 percent over the past year.

Adjusted earnings came in above $25 a share, compared with analyst expectations of roughly $21. GAAP net income exceeded $28bn, or nearly $25 a share, up from just under $2bn in the year-ago quarter. Gross margins hit above 81 percent, up from 69 percent in the prior quarter and 27 percent a year earlier.

The headline number is revenue growth. Micron brought in nearly $42bn against a consensus estimate of roughly $36bn, driven almost entirely by surging demand for high-bandwidth memory, the stacked DRAM chips that sit next to GPUs inside AI accelerators built by Nvidia and Google. HBM has become the binding constraint on AI infrastructure expansion, and Micron is one of only three companies in the world that can make it.

CEO Sanjay Mehrotra said Micron can currently fulfil only between half and two-thirds of customer demand for HBM. The company’s entire 2026 HBM supply is sold out under multi-year contracts, and it has collected $22bn in customer cash deposits, essentially prepayments from hyperscalers desperate to lock in supply.

Micron’s next-generation HBM4 chips are ramping what the company described as twice as fast as the previous HBM3E generation. HBM4 revenue has already exceeded one billion dollars. The technology is essential for the latest accelerators from Nvidia and Google, where memory bandwidth rather than raw compute increasingly determines inference throughput.

The forward guidance was equally aggressive. Micron projected fiscal fourth-quarter revenue of approximately $50bn, plus or minus one billion, against analyst estimates of roughly $44bn and a year-ago figure of just over $11bn. The company raised its full-year capital expenditure forecast to more than $25bn, up from a previous target of $20bn, to expand production capacity for HBM and advanced DRAM.

Micron’s market capitalisation crossed one trillion dollars on 26 May, making it the latest memory chipmaker to reach that threshold as the AI-driven memory supercycle reshapes valuations across the semiconductor industry. The stock’s roughly 700 percent gain over the past year reflects a market that is pricing memory not as a cyclical commodity but as structural AI infrastructure.

The company said it expects the total addressable market for HBM to grow at a compound annual rate of roughly 40 percent through 2028, rising from approximately $35bn in 2025 to around $100bn. Micron plans to return 100 percent of excess free cash flow to shareholders, a commitment enabled by the cash deposit programme that reduces the capital risk of its expansion.

There are caveats worth noting. Micron remains the smallest of the three HBM suppliers, behind SK Hynix and Samsung, and its share of Nvidia’s HBM4 allocations is the thinnest of the trio. The broader memory market is also shifting, with Chinese manufacturers like CXMT expanding aggressively into consumer DRAM segments that the Big Three have deprioritised in favour of AI chips.

Memory pricing is cyclical by nature, and the current supercycle depends on hyperscaler capital expenditure continuing at its current pace. If AI infrastructure spending slows or HBM supply catches up with demand, the margins that Micron reported this quarter would compress rapidly. The 81 percent gross margin is historically extraordinary for a memory company and reflects shortage economics as much as product superiority.

For now, the numbers speak for themselves. Revenue that quadruples in a year, margins that triple, and a guidance print that exceeds estimates by more than $6bn are not normal results for any company, let alone one that was losing money two years ago. Micron’s earnings confirm that the AI memory shortage is intensifying, not easing, and that the companies making the chips inside AI accelerators are capturing value at a rate the market is still recalibrating to price.



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Meta stripped NameTag facial recognition code from its AI app one day after WIRED exposed it on 50 million phones. Meta says no decision has been made.

Meta removed nearly all traces of an unreleased facial recognition system from its smart glasses companion app on Friday, one day after WIRED reported that the software had been quietly embedded in an app installed on more than 50 million phones. The feature, which Meta internally called NameTag, was designed to convert faces captured by the company’s Ray-Ban smart glasses into unique biometric signatures and compare them against a database stored on the user’s device. WIRED also found that faces the system failed to recognise were cropped, indexed, and stored locally for future processing.

Andy Stone, Meta’s vice president of communications, told WIRED on Monday that the feature is “purely exploratory,” adding that no final decision has been made on what to do with it. That characterisation sits uneasily with the evidence WIRED documented. The version of Meta AI published the day of WIRED’s Thursday report contained several code libraries explicitly named for face recognition, a process for running the NameTag recognition pipeline, and a “Person recognised” alert the app would have shown if someone were identified.

Friday’s release stripped all of it out, along with a folder where the app would have stored the cropped images and biometric signatures of unrecognised faces. Meta did not answer WIRED’s questions about why the code was removed or whether the changes were planned before the story was published. A few fragments remain in the latest version, including an internal debug menu label and a dormant link meant to open a recognised person’s profile, pointing to parts of the system that are no longer there.

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The gap between Meta’s public statements and the code WIRED found is the central tension. Before the Thursday report, Stone dismissed the findings by writing that the company could not answer questions about how the system would work because “the feature does not exist.” Andrew Bosworth, Meta’s chief technology officer, called the reporting “incredibly misleading” and “absolutely dishonest.” Yet the code was functional enough to include three AI models, one to detect faces, another to crop them, and a third to encode them as biometric data, all embedded in the companion app for a product already at the centre of a mounting privacy crisis.

Meta declined to answer ten questions WIRED posed before publishing, including whether it had already created the database of face profiles NameTag uses, how long the app retains photographs and biometric data of unrecognised people, and whether that data would ever be sent back to Meta’s servers. The company also did not respond to questions about whether it was building NameTag for blind or low-vision users, or to criticism from privacy advocates who warned the system could let stalkers and abusers identify strangers in public.

NameTag first surfaced in February, when The New York Times, citing internal Meta documents, reported that the company was developing face recognition for its smart glasses and considering a launch as early as this year. One internal memo reportedly described releasing the feature during a “dynamic political environment” when privacy and civil liberties advocates would be distracted by other concerns. WIRED subsequently found that much of NameTag’s machinery had been built into the Meta AI app as early as January, months before any public acknowledgement, adding another layer to the company’s pattern of shipping first and disclosing later when it comes to its smart glasses.

Kade Crockford, director of the technology for liberty programme at the American Civil Liberties Union of Massachusetts, said the removal does not undo the original decision to ship the code and pointed to it as evidence that consumer privacy needs stronger legal protection than Congress has been willing to provide. The Massachusetts House of Representatives last week unanimously passed a consumer privacy bill that, if enacted as written, would impose strong enforcement provisions including a private right of action allowing aggrieved users to sue. “State lawmakers need to do their job and step up to protect consumer privacy,” Crockford said.

Meta’s sneaky tactics in slipping the face-recognition code into its smart glasses show exactly why data privacy bills need the teeth of strong enforcement,” Crockford added. “Companies like Meta prioritise their bottom line, so lawmakers need to speak in the only language its C-suite understands.” Whether a code removal prompted by investigative reporting constitutes a victory or merely a tactical retreat depends on what Meta does next, and on whether the regulatory pressure building on both sides of the Atlantic produces enforceable consequences before the feature quietly returns under a different name.



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