AI data centers Archives

Western Digital has sold out its entire 2026 HDD production capacity. Every drive the company will manufacture this year is already spoken for, committed through long-term agreements to the seven largest cloud and AI infrastructure customers on the planet. On January 29, 2026, during the company’s Q2 earnings call, CEO Irving Tan confirmed what had been building for months: consumer buyers and PC manufacturers are no longer the priority. They are barely an afterthought.

The numbers tell the story with surgical clarity. Western Digital’s cloud segment now accounts for 89% of the company’s total revenue. The consumer segment has collapsed to 5%. Two of the long-term agreements extend into 2027. One reaches into 2028. This is not a temporary squeeze. It is a structural reallocation of global storage production toward AI data centers, and it mirrors a pattern that should alarm anyone who builds, upgrades, or repairs their own computer.

Full Allocation, Zero Slack

Seagate, the only other major HDD manufacturer, is in the same position: fully allocated. Between the two companies, the global supply of high-capacity hard drives is locked up. HDD prices have reached their highest point in two years, and the trajectory points in one direction.

The demand is not mysterious. The same AI capital expenditure frenzy that has Amazon, Alphabet, Meta, and Microsoft committing over $650 billion to infrastructure in 2026 requires storage at a scale that dwarfs what consumer electronics ever demanded. Training datasets measured in petabytes. Inference logs accumulating continuously. Backup and redundancy requirements that multiply every primary storage investment by three or four times. HDDs remain the most cost-effective option for mass storage at data center scale, and the hyperscalers are buying every last one.

The Consumer Squeeze

There was a time, not long ago, when building a PC was one of the most accessible hobbies in technology. A few hundred dollars, a weekend, a YouTube tutorial. Storage was the easiest component to source. A 2TB drive cost less than dinner for two. That era is ending, and the forces killing it are not accidental.

AI companies are outbidding regular consumers for the same physical hardware. This is not a metaphor. It is a direct allocation decision made by manufacturers who have concluded, correctly from a revenue standpoint, that selling drives by the hundred thousand to cloud providers is more profitable than selling them one at a time to a builder in Phoenix or a small business in Ohio.

The pattern extends beyond storage. RAM prices are already climbing as memory manufacturers redirect capacity toward AI accelerators and data center modules. GPUs were captured years ago by crypto miners and then AI training clusters. Now storage joins the list. Component by component, the AI buildout is straining the physical infrastructure that once served a broad consumer market, and concentrating it into a narrow pipeline that serves a handful of corporate buyers.

What “Sold Out” Actually Means

When a manufacturer says their capacity is “sold out,” the phrasing obscures a choice. Western Digital is not a mine that has been emptied. It is a factory that has decided whom to serve. The company could, in theory, reserve a portion of production for the consumer and OEM channels that sustained its business for decades. It has chosen not to, because the economics of AI storage contracts are too attractive to leave capacity on the table.

This is rational corporate behavior. It is also a signal that the consumer technology market, the one that made personal computing accessible and affordable, is being deprioritized by its own supply chain.

A reasonable counterpoint: SSDs are getting cheaper and faster. The consumer market never needed HDDs to survive. Solid state storage prices have fallen dramatically over the past five years, and for most PC builders, an SSD is already the default boot and gaming drive. The HDD squeeze may accelerate a transition that was happening anyway, and consumers could come out better for it with faster, more reliable storage at competitive prices. The real losers are budget builders and anyone who needs bulk storage on the cheap, a meaningful but narrowing demographic. The broader consumer market might absorb this shift without catastrophic harm.

I built my PC during a window when components were cheap and the hobby was genuinely accessible to anyone willing to spend a weekend learning. That window is closing, and it is not closing because of some natural market cycle. It is closing because companies worth hundreds of billions decided they need every hard drive on the planet more than you do. The SSD transition argument is real, but it misses the point. The issue is not whether consumers can survive without HDDs. The issue is that an entire tier of affordable, high-capacity storage just got pulled out from under regular people, and nobody asked them.

What This Means for Everyday People

If you are planning a PC build in 2026, budget more for storage than you did last year. HDD prices will rise and availability will thin, especially for high-capacity drives in the 8TB to 20TB range that data hoarders and creators rely on. OEM manufacturers like Dell and HP will absorb some of these costs and pass the rest along, which means laptop and desktop prices will reflect the squeeze even if you never buy a bare drive.

The broader lesson is one that keeps repeating across every corner of hardware manufacturing. The AI buildout is not a parallel economy that exists alongside the consumer market. It is a competing economy that draws from the same finite pool of silicon, memory, storage, and power. When a company worth billions competes with a hobbyist for the same hard drive, the hobbyist loses. Every time.

Storage is the latest casualty. It will not be the last., reported by Tom’s Hardware

For inquiries and analysis contact laterstack@proton.me

Microsoft is testing high-temperature superconductor (HTS) cables to power its AI data centers, a technology that eliminates electrical resistance entirely. Zero voltage drops. Zero heat generation from the cables themselves. VEIR, a Massachusetts-based startup backed by Microsoft, completed a successful test of its 3-megawatt superconducting cable powering a server rack in a simulated data center environment. The pitch is elegant: replace the copper arteries of a data center with superconducting ones, and the power delivery problem shrinks by an order of magnitude. The cables themselves can be more than 10x smaller and lighter than their copper equivalents.

It is a genuinely impressive piece of engineering. It also will not matter for years, and the communities whose power grids are being consumed by AI expansion right now cannot wait that long.

The Physics Works. The Calendar Does Not.

The science behind HTS cables is well established. Cool certain ceramic materials below a critical temperature using liquid nitrogen, and they conduct electricity with zero resistance. No energy lost as heat in transmission. No need for massive copper bus bars and the ventilation systems required to cool them. Microsoft’s research team envisions replacing overhead power line corridors with compact underground HTS trenches, collapsing the physical footprint of data center power infrastructure dramatically. American Superconductor (AMSC), traded on NASDAQ, is a primary supplier of the HTS wire and systems that make this possible.

VEIR closed a $75 million Series B round with Microsoft among the investors. The test validated that the technology performs as promised under data center load conditions. But validated performance in a controlled simulation and deployed performance at production scale are separated by years of engineering, regulatory approvals, and reliability testing. The current pilots are still evaluating long-term maintenance costs of the liquid nitrogen cooling systems that keep the cables in their superconducting state. This is pre-deployment work. Microsoft is not installing HTS cables in Azure data centers next quarter. It is studying whether HTS cables might be viable for Azure data centers in the future.

The Gap Between Innovation and Relief

Power is the single largest bottleneck constraining AI data center expansion. Not GPUs. Not talent. Not capital. Power. The electricity cost pressures that AI data centers are already imposing on local communities are not theoretical. They are showing up in utility rate filings, in city council debates, in the monthly bills of families who live near facilities they never asked for. When a hyperscaler breaks ground on a new campus, the local grid absorbs the impact immediately. Utility companies file for rate increases. Residential customers subsidize industrial consumption through higher bills and degraded grid reliability.

The scale of capital flowing into AI infrastructure makes this a structural problem, not a temporary one. Big Tech is pouring hundreds of billions into data center construction right now, using copper cables, drawing from existing grids, and socializing the costs onto local ratepayers. HTS cables might eventually reduce the power lost in delivery. They do nothing to reduce the total power consumed by the facilities themselves. A data center running on superconducting cables still demands the same megawatts from the grid. It just wastes fewer of them in transit.

This distinction matters. The coverage of Microsoft’s HTS testing has treated it as a solution to the widening gap between AI energy consumption and available supply. It is not. It is an efficiency improvement to the plumbing. An important one, potentially, but not a fix for the fact that the reservoir is running dry.

The counterargument deserves serious consideration. Efficiency improvements compound. If HTS cables eliminate even 5 to 8 percent of power losses in distribution within a data center campus, that represents meaningful megawatts recovered at scale. A facility drawing 500 megawatts could reclaim 25 to 40 megawatts through zero-resistance transmission alone. That is power equivalent to tens of thousands of homes, freed without building a single new generation source. Multiply this across every hyperscaler campus worldwide, and the aggregate impact is substantial. Dismissing efficiency gains because they do not solve the entire problem is a fallacy. Every grid technology we rely on today was once a pilot that skeptics called insufficient.

That critique is fair, and it still sidesteps the timing question. The communities absorbing the grid strain of AI expansion today are not helped by a technology that might deploy at scale in five to seven years. Efficiency gains that arrive after the damage is done are retrospective improvements, not solutions. Microsoft’s superconductor research is a long bet on future infrastructure. It does not address the present reality that data centers are pulling power from grids built for cities, not server farms, and that the people living in those cities are footing the bill through higher rates and reduced reliability.

The production timeline is the part nobody wants to talk about honestly. This is years away from deployment. Maybe a decade before it shows up in enough facilities to matter at scale. Meanwhile the data centers are going up right now, pulling power from grids that were sized for residential neighborhoods and small businesses, not for buildings that consume more electricity than some towns. Superconducting cables are a solution to a future version of this problem. The current version, where families in Virginia and Texas and Arizona are watching their utility bills climb because a hyperscaler moved in next door, does not get fixed by a lab test in Massachusetts.

What This Means for Everyday People

If you live near a data center or in a region where one is planned, superconducting cables are not coming to help you anytime soon. The technology is real, the timeline is long, and the power draw on your local grid is happening now. Utility rate increases driven by data center demand are already being approved in multiple states. The benefits of AI accrue to shareholders and users of cloud services. The costs accrue to the communities that host the physical infrastructure. Until that asymmetry is addressed through regulation, rate structures, or technology that actually reduces total consumption rather than just improving delivery efficiency, the people closest to the machines will continue paying the highest price for progress they did not choose., Tom’s Hardware reported

For inquiries and analysis contact laterstack@proton.me

TORONTO – Bitfarm, a major Bitcoin mining operator with twelve cryptocurrency facilities, announced a strategic pivot from mining digital assets to providing AI data center services by 2027. The company plans to leverage its existing energy infrastructure to deploy large-scale Nvidia-powered server racks, including the GB300 NVL72 units.

CEO Ben Gagnon stated that the company’s energized capacity of 341 megawatts allows rapid scaling without long delays from local authorities or utility negotiations. The move positions Bitfarm as a competitive player in AI workloads, providing infrastructure faster than other hyperscalers constrained by power and facility limitations.

Infrastructure Advantage and Facility Upgrades

Bitfarm plans to convert its Washington facility into a GPU-as-a-service site using state-of-the-art liquid cooling, while its Panther Creek, Pennsylvania location could reach 350 megawatts. The company has converted a $300 million debt facility from Macquarie to fund these AI-focused operations.

“Despite being less than 1% of our total developable portfolio, we believe that the conversion of just our Washington site to GPU-as-a-service could potentially produce more net operating income than we have ever generated with Bitcoin mining,” said Gagnon.

This pivot allows Bitfarm to diversify beyond cryptocurrency, which has suffered from price volatility and operational instability. The company reported a $46 million third-quarter loss due in part to fluctuating Bitcoin performance and underperforming mining rigs.

Market Context and Risks

The AI infrastructure pivot comes amid controversy over cryptocurrency tax investigations, where hundreds of millions of dollars’ worth of GPUs were implicated. While Bitfarm’s existing energy assets reduce entry barriers, companies investing billions in specialized AI infrastructure face potential losses if the AI market encounters a downturn.

Bitfarm’s move highlights a broader trend of cryptocurrency miners repurposing resources to meet growing demand in AI computing, where high-performance GPUs and power-intensive facilities are increasingly valuable.

Looking Ahead

Bitfarm’s AI pivot represents a significant shift in the blockchain and crypto mining industry, emphasizing adaptability and the importance of diversified operations. By leveraging existing power reserves and facility infrastructure, the company is well-positioned to capture opportunities in GPU-based AI workloads while mitigating exposure to cryptocurrency market volatility.