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HKYNC News & Views November 8, 2026 – Executive Summary & References
Hickory Hound News & Views Archive
Executive Summaries for all News & Views are up to date!!!
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Examines October’s economy from Hickory households to international markets. Its Strategic Summary and Hound’s Reminder test whether expanding production and industrial investment are delivering lasting financial security. The Grok Macro-Micro Report tracks employment, manufacturing, fuel prices, and regional projects; ChatGPT’s Intelligence Briefing contrasts stronger GDP with weaker purchasing power and hiring. The six-level report examines bankruptcy pressures, Catawba County investments, Helene recovery, statewide employment, national inflation, and global trade. The Pattern Emerging identifies gaps between capital and household outcomes, while the 30-day outlook highlights key upcoming economic indicators and local project milestones.
The next ESR will be released on the evening of Tuesday November 17th.
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Monday Mashup - Economic Stories of Relevance — 2022 - examines how inflation, Russia’s invasion of Ukraine, and rapid interest-rate hikes transformed the recovery into an era of economic restraint. Households faced shrinking purchasing power, expensive gasoline, declining savings, and rising borrowing costs despite strong employment. Hickory and Catawba County added manufacturing jobs while major data-center investments signaled a shift toward capital-intensive development. Across the Foothills Corridor, diverse industries confronted higher operating costs. North Carolina attracted record industrial investment, while national housing slowed and global energy markets fractured. The report concludes that growth persisted, but financing and operating productive capacity had become increasingly expensive.
Upcoming: Monday Mashup - Economic Stories of Relevance — 2023 - examines a year when inflation eased, employment remained resilient, and high interest rates reshaped economic opportunity. From household budgets and housing affordability to Hickory’s fiber-optic expansion, Foothills industrial reuse, and North Carolina’s manufacturing investments, the report traces the widening gap between capital commitments and immediate job growth. National banking failures exposed financial vulnerabilities, while federal incentives accelerated strategic construction. Internationally, sluggish trade and shifting supply chains signaled a changing economic order. Across six reporting levels, 2023 emerges as a year of resilience under restraint, not a return to familiar pre-pandemic economic conditions.
Opening Reflection
The Price of Human Potential
For much of the personal computer's history, technological progress came with a promise that ordinary people could understand: as computers became more powerful, the cost of putting that power into your own hands generally came down. What once required a room full of expensive equipment and a staff of specialists could eventually be accomplished by one person sitting at a desk, working from home, or trying to turn an idea into something useful.
That transformation changed much more than the computer industry. It changed what individuals were capable of accomplishing without having to depend on large institutions, corporations, or government agencies.
A student could learn programming without enrolling in an expensive technical program. A mechanic could research complex repairs and manage a business without hiring an office staff. Writers, photographers, accountants, designers, researchers, and entrepreneurs gained access to tools that once required considerable financial resources. A person could purchase equipment that allowed them to be creative and solve complex problems at levels previously inconceivable.What made this revolution remarkable wasn't simply that computers became faster. It was that their growing capabilities became increasingly affordable.
For decades, additional memory allowed people to tackle larger projects, expanded storage made it practical to preserve years of work, and improvements in processing power opened doors to activities that had once been too expensive or technically demanding. A computer purchased for a reasonable price could become considerably more useful with a few upgrades. Rather than having to replace everything, people could often build upon what they already owned.
The personal computer became more than another household appliance. It became an investment in an individual's ability to do things independently. It could serve as a library, drafting table, printing press, accounting department, communications center, and creative workshop, all within the same machine.
At its core, a personal computer is really just a tool you own, giving you the freedom to create and work on your own terms.
That is why it matters so much—a computer's real value isn't just about the price tag. Its greater value lies in what that person can accomplish with it over time.
Unfortunately, the economics that helped make personal computing widely accessible are currently facing a daunting challenge.
According to technology research firm Gartner, the combined prices of computer memory and solid-state storage are projected to increase by 130% by the end of 2026 compared with 2025. Those component costs are expected to push average personal computer prices up approximately 17% higher. Gartner also estimates that memory, which accounted for roughly 16% of the cost of manufacturing a PC in 2025, could represent as much as 23% of the cost in 2026.
The firm initially projected worldwide PC shipments would decline 10.4% during 2026. Its preliminary third-quarter results subsequently showed a 22.4% decline compared with the same quarter in 2025, as rising component costs made new computers more expensive and discouraged purchases. 1 2
For anyone unfamiliar with computer hardware, those figures might sound like another complicated problem involving electronic components. But the consequences are much easier to understand than the terminology.
Computer memory, commonly called RAM, provides the working space a computer needs while performing tasks. Think of a carpenter trying to build something on a workbench. The carpenter might have all the necessary tools and materials, but if the workbench is too small, everything becomes more difficult. Additional working space allows more parts of the project to be handled at once.
Computer storage, whether on a traditional hard drive or a newer solid-state drive, serves a different purpose. It is where documents, photographs, programs, business records, and completed projects are kept for future use.
The more demanding the work becomes, the more important these capabilities can be. A person editing videos, creating detailed designs, managing large amounts of information, or experimenting with artificial intelligence may need substantially more computing capacity than someone who primarily browses the internet or sends emails.
When memory and storage become considerably more expensive, the effects reach beyond the price of a new laptop. Upgrading an existing computer becomes more costly, replacing worn-out equipment becomes harder to justify, and people with limited financial resources may have to postpone projects or settle for machines that cannot adequately handle the work they want to accomplish.
A large corporation can usually absorb a few hundred dollars in additional equipment costs. A student, a family operating on a tight budget, or someone attempting to start a small business may not have that flexibility.
What looks like inflation in the computer industry can become a barrier to individual creativity, economic opportunity, and personal independence.
This is especially relevant in the Catawba Valley because our region is becoming an increasingly important part of the infrastructure supporting the world's expanding computing economy.
Microsoft is developing data centers in Catawba County as part of an announced investment of at least $1 billion over 10 years. Google has operated a major data-center facility in Lenoir since 2008, following its initial investment announcement in 2007. Meanwhile, Corning is expanding optical cable manufacturing in Hickory to help meet the enormous demand for high-speed connections between computers and data centers, supported by a multiyear agreement with Meta valued at up to $6 billion. 3 4 5
These developments represent real economic opportunities. They support manufacturing, construction, technical employment, investment, and the growth of industries that may become increasingly important to our regional economy.
But they also illustrate a larger contradiction emerging across the technology industry.
The same worldwide expansion of artificial intelligence and data centers that is creating demand for new infrastructure is also increasing competition for the semiconductor manufacturing capacity needed to produce memory and storage. Manufacturers have strong financial incentives to serve large institutional customers purchasing enormous quantities of specialized, highly profitable components. That can leave manufacturers of personal computers facing higher costs and tighter supplies.
We are helping build the infrastructure that allows some of the world's largest technology companies to operate increasingly powerful computing systems. Yet at the same time, the ordinary individual may find it more expensive to acquire or upgrade a capable computer at home.
There is nothing inherently wrong with artificial intelligence, data centers, or cloud computing. These technologies provide tremendous benefits and make it possible to accomplish things that would be impractical using a personal computer alone. They can expand the opportunities available to individuals and businesses, and they deserve a place in our economic future.
The concern is whether this progress will continue to strengthen the capabilities of ordinary people or gradually make them more dependent on purchasing access to computing power owned and controlled by someone else.
There is a meaningful difference between having access to technology and having the ability to own and control the tools necessary to use it independently.
An internet connection and a subscription can provide access to extraordinary services, but that arrangement is not the same as owning a computer capable of storing your work, running demanding applications, and supporting your own projects without relying entirely on an outside provider. Both approaches have value, and people should have the practical ability to choose between them.
For much of the last half-century, the personal computing revolution gave individuals greater freedom to learn, experiment, produce, and compete. The declining cost of computing capability helped remove barriers that had historically separated ordinary people from the resources available to large organizations.
We should be concerned if that relationship begins moving in the opposite direction.
The issue isn't whether artificial intelligence represents technological progress. It certainly does. Nor is it whether the enormous investments being made in computing infrastructure can benefit our economy. They can, and in many cases they already do.
The more important question is whether the benefits of that progress will remain within reach of the people whose ideas, labor, and creativity ultimately give technology its purpose.
If society continues producing more computing power than ever before, but ordinary people find themselves increasingly unable to afford the tools needed to use that power independently, what exactly are we gaining?
That is the question behind the rising cost of computer memory, and it is a much larger issue than the price of a few electronic components.
Ultimately, we should measure technological progress not only by how powerful our machines become, but also by how much they expand the potential of the human beings to access and use them.
The Feature
The Silicon Enclosure: How AI Hardware Inflation is Choking Personal Independence and Limiting Potential
Sometimes an important economic discovery begins with something as ordinary as shopping for a computer. You aren't necessarily looking for a major technological breakthrough or trying to understand the future of artificial intelligence. You're simply attempting to purchase something useful, improve a piece of equipment you already own, or make your work a little easier. Then you encounter a price that doesn't make sense, and what appeared to be a routine purchase turns into a much larger question about what is happening in the marketplace.
That's essentially how this investigation began. I was examining a compact personal computer costing approximately $716, equipped with 32 gigabytes (GB) of memory and a 1-terabyte solid-state drive. It was a capable machine, but I wanted to understand what it would cost to increase its memory to 64GB, providing additional working capacity for more demanding analytical projects. What I encountered was surprising. Some listings for compatible DDR5 memory approached or exceeded $1,000, meaning that a memory upgrade could cost more than the computer itself. Those listings weren't necessarily typical of every retailer or available product, but the prices were high enough to make me question what was happening.
For decades, one of the greatest advantages of owning a personal computer was the ability to improve its capabilities without replacing the entire machine. More memory meant you could work with larger files, operate more demanding programs, and accomplish tasks that might otherwise overwhelm your equipment. Larger storage drives allowed you to keep more information, while faster processors reduced the time required to complete complicated work. Upgrading was often a practical way to extend the life of your investment, and over the years, the amount of computing power available for a reasonable price generally improved.
Now, something about that relationship appears to be changing. The more I examined memory prices, the more I discovered that the problem wasn't limited to a few expensive components or unusual retail listings. The emerging picture involved semiconductor manufacturers, global investments in artificial intelligence, the rapid expansion of data centers, and an increasingly competitive struggle for the physical resources necessary to manufacture computer memory and storage.
What began as a question about the cost of upgrading a personal computer eventually led to something much more consequential: Are we entering a period when the technology industry's pursuit of greater computing power makes it increasingly difficult for ordinary people to afford independent computing power of their own?
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Part I — The Upstream Squeeze: Where the Memory Is Going
To understand why computer memory has become so expensive, we first need to understand something fundamental about artificial intelligence and cloud computing. Although we often describe these technologies as services operating somewhere on the internet, they depend on enormous quantities of physical equipment. Every interaction with a major AI system requires computers to process information, and those computers depend on processors, memory, storage, electrical connections, cooling equipment, and communications networks. The cloud isn't an imaginary place where information floats around without physical limitations. It consists of actual machines operating inside buildings, consuming resources, and requiring continuous investment.
Memory plays a particularly important role in this process because computers must be able to retrieve and move information quickly while performing calculations. Ordinary personal computers generally use dynamic random-access memory, commonly called DRAM, to provide temporary working space for the operating system and applications. Think of memory as the work surface available to someone building a complicated project. A larger workbench allows more materials and tools to remain accessible at the same time, making it easier to work efficiently. Without enough space, the person must constantly rearrange things, slowing the entire process.
Advanced AI processors frequently depend on a specialized type called high-bandwidth memory, or HBM. This memory is designed to move enormous amounts of information at very high speeds, which is essential when powerful processors are performing billions of calculations. However, manufacturing it requires considerably more semiconductor resources than producing comparable amounts of conventional computer memory. Micron, one of the world's major memory manufacturers, has explained that its HBM3E generation requires approximately three times as much silicon as DDR5 memory to produce the same number of bits. The company expects the manufacturing difference to become even greater with newer generations, potentially exceeding four to one with HBM4E. (Micron)
This doesn't mean that every specialized AI memory chip directly replaces three or four ordinary memory chips. The distinction is important because we're discussing manufacturing resources rather than a simple exchange of finished products. Semiconductor manufacturing begins with thin circular slices of silicon called wafers, which are processed into large numbers of electronic components. When one type of memory requires substantially more wafer area to deliver the same storage capacity, expanding production of that memory can reduce the manufacturing resources available for other products.
The scale of this competition is becoming significant. According to TrendForce, high-bandwidth memory is expected to account for approximately 22% of the DRAM wafer input used by the three largest memory suppliers by the end of 2026, even though it will represent only about 9% of the total DRAM memory capacity they produce. This means specialized memory used in advanced computing consumes a much larger share of manufacturing resources than its share of total output might suggest. As demand for AI infrastructure grows, that imbalance places additional pressure on an industry already operating with limited production capacity. (TrendForce)
Expanding semiconductor manufacturing isn't as simple as adding another production line at a conventional factory. New facilities can require billions of dollars, highly specialized equipment, advanced engineering, and years of planning before meaningful quantities of finished products become available. Manufacturers must therefore make decisions about how to use the capacity they already possess. When enormous technology companies are prepared to purchase specialized memory through substantial long-term agreements, suppliers have powerful financial incentives to direct resources toward those customers.
There doesn't have to be anything malicious about this process. From the manufacturer's perspective, producing high-demand components for major customers can be a perfectly rational business decision. But when many companies make similar decisions at the same time, the collective consequences can be quite different from what any one company intended. The industry may generate impressive profits and expand its most advanced products while leaving the ordinary consumer market competing for increasingly expensive supplies.
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Part II — The Market Fallout:
When Affordable Computers Become Less Capable
The effects of these manufacturing decisions eventually appear in the products available to consumers. Computer manufacturers must purchase memory, processors, storage, displays, batteries, and numerous other components before they can assemble and sell a finished machine. When the price of one essential component increases dramatically, manufacturers must either absorb that expense, raise their selling prices, or reduce costs elsewhere. For companies already competing in the low-priced computer market, there may not be much room to absorb additional costs without losing money.
The numbers emerging during 2026 illustrate how serious the situation has become. In February, technology research firm Gartner projected that combined DRAM and solid-state-storage prices would rise approximately 130% by the end of the year compared with 2025. The firm estimated that these increases would push average personal computer prices roughly 17% higher, while memory's share of the cost of manufacturing a PC would rise from approximately 16% to 23%. Gartner initially expected worldwide PC shipments to decline 10.4% during 2026, reflecting the growing difficulty of maintaining affordable prices. (Gartner, February 26, 2026)
By October, the market was showing even more severe signs of strain. Gartner's preliminary third-quarter figures indicated that worldwide PC shipments had fallen 22.4% compared with the same quarter in 2025. The firm reported that memory costs, particularly DRAM, had risen dramatically and that manufacturers were passing those expenses along through higher retail prices. Instead of concentrating on affordable entry-level products, some manufacturers were giving greater priority to more expensive configurations where stronger profit margins made rising component costs easier to manage. (Gartner, October 12, 2026)
Consider what this means to someone purchasing a basic computer for school, work, or a small business. A machine that previously included enough memory and storage for several years of productive use may now cost considerably more, while a less expensive alternative may offer fewer capabilities. The person shopping for that computer faces a choice between paying more than originally planned or accepting limitations that could become frustrating as software and workloads grow more demanding. What looks like a technical issue involving semiconductor prices eventually becomes an ordinary household decision about what someone can afford to accomplish.
Gartner has warned that the market for new personal computers costing less than $500 could effectively disappear by 2028 if current conditions persist. The firm also expects consumers to keep their computers longer, with replacement cycles stretching as purchasing new equipment becomes more expensive. Holding onto an older computer can certainly be sensible, but there are limits to how long aging equipment can remain useful, especially when new software requires additional memory, newer processors, or updated operating systems. Delaying replacement may save money initially while creating other difficulties involving performance, compatibility, and security.
This is where the familiar economic concept of shrinkflation becomes relevant. We generally associate the term with groceries, where the quantity inside a package decreases even though the price remains the same or rises. In computing, shrinkflation can take the form of less memory, reduced storage, fewer upgrade options, or higher prices for equipment offering essentially the same productive capabilities. The consumer may still receive a perfectly functional computer, but the amount of useful computing power available for an affordable price has declined.
The larger concern involves the opportunities that disappear when adequate equipment becomes too expensive. A student learning engineering or software development needs more than basic internet access. A photographer, designer, or independent filmmaker may need substantial memory and storage to work with original material. Someone starting a business may depend on a computer for accounting, research, communications, and managing daily operations. These people aren't purchasing technology merely for entertainment. They're investing in tools that allow them to learn skills, produce work, generate income, and potentially improve their circumstances.
When those tools become less affordable, the resulting limitations don't fall equally across society. Large organizations can often accommodate higher equipment costs through substantial operating budgets, while a person starting from scratch may have only a few hundred dollars available. That difference creates a competitive advantage for those who already possess financial resources. Over time, a market that increasingly favors expensive computers could weaken one of the personal computing revolution's most important accomplishments: reducing the financial barriers between an individual with an idea and the equipment necessary to pursue it.
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Part III — The Foothills Feedback Loop:
Building the Future While Paying More to Participate
What makes this situation particularly interesting from our perspective is that Hickory and the surrounding Foothills are directly involved in building the infrastructure supporting this new technological economy. We aren't simply purchasing products manufactured elsewhere or reading about developments taking place in distant metropolitan areas. Our region has become an important location for data centers, optical communications manufacturing, and the supporting industries that make large-scale computing possible.
In November 2022, Microsoft announced plans to invest at least $1 billion over approximately 10 years in the phased development of four data centers in Catawba County. The project involves communities including Hickory, Conover, and Maiden. Google established its data-center presence in Lenoir in 2007 and opened its original facility the following year. Since then, the company reports investing more than $4 billion in North Carolina, helping establish this part of the Foothills as a significant location for large-scale computing infrastructure. (Catawba County; Google)
Meanwhile, Corning is expanding its optical communications operations in Hickory to help meet the growing demand for high-speed data connections. In January 2026, the company announced a multiyear agreement with Meta valued at up to $6 billion, including a significant expansion of optical cable manufacturing capacity in Hickory. A separate multibillion-dollar agreement with Amazon, announced in June, is expected to create approximately 1,000 manufacturing jobs across Corning's North Carolina operations and support additional workforce development through Catawba Valley Community College. These are substantial commitments to an industry that depends on the ability to move extraordinary amounts of information quickly and reliably. (Corning and Meta; Corning and Amazon)
These investments shouldn't be dismissed or treated as though they have no value to our communities. They can provide construction work, manufacturing employment, technical training, new tax revenue, and opportunities for businesses supplying materials and services. For a region that has spent decades adjusting to the decline of traditional furniture and textile manufacturing, participation in expanding technology industries offers genuine economic possibilities. The presence of companies such as Corning also demonstrates that our existing manufacturing knowledge and workforce capabilities can remain relevant as the economy changes.
But an interesting contradiction emerges when we compare what our region is helping produce with what ordinary people increasingly must pay to use modern technology independently. We are expanding factories that manufacture the communications infrastructure connecting enormous computing facilities, while global demand for those facilities is helping intensify competition for the memory and storage needed in personal computers. The local investments aren't themselves proof that a resident's computer upgrade has become more expensive because of a particular data center in Catawba County. Rather, both developments are connected to the same worldwide transformation in computing demand and investment priorities.
The relationship deserves examination because economic development is about more than the construction of facilities or the announcement of large investment figures. Those things matter, but they don't tell us everything about how an industry changes the economic opportunities available to a community. We should also ask whether residents can afford the tools needed to participate in the industries being developed around them, whether local workers gain lasting skills, and whether the resulting infrastructure strengthens the region's broader economic independence.
Electricity and infrastructure costs introduce another layer to the discussion. Data centers can require enormous electrical supplies, and their expansion raises legitimate questions about transmission capacity, generation investments, water availability, and the allocation of infrastructure expenses. However, we shouldn't assume that every dollar spent on serving a data center is automatically charged to existing residential customers. In October 2026, Duke Energy announced a proposed settlement with the North Carolina Public Staff and major technology companies that would strengthen financial protections, including upfront payments for dedicated electrical connections and guarantees associated with certain shared grid improvements. The agreement remained subject to state regulatory approval, with a decision expected in November. (Duke Energy)
That arrangement addresses an important concern, but it doesn't eliminate the need to examine how rapid industrial growth affects long-term utility planning and household costs. Electricity systems must be designed around expected future demand, and the decisions made today can influence generating capacity, transmission investments, and rates for many years. A responsible economic discussion should recognize the benefits of attracting new industrial customers while continuing to ask whether the costs and obligations are being distributed fairly.
The larger issue is the direction of economic opportunity. We should welcome investments that strengthen our industrial base, but we should also measure whether the people living here are becoming more capable of producing value for themselves. If the Foothills become increasingly important to the infrastructure of centralized computing while independent computing becomes less affordable, we need to understand how those two developments fit together and what they mean for our economic future.
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Part IV — The Archival Choke Point:
When Keeping Your Own Work Becomes Expensive
Computer memory is only one part of the affordability problem. The other involves storage, which may be less exciting to discuss but is equally important to anyone who has spent years creating or accumulating valuable information. Memory provides the temporary working space a computer needs to operate, while storage preserves the documents, photographs, programs, research, and other materials that remain after the computer is turned off. Without affordable storage, the ability to retain and manage substantial amounts of information becomes more difficult.
Over the past several decades, improvements in storage technology allowed ordinary people to maintain personal collections that would once have required considerable institutional resources. A writer could preserve years of manuscripts, a photographer could keep original images, and a small business could retain its accounting records and operational documents. Families accumulated digital photographs, videos, and records that might otherwise have been scattered or lost. As storage capacity increased and prices generally declined, maintaining these archives became a realistic responsibility for individuals rather than something only large organizations could afford.
The current storage market is experiencing pressures similar to those affecting conventional computer memory. In April 2026, Gartner projected that NAND flash memory prices would increase approximately 234% during the year, reflecting extraordinary demand and constraints in the semiconductor market. NAND is the technology used in most modern solid-state drives, making its price especially important to computers and storage devices. TrendForce has also reported that expanding AI infrastructure and cloud computing operations are driving substantial demand for enterprise solid-state drives, with manufacturers allocating resources toward customers purchasing large quantities of high-capacity equipment. (Gartner, April 8, 2026; TrendForce)
Traditional mechanical hard drives still provide an economical way to store large quantities of information, particularly when immediate access speed isn't essential. They aren't disappearing merely because AI and cloud services are expanding. Nevertheless, the broader increase in storage demand and the changes taking place in the industry remind us that preserving information has a continuing economic cost, whether we purchase the storage equipment ourselves or pay another organization to maintain it.
This distinction becomes especially important when we consider cloud storage. Online services can provide convenience, accessibility from multiple locations, collaboration, and protection against certain disasters that could destroy locally stored information. Those are real benefits, and a sound approach to protecting important files may combine local storage with remote backups. However, keeping information on a drive you own is economically different from paying a provider to maintain access to information on its equipment.
When you purchase a storage drive, you acquire a physical resource that can remain available without a recurring service fee, although the equipment still requires maintenance, appropriate backups, and eventual replacement. When you subscribe to cloud storage, continued access depends on the provider's infrastructure, pricing, service availability, and account conditions. Neither approach guarantees complete safety, and neither should be considered the only acceptable method of preserving important information. The concern arises when rising hardware costs gradually make local ownership impractical, leaving people increasingly dependent on arrangements they must continue paying for.
For someone who has spent years developing a business, conducting research, creating original work, or maintaining a personal archive, that distinction is substantial. The information represents accumulated time, effort, experience, and knowledge. Losing practical control over where that information resides or how it can be accessed can create dependencies extending far beyond the convenience of opening a file. Affordable independent storage is therefore not simply a technical preference; it is part of the larger question of whether individuals can retain meaningful control over the products of their own labor.
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Part V — The Cloud Trap and the Mobile Downgrade:
When Access Begins Replacing Ownership
The changing economics of hardware are occurring alongside another major transformation in the technology industry: the movement away from purchasing equipment and software toward paying fees for access to digital services. Software subscriptions, cloud storage, remote processing, and online applications are becoming increasingly common. In many cases, these arrangements are convenient and economical because they allow customers to use powerful systems without having to purchase, maintain, and upgrade every component themselves.
Artificial intelligence provides an excellent example of the benefits. The computing infrastructure required to develop and operate advanced AI models would be impossible for most individuals or small businesses to reproduce independently. Through online services, however, ordinary people can use these tools for research, analysis, writing, design, programming, and numerous other activities. I use these technologies myself, and I have no objection to the advantages they offer. The ability to access extraordinary computing resources without personally owning the underlying equipment can expand opportunities rather than restrict them.
The important question is whether people retain a meaningful choice between using outside services and maintaining their own independent computing capabilities. Renting additional computing power because it offers a clear advantage is different from renting computing power because purchasing capable equipment has become unaffordable. In the first situation, the service supplements resources an individual already controls. In the second, the individual may become increasingly dependent on an outside provider for activities that once could be performed locally.
That difference is particularly important when dealing with information ownership, privacy, recurring expenses, and the ability to work without a continuous internet connection. Cloud services can change prices, revise subscription plans, discontinue features, or alter their operating conditions. Local software and equipment have limitations of their own, but they can provide greater control over certain activities and reduce dependence on external decisions. The strongest position for an individual is generally having the practical freedom to select whichever arrangement best meets the requirements of the work.
Smartphones introduce another part of this transformation. Modern phones are extraordinarily capable computers, providing communications, photography, navigation, banking, research, and access to countless digital services through a device small enough to carry in a pocket. For many everyday activities, they are more convenient than a traditional personal computer. But that convenience shouldn't obscure the differences between a mobile device designed primarily around portability and a general-purpose workstation intended for prolonged, demanding productive work.
Someone writing a detailed research report, editing substantial amounts of video, developing software, or working with complicated financial information may benefit enormously from a larger display, full keyboard, precision input devices, substantial memory, and the ability to manage files and applications with fewer restrictions. Some phones can perform many of these tasks, particularly when connected to additional equipment, but they aren't always practical substitutes for computers designed specifically around those activities. The issue isn't whether smartphones are useful or technologically sophisticated. It is whether their growing dominance, combined with increasingly expensive personal computers, changes the kinds of productive capabilities ordinary people can afford to possess.
There is a meaningful economic difference between being connected to the digital economy and having the independent capacity to produce within it. A person can use a phone to watch videos, read articles, communicate with others, and purchase services without possessing the equipment necessary to create more demanding original work. That doesn't make those activities unimportant, nor does it mean smartphones cannot be productive tools. It simply means that access to information and services isn't equivalent to unrestricted ownership of the tools required to create, analyze, and manage information independently.
If the affordable end of the computer market continues losing ground while connected devices and subscription services become the primary alternatives, society may remain more digitally connected than ever before while becoming less independent in how it uses that connectivity. The technology would continue advancing, but a growing share of its capabilities could reside in systems controlled by comparatively few large organizations. That would represent a significant departure from the original personal computing revolution, which expanded access by placing increasingly powerful equipment directly into the hands of ordinary individuals.
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Part VI — The Endgame:
When Technology Begins Consuming Its Own Foundation
The final concern emerging from this investigation is more speculative than the market data, but it may also be the most consequential. Artificial intelligence is designed to expand human analytical and productive capabilities, yet its development depends heavily on information accumulated through human activity. Books, research papers, software, photographs, technical documentation, artistic work, and countless other forms of original material provide much of the foundation upon which these systems were built. AI can process, organize, and generate information on an extraordinary scale, but that doesn't eliminate the importance of people continuing to make original discoveries and produce new knowledge.
An interesting parallel appears in research involving what scientists call model collapse. A study published in the journal Nature in 2024 examined what can happen when successive generations of generative AI models are repeatedly trained on material produced by earlier models. Under certain conditions, the models gradually lose information about the original data, especially unusual or less frequently represented patterns. The researchers found that preserving access to genuine original information is important to maintaining the quality and diversity of what future models can learn. (Nature)
That research doesn't establish that rising computer memory prices will cause artificial intelligence to collapse, and the two issues should not be confused. Model collapse is a technical problem involving training information and the behavior of successive AI systems. The affordability of personal computing is an economic problem involving access to equipment and productive resources. However, both issues point toward a broader principle worth examining: technological systems depend on the continuing availability of original human knowledge, experimentation, and creative activity.
Consider how much innovation has emerged because people gained access to relatively affordable computers. Someone with limited financial resources could learn programming, develop a useful application, publish independent research, start a business, or create something that eventually reached a much larger audience. Many such efforts began outside major institutions, often with little more than a personal computer, access to information, and a willingness to invest substantial time in learning. The significance of affordable computing wasn't simply that it made existing work easier. It allowed people who previously lacked the necessary resources to participate in creating something new.
If increasingly expensive hardware makes independent productive work more difficult, the number of people capable of pursuing these opportunities could face greater constraints. A student may still have access to online educational material but lack equipment adequate for advanced projects. A small business owner may be able to subscribe to sophisticated services while finding it difficult to maintain independent systems. A researcher or creative professional may gain access to powerful AI tools but become more dependent on outside providers to store information, operate software, and preserve the results.
These outcomes aren't inevitable, and advances in efficient hardware, local AI systems, refurbished equipment, and competing technologies could help preserve affordable alternatives. Nevertheless, the current market direction raises questions that deserve attention before long-term dependencies become firmly established. Greater computing power at the institutional level doesn't automatically translate into greater economic opportunity for every individual. The distribution of that power, the cost of accessing it, and the ability to own productive equipment remain important factors.
The possibility that concerns me is that the technology industry could concentrate so much financial and manufacturing capacity on expanding centralized computing that it unintentionally weakens the distributed human productive capacity upon which future innovation depends. We could build increasingly powerful systems designed to analyze and generate knowledge while reducing the affordability of the personal tools through which people learn, experiment, and produce original work. In effect, the industry could become so successful at expanding one form of computing power that it makes another form less accessible.
This is technological cannibalization. It isn't a claim that artificial intelligence is literally consuming itself or that technology companies are deliberately attempting to eliminate personal computers. It is an economic warning about individually rational decisions producing a collectively undesirable result. Semiconductor manufacturers seek profitable customers, cloud companies expand their services, software publishers pursue recurring revenue, and consumers choose convenience wherever possible. Each decision may make sense on its own, yet the combined direction can gradually shift more productive capability away from individual ownership and toward institutional control.
History provides plenty of examples of industries that became highly efficient at generating wealth without necessarily distributing the resulting economic gains broadly. Technological development can increase total output while leaving individuals with fewer choices about how they work, what they own, and whom they must depend upon. The personal computer helped weaken some of those barriers by making important productive tools affordable to people who lacked access to institutional infrastructure. If the AI revolution is to build upon that achievement rather than reverse it, preserving the affordability and usefulness of individually owned computing deserves a place in the technological conversation.
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The Larger Question: Who Will Own the Ability to Produce?
What began as an investigation into the cost of upgrading a $716 personal computer has revealed a much larger economic concern. Here in the Foothills, we're participating in the construction of an extraordinary new technological economy, one capable of creating jobs, attracting investment, and expanding what computers can accomplish. At the end of the day, though, real economic progress comes down to what regular folks can actually accomplish on their own.
If we build increasingly powerful computing infrastructure while making it harder for individuals to afford capable equipment, preserve their own work, and develop independent enterprises, we risk undermining one of the greatest achievements of the personal computer revolution. The question isn't whether artificial intelligence will continue advancing. It will. The question is whether that advancement will strengthen the independence of the people who use it or gradually make them more dependent on those who own machinery and control the systems.
My Own Time
When Progress Becomes Something We Can No Longer Afford
There is a personal reason this subject is so concerning to me. I remember back when owning a computer meant you could really expand what you were able to do on your own, giving you a real sense of independence. The possibilities seemed limitless, if you were willing to put in the time to learn the processes.
With every new technological breakthrough, we gained real ground: extra memory let us tackle bigger projects, larger hard drives kept years of work safe, and faster processors made things possible that used to be out of reach. The direction was clear as real computing power moved away from big institutions and corporations and right into our own hands.
That shift was profoundly empowering precisely because direct ownership was at its core.
With a proper personal computer you didn't need a monthly subscription just to open your own files or work on a creative project; you had your own private space to experiment, learn as you go, bring new ideas to life, and hold onto your work without needing anyone else's permission.
Personally, I have no issues with AI, Data Centers, and Cloud Computing. I use these tools all the time in my work. These tools bring huge benefits when you need extra scale, connectivity, and flexibility. Massive regional tech investments and manufacturing growth bring real opportunities at ground level, locally, nationally, and globally. But we can't ignore the risks that come with this technology. [23]
To put it simply, we risk losing our personal independence and control over our data if owning a computer stops being affordable or practical.
The primary concern is not that personal hardware will disappear entirely.
Rather, the danger lies in a shift where genuine productive capacity and data ownership become something most people must continuously pay subscription fees for access to rather than directly own.
This dynamic resembles historical company towns, where workers resided in corporate housing, purchased supplies with company scrip, and enjoyed access to basic necessities while lacking true structural independence from the employer. This is how you become a Feudal colony.
Today's centralization doesn't require deliberate malice; it emerges naturally as semiconductor makers prioritize high-margin corporate and institutional clients, cloud providers construct more massive facilities, software publishers favor recurring revenues that come with subscriptions, and consumers opt for cheaper connected hardware like their smartphones.
Although each choice is financially logical on its own, their cumulative impact nudges society toward an outcome few would actively choose. This structural shift is precisely why the hardware memory squeeze matters.
A physical module of RAM might seem like a minor component to your average person, but the independent computing power it provides is fundamental to technological growth capabilities. It is all about access to creativity. What if I took away a painters brushes? Or a sculptor's chisels? And said they have to rent them from me.
When affordable technology allows individuals to analyze, build, and innovate at levels once restricted to large organizations, it expands personal freedom and democratizes economic opportunity.
On the flip side, if that power gets locked behind soaring hardware costs, endless subscriptions, and centralized infrastructure, overall tech might keep moving forward while leaving individual users with less self-reliance.
Ultimately, true technological progress shouldn't be measured solely by the total computing power society generates.
It should also be measured by how much of that power stays affordable, accessible, and right in the hands of everyday people.
