Tech
With a Spike in RAM Prices, Now Might Be the Best Time to Buy a Laptop
Tariffs. Inflation. Historic corporate shake-ups and mergers. With all the factors the tech industry is facing, you might think the price of a common product like a laptop would have risen this year. But just the opposite has been happening.
I’ve been watching laptop prices slowly drop throughout 2025, a trend that peaked during Black Friday and Cyber Monday. Regardless of the state of the economy, I feel like I can say that laptop prices have never been lower. Some of my favorite laptops have recently offered significant price cuts across Macs, Windows, and Chromebooks. In a time when money is tight for so many of us, that’s welcome news. But with a RAM shortage brewing behind the scenes, there’s good reason to think it won’t last for much longer.
Just Look at the MacBook
Photograph: Brenda Stolyar
There’s one perfect example to demonstrate my point: the MacBook Air. For years now, the latest MacBook has been sold at $999. In 2022, Apple briefly bumped the price of the M2 version to $1,199 but kept the previous-gen M1 MacBook Air for $999. The last MacBook to be sold for less than $999 was in 2015, when Apple had an 11-inch model for $899. That’s a long time to stay static, considering how much more nearly everything in your life costs today than it did in 2015.
Don’t forget the discounts. The M4 MacBook Air is the latest model, and it dropped to $749 in November at retailers like Best Buy, Amazon, and Walmart. Before that, it was selling for $800 for many months. That’s an incredible price for this laptop, especially since the starting configuration comes with 16 GB of RAM.
Apple has offered a supply of older models through third-party retailers. Walmart briefly dropped the price of the M1 MacBook Air to $499. These aren’t refurbished or used; they’re new. That alone is unusual for Apple. There was a time when Apple was seen as the overpriced alternative. But for modern, entry-level Macs, that’s just not true anymore. Even the brand-new M5 MacBook Pro got an unprecedented $150 discount on Black Friday, just a month after it was announced, and that discount is still in place today.
A Virginia startup calling itself Operation Bluebird announced this week that it has filed a formal petition with the US Patent and Trademark Office, asking the federal agency to cancel X Corporation’s trademarks of the words “Twitter” and “tweet” since X has allegedly abandoned them.
“The TWITTER and TWEET brands have been eradicated from X Corp.’s products, services, and marketing, effectively abandoning the storied brand, with no intention to resume use of the mark,” the petition states. “The TWITTER bird was grounded.”
If successful, two leaders of the group tell Ars, Operation Bluebird would launch a social network under the name Twitter.new, possibly as early as late next year. (Twitter.new has created a working prototype and is already inviting users to reserve handles.)
Neither X Corporation nor its owner Elon Musk immediately responded to Ars Technica’s request for comment.
Michael Peroff, an Illinois attorney and founder of Operation Bluebird, said that in the intervening years, more Twitter-like social media networks have sprung up or gained traction—like Threads, Mastodon, and Bluesky. But none have the scale or brand recognition that Twitter did prior to Musk’s takeover.
“There certainly are alternatives,” Peroff said. “I don’t know that any of them at this point in time are at the scale that would make a difference in the national conversation, whereas a new Twitter really could.”
Similarly, Peroff’s business partner, Stephen Coates, an attorney who formerly served as Twitter’s general counsel, said that Operation Bluebird aims to re-create some of the magic that Twitter once had.
“I remember some time ago, I’ve had celebrities react to my content on Twitter during the Super Bowl or events,” he told Ars. “And we want that experience to come back, that whole town square, where we are all meshed in there.”
Could It Work?
Elon Musk bought Twitter in 2022 for $44 billion. He eventually changed the company name and brand identity from Twitter to X. That decision, Operation Bluebird says, created an opening for the Twitter name to be formally abandoned.
In July 2023, Musk himself tweeted that “we shall bid adieu to the twitter brand, and gradually, all the birds.”
That was when Peroff, a Chicago-area attorney specializing in trademark and IP law, saw an opportunity not only to claim the name Twitter but also to use the iconic illustrated logo that was affectionately referred to internally as “Larry Bird.”
A popular topic of conversation of late has been the existence of a bubble in artificial intelligence (AI) and the likelihood that this bubble will burst with great detriment to the IT industry as a whole. Yet, and perhaps surprisingly, the impact of a bursting bubble on digital twins might not be as problematic as one might think.
Ready adoption and fast diffusion of AI might warrant the tremendous investment flows of past years and could create revenue and profit streams quickly. We might well be standing on the precipice of a bubble popping that will lead to massive valuation corrections, but digital twins stand to benefit from advancing AI either way – however, the timeline of AI-enabled applications of digital twins might move.
Since the start of 2023, AI-related companies have ballooned in valuation. OpenAI has been closely associated with starting the AI frenzy with the release of ChatGPT at end of 2022. The company was valued at $29bn in 2023 and reached $500bn in October of 2025, with observers wondering if the company could pull off a $1tn initial public offering soon.
AI-chip leader Nvidia’s stock meanwhile has multiplied by 13 between the beginning of 2023 and end of October 2025, making it the first $5tn company ever. Even companies that are related but are not at the centre of AI developments increased substantially in value, with the stock price of Microsoft and Alphabet more than doubling and tripling, respectively, during that time period.
AI encompasses many different types of technologies and has many use cases that it should be seen as an enabling technology rather than a sole application or a market. AI will play a major role across virtually all application areas, but to varying degrees. Similar to the way the internet shaped past decades – and will continue to shape coming decades – AI will transform industries for good in the long term, and potential potholes on the path that create setbacks are only par for the course.
Looking back to gaze ahead
It is worth recalling the dot.com era from the end of the previous century to judge AI’s current hype. The Nasdaq Composite index – a stock index that skews toward information-technology companies – peaked at more than 5,100 points in March 2000 and then rapidly declined to a final low of just barely above 1,100 points in October 2002 (it took more than 12 years then to move beyond 5,000 points again).
The January 2000 Super Bowl event marked the height of the bubble with 14 in-game ads by dot.com companies – only one of them still active as an independent company today. Now, many analysts see the signs of a tremendous AI bubble accumulate.
A crash is likely in the making. Similarly to 2000, a bursting bubble does not mean that AI will go away, as internet-enabled companies and business models did not vanish. On the contrary, AI will flourish as the internet did. In fact, many infrastructure elements such as datacentres will become affordable for general use after lofty valuations come down.
During the late 1990s, the construction of fibre communication networks was perceived as a tremendous business opportunity. The business never became as profitable as expected, but the initial excitement created an infrastructure of dark fibre – unused but readily available communication lines – that supports today’s business models as a commodity that can be readily leveraged.
AI as an enabling technology will boost capabilities and accelerate the use of advanced digital twins. In particular, digital twins that have to work with difficult-to-capture data and not completely understood real-world dynamics will benefit tremendously. Digital twins of machineries can rely on solid understanding of physics and measurable data that sensors can cost-effectively capture.
Factory environments have many known dynamics and interactions of equipment – even workers’ likely movement patterns can be plugged into simulations. But urban digital twins attempt to capture dynamics and behaviours of relevant elements across entire cities. They are not only subject to less understood dynamics but also phenomena that are difficult – often impossible – to measure.
AI can make available data usable and create data of unmeasurable phenomena. AI in digital twins also allow the use of scenarios to better prepare for sudden events that can affect the entire system in unexpected ways. City managers thereby can develop strategies for unusual weather events, pandemic-like occurrences or localised industrial accidents with ripple effects across the urban landscape.
Digital twins and AI to plan for tomorrow’s cities
Digital twins of urban environments are difficult to design, implement and maintain. The potential impact such digital twins can have commercially and societally promises to be substantial, however. Because of the number of parameters, intersecting dynamics and range of conceivable scenarios, the benefits AI can provide in understanding urban environments are massive. AI and digital twins reinforce each other.
AI can speed up the building of digital twins by supporting code development for virtual environments. Such applications accelerate overall design development and allow embedding design details more easily. For clients and users, AI reduces costs, enables faster implementation of digital twins, and allows for quick and inexpensive changes and alterations as requirements change or new needs arise. In addition, AI can improve the interface experience between virtual environments as well as simulations of operations and users.
Ari Lightman, professor at Carnegie Mellon University, explains: “Generative AI would be used to look at the entire simulation and turn it into a summary for humans. It could tell me things I might be missing and summarise things in a way I can understand.”
AI doesn’t only benefit digital twins but digital twins also support AI’s capabilities. Scott Likens, emerging technology leader at PwC, says: “We’re using digital twins to generate information for large language models [LLMs]…We see opportunity to have the digital twins generate the missing pieces of data we need, and it’s more in line with the environment because it’s based on actual data.” Such synthetic data of missing pieces are also finding use in other applications as “AI, XR, digital twins set to transform robotics”.
Nvidia serves the market of smart cities as city planners and managers are turning to digital twins and AI agents for urban planning scenario analysis and data-driven operational decisions, according to the company. It is providing a range of solutions to enable users to create photo-realistic, simulation-ready digital twins of urban environments to optimise city operations.
A partnership of Japanese companies is developing the digital entertainment city Namba in Osaka, Japan. The aim is to create the world’s first smart city that integrates AI, extended reality [XR], and decentralised physical infrastructure networks [a blockchain-based approach to manage decentralised networks] on a city-wide scale. The group intends to offer services beyond entertainment and tourism. Namba, being a neighbourhood within Osaka, has a limited claim to a city-wide application of the concept, however.
The silver lining of AI overinvestment
The existence of an AI investment bubble is increasingly perceived as a foregone conclusion. AI companies and technology suppliers are now even investing in each other’s operations, adding to lofty valuations. There are obvious indications of a bubble, but positive effects can emerge from the current investment excitement. Whatever the outcome, applications for digital twins will see their timeline solidify as the immediate future of AI plays out.
If use of AI applications proves to be an all-encompassing and rapidly growing market opportunity, the immense investment of the past couple of years will be retroactively viewed as forward-looking wisdom that locked in favourable competitive positions and profits for years to come. More likely though, investors have outrun their headlights, and expectations of adoption and diffusion of AI applications over the next years are vastly overrated.
If so, there will be a shock to the system like the burst of the dot.com bubble at the beginning of the century when the Nasdaq Composite Index dropped by almost 80% within 30 months. Initial warnings existed, with the former chair of the Federal Reserve using the phrase “irrational exuberance” when discussing the development at the stock market in December of 1996. Warnings of an exuberant AI bubble are common today.
Bursting investment bubbles hurt investors and bring down many companies –25 years ago, a slew of dot.com companies vanished. But related overinvestment in infrastructure can make assets suddenly affordable, opening new opportunities. Such affordability changes cost structures that enable business models that could not have become successful at previous valuations. Infrastructure overhang – infrastructure build for rapid growth that does not materialise in the short run – leads to commodification of infrastructure elements, which can democratise a technology for incumbents and startups alike.
The over-investment in fibre during the dot.com years ended up creating dark fibre – overbuilt fibre cables for data transmission – and this infrastructure has served as a ready and inexpensive resource ever since. For AI, investment in datacentres is comparable to the fibre investment from 30 years ago.
Morgan Stanley analysts forecast datacentre spending globally of up to almost $3tn between now and 2028. The amount is staggering, and it is difficult to imagine use cases and adoption rates that will provide the required return on investment for virtually any business model. But as initial investors see their investments decrease or vanish, new players can snap up or use related infrastructures at bargain prices.
Alkesh Shah, a tech analyst with Bank of America, explains the underlying reason for such recurring dynamics: “You always overestimate how fast the change will happen, and you underestimate the magnitude of the change.”
The impact digital twins will have on the marketplace will follow a similar dichotomy between today’s expectations of rate of change and tomorrow’s impact of such change. Digital twins require many technological bits and pieces to come together, and AI will play an important role for digital twins – if not tomorrow, then the day after tomorrow.
Martin Schwirn is the author of “Small data, big disruptions: How to spot signals of change and manage uncertainty” (ISBN 9781632651921). He is also senior advisor for strategic foresight at Business Finland, helping startups and incumbents to find their position in tomorrow’s marketplace.
Odlin confirms that for all of the Icelandic wood-chip ocean deposits, it was impossible for Running Tide to monitor the wood chips for more than three hours after their release, saying, “We couldn’t measure signal from noise in the ocean on the alkalinity.”
The Dead Zone
Despite having sold credits to Stripe, Shopify, Microsoft, and the Chan Zuckerberg Initiative, financial pressures on Running Tide continued to mount as the flow of funds from Silicon Valley dried up. According to one former employee, Odlin would start meetings in spring 2024 by announcing that the company had only a few more weeks of funds before it would have to close. That June, Odlin admitted defeat.
In a LinkedIn post on June 14, 2024, Odlin wrote that “there simply isn’t the demand needed to support large-scale carbon removal.” The company ceased global operations that month. Nearly all employees in Iceland and the US were suddenly let go. One employee was presenting about Running Tide at an algae conference when he was told the news.
“People were happy with our credits. We were filling our contracts. We were selling additional contracts. It just wasn’t enough,” Odlin says. Running Tide had sold $30 million of credits and said it had commitments for tens of millions more, but by Odlin’s estimate, the company needed somewhere between $100 million and $150 million of sales. “That was, like, the rent we were designed for.”
The legacy the company leaves behind after its wood-chip dumping is unclear. It’s simply not known what effect the sinking of biomass will have on the ocean, and the scientists and deep-sea experts WIRED spoke to remain hesitant about pursuing such marine geoengineering until more is understood about the deep sea.
Dumping biomass in the ocean could create “dead zones,” areas where aquatic life is starved of oxygen, says Samantha Joye, a Regents’ Professor in the Department of Marine Sciences at the University of Georgia, who has worked on dead zones in the Mississippi Delta as well as on the cleanup of the 2010 Deepwater Horizon oil spill.
Deep sea environments—some of which provide life-saving drugs or insights into how early Earth formed—could also be forever damaged, Joye adds. A recent carbon flux report by Convex Seascape Survey, an international research collaboration, found that once the seabed is disrupted, this could actually halt the ability for sediments to absorb carbon. Joye also points out that without proper research, ocean alkalinity enhancement could also cause spikes in ocean acidity if it draws lots of carbon into the sea that isn’t then distributed into its deep waters—the very opposite of what the treated wood chips were trying to achieve.
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