BS Summary: This article contains 25 faulty reasoning types, including Post Hoc (False Cause), Negativity Bias, and Availability Heuristic, with Biased Writer Voice as the most egregious example at 66.9% saturation with 458 hits. Analysis detected 1,903 faulty-reasoning hits from 685 analyzed words, generating a BS Score of 45.8% and a BS Rank of 42% (12,874 of 21,887 articles). This article is better (less manipulative) than 58.80% of the article peer group.
It’s a good time to be in the memory business.
As the AI datacenter business booms, SK Hynix and Micron’s revenues have tripled in the last year, and Samsung’s has roughly doubled.
But while the trio have the AI revolution to thank for their good fortune, the deck is stacked for a reversal.
Such is the memory business historically.
Today, sky high demand for high-bandwidth memory (HBM), DDR5, and NAND flash memory needed for GPU servers has devoured any remaining capacity, leading to shortages that have driven up prices on everything from consumer electronics to AI infrastructure.
You can't even buy a budget smartphone these days.
The big three memory vendors are now in the process of investing hundreds of billions of dollars to bring new fab capacity online.
In June, South Korean President Lee Jae Myung announced a $576 billion investment led by SK Hynix and Samsung to bolster chip production and shore up AI supply chains.
On Thursday, Micron said that it would invest up to $3 billion to strengthen the US semiconductor supply chain, and according to recent reports, the Idaho-based chipmaker is also working to boost production across its Singapore, Taiwan, and Japan sites.
Unfortunately, it's a slow process.
Semiconductor manufacturing is among the most complex and resource-intensive industries in the world, and building a new DRAM or NAND flash wafer fab is not a trivial endeavor.
Before the first chip can roll off the production line, financing must be secured, a location must been selected, permits must be won, and tens of millions of dollars of support facilities ranging from power conditioning and air handling to the ultra-pure water filtration systems must be deployed.
Even after the clean rooms are completed, hundreds of millions of dollars of specialized lithography, wafer transport, and test equipment must be installed and validated.
And once everything is ready to be powered on, it can take months to dial everything in and bring yields to acceptable levels.
This process often takes years even without delays.
So while there are a handful of new memory fabs already under way, anything SK, Samsung, or Micron starts today will take at least three years to bring online, and even longer to ramp production.
That means memory prices are going to stay high for the foreseeable future.
A recent IDC report warns that we may not see relief from the RAMpocalypse until at least 2028.
That’s great news for memory makers, whose revenues will stay inflated.
But it’s a big problem for AI startups and model devs, who will be paying higher infrastructure prices until that happens.
OpenAI and others have spent the last four years or so and hundreds of billions of VC capital developing ever more capable models, agents, and tools.
It’s no longer a matter of whether the technology works, but rather whether the benefits justify continued investment at current or higher levels.
Sooner or later, these startups will have to turn a profit, and sky high memory prices certainly aren’t helping to find anything resembling a margin in the cost per token.
The question now is whether or not the memory vendors can bring new capacity online before the great AI houses exhaust their VC-subsidized runway and the music stops.
Historically, memory is a commodity, with wild swings in pricing characterized by boom and bust cycles.
Memory vendors therefore rely on boom cycles to finance fabs, knowing full well that, once they come online, the additional capacity could end up cratering prices.
As we reported late last year, the AI boom has changed this dynamic dramatically.
Where we should have expected memory prices to fall across 2025 and 2026, we’ve seen the exact opposite as AI infrastructure consumes every bit of DRAM and NAND it can get its hands on.
But if the anticipated demand for AI falls short, everyone loses and memory vendors will find themselves at the bottom of a bust cycle to end all bust cycles.
On a bright note, the sky-high price of memory will no longer factor into why you can't afford a new laptop or smartphone.
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40 attributed words58% of attributed speech84% writer coverage
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