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2-3x is completely dwarfed by the remaining improvements in training which is still in its infancy relatively

What’s the lifespan/refurbishability of the capex elements like the “GPU” modules or even the DRAM soldered into them?

I’m so mad I didn’t max out my main server when I had the chance. Used enterprise sticks were dirt cheap on eBay.

I paid $279 for crucial 96gb DDR5 5600 MHz SO-DIMM ram October 22 of last year. Amazon has the same kit going for $1,048.90 right now.

I bought 192GB of DDR3 a year ago for literally $60 ($5 a stick). It's about $22 a stick now, so more like $350 today. What on earth is _anybody_ doing with DDR3?

2x16gb for $105 total April of 2025. $600 for that now. Makes no sense.

Makes prior assumptions that getting tens of gigs of ram is cheap thrown out the window. Would likely lead to super fast SSDs such as optain being way more valuable

I bought a couple of used computers with 256 GB of DDR 4 (total) a year ago. The ram is worth more than I paid for the whole machines now.

Ramflation

It is one of the thing with consumer when they remember they brought it at the absolutely lowest price point when DRAM maker were bleeding money.

Those are not normal pricing. Before the pricing collapse in early 2020, 96GB DDR5 would have cost about $450 to $500. And I will need to restate again the cost of DRAM hasn't really changed much in the past 20 years. Its price just goes up and down in cycles.

So in reality it is more like going from $500 to $1300. But consumer felt it was more like going from $200 to $1300.

Crucial are already selling DRAM made by CXMT. And China are already throwing money at it. I doubt the memory bubble will burst in next 12-24 months. As in going back to money losing DRAM pricing. As they will all pivot to HBM or other money making products. But the bulk of lower end consumer DDR5 or LPDDR5 will goes to Chinese Foundry. Assuming they have figure out how to do them well. Which they have improved but are still so far away from industry leaders.

Normally memory maker will push the next DDR standard to market just to push out Chinese competitors, I am not sure it will work the same this time around. DDR5 have plenty of other usage / demands.

In theory the new futures markets for chip components would help here, since it would allow DRAM suppliers to insulate themselves from that risk.

According to the recent article HBM memory is 3x less efficient wafer area wise than LPDDR; but the bandwidth is more than triple.

What if its in everyone's interest to buy computers at say 1/3rd the rate and switch everything over to HBM?

the discrepancy between compute and memory has been growing for ages, perhaps a painful switch to HBM is exactly what we need?

Would you rather have 3 intermediate computers with low memory bandwidth, or wait a little longer statistically so that we can all enjoy a new computer at 1/3rd the rate but much higher bandwidth than the area ratio?

I mean the biggest risk is Chinese CXML benefits and capturing markets that others are leaving hanging and then being able to compete and push out the others when costs start to normalize.

As for 20-25% growth not being enough, I think it's not that far off, if we assume data center build out plans hit a wall and slow down significantly, and the AI heat starts to cool off.

I don't think 20-25% may be enough in the short term but if the AI build out stops within this year, we have a massive oversupply instead of a under supply.

An unbelievably good deal at $4000 plus?

It's gone up like 300% in cost in the last year.

if you can buy one!

The RTX 5090 is faster than an H200. It just has less ram (32 vs 141), doesn't have NVLink, and technically isn't allowed to be used in a datacenter.

The datacenter GPUs sell at an 80% margin. They're incredibly overpriced. But the laws of supply and demand are undefeated and so here we all are.

I have an alternative take.

If hyperscalers are using more RAM, and that RAM is not available for consumers, it means all the heavy stuff will happen in the cloud. Why would we want both the hyperscalers and consumers to have RAM simultaneously? Consumers would want more RAM to run local models but then hyperscalers capacity will be unused.

Poor people are already being priced out of cheap phones due to rise in RAM-related unit costs. https://www.cnet.com/tech/mobile/smartphone-sales-to-plummet...

I feel like by the time the AI bubble bursts the PC market will be irreparably damaged. Manufactures who have been making "enterprise" parts aren't going to go back to making consumer parts because there will be no market for it. And with a glut of datacenters not making any money on slop, they are going to be repurposed for saas, stuff like OnShape but for every application.

Most users don't seem to care about storing everything they generate in cloud services and this could easily be sold as an alternative to owning "expensive" desktop or laptop hardware.

This is 100% going to kill the home built pc market. When I started building gaming pcs, the top top card was 750$ (NZD). Now they’re 10,000 just for the gpu and another 1-2000 for ram.

People used to get into gaming pcs as an affordable hobby, now it’s making general aviation look like plan B.

I think it's the opposite. Sure in short term hobbyists are getting squeezed, but the amount of capital that they can put into pushing the edge is small compared to Fortune 500. Sooner or later hobbyists will benefit, especially if the market crashes.

also for ones fully into AI

What if this is the lowest that prices will ever be?

Yeah I upgraded all of my systems to DDR5 last year, so now I have to buy for ddr5 memory upgrades.

Had to fork over almost $1k for a 64G DDR5 kit a few weeks back. At least AMD chips large L3 cache allows folks to get away with lower grade udimms.

Also had to do an Intel build, and there was no way we were going cudimm at current prices. =3

I have always felt insulted that most laptops even offer a low 4 GB of RAM I rather take 16 GB in previous gen memory

My several years old laptop has 128GB of RAM, is that not enough? I admit that it's a pretty heavy one.

I'm not sure if they should vertically integrate, it would probably be a better idea to directly fund the expansion of capacity, much like Apple does when they scale up a new technology for iPhones.

However, that the hyperscalers and AI companies aren't doing this says a lot about their true beliefs about how much future demand AI will have.

AI companies claim they will need a ton of massive expansion, but are unwilling to take on the risk of the capital needed for that expansion.

I'm hearing a lot of sad whining from AI folks about how these chip makers are holding them back, but who actually has the money to finance the expansion easily? Chip makers have been through this game far longer, when Sam Altman went around claiming it was time for $7T of fabs the AI companies made it clear that they were willing to make ridiculous claims, eliminating credibility.

What's needed now is for them to funnel a tiny amount of their massive piles of cash into financing fabs directly.

Because fabs are about the most complex cutting edge technology out there: the "rocket science" of our day (or one of them). And merely having the money is not sufficient. It would be very easy to blow several billion dollars and end up with nothing to show for it.

Just look at how Intel has struggled to compete in recent years, and they have been in the business for decades.

A fab takes years to build even when you have the necessary know-how. If you don't it'll take some additional experimenting before you can compete with the established manufacturers. By the time you can produce a usable chip the shortage might be over.

It’s fab capacity. Fwiw dram is different enough that fabs are not transferable between dram memory and other usages. It’s nice to think ‘wow if they made the current 10nm dram on the latest 2nm processes it’d be much faster’ but it doesn’t work that way. The specific size is needed for the capacitance. Sram can be made on fabs that make other circuitry since it’s transistor not capacitor based but is less dense.

Dram is just extremely specialised.

There is a good article (featured on HN a couple of days ago) that explains the issue: https://davidoks.blog/p/ai-is-killing-the-cheap-smartphone

Do we though? DLSS 5 changes that somewhat from a “we need powah” to “we need models”. I think the future consumer GPU market will be tuned for image and world inference while workstation cards will be tuned for image and video inference. The old way of thinking about this will come to an end when we stop looking at the render loop as the be-all-end-all…

Or, we could be fucked.

Keeping prices at this level is precisely how one or more competitor will rise up. Making memory isn’t super hard. That’s why it is a commodity. The problem with the memory market is that up and down cycles have bankrupted the vast majority of players in the past. Now we only have 3 players left except for a few smaller ones in China.

The reason memory prices can stay high for years in this mega cycle is because the 3 players will be very cautious on overbuilding. They’d rather under build, make great profit (not maximum) and reduce the risk of going bust if this suddenly ends.

Same for TSMC in chips.

Great opportunity for Chinese companies though. This shortage is exactly what Chinese companies need to scale.

If the collude to say make the price $1000 for a component that costs them $100(including opportunity costs), then either a new company or a greedy company in the collusion can make their price secretly $900 and get massively more profit.

Right now their opportunity cost is too high.

> risky it is to spin up a new fab

You don't need a new fab. You can build memory in 20 years old fab.

Then that's a cartel and hopefully regulators will act.

Then China will come and eat their lunch. I for one will only buy Chinese RAM from now on, no matter the prices.

Nine years after Google's seminal paper lit the fuse on AI, a total lack of manufacturing foresight has trapped over a trillion dollars of incoming capital in a hardware bottleneck.

The entire sector is now facing a critical RAM starvation crisis where memory manufacturers are actively slow-rolling supply just to keep prices high and avoid running out entirely.

This has created an unprecedented supply-and-demand distortion where desperate companies are getting rejected even at a 5x markup, and mission-critical SKUs are skyrocketing to 10x and 20x their baseline value.

It is a macroeconomic squeeze at a staggering scale, and the massive venture scale opportunity lies in capturing the value created by this memory gatekeeper.

From the perspective of an armchair economist, the winners will be the investors who invest in RAM wisely. The losers will likely be cash strapped SAAS companies. They’re almost completely dependent on a fleet of servers in the hyperscalers, and they’re leasing those servers and services. That leaves small SAAS companies exposed to incoming inflation in the cost of hosting.

RAM is a boom-and-bust industry, so memory manufacturers were reluctant to invest. Here's a good blog post on the economics:

https://davidoks.blog/p/ai-is-killing-the-cheap-smartphone

Maybe long-term purchase agreements from big buyers might have helped convince them it's okay to build, but apparently it didn't happen.

The same reason they didn’t all sell everything to buy NVIDIA the day chatGPT came out

Up 700% in a year.

WallstreeetBets has been disturbingly accurate in its predictions - basically anything related to AI.

Or will more efficient algorithms just mean we run even more AI models, increasing the demand for AI chips even more?

I mean, god willing, but it'll be just as likely that we'll blissfully consume 100 million token contexts in that case.