IHeartBadCode

LOL!! Good for them. Fucking grifters just grifting.

Wow who could have guessed?

Things to note.

• Gambling is a revenue stream for States.
• States up to this point have been terrible at managing revenue, gambling now gives them this glut of cash.
• Gambling has been promoted as a social activity. Know a gambling platform? Likely there’s a whole social media presence for it. And for some digital platforms that include gambling, they may even have whole social network.
• Aggressive advertising and hidden psychological factors have played a role in how people view it. “Risk-free” sign up, give the impression of harmless entertainment and some platforms deeply hide the gambling aspect.
• Low barrier to entry. Gambling usually has very little friction to get people into the platform, some even allow very low wagers, allowing “everyone” to get in.
• The escape illusion is real for the most hardcore. During periods of high inflation, stagnant wages, and high living costs, individuals look for alternative income sources, looking to escape their current situation.
• And finally, the gig market mindset where everyone feels a need to have a side hustle. Digital income streams with low entry have become popular for fulfilling this mindset.

Human beings are terrible at balancing short-term gains for long-term consequences. It’s mixed into our DNA. Our ancient ancestors, securing immediate calories or escaping a threat was a matter of life and death. Long-term planning wasn’t as critical as immediate survival. Now do note, that’s not an excuse for the people who foolish went head long into this.

This is why this struggle with the rich and powerful is eternal. It fundamentally taps on an ingrained flaw we collective fall for every single time. There is no one solution, there can never be one solution. People must forever fight themselves and the powerful from the exploitation of this fundamental flaw of humanity.

I distinctly remember the conversations about Office’s phone home system and people specifically saying “this seems problematic” and Microsoft hand waving those concerns away.

AI’s demand for memory is pretty difficult to really get across because there’s a lot of complex factors, but whatever you can imagine is the demand, it’s higher than that.

You can look at pre and post AI to get a slightly better picture, but then the numbers don’t look terrible and so the demand isn’t as clear.

2020-2023 primary customers were smartphones, laptops, PC. Data centers were eating about 32% of the global market for RAM. Monolithic DDR4/DDR5 was the main product and High Bandwidth Memory (HBM) was about 8%. Total memory set being sold was like 16GB kits to 64GB kits, obviously server kits were going out, just the majority was those mostly for PCs.

2025 hits and the primary customer is AI Data Centers. To put it at scale, you have literally everything that uses memory (and I mean literally every fucking thing on this planet) and AI Data Centers. And the break between those two bins are 30% and 70%. AI data centers are consuming more than twice the memory of literally everything combined that uses RAM that isn’t an AI data center.

The primary RAM being made now is HBM, which is way more complex. 23% of all the wafers that will be used to make integrated circuits will be HBM RAM. And by wafers, I mean all the chips that will be made this year, lock, stock, and barrel. If you randomly picked up a wafer out of a fab you have a almost 1 in 4 chance to pick up RAM. And finally the average kit going out is 1TB to 2TB kits, which is a lot more than the old 16GB to 64GB kits.

Now I mention HBM because it eats more wafer, that’s because unlike DDR4/5 RAM, HBM RAM is a three-dimensional circuit. 12 to 16 layers of silicon is stacked on top of each other. So HBM consumes about 300% more silicon than other memory (not every layer is one-to-one in size). So you don’t just have one fab making chips, you have several fabs making the layers.

The next thing is that building fabs is complex. I hate trying to explain the complexity, but you can’t do it overnight. Usually you have to build these things over the course of five years. Just to give you some idea of how technical the construction is. If you had a road within 500 feet of a chip fabricator sitting on a regular concrete floor, the car driving on the road would create enough shakiness in the Earth to cause the chip fabricator to bounce around too much. So when they build the place that have to literally isolate the small earth quakes humans walking around inside the place cause. This requires very complex floor building. And this is just the floor, not to mention how clean the place has to be kept, isolated as much as possible atmosphere, literally specific sections are under vacuum. It’s massively complex to build ONE of these.

The complexity comes with a price tag. Average cost to build one memory making factory is around $15B to $20B. It’s serious cash, but even if you have 5 years and $20B, there’s a specific bottleneck. ASML. ASML is the only company on the entire face of the Earth that makes the chip making machines. They’ve indicated that if you ordered a machine today, you can expect it roughly 1½ to 2 years from now. That’s how many people have put in an order for the machines to make memory.

So all that aside, there’s one more bottleneck. HBM has to be stacked in layers, there are very few people on this planet that can do that, and they have years long backlog. And even then, most times the stacking fails. About 30% to 50% of all HBM is trashed because the layers fell apart. And the people who stack are entirely different people than the layer makers. But they’re the same people that take that DDR4/5 wafer and cap it into that little black rectangle you see on your sticks of memory. So they have pretty much ~100% of their employees doing nothing but stacking layers of memory together.

Another thing is economic prioritization, HBM is about 500% more than DDR4/5’s price tag per GB. A fab producing wafers of DDR4/5 is making about $x.xx. A fab producing a couple of the layers for HBM is making about 500% × $x.xx on average (it’s complicated because of the layers), even with the stacking issues. And the profit margin on HBM is 70% versus DDR4/5 before AI which was fingernail thin. SK Hynix was actually taking a loss on production of DDR5 at about -1.6%. So going from -1.6% to 70% profit has created a crowding out effect. Not to mention that since there was a bit of a bleeding out period after COVID, some literally stopped making RAM. Which has made the issue even worse.

The last thing before I run out of characters is the AI growth. AI needs about 300% more memory every ten months. That’s how fast these models are growing. That’s caused a panic buying and also caused a rushing to fulfill. The industry is losing it’s collective mind because the money to be made is big and so lots think it can’t last and trying to get their cut before the gravy train derails.

Says guy who tanked immigration reform so that it could be an election issue.

Ish.

The issue is that it isn’t a straight shot as a lot of people paint. Call Centers work off of User Interfaces, AI can’t see or use those, so those UIs suddenly have to be retooled in a way that the AI understands, which that’s not easy. Additionally there’s business logic that is complex and there’s a lot of siloed knowledge, all of that is hard to extract and put into a model that’s usable.

The thing is that these LLM and AI companies were thinking the rest of the world is as structured as the data models they trained their AIs on and that’s just not the case. The LLMs can absolutely do the task if given the task correctly, it just that it’s near impossible to give the task they need to perform correctly in 100% of the situations. Hell, even humans fail this, people get written up at call centers all the time.

To put it simple, you ever hear the joke, “we don’t have to worry about AI taking the programmers jobs because then the CEO would have to accurately explain the problem they’re trying to solve/sell”? It’s IRL that, that’s holding up a ton of the LLMs in call centers. Like there’s two VERY narrow processes that the company I work for has implemented AI for, and those are really basic situations where explaining the full scope is pretty easy.

But take what I have to say with a grain of salt. I can’t say the company I work for has ever really been that gung-ho about AI to begin with. But I can tell you that it’s WAY, WAY, WAY more work to deploy AI than the tech bros like to paint it. Like you can just hit the button and “go”, but it’s going to crash and burn. Like to get it right is way more work than the AI industry let’s on.

It’s located on the Ruby Pipeline which will serve as the primary source of energy in the short term. Additionally, the data center being classified as a national security site, is located near the Utah Test and Training Range.

Longer term the facility is looking at nuclear facilities for power and the possibility for a runway and aviation facilities.

The primary customer of this facility will be the United States military.

Good luck. The data center is classified as a national security site and has the Utah Test and Training Range base nearby.

They’re building it with the intention of military security.

This highlights the core issue with these developments. Laws are created to handle this kind of situation. Michigan has the Zoning Enabling Act (MCL 125.3207) and the town had no land established as industrial zoning. By omission this amounts to a total ban in violation of Michigan laws.

It shows how laws are being used to set small townships who are barely keeping this side of legal for State laws can be manipulated. And this is a common refrain. Small towns don’t have the legal representation in local boards or governments to verify every single rule that States hand down and instead have to deal with violations as the appear.

This will continue to happen until States begin to grant smaller towns more authority over land use and zoning conditions. Which is why the “stop all data center construction” arguments at the Federal level are moot. The largest part that needs to be address needs to happen at each State level. Even if a law at the Federal level prohibited data centers for AI use under instate commerce, States still have a inherent right to the land that isn’t Federally owned and can just ignore those laws at the Federal level, they would never survive a 10th Amendment challenge.

The whole data-center thing HAS TO BE fought at the State level, there’s no other way around it.

If the cost of keeping humans is higher than the cost of automating, they’ll just automate the process. Or have the place ran by wire, where humans pilot lifts remotely.

Many local government’s aren’t on the home rule, they follow some form of the Dillon Rule. This applies to utilities and land use. For some local areas they are required by some degree to follow the State’s allocation and billing of utilities to remain classified as a public utility in the State.

In many areas our legal framework at the State and local level were never made to handle what’s coming down the pipe with new advances. This is why I always indicate that data centers and their impact need to be addressed at the local level. That’s why I think Federal regulation is the wrong step for the building part of AI. This is very much a local and/or State level that needs to desperately be answered there.

The good news is that we see more people who are involved with their local government with this issue. But this underlying issue has been one since the 1970s, it’s just that these companies have hired firms that are incredibly well versed in the shortcomings of local ordinances and State law. It’s super difficult to patch up flaws in the laws when they’re being exploited at rapid fire pace.

That supply is constrained artificially for particular markets. There’s nothing that stops Samsung, Hynix, or Micron from indicating particular runs for different sectors. And if those three had not removed other competition, we would have producers to increase that supply.

Again, this doesn’t absolve the AI industry in the least. But we have makers that are only making limited selections of product for pure gain and are able to do that via their manipulation of the market. We don’t always have to have a good guy and a bad guy, it can bad guys all around.

We are paying more for a PlayStation so that idiots can use ChatGPT to mislead people on dating apps – something is rotten in the state of gaming

I need people to understand, AI is the current “thing”. We have an industry that produces memory for this planet that is a functional monopoly. Today their excuse is AI. But their excuse for that sudden increase changes roughly every four years. And we continue to let them get away with it, because we collectively blame the consumer.

And do know, I’m not saying AI companies get pass from me. That’s not the point here. The large AI companies and us regular people are consumers of the exact same product that only three companies provide. Those three companies have been legally found guilty in several courts of law across the world of colluding to increase prices, and because there’s not really any other alternative, they chalk the fines up as the cost of business and we write it off as a necessary evil.

But when we blame AI (which there’s lots to blame AI companies for, again that’s beside the point here) we are just blaming a consumer of a product. We are basically saying “Why do they get that thing I wanted. I should be the one who gets it, not them.” Now there’s a lot of industry regulation and international treaties that ensure we’re at the bottom of the list and AI companies pay into keeping that status quo. But let’s be real here, if it wasn’t them, it would be someone else.

When we say the reason computers and technology is getting expensive is because of AI, we are actually avoiding the real culprit here. A tightly controlled market, not unlike say the diamond business of old. And should AI fade away (which math equations that represent ways to optimize pattern matching are something we’ve found to be incredibly helpful) that tightly controlled, highly colluded, industry remains. And then we eventually find ourselves right back where we left off and are convinced to blame something else.

Again, this isn’t trying to absolve the sins of AI companies. But it’s to point out that this isn’t an “AI has done all of this all by itself.” And when we do that, we’re providing cover for an industry that largely runs corrupt with impunity.

You did amazing. Keep up the good work!