I’m curious as to what appeals to you about AI. With so much contoversy nowadays I’d like to hear some people’s opinions.

First let me just say that this isn’t “theory” in the usual sense—I’m not connecting to anything specific in Marx or anything, though my world view is heavily influenced by a disorganized mishmash of Left theory. I’m not great at citing sources or remembering names and arguments. So, I’m sorry if this is the wrong flair or wrong sub for this post. I just don’t know where else to put these thoughts and get human feedback from fellow Lefties who don’t knee-jerk hate AI for existing.

So:

I keep seeing comments on other subs about the AI bubble and how it’s just a fad that will eventually run out of steam, and then the price of RAM, etc. will return to normal. They say the companies investing in AI are inflating its value as a scam to milk investments or something. Everyone hates data centers.

Ok

But that all assumes that the biggest fish in the capital class are either wrong about a giant investment (unlikely considering their resources and the inside knowledge that brings), or they’re all playing out this particular scam at the same time because… it will benefit them more than the usual scam of capitalism already does? No. I think the “AI will pass” arguments are all copium. People just don’t want to face the possibility that AI is changing the world. Honestly, it reminds me of COVID deniers back in ‘20.

Except AI is going to change the world more than COVID. It’s the next printing press. It’s the power to make any program imaginable, to solve any problem that is solvable. It’s still in its infancy, but look how far it’s come just in the last year. Look what you can do with Opus 5.5. Now imagine what AI devs are doing with it—each advancement in AI will feed into the next advancement in a positive feedback loop. I used to be skeptical of the whole singularity idea, but when I think of what AI devs might be capable of now, using current frontier models, I think it’s basically inevitable.

But that’s all setup to my real point, and probably stuff most of you already assume or at least think about.

The real point is data centers. Centralization of compute — and emptying the market/pricing people out of necessary components. They know AI is the future. Compute is tomorrow’s equivalent of yesterday’s land—the ones who hold it will be the lords over all.

Data centers are an ongoing land grab on computing power, and only the big companies even know it’s happening.

My prediction? The elements necessary to run AI will never be cheaper than they are today. Just like land, the price will continue to increase and never come down. It may fluctuate here and there but it’s an upward trend from here on.

So—am I way off base? I don’t really want to argue for this position, but I would like to be talked down from it. I’d much rather believe in the bubble, to be honest.

Daniel Erasmus has spent about 25 years doing scenario planning for banks, governments and companies, and his starting point is that experts are bad at predicting the future. In 2006, a scenario he worked on helped one bank prepare for a global financial collapse. When the crisis hit in 2008, it was one of only two banks in the world to grow its assets.

We recorded this conversation at DWeb Camp 2026 outside Berlin. Daniel explains how scenario planning works and how scenario work during COVID flagged a food security risk, which led a bank to start a program that has since given away about 120 million meals. We also talk about ClimateGPT, the open climate model he built, why he thinks climate is a bigger danger than AI, and how he answers the critique that AI uses too much energy.

Daniel Erasmus is head of AI at Internet Archive Europe and a member of the Club of Rome. He built ClimateGPT, an open source and open access AI model focused on climate and the social decisions around it.

Tasmania, Australia, wants AI data center operators to help fund local communities, cover their own infrastructure costs, invest in renewables, and publicly report their energy and water use.

Not exactly seizing the means of production, but its a start.

These companies depend on public infrastructure, shared resources, and human labor to build their AI empires. So why should communities shoulder the costs while shareholders pocket the gains?

Now, the proposal still needs teeth. Without enforceable obligations, a community benefit fund can turn into little more than a corporate tip jar.

But theres a useful principle here. AI infrastructure isnt some private kingdom floating above society. Its built on collective resources, and the public should have a say in how its developed and who benefits.

For the left, that means pushing beyond compensation toward public ownership, democratic oversight, worker bargaining power, and a share of the productivity gains.

We dont have to choose between letting corporations run the show and opposing technological development altogether.

Make them pay their share. Then fight for a seat at the table, ownership of the table, and control over what gets built on it.

Nicolas d Villarreal, whose two self-published books I have read, seems to have a lot of insights in regards to how the structuralism of LLMs interweaves along with the labour theory of value from eighteenth-century historiography.

Do check out Daniel Tutt's other interviews with him, along with his Substack, to get a taste of how he brings his own experimentations with LLMs and programming.

Will it with our labor augmentation today.

His free writings

https://substack.com/@nicolasdvillarreal?utm_source=share&utm_medium=android&r=3b6dwt