This is standard for most of the world. Really, only some countries, all of them developed, are exceptions to this.

What does cause inflation, however, is when more dollars are printed versus things being made. You can't precisely measure the latter, so you have to make do with price indices and such. Which makes inflation hard to actually gauge, especially when everyone expects more and more to be produced every year (i.e. they expect their savings and investments to appreciate/gain interest) so you have to print more dollars to at least keep up the facade.

But would they be able to realize their potential without further (mostly monetary and institutional) support from their country? In that way, things now are not so different from before. However, the story will probably change in a few years' time.

Computational intelligence obviates the role of the human in making capital reproduce and multiply. Mathematics as its own field of study might become pointless other than as a hobby - an endeavour reserved for those entitled to the machine's output. What the machine develops in the place of mathematics may not be recognizable enough to even share the same label - that is, if it even uses mathematical principles rather than just finding correlations that are 'good enough' for its use.

What's also interesting is the use of emojis to represent dead ends. I guess they really have become morphemes now.

They were hardly the only ones in the space. OpenAI has been around since 2015. GPT-3 was released in 2020 and ChatGPT in 2022. Not to mention, I wouldn't call something produced by a handful of megacorporations worldwide particularly democratized. In fact, Google's transparency is what allowed it to be democratized, because it published its findings about transformers publicly.

> So far, LLMs are great and all, but they only really "fill in the blanks." That's a fundamental limitation of the entire concept of modelling in general; you cannot generalize to out-of-distribution inputs. The bottleneck is going to end up being human beings no matter which way you slice it.

This is a laughably naïve take especially when LLMs have a) been trained on quite literally all the data the world can provide and b) are being trained more and more using reinforcement learning techniques - which don't rely on data at all and instead on producing emergent behaviour from a set of ground rules. With every new release their agentic capabilities improve and they become more independent, requiring only the impetus to get going.

> This is also called the Jevons paradox, when making a resource less expensive leads to overall market growing.

Oh yes, there will definitely be more software. That is guaranteed. What is not guaranteed is how many humans will be involved in making it. Just as more coal is being mined than ever but fewer people are involved in it. Efficiencies in coal mining aren't what made the average coal miner's working conditions or income better, regulations are.

> If you went back a thousand years ago and told someone carrying a bucket full of water that one day pipes would run across the civilized world and water would literally be free basically everywhere

If you told a Roman this, they would not be as surprised as you would think as aqueducts already existed back then. They would be more surprised that the common man had the ability to vote in most countries. I doubt it will stay that way with improvements in AI, at least not without a great reduction in population.

Let's say your income is $100. You spend $50 and invest $50. The prices of goods goes up 4.2%, so to keep your current living standards, you must now spend $51.20. Your income increases by 4.2% to $104.20. After expenditures, you now have $51.20, or exactly half your income, to invest. So you haven't made any progress. And investing $50 now is equivalent to investing $47.98 before in terms of what you could have bought instead of investing.

For now. And that too at a massively discounted rate to drive adoption.

> When open weight models trail _at most_ a year behind the closed ones and compute continues to proliferate?

Open-weight models require computing power to run. Consumer hardware prices are rising because of AI build-out, so much so that companies that used to serve ordinary consumer markets are switching to serve only datacenters. Megacompute does indeed continue to proliferate.

> One of the few things we have figured out about AI is that productivity gains are mostly captured by the people using the tools, not the person paying for the model. In other words, using an LLM is a skill and there is still no substitute for the human driving it.

Will this be the case in 20 years? Agentic workflows have come as far as they have in about two years of existence. Do you really need the problem between chair and keyboard will be needed after another 10? And do you really think that in 20 years time that we will all be paid to prompt increasingly advanced and independent LLMs?

> everyone who is willing to accept the machine's gifts has their every material need catered to

The way automation is going, knowledge work will be automated first before any physical production processes are. A lot of people will lose their livelihoods before goods in particular become "the machine's gifts". What do you think happens then? Will the capital owners who have captured this reduction in costs reduce prices proportionally? Or will they keep the gains for themselves? Do you think governments around the world will tax the upper class to the point of being able to give everyone their current livelihoods through government benefits?

You are pretty much just describing some sort of fantasy automated communism. Not to mention, in your world, gatekeeping the machines would instantly become the most profitable venture possible.

You wouldn't ask a chemistry professor to write code. So just because LLMs create negative value for software development doesn't mean that they can't be helpful for bioweapons synthesis, especially considering the range of chemistry and biology sources Anthropic would have fed to its LLM that wouldn't be publicly accessible. The LLM doesn't even need to be particularly accurate so long as the amateur bioweapons researcher takes adequate precautions before following its instructions and does some background research beforehand.

From your example, perhaps you mean "competence does not imply knowledge" or more accurately in fact "lack of competence implies lack of knowledge" i.e. !competence -> !knowledge, in that competence && !knowledge is common but !competence && knowledge is rare.

The Industrial Revolution indeed did not completely eliminate the need for a human workforce. The AI Revolution will.

Themselves. The economy is a big cycle where money changes hands to drive production i.e. things getting made. AI will simultaneously greatly increase production (especially once humanoid robots are as dexterous as humans) and make the humans whose jobs it will do economically irrelevant.

So the rich will buy and sell very nice things to each other while the rest of us get left out in the cold because we simply cannot compete with the robots. And because they will capture and control all resources (either by law or by force) we won't be able to create a functioning parallel economy either.