dag100

The 80s happened because of the stagnation of the 70s.

But, ideally, with each day, more useful products and services are being made and delivered. It'd be useful to have extra dollars around to account for more stuff being made and more things being done. Thus having more dollars in existence doesn't necessarily mean the value of a dollar is decreasing.

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.

> mathematics were one of the rare sciences were great scientists could emerge from any country with a good education system.

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.

Is it really that surprising that no-one has invested the time and effort into figuring out the personal information of some tech employee-turned-founder? I bet no-one outside of tech even knows his name.

Can't really practice medical or legal skills from the comfort of your home on devices everyone has had for 10 years now. Also, unlike computers which must obey every whim of their master, lawyers and doctors deal with humans. Which makes raw skill less important.

Asking for payment for written work is hardly rent-seeking...

Really makes you wonder who is going through the reasoning traces and how many of them they are parsing through per-hour for their eyes to completely gloss over at seeing this rather than recognise that this, in fact, completely legible.

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

Err, yes, until the surplus kills off all other competition and allows the supplier to jack prices up sky high, or otherwise bend consumers to their will. There's a reason most countries will stop foreign firms from doing this to them.

> The point is that the technology is already too democratized for anyone to hold onto it. Google had chatbot LLMs in 2019 and tried to keep them under wraps, how many years did that buy them?

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.

It's more about information availability rather than intelligence. An LLM has had access to more information during its training period than you'd ever even come across over a hundred lifetimes. It has been trained on billions of books and articles across every single subject that exists on the planet. Can you imagine what real intelligence could do with all that information?

> If I invest half my income and spend half my income, and the prices of goods goes up 4.2% and my income goes up 4.2%, then I've made progress; I'm now investing more than half my income, because the half of my income I was spending has stayed even and the half I was investing has increased.

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.

> How could there be, when literally anyone can plop down $20 and get access to a frontier model?

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.

> So it is absolutely strange and contrasting to see you believe that LLMs are so weak as to create negative value while the CEO is asking about regulations because AI is too powerful.

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.

> Knowledge often does not produce competence

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.

Fine, it is not effectively what happened then. It is worse. At least workers are required to run factories (even though working conditions were ridiculously horrible back then). With AI, in maybe 20 years, 95% of all white-collar workers will be economically irrelevant. You won't need accountants, or programmers, or designers. And we can't all become lawyers and surgeons, or tradesmen.

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

> If we're all broke/starving/being exterminated, who will the rich sell to?

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.

How is it inaccurate? If I only care about buying apples, and apples get 10% more expensive, and my salary only increases by 5%, then I can't buy as many apples as I could have before. How many apples I do actually buy in the end is irrelevant to the calculation.

It's hardly speculative when it is effectively what happened just after the Industrial Revolution, but with more power ceded to capital. In many ways, it's already happening.

That is the status quo now. If LLMs get better and better, managers will simply direct them, well, directly. That's what the parent comment means by the machine learning to do your job. It completely, not mostly, replaces you.

People would be more pro-automation if it didn't entail losing their livelihoods and ability to access food and shelter.

This really underscores how so much LLM "intelligence" is based off of people's experiences that they wrote about. It saddens me somewhat to see that it has basically all been captured by corporations now, and perhaps in a few years there will be little point in knowing things yourself simply because the LLMs will have gotten so good that there is no point to wasting the extra effort. Of course, this might lead to the atrophy of people's thinking muscles and a dumber and more subservient populace, but does anyone really care? Judging by the meteoric rise in the capabilities of LLMs over the past five years, is it really naïve to expect most knowledge work to be obsolete in the next ten?

The other stuff in this thread about decompiling firmware is a lot more interesting to me, though, seeing as it used to be a fairly demanding but rewarding task that has now been "solved" by Claude. It's a magic trick that is a lot harder to pull off than the other things in this thread.

It's because the people at IBM, India get paid multiple times what the contractors get paid. IBM, India, thus hires much better programmers than contractors. This sort of outsourcing isn't nearly as cheap - maybe half the income of a programmer in the US.

> ChatGPT will not build housing, raise livestock, or perform surgery.

I have a bad feeling that it's closer than you'd expect at all three of those things. Especially the last one. Robo-surgeons, remotely controlled by another surgeon somewhere else, already exist. Maybe it won't happen in the next 5 years, but do you really think AI capabilities won't get there in 20-25 years or so?

> Even godawful economic growth would compound way too much.

You vastly overestimate how much of the growth would be going to the workers in question. Especially as, before fiat currency and electric communication, prices were (relatively) more stable than today, and hence so were incomes, especially for labour work. Why would some factory owner in the 1800s pay his workers more than he needed to find new workers? Most economic growth was captured by capital owners and what would today be known as the middle class, but back then were merchants, doctors, etc. - basically just the tier below the capital owners in the social hierarchy. The vast majority of people were peasants.

If you belong to that group you are already completely irrelevant except for your ability to vote.

It means it took 70 years for the average income and employment rate of socio-economic class of people who used to work those jobs (presumably formulated as some percentile of society by income) to rise back to the the same level.

> instead of humans with their own families and community ties

This is an age-old problem with armies and has a similarly age-old solution: just send soldiers from one community to police other communities. For example, during the Tienanmen Square Massacre, some Beijing-based units refused to fire on protesters, so units from further away were called in instead.

> Found it. Youth unemployment is currently at about the (eyeball) median rate for the last 32 years.

It is currently there. The economy doesn't seem to be getting friendlier to the youth though. That median also seems pretty heavily skewed by a seven-year jump in youth unemployment after 2008, which seems like a bad omen.

There are always newer technologies and techniques to be implemented. Better algorithms. Larger deployments. Better reliability. There are also almost always bugs to fix. So, so many bugs.

You could RTFA and find out.

(26 different artificial eggs. The artificial egg is the main development. Basically they take a chicken embryo (by cracking open a fertilized egg) and allow it to develop inside the artificial egg, and from which it can eventually be "hatched". Other methods for growing chickens from embryos outside their eggs have not had very high success rates.)