I'm not sure what you mean with this?

Sure, hypothetically e.g. any western car manufacturer could poach a bunch of BYD employees. But it's not really practical for most businesses.

> The actual problem is, there is no market to go up to anymore.

This is the "Market for Lemons" problem, yes.

It's less of a problem than you might think. Convincing the entire wider world that you're legitimate is a problem. One made infinitely worse by store marketplaces like Amazon preferring to push "aqekj;bgrsabhghwjbgawrjwsraG" brand garbage.

So you just don't. The trick is to start small. The smallest you can sustain. (This doesn't work for cars, or anything that's sufficiently complex. You won't be taking on Salesforce.)

But so long as you can find a market niche where there's demand for quality, you can carve out a living, and from there, scale up.

The problem with that is twofold: Venture Capital has supplanted other forms of investment and "small business generating single digit millions in revenue" is utterly unappealing to VCs, even though the investment required is downsized accordingly.

And problem #2: The cost of starting a business is too high right now. Real estate and cost of living just make it unaffordable to even try. + Healthcare if you're in the US.

This is on me for being a bit too snarky.

So yes, Desktop Linux has "gotten better". What it hasn't done is solved any of the systemic problems.

The Open Source development quirks that created the shitshow of the 1999 is still here. Gnome is better but still suffers massively from mainstream features being declared stupid by the maintainers. (A power button that turns off the machine? Heretical.)

Valve's recent successes are pretty illustrative here. They used their money to directly hijack the projects their products rely on.

For what it pertains the comparison, Windows is not without this "slow" improvement either. 95 and 98 are lightyears behind contemporary Windows in so many ways. Until quite recently it still made about as much sense to use Linux as it did back then; Not much.

Take your Linux Laptop example. Sure, Linux finally kind of worked on some specific models that were tested for it. Meanwhile, Windows had moved from "it'll work with some mucking about with drivers" to "It works universally, on practically all hardware". Really, by the mid 2010s Windows would finally be quite tolerant of you changing the hardware.

Hence my original point; Desktop Linux hasn't really caught up with Windows in any meaningful sense. Windows is just nose-diving into the ground in the last few years.

People were making that exact criticism of Microsoft Windows for decades.

It's only really in the last decade that Windows got decent enough at security for this attitude to wear off.

The beancounters have cut all the corners on physical products that they could find. Now even design and manufacturing is outsourced to the lowest bidder, a bunch of monkeys paid peanuts to do a job they're woefully unqualified for.

And the end result is just a market for lemons. Nobody trusts products to be good anymore, so they just buy the cheapest garbage.

Which, inevitably, is the stuff sold directly by Chinese manufacturers. And so the beancounters are hoisted by their own petard.

We've seen it happen to small electronics and general goods.

We're seeing it happen right now to cars. Manufacturers clinging on to combustion engines and cutting corners. Why spend twice the money on a western brand when their quality is rapidly declining to meet BYD models half the price.

---

And we're seeing it happen to software. It was already kind of happening before AI; So much of software was enshittifying rapidly. But AI is just taking a sledgehammer to quality. (Setting aside whether this is an AI problem or a "beancounters push everyone into vibecoding" problem)

E.g. Desktop Linux has always been kind of a joke. It hasn't gotten better, the problems are all still there. Windows is just going down in flames. People are jumping ship now.

SaaS is quickly going that way as well. If it's all garbage, why pay for it. Either stop using it or just slop something together yourself.

---

And in the background of this something ominous: Companies can't just pivot back to higher quality after they've destroyed all their inhouse knowledge. So much manufacturing knowledge is just gone, starting a new manufacturing firm in the west is a staffing nightmare. Same story with cars, China has the EV knowledge. And software's going the same way. These beancounters are all chomping at the bit to fire all their devs and replace them with teenagers in the developing world spitting out prompts. They can't move back upmarket after that's done.

Even when the knowledge still lives, when the people with the skills requires have simply moved to other industries and jobs, who's going to come back? Why leave your established job for the former field, when all it takes is the management or executive in charge being replaced by another dipshit beancounter for everyone to be laid off again.

With how much scale AI datacenters want and how the Trump administration has made supply problems significantly worse, we'd be talking decades, plural.

But all the economic indicators suggest those are "bad economy" layoffs dressed up as "AI" layoffs to keep the shareholders happy.

It's physically impossible to build out the datacenters required for the "AI is actually good and we have mass layoffs" scenario. This Anthropic investment is spurred on because they've already hit a brick wall with capacity.

$40B goes a long way, but not for datacenters where nearly every single component and service is now backordered. Even if you could build the DC, the power connection won't be there.

The current oil crisis just makes all of that even worse.

This is why welfare systems exist. Because otherwise the system will push people to crime, especially so in our current implementation of Capitalism where it is possible to become unemployed/unemployable through no fault of one's own.

Therein lies the problem. AI firms just bulldozed ahead and "just did it" with no consideration for the ethics or legality. (Nor for that matter, how they're going to get this data in the future now that they're pushing artists into unemployment and filling the internet with slop.)

There is no "imagined counterfactual", people just want AI firms to follow basic ethics and apply consent. Something tech in general is woefully inadequate at.

The counterfactual isn't offered by artists, but AI companies. "If we had to ask consent then we couldn't have made this". Okay, so? The world isn't worse off without OpenAI's image generator. Who cares, there's no economic value to these slop images, they're merely replacing stock assets & quickly thrown together MS paint placeholders.

Given how much of a shitshow this technology has always been (I refuse to mince words: This tech had it's "big break" as "deepfakes", and Elon Musk has escalated that even further. It's always been sexual harassment.) The actual net value to society is almost certainly negative.

This also applies to AI, just worse because:

A) AI is not a human brain, and pretending that the process of human authorship is the same as AI is either a massive misunderstanding of the mechanics and architecture of these systems, or plain disingenuous nonsense.

B) AI has no capability of original thought. Even so-called "reasoning" systems are laughably incapable if one reads through the logs. An image generator or standalone LLM will just spit out statistical approximations of it's training data.

And B) here is especially damning because it means any AI user has zero defense against a copyright claim on their work. This creates enormous legal risks.

The model for copyright trolling is trivial. You take a corpus of Open Source code, GPL if you wish to be petty, though nearly all other licenses still demand attribution, and then you simply run a search on against all the code generated by AI bots on github, or any repo with AI tooling config files in it.

Won't be long before the FSF does something similar.

Anti-fraud regulators like the SEC give an inherent trustworthiness and credibility to CEOs and other market participants. You can trust that they're not lying to you, because they would be sent to jail if they were.

Another example are general anti-fraud regulations; Consider how one would trust North American or European steel suppliers more than Chinese steel suppliers.

It's not that the Chinese are "evil lying people" and Americans are "saints who never lie", it's that you can trust American, Canadian, and European courts to hold the liars accountable by regulations even if you're not in any of those regions. But the Chinese liars won't be held accountable by regulations.

Thus also the opposite, if someone opts out of this credibility granted to them by anti-fraud regulations, their words may not be quite so truthful.

A bit of google searching later can get us a specific interview. https://www.dwarkesh.com/p/dario-amodei-2

> Let’s say half of your compute is for training and half of your compute is for inference. The inference has some gross margin that’s more than 50%.

But the context, the very previous sentence is:

> Think about it this way. Again, these are stylized facts. These numbers are not exact. I’m just trying to make a toy model here.

Here, Amodei is in effect using weasel words. He is not giving any actionable claims about Anthropics margins, merely plucking an arbitrary number. Why 50%? Is 50% reasonable? Is 50% accurate to the company? Those are all conclusions the listener draws, not Amodei.

> I don't know about SEC rules

The main premise is that, as a CEO, there are some regulations you are beholden to. You're not allowed to announce you've made a trillion dollar profit, sell all your stock, and then go "teehee just kidding". The SEC prosecute you for securities fraud if you do that stuff.

This makes such weasel words as earlier suspicious. Because the exact statement Amodei gives is not prosecutable. He's not saying anything about the company, just doing a little "toy model".

The degree to which it is intentional that this hearsay travels and is extrapolated from "Well he picked 50% because it's a reasonable figure, and because he's CEO, a reasonable figure would have to be a figure akin to what his company can achieve" into "Anthropic has 50% margin", that's up for debate. Maybe it is intentional, maybe Amodei is exactly the same kind of shitweasel as Altman is. Probably he's just a dumbass who runs his mouth in interviews and for whatever reason cannot issue the true number in an authoritative statement to dismiss this misconception.

Hence my original comment; If the real number were better than the hearsay rumours of the number, Amodei would immediately issue a correction; It'd be great for the company. Hell, even if 50% were about the margin, that'd be great! To promote that from mere hearsay to "we're profitable, go invest all your money" would also be huge. Really, any kind of margin at all would put him ahead of OpenAI.

But he doesn't issue a correction. He doesn't affirm the statement. Perhaps he has other reasons for that, but a rather big reason could be that the margin number is in fact pretty bad.

Now, the observant reader will note I am also using a weasel word there. I do not know whether the number is good or bad, your take away should be "it could be bad." Not "it is bad". Go pressure Amodei into giving us the real number.

> Most likely the subscription inference cost is much lower than you expect.

This is probably not true because they'd be screaming it off every rooftop were that the case.

Same deal with the API inference. Even the "profitable on inference" claim is sourced back to hearsay of informal statements made by OpenAI/Anthropic staff. No formal announcements, nothing remotely of the "You can trust what I'm saying, because if I'm lying the SEC will have my head" sort.

Yet making such statements would be invaluable. If Anthropic can demonstrate profitability before OpenAI, they could poach most of the funding. There's no reason to keep it a company secret.

And API inference is only part of the total costs, not even bringing in training and ongoing fine-tuning. If they're not even profitable on inference, how could they hope to be profitable overall.

Most of this is still structured around "find use cases for AI" rather than one (or more) clear use cases being the reason for adopting AI.

There's no "Lotus 1-2-3" of AI. Even the software development applications are still somewhat controversial and highly pushed based on "Sam Altman promised me 10x developers".

2) No, actually? It's not all that "clear". The current net-beneficial impacts are highly contained to software development, and even there it seems to be of dubious financial value.

This is the whole problem. AI has to be even more worldchanging, even more used, even more endlessly profitable than the smartphone. Companies are massively overinvested now, if AI turns out anything less than that, they're all fucked. The need to make "the next iPhone" has meant no product is allowed to be merely "very good".

Culturally, AI has already lost. People have always snarked about the iPhone being a luxury product that's too expensive compared to the competition, but the fundamental premise was always accepted. Even in today's era of widespread recognition that people are "on their phones too much", the smartphone itself isn't up for debate.

They loathe AI. Palantir is singing the praises of AI as a tool for fascism. There have been multiple attempts to attack Altman's house because of the "AI is so impactful it'll kill us all!" rhetoric. People are furious about what just the hype around AI alone is doing to the job market.

And in the background, everyone is aware that it's a bubble. That even if AI did everything promised and more, that it is physically impossible to build enough datacenters quickly enough and that the mass-unemployment will annihilate the economy.

You're not. This is a big reason why "tech" went so all-in on AI.

The era of rapid innovation and rapid growth on phones is over. We hit "peak smartphone" in 2019-2020, look at a chart of iphone or Samsung models. Like a lightswitch they locked in on a specific design.

Hell, the more curmudgeon-y will complain that phones have degraded since. Gone is the 3.5mm jack, gone is the SD card slot. "Fuck you, buy our expensive bluetooth junk." "Fuck you buy our cloud storage".

(The reality is that consumers appear to prefer bluetooth audio and cloud storage, phones that do still retain the 3.5mm/sd card slot aren't gaining ground in the market. Sony is likely to close down their phone division in the upcoming years despite being one of the last holdouts.)

Hence all the desire in tech to find "The next iPhone", and the dozens of attempts to make "AI hardware" despite the fact that literally all of it has failed against the simple question of "why can't this be a smartphone/smartwatch app?"

This extends to AI in general. It can't just be a tool with some specific applications, it has to "Change The World", "Be the next iPhone".

The end result of major tech companies sweeping in, taking everyone's creative work, outcompeting the originals with AI derivatives, and telling every artist on the planet "fuck off, send a job application to McDonalds" is significantly less art.

Copyright was invented to prevent exactly this scenario.

The thread's linked article is about comparing MS-DOS' security, but the comparison works on another level as well: I remember MS-DOS. When the very idea of the home/office computer was new. When regular people learned how to use these computers.

All this pretension that computers are "hard to use", that LLMs are making the impossible possible, it's all ahistoric nonsense. "It would've taken me months!" no, you would've just had to spend a day or two learning the basics of python.

> more can be reallocated from the federal government (funded with debt)

While this is the most reliable funding, it's still not very accessible. OpenAI is a money pit, and their demands are growing quickly. The US government has started a bunch of very expensive spending. If OpenAI were to require yearly bundles of it's recent "$120B" deal, that's 6% of the US' discretionary budget. 12.5% of the non-military discretionary budget. (And the military is going to ask for a lot more money this year) Even the idea of just issuing more debt is dubious because they're going to want to do that to pay for the wars that are rapidly spiralling out of control.

None of this is saying that the US government can't or wouldn't pay for it, but it's non trivial and it's unclear how much Altman can threaten the US government "give me a trillion dollars or the economy explodes" without consequences.

Further deficit-spending isn't without it's risks for the US government either. Interests rates are already creeping up, and a careless explosion of deficit may well trigger a debt crisis.

> from public companies (funded with people’s retirement funds)

This would be at great cost. OpenAI would need to open up about it's financial performance to go public itself. With it's CFO being put on what is effectively Administrative Leave for pushing against going public, we can assume the financials are so catastrophic an IPO might bomb and take the company down with it. Nobody's going to be investing privately in a company that has no public takers.

Getting money through other companies is also running into limits. Big Tech has deep pockets but they've already started slowing down, switching to debt to finance AI investment, and similarly are increasingly pressured by their own shareholders to show results.

> from people’s pockets via wealth redistribution upwards

The practical mechanism of this is "AI companies raise their prices". That might also just crash the bubble if demand evaporates. For all the hype, the productivity benefit hasn't really shown up in economy-wide aggregates. The moment AI becomes "expensive", all the casual users will drop it. And the non-casual users are likely to follow. The idea of "AI tokens" as a job perk is cute, but exceedingly few are going to accept lower salary in order to use AI at their job.

There's simply not much money to take out of people's pockets these days, with how high cost of living has gotten.

> from offshore investment.

This is a pretty good source of money. The wealthy Arabian oil states have very deep slush funds, extensively investing in AI to get ties to US businesses and in the hope of diversifying their resource economies.

...

...

"Was". Was a good source of money.