That pretty much tells you how this will end, right there.
GDP measures exchange of money with the assumption that this is a proxy for actual economic output... except cases like this where monetary exchanges like this which accomplish nothing.
Has it occurred to you, especially since one of the economists in the joke admits they feel they ate shit for nothing, that they actually do not feel the exercise was worth it? Have you never spent money on something, thinking it would be worth it, then afterwards realised it was a waste of money? Have you also never taken a job and then realised “I didn’t charge enough for the trouble”?
I’m reminded of a bit of news I heard a while back, where one teenager challenged a friend to eat rat shit they found on the street. The eater died shortly after, because the poop contained rat poison. I doubt any of them found it worth it.
If instead it was just one person and they went to a movie theater. If you ignore the entertainment value it may just look like the person through away the admission cost.
I wouldn't be surprised if they're banking long-term on its failure and got in early so they had equity preference.
https://www.teenvogue.com/story/rfk-wellness-farms-us-disabi...
> Big picture, to drive a 10% return on our modeled AI investments through 2030 would require ~$650 billion of annual revenue into perpetuity, which is an astonishingly large number. But for context, that equates to 58bp of global GDP, or $34.72/month from every current iPhone user...
As a current iPhone user, I'm not signing up for that especially if it is on top of the monthly cell service fee.
I do realize though that you were trying to provide useful context.
Think outside the coastal high paid SWE bubble and realize vast swathes of people use 5 year old phones on a $25/phone family mobile plan.
Retirees, youth, blue collar, lots of people who don’t want/need AI or wouldn’t fork out $140 for their family of 4 to access it.
$35/head is a pretty high bar if you compare to per capita total streaming subscriptions across music and movies across all providers for example.
I agree, and would add that it’s contributing to inflation in hard assets.
Basically:
* it’s a safe bet that labor will have lower value in 2031 than it has today
* if you have a billion to spend, and you agree, you will be inclined to put your wealth into hard assets, because AI depends on them
In a really abstract way, the world is not responsible for feeding a new class of workers: robots.
And robots consume electricity, water, space, and generate heat.
Which is why those sectors are feeling the affects of supply and demand.
If AI makes workers more productive, labor will have higher value than it has today. Which specific workers are winning in that scenario may vary tremendously, of course, but I don't think anyone is seriously claiming AI will make everyone less productive.
Workers being more productive does not necessarily translate to workers getting more leverage or a larger piece of the pie.
I think with a smaller employee pool though it is unlikely that it all evens out without the AI providers holding the users hostage for quarterly profits' sake.
It’s not a challenge at all.
To win, all you need is to starve your competitors of RAM.
RAM is the lifeblood of AI, without RAM, AI doesn’t work.
> Sample HBF modules are expected in the second half of 2026, with the first AI inference hardware integrating the tech anticipated in early 2027.
https://www.tomshardware.com/tech-industry/sandisk-and-sk-hy...
That's far larger than the population of the USA (unclear to me if that 650bb number is global or USA only) but by sheer scale this is assuming that these companies can collect that fee from a global customer base - including users in developing economies, EU, China, etc. and after the middleman fees are accounted for.
The comments in this thread seem to be thinking within the context of 'the poorest in their nation'. This calculation assumes collecting this fee from among 'the poorest in the world'.
Sure, 1.56bb users could also be interpreted as 'the wealthiest 20% of the world'. But the tail is especially long on this curve given how wealth is concentrated in a small percentage of the global population (1% of users have 50% of wealth).
Obviously, China will protect its homegrown AI industry. Current geopolitics trending towards US decoupling in Europe might slow it. But under the old status quo, US AI would have been rapidly adopted in the EU (and it still might. It depends greatly on how much of the Trump Doctrine outlasts the current administration).
Developing countries eventually adopt new technologies. First they adopted personal computers and became customers of Microsoft, then they adopted the Internet and became customers of Google, they adopted smartphones and became customers of Apple. Eventually they will adopt AI and become customers of someone. The question is whether it will be US tech or Chinese tech.
Even if scaling hit a wall, commoditizing what we have now would do it. We have so much scaffolding and organizational overhang with the current models, it’s crazy.
Bunch of tiny companies would love to hire a mathematician to optimise what they are doing to get a 5-10% improvement. Unfortunately a 5-10% improvement in a small business can't justify the cost of hiring another person, and good mathematicians with business sense and empathy are a rare commodity.
You can reduce quality of cleaning. But it's very hard to clean faster and better at the same time.
These industries are not going to be optimized by an AI. The only optimization is lower overhead or lower salaries.
Sure, we could have robots in daycare, but I don't think lack of AI is why my wife would have concerns :)
Teachers, cleaners, and daycare workers may see 0% gains, but don't be surprised if that is made up for by 10% gains the productivity of tech, law, marketing, advertising, manufacturing, government, etc. (okay maybe not government).
Consider all the labor and capital spent across all the advertising real estate in the world. Commercial, online ads, billboards, labeling. The inputs to make all these things are now greatly reduced. To increase productivity, it doesn't matter that the market is flooded, just that it's much easier to make these things.
At some point you're stacking bricks and hitting nails.
AI just won't make you stack bricks much faster :)
The list of people claiming that maths won't work who then get bulldozed by mathematicians is long.
https://www.bea.gov/sites/default/files/2026-01/gdp3q25-upda...
Given how much of the spending is hard goods and simply not AI-able (rent, most of housing new construction, most of other goods, most health care, much of other services), the replacement theory would require a massive displacement.
Or obviously it can be spread out, e.g. ~1% additional increase over 5 years.
Developed countries have slow growth because they need to invent the improvements not just copy what works from other countries.
Starting at 1949 is overly generous IMO, but yes the purges that followed didn’t help.
Chinese GDP was higher during WWII than over the next several years, the actual minimum 1959 to 1961 was well into communist rule. Literally CCP rule was worse than the anarchy of civically war, it’s right up there with the insanity of Pol Pot.
There was no GDP data under KMT - it wasn't even formally calculated.
CCP started GDP calculations, but using soviet MPS GDP accounting system that basically omitted services and lowballed production prices.
The only GDP data we have that is pseudo normalized are via estimates like Maddison project. Even they don't bother to recompose China/KMT data during WW2. The TLDR is prewar peak 1939 data (right before JP invasion) around 288B, PRC took over in 1949, GDP was 245B in 1950, grew to 306B by 1952. GLF tanked GDP from 460b to 350B... i.e. the worst case scenario of GLF floor was still 40% larger than 1950.
E: Note wiki data links to ourworldindata that pulls from Maddison and in table form KMT/WW2 data is not available and only pulling from closest data point 1938/1950 and naively extrapolating per capita. Because KMT data doesn't exist.
At the low end of economic output starvation or the lack thereof is a strong indication of GDP. You do need to adjust for exports and imports but you don’t need to have a particularly deep insight into the economy beyond that.
> starvation or the lack thereof is a strong indication of GDP
No that's just an indicator that some cohort starved due to distribution failure. And to be blunt... that cohort was rural / peasants doing mostly subsistence agriculture tier production that do not count much towards GDP. An urban worker in industry can generate 10x GDP surplus than farmers in a commune.
Hence starvation (mostly in rural) has disproportionately less GDP weight vs urban worker productivity. An economy losing millions of peasants while still modernizing/industrializing can easily maintain higher total GDP than peaceful agrarian society. AKA CCP speed running first 5 year plan post WW2 raised the GDP floor so much that they can unalive 10s of millions of peasants and still have higher GDP vs pre/post war which, was incidentally also not peaceful agrarian society, but even messier interregnum shitshow with significantly shit state capacity than relatively unified postwar PRC under CCP. Republican Era KMT (during anarchy/civil war) simply couldn't organize fragmented China to be as productive as PRC under CCP, who can lose millions of peasants with marginal productivity of labour near zero and still do massively better in gdp/economic terms.
Re-education camps don’t generate value. They didn’t have a surplus of urban workers instead Mow just destroyed the economy. Killing off the educated doctors etc isn’t a free action, it has negative consequences.
China literally had net migration out of cities, so no this wasn’t over investment in industry or a distribution issue this was just abject failure and total economic collapse. Total Anarchy would have been better for the economy than Mao.
1. Mass starvation at a few points due to central planning errors
2. Horrifying purges and paranoia that cannot be excused as "errors"
3. Achieving mass literacy and a partially industrial economy in a single generation, from a medeival starting point.
Most good Americans who paid attention in civics class learned 1 and 2 very well without truly appreciating 3.
You have to understand that they were coming from a peasant economy where nobody could even read. It's an accomplishment despite Mao's shortcomings and awful deeds. And look at the scoreboard today. Highest GDP by purchasing power parity in the world. Xiaomi cars are nicer than Teslas, only non-American tech industry, high speed rail, etc etc.
There’s a long list of countries that industrialized more quickly without suffering such internal economic issues. The USSR and China suffered because of poor governance not industrialization.
Second, Mass literacy occurs via teaching kids. It has little to do with what the wider economy as seen by both modern and historic literacy rates.
It’s been 65 years since the Chinese famine, what actually fixed the country was economic reforms. MAO’s death helped but the system simply didn’t work so they tried something else.
Between 1954/ 1959 PRC exchanged material for capita goods and Soviet training speed run industrialization. AKA they were turning surplus rocks they couldn't process into machines so they can process non export into capita stock. You know, developing. This economic/history 101.
Mao even including GLF engineered one of the greatest most condensed human uplift effort. World Bank summary of CCP progress from postwar to 70s, i.e. under Mao noted how PRC, relative to developing pears was significantly more industrialized, like 40% vs low income avg 25% share of economy. With matching proxy indicators like 3x energy consumption per capita vs India, 2x literacy, 1/3 infant mortality rate. aka Mao speedrun PRC to middle income industrial levels - GLF one step back, 5 step forward success. State provided services were also assessed to be far more effective in meeting basic needs vs low income peers. Life expectancy 65yrs vs 50yrs (India) for low income... "outstandingly high" in WB remark. WB concludes CCP efforts by late 70s... again Mao's doing left "low-income groups far better off in terms of basic needs than their counterparts in most other poor countries"... "most remarkable achievement during the past three decades".
All the subsequent snowballing from Deng, not possible without Mao building a captive, mobile, diciplined rural workforce with high industrial experience, reeducating masses to be fungible workers for migrant economy.
In retrospect, GLF in fact, close to free action. Post WW2 PRC was so devoid of talent that Mao could depopulate cities and slap doctors around with trivial long term penalty option. Starting proper industrialization, mass mobilizing low end barefoot doctors alone out state capacities GLF/CR missteps and saved more lives than it bled. i.e. even in terms of mortality vs death averted, Mao comes out massively ahead. That +15 years above baseline life expectancy x 1000 billion new births is about ~200m lives worth. This not accounting averted deaths of countries who started similarly but did not poverty / malnutrition alleviate early enough, i.e. India generating GLF deaths every few years over decades. That averted another 200m deaths. Most of this attributed to Mao speedrunning nation building did actually solve famine after GLF via all the infra built. Something that historically every Chinese polity had to worry about.
Any leader who improved HDI for as much people in as short of a time as Mao would have been given a Nobel Economics Prize and Nobel Peace Prize. Fixating on spike of deaths at PRC scale is boring libtard innumeracy, i.e. ~4% which plenty of leaders of matched/exceeded. Not nice but completely valid to treat human resources as resource and trade for long term gains. Mao increased PRC industrial output by like 30x, from macro economic utilitarian, HDI trend line goes up, PRC brrrting growth, dead peasants and sad elites simply doesn't fucking matter, it's minor shock to overall system capacity which Mao built so much in so fast that it raised aggregate Chinese HDI above most peers even if it also broke a few millions of eggs.
This wasn’t an exchange of good this was a subsidy. Loan repayments at extremely generous 1% interest rates. The use of raw materials shows just how poorly their efforts where despite the aid.
You can try and repaint history into a history of pulling themselves up, but the reality is they had a high literacy rate and for the time period a well functioning economy before the communists took over. Afterwards 50 million people starved to death that’s not progress that’s horrifying inefficiency writ large.
The CCP still has a hate boner for Taiwan because it shows they are objectively doing a bad job as that fragment of the same country still has a higher standard of living and better technology despite the massive disadvantages of vastly smaller economies of scale.
Chinese literacy rates was fucking pre CCP, it was agrarian nation that CCP uplifted. If you want to cope with repainting history, go accuse world bank... in the 80s, by every metric except human lives, CCP was horrifyingly efficient, precisely because they value human lives less.
What techstack does TW have that PRC doesn't? TSMC based off foreign tech stack. Let's not forget ROC is also outcome of subsidy / finance program by US. The difference between PRC and ROC is PRC sugar daddy was poor USSR, TW was rich US, and population scale means US could injected more to smaller pop to bring up development. All while US+co sanctioning PRC btw, hence PRC succeeded where TW has not, and did so on hard mode.
Smaller economies of scale is precisely why TW/ROC is unimpressive, TW should be much richer for how small it is and how lavishly it was rewarded. There's reason TW has to literally ban TWners from working in PRC high end industries... because PRC tier1 opportunities has vastly exceeded TW.
We could have simply not calculated imputed rent (or all of rents).
In 1979, median income in the US was $16,530 USD a year.
Not exactly an apples to apples comparison.
Certainly, as just a few examples, they are not for the well-being of the Uyghar population or pro-democracy activists or journalists investigating human rights violation or supporters of Tibetan independence.
Apple will be around in a hundred years.
Will the USA?
By the 19th century, the rise of nation-states accelerated due to the spread of nationalism, the decline of feudal structures, and the unification of countries like Germany (1871) and Italy (1861). Centralized governments, uniform laws, national education systems, and a sense of collective identity became defining features. The French Revolution (1789) played a pivotal role by promoting citizenship, legal equality, and national sovereignty over dynastic rule
Maybe in 2300 they'll say something similar about nationalism
The world is changing fast.
I only have a meme to describe what we are facing https://imgur.com/a/xYbhzTj
The tech industry going through a boom and settling back down at a higher place than before isn't the end of the world. They all start merging together soon.
If that comes to pass you will work the same or more for less money than now.
Basically jump back to a true plutocracy since only a few people will syphon the wealth generated by AI and that wealth will give them substantial temporal power.
Well, there you go; as they say, it's okay for trivial stuff.
This shit was legacy when I was a wee new hire.
Github Copilot has been great in getting that code coverage up marginally but ass otherwise. I could write you a litany of my grievances with it but the main one is how it keeps inventing methods when writing feature code. For example, in a given context, it might suggest `customer.getDeliveryAddress()` when it should be `customer.getOrderInfo().getDeliveryInfo().getDeliveryAddress()`. It's basically a dice roll if it will remember this the next time I need a delivery address (but perhaps no surprises there). I noticed if I needed a different address in the interim (like a billing address), it's more likely to get confused between getting a delivery address and a billing address. Sometimes it would even think the address is in the request arguments (so it would suggest something like `req.getParam('deliveryAddress')`) and this happens even when the request is properly typed!
I can't believe I'm saying this but IntelliSense is loads better at completing my code for me as I don't have to backtrack what it generated to correct it. I could type `CustomerAddress deliveryAddress = customer` let it hang there for a while and in a couple of seconds it would suggest to `.getOrderInfo()` and then `.getDeliveryInfo()` until we get to `.getDeliveryAddress()`. And it would get the right suggestions if I name the variable `billingAddress` too.
"Of course you have to provide it with the correct context/just use a larger context window" If I knew the exact context Copilot would need to generate working code, that eliminates more than half of what I need an AI copilot in this project for. Also if I have to add more than three or four class files as context for a given prompt, that's not really more convenient than figuring it out by myself.
Our AI guy recently suggested a tool that would take in the whole repository as context. Kind of like sourcebot---maybe it was sourcebot(?)---but the exact name escapes me atm. Because it failed. Either there were still too many tokens to process or, more likely, the project was too complex for it still. The thing with this project is although it's a monorepo, it still relies on a whole fleet of external services and libraries to do some things. Some of these services we have the source code for but most not so even in the best case "hunting for files to add in the context window" just becomes "hunting for repos to add in the context window". Scaling!
As an aside, I tried to greenfield some apps with LLMs. I asked Codex to develop a minimal single-page app for a simple internal lookup tool. I emphasized minimalism and code clarity in my prompt. I told it not to use external libraries and rely on standard web APIs.
What it spewed forth is the most polished single-page internal tool I have ever seen. It is, frankly, impressive. But it only managed to do so because it basically spat out the most common Bootstrap classes and recreated the W3Schools AJAX tutorial and put it all in one HTML file. I have no words and I don't know if I must scream. It would be interesting to see how token costs evolve over time for a 100% vibe-coded project.
"notoriously bad" is news to me. I find no indication from online sources that would warrant the label "notoriously bad".
https://arxiv.org/html/2409.19922v1#S6 from 2024 concludes it has the highest success rate in easy and medium coding problems (with no clear winner for hard) and that it produces "slightly better runtime performance overall".
https://research.aimultiple.com/ai-coding-benchmark/ from 2025 has Copilot in a three-way tie for third above Gemini.
> Have you tried (paid plans) codex, Claude or even Gemini on your legacy project?
This is usually the part of the pitch where you tell me why I should even bother especially as one would require me to fork up cash upfront. Why will they succeed where Copilot has failed? I'm not asking anyone to do my homework for me on a legacy codebase that, in this conversation, only I can access---that's outright unfair. I'm just asking for a heuristic, a sign, that the grass might indeed be greener on that side. How could they (probably) improve my life? And no, "so that you pass the bare minimum to debate the usefulness of AI tools" is not the reason because, frankly, the less of these discussions I have, the better.
If you want to see if your project and your work can benefit from AI you must use codex, Claude code or Gemini (which wasn't a contender until recently).
So it would be easy to link me to something that shows this consensus, right? It would help me see what the "consensus" has to say about the known limitations of Copilot too. It would help me see the "why" that you seem allergic to even hint at.
Look, I'm trying to not be close-minded about LLMs hence why I'm taking time out of my Sunday to see what I might be missing. Hence my comment that I don't want to invest time/money in yet-another-LLM just for the "privilege" of debating the merits of LLMs in software engineering. If I'm to invest time/money in another coding LLM, I need a signal, a reason, to why it might be better than Copilot for helping me do my job. Either tell me where Copilot is lacking or where your "contenders" have the upper-hand. Why is it a "must" to use Codex/Claude/Gemini other than trustmebro?
We got lucky with the dotcom bubble.
There's no guarantee of anything, and it's totally possible for the industry to collapse and stay that way.
I don't recognize that cartoon and there's no audio. I'm going to need help with that one.
The numbers actually work really well, (un)fortunately.
Half this board is in the most hyped echo chamber I’ve ever seen.
Even if these things worked great for everyone, the percent of free uses who convert to paid users is low single digits per cent. For OpenAI to have any chance of breaking even in the consumer space, they need to develop an ad biz that makes around 20-25% of G does. That's a tall order in that G doesn't make good dough from search anymore as SERP page clicks are down 80% with AI summaries being good enough for most.
I pay for gpt myself, and my work pays for Copilot, GPT, Claude, cursor, Glean, and other enterprise tools. And we make enterprise tools on top of AI that our customers pay extra for.
Averaging the revenue over headcount isn’t the right model, anymore than it would be for RIOT games or YouTube.
The famous MIT study (95% of AI initiatives fail, remember that one?) actually found that pretty much every worker was using AI almost daily, but used their personal accounts (hence the corporate ones not being used).
If you are brand new to the tech world, and this is your first new product cycle, the way it works is that there is a free-cool-we're-awesomely-generous phase, and then when you are hooked and they are entrenched, the real price comes to fruition. See...pretty much every tech start-up burning runway cash.
Right now they are getting us hooked, and like the dumbasses consumers are, they will become totally dependent and think it will stay this cheap.
I also often see people post AI generated advice and answers that are simply incorrect in Facebook groups and get roasted with 100s of people chiming in on how you can trust ChatGPT.
I just can't see regular people are going to pay more than (NetFlix + HBO + Prime + WM+) for an AI subscription. I think you would see tons of competitors pop up if that were at all viable.
That has indeed been the strategy, but it's not like it always or even usually works out. We've seen plenty of companies that try to raise their prices and people aren't hooked. (Though I am almost certain in this case at least professionals if not the general public will indeed be hooked.)
What they found is that people search the Internet for things and an AI bot is right there. What they didn't find is people using Vibe coded apps, learning from AI or buying AI services. They did find companies buying AI services, but as an experiment. Also, blaming AI is easy when someone messes up and costs a customer or sale. The more that happens, the sooner the company stops experimenting. If that happens in a widespread way, then this bubble collapses.
None of them ever considered getting a paid account, nor would they have. I'm not saying nobody will, but if you actually don't know any such people then there is something unusual about the crowd you run with.
If I understood you correctly and my math is correct, your suggestions only cover 6% of 650 billion, the news is suggesting AI companies need more than 10x more. So either it's 5 billion people paying 60-80, or 500 million people paying 600-800/month, or something in between + a little extra.
But we're still short on 26%
> Something they find as indispensable as a cell phone or internet bill.
Source?
I find it funny that Microsoft is scaling compute like crazy and their own products like Copilot are being dwarfed by the very models they wish to serve on that compute.
Meanwhile Apple is only spending 1 billion a year to use Google's models.
The problem isn't that AI/LLMs can't be useful or generate revenue, the problem is still the cost. We're no where near production ready AI, it can sort of do coding and some medical stuff, but we're not at a level of technology where the potential is fully realized. How much are investors willing to pour into more research?
We looking at OpenAI contemplating ads and erotic chatbots. That's not a successful business who have those ideas for profit generation.
Revenue is pointless without eventual profit.
If you take half the software engineers in the US and replace them with AI, you're halfway there. And why stop with software?
There's a reason for the fervor and excitement of these companies.
The positive outlook is that you don't fire folks - they have even more work to do. But we'll see how it pans out in practice.
Sure I assume there's a good market there, luxury yachts exist after all, but what is a company like Netflix going to do when people are too poor to even afford the streaming services that cost 10 bucks a month?
Not to get conspiratorial, but the only logical thing for me here is that They want as many of the plebs dead as possible so that the remainder of us are beholden to them and their money, once they own all the AI factories.
Or this kind of financial crash is exactly what they want. If they can drive the markets to failure, only the largest companies can hold on - and acquire more of the failing companies in the process.
The issue is that every company in a position to do so is trying to stake a claim in a new market. Not every company will win. No-one has a surefire way of identifying "mistakes" ahead of time.
What alternative do you think would work better, short of central planning?
Do high interest rates not, by definition, favor capital over labor?
The economics are not all in profit.
The really stupid bubbles end up getting themselves metastasized into the public retirement system, I'm just waiting for that to start any day now.
Not sure what you mean exactly but every single 401k is tied into this.
It seems so blatantly obvious, yet nobody wants to listen, and practically everyone knows better. We live in interesting times.
> bizarre
It isn't bizarre at all. Without work people devolve into playing video games and smoking pot in their mom's basement.
I remember summer vacations from school. It was great for a while, but soon I was looking forward to getting back to school.
Where I grew up the people who didn’t work almost universally turned into consumers of everything and creators of basically nothing. The exceptions were retirees who had a lifetime if work experience prior to their idle years. For those folks it was gardening and other similar hobbies that provided meaning but not much output for society as a whole.
I think if you offered the entire population the ability to do no work other than what they felt like doing, exceedingly few people would be motivated to do the needful. A few more would be motivated to do things like create art and otherwise contribute back to other people but I am thinking along the lines of the 80/20 rule here.
I think our future if we ever figured out automation and UBI looks a lot like Wall-E vs some sort of utopia. In fact I believe that sort of setup is as close to a utopian society as I can imagine being realistic.
I did apartment maintenance for a place where about half the recipients had paid for rent, utilities, and bare necessities provided by the government. It was easy to play the odds and know which apartment was which the moment you stepped foot into one. It’s not a perfect correlation to what UBI would look like for many reasons, but it’s closer than the average upper middle class suburbanite imagines people will act like if given the opportunity.
I think UBI advocates may have a point once you're 2-3 generations into some sort of UBI system. But bootstrapping that system is not possible, most people will revert to do nothing of value to society, no projects, nothing.
Why aren’t you smoking pot in your basement?
People can find other things to do than work for a wage. I don’t get what your original objection is about when you yourself work even though you don’t have to.
Some local volunteer organizations seem to only have people 60+ years of age.
I have no problem finding fulfilling and meaningful projects outside of my work! There are many people like me :)
I'm sure there are. Doesn't mean most people are like that. Consider retirees. Some find meaningful activities, many just rot away out of not having a purpose.
What percentage of people currently living off of welfare are doing meaningful work?
Do you have that number? Do you have any numbers to back up your claims or are you just talking about what works for you?
Most of them, since the vast majority of "welfare" programs exclusively assist people who are in work.
People devolve like that when they have no purpose or opportunities. Which I’m sure would happen with the real goal of UBI: barely subsistence support in order to grow a larger pool of reserve labor while the rich (who are not degenerate at all[1]) live large.
Purpose, though, comes from within.
I also get the feeling that such experiments just prove that giving people money makes them happier. But there’s nothing to account for the fact that prices in the market haven’t changed, the tax structure hasn’t changed, and no goods or services experienced any shortages.
I'm not aware of any realistic UBI tests. Could you point me to any?
The ones I'm aware of were either or both:
1. Time limited, so participants were aware that they needed to still have a job or at least be employable after the experiment has concluded.
2. Were funded externally, so participants only reaped the benefits of UBI but didn't incur the drawbacks (i.e. didn't have to fund the program by much higher income taxes) which could have discourage them from working.
It was basically a supplementary source of income - money for nothing for a limited time period, not an actual UBI program.
Skill issue
Some people might, others wouldn't. Not everyone is a pot-smoking teenager.
UBI guy playing games in moms basement comes accross as harmless in comparison.
People would work for two reasons. One is to make extra money and afford a lifestyle beyond what UBI provides. The second is to… do things that are meaningful. If people derive meaning from work then that’s why they’ll work.
Some people will just sit around on UBI. Those are the same people who sit around today on welfare or dead end bullshit jobs that don’t really produce much value.
I’m not totally sold on UBI but there’s a lot of shallow bad arguments against it that are pretty easy to dismiss.
The "twist" is they rot as e-waste every 18 months when newer models arrive, generating roughly 30,000 metric tonnes of eWaste annually[0] with no recycling programmes from manufacturers (like Bitmain)... which is comparable to the entire country of the Netherlands.
Turns out the decentralised currency for the people is also an environmental disaster built on planned obsolescence. Who knew.
[0]: https://www.sciencedirect.com/science/article/abs/pii/S09213...
Only proof of work systems, such as Bitcoin. Proof of stake such as Ethereum is a lot less energy intensive
Is it any worse now than say, the NYSE ?
This reference says energy usage was 0.0026 TWh (2.6 GWh, or 2600 MWh) in a year
https://ethereum.org/energy-consumption
If the power was used over the whole year (and not just one hour)
(2600 MWh / year) / (24 * 365 h/year) = 0.29 MWh = 296 kWh. Thats like hair dryer levels of power consumption (if the hair dryver was left on all the time)
Let's say tomorrow OpenAI and Anthropic have a huge down round, or whatever event people think would mark the end of the bubble. That doesn't mean suddenly nobody is using AI. It means they have to rapidly reduce burn e.g. not doing new model versions, laying off staff and reducing the comp of those that remain, hiking prices a lot, getting more serious about ads and other monetized features. They will still be selling plenty of inferencing.
In practice the action is mostly taking place out of public markets. We won't necessarily know what's happening at the most exposed companies until it's in the rear view mirror. Bubbles are a public markets phenomenon. See how "ride sharing"/taxi apps played out. Market dumping for long periods to buy market share, followed by a relatively easy transition to annual profitability without ever going public. Some investors probably got wiped along the way but we don't know who exactly or by how much.
Most likely outcome: AI bubble will deflate steadily rather than suddenly burst. Resources are diverted from training to inferencing, new features slow down, new models are weaker and more expensive than new models and the old models are turned off anyway. That sort of thing. People will call it enshittification but it'll really just be the end of aggressive dumping.
It's also possible non-tech industries just have a collective imagination failure and can't find use cases for AI, but I doubt it.
Some local models run well already too and do the job. Not sure if i would pay any money when a discarded mac can run these just fine already.
This may turn out like trying to make people game over streaming.
At least, the GPUs that are currently plugged in. A lot of this bullshit bubble crap is because most of those GPUs (and RAM) is sitting unplugged in a warehouse, because we don't even have enough power to turn all of them on.
So if your question is how to use a GPU... I got plenty of useful non-AI related ideas. But only if we can plug them in.
I wouldn't be surprised if many of those GPUs are just e-waste, never to turn on due to lack of power.
That's my fear.
The problem is these GPUs are specifically made for datacenters, So it's not like your average consumer is going to grab one to put into their gaming PCs.
I also worry about what the pop ends up doing to consumer electronics. We'll have a bunch of manufacturers that have a bunch of capacity that they can no longer use to create products which people want to buy and a huge backstop of second hand goods that these liquidated AI companies will want to unload. That will put chip manufactures in a place where they'll need to get their money primarily from consumers if they want to stay in business. That's not the business model that they've operated on up until this point.
We are looking at a situation where we have a bunch of oil derricks ready to pump, but shut off because it's too expensive to run the equipment making it not worth the energy.
Servers can (and do!!) use 10+ year old hardware. Consumers are kind of the weird the ones who are so impatient they need the latest and greatest.
Seems like the G in GPU is very obsolete now:
https://www.tomshardware.com/news/nvidia-h100-benchmarkedin-...
> As it turns out Nvidia's H100, a card that costs over $30,000 performs worse than integrated GPUs in such benchmarks as 3DMark and Red Dead Redemption 2
The flock cameras are going to be fed into them.
The bitcoin network will be crashed.
A technological arms race just occurred in front of your eyes for the past 5 years and you think they're going to let the stockpile fall into civilian hands?
That's truly e-waste. Now in practice, we programmers find uses of 10+ year old hardware as cheap webhosta, compiler/build boxes, Bamboo, unit tests, fuzzers and whatever. So as long as we can turn them on we programmers can and will find a use.
But because we are power constrained, when the more efficient 1.8nm or 1.5nm chips get released (and when those chips use 30% or less power), no one will give a shit about the obsolete stockpile.
In what sense? Not competitive for chat bot providers to use? Is that a metric that matters?
> when the more efficient 1.8nm or 1.5nm chips get released
What if they don't get released? You don't have a broad and competitive set of players providing products in this realm. How hard would it be to stop this?
> no one will give a shit about the obsolete stockpile.
You have lived your life with ready access to cutting edge resources. You ever wonder how long that trend could _possibly_ last?
I would love to live in the world where everyone joins a pool for inference or training, and as such gets the open source weights and models for free.
We could call it: FOSS
No they're not. You don't get to decide what other people desire.
Wild speculation detached from reality which destroys personal fortunes are not "a desirable feature."
It's only a "desirable feature" to the nihilistic maniacs that run the markets as it's only beneficial to them.
This is not the definition of a bubble, and is specifically contrary to what i said.
A good bubble, like the automobile industry in the example I linked, paves the way for a whole new economic modalit - but value was still destroyed when that bubble popped and the market corrected.
You may think its better to not have bubbles and limit the maximum economic rate of change (and you may be right), but the current system is not obviously wrong and has benefits.
... and which forces do you think are the core concept of "the American experiment"?
With these assumptions:
– Big 4 keep spending at current pace for 3 more years
– Returns only start showing after aprox 2 years
– Heavy competition with around 20% operating margin on AI and Cloud
– Use of 9% cost of capital
This is the current reality:
AWS aprox $142B/yr
Azure aprox $132B/yr
Google Cloud around $71B/yr
Combined its about $330B to $340B annual cloud revenue today
And lets says Global public cloud market of $700B total today.
To justify the current capex trajectory under those assumptions, by year 3 the big hyperscalers would need roughly $800B to $900B in new annual revenue just to earn a normal return on the capital being deployed.
That implies combined hyperscaler cloud and AI revenue going from: $330B today to $1.2T within 3 years :-))
In other words...Cloud would need to roughly do 4× in a very short window, and the incremental revenue alone would exceed the entire current global cloud market.
So for the investment wave to make financial sense, at least one of these must be true:
1 Cloud/AI spending globally explodes far beyond all prior forecasts
2 AI massively increases revenue/profit in ads, software, commerce and not just cloud
3 A winner takes all outcome where only 1 or 2 players earn real returns
4 Or a large share of this capex never earns an economic return and is defensive
People keep modeling this like normal cloud growth. But what we have is insanity
But the real money was investment that didn’t see a return for the investor. The investments needed to have higher final consumption (such as through better productivity or through displacing other costs) to pay back the investment.
You’re ignoring the fact that gaming is going to the cloud.
That industry is bigger than Hollywood.
Desktop computers will invariably follow.
The RAM shortage will drive the transition.
For instance, my wife uses her personal laptop about four days a year.
People like that won’t be buying personal desktops or laptops, five years from now. The RAM shortage will drive a transition into thin clients.
I already see it with our kids. They use an iPhone, unless they need to type. Then they use an iPad with a BT keyboard.
Eventually China will catch up in EUV fabrication and flood the market with cheap silicon. When that happens a terabyte of RAM will cost what 128gb costs now.
In the saddest way possible, the niche of gamers are people playing on desktops with ethernet connections.
The majority of gamers are buying booster packs on mobile games.
Throughput has increased but latency hasn’t changed much
Latency hasn’t decreased substantially since the late 90s when I remember getting sub 50 ms ping in Quake III from my dorm room in college
By that yardstick, we've actually done very well in a lot of cases. :)
You think we'll replace gaming and desktop computers into the cloud in the timeline of the poster above (2-4 years?)
Just not realistic.