If most of the jobs its creating are related to construction of infrastructure then that's not really positive news as these jobs are temporary, once demand settles then why kind of jobs are going to be created?
It might be benefiting other areas, but I think as the technology improves a lot of those are going to start looking like what's happening in software development (which is arguably what the technology is best at right now).
Most of these jobs are the same jobs that arose thanks to the CHIPS and IRA. Much of the AI boom and trade is building on top of the capex that arose from the semiconductor/hardware portfolio during that era.
Many of the current DCs being built out are also being powered or tied with renewable energy projects that were funded by the IRA, as many DC builders with deep pockets do know the political dimension. If this is what keeps the CHIPS, IRA, and the IIJA alive I'm happy.
Every industry and career type goes through ebbs and flows. The 2010s was a white collar boom, and the 2020s is now a white collar bust. Meanwhile the 2010s was a skilled trades bust and the 2020s is now a skilled trades boom.
There is almost always a next big thing. What happens when it ends is people move to the next thing. Practically everything needs some kind of construction, management, software, hardware, etc.
I'd be rich if I knew what the next big thing was but the economy has been running on the assumption that there will be a next big thing for many, many decades. Each cycle has the same rhymes of "what happens when it ends" questions but there has always something.
The construction jobs are only temporary if the compute infrastructure build-out decelerates. That seems pretty unlikely in the mid-term! It would mean that, like, there's a fixed appetite for data centers, and once we satisfy that appetite, we stop building them.
For better or worse, it looks more like that we're gonna tile the whole damn planet in data centers, at a faster and faster clip.
> The Economist estimates that AI has so far created around 1m new jobs in America. That easily exceeds the roughly 200,000 lay-offs attributed to AI since mid-2023, and appears more than enough to offset weaker hiring in many back-office roles. America’s AI infrastructure splurge has created many of them. (...) That building spree requires armies of workers: electricians to wire them, HVAC specialists to stop racks from overheating, grid engineers to hook them up to the power supply and technicians to install and maintain the machines.
I'm not sure whether the salaries of the new jobs are on par with those of the lost jobs.
"easily exceeds the roughly 200,000 lay-offs attributed to AI "
Except that is hogwash, "attributed to AI" is basically the CEO screwing up something in the business and AI-washing their mistake because it's convenient.
“One million high-paying upper-middle class family supporting jobs were destroyed, but on the bright side, one million minimum-wage Walmart greeter jobs were created! See? We’re breaking even!”
I'm a consultant and I've already worked for multiple AI companies that shut down over the last two years. I think the main problem is that they all are relying on the big token providers and trying to capture value with various services.
At some point the token costs will increase so much, it will put all of these AI companies out of business.
Don't get me wrong. AI is definitely useful. The high costs are currently being subsidized by VC and other investors and unless there is a major breakthrough, it's just not going to work in the long-term.
That would be even worse for them, since then current customers of these AI-middleman corpos would just start deploying their own self-hosted and private LLM services. In before the complexity argument, there may well be some completely different middlemen corpos, who will assist in such deployments and initial ramp-ups.
Self-hosting takes either cloud- or on-prem-engineering chops, which are in short supply. In my view, that becomes the primary driver for lowering token costs. Secondary are the alternative model sources like Z.ai and Moonshot, which between open weights and lower prices help to drive commoditization. But there is a political risk with these, for example, Z.al is on the U.S. Department of Commerce Entity List, which blocks American companies from selling advanced technology and goods to the firm.
you seem to be discounting or unaware of the possibility of a) automating a significant chunk of new buildouts, and b) domestic companies seeking a slice of the “sell open model hosting for less than competitors” pie.
I truly believe the cost per token for most people will eventually go approximately to zero even in the absence of subsidy unless there is a dramatic state intervention to curtail free computing and hardware R&D and manufacturing.
There seems to be a weird self-fulfilling narrative here:
1) "AI companies will go bust because tokens will cost too much" >> 2) "Don't let them build data centers that will sit empty" >> 3) Demand outstrips supply by a lot >> 4) Token costs too much.
This is no different from the NIMBY's that block all the housing then sit in a huff saying "see! everyone's leaving. good thing we didn't build anything!" when the rents go up.
Are you seeing companies that are in over their heads because they don't have enough domain knowledge?
I think that's always been an issue in tech, but it feels like AI exacerbates the issue. I see people starting companies and services where their primary domain knowledge seems to be whatever their AI tells them. It's sometimes enough to get off the ground, but I wonder how long it takes for customers/clients who actually need the domain knowledge to bail.
Not to mention if you make a successful value add the token provider will add it to their own harness and they're not paying the retail price they charge you for the tokens they consume.
yea this is something I've been wondering about. I'm not too keen on the finance aspect, but I understand that the big players aren't turning a profit. OpenAI is still losing money. I've seen some discussion related to increased token costs. If that continues, isn't dependence on their services a risk?
I believe this to be completely mistaken, because the bang-for-buck is getting better. Luna on max thinking is very capable and builds you a feature for 20 cents.
Its just that in a gold rush, there are few winners and many losers. There used to be hundreds of car companies in the beginning, only a dozen or so survived long term.
I can’t read the article but in my group, which is not terribly AI exposed due to its hands-on nature, we are in fact hiring extra people into next year to handle additional AI initiatives that I am confident will succeed. In subsequent years, the plan as I have heard it is to let headcount go down by attrition.
I would not take extra hiring now as evidence that AI is preserving job numbers.
The article mostly cites the huge growth in blue-collar jobs caused by the data center buildout. It’s very handy-wavy about white collar jobs, “yes lots of jobs have been lost, but also the tech sector always has a lot of year-to-year churn, maybe this is just churn”.
Not a super insightful article. The AI jobs apocalypse may or may not be real, but this article doesn’t provide any compelling evidence for its thesis.
It's handy-wavy because nobody knows how it will turn out and which new jobs will be created. In the same way as every predictions about AI bust, job lost, moat (or lack of it) is. If you feel confident about your predictions, don't.
I was laid off as a senior product manager in December of 2025. I’ve been looking for a new job in clean energy (which is supposedly “having a moment” due to data centers) since then. There is no “jobs boom”. There are certainly job openings — black holes into which you can lodge your resume. Occasionally, multiple rounds of interviews that go nowhere. I’ve been paying my bills as an art fabricator and live event electrician, the kinds of blue collar jobs that are supposed to make up for the destruction of “knowledge work”. The work is inconsistent, and the pay is less than half of what I made before. There is no “jobs boom”, of any kind.
While I'm still catastrophically worried about what AI means for my career, I've noticed that my current employer - very AI forward, and growing the team - is still facing an ever expanding backlog.
High productivity is generally good for the employee, unless you're productive enough you run out of work to do. So how much code is needed?
Yes I’ve seen very little change over the past 3 years in my role (platform engineering) except mostly JIRA tickets are more unreadable because people just have Claude vomit a novel into it.
I mean I use it every day of course, but the velocity of work doesn’t really seem to be budging lol. And frankly a lot of time wasted on AI made gadgets, and meetings about those gadgets (look at this dashboard Claude made! etc)
I hope this results in a rebalancing of the social and economic power of high-IQ versus average-IQ workers. We will need construction workers and tradespeople to build and maintain these AI data centers. Probably even with robots. But we won’t need as many engineers, lawyers, and other people whose job it is to consume and generate bits. If we tax the proceeds of AI generated productivity sufficiently, this could be the beginning of returning to the dynamics of the 1940s-1960s, where economic power was more concentrated among skilled blue collar workers than it is now.
As a programmer, but working in two non-SWE roles, I have turned job A 70% over to AI, and job B 90%.
Where systems and scaffolds can be put in place to manage various aspects of a job, would this not be considered, partially, an "AI job"?
If you work in government grants and R&D, what if agents can now triage 100-1000x the opportunity count that you could ever handle alone, and you had a pipeline system in place to manage said opportunities and relationships? And then you, as the human, become the mouthpiece and reviewer of hoards of filtered output? Is that Federal Grants & R&D position now not mostly an AI job?
I'd say a large percentage of digital-based jobs can be considered varying percentages of AI jobs.
I think they mean jobs directly related to AI, not merely exercising AI to increase productivity:
AI is also creating a new class of white-collar jobs. Engineers build the models, data annotators label their inputs and judge their answers, “forward-deployed” engineers adapt them for customers, and newly minted “heads of AI” decide what companies should do with the technology.
> On September 4th the Bureau of Labour Statistics reported that the American economy added 162,000 jobs in August, far above expectations.
Good news that ought to be taken with a pinch of salt given how the current administration responds to unfavorable BLS data -
> On Friday, August 1, [2025] President Trump fired Dr. Erika McEntarfer from her role as the Commissioner of the Bureau of Labor Statistics (BLS). In social media posts announcing and confirming her firing, he said that he believed the jobs report released by the agency earlier that day included numbers that were “rigged in order to make the Republicans, and ME, look bad.”
Even outside of the current administration, isn't BLS data notorious for being adjusted after the fact, often downwards? Basing reporting on fresh BLS data seems ill-advised.
The first series of "Blackadder" has a vignette of such reportage:
Messenger 3: My Lord, news…
King: What?
Messenger 3: Lord Wessex is dead.
King: This news is not so good.
Messenger 3: Pardon, My Lord?
King: I like it not. Bring me some other news.
Messenger 3: Pardon, My Lord?
King: I LIKE NOT THIS NEWS! BRING ME SOME OTHER NEWS!!!
Messenger 3: Yes, My Lord!
(Messenger 3 leaves; King tosses things around angrily;
Messenger 4 enters — actually just Messenger 3 pretending to be a new messenger delivering new news.)
Messenger 4: My Lord, news…
King: What?
Messenger 4: Lord Wessex is not dead.
King: Ah, good news! Let there be joy and celebration; let jubilation reign!
Wasn’t she only in that job for a year? Maybe she was doing a bad job.
The current head of the BLS seems well qualified. Here are some select quotes from a NYT article [1]:
“Erica Groshen, who was commissioner during the Obama administration, also praised the selection. “He’s a B.L.S.-er, he’s a data nerd,” she said.”
“The firing, and Mr. Antoni’s subsequent nomination, raised concerns that Mr. Trump would seek to interfere in the agency’s operations and perhaps try to skew its estimates to his political advantage. “
“There is no evidence that has happened so far. The agency has been run since August by William Wiatrowski, its longtime deputy commissioner, who also led the bureau on an interim basis under President Joseph R. Biden Jr. Economists continue to view the numbers the agency produces as reliable.”
Now these comments were written back in January of this year.
Can you cite any specific examples of wrongdoing? Or inaccurate numbers or figures outside of normal revisions?
When I see bad numbers from the BLS I say yes that’s probably true. When I see good numbers from the BLS I say yes that’s probably true.
AI boosters: "look, AI is creating jobs, all of these doomers scaring you with job loses, don't listen to them"
also AI boosters: "we are going to build a million robots, and the robots will build factories producing robots, there will be infinite abundance, nobody will need to work anymore"
I've spent 10 years implementing new technology into businesses from all over the world and the thing that has killed the most projects at the proof of concept phase has not been whether it works. It's whether the cost of going to production from PoC produces a significant ROI. AI is absolutely changing the economics there.
Humans were simply nowhere near answering all the useful questions they had which software could answer. The problem was that software was expensive.
Now, software is cheaper and so people who couldn't afford to answer questions they've long wondered about can afford to answer them.
>people who couldn't afford to answer questions they've long wondered about can afford to answer them.
If the software isn't downright free – today, you can slap a $349 RTX 5060 [†] into any POS surplus computer and have an offline assistant, running Llama or Ornith, via Ollama in linux (i.e. the LLM and OS are FREE open-source software) [∑]
I have a working demo of this that has been shown/leant to several friends, and they're all surprised that it "all works so well, without being online, for only a few hundred dollars."
When I've demonstrated Mistral-small on my 5070Ti... that has been a real jaw dropper. I haven't shown anybody qwen3.8:27b, yet... but dammmmm, what a month of learning it's been.
----
A friend that was going through wifecancer confided in me that "you can ask it anything, without feeling embarassed" – and that has stuck with me (that so many smart people are afraid to ask simple questions [*], out of perceptional worries).
----
[†] (8GB DDR7) brand new from Wal-Mart
[∑] My first linux/LLM machine was built with setup help from Perplexity.ai (with a dozen "assists" - I am bluecollar, non-coder). This used an obsolete i5 (and $200 used VEGA64 GPU) to create a decent Llama3.1 LLM machine (~100wpm typeback, perhaps 70 tokens/s).
[*] even to their own detriment, of shame, when simple solutions often do exist
No longer convinced that’s true. Some of the indebted providers might go under but there is nothing preventing someone from just setting up a new provider and serving tokens debt free. GLM or whatever.
That provides continuous downward pressure on token prices even if it isn’t Astra level
>The Economist, Silicon Valley's primary submarine, dispels the notion that AI causes unemployment because SV has realized that the peasants get unruly.
Right, but OP's implication is that they're trying to placate the masses (that somehow read the economist?), even though a few months before they were putting out alarmist covers. You can't have it both ways. If you're arguing that economist being pro-job loss is part of a globalist conspiracy and so is the economist being anti-job loss, then you just created an unfalsifiable statement, a "heads I win, tails you lose" argument.
If most of the jobs its creating are related to construction of infrastructure then that's not really positive news as these jobs are temporary, once demand settles then why kind of jobs are going to be created?
It might be benefiting other areas, but I think as the technology improves a lot of those are going to start looking like what's happening in software development (which is arguably what the technology is best at right now).
So yeah, idk.
Isn't this true for "all" construction? Nobody says,
"The housing construction jobs are temporary, we shouldn't count them."
There will always be CapEx to spend.
AI construction jobs are temporary up to Kardashev 3 or so.
But it will be automated long before then
Humans become irrelevant well before then.
Most of these jobs are the same jobs that arose thanks to the CHIPS and IRA. Much of the AI boom and trade is building on top of the capex that arose from the semiconductor/hardware portfolio during that era.
Many of the current DCs being built out are also being powered or tied with renewable energy projects that were funded by the IRA, as many DC builders with deep pockets do know the political dimension. If this is what keeps the CHIPS, IRA, and the IIJA alive I'm happy.
Every industry and career type goes through ebbs and flows. The 2010s was a white collar boom, and the 2020s is now a white collar bust. Meanwhile the 2010s was a skilled trades bust and the 2020s is now a skilled trades boom.
There is almost always a next big thing. What happens when it ends is people move to the next thing. Practically everything needs some kind of construction, management, software, hardware, etc.
I'd be rich if I knew what the next big thing was but the economy has been running on the assumption that there will be a next big thing for many, many decades. Each cycle has the same rhymes of "what happens when it ends" questions but there has always something.
Everything is temporary, especially jobs.
insightful
The construction jobs are only temporary if the compute infrastructure build-out decelerates. That seems pretty unlikely in the mid-term! It would mean that, like, there's a fixed appetite for data centers, and once we satisfy that appetite, we stop building them.
For better or worse, it looks more like that we're gonna tile the whole damn planet in data centers, at a faster and faster clip.
> The Economist estimates that AI has so far created around 1m new jobs in America. That easily exceeds the roughly 200,000 lay-offs attributed to AI since mid-2023, and appears more than enough to offset weaker hiring in many back-office roles. America’s AI infrastructure splurge has created many of them. (...) That building spree requires armies of workers: electricians to wire them, HVAC specialists to stop racks from overheating, grid engineers to hook them up to the power supply and technicians to install and maintain the machines.
I'm not sure whether the salaries of the new jobs are on par with those of the lost jobs.
"easily exceeds the roughly 200,000 lay-offs attributed to AI "
Except that is hogwash, "attributed to AI" is basically the CEO screwing up something in the business and AI-washing their mistake because it's convenient.
“One million high-paying upper-middle class family supporting jobs were destroyed, but on the bright side, one million minimum-wage Walmart greeter jobs were created! See? We’re breaking even!”
I'm a consultant and I've already worked for multiple AI companies that shut down over the last two years. I think the main problem is that they all are relying on the big token providers and trying to capture value with various services.
At some point the token costs will increase so much, it will put all of these AI companies out of business.
Don't get me wrong. AI is definitely useful. The high costs are currently being subsidized by VC and other investors and unless there is a major breakthrough, it's just not going to work in the long-term.
Why assume token costs will increase as opposed to become commoditized?
That would be even worse for them, since then current customers of these AI-middleman corpos would just start deploying their own self-hosted and private LLM services. In before the complexity argument, there may well be some completely different middlemen corpos, who will assist in such deployments and initial ramp-ups.
Self-hosting takes either cloud- or on-prem-engineering chops, which are in short supply. In my view, that becomes the primary driver for lowering token costs. Secondary are the alternative model sources like Z.ai and Moonshot, which between open weights and lower prices help to drive commoditization. But there is a political risk with these, for example, Z.al is on the U.S. Department of Commerce Entity List, which blocks American companies from selling advanced technology and goods to the firm.
you seem to be discounting or unaware of the possibility of a) automating a significant chunk of new buildouts, and b) domestic companies seeking a slice of the “sell open model hosting for less than competitors” pie.
I truly believe the cost per token for most people will eventually go approximately to zero even in the absence of subsidy unless there is a dramatic state intervention to curtail free computing and hardware R&D and manufacturing.
There seems to be a weird self-fulfilling narrative here:
1) "AI companies will go bust because tokens will cost too much" >> 2) "Don't let them build data centers that will sit empty" >> 3) Demand outstrips supply by a lot >> 4) Token costs too much.
This is no different from the NIMBY's that block all the housing then sit in a huff saying "see! everyone's leaving. good thing we didn't build anything!" when the rents go up.
Are you seeing companies that are in over their heads because they don't have enough domain knowledge?
I think that's always been an issue in tech, but it feels like AI exacerbates the issue. I see people starting companies and services where their primary domain knowledge seems to be whatever their AI tells them. It's sometimes enough to get off the ground, but I wonder how long it takes for customers/clients who actually need the domain knowledge to bail.
Not to mention if you make a successful value add the token provider will add it to their own harness and they're not paying the retail price they charge you for the tokens they consume.
yea this is something I've been wondering about. I'm not too keen on the finance aspect, but I understand that the big players aren't turning a profit. OpenAI is still losing money. I've seen some discussion related to increased token costs. If that continues, isn't dependence on their services a risk?
I believe this to be completely mistaken, because the bang-for-buck is getting better. Luna on max thinking is very capable and builds you a feature for 20 cents.
Its just that in a gold rush, there are few winners and many losers. There used to be hundreds of car companies in the beginning, only a dozen or so survived long term.
I can’t read the article but in my group, which is not terribly AI exposed due to its hands-on nature, we are in fact hiring extra people into next year to handle additional AI initiatives that I am confident will succeed. In subsequent years, the plan as I have heard it is to let headcount go down by attrition.
I would not take extra hiring now as evidence that AI is preserving job numbers.
The article mostly cites the huge growth in blue-collar jobs caused by the data center buildout. It’s very handy-wavy about white collar jobs, “yes lots of jobs have been lost, but also the tech sector always has a lot of year-to-year churn, maybe this is just churn”.
Not a super insightful article. The AI jobs apocalypse may or may not be real, but this article doesn’t provide any compelling evidence for its thesis.
It's handy-wavy because nobody knows how it will turn out and which new jobs will be created. In the same way as every predictions about AI bust, job lost, moat (or lack of it) is. If you feel confident about your predictions, don't.
What type of activities your group performs?
https://archive.md/5hi5i
I was laid off as a senior product manager in December of 2025. I’ve been looking for a new job in clean energy (which is supposedly “having a moment” due to data centers) since then. There is no “jobs boom”. There are certainly job openings — black holes into which you can lodge your resume. Occasionally, multiple rounds of interviews that go nowhere. I’ve been paying my bills as an art fabricator and live event electrician, the kinds of blue collar jobs that are supposed to make up for the destruction of “knowledge work”. The work is inconsistent, and the pay is less than half of what I made before. There is no “jobs boom”, of any kind.
While I'm still catastrophically worried about what AI means for my career, I've noticed that my current employer - very AI forward, and growing the team - is still facing an ever expanding backlog.
High productivity is generally good for the employee, unless you're productive enough you run out of work to do. So how much code is needed?
I was also sure to be homeless by now. But despite aggressively trying to automate myself away I'm somehow more busy than ever.
Relatable. Every time I finish working on something, I spot so many more new things that can be built.
Yes I’ve seen very little change over the past 3 years in my role (platform engineering) except mostly JIRA tickets are more unreadable because people just have Claude vomit a novel into it.
I mean I use it every day of course, but the velocity of work doesn’t really seem to be budging lol. And frankly a lot of time wasted on AI made gadgets, and meetings about those gadgets (look at this dashboard Claude made! etc)
> AI startups are hiring like there is no tomorrow.
This is not reassuring
I hope this results in a rebalancing of the social and economic power of high-IQ versus average-IQ workers. We will need construction workers and tradespeople to build and maintain these AI data centers. Probably even with robots. But we won’t need as many engineers, lawyers, and other people whose job it is to consume and generate bits. If we tax the proceeds of AI generated productivity sufficiently, this could be the beginning of returning to the dynamics of the 1940s-1960s, where economic power was more concentrated among skilled blue collar workers than it is now.
> If we tax the proceeds of AI generated productivity sufficiently
That's not going to happen.
What about like a PNG tax for transparent pixels?
Transparent pixels harm the environment because they use energy and don't even do anything
Does anyone here question the integrity of the US government’s jobs report two months away from a mid-term election?
Not really. We'd see a lot of resignations if the numbers were being fudged. Statisticians, as a rule, take a dim view of falsifying data.
AI boom for jobs has always been here. Companies want to be on top of this stuff more then ever. Especially if they can replace more workers with it.
Remind me what percentage of the workforce works “AI jobs”?
Well one way to look at it is:
As a programmer, but working in two non-SWE roles, I have turned job A 70% over to AI, and job B 90%.
Where systems and scaffolds can be put in place to manage various aspects of a job, would this not be considered, partially, an "AI job"?
If you work in government grants and R&D, what if agents can now triage 100-1000x the opportunity count that you could ever handle alone, and you had a pipeline system in place to manage said opportunities and relationships? And then you, as the human, become the mouthpiece and reviewer of hoards of filtered output? Is that Federal Grants & R&D position now not mostly an AI job?
I'd say a large percentage of digital-based jobs can be considered varying percentages of AI jobs.
I think they mean jobs directly related to AI, not merely exercising AI to increase productivity:
AI is also creating a new class of white-collar jobs. Engineers build the models, data annotators label their inputs and judge their answers, “forward-deployed” engineers adapt them for customers, and newly minted “heads of AI” decide what companies should do with the technology.
Paywalled
> On September 4th the Bureau of Labour Statistics reported that the American economy added 162,000 jobs in August, far above expectations.
Good news that ought to be taken with a pinch of salt given how the current administration responds to unfavorable BLS data -
> On Friday, August 1, [2025] President Trump fired Dr. Erika McEntarfer from her role as the Commissioner of the Bureau of Labor Statistics (BLS). In social media posts announcing and confirming her firing, he said that he believed the jobs report released by the agency earlier that day included numbers that were “rigged in order to make the Republicans, and ME, look bad.”
https://www.epi.org/policywatch/firing-bls-commissioner-erik...
Even outside of the current administration, isn't BLS data notorious for being adjusted after the fact, often downwards? Basing reporting on fresh BLS data seems ill-advised.
Yeah, it's survey based and some employers don't hit the first few deadlines.
Last month got revised to being positive, at the same time that this month was being released.
The first series of "Blackadder" has a vignette of such reportage:
Messenger 3: My Lord, news…
King: What?
Messenger 3: Lord Wessex is dead.
King: This news is not so good.
Messenger 3: Pardon, My Lord?
King: I like it not. Bring me some other news.
Messenger 3: Pardon, My Lord?
King: I LIKE NOT THIS NEWS! BRING ME SOME OTHER NEWS!!!
Messenger 3: Yes, My Lord!
(Messenger 3 leaves; King tosses things around angrily; Messenger 4 enters — actually just Messenger 3 pretending to be a new messenger delivering new news.)
Messenger 4: My Lord, news…
King: What?
Messenger 4: Lord Wessex is not dead.
King: Ah, good news! Let there be joy and celebration; let jubilation reign!
When news doesn't confirm my belief, doubt it and make sure people know.
Trust me I do the same.
Wasn’t she only in that job for a year? Maybe she was doing a bad job.
The current head of the BLS seems well qualified. Here are some select quotes from a NYT article [1]:
Now these comments were written back in January of this year.Can you cite any specific examples of wrongdoing? Or inaccurate numbers or figures outside of normal revisions?
When I see bad numbers from the BLS I say yes that’s probably true. When I see good numbers from the BLS I say yes that’s probably true.
[1] https://www.nytimes.com/2026/01/30/business/trump-bureau-of-...
AI boosters: "look, AI is creating jobs, all of these doomers scaring you with job loses, don't listen to them"
also AI boosters: "we are going to build a million robots, and the robots will build factories producing robots, there will be infinite abundance, nobody will need to work anymore"
> there will be infinite abundance
Maybe.
> nobody will need to work anymore
If we define "nobody" as very wealthy people who partake in that abundance while everyone else ... goes away.
First of all, cite them. Second of all, on which time scale, are they both talking about the near, mid or long terms?
I've spent 10 years implementing new technology into businesses from all over the world and the thing that has killed the most projects at the proof of concept phase has not been whether it works. It's whether the cost of going to production from PoC produces a significant ROI. AI is absolutely changing the economics there.
Humans were simply nowhere near answering all the useful questions they had which software could answer. The problem was that software was expensive.
Now, software is cheaper and so people who couldn't afford to answer questions they've long wondered about can afford to answer them.
>people who couldn't afford to answer questions they've long wondered about can afford to answer them.
If the software isn't downright free – today, you can slap a $349 RTX 5060 [†] into any POS surplus computer and have an offline assistant, running Llama or Ornith, via Ollama in linux (i.e. the LLM and OS are FREE open-source software) [∑]
I have a working demo of this that has been shown/leant to several friends, and they're all surprised that it "all works so well, without being online, for only a few hundred dollars."
When I've demonstrated Mistral-small on my 5070Ti... that has been a real jaw dropper. I haven't shown anybody qwen3.8:27b, yet... but dammmmm, what a month of learning it's been.
----
A friend that was going through wifecancer confided in me that "you can ask it anything, without feeling embarassed" – and that has stuck with me (that so many smart people are afraid to ask simple questions [*], out of perceptional worries).
----
[†] (8GB DDR7) brand new from Wal-Mart
[∑] My first linux/LLM machine was built with setup help from Perplexity.ai (with a dozen "assists" - I am bluecollar, non-coder). This used an obsolete i5 (and $200 used VEGA64 GPU) to create a decent Llama3.1 LLM machine (~100wpm typeback, perhaps 70 tokens/s).
[*] even to their own detriment, of shame, when simple solutions often do exist
> Now, software is cheaper and so people who couldn't afford to answer questions they've long wondered about can afford to answer them.
Temporarily. Token price will rise sharply when the bills finally come due.
No longer convinced that’s true. Some of the indebted providers might go under but there is nothing preventing someone from just setting up a new provider and serving tokens debt free. GLM or whatever.
That provides continuous downward pressure on token prices even if it isn’t Astra level
So the lore of capitalism was on point this time -- whenever one market closes, resources (you) are freed to form a new market.
Interesting how we got frank propaganda on the front page now. Pretty sad. There are no jobs. Not real jobs.
Blatant propaganda is not an effective remedy to the severe public anti-AI sentiment, sorry.
[flagged]
[flagged]
>The Economist, Silicon Valley's primary submarine, dispels the notion that AI causes unemployment because SV has realized that the peasants get unruly.
???
From a few months ago: https://www.economist.com/content-assets/images/20260516_DE_...
Every single aspect of that cover is manipulative marketing.
Right, but OP's implication is that they're trying to placate the masses (that somehow read the economist?), even though a few months before they were putting out alarmist covers. You can't have it both ways. If you're arguing that economist being pro-job loss is part of a globalist conspiracy and so is the economist being anti-job loss, then you just created an unfalsifiable statement, a "heads I win, tails you lose" argument.
I suspect "submarine" was meant in this sense: https://www.paulgraham.com/submarine.html
Note well: This does not mean that I agree with any part of what he said. Just explaining the term.
That was when Silicon Valley still favored the job loss narrative to drive up CEO interest for AI.
Now protests are getting louder and the midterms are close.