23 ms·

Will AI be the basis of many future industrial fortunes, or a net loser?

239 points by saucymew 1y ago

carom 1y ago
This article seems to have scoped AI as LLMs and totally missed the revolutionary application that is self driving cars. There will be a lot more applications outside of chat assistants.
- mafro 1y ago
  The same idea applies to self-driving cars though, no? That is an industry where the "AI revolution" will enrich only the existing incumbents, and there is a huge bar to entry. Self-driving cars are not going to create generational wealth through invention like microprocessors did.
HPsquared 1y ago
The title is a false dichotomy. It could be a net gain but spread across the whole society if the value added is not concentrated. This is what happens when users gain value which they themselves capture, and the AI companies only get the nominal $20/month or whatever. In those cases it's a net gain for the economy as a whole if valuable work was done at low cost. The inverse of the broken window fallacy.
- deleted 1y ago
  [deleted]
- mattmanser 1y ago
  Like all tech we've had recently, that won't last, it's always bait and switch. It will not remain cheap as soon as the competition is dead, which is simply a case of who's got the biggest VC supplied war chest.
  - kasey_junk 1y ago
    Like with databases? There are none of those freely available now that Oracle won right?
    - mattmanser 1y ago
      Snark only works when you've got a valid point. One person can write sqllite. You can iterate up to bigger opensource DBs like postgre. One person cannot create a modern LLM model unless they have 10s of millions of dollars to burn on compute. LLMs are a fundamental shift from what was achievable in software and OSS, and we're basically living off scraps from the big players releasing their old models. They're already trying to create regulatory moats too.
      - kasey_junk 1y ago
        Oracle is far and away better than any of the open source databases. For a long time it wasn’t particularly close. Db didn’t get parity with Oracle, they got good enough that you have to justify spending for Oracle and incurring the down sides of its company’s model. Similarly, no db that competes with Oracle was written by one person, they were and are funded mostly by private companies and foundations. There is a future where open weight models are good enough and the foundation labs are the truly luxury tier for a small subset of the user base. That’s before talking about something like productivity software which Google _gives away_ while it’s a main business of Microsoft. Blindly saying that there is only a future where the foundation llms capture all of the business is hyperbolic and ignores history. The llms look more db shaped to me than they look like car shares. Those truly are network effect dominated.
        mattmanser 1y ago
        You mean the history where MS captured the OS, Applle/Google the phone, Google capture the entire search market for 20 years, Facebook the social web, Amazon shopping, NVidia/AMD, Netflix, Spotify, I could go on and on and on. Most things in tech settle into monopolies or duopolies. LLMs are more akin to the search market than the database market. They need to be updated constantly. Selectively picking out the one technology that's basically no-one's primary business is an odd way to try and convince me. It must be over 20 years now since any large company consider a DB to be a significant product. Open source winners like Linux and MySql/Postgre are the oddity, not the norm.
Mistletoe 1y ago
AI made me this summary (I’ve grown quite weary of reading AI think pieces) and it seems like a really good comparison. >The article "AI Will Not Make You Rich" argues that generative AI is unlikely to create widespread wealth for investors and entrepreneurs. The author, Jerry Neumann, compares AI to past technological revolutions, suggesting it's more like shipping containerization than the microprocessor. He posits that while containerization was a transformative technology, its value was spread so thinly that few profited, with the primary beneficiaries being customers. >The article highlights that AI is already a well-known and scrutinized technology, unlike the early days of the personal computer, which began as an obscure hobbyist project. The author suggests that the real opportunities for profit will come from "fishing downstream" by investing in sectors that use AI to increase productivity, such as professional services, healthcare, and education, rather than investing in the AI infrastructure and model builders themselves. I used to be the biggest AI hater around, but I’m finding it actually useful these days and another tool in the toolbox.
- grugagag 1y ago
  Did you read the article or you just relied on the AI generated summary? Lots of people argue that this kind of shortcut will make us dumber and the argument does make sense.
GMoromisato 1y ago
I think AI will be more like the smartphone revolution that Apple kicked off in 2005. Today there are two companies that provide the smartphone platform (Apple/Google), but thousands of large and small companies that build on top of it, including Uber, Snapchat, etc. In that scenario, everyone makes money: OpenAI, Google (maybe Anthropic, maybe Meta) make money on the platform, but there are thousands of companies that sell solutions on top. Maybe, however, LLMs get commoditized and open-source models replace OpenAI, etc. In that case, maybe only NVIDIA makes money, but there will still be thousands of companies (and founders/investors) making lots of money on AI everything.
- ToucanLoucan 1y ago
  I think there’s a gaping hole in your analogy: who in their right mind is spending $1,200 biennially to access LLMs at base, and subsequently spending several monthly subscriptions in a small amount to access particular LLM-powered “apps?” Every use case I have for LLMs is satisfied with copilot, but even then if it costs like $5 a month to access someday, I’d just as soon not have it. Let alone the subsequent spending.
cramcgrab 1y ago
Obviously the maker. Just look at how and who.
HarHarVeryFunny 1y ago
I would imagine AI will be similar to factory automation. There will be millions of factories all benefiting from it, and a relatively small number of companies providing the automation components (conveyor belt systems, vision/handling systems, industrial robots, etc). The technology providers are not going to become fabulously rich though as long as there is competition. Early adopters will have to pay up, but it seems LLMs are shaping up to be a commodity where inference cost will be the most important differentiator, and future generations of AI are likely to be the same. Right now the big AI companies pumping billions into it to advance the bleeding edge necessarily have the most advanced products, but the open source and free-weight competition are continually nipping at their heels and it seems the current area where most progress is happening is agents and reasoning/research systems, not the LLMs themself, where it's more about engineering rather than who has the largest training cluster. We're still in the first innings of AI though - the LLM era, which I don't think is going to last for that long. New architectures and incremental learning algorithms for AGI will come next. It may take a few generations of advance to get to AGI, and the next generation (e.g. what DeepMind are planning in 5-10 year time frame) may still include a pre-trained LLM as a component, but it seems that it'll be whatever is built around the LLM, to take us to that next level of capability, that will become the focus.
bgwalter 1y ago
It is interesting that the early shipping containerization boom resulted in a bubble in 1975 and had a new low around 1990. 1990 is when the real outsourcing mania started, which led to the destruction of most Western manufacturing. Apart from cheap Chinese trinkets the quality of life and real incomes have gotten worse in the West while the rich became richer. So this is an excellent analogy for "AI": Finding a new and malicious application can revive the mania after an initial bubble pop while making societies worse. If we allow it, which does not have to be the case. [As usual, under the assumption that "AI" works, of which there is little sign apart from summarizing scraped web pages.]
unleaded 1y ago
Something that's confused/annoyed me about the AI boom is that it's like we've learned to run before we learned to walk. For example, there are countless websites where you can generate a sophisticated, photorealistic image of anything you like, but there is no tool I know of that you can ask "give me a 16x16 PNG icon of an apple" and get exactly that. I know why—Neural networks excel at fixed size, organic data, but I don't think that makes it any less ridiculous. It also means that AI website generators are forced to generate assets with code when ordinary people would just use images/sound files (yes, I have really seen websites using webaudio synths for sound effects). Hopefully the boom will slow down and we'll all slowly move away from Holy Shit Hype things and implement more boring, practical things. (although I feel like the world has shunned boring practical things for quite a while before)
- qwertygnu 1y ago
  As you seem to understand, creating something that generally fits a description is the walking for AI. Following exact directions is the running. It may just feel reversed because of the path of other technology.
- SquibblesRedux 1y ago
  I just asked ChatGPT-5 to "give me a 16x16 PNG icon of an apple" and it did exactly that. It looks good, too. Not that I don't recognize the inherent limits of LLMs, but there are as many edge cases covered as are found in the training sets. (More or less.)
  - unleaded 1y ago
    well i just asked it the same thing and it gave me a 1MB 1024x1024 png with fringed edges & sensor noise that measures out to a 17x21 pixel image. https://files.catbox.moe/1q4jtp.png https://files.catbox.moe/1q4jtp.png In the time it would take to keep retrying until it makes one that fits, then reshaping it to fit into 16x16 nicely I could have just drawn one myself.
CM30 1y ago
Practically speaking, it's going to be both more impactful than we think and less impactful than we think at the same time. On the one hand, there are a lot of fields that this form of AI can and will either replace or significantly reduce the number of jobs in. Entry level web development and software engineering is at serious risk, as is copywriting, design and art for corporate clients, research assistant roles and a lot of grunt work in various creative fields. If the output of your work is heavily represented in these models, or the quality of the output matters less than having something, ANYTHING to fill a gap on a page/in an app, then you're probably in trouble. If your work involves collating a bunch of existing resources, then you're probably in trouble. At the same time, it's not going to be anywhere near as powerful as certain companies think. AI can help software engineers in generating boilerplate code or setup things that others have done millions of times before, but the quality of its output for new tasks is questionable at best, especially when the language or framework isn't heavily represented in the model. And any attempts to replace things like lawyers, doctors or other such professions with AI alone are probably doomed to fail, at least for the moment. If getting things wrong is a dealbreaker that will result in severe legal consequences, AI will never be able to entirely replace humans in that field. Basically, AI is great for grunt work, and fields where the actual result doesn't need to be perfect (or even good). It's not a good option for anything with actual consequences for screwing up, or where the knowledge needed is specialist enough that the model won't contain it.
amradio1989 1y ago
AGI is where the real money is. Gen AI is okay but mostly benefits the consumer. Gen AI is not nearly powerful enough to justify current investments. A lot of money is going to go up in smoke.
jschveibinz 1y ago
We have a limited time on earth. AI may present an opportunity for us to improve the quality of life or the amount of time spent doing things we really want to do while we are here. Those who spend time figuring out how to use AI for these purposes will be heroes, and only then will AI have been a positive development for humanity. Get to work, heroes!
- deleted 1y ago
  [deleted]
- akomtu 1y ago
  Creating a machine lifeform that competes with humans for resources is hardly a heroic act.
gusfoo 1y ago
I genuinely think that large language models are a useful technology in data processing. Being "language models" I find it easy to use LLMs to extract subject, object, quantity, time, verb, amount, user's language code and so on from the input text, and to a fairly trustworthy level. After that, standard Information Retrieval techniques take over. What LLMs are absolutely not useful for, in my opinion, is answering questions or writing code, or summarising things, or being factual in any sense at all.
estimator7292 1y ago
The problem with viewing AI through the lens of capitalism is the fact that you can't make it artificially scarce. AI is largely capable of running on-device. In a few years, it's likely that most tasks that most people want AI for will be possible from a tiny model living in their phone. Open source models are plentiful, functional, and only becoming moreso. But you can't monetize that. We're currently dumping billions of dollars into datacenter moats that are just gonna evaporate inside the decade. For the average user doing their daily "who was that actor in that movie" query, no, you absolutely cannot monetize AI because all of your local devices can run the model for free with enough quality that no one will know or care that there's a difference. For enterprise scale building a trillion dollar datacenter and 15 nuclear reactors to replace a hundred developers... also no. LLMs are not capable of that, and likely won't be in the foreseeable future. It's also extremely unclear that one could ever get an ROI on in-house AI like this. It might be more plausible if it were a commodity technology you can just buy, but then you can't make a moat. The only hypothetical fortune to be found is by whoever is selling AI to people who think they need to buy AI. Just like bitcoin or NFTs. The good news is that this has two possible outcomes: capitalist AI vendors will want to remove AI from individual access so they can sell it to you: everyone gets less AI. Capitalists realize they can never monetize AI when it's free and open source, and give up: everyone gets less AI. Win-win-win, in my book.
SilverElfin 1y ago
Maybe the basis of concentration of power and wealth more than anything else
tim333 1y ago
>The disruption is real. It's also predictable. I'm not sure it is very predictable. We have people saying AI is LLMs and they won't be much use and there'll be another AI winter (Ed Zitron), and people and people saying we'll have AGI and superintelligence shortly (Musk/Altman), and if we do get superintelligence it's kind of hard to know how that will play out. And then there's John von Neumann (1958): >[the] accelerating progress of technology and changes in human life, which gives the appearance of approaching some essential singularity in the history of the race beyond which human affairs, as we know them, could not continue. which is what kicked of the misuse of a perfectly good mathematical term for all that stuff. Compared to the other five revolutions listed - industrial, rail, electricity, cars and IT, I think AI is a fair bit less predictable.
NumberCruncher 1y ago
Making an industrial fortune is relative. It might just mean that jumping on the AI hype helps you preserve your fortune or position in the industry, while everyone else who misses the hype goes out of business. I remember back in 2004, my first project was testing a teleconferencing system. We set up a huge screen with cameras at one of our subsidiaries and another at the HQ, and I had a phone on my desk with a built-in camera and screen. Did the company roll out the system? No, it didn’t. It was just too expensive. Did they make a fortune from that experience? No, they didn’t. But I’m pretty sure all companies in the knowledge industry that didn’t enable video calls and screen sharing for their employees went out of business years ago...
ath3nd 1y ago
With AI everyone is a net loser. People using it get dumber. What is being produced is slop and discardable poc-like trash The environmental costs of building and training LLMs are huge. That compute and water could have been useful for something. Even the companies building and peddling AI are losers. They are not profitable, need constant billions of dollars of financial help to even syay afloat and pay their compute depth. The worst part is that even bigger losers will be the general population. Not only are our kids gonna be dumber than us thanks to never having to think for themselved, but our pensions are tied to the stock market that will inevitably collapse when the realization that the top 30% of companies in terms of value are just dominoes waiting to collapse. But the biggest loser of all is Elon Musk. Just because of who he is.
noduerme 1y ago
This is a great perspective. If anything, I'd think that crypto in 2010 had all the hallmarks of a new wave as described. The concept was open to anyone who wanted to tinker with it. It had to be sold to skeptical consumers by wildcat startups. It certainly had the potential to upend the financial industry, but no incumbent would touch it. Yet it did end up more or less being sucked into the gravity well of the incumbents, although in the case of crypto we very much need to consider governments which control the money supply to be the heavyweights, even more so than banks and lenders. Maybe I'm pessimistic, but I'm not sure any new innovation now can escape the gravitational nexus of the duopoly of government and incumbent tech, in a way that would lead to the kind of wild growth and experimentation we had with microprocessors in the 70s. We had some guy named Satoshi write a paper that basically handed the keys to anyone who wanted to experiment - and 17 years later, after a significant bubble, that wave has done very little to change the status quo. I suppose if someone released a DIY genome editor or protein folding was solved or, like, a working Mr. Fusion device showed up on Kickstarter, or a "feed"/"seed" a la the Diamond Age made it possible to turn dirt into anything you wanted, or a FTL drive came out of someone's garage or something... yeah. That would seriously upset the incumbents. But even with sci-fi stuff like that, what's the moat once you make your findings public anymore? This article suggests that the only serious moat has ever been that large companies are slowed down by inertia and take some time to spin up once their internal cultures go from deriding something to deciding it's essential. How do we know if we have stalled to the point that no one will come along and be the next Amazon or Google, until 50 years from now we see that no one did?
wewewedxfgdf 1y ago
You can't make such generalized statements about anything in computing/business. The AI revolution has only just got started. We've barely worked out basic uses for it. No-one has yet worked out revolutionary new things that are made possible only by AI - mostly we are just shoveling in our existing world view.
- kg 1y ago
  The way I look at this question is: Is there somehow a glaring vulnerability/missed opportunity in modern capitalism that billions of people somehow haven't discovered yet? And if so, is AI going to discover it? And if so, is a random startup founder or 'little guy' going to be the one to discover and exploit it somehow? If so, why wouldn't OpenAI or Anthropic etc get there first given their resources and early access to leading technology? IIRC Sam Altman has explicitly said that their plan is to develop AGI and then ask it how to get rich. I can't really buy into the idea that his team is going to fail at this but a bunch of random smaller companies will manage to succeed somehow. And if modern AI turns into a cash cow for you, unless you're self-hosting your own models, the cloud provider running your AI can hike prices or cut off your access and knock your business over at the drop of a hat. If you're successful enough, it'll be a no-brainer to do it and then offer their own competitor.
  - wewewedxfgdf 1y ago
    >> Is there somehow a glaring vulnerability/missed opportunity in modern capitalism that billions of people somehow haven't discovered yet? Absolutely with 150% certainty yes, and probably many. The www started April 30, 1993, facebook started February 4, 2004 - more than ten years until someone really worked out how to use the web as a social connection machine - an idea now so obvious in hindsight that everyone probably assumes we always knew it. That idea was simply left lying around for anyone to pick up and implement rally fropm day one of the WWW. Innovation isn't obvious until it arrives. So yes absolutely the are many glaring opportunities in modern capitalism upon which great fortunes are yet to be made, and in many cases by little people, not big companies. >> if so, is a random startup founder or 'little guy' going to be the one to discover and exploit it somehow? If so, why wouldn't OpenAI or Anthropic etc get there first given their resources and early access to leading technology? I don't agree with your suggestion that the existing big guys always make the innovations and collect the treasure. Why did Zuckerberg make facebook, not Microsoft or Google? Why did Gates make Microsoft, not IBM? Why did Steve and Steve make Apple, not Hewlett Packard? Why did Brin and Page make Google - the worlds biggest advertising machine, not Murdoch?
ThrowawayTestr 1y ago
And Dropbox will never take off
- unleaded 1y ago
  people also said the juicero and the smart condom would never take off. this isnt a very useful gotcha
  - fred_is_fred 1y ago
    The dig on Dropbox is that it was easy to build, not that it wasn’t useful. Juicero was neither easy to build (relatively) nor useful.
- giveita 1y ago
  Non sequitur: Dropbox is a single company in the industry benefiting from the first wave. His argument would not exclude Dropbox anyway.
nextworddev 1y ago
AI by nature is kind of like a black hole of value. Necessarily, a very small fraction will capture the vast majority of value. Luckily, you can just invest wisely to hedge some of the risk of missing out.
xnx 1y ago
AI could've made someone unimaginably rich if they were the only one that had it. We're very lucky Google didn't keep "Attention is All You Need" to themselves.
- back2dafucha 1y ago
  I doubt we'll feel that way in 5 years.
  - echelon 1y ago
    Because now they're keeping everything to themselves?
    - visarga 1y ago
      Attention (technology) is all they need (to keep secret).
Waterluvian 1y ago
I think the interesting idea with “AI” is that it seems to significantly reduce barriers to entry in many domains. I haven’t seen a company convincingly demonstrate that this affects them at all. Lots of fluff but nothing compelling. But I have seen many examples by individuals, including myself. For years I’ve loved poking at video game dev for fun. The main problem has always been art assets. I’m terrible at art and I have a budget of about $0. So I get asset packs off Itch.io and they generally drive the direction of my games because I get what I get (and I don’t get upset). But that’s changed dramatically this year. I’ll spend an hour working through graphics design and generation and then I’ll have what I need. I tweak as I go. So now I can have assets for whatever game I’m thinking of. Mind you this is barrier to entry. These are shovelware quality assets and I’m not running a business. But now I’m some guy on the internet who can fulfil a hobby of his and develop a skill. Who knows, maybe one day I’ll hit a goldmine idea and commit some real money to it and get a real artist to help! It reminds me of what GarageBand or iMovie and YouTube and such did for making music and videos so accessible to people who didn’t go to school for any of that, let alone owned complex equipment or expensive licenses to Adobe Thisandthat.
- ta12653421 1y ago
  Regarding assets, check out Nano Banana: https://github.com/PicoTrex/Awesome-Nano-Banana-images/blob/main/README_en.md https://github.com/PicoTrex/Awesome-Nano-Banana-images/blob/... For you the example of "extract object and create iso model" should be relevant :)
- SideburnsOfDoom 1y ago
  > "AI" is that it seems to significantly reduce barriers to entry in many domains. If you ask an LLM to generate some imagery, in what way have you entered visual arts? If you ask an LLM to generate some music, in what way have you entered being a musician? If you ask an LLM to generate some text, in what way have you entered writing?
- Havoc 1y ago
  Yeah that seems accurate. I mainly use AI for selfhosting/homelab stuff and the leverage there is absolutely wild - basically knows "everything".
pevansgreenwood 1y ago
[dead]
firesteelrain 1y ago
There are plenty of companies making money. We are using several “AI powered” job aids that are leading to productivity gains and eliminating technical debt. We are licensing the product via subscription. Money is being made by the companies selling the products. Example https://specinnovations.com/blog/ai-tools-to-support-requirements-engineering-and-test-case-developments https://specinnovations.com/blog/ai-tools-to-support-require...
palata 1y ago
Counterpoint: those engineers who get paid millions to work on AI.
- oblio 1y ago
  All 5000 of them?
  - palata 1y ago
    My point is that AI makes some people rich. Nothing makes everyone rich, otherwise nobody would be rich. Not that it is a good thing, but that's how it is.
dweinus 1y ago
I don't think most commenters have read the article. I can understand, it's rambly and a lot of it feels like they created a thesis first and then ham-fisted facts in later. But it's still worth the read for the last section which is a more nuanced take than the click-bait title suggests.
- deleted 1y ago
  [deleted]
mhb 1y ago
Seems like the thing to do to get rich would be to participate in services that it will take a while for AI to be able to do: nursing, plumbing, electrician, carpentry (i.e., Baumol). Also energy infrastructure.
kristianc 1y ago
> Yet some technological innovations, though societally transformative, generate little in the way of new wealth; instead, they reinforce the status quo. Fifteen years before the microprocessor, another revolutionary idea, shipping containerization, arrived at a less propitious time, when technological advancement was a Red Queen’s race, and inventors and investors were left no better off for non-stop running. This collapses an important distinction. The containerization pioneers weren’t made rich - that’s correct, Malcolm McLean, the shipping magnate who pioneered containerization didn’t die a billionaire. It did however generate enormous wealth through downstream effects by underpinning the rise of East Asian export economies, offshoring, and the retail models of Walmart, Amazon and the like. Most of us are much more likely to benefit from downstream structural shifts of AI rather than owning actual AI infrastructure. This matters because building the models, training infrastructure, and data centres is capital-intensive, brutally competitive, and may yield thin margins in the long run. The real fortunes are likely to flow to those who can reconfigure industries around the new cost curve.
- dash2 1y ago
  The article's point is exactly that you should invest downstream of AI.
  - th0ma5 1y ago
    The problem is different though, the containers were able to be made by others and offered dependable success, and anything downstream of model creators is at the whim of the model creator... And so far it seems not much that one model can do that another can't, so this all doesn't bode well for a reliable footing to determine what value, if at all, can be added by anyone for very long.
    - dash2 1y ago
      So if models, like containers, are able to be made by others (because they can all do the same thing), then they'll be commoditized and as the article suggests you should look for industries to which AI is a complement.
Nevermark 1y ago
> Consumers, however, will be the biggest beneficiaries. This looks certain. Few technologies have had as much adoption by so many individuals as quickly as AI models. (Not saying everything people are doing has economic value. But some does, and a lot of people are already getting enough informal and personal value that language models are clearly mainstreaming.) The biggest losers I see are successive waves of disruption to non-physical labor. As AI capabilities accrue relatively smoothly (perhaps), labor impact will be highly unpredictable as successive non-obvious thresholds are crossed. The clear winners are the arms dealers. The compute sellers and providers. High capex, incredible market growth. Nobody had to spend $10 or $100 billion to start making containers.
bossyTeacher 1y ago
Funny thing with people suddenly pretending we just got AI with LLMs. Arguably, AIs has been around for way longer, it just wasn't chatty. I think when people talking about AI, they are either talking about LLMs specifically or transformers. Both seem like a very reductive view of the AI field even if transformers are hottest thing around.
whistle650 1y ago
[flagged]
- Fade_Dance 1y ago
  >Many psychiatric medications (SSRIs, lithium, ketamine for depression) are effective, but their exact pathways and why they work for some and not others are unclear. >General anesthesia works consistently, yet the precise molecular-level reason consciousness disappears isn’t settled science. (this response written by... AI)
  - whistle650 1y ago
    Agreed, and I did mention medicines as examples of things that work but we don’t understand. But they weren’t “made” by us in quite the same way imo.
- wsintra2022 1y ago
  Except.. people do know exactly how these things work. They know because they are creating them. They know because they are improving them. What nonsense to say we do not know how these things work. Engineers building Qwen for example not only know how things work but they put all the work out there for people to reproduce (if they had the means) that work.
  - whistle650 1y ago
    Ok, so how does general anesthesia work? How does ketamine work for depression? The recipes for those are well-known.
    - deleted 1y ago
      [deleted]
  - visarga 1y ago
    We know in the same sense we understand the rules in Conway's game of life - at low level - but don't understand what those rules will produce at high level (gliders, guns) except by executing and seeing. Analogous to knowing what the code looks like and not knowing if it will halt. Knowing the low level rules, or the recursive transition rule of a system does not tell you its evolution in time.
wsintra2022 1y ago
>When any would-be innovator can build and train an LLM on their laptop and put it to use in any way their imagination dictates, it might be the seed of the next big set of changes That’s kinda happening, small local models, huggingface communities, civit ai and image models. Lots of hobby builders trying to make use of generative text and images. It just there’s not really anything innovative about text generation since anyone with a pen and paper can generate text and images.
pizzly 1y ago
I think OP's thesis should be expanded. -AI is leading to cost optimizations for running existing companies, this will lead to less employment and potentially cheaper products. Less people employed temporary will change demand side economics, cheaper operating costs will reduce supply/cost side -The focus should not just be on LLM's (like in the article). I think LLMs have shown what artificial neural networks are capable of, from material discovery, biological simulation, protein discovery, video generation, image generation, etc. This isn't just creating a cheaper, more efficient way of shipping goods around the world, its creating new classifications of products like the microcontroller invention did. -The barrier to start businesses is less. A programmer not good at making art can use genAI to make a game. More temporary unemployment from existing companies reducing cost by automating existing work flows may mean that more people will start their own businesses. There will be more diverse products available but will demand be able to sustain the cost of living of these new founders? Human attention, time etc is limited and their may be less money around with less employment but the products themselves should cost cheaper. -I think people still underestimate what last year/s LLMs and AI models are capable of and what opportunities they open up, Open source models (even if not as good as the latest gen), hardware able to run these open source models becoming cheaper and more capable means many opportunities to tinker with models to create new products in new categories independent of being reliant on the latest gen model providers. Much like people tinkering with microcontrollers in the garage in the early days as the article mentioned. Based on the points above alone while certain industries (think phone call centers) will be in the red queen race scenario like the OP stated there will new industries unthought of open up creating new wealth for many people.
- franktankbank 1y ago
  Imagine a giant trawling net scooping up the last two-three decades undeprecated of work on the web/data/game/operating system space and cutting out the people who did all that work. What do you think is going to happen to the progression in those areas? I guess it was "done"? The LLM AI is only as good as its input, as far as I can tell there is no reason to believe any of its second order outputs. RLHF is an interesting plug for that hole but its only as good as the human feedback and even then those things taken to second order aren't going to be any good. This collapses the barrier to entry to existing products, aka those people are going to be swamped with new competition.
zkmon 1y ago
A few issues: 1. The tech revolutions of the past were helped by the winds of global context. There were many factors that propelled those successful technologies on the trajectories. The article seems to ignore the contextual forces completely. 2. There were many failed tech revolutions as well. Success rate was varied from very low to very high. Again the overall context (social, political, economic, global) decides the matters, not technology itself. 3. In overall context, any success is a zero-sum game. You maybe just ignoring what you lost and highlighting your gains as success. 4. A reverse trend might pickup, against technology, globalization, liberalism, energy consumption etc
Ozzie_osman 1y ago
Like any gold rush, there will be gold, but there will also be folks who take huge bets and end up with a pan of dirt. And of course, there will be grifters.
rf15 1y ago
If we can create an AGI, then an an AGI can likely create more AGIs, and at that point you're trying to sell people things they can just have for free/traditional money and power are worthless now. Thus, an AGI will not be built as a commercial solution.
visarga 1y ago
AI is used by students, teachers, researchers, software developers, marketers and other categories and the adoption rates are close to 90%. Even if it does not make us more productive we still like using it daily. But when used right, it does make us slightly more productive and I think it justifies its cost. So yes, in the long run it will be viable, we both like using it and it helps us work better. But I think the benefits of AI usage will accumulate with the person doing the prompting and their employers. Every AI usage is contextualized, every benefit or loss is also manifested in the local context of usage. Not at the AI provider. If I take a photo of my skin sore and put it on ChatGPT for advice, it is not OpenAI that is going to get its skin cured. They get a few cents per million tokens. So the AI providers are just utilities, benefits depend on who sets the prompts and and how skillfully they do it. Risks also go to the user, OpenAI assumes no liability. Users are like investors - they take on the cost, and support the outcomes, good or bad. AI company is like an employee, they don't really share in the profit, only get a fixed salary for work
- sumanthvepa 1y ago
  This. Right now the consumer surplus created by improved productivity is being captured by users and to a small extent their employers. But that may not remain the case in future.
- grues-dinner 1y ago
  > AI is used by students, teachers, researchers, software developers, marketers and other categories and the adoption rates are close to 90%. Even if it does not make us more productive we still like using it daily. Nearly everyone uses pens daily but almost no one really cares about them or says their company runs using pens. You might grumble when the pens that work keeps in the stationary cupboard are shit, perhaps. I imagine eventually "AI" services will be commoditised in the same way that pens are now. Loads of functional but faily low-quality stuff, some fairly nice but affordable stuff and some stratospheric gold plated bricks for the military and enthusiasts. In the middle is a large ecosystem of ink manufacturers, lathe makers, laser engravers, packaging companies and logistics and so on and on that are involved. The explosive, exponential winner-takes-all scenario where OpenAI and it's investors literally ascend to godhood and the rest of humanity lives forever under their divine bootheels doesn't seem to be the trajectory we're on.
tempodox 1y ago
Never say never, but I certainly don’t see LLMs as the basis for industrial fortunes. Maybe future forms of “AI” could be that.
graycat 1y ago
Apparently a lot of money is flowing into AI. Looking around, can find curious things current AI can't do but likely can find important things it can do. Uh, there's "a lot of money", can't be sure AI won't make big progress, and even on a national scale no one wants to fall behind. Looking around, it's scary about the growth -- Page and Brin in a garage, Bezos in a garage, Zuckerberg in school and "Hot or Not", Huang and graphics cards, .... One or two guys, ... and in a few years change the world and $trillions in company value??? Smoking funny stuff? Yes, AI can be better than a library card catalog subject index and/or a dictionary/encyclopedia. But a step or two forward and, remembering 100s of soldiers going "over the top" in WWI, asking why some AI robots won't be able to do the same? Within 10 years, what work can we be sure AI won't be able to do? So people will keep trying with ASML, TSMC, AMD, Intel, etc. -- for a yacht bigger than the one Bezos got or for national security, etc. While waiting for AI to do everything, starting now it can do SOME things and is improving. Hmm, a SciFi movie about Junior fooling around with electronics in the basement, first doing his little sister Mary's 4th grade homework, then in the 10th grade a published Web site book on the rise and fall of the Eastern Empire, Valedictorian, new frontiers in mRNA vaccines, ...? And what do people want? How 'bout food, clothing, shelter, transportation, health, accomplishment, belonging, security, love, home, family? So, with a capable robot (funded by a16z?), it builds two more like itself, each of those ..., and presto-bingo everyone gets what they want? "Robby, does P = NP?" "Is Schrödinger's equation correct?" "How and when can we travel faster than the speed of light?" "Where is everybody?"
lemonberry 1y ago
I can see AI helping some businesses do really well. I can also see it becoming akin to mass manufacturing. Take furniture for example, there's a lot of mass produced furniture of varying quality. But there are still people out there making furniture by hand. A lot of the hand built furniture is commanding higher prices due to the time and skill required. And people buy it! I think we'll see a ton of games produced by AI or aided heavily by AI but there will still be people "hand crafting" games: the story, the graphics, etc. A subset of these games will have mass appeal and do well. Others will have smaller groups of fans. It's been some time since I've read it, but these conversation remind me of Walter Benjamin's essay, "The Work of Art in the Age of Mechanical Reproduction".
- RataNova 1y ago
  There's always going to be a market for things that feel personal, intentional, and imperfect in a way that only human creators can deliver
  - ACCount37 1y ago
    Like there's market for hand-made, artisanal spoons and forks. Is it a large market though?
    - pydry 1y ago
      It'd be larger if wealth inequality werent so staggeringly high. The first automated-server restaurants (Horn and hardart) appeared in the 1930s during the depression. They were popular because they were cheap. Far from being the wave of the future, they went out of business in the 1950s when people started having disposable income. Part of the reason we accept slop, impersonal service and mass produced crud is not because "demand" is indifferent to it, but because disposable income is so often politically repressed, meaning the market is forced to prioritize price.
      - lotsofpulp 1y ago
        I have doubts on the quality and how automated a 1930s restaurant could have been.
RataNova 1y ago
The part that stuck with me most: "Success will mean defeat." That nails the challenge of investing in the current AI landscape
another_twist 1y ago
I guess one flaw in the argument about success leading to failure due to model providers eating the product layer, esp for B2B, is it ignores switching costs. B2B integrations such as Glean or Abridge which work with an existing infrastructure setup are hard to throw away and there's little incentive to do so. So in that sense, I dont think AI providers will manage to eat this layer completely without bloating themselves to an unmanageable degree. As an analogy, while Google / Apple control the entire mobile ecosystem, they dont make the most valuable apps. Case in point, gaming apps such as Fortnite who have made billions in microtransactions while running on platforms controlled by other behemoths. They are good investments too.
PolicyPhantom 1y ago
I think the real challenge is not whether AI will “replace” people, but how we preserve the spaces where skills are actually practiced and refined. Entry-level jobs, internships, and junior projects have always been more about learning curves than efficiency. If AI shortcuts those too aggressively, we risk cutting off the very ladder that produces the next generation of capable engineers and creators. Maybe the question isn’t “Will AI take jobs?” but “How do we redesign pathways so humans still get the training ground they need—while AI handles the repetitive load?”

239 points by saucymew 1y ago

This article seems to have scoped AI as LLMs and totally missed the revolutionary application that is self driving cars. There will be a lot more applications outside of chat assistants.

mafro 1y ago
The same idea applies to self-driving cars though, no? That is an industry where the "AI revolution" will enrich only the existing incumbents, and there is a huge bar to entry. Self-driving cars are not going to create generational wealth through invention like microprocessors did.

HPsquared 1y ago

The title is a false dichotomy. It could be a net gain but spread across the whole society if the value added is not concentrated. This is what happens when users gain value which they themselves capture, and the AI companies only get the nominal $20/month or whatever. In those cases it's a net gain for the economy as a whole if valuable work was done at low cost. The inverse of the broken window fallacy.

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mattmanser 1y ago
Like all tech we've had recently, that won't last, it's always bait and switch. It will not remain cheap as soon as the competition is dead, which is simply a case of who's got the biggest VC supplied war chest.
- kasey_junk 1y ago
  Like with databases? There are none of those freely available now that Oracle won right?
  - mattmanser 1y ago
    Snark only works when you've got a valid point. One person can write sqllite. You can iterate up to bigger opensource DBs like postgre. One person cannot create a modern LLM model unless they have 10s of millions of dollars to burn on compute. LLMs are a fundamental shift from what was achievable in software and OSS, and we're basically living off scraps from the big players releasing their old models. They're already trying to create regulatory moats too.
    - kasey_junk 1y ago
      Oracle is far and away better than any of the open source databases. For a long time it wasn’t particularly close. Db didn’t get parity with Oracle, they got good enough that you have to justify spending for Oracle and incurring the down sides of its company’s model. Similarly, no db that competes with Oracle was written by one person, they were and are funded mostly by private companies and foundations. There is a future where open weight models are good enough and the foundation labs are the truly luxury tier for a small subset of the user base. That’s before talking about something like productivity software which Google _gives away_ while it’s a main business of Microsoft. Blindly saying that there is only a future where the foundation llms capture all of the business is hyperbolic and ignores history. The llms look more db shaped to me than they look like car shares. Those truly are network effect dominated.
      - mattmanser 1y ago
        You mean the history where MS captured the OS, Applle/Google the phone, Google capture the entire search market for 20 years, Facebook the social web, Amazon shopping, NVidia/AMD, Netflix, Spotify, I could go on and on and on. Most things in tech settle into monopolies or duopolies. LLMs are more akin to the search market than the database market. They need to be updated constantly. Selectively picking out the one technology that's basically no-one's primary business is an odd way to try and convince me. It must be over 20 years now since any large company consider a DB to be a significant product. Open source winners like Linux and MySql/Postgre are the oddity, not the norm.

Mistletoe 1y ago

AI made me this summary (I’ve grown quite weary of reading AI think pieces) and it seems like a really good comparison. >The article "AI Will Not Make You Rich" argues that generative AI is unlikely to create widespread wealth for investors and entrepreneurs. The author, Jerry Neumann, compares AI to past technological revolutions, suggesting it's more like shipping containerization than the microprocessor. He posits that while containerization was a transformative technology, its value was spread so thinly that few profited, with the primary beneficiaries being customers. >The article highlights that AI is already a well-known and scrutinized technology, unlike the early days of the personal computer, which began as an obscure hobbyist project. The author suggests that the real opportunities for profit will come from "fishing downstream" by investing in sectors that use AI to increase productivity, such as professional services, healthcare, and education, rather than investing in the AI infrastructure and model builders themselves. I used to be the biggest AI hater around, but I’m finding it actually useful these days and another tool in the toolbox.

grugagag 1y ago
Did you read the article or you just relied on the AI generated summary? Lots of people argue that this kind of shortcut will make us dumber and the argument does make sense.

GMoromisato 1y ago

I think AI will be more like the smartphone revolution that Apple kicked off in 2005. Today there are two companies that provide the smartphone platform (Apple/Google), but thousands of large and small companies that build on top of it, including Uber, Snapchat, etc. In that scenario, everyone makes money: OpenAI, Google (maybe Anthropic, maybe Meta) make money on the platform, but there are thousands of companies that sell solutions on top. Maybe, however, LLMs get commoditized and open-source models replace OpenAI, etc. In that case, maybe only NVIDIA makes money, but there will still be thousands of companies (and founders/investors) making lots of money on AI everything.

ToucanLoucan 1y ago
I think there’s a gaping hole in your analogy: who in their right mind is spending $1,200 biennially to access LLMs at base, and subsequently spending several monthly subscriptions in a small amount to access particular LLM-powered “apps?” Every use case I have for LLMs is satisfied with copilot, but even then if it costs like $5 a month to access someday, I’d just as soon not have it. Let alone the subsequent spending.

cramcgrab 1y ago

Obviously the maker. Just look at how and who.

HarHarVeryFunny 1y ago

I would imagine AI will be similar to factory automation. There will be millions of factories all benefiting from it, and a relatively small number of companies providing the automation components (conveyor belt systems, vision/handling systems, industrial robots, etc). The technology providers are not going to become fabulously rich though as long as there is competition. Early adopters will have to pay up, but it seems LLMs are shaping up to be a commodity where inference cost will be the most important differentiator, and future generations of AI are likely to be the same. Right now the big AI companies pumping billions into it to advance the bleeding edge necessarily have the most advanced products, but the open source and free-weight competition are continually nipping at their heels and it seems the current area where most progress is happening is agents and reasoning/research systems, not the LLMs themself, where it's more about engineering rather than who has the largest training cluster. We're still in the first innings of AI though - the LLM era, which I don't think is going to last for that long. New architectures and incremental learning algorithms for AGI will come next. It may take a few generations of advance to get to AGI, and the next generation (e.g. what DeepMind are planning in 5-10 year time frame) may still include a pre-trained LLM as a component, but it seems that it'll be whatever is built around the LLM, to take us to that next level of capability, that will become the focus.

bgwalter 1y ago

It is interesting that the early shipping containerization boom resulted in a bubble in 1975 and had a new low around 1990. 1990 is when the real outsourcing mania started, which led to the destruction of most Western manufacturing. Apart from cheap Chinese trinkets the quality of life and real incomes have gotten worse in the West while the rich became richer. So this is an excellent analogy for "AI": Finding a new and malicious application can revive the mania after an initial bubble pop while making societies worse. If we allow it, which does not have to be the case. [As usual, under the assumption that "AI" works, of which there is little sign apart from summarizing scraped web pages.]

unleaded 1y ago

Something that's confused/annoyed me about the AI boom is that it's like we've learned to run before we learned to walk. For example, there are countless websites where you can generate a sophisticated, photorealistic image of anything you like, but there is no tool I know of that you can ask "give me a 16x16 PNG icon of an apple" and get exactly that. I know why—Neural networks excel at fixed size, organic data, but I don't think that makes it any less ridiculous. It also means that AI website generators are forced to generate assets with code when ordinary people would just use images/sound files (yes, I have really seen websites using webaudio synths for sound effects). Hopefully the boom will slow down and we'll all slowly move away from Holy Shit Hype things and implement more boring, practical things. (although I feel like the world has shunned boring practical things for quite a while before)

qwertygnu 1y ago
As you seem to understand, creating something that generally fits a description is the walking for AI. Following exact directions is the running. It may just feel reversed because of the path of other technology.
SquibblesRedux 1y ago
I just asked ChatGPT-5 to "give me a 16x16 PNG icon of an apple" and it did exactly that. It looks good, too. Not that I don't recognize the inherent limits of LLMs, but there are as many edge cases covered as are found in the training sets. (More or less.)
- unleaded 1y ago
  well i just asked it the same thing and it gave me a 1MB 1024x1024 png with fringed edges & sensor noise that measures out to a 17x21 pixel image. https://files.catbox.moe/1q4jtp.png https://files.catbox.moe/1q4jtp.png In the time it would take to keep retrying until it makes one that fits, then reshaping it to fit into 16x16 nicely I could have just drawn one myself.

CM30 1y ago

Practically speaking, it's going to be both more impactful than we think and less impactful than we think at the same time. On the one hand, there are a lot of fields that this form of AI can and will either replace or significantly reduce the number of jobs in. Entry level web development and software engineering is at serious risk, as is copywriting, design and art for corporate clients, research assistant roles and a lot of grunt work in various creative fields. If the output of your work is heavily represented in these models, or the quality of the output matters less than having something, ANYTHING to fill a gap on a page/in an app, then you're probably in trouble. If your work involves collating a bunch of existing resources, then you're probably in trouble. At the same time, it's not going to be anywhere near as powerful as certain companies think. AI can help software engineers in generating boilerplate code or setup things that others have done millions of times before, but the quality of its output for new tasks is questionable at best, especially when the language or framework isn't heavily represented in the model. And any attempts to replace things like lawyers, doctors or other such professions with AI alone are probably doomed to fail, at least for the moment. If getting things wrong is a dealbreaker that will result in severe legal consequences, AI will never be able to entirely replace humans in that field. Basically, AI is great for grunt work, and fields where the actual result doesn't need to be perfect (or even good). It's not a good option for anything with actual consequences for screwing up, or where the knowledge needed is specialist enough that the model won't contain it.

amradio1989 1y ago

AGI is where the real money is. Gen AI is okay but mostly benefits the consumer. Gen AI is not nearly powerful enough to justify current investments. A lot of money is going to go up in smoke.

jschveibinz 1y ago

We have a limited time on earth. AI may present an opportunity for us to improve the quality of life or the amount of time spent doing things we really want to do while we are here. Those who spend time figuring out how to use AI for these purposes will be heroes, and only then will AI have been a positive development for humanity. Get to work, heroes!

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akomtu 1y ago
Creating a machine lifeform that competes with humans for resources is hardly a heroic act.

gusfoo 1y ago

I genuinely think that large language models are a useful technology in data processing. Being "language models" I find it easy to use LLMs to extract subject, object, quantity, time, verb, amount, user's language code and so on from the input text, and to a fairly trustworthy level. After that, standard Information Retrieval techniques take over. What LLMs are absolutely not useful for, in my opinion, is answering questions or writing code, or summarising things, or being factual in any sense at all.

estimator7292 1y ago

The problem with viewing AI through the lens of capitalism is the fact that you can't make it artificially scarce. AI is largely capable of running on-device. In a few years, it's likely that most tasks that most people want AI for will be possible from a tiny model living in their phone. Open source models are plentiful, functional, and only becoming moreso. But you can't monetize that. We're currently dumping billions of dollars into datacenter moats that are just gonna evaporate inside the decade. For the average user doing their daily "who was that actor in that movie" query, no, you absolutely cannot monetize AI because all of your local devices can run the model for free with enough quality that no one will know or care that there's a difference. For enterprise scale building a trillion dollar datacenter and 15 nuclear reactors to replace a hundred developers... also no. LLMs are not capable of that, and likely won't be in the foreseeable future. It's also extremely unclear that one could ever get an ROI on in-house AI like this. It might be more plausible if it were a commodity technology you can just buy, but then you can't make a moat. The only hypothetical fortune to be found is by whoever is selling AI to people who think they need to buy AI. Just like bitcoin or NFTs. The good news is that this has two possible outcomes: capitalist AI vendors will want to remove AI from individual access so they can sell it to you: everyone gets less AI. Capitalists realize they can never monetize AI when it's free and open source, and give up: everyone gets less AI. Win-win-win, in my book.

SilverElfin 1y ago

Maybe the basis of concentration of power and wealth more than anything else

tim333 1y ago

>The disruption is real. It's also predictable. I'm not sure it is very predictable. We have people saying AI is LLMs and they won't be much use and there'll be another AI winter (Ed Zitron), and people and people saying we'll have AGI and superintelligence shortly (Musk/Altman), and if we do get superintelligence it's kind of hard to know how that will play out. And then there's John von Neumann (1958): >[the] accelerating progress of technology and changes in human life, which gives the appearance of approaching some essential singularity in the history of the race beyond which human affairs, as we know them, could not continue. which is what kicked of the misuse of a perfectly good mathematical term for all that stuff. Compared to the other five revolutions listed - industrial, rail, electricity, cars and IT, I think AI is a fair bit less predictable.

NumberCruncher 1y ago

Making an industrial fortune is relative. It might just mean that jumping on the AI hype helps you preserve your fortune or position in the industry, while everyone else who misses the hype goes out of business. I remember back in 2004, my first project was testing a teleconferencing system. We set up a huge screen with cameras at one of our subsidiaries and another at the HQ, and I had a phone on my desk with a built-in camera and screen. Did the company roll out the system? No, it didn’t. It was just too expensive. Did they make a fortune from that experience? No, they didn’t. But I’m pretty sure all companies in the knowledge industry that didn’t enable video calls and screen sharing for their employees went out of business years ago...

ath3nd 1y ago

With AI everyone is a net loser. People using it get dumber. What is being produced is slop and discardable poc-like trash The environmental costs of building and training LLMs are huge. That compute and water could have been useful for something. Even the companies building and peddling AI are losers. They are not profitable, need constant billions of dollars of financial help to even syay afloat and pay their compute depth. The worst part is that even bigger losers will be the general population. Not only are our kids gonna be dumber than us thanks to never having to think for themselved, but our pensions are tied to the stock market that will inevitably collapse when the realization that the top 30% of companies in terms of value are just dominoes waiting to collapse. But the biggest loser of all is Elon Musk. Just because of who he is.

noduerme 1y ago

This is a great perspective. If anything, I'd think that crypto in 2010 had all the hallmarks of a new wave as described. The concept was open to anyone who wanted to tinker with it. It had to be sold to skeptical consumers by wildcat startups. It certainly had the potential to upend the financial industry, but no incumbent would touch it. Yet it did end up more or less being sucked into the gravity well of the incumbents, although in the case of crypto we very much need to consider governments which control the money supply to be the heavyweights, even more so than banks and lenders. Maybe I'm pessimistic, but I'm not sure any new innovation now can escape the gravitational nexus of the duopoly of government and incumbent tech, in a way that would lead to the kind of wild growth and experimentation we had with microprocessors in the 70s. We had some guy named Satoshi write a paper that basically handed the keys to anyone who wanted to experiment - and 17 years later, after a significant bubble, that wave has done very little to change the status quo. I suppose if someone released a DIY genome editor or protein folding was solved or, like, a working Mr. Fusion device showed up on Kickstarter, or a "feed"/"seed" a la the Diamond Age made it possible to turn dirt into anything you wanted, or a FTL drive came out of someone's garage or something... yeah. That would seriously upset the incumbents. But even with sci-fi stuff like that, what's the moat once you make your findings public anymore? This article suggests that the only serious moat has ever been that large companies are slowed down by inertia and take some time to spin up once their internal cultures go from deriding something to deciding it's essential. How do we know if we have stalled to the point that no one will come along and be the next Amazon or Google, until 50 years from now we see that no one did?

wewewedxfgdf 1y ago

You can't make such generalized statements about anything in computing/business. The AI revolution has only just got started. We've barely worked out basic uses for it. No-one has yet worked out revolutionary new things that are made possible only by AI - mostly we are just shoveling in our existing world view.

kg 1y ago
The way I look at this question is: Is there somehow a glaring vulnerability/missed opportunity in modern capitalism that billions of people somehow haven't discovered yet? And if so, is AI going to discover it? And if so, is a random startup founder or 'little guy' going to be the one to discover and exploit it somehow? If so, why wouldn't OpenAI or Anthropic etc get there first given their resources and early access to leading technology? IIRC Sam Altman has explicitly said that their plan is to develop AGI and then ask it how to get rich. I can't really buy into the idea that his team is going to fail at this but a bunch of random smaller companies will manage to succeed somehow. And if modern AI turns into a cash cow for you, unless you're self-hosting your own models, the cloud provider running your AI can hike prices or cut off your access and knock your business over at the drop of a hat. If you're successful enough, it'll be a no-brainer to do it and then offer their own competitor.
- wewewedxfgdf 1y ago
  >> Is there somehow a glaring vulnerability/missed opportunity in modern capitalism that billions of people somehow haven't discovered yet? Absolutely with 150% certainty yes, and probably many. The www started April 30, 1993, facebook started February 4, 2004 - more than ten years until someone really worked out how to use the web as a social connection machine - an idea now so obvious in hindsight that everyone probably assumes we always knew it. That idea was simply left lying around for anyone to pick up and implement rally fropm day one of the WWW. Innovation isn't obvious until it arrives. So yes absolutely the are many glaring opportunities in modern capitalism upon which great fortunes are yet to be made, and in many cases by little people, not big companies. >> if so, is a random startup founder or 'little guy' going to be the one to discover and exploit it somehow? If so, why wouldn't OpenAI or Anthropic etc get there first given their resources and early access to leading technology? I don't agree with your suggestion that the existing big guys always make the innovations and collect the treasure. Why did Zuckerberg make facebook, not Microsoft or Google? Why did Gates make Microsoft, not IBM? Why did Steve and Steve make Apple, not Hewlett Packard? Why did Brin and Page make Google - the worlds biggest advertising machine, not Murdoch?

ThrowawayTestr 1y ago

And Dropbox will never take off

unleaded 1y ago
people also said the juicero and the smart condom would never take off. this isnt a very useful gotcha
- fred_is_fred 1y ago
  The dig on Dropbox is that it was easy to build, not that it wasn’t useful. Juicero was neither easy to build (relatively) nor useful.
giveita 1y ago
Non sequitur: Dropbox is a single company in the industry benefiting from the first wave. His argument would not exclude Dropbox anyway.

nextworddev 1y ago

AI by nature is kind of like a black hole of value. Necessarily, a very small fraction will capture the vast majority of value. Luckily, you can just invest wisely to hedge some of the risk of missing out.

xnx 1y ago

AI could've made someone unimaginably rich if they were the only one that had it. We're very lucky Google didn't keep "Attention is All You Need" to themselves.

back2dafucha 1y ago
I doubt we'll feel that way in 5 years.
- echelon 1y ago
  Because now they're keeping everything to themselves?
  - visarga 1y ago
    Attention (technology) is all they need (to keep secret).

Waterluvian 1y ago

I think the interesting idea with “AI” is that it seems to significantly reduce barriers to entry in many domains. I haven’t seen a company convincingly demonstrate that this affects them at all. Lots of fluff but nothing compelling. But I have seen many examples by individuals, including myself. For years I’ve loved poking at video game dev for fun. The main problem has always been art assets. I’m terrible at art and I have a budget of about $0. So I get asset packs off Itch.io and they generally drive the direction of my games because I get what I get (and I don’t get upset). But that’s changed dramatically this year. I’ll spend an hour working through graphics design and generation and then I’ll have what I need. I tweak as I go. So now I can have assets for whatever game I’m thinking of. Mind you this is barrier to entry. These are shovelware quality assets and I’m not running a business. But now I’m some guy on the internet who can fulfil a hobby of his and develop a skill. Who knows, maybe one day I’ll hit a goldmine idea and commit some real money to it and get a real artist to help! It reminds me of what GarageBand or iMovie and YouTube and such did for making music and videos so accessible to people who didn’t go to school for any of that, let alone owned complex equipment or expensive licenses to Adobe Thisandthat.

ta12653421 1y ago
Regarding assets, check out Nano Banana: https://github.com/PicoTrex/Awesome-Nano-Banana-images/blob/main/README_en.md https://github.com/PicoTrex/Awesome-Nano-Banana-images/blob/... For you the example of "extract object and create iso model" should be relevant :)
SideburnsOfDoom 1y ago
> "AI" is that it seems to significantly reduce barriers to entry in many domains. If you ask an LLM to generate some imagery, in what way have you entered visual arts? If you ask an LLM to generate some music, in what way have you entered being a musician? If you ask an LLM to generate some text, in what way have you entered writing?
Havoc 1y ago
Yeah that seems accurate. I mainly use AI for selfhosting/homelab stuff and the leverage there is absolutely wild - basically knows "everything".

pevansgreenwood 1y ago

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firesteelrain 1y ago

There are plenty of companies making money. We are using several “AI powered” job aids that are leading to productivity gains and eliminating technical debt. We are licensing the product via subscription. Money is being made by the companies selling the products. Example https://specinnovations.com/blog/ai-tools-to-support-requirements-engineering-and-test-case-developments https://specinnovations.com/blog/ai-tools-to-support-require...

palata 1y ago

Counterpoint: those engineers who get paid millions to work on AI.

oblio 1y ago
All 5000 of them?
- palata 1y ago
  My point is that AI makes some people rich. Nothing makes everyone rich, otherwise nobody would be rich. Not that it is a good thing, but that's how it is.

dweinus 1y ago

I don't think most commenters have read the article. I can understand, it's rambly and a lot of it feels like they created a thesis first and then ham-fisted facts in later. But it's still worth the read for the last section which is a more nuanced take than the click-bait title suggests.

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mhb 1y ago

Seems like the thing to do to get rich would be to participate in services that it will take a while for AI to be able to do: nursing, plumbing, electrician, carpentry (i.e., Baumol). Also energy infrastructure.

kristianc 1y ago

> Yet some technological innovations, though societally transformative, generate little in the way of new wealth; instead, they reinforce the status quo. Fifteen years before the microprocessor, another revolutionary idea, shipping containerization, arrived at a less propitious time, when technological advancement was a Red Queen’s race, and inventors and investors were left no better off for non-stop running. This collapses an important distinction. The containerization pioneers weren’t made rich - that’s correct, Malcolm McLean, the shipping magnate who pioneered containerization didn’t die a billionaire. It did however generate enormous wealth through downstream effects by underpinning the rise of East Asian export economies, offshoring, and the retail models of Walmart, Amazon and the like. Most of us are much more likely to benefit from downstream structural shifts of AI rather than owning actual AI infrastructure. This matters because building the models, training infrastructure, and data centres is capital-intensive, brutally competitive, and may yield thin margins in the long run. The real fortunes are likely to flow to those who can reconfigure industries around the new cost curve.

dash2 1y ago
The article's point is exactly that you should invest downstream of AI.
- th0ma5 1y ago
  The problem is different though, the containers were able to be made by others and offered dependable success, and anything downstream of model creators is at the whim of the model creator... And so far it seems not much that one model can do that another can't, so this all doesn't bode well for a reliable footing to determine what value, if at all, can be added by anyone for very long.
  - dash2 1y ago
    So if models, like containers, are able to be made by others (because they can all do the same thing), then they'll be commoditized and as the article suggests you should look for industries to which AI is a complement.

Nevermark 1y ago

> Consumers, however, will be the biggest beneficiaries. This looks certain. Few technologies have had as much adoption by so many individuals as quickly as AI models. (Not saying everything people are doing has economic value. But some does, and a lot of people are already getting enough informal and personal value that language models are clearly mainstreaming.) The biggest losers I see are successive waves of disruption to non-physical labor. As AI capabilities accrue relatively smoothly (perhaps), labor impact will be highly unpredictable as successive non-obvious thresholds are crossed. The clear winners are the arms dealers. The compute sellers and providers. High capex, incredible market growth. Nobody had to spend $10 or $100 billion to start making containers.

bossyTeacher 1y ago

Funny thing with people suddenly pretending we just got AI with LLMs. Arguably, AIs has been around for way longer, it just wasn't chatty. I think when people talking about AI, they are either talking about LLMs specifically or transformers. Both seem like a very reductive view of the AI field even if transformers are hottest thing around.

whistle650 1y ago

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Fade_Dance 1y ago
>Many psychiatric medications (SSRIs, lithium, ketamine for depression) are effective, but their exact pathways and why they work for some and not others are unclear. >General anesthesia works consistently, yet the precise molecular-level reason consciousness disappears isn’t settled science. (this response written by... AI)
- whistle650 1y ago
  Agreed, and I did mention medicines as examples of things that work but we don’t understand. But they weren’t “made” by us in quite the same way imo.
wsintra2022 1y ago
Except.. people do know exactly how these things work. They know because they are creating them. They know because they are improving them. What nonsense to say we do not know how these things work. Engineers building Qwen for example not only know how things work but they put all the work out there for people to reproduce (if they had the means) that work.
- whistle650 1y ago
  Ok, so how does general anesthesia work? How does ketamine work for depression? The recipes for those are well-known.
  - deleted 1y ago
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- visarga 1y ago
  We know in the same sense we understand the rules in Conway's game of life - at low level - but don't understand what those rules will produce at high level (gliders, guns) except by executing and seeing. Analogous to knowing what the code looks like and not knowing if it will halt. Knowing the low level rules, or the recursive transition rule of a system does not tell you its evolution in time.

wsintra2022 1y ago

>When any would-be innovator can build and train an LLM on their laptop and put it to use in any way their imagination dictates, it might be the seed of the next big set of changes That’s kinda happening, small local models, huggingface communities, civit ai and image models. Lots of hobby builders trying to make use of generative text and images. It just there’s not really anything innovative about text generation since anyone with a pen and paper can generate text and images.

pizzly 1y ago

I think OP's thesis should be expanded. -AI is leading to cost optimizations for running existing companies, this will lead to less employment and potentially cheaper products. Less people employed temporary will change demand side economics, cheaper operating costs will reduce supply/cost side -The focus should not just be on LLM's (like in the article). I think LLMs have shown what artificial neural networks are capable of, from material discovery, biological simulation, protein discovery, video generation, image generation, etc. This isn't just creating a cheaper, more efficient way of shipping goods around the world, its creating new classifications of products like the microcontroller invention did. -The barrier to start businesses is less. A programmer not good at making art can use genAI to make a game. More temporary unemployment from existing companies reducing cost by automating existing work flows may mean that more people will start their own businesses. There will be more diverse products available but will demand be able to sustain the cost of living of these new founders? Human attention, time etc is limited and their may be less money around with less employment but the products themselves should cost cheaper. -I think people still underestimate what last year/s LLMs and AI models are capable of and what opportunities they open up, Open source models (even if not as good as the latest gen), hardware able to run these open source models becoming cheaper and more capable means many opportunities to tinker with models to create new products in new categories independent of being reliant on the latest gen model providers. Much like people tinkering with microcontrollers in the garage in the early days as the article mentioned. Based on the points above alone while certain industries (think phone call centers) will be in the red queen race scenario like the OP stated there will new industries unthought of open up creating new wealth for many people.

franktankbank 1y ago
Imagine a giant trawling net scooping up the last two-three decades undeprecated of work on the web/data/game/operating system space and cutting out the people who did all that work. What do you think is going to happen to the progression in those areas? I guess it was "done"? The LLM AI is only as good as its input, as far as I can tell there is no reason to believe any of its second order outputs. RLHF is an interesting plug for that hole but its only as good as the human feedback and even then those things taken to second order aren't going to be any good. This collapses the barrier to entry to existing products, aka those people are going to be swamped with new competition.

zkmon 1y ago

A few issues: 1. The tech revolutions of the past were helped by the winds of global context. There were many factors that propelled those successful technologies on the trajectories. The article seems to ignore the contextual forces completely. 2. There were many failed tech revolutions as well. Success rate was varied from very low to very high. Again the overall context (social, political, economic, global) decides the matters, not technology itself. 3. In overall context, any success is a zero-sum game. You maybe just ignoring what you lost and highlighting your gains as success. 4. A reverse trend might pickup, against technology, globalization, liberalism, energy consumption etc

Ozzie_osman 1y ago

Like any gold rush, there will be gold, but there will also be folks who take huge bets and end up with a pan of dirt. And of course, there will be grifters.

rf15 1y ago

If we can create an AGI, then an an AGI can likely create more AGIs, and at that point you're trying to sell people things they can just have for free/traditional money and power are worthless now. Thus, an AGI will not be built as a commercial solution.

visarga 1y ago

AI is used by students, teachers, researchers, software developers, marketers and other categories and the adoption rates are close to 90%. Even if it does not make us more productive we still like using it daily. But when used right, it does make us slightly more productive and I think it justifies its cost. So yes, in the long run it will be viable, we both like using it and it helps us work better. But I think the benefits of AI usage will accumulate with the person doing the prompting and their employers. Every AI usage is contextualized, every benefit or loss is also manifested in the local context of usage. Not at the AI provider. If I take a photo of my skin sore and put it on ChatGPT for advice, it is not OpenAI that is going to get its skin cured. They get a few cents per million tokens. So the AI providers are just utilities, benefits depend on who sets the prompts and and how skillfully they do it. Risks also go to the user, OpenAI assumes no liability. Users are like investors - they take on the cost, and support the outcomes, good or bad. AI company is like an employee, they don't really share in the profit, only get a fixed salary for work

sumanthvepa 1y ago
This. Right now the consumer surplus created by improved productivity is being captured by users and to a small extent their employers. But that may not remain the case in future.
grues-dinner 1y ago
> AI is used by students, teachers, researchers, software developers, marketers and other categories and the adoption rates are close to 90%. Even if it does not make us more productive we still like using it daily. Nearly everyone uses pens daily but almost no one really cares about them or says their company runs using pens. You might grumble when the pens that work keeps in the stationary cupboard are shit, perhaps. I imagine eventually "AI" services will be commoditised in the same way that pens are now. Loads of functional but faily low-quality stuff, some fairly nice but affordable stuff and some stratospheric gold plated bricks for the military and enthusiasts. In the middle is a large ecosystem of ink manufacturers, lathe makers, laser engravers, packaging companies and logistics and so on and on that are involved. The explosive, exponential winner-takes-all scenario where OpenAI and it's investors literally ascend to godhood and the rest of humanity lives forever under their divine bootheels doesn't seem to be the trajectory we're on.

tempodox 1y ago

Never say never, but I certainly don’t see LLMs as the basis for industrial fortunes. Maybe future forms of “AI” could be that.

graycat 1y ago

Apparently a lot of money is flowing into AI. Looking around, can find curious things current AI can't do but likely can find important things it can do. Uh, there's "a lot of money", can't be sure AI won't make big progress, and even on a national scale no one wants to fall behind. Looking around, it's scary about the growth -- Page and Brin in a garage, Bezos in a garage, Zuckerberg in school and "Hot or Not", Huang and graphics cards, .... One or two guys, ... and in a few years change the world and $trillions in company value??? Smoking funny stuff? Yes, AI can be better than a library card catalog subject index and/or a dictionary/encyclopedia. But a step or two forward and, remembering 100s of soldiers going "over the top" in WWI, asking why some AI robots won't be able to do the same? Within 10 years, what work can we be sure AI won't be able to do? So people will keep trying with ASML, TSMC, AMD, Intel, etc. -- for a yacht bigger than the one Bezos got or for national security, etc. While waiting for AI to do everything, starting now it can do SOME things and is improving. Hmm, a SciFi movie about Junior fooling around with electronics in the basement, first doing his little sister Mary's 4th grade homework, then in the 10th grade a published Web site book on the rise and fall of the Eastern Empire, Valedictorian, new frontiers in mRNA vaccines, ...? And what do people want? How 'bout food, clothing, shelter, transportation, health, accomplishment, belonging, security, love, home, family? So, with a capable robot (funded by a16z?), it builds two more like itself, each of those ..., and presto-bingo everyone gets what they want? "Robby, does P = NP?" "Is Schrödinger's equation correct?" "How and when can we travel faster than the speed of light?" "Where is everybody?"

lemonberry 1y ago

I can see AI helping some businesses do really well. I can also see it becoming akin to mass manufacturing. Take furniture for example, there's a lot of mass produced furniture of varying quality. But there are still people out there making furniture by hand. A lot of the hand built furniture is commanding higher prices due to the time and skill required. And people buy it! I think we'll see a ton of games produced by AI or aided heavily by AI but there will still be people "hand crafting" games: the story, the graphics, etc. A subset of these games will have mass appeal and do well. Others will have smaller groups of fans. It's been some time since I've read it, but these conversation remind me of Walter Benjamin's essay, "The Work of Art in the Age of Mechanical Reproduction".

RataNova 1y ago
There's always going to be a market for things that feel personal, intentional, and imperfect in a way that only human creators can deliver
- ACCount37 1y ago
  Like there's market for hand-made, artisanal spoons and forks. Is it a large market though?
  - pydry 1y ago
    It'd be larger if wealth inequality werent so staggeringly high. The first automated-server restaurants (Horn and hardart) appeared in the 1930s during the depression. They were popular because they were cheap. Far from being the wave of the future, they went out of business in the 1950s when people started having disposable income. Part of the reason we accept slop, impersonal service and mass produced crud is not because "demand" is indifferent to it, but because disposable income is so often politically repressed, meaning the market is forced to prioritize price.
    - lotsofpulp 1y ago
      I have doubts on the quality and how automated a 1930s restaurant could have been.

RataNova 1y ago

The part that stuck with me most: "Success will mean defeat." That nails the challenge of investing in the current AI landscape

another_twist 1y ago

I guess one flaw in the argument about success leading to failure due to model providers eating the product layer, esp for B2B, is it ignores switching costs. B2B integrations such as Glean or Abridge which work with an existing infrastructure setup are hard to throw away and there's little incentive to do so. So in that sense, I dont think AI providers will manage to eat this layer completely without bloating themselves to an unmanageable degree. As an analogy, while Google / Apple control the entire mobile ecosystem, they dont make the most valuable apps. Case in point, gaming apps such as Fortnite who have made billions in microtransactions while running on platforms controlled by other behemoths. They are good investments too.

PolicyPhantom 1y ago

I think the real challenge is not whether AI will “replace” people, but how we preserve the spaces where skills are actually practiced and refined. Entry-level jobs, internships, and junior projects have always been more about learning curves than efficiency. If AI shortcuts those too aggressively, we risk cutting off the very ladder that produces the next generation of capable engineers and creators. Maybe the question isn’t “Will AI take jobs?” but “How do we redesign pathways so humans still get the training ground they need—while AI handles the repetitive load?”