5 ms·

Some napkin math -- total global labor compensation is about 50% of the GDP, which puts it in the USD 50 - 60 Trillion range: https://ourworldindata.org/grapher

• e9 4mo ago
  I want to propose alternative reality where 1.5-2.5T in value doesn't go to a handful of companies. Instead it turns out to be like restaurants where this gets distributed to lots and lots of small, local, mostly interchangeable teams. There will of course be some super star "chefs" leading the industry and setting trends and some "restaurant chain" like big businesses and supply chain for all of this.
  • actionfromafar 4mo ago
    Sysco is pretty big.
  • xxpor 4mo ago
    The world is not zero sum. Value is created, not just preserved. Anthropic and OpenAI creating value does not imply that smaller guys can not also create value.
    • afavour 4mo ago
      But marketplaces also exist and big players in a marketplace are often able to manipulate the market such that they are advantaged and small players are not able to break in.
      • mpyne 4mo ago
        This is true of every market that has ever existed, and that's not stopped small players from finding niches.
  • bdamm 4mo ago
    How? Training and operating models seems to naturally focus on those willing to invest quite significantly in these operations.
    • nish__ 4mo ago
      If RAM prices come down, running your own models will be relatively affordable.
  • keeda 4mo ago
    FWIW I do think that availability of competitive open weight and other non-frontier models, along with improvements in harnesses that can get good results out of these models, will result in less concentration and a healthier marketplace. However, these frontier labs are also making moves that could let them capture a disproportionate share of the upside. One possibility is a situation analogous to the smartphone manufacturing space, where there are dozens of players but just a handful (e.g. Apple, Samsung in smartphones) capture the lion's share of the revenue.
    • skeptic_ai 4mo ago
      Apple you can’t exit the ecosystem. Samsung the same. And is the best android device. If tomorrow comes a Nokia os will be dead in the water: it has no apps. But with a new llm that doesn’t matter. There is nothing sticky about typing Gemini, Claude or codex in a cli.
      • keeda 4mo ago
        There's nothing sticky today but you can bet they're working maniacally to fix that. These companies will make most of their money in the enterprise space and there are probably unlimited ways to engineer stickiness in an enterprise setting. Like, MSFT still rakes in those billions despite pretty much every one of their products having commodity competitors. The AI labs are also making moves to secure long-term enterprise presence, such as their Forward Deployed Engineer strategy. I think that is a trojan horse play that could make enterprises dependent on them forever, much like so many companies are still dependent on IBM's mainframes. As an extreme example, you could imagine a company's core business logic encoded in the weights of a proprietary model custom-trained and hosted by one of these model providers, something even more inscrutable and sticky than ancient COBOL codebases.
• danenania 4mo ago
  I’d also point out that LLM inference revenue already totals more than 100B annually based on publicly reported numbers. Almost none of that is replacing knowledge workers. Almost all is increasing their productivity. So empirically what you describe is already happening to a nontrivial degree.
  • rimliu 4mo ago
    Where does this BS come from?
    • danenania 4mo ago
      > publicly reported numbers Anyone can google it /shrug
• ricardobayes 4mo ago
  I am deeply surprised by the silence of philosophers, sociologists, liberal arts majors, economists. Where are the think tanks who contemplate and debate the societal aspects? The tech is advancing full steam but the "other side" doesn't feel anywhere nearly ready.
  • bloppe 4mo ago
    Idk why you're perceiving silence. Feels to me like this is the main thing people talk about nowadays.
    • scarmig 4mo ago
      It has to do with the scope of what they're discussing. It seems extraordinarily small: e.g. what if AI increases productivity growth by 0.4%? Do data centers use too much water? Are AIs racist when reviewing resumes? The frontier labs, on the other hand, are thinking about replacing all human labor, ending death, and the risk of it causing human extinction. Most of the apparatus we're talking about approach it very parochially; it's almost like they're embarrassed to take the grander ideas even a little seriously, for being too nerdy/sci-fi.
      • freejazz 4mo ago
        The public would happily string up any of these CEOs if given the chance
      • icepush 3mo ago
        Death is a quirk of the universe underwritten by the current understanding of the second thermodynamic law. I don’t think any AI companies are making progress on that any time soon.
  • digitaltrees 4mo ago
    Reid Blackmun has written several books and has a consultanting agency to guide ethical implementation of AI
  • 4mo ago
• parineum 4mo ago
  > If LLMs can boost their productivity even by an average of 5% (studies from ~2024 put it in the ~30% range depending on task) that is ~1.5 - 2.5T in value Minus the cost of inference, that might not be the boon you're making it out to be. I hear what people around here are spending on their api and I'm skeptical that these tools are making me that much more productive. Personally, for assisted development, I haven't seen much progress in a while.
• hedora 4mo ago
  You’re trying to apply value based pricing (infinite margin upside) to a commodity. Pre-bubble pricing: $1400 gets a 128GiB iGPU optimized for inference. Glm and kimi need 800-1000GiB. Call it 1TiB. The $1400 boxes could be ganged into sets of 4-8, with a switch. Call the switch $1000. Each box has a TDP of 250W. 8 x 250/120V = 16.666A, or one household circuit in the US, so no new power infrastructure is needed. $1400 x 8+1000=$12,200. Assuming standard five year depreciation, that’s $2440 a year. There are a billion knowledge workers alive today. So that’s $2.4T annual revenue. Average net profit margins on computer hardware are 4.3%. That works out to $105B net income, globally. So, I guess the question is whether the (currently #2) open weight models provide $1.4-2.4T less value per year than the #1 and #3 models, and, if so, if customers can measure this, or are willing to spend 2x more and deal with censorship, data theft, intentional enshitification, sabotage, ads, product placement, etc, to get the slightly “better” model. Also, note that my numbers assume moore’s law stopped for all time in 2024, but we’ve seen HW improvements since then.
  • keeda 4mo ago
    Right, that number is more of an estimate of the value proposition of the entire AI industry rather than projections of revenue or valuations... it's essentially an estimate on how much the market could theoretically bear. Whether the companies can capture that value is, to your point, rightly a different question. I do think open weight and other competitor models, especially with better harnesses, will play a significant role in the equation and will result in less concentration in the market. However, I do also think the big AI companies will capture a lot of that value. Partially for the same reasons that the cloud industry has been growing like gangbusters, even pre-AI, despite on-prem being much cheaper: companies will outsource anything that is not deemed a "core competency" for their business. A lot of the problems you mentioned will be relegated to the consumer market and won't apply to enterprise contracts -- which is where the real money is.
    • wiker 3mo ago
      A buzz word here, a buzz word there. Mate your logic is insanely broken, underpinned by wishy washy assumptions mixed with shaky predictions about the future. Aka a whole lotta noise
• everforward 4mo ago
  > Note, at 5% productivity boost, humans are not just in the loop, they are the loop. AGI or large-scale replacement of humans is not even needed, but the financial opportunity is already immense, and it scales with how much human productivity can be improved (i.e. how much work can be offloaded to LLMs.) The studies I've seen recently (at least in the software space) put it at something like a 10% increase in coding speed, which for me would probably translate to something like a 3% increase in productivity. I spend a lot more time on things like getting agreement between teams, documenting approaches to things that don't exist on the wiki, etc, that LLMs are significantly less effective at. Or just can't do; no one will be happy if I send an LLM instead of me to meetings. I suspect a lot of roles are like that. They give a 10-30% boost to the core role function, but that core role is still only 30-50% of what you do. > that is ~1.5 - 2.5T in value annually That seems really large, but it's ~2-3x Walmart's yearly revenue, and OpenAI and Anthropic both have estimated valuations that compare to Walmart's market cap. And this is before we consider that they need to do it for cheaper or why would anyone bother. Realistically, potential revenue is probably half that at best. It's also before cutthroat pricing really kicks in. People are willing to pay for Claude right now; I still suspect that as time goes on people will start looking towards Deepseek/GLM/etc models that provide 95% of the performance at 10% of the price. That'll cut the market even further. The question is how much demand for knowledge work swells as prices fall, and whether that's a soft landing or a crash.
  • keeda 4mo ago
    > That seems really large, but it's ~2-3x Walmart's yearly revenue, and OpenAI and Anthropic both have estimated valuations that compare to Walmart's market cap. ... It's also before cutthroat pricing really kicks in. Right, that's more of an estimate on the value proposition of the overall AI industry, rather than valuations of the industry or specific players. While I don't think OpenAI and Anthropic will capture all of the potential upside, I do suspect they will do much better than other players despite the competition (https://news.ycombinator.com/item?id=48740472 https://news.ycombinator.com/item?id=48740472) > And this is before we consider that they need to do it for cheaper or why would anyone bother. Typically yes, but there are reasons companies may be willing to pay the same amount or even more, such as "AI doesn't need sleep, holidays, insurance, or benefits" and "AI is easier to procure and replace than humans." > The studies I've seen recently (at least in the software space) put it at something like a 10% increase in coding speed... Curious to see which studies you're looking at, the studies I'm thinking of (some here: https://news.ycombinator.com/item?id=45379452 https://news.ycombinator.com/item?id=45379452) are from 2024 - 2025, so already old and before agents really took off. However, your point about meetings and agreements and documenting is much more germane. My theory is that the largest productivity gains -- and subsequent labor displacement -- will come from reducing coordination overhead: https://news.ycombinator.com/item?id=48040999 https://news.ycombinator.com/item?id=48040999
• 4rf 4mo ago
  What a load of nonsense lmao. Pls stop posting you are creating noise.
• lubujackson 4mo ago
  This assumes the hand-wavvy "production" of knowledge workers translates directly and equally into money. Making a CEO 5% more productive might mean a billion dollars or it might mean nothing. Making a developer 5% more productive might mean the app gets finished faster or some more tickets are closed, but certainly direct monetary relationship between "work done" and "money made", especially if the knowledge work being optimized is, across the board, more of the busy work ("known-knowns") and not the "what should our new product line be" that tends to move the needle in spurts. If you are a software contractor, yes more productivity turns directly into money. But it is the same for all other contractors, so there is no gain there either. This is really a structural transformation that crosses industry boundaries, not unlike when we all got on the internet. All I know from living through that is certain changes are obvious even if they take a decade (there will be more AI and more deeply integrated in our lives) but most of the secondary effects are unknowable. If living through the dot com era taught me anything is that transformative tech routes around walled gardens (i.e. AOL/Prodigy) which is bad news for Anthropic/OpenAI. The wild west that comes after is a window of opportunity for founders but investors will overcommit early (like now) and undercommit when the dust is settled (post bubble).
  • troglodytetrain 3mo ago
    yeah, my personal work experience has taught me that extra productivity is actual really just a problem for many companies. You do more work now I have to too. We don't have to work because we have special relationships with or as gatekeepers ensuring we receive regular income from government, other corps, etc. Look at what happened to twitter. So many companies aren't 'productive', they are simply parked somewhere where they can charge a toll, and then they pretend legitimacy.
• troglodytetrain 3mo ago
  So, maybe a dumb question, but do we have any real reason to believe that productivity at any level is actually associated with the actual underlying profit and earnings of any of the companies that are heavily 'knowledge work' focused, like big tech? Sure, for a factory, or a farm it makes sense. But for tech I get the impression that valuation has been fundamentally unmoored from actual production for decades already. Its less about 'productivity' and more about vibes.