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AI is going to be a highly-competitive, extremely capital-intensive commodity market that ends up in a race to the bottom competing on cost and efficiency of de

by avalys 9mo ago

AI is going to be a highly-competitive, extremely capital-intensive commodity market that ends up in a race to the bottom competing on cost and efficiency of delivering models that have all reached the same asymptotic performance in the sense of intelligence, reasoning, etc. The simple evidence for this is that everyone who has invested the same resources in AI has produced roughly the same result. OpenAI, Anthropic, Google, Meta, Deepseek, etc. There's no evidence of a technological moat or a competitive advantage in any of these companies. The conclusion? AI is a world-changing technology, just like the railroads were, and it is going to soon explode in a huge bubble - just like the railroads did. That doesn't mean AI is going to go away, or that it won't change the world - railroads are still here and they did change the world - but from a venture investment perspective, get ready for a massive downturn.

ares623 9mo ago
Just in time for a Government guaranteed backstop.
bee_rider 9mo ago
Massive upfront costs and second place is just first loser. It’s like building fabs but your product is infinitely copyable. Seems pretty rough.
- gerdesj 9mo ago
  What exactly is "second" place? No-one really knows what first place looks like. Everyone is certain that it will cost an arm, a leg and most of your organs. For me, I think that, the possible winners will be close to fully funded up front and the losers will be trying to turn debt into profit and fail. The rest of us self hoster types are hoping for a massive glut of GPUs and RAM to be dumped in a global fire sale. We are patient and have all those free offerings to play with for now to keep us going and even the subs are so far somewhat reasonable but we will flee in droves as soon as you try to ratchet up the price. It's a bit unfortunate but we are waiting for a lot of large meme companies to die. Soz!
  - raw_anon_1111 9mo ago
    First place looks a lot like Google…
  - vkou 9mo ago
    You and the other hobbyists aren't what's driving valuations. Enterprise subscriptions are.
    - ljlolel 9mo ago
      OpenAI is 80% consumer subs
      - vkou 9mo ago
        And do those subs justify their valuation? They don't, the only thing that can justify it is if they get themselves into every business workflow. That's what the investors are counting on.
fooblaster 9mo ago
There is a pretty big moat for Google: extreme amounts of video data on their existing services and absolutely no dependence on Nvidia and it's 90% margin.
- fooblaster 9mo ago
  And yes, all their competitors are making custom chips. Google is on TPU v7. absolutely nobody is going to get this right on the first try among their competitors - Google didn't.
  - CharlieDigital 9mo ago
    Bigger problem for late starts now is that it will be hard to match the performance and cost of Google/Nvidia. It's an investment that had to have started years ago to be competitive now.
- nateb2022 9mo ago
  I have yet to be convinced the broader population has an appetite for AI produced cinematography or videos. Independence from Nvidia is no more of a liability than dependence on electricity rates; it's not as if it's in Nvidia's interest to see one of its large customers fail. And pretty much any of the other Mag7 companies are capable of developing in-house TPUs + are already independently profitable, so Google isn't alone here.
  - fooblaster 9mo ago
    If you think they are going to catch up with Google's software and hardware ecosystem on their first chip, you may be underestimating how hard this is. Google is on TPU v7. meta has already tried with MTIA v1 and v2. those haven't been deployed at scale for inference.
    - nateb2022 9mo ago
      I don't think many of them will want to, though. I think as long as Nvidia/AMD/other hardware providers offer inference hardware at prices decent enough to not justify building a chip in-house, most companies won't. Some of them will probably experiment, although that will look more like a small team of researchers + a moderate budget rather than a burn-the-ships we're going to use only our own hardware approach.
nateb2022 9mo ago
> AI is going to be a highly-competitive, extremely capital-intensive commodity market It already is. In terms of competition, I don't think we've seen any groundbreaking new research or architecture since the introduction of inference time compute ("thinking") in late 2024/early 2025 circa GPT-o4. The majority of the cost/innovation now is training this 1-2 year old technology on increasingly large amounts of content, and developing more hardware capable of running these larger models at more scale. I think it's fair to say the majority of capital is now being dumped into hardware, whether that's HBM and research related to that, or increasingly powerful GPUs and TPUs. But these components are applicable to a lot of other places other than AI, and I think we'll probably stumble across some manufacturing techniques or physics discoveries that will have a positive impact on other industries. > that ends up in a race to the bottom competing on cost and efficiency of delivering One could say that the introduction of the personal computer became a "race to the bottom." But it was only the start of the dot-com bubble era, a bubble that brought about a lot of beneficial market expansion. > models that have all reached the same asymptotic performance in the sense of intelligence, reasoning, etc. I definitely agree with the asymptotic performance. But I think the more exciting fact is that we can probably expect LLMs to get a LOT cheaper in the next few years as the current investments in hardware begin to pay off, and I think it's safe to assume that in 5-10 years, most entry-level laptops will be able to manage a local 30B sized model while still being capable of multitasking. As it gets cheaper, more applications for it become more practical. --- Regarding OpenAI, I think it definitely stands in a somewhat precarious spot, since basically the majority of its valuation is justified by nothing less than expectations of future profit. Unlike Google, which was profitable before the introduction of Gemini, AI startups need to establish profitability still. I think although initial expectations were for B2C models for these AI companies, most of the ones that survive will do so by pivoting to a B2B structure. I think it's fair to say that most businesses are more inclined to spend money chasing AI than individuals, and that'll lead to an increase in AI consulting type firms.
- mark_l_watson 9mo ago
  > in 5-10 years, most entry-level laptops will be able to manage a local 30B sized model I suspect most of the excitement and value will be on edge devices. Models sized 1.7B to 30B have improved incredibly in capability in just the last few months and are unrecognizably better than a year ago. With improved science, new efficiency hacks, and new ideas, I can’t even imagine what a 30B model with effective tooling available could do in a personal device in two years time.
phyzix5761 9mo ago
I, personally, use chatGPT for search more than I do Google these days. It, more often than not, gives me more exact results based on what I'm looking for and it produces links I can visit to get more information. I think this is where their competitive advantage lies if they can figure out how to monetize that.
- aprilthird2021 9mo ago
  I'm genuinely curious. Why do you do this instead of Google Searches which also have an AI Overview / answer at the top, that's basically exactly the same as putting your search query into a chat bot, but it ALSO has all the links from a regular Google search so you can quickly corroborate the info even using sources not from the original AI result (so you also see discordant sources from what the AI answer had)?
  - thom 9mo ago
    The regular google search AI doesn’t do thinky thinky mode. For most buying decisions these days I ask ChatGPT to go off and search and think for a while given certain constraints, while taking particular note of Reddit and YouTube comments, and come back with some recommendations. I’ve been delighted with the results.
    - Marsymars 9mo ago
      I wouldn’t be surprised if ChatGPT was Pareto optimal for buying decisions… but I suspect there are a whole pile of Pareto optimal ways to make buying decisions, including “buy one of the Wirecutter picks” or “buy whatever Costco is selling”.
      - thom 9mo ago
        Even in the case where you have a good shortlist of items, the ability to then ask follow up questions in a conversational format is very useful for me. Anyway, just explaining why one might use ChatGPT for this rather than the Google search box, obviously your mileage is welcome to vary.
gerdesj 9mo ago
"AI is going to be a highly-competitive" - In what way? It is not a railroad and the railroads did not explode in a bubble (OK a few early engines did explode but that is engineering). I think LLM driven investments in massive DCs is ill advised.
- fcantournet 9mo ago
  Yes they did, at least twice in the 19th century. It was the largest financial crisis before 1929
  - johnnyanmac 9mo ago
    It did. I question the issue of "what problem am I trying to solve" with AI, though. Transportation across a huge swath of land had a clear problem space, and trains offered a very clear solution; created dedicated railing and you can transport 100x the resources at 10x the speed of a horseman (and I'm probably underselling these gains). In times where trekking across a continent took months, the efficiencies in communication and supply lines are immediately clear. AI feels like a solution looking for a problem. Especially with 90% of consumer facing products. Were people asking for better chatbots, or to quickly deepfake some video scene? I think the bubble popping will re-reveal some incredible backend tools in tech, medical, and (eventually) robotics. But I don't think this is otherwise solving the problems they marketed on.
    - heavyset_go 9mo ago
      > AI feels like a solution looking for a problem. The problem is increasing profits by replacing paid labor with something "good enough".
      - MangoToupe 9mo ago
        This is a use case that hasn't yet been proven out, though. "Good enough" for an executive may not be "good enough" to keep the company solvent, and there's no shortage of private equity morons who have no understanding of their own assets.
variadix 9mo ago
This will remain the case until we have another transformer-level leap in ML technology. I don’t expect such an advancement to be openly published when it is discovered.
energy123 9mo ago
> There's no evidence of a technological moat or a competitive advantage in any of these companies. I disagree based on personal experience. OpenAI is a step above in usefulness. Codex and GPT 5.2 Pro have no peers right now. I'm happy to pay them $200/month. I don't use my Google Pro subscription much. Gemini 3.0 Pro spends 1/10th of the time thinking compared to GPT 5.2 Thinking and outputs a worse answer or ignores my prompt. Similar story with Deepseek. The public benchmarks tell a different story which is where I believe the sentiment online comes from, but I am going to trust my experience, because my experience can't be benchmaxxed.
- harrall 9mo ago
  I use both and ChatGPT will absolutely glaze me. I will intentionally say some BS and ChatGPT will say “you’re so right.” It will hilariously try to make me feel good. But Gemini will put me in my place. Sometimes I ask my question to Gemini because I don’t trust ChatGPT’s affirmations. Truthfully I just use both.
  - gridspy 9mo ago
    I told ChatGPT via my settings that I often make mistakes and to call out my assumptions. So now it 1. Glazes me 2. Lists a variety of assumptions (some can be useful / interesting) Answers the question At least this way I don't spend a day pursuing an idea the wrong way because ChatGPT never pointed out something obvious.
    - nubg 9mo ago
      Care to share the system prompt?
- wild_egg 9mo ago
  I still find it so fascinating how experiences with these models are so varied. I find codex & 5.2 Pro next to useless and nothing holds a candle to Opus 4.5 in terms of utility or quality. There's probably something in how varied human brains and thought processes are. You and I likely think through problems in some fundamentally different way that leads to us favouring different models that more closely align with ourselves. No one seems to ever talk about that though and instead we get these black and white statements about how our personally preferred model is the only obvious choice and company XYZ is clearly superior to all the competition.
adventured 9mo ago
Your premise is wrong in a very important way. The cost of entry is far beyond extraordinary. You're acting like anybody can gain entry, when the exact opposite is the case. The door is closing right now. Just try to compete with OpenAI, let's see you calculate the price of attempting it. Scale it to 300, 500, 800 million users. Why aren't there a dozen more Anthropics, given the valuation in question (and potential IPO)? Because it'll cost you tens of billions of dollars just to try to keep up. Nobody will give you that money. You can't get the GPUs, you can't get the engineers, you can't get the dollars, you can't build the datacenters. Hell, you can't even get the RAM these days, nor can you afford it. Google & Co are capturing the market and will monetize it with advertising. They will generate trillions of dollars in revenue over the coming 10-15 years by doing so. The barrier to entry is the same one that exists in search: it'll cost you well over one hundred billion dollars to try to be in the game at the level that Gemini will be at circa 2026-2027, for just five years. Please, inform me of where you plan to get that one hundred billion dollars just to try to keep up. Even Anthropic is going to struggle to stay in the competition when the music (funding bubble) stops. There are maybe a dozen or so companies in existence that can realistically try to compete with the likes of Gemini or GPT.
- zozbot234 9mo ago
  > Just try to compete with OpenAI, let's see you calculate the price of attempting it. Scale it to 300, 500, 800 million users. Apparently the DeepSeek folks managed that feat. Even with the high initial barriers to entry you're talking about, there will always be ways to compete by specializing in some underserved niche and growing from there. Competition seems to be alive and well.
  - thom 9mo ago
    DeepSeek certainly managed that on the training side but in terms of inference, the actual product was unusably slow and unreliable at launch and for several months after. I have not bothered revisiting it.
    - snuxoll 9mo ago
johnnyanmac 9mo ago
>That doesn't mean AI is going to go away, or that it won't change the world - railroads are still here and they did change the world - but from a venture investment perspective, get ready for a massive downturn. I don't know why people always imply that "the bubble will burst" means that "literally all Ai will die out and nothing will remain that is of use". The Dotcom bubble didn't kill the internet. But it was a bubble and it burst nonetheless, with ramifications that spanned decades. All it really means when you believe a bubble will pop is "this asset is over-valued and it will soon, rapidly deflate in value to something more sustainable" . And that's a good thing long term, despite the rampant destruction such a crash will cause for the next few years.
- mr_toad 9mo ago
  But some people do believe that AI is all hype and it will all go away. It’s hard to find two people who actually mean the same thing when they talk about a “bubble” right now.
- latchup 9mo ago
  I don't think anyone seriously believes AI will disappear without a trace. At the very least, LLMs will remain as the state of the art in high-level language processing (editing, translation, chat interfaces, etc.) The real problem is the massive over-promises of transforming every industry, replacing most human labor, and eventually reaching super-intelligence based on current models. I hope we can agree that these are all wholly unattainable, even from a purely technological perspective. However, we are investing as if there were no tomorrow without these outcomes, building massive data-centers filled with "GPUs" that, contrary to investor copium, will quickly become obsolete and are increasingly useless for general-purpose datacenter applications (Blackwell Ultra has NO FP64 hardware, for crying out loud...). We can agree that the bubble deflating, one way or another, is the best outcome long term. That said, the longer we fuel these delusions, the worse the fallout will be when it does. And what I fear is that one day, a bubble (perhaps this one, perhaps another) will grow so large that it wipes out globalized free-market trade as we know it.
  - zozbot234 9mo ago
adamnemecek 9mo ago
AI is capital intensive because autodiff kinda sucks.
api 9mo ago
If performance indeed asymptotes, and if we are not at the end of silicon scaling or decreasing cost of compute, then it will eventually be possible to run the very best models at home on reasonably priced hardware. Eventually the curves cross. Eventually the computer you can get for, say, $2000, becomes able to run the best models in existence. The only way this doesn’t happen is if models do not asymptote or if computers stop getting cheaper per unit compute and storage. This wouldn’t mean everyone would actually do this. Only sophisticated or privacy conscious people would. But what it would mean is that AI is cheap and commodity and there is no moat in just making or running models or in owning the best infrastructure for them.
guluarte 9mo ago
Also that open source models are just months behind
dheera 9mo ago
People seem to have the assumption that OpenAI and Anthropic dying would be synonymous with AI dying, and that's not the case. OpenAI and Anthropic spent a lot of capital on important research, and if the shareholders and equity markets cannot learn to value and respect that and instead let these companies die, new companies will be formed with the same tech, possibly by the same general group of people, thrive, and conveniently leave out the said shareholders. Google was built on the shoulders of a lot of infrastructure tech developed by former search engine giants. Unfortunately the equity markets decided to devalue those giants instead of applaud them for their contributions to society.
- tootie 9mo ago
  Isn't it really the other way around? Not to say OpenAI and Anthropic haven't done important work, but the genesis of this entire market was paper on attention that came out of Google. We have the private messages inside OpenAI saying they needed to get to market ASAP or Google would kill them.
- raw_anon_1111 9mo ago
  You weren’t around pre Google were you? The only thing Google learned from other search engines is what not to do - like rank based on the number of times a keyword appeared and not to use expensive bespoked servers
  - dheera 9mo ago
    I was around pre-Google. Ranking was Google's 5% contribution to it. They stood on the shoulders of people who invented physical server and datacenter infrastructure, Unix/Linux, file systems, databases, error correction, distributed computing, the entire internet infrastructure, modern Ethernet, all kinds of stuff.
    - raw_anon_1111 9mo ago
      And none of that had to do with learning from other search engines…
deleted 9mo ago
[deleted]
Davidzheng 9mo ago
Um meta didn't achieve the same results yet. And does it matter if they can all achieve the same results if they all manage high enough payoffs? I think subscription based income is only the beginning. Next stage is AI-based subcompanies encroaching on other industries (e.g. deepmind's drug company)
jfrbfbreudh 9mo ago
Google’s moat: Try “@gmail” in Gemini Google’s surface area to apply AI is larger than any other company’s. And they have arguably the best multimodal model and indisputably the best flash model?
- avalys 9mo ago
  If the “moat” is not AI technology itself but merely sufficient other lines of business to deploy it well, then that’s further evidence that venture investments in AI startups will yield very poor returns.
  - tjwebbnorfolk 9mo ago
    It's funny that a decade ago the exit strategy of many of these startups would have been to get acquired by MSFT / META / GOOG. Now, the regulators have made a lot of these acquisitions effectively impossible for antitrust reasons. Is it better for society for promising startups to die on the open market, or get acquired by a monopoly? The third option -- taking down the established players -- appears increasingly unlikely.
    - maeln 9mo ago
      > Now, the regulators have made a lot of these acquisitions effectively impossible for antitrust reasons. Is there any evidence that this is the case ? For very big merger (like nvdia and Arm tried) sure, but I can't think of a single time regulator stop a big player from buying a start up.
      - tjwebbnorfolk 9mo ago
        I'm sure you realize you're asking me to prove a negative? I don't have the ability to prove to you that something didn't happen or why. What I know is that a lot of deals aren't even being considered that once were, and antitrust is a huge factor in that consideration.
    - shimman 9mo ago
xbmcuser 9mo ago
This is why I think China will win the AI race. As once it becomes a commodity no other country is capable of bringing down manufacturing and energy costs the way China is today. I am also rooting for them to get on parity with node size for chips for the same reason as they can crash the prices PC hardware.
BenFranklin100 9mo ago
I’m waiting to get an RTX 5090 on the cheap.
- 2OEH8eoCRo0 9mo ago
  A penny saved is a penny earned
578_Observer 9mo ago
The "Railway Bubble" analogy is spot on. As a loan officer in Japan who remembers the 1989 bubble, I see the same pattern. In the traditional "Shinise" world I work with, Cash is Oxygen. You hoard it to survive the inevitable crash. For OpenAI, Cash is Rocket Fuel. They are burning it all to reach "escape velocity" (AGI) before gravity kicks in. In 1989, we also bet that land prices would outrun gravity forever. But usually, Physics (and Debt) wins in the end. When the railway bubble bursts, only those with "Oxygen" will survive.
- ManuelKiessling 9mo ago
  I‘m aware this means leaving the original topic of this thread, but would you mind giving us a rundown of this whole Japan 1989 thing? I would love to read a first-person account.
  - 578_Observer 9mo ago
    I am honored to receive a question from a fellow "Craftsman" (I assume from your name). To be honest, in 1989, I was just a child. I didn't drink the champagne. But as a banker today, I am the one cleaning up the broken glass. So I can tell you about 1989 from the perspective of a "Survivor's Loan Officer." I see two realities every day. One is the "Zombie" companies. Many SMEs here still list Golf Club Memberships on their books at 1989 prices. Today, they are worth maybe 1/20th of that value. Technically, these companies are insolvent, but they keep the "Ghost of 1989" on the books, hoping to one day write it off as a tax loss. It is a lie that has lasted 30 years. But the real estate is even worse. I often visit apartment buildings built during the bubble. They are decaying, and tenants have fled to newer, modern buildings. The owner cannot sell the land because demolition costs hundreds of thousands of dollars—more than the land is worth. The owner is now 70 years old. His family has drifted apart. He lives alone in one of the empty units, acting as the caretaker of his own ruin. The bubble isn't just a graph in a history book. It is an old man trapped in a concrete box he built with "easy money." That is why I fear the "Cash Burn" of AI. When the fuel runs out, the wreckage doesn't just disappear. Someone has to live in it.
    - 9mo ago
parentheses 9mo ago
This is different because now the cats out of the bag: AI is big money! I don't expect AGI or Super intelligence to take that long but I do think it'll happen in private labs now. There's an AI business model (pay per token) that folks can use also.
- oblio 9mo ago
  > don't expect AGI or Super intelligence to take that long I appreciate the optimism for what would be the biggest achievement (and possibly disaster) in human history. I wish other technologies like curing cancer, Alzheimer's, solving world hunger and peace would have similar timelines.
  - barrenko 9mo ago
    We are making decent strides on the first two, the latter two are like wanting cats to stop scratching. What's the point of being a cat than?
__MatrixMan__ 9mo ago
I think we'll find that that asymptote only holds for cases where the end user is not really an active participant in creating the next model: - take your data - make a model - sell it back to you Eventually all of the available data will have been squeezed for all it's worth the only way to differentiate oneself as an AI company will be to propel your users to new heights so that there's new stuff to learn. That growth will be slower, but I think it'll bear more meaningful fruit. I'm not sure if today's investors are patient enough to see us through to that phase in any kind of a controlled manner, so I expect a bumpy ride in the interim.
- conartist6 9mo ago
  Yeah except that models don't propel communities towards new heights. They drive towards the averages. They take from the best to give to the worst, so that as much value is destroyed as created. There's no virtuous cycle there...
  - __MatrixMan__ 9mo ago
    Is that constraint fundamental to what they are? Or are they just reflecting the behavior of markets when there's low hanging fruit around? When you look at models that were built for a specific purpose, closely intertwined with experts who care about that purpose, they absolutely propel communities to new heights. Consider the impact of alphafold, it won a Nobel prize, proteomics is forever changed. The issue is that that's not currently the business model that's aimed at most of us. We have to have a race to the bottom first. We can have nice things later, if we're lucky, once a certain sort of investor goes broke and a different sort takes the helm. It's stupid, but its a stupidity that predates AI by a long shot.
    - conartist6 9mo ago
      Experts making a specialized model isn't an example of an AI contributing value to society. All the value a model can offer comes from one of exactly two places: the person building the model, or the people the model trained on. We know that the model training on the model training on the model leads to model collapse...
hakfoo 9mo ago
The railroads provided something of enduring value. They did something materially better than previous competitors (horsecarts and canals) could. Even today, nothing beats freight rail for efficient, cheap modest-speed movement of goods. If we consider "AI" to be the current LLM and ImageGen bubble, I'm not sure we can say that. We were all wowed that we could write a brief prompt and get 5,000 lines of React code or an anatomically questionable deepfake of Legally Distinct Chris Hemsworth dancing in a tutu. But once we got past the initial wow, we had to look at the finished product and it's usually not that great. AI as a research tool will spit back complete garbage with a straight face. AI images/video require a lot of manual cleanup to hold up to anything but the most transient scrutiny. AI text has such distinct tones that it's become a joke. AI code isn't better than good human-developed code and is prone to its own unique fault patterns. It can deliver a lot of mediocrity in a hurry, but how much of that do we really need? I'd hope some of the post-bubble reckoning comes in the form of "if we don't have AI to do it (vendor failures or pricing-to-actual-cost makes it unaffordable), did we really need it in the first place?" I don't need 25 chatbots summarizing things I already read or pleading to "help with my writing" when I know what I want to say.
- cco 9mo ago
  I was really hoping, and with a different administration I think there was a real shot, for a huge influx of cash into clean energy infrastructure. Imagine a trillion dollars (frankly it might be more, we'll see) shoved into clean energy generation and huge upgrades to our distribution. With a bubble burst all we'd be left with is a modern grid and so much clean energy we could accelerate our move off fossil fuels. Plus a lot of extra compute, that's less clear of a long term value. Alas.
- choeger 9mo ago
  You're absolutely correct! ( ;) ) The issue is that generation of error-prone content is indeed not very valuable. It can be useful in software engineering, but I'd put it way below the infamous 10x increase in productivity. Summarizing stuff is probably useful, too, but its usefulness depends on you sitting between many different communication channels and being constantly swamped in input. (Is that why CEOs love it?) Generally, LLMs are great translators with a (very) lossly compressed knowledge DB attached. I think they're great user Interfaces, and they can help streamline buerocracy (instead of getting rid of it) but they will not help getting down the cost of production of tangible items. They won't solve housing. My best bet is in medicine. Here, all the areas that LLMs excell at meet. A slightly distopian future cuts the expensive personal doctors and replaces them with (few) nurses and many devices and medicine controlled by a medical agent.
pier25 9mo ago
Did railroads change the world though? They only lasted a couple of decades as the main transportation method. I'd say the internal combustion engine was a lot more transformative.
- xhevahir 9mo ago
  Pretty much every major historical trend of Western societies in the second half of the eighteenth century, from the development of the modern corporation to the advent of total war, was intimately tied to railroad transportation.
- Marsymars 9mo ago
  Transportation of people, yeah, but it still carries a majority of inter-city freight in North America.
- anshumankmr 9mo ago
  Umm yes? The metro even if not a big deal in the states is like a small but quiet way it has changed public transport, plus moving freight, plus people over large distances, plus the bullet train that mixed luxury, speed and efficiency onto trains, all of these are quietly disruptive transformations, that I think we all take for granted.
- oblio 9mo ago
  Railroads built America and won multiple large wars.
- tliltocatl 9mo ago
  Besides from he fact the freight is still universally carried by the rail when possible, railroads changed the world just like the vacuum valves did. If not for them nobody would invest in developing tire transport or transistors.
jotras 9mo ago
Something nobody's talking about: OpenAI's losses might actually be attractive to certain investors from a tax perspective. Microsoft and other corporate investors can potentially use their share of OpenAI's operating losses to offset their own taxable income through partnership tax treatment. It's basically a tax-advantaged way to fund R&D - you get the loss deductions now while retaining upside optionality later. This is why the "cash burn = value destruction" framing misses the mark. For the right investor base, $10B in annual losses at OpenAI could be worth $2-3B in tax shields (depending on their bracket and how the structure works). That completely changes the return calculation. The real question isn't "can OpenAI justify its valuation" but rather "what's the blended tax rate of its investor base?" If you're sitting on a pile of profitable cloud revenue like Microsoft, suddenly OpenAI's burn rate starts looking like a pretty efficient way to minimize your tax bill while getting a free option on the AI leader. This also explains why big tech is so eager to invest at nosebleed valuations. They're not just betting on AI upside, they're getting immediate tax benefits that de-risk the whole thing.
- rebuilder 9mo ago
  It’s hardly a free option, by your numbers it’d be a 20-30% discount.
  - thrwaway55 9mo ago
    Sure but if there's no moat would you rather pay 100% or 80% until the credits run out? You reap the 100% spend in the meantime. Not everyone even has the no moat discount.
- ludicrousdispla 9mo ago
  >> For the right investor base, $10B in annual losses at OpenAI could be worth $2-3B in tax shields So just a loss for governments, or in other words, socializing the losses.
  - booi 9mo ago
    Hi, I'm here to hold the bag?
zeofig 9mo ago
I still don't understand how it's world-changing apart from considerably degrading the internet. It's laughable to compare it to railroads.
- kolinko 9mo ago
  Did you try asking chatgpt to explain?
- tliltocatl 9mo ago
  Translation is big thing, maybe not the same scale as railroads, but still important. The rest is of dubious economic utility (as in you can do it with LLM easier than without, but if you think a little you could just as well not do it at all without losing anything). On the other hand, disrupting signalling will have pretty long-lasting consequences. People used to assume that a long formal-sounding text is a signal of seriousness, certainly so if it's personally addressed. Now it's just a sign of sloppiness. School essays are probably dead as a genre (good riddance). Hell, maybe even some edgy censorable language will enter mainstream as a definite proof of non-LLMness - and stay.
- tim333 9mo ago
  When it gets a bit better two robots can make four robots and so on to infinity.
matwood 9mo ago
Or the airlines. Airlines have created a huge amount of economic value that has mostly been captured by other entities.
Chyzwar 9mo ago
Anthropic is building moat around theirs models with claude code, Agent SDK, containers, programmatic tool use, tool search, skills and more. Once you fully integrate you will not switch. Also being capital intensive is a form of moat. I think we will end up with market similar to cloud computing. Few big players with great margins creating cartel.
- mhuffman 9mo ago
  >Anthropic is building moat around theirs models with claude code, Agent SDK, containers, programmatic tool use, tool search, skills and more. I think this is something the other big players could replicate rapidly, even simulating the exact UI, interactions, importing/exporting existing items, etc. that people are used to with claude products. I don't think this is that big of a moat in the long run. Other big players just seem to be carving up the landscape and see where they can can fit in for now, but once resource rich eyes focus on them, Anthropic's "moat" will disappear.
- iLoveOncall 9mo ago
  A GPT wrapper isn't a moat.
  - bogdan 9mo ago
    Most things are wrappers around RDBMSs.
    - blinding-streak 9mo ago
      Most true and interesting comment I've read on HN in a while!
  - visarga 9mo ago
    A generic wrapper is not a moat, but the context is. Both the LLM provider and the wrapper provider depend on local context for task activities. The value flows to the context, the LLMs and wrappers are commodities. Who sets the prompts stands to benefit, not who serves AI services.
throw310822 9mo ago
> AI is a world-changing technology, just like the railroads were This comparison keeps popping up, and I think it's misleading. The pace of technology uptake is completely different from that of railroads: the user base of ChatGPT alone went from 0 to 200 million in nine months, and it's now- after just three years- around 900 million users on a weekly basis. Even if you think that railroads and AI are equally impactful (I don't, I think AI will be far more impactful) the rapidity with which investments can turn into revenue and profit makes the situation entirely different from an investor's point of view.
- steve1977 9mo ago
  Railroads enabled people and goods to move from one place to another much easier and faster. AI enables people to... produce even more useless slop than before?
  - throw310822 9mo ago
    At this point I'm taking the word "slop" as a sign meaning "I really didn't think this through and I'm just autocompleting based on a gut feeling and the first word that comes to mind".
    - steve1977 9mo ago
      That's an easy way out, isn't it?
      - mikkupikku 9mo ago
        Using thought terminating clichés in general is, and that can include "slop".
        steve1977 9mo ago
        It wasn't meant to be thought terminating. If anything, it was a bit provocative.
nr378 9mo ago
> The simple evidence for this is that everyone who has invested the same resources in AI has produced roughly the same result. I think this conflates together a lot of different types of AI investment - the application layer vs the model layer vs the cloud layer vs the chip layer. It's entirely possible that it's hard to generate an economic profit at the model layer, but that doesn't mean that there can't be great returns from the other layers (and a lot of VC money is focused on the application layer).
- londons_explore 9mo ago
  Whilst those other layers are useful, none of them are particularly hard to build or rebuild when you have many millions of dollars on hand. One doesn't need tens of billions for them.
  - tucnak 9mo ago
    Yeah, because making good chips (TPU) and compilers (XLA) is notoriously easy, right?
    - londons_explore 9mo ago
      All of that is below the model
retinaros 9mo ago
for me its clear OpenAI and Anthropic have a lead. I dont buy Gemini 3 being good. it isnt. whatever the benchmark said. same for meta and deepseek.
Bombthecat 9mo ago
Eh, I wouldn't be so sure, chips with brain matter and or light are on its way and or quantum chips, one of those or even a combination will give AI a gigantic boost in performance. Finally replacing a lot more humans and whoever implements it first will rule the world.
- nineteen999 9mo ago
  You seem to have forgotten that the ruling class requires tax payers to fund their incomes. If we're all out of work, there's nobody to buy their products and keep them rich.
  - CuriousSkeptic 9mo ago
    Not sure this equation works out. If demand for labor goes towards zero it really means there is no demand. In other words, when AI and robots fulfil every desire of their owners there really is no need for “tax payers”
    - nineteen999 9mo ago
      If you really think 8 billion people are going to not tear the arms and legs off their overlords and their robot minions before that you're completely daft.
- oblio 9mo ago
  > chips with brain matter and or light The... what now?
  - Bombthecat 9mo ago
    https://www.technologyreview.com/2023/12/11/1084926/human-brain-cells-chip-organoid-speech-recognition https://www.technologyreview.com/2023/12/11/1084926/human-br... They are getting better, faster etc etc. And I get down voted again for the truth people don't want to hear lol
cma 9mo ago
Deepseek has invested the same amount as OpenAI?
sunchit 9mo ago
Have you thought about what happens if we get a new improvement in model architecture like transformers that grows the compute needs even further
epolanski 9mo ago
Like railroads, internet, electricity, aviation or car industries before: they've all been indeed the future, and they all peaked (in relative terms), at the very early stages of these industries future. And among them the overwhelming majority of companies in the sectors died. Out of the 2000ish car-related companies that existed in 1925 only 3 survived to today. And none of those 3 ended up a particularly good long term investment.
trgn 9mo ago
very few software has commoditized, doubt it will be the fate of AI tech stack.
- o_nate 9mo ago
  Perhaps it would be useful to define what we mean by "commoditization" in terms of software. I would say a software product that is not commoditized is one where the brand still can command a premium, which in the world of software, generally means people are willing to pay non-zero dollars for it. Once software is commoditized it generally becomes free or ad-supported or is bundled with another non-software product or service. By this standard I would say there are very few non-commoditized consumer software products. People pay for services that are delivered via software (e.g. Spotify, Netflix) but in this case the software is just the delivery mechanism, not the product. So perhaps one viable path for chatbots to avoid commoditization would be to license exclusive content, but in this scenario the AI tech itself becomes a delivery mechanism, albeit a sophisticated one. Otherwise it seems selling ads is the only viable strategy, and precedents show that the economics of that only work when there is a near monopoly (e.g. Meta or Google). So it seems unlikely that a lot of the current AI companies will survive.
louiskottmann 9mo ago
This is so obviously right. I may add that investors are mostly US-centric, and so will the bubble-bursting chaos that ensues.
jklinger410 9mo ago
> The simple evidence for this is that everyone who has invested the same resources in AI has produced roughly the same result. OpenAI, Anthropic, Google, Meta, Deepseek, etc. There's no evidence of a technological moat or a competitive advantage in any of these companies. I think this is analysis is too surface level. We are seeing Google Gemini pull away in terms of image generation, and their access to billions of organic user images gives them a huge moat. And in terms of training data, Google also has a huge advantage there. The moat is the training data, capital investment, and simply having a better AI that others cannot recreate. I don't see how Google doesn't win this thing.
kkukshtel 9mo ago
I like to tell people that all the AI stuff happening right now is capitalism actually working as intended for once. People competing on features and price where we arent yet in a monopoly/duopoly situation yet. Will it eventually go rotten? Probably — but it's nice that right now for the first time in a while it feels like companies are actually competing for my dollar.
- the_overseer 9mo ago
  Aaahh the beautiful free market where the energy prices keep increasing and if it all fails they will be saved by the government that they bribed before. Don't forget the tax subsidies. AKA your money. Pure honest capitalism....
heresie-dabord 9mo ago
> AI is a world-changing technology As stated in TFA, this simply has not been demonstrated , nor are there any artifacts of proof. It's reasonable to suspect that there is no special apparatus behind the curtain in this Oz. From TFA: "One vc [sic] says discussion of cash burn is taboo at the firm, even though leaked figures suggest it will incinerate more than $115bn by 2030."
runeks 9mo ago
> The conclusion? AI is a world-changing technology, just like the railroads were, and it is going to soon explode in a huge bubble - just like the railroads did. Why "soon"? All your arguments may be correct, but none of them imply when the pending implosion will happen.
scrollop 9mo ago
Also what will happen if/when a different lab (or a current lab) develop a new architecture that can actually achieve AGI? The other, highly invested, companies (if openai and anthropic) may be in for a free fall. You never wake to be left in the wake of "the next big thing".
b3nji 9mo ago
I thought the same. Have you thought that there was a massive physical infrastructure left behind by the original railroad builders, all compatible with future vehicles? Other companies were able to buy the railroads for low prices and use. Large Language Models change their power consumption requirements monthly, the hardware required to run them is replaced at a rapid rate too. If it were to stop tomorrow, what would you be left with? Out of date hardware, massively wasted power, and a gigantic hole in your wallet. You could argue you have the blueprints for LLM building, known solutions, and it could all be rebuilt. The thing is, would you want to rebuild, and invest so much again for arguably little actual, tangible output? There isn't anything you can reuse, like others that came after could reuse the railroads.
mettamage 9mo ago
> The simple evidence for this is that everyone who has invested the same resources in AI has produced roughly the same result. OpenAI, Anthropic, Google, Meta, Deepseek, etc. There's no evidence of a technological moat or a competitive advantage in any of these companies. Practically, what I'm finding is that whenever I ask Claude to search stuff on Reddit, it can't but Gemini can. So I think the practical advantages are where certain organizations have unfair data advantages. What I found out is that LLMs work a lot better when they have quality data.

by avalys 9mo ago

ares623 9mo ago

Just in time for a Government guaranteed backstop.

bee_rider 9mo ago

Massive upfront costs and second place is just first loser. It’s like building fabs but your product is infinitely copyable. Seems pretty rough.

gerdesj 9mo ago
What exactly is "second" place? No-one really knows what first place looks like. Everyone is certain that it will cost an arm, a leg and most of your organs. For me, I think that, the possible winners will be close to fully funded up front and the losers will be trying to turn debt into profit and fail. The rest of us self hoster types are hoping for a massive glut of GPUs and RAM to be dumped in a global fire sale. We are patient and have all those free offerings to play with for now to keep us going and even the subs are so far somewhat reasonable but we will flee in droves as soon as you try to ratchet up the price. It's a bit unfortunate but we are waiting for a lot of large meme companies to die. Soz!
- raw_anon_1111 9mo ago
  First place looks a lot like Google…
- vkou 9mo ago
  You and the other hobbyists aren't what's driving valuations. Enterprise subscriptions are.
  - ljlolel 9mo ago
    OpenAI is 80% consumer subs
    - vkou 9mo ago
      And do those subs justify their valuation? They don't, the only thing that can justify it is if they get themselves into every business workflow. That's what the investors are counting on.

fooblaster 9mo ago

There is a pretty big moat for Google: extreme amounts of video data on their existing services and absolutely no dependence on Nvidia and it's 90% margin.

fooblaster 9mo ago
And yes, all their competitors are making custom chips. Google is on TPU v7. absolutely nobody is going to get this right on the first try among their competitors - Google didn't.
- CharlieDigital 9mo ago
  Bigger problem for late starts now is that it will be hard to match the performance and cost of Google/Nvidia. It's an investment that had to have started years ago to be competitive now.
nateb2022 9mo ago
I have yet to be convinced the broader population has an appetite for AI produced cinematography or videos. Independence from Nvidia is no more of a liability than dependence on electricity rates; it's not as if it's in Nvidia's interest to see one of its large customers fail. And pretty much any of the other Mag7 companies are capable of developing in-house TPUs + are already independently profitable, so Google isn't alone here.
- fooblaster 9mo ago
  If you think they are going to catch up with Google's software and hardware ecosystem on their first chip, you may be underestimating how hard this is. Google is on TPU v7. meta has already tried with MTIA v1 and v2. those haven't been deployed at scale for inference.
  - nateb2022 9mo ago
    I don't think many of them will want to, though. I think as long as Nvidia/AMD/other hardware providers offer inference hardware at prices decent enough to not justify building a chip in-house, most companies won't. Some of them will probably experiment, although that will look more like a small team of researchers + a moderate budget rather than a burn-the-ships we're going to use only our own hardware approach.

nateb2022 9mo ago

> AI is going to be a highly-competitive, extremely capital-intensive commodity market It already is. In terms of competition, I don't think we've seen any groundbreaking new research or architecture since the introduction of inference time compute ("thinking") in late 2024/early 2025 circa GPT-o4. The majority of the cost/innovation now is training this 1-2 year old technology on increasingly large amounts of content, and developing more hardware capable of running these larger models at more scale. I think it's fair to say the majority of capital is now being dumped into hardware, whether that's HBM and research related to that, or increasingly powerful GPUs and TPUs. But these components are applicable to a lot of other places other than AI, and I think we'll probably stumble across some manufacturing techniques or physics discoveries that will have a positive impact on other industries. > that ends up in a race to the bottom competing on cost and efficiency of delivering One could say that the introduction of the personal computer became a "race to the bottom." But it was only the start of the dot-com bubble era, a bubble that brought about a lot of beneficial market expansion. > models that have all reached the same asymptotic performance in the sense of intelligence, reasoning, etc. I definitely agree with the asymptotic performance. But I think the more exciting fact is that we can probably expect LLMs to get a LOT cheaper in the next few years as the current investments in hardware begin to pay off, and I think it's safe to assume that in 5-10 years, most entry-level laptops will be able to manage a local 30B sized model while still being capable of multitasking. As it gets cheaper, more applications for it become more practical. --- Regarding OpenAI, I think it definitely stands in a somewhat precarious spot, since basically the majority of its valuation is justified by nothing less than expectations of future profit. Unlike Google, which was profitable before the introduction of Gemini, AI startups need to establish profitability still. I think although initial expectations were for B2C models for these AI companies, most of the ones that survive will do so by pivoting to a B2B structure. I think it's fair to say that most businesses are more inclined to spend money chasing AI than individuals, and that'll lead to an increase in AI consulting type firms.

mark_l_watson 9mo ago
> in 5-10 years, most entry-level laptops will be able to manage a local 30B sized model I suspect most of the excitement and value will be on edge devices. Models sized 1.7B to 30B have improved incredibly in capability in just the last few months and are unrecognizably better than a year ago. With improved science, new efficiency hacks, and new ideas, I can’t even imagine what a 30B model with effective tooling available could do in a personal device in two years time.

phyzix5761 9mo ago

I, personally, use chatGPT for search more than I do Google these days. It, more often than not, gives me more exact results based on what I'm looking for and it produces links I can visit to get more information. I think this is where their competitive advantage lies if they can figure out how to monetize that.

aprilthird2021 9mo ago
I'm genuinely curious. Why do you do this instead of Google Searches which also have an AI Overview / answer at the top, that's basically exactly the same as putting your search query into a chat bot, but it ALSO has all the links from a regular Google search so you can quickly corroborate the info even using sources not from the original AI result (so you also see discordant sources from what the AI answer had)?
- thom 9mo ago
  The regular google search AI doesn’t do thinky thinky mode. For most buying decisions these days I ask ChatGPT to go off and search and think for a while given certain constraints, while taking particular note of Reddit and YouTube comments, and come back with some recommendations. I’ve been delighted with the results.
  - Marsymars 9mo ago
    I wouldn’t be surprised if ChatGPT was Pareto optimal for buying decisions… but I suspect there are a whole pile of Pareto optimal ways to make buying decisions, including “buy one of the Wirecutter picks” or “buy whatever Costco is selling”.
    - thom 9mo ago
      Even in the case where you have a good shortlist of items, the ability to then ask follow up questions in a conversational format is very useful for me. Anyway, just explaining why one might use ChatGPT for this rather than the Google search box, obviously your mileage is welcome to vary.

gerdesj 9mo ago

"AI is going to be a highly-competitive" - In what way? It is not a railroad and the railroads did not explode in a bubble (OK a few early engines did explode but that is engineering). I think LLM driven investments in massive DCs is ill advised.

fcantournet 9mo ago
Yes they did, at least twice in the 19th century. It was the largest financial crisis before 1929
- johnnyanmac 9mo ago
  It did. I question the issue of "what problem am I trying to solve" with AI, though. Transportation across a huge swath of land had a clear problem space, and trains offered a very clear solution; created dedicated railing and you can transport 100x the resources at 10x the speed of a horseman (and I'm probably underselling these gains). In times where trekking across a continent took months, the efficiencies in communication and supply lines are immediately clear. AI feels like a solution looking for a problem. Especially with 90% of consumer facing products. Were people asking for better chatbots, or to quickly deepfake some video scene? I think the bubble popping will re-reveal some incredible backend tools in tech, medical, and (eventually) robotics. But I don't think this is otherwise solving the problems they marketed on.
  - heavyset_go 9mo ago
    > AI feels like a solution looking for a problem. The problem is increasing profits by replacing paid labor with something "good enough".
    - MangoToupe 9mo ago
      This is a use case that hasn't yet been proven out, though. "Good enough" for an executive may not be "good enough" to keep the company solvent, and there's no shortage of private equity morons who have no understanding of their own assets.

variadix 9mo ago

This will remain the case until we have another transformer-level leap in ML technology. I don’t expect such an advancement to be openly published when it is discovered.

energy123 9mo ago

> There's no evidence of a technological moat or a competitive advantage in any of these companies. I disagree based on personal experience. OpenAI is a step above in usefulness. Codex and GPT 5.2 Pro have no peers right now. I'm happy to pay them $200/month. I don't use my Google Pro subscription much. Gemini 3.0 Pro spends 1/10th of the time thinking compared to GPT 5.2 Thinking and outputs a worse answer or ignores my prompt. Similar story with Deepseek. The public benchmarks tell a different story which is where I believe the sentiment online comes from, but I am going to trust my experience, because my experience can't be benchmaxxed.

harrall 9mo ago
I use both and ChatGPT will absolutely glaze me. I will intentionally say some BS and ChatGPT will say “you’re so right.” It will hilariously try to make me feel good. But Gemini will put me in my place. Sometimes I ask my question to Gemini because I don’t trust ChatGPT’s affirmations. Truthfully I just use both.
- gridspy 9mo ago
  I told ChatGPT via my settings that I often make mistakes and to call out my assumptions. So now it 1. Glazes me 2. Lists a variety of assumptions (some can be useful / interesting) Answers the question At least this way I don't spend a day pursuing an idea the wrong way because ChatGPT never pointed out something obvious.
  - nubg 9mo ago
    Care to share the system prompt?
wild_egg 9mo ago
I still find it so fascinating how experiences with these models are so varied. I find codex & 5.2 Pro next to useless and nothing holds a candle to Opus 4.5 in terms of utility or quality. There's probably something in how varied human brains and thought processes are. You and I likely think through problems in some fundamentally different way that leads to us favouring different models that more closely align with ourselves. No one seems to ever talk about that though and instead we get these black and white statements about how our personally preferred model is the only obvious choice and company XYZ is clearly superior to all the competition.

adventured 9mo ago

Your premise is wrong in a very important way. The cost of entry is far beyond extraordinary. You're acting like anybody can gain entry, when the exact opposite is the case. The door is closing right now. Just try to compete with OpenAI, let's see you calculate the price of attempting it. Scale it to 300, 500, 800 million users. Why aren't there a dozen more Anthropics, given the valuation in question (and potential IPO)? Because it'll cost you tens of billions of dollars just to try to keep up. Nobody will give you that money. You can't get the GPUs, you can't get the engineers, you can't get the dollars, you can't build the datacenters. Hell, you can't even get the RAM these days, nor can you afford it. Google & Co are capturing the market and will monetize it with advertising. They will generate trillions of dollars in revenue over the coming 10-15 years by doing so. The barrier to entry is the same one that exists in search: it'll cost you well over one hundred billion dollars to try to be in the game at the level that Gemini will be at circa 2026-2027, for just five years. Please, inform me of where you plan to get that one hundred billion dollars just to try to keep up. Even Anthropic is going to struggle to stay in the competition when the music (funding bubble) stops. There are maybe a dozen or so companies in existence that can realistically try to compete with the likes of Gemini or GPT.

zozbot234 9mo ago
> Just try to compete with OpenAI, let's see you calculate the price of attempting it. Scale it to 300, 500, 800 million users. Apparently the DeepSeek folks managed that feat. Even with the high initial barriers to entry you're talking about, there will always be ways to compete by specializing in some underserved niche and growing from there. Competition seems to be alive and well.
- thom 9mo ago
  DeepSeek certainly managed that on the training side but in terms of inference, the actual product was unusably slow and unreliable at launch and for several months after. I have not bothered revisiting it.
  - snuxoll 9mo ago

johnnyanmac 9mo ago

>That doesn't mean AI is going to go away, or that it won't change the world - railroads are still here and they did change the world - but from a venture investment perspective, get ready for a massive downturn. I don't know why people always imply that "the bubble will burst" means that "literally all Ai will die out and nothing will remain that is of use". The Dotcom bubble didn't kill the internet. But it was a bubble and it burst nonetheless, with ramifications that spanned decades. All it really means when you believe a bubble will pop is "this asset is over-valued and it will soon, rapidly deflate in value to something more sustainable" . And that's a good thing long term, despite the rampant destruction such a crash will cause for the next few years.

mr_toad 9mo ago
But some people do believe that AI is all hype and it will all go away. It’s hard to find two people who actually mean the same thing when they talk about a “bubble” right now.
latchup 9mo ago
I don't think anyone seriously believes AI will disappear without a trace. At the very least, LLMs will remain as the state of the art in high-level language processing (editing, translation, chat interfaces, etc.) The real problem is the massive over-promises of transforming every industry, replacing most human labor, and eventually reaching super-intelligence based on current models. I hope we can agree that these are all wholly unattainable, even from a purely technological perspective. However, we are investing as if there were no tomorrow without these outcomes, building massive data-centers filled with "GPUs" that, contrary to investor copium, will quickly become obsolete and are increasingly useless for general-purpose datacenter applications (Blackwell Ultra has NO FP64 hardware, for crying out loud...). We can agree that the bubble deflating, one way or another, is the best outcome long term. That said, the longer we fuel these delusions, the worse the fallout will be when it does. And what I fear is that one day, a bubble (perhaps this one, perhaps another) will grow so large that it wipes out globalized free-market trade as we know it.
- zozbot234 9mo ago

adamnemecek 9mo ago

AI is capital intensive because autodiff kinda sucks.

api 9mo ago

If performance indeed asymptotes, and if we are not at the end of silicon scaling or decreasing cost of compute, then it will eventually be possible to run the very best models at home on reasonably priced hardware. Eventually the curves cross. Eventually the computer you can get for, say, $2000, becomes able to run the best models in existence. The only way this doesn’t happen is if models do not asymptote or if computers stop getting cheaper per unit compute and storage. This wouldn’t mean everyone would actually do this. Only sophisticated or privacy conscious people would. But what it would mean is that AI is cheap and commodity and there is no moat in just making or running models or in owning the best infrastructure for them.

guluarte 9mo ago

Also that open source models are just months behind

dheera 9mo ago

People seem to have the assumption that OpenAI and Anthropic dying would be synonymous with AI dying, and that's not the case. OpenAI and Anthropic spent a lot of capital on important research, and if the shareholders and equity markets cannot learn to value and respect that and instead let these companies die, new companies will be formed with the same tech, possibly by the same general group of people, thrive, and conveniently leave out the said shareholders. Google was built on the shoulders of a lot of infrastructure tech developed by former search engine giants. Unfortunately the equity markets decided to devalue those giants instead of applaud them for their contributions to society.

tootie 9mo ago
Isn't it really the other way around? Not to say OpenAI and Anthropic haven't done important work, but the genesis of this entire market was paper on attention that came out of Google. We have the private messages inside OpenAI saying they needed to get to market ASAP or Google would kill them.
raw_anon_1111 9mo ago
You weren’t around pre Google were you? The only thing Google learned from other search engines is what not to do - like rank based on the number of times a keyword appeared and not to use expensive bespoked servers
- dheera 9mo ago
  I was around pre-Google. Ranking was Google's 5% contribution to it. They stood on the shoulders of people who invented physical server and datacenter infrastructure, Unix/Linux, file systems, databases, error correction, distributed computing, the entire internet infrastructure, modern Ethernet, all kinds of stuff.
  - raw_anon_1111 9mo ago
    And none of that had to do with learning from other search engines…

deleted 9mo ago

[deleted]

Davidzheng 9mo ago

Um meta didn't achieve the same results yet. And does it matter if they can all achieve the same results if they all manage high enough payoffs? I think subscription based income is only the beginning. Next stage is AI-based subcompanies encroaching on other industries (e.g. deepmind's drug company)

jfrbfbreudh 9mo ago

Google’s moat: Try “@gmail” in Gemini Google’s surface area to apply AI is larger than any other company’s. And they have arguably the best multimodal model and indisputably the best flash model?

avalys 9mo ago
If the “moat” is not AI technology itself but merely sufficient other lines of business to deploy it well, then that’s further evidence that venture investments in AI startups will yield very poor returns.
- tjwebbnorfolk 9mo ago
  It's funny that a decade ago the exit strategy of many of these startups would have been to get acquired by MSFT / META / GOOG. Now, the regulators have made a lot of these acquisitions effectively impossible for antitrust reasons. Is it better for society for promising startups to die on the open market, or get acquired by a monopoly? The third option -- taking down the established players -- appears increasingly unlikely.
  - maeln 9mo ago
    > Now, the regulators have made a lot of these acquisitions effectively impossible for antitrust reasons. Is there any evidence that this is the case ? For very big merger (like nvdia and Arm tried) sure, but I can't think of a single time regulator stop a big player from buying a start up.
    - tjwebbnorfolk 9mo ago
      I'm sure you realize you're asking me to prove a negative? I don't have the ability to prove to you that something didn't happen or why. What I know is that a lot of deals aren't even being considered that once were, and antitrust is a huge factor in that consideration.
  - shimman 9mo ago

xbmcuser 9mo ago

This is why I think China will win the AI race. As once it becomes a commodity no other country is capable of bringing down manufacturing and energy costs the way China is today. I am also rooting for them to get on parity with node size for chips for the same reason as they can crash the prices PC hardware.

BenFranklin100 9mo ago

I’m waiting to get an RTX 5090 on the cheap.

2OEH8eoCRo0 9mo ago
A penny saved is a penny earned

578_Observer 9mo ago

The "Railway Bubble" analogy is spot on. As a loan officer in Japan who remembers the 1989 bubble, I see the same pattern. In the traditional "Shinise" world I work with, Cash is Oxygen. You hoard it to survive the inevitable crash. For OpenAI, Cash is Rocket Fuel. They are burning it all to reach "escape velocity" (AGI) before gravity kicks in. In 1989, we also bet that land prices would outrun gravity forever. But usually, Physics (and Debt) wins in the end. When the railway bubble bursts, only those with "Oxygen" will survive.

ManuelKiessling 9mo ago
I‘m aware this means leaving the original topic of this thread, but would you mind giving us a rundown of this whole Japan 1989 thing? I would love to read a first-person account.
- 578_Observer 9mo ago
  I am honored to receive a question from a fellow "Craftsman" (I assume from your name). To be honest, in 1989, I was just a child. I didn't drink the champagne. But as a banker today, I am the one cleaning up the broken glass. So I can tell you about 1989 from the perspective of a "Survivor's Loan Officer." I see two realities every day. One is the "Zombie" companies. Many SMEs here still list Golf Club Memberships on their books at 1989 prices. Today, they are worth maybe 1/20th of that value. Technically, these companies are insolvent, but they keep the "Ghost of 1989" on the books, hoping to one day write it off as a tax loss. It is a lie that has lasted 30 years. But the real estate is even worse. I often visit apartment buildings built during the bubble. They are decaying, and tenants have fled to newer, modern buildings. The owner cannot sell the land because demolition costs hundreds of thousands of dollars—more than the land is worth. The owner is now 70 years old. His family has drifted apart. He lives alone in one of the empty units, acting as the caretaker of his own ruin. The bubble isn't just a graph in a history book. It is an old man trapped in a concrete box he built with "easy money." That is why I fear the "Cash Burn" of AI. When the fuel runs out, the wreckage doesn't just disappear. Someone has to live in it.
  - 9mo ago

parentheses 9mo ago

This is different because now the cats out of the bag: AI is big money! I don't expect AGI or Super intelligence to take that long but I do think it'll happen in private labs now. There's an AI business model (pay per token) that folks can use also.

oblio 9mo ago
> don't expect AGI or Super intelligence to take that long I appreciate the optimism for what would be the biggest achievement (and possibly disaster) in human history. I wish other technologies like curing cancer, Alzheimer's, solving world hunger and peace would have similar timelines.
- barrenko 9mo ago
  We are making decent strides on the first two, the latter two are like wanting cats to stop scratching. What's the point of being a cat than?

__MatrixMan__ 9mo ago

I think we'll find that that asymptote only holds for cases where the end user is not really an active participant in creating the next model: - take your data - make a model - sell it back to you Eventually all of the available data will have been squeezed for all it's worth the only way to differentiate oneself as an AI company will be to propel your users to new heights so that there's new stuff to learn. That growth will be slower, but I think it'll bear more meaningful fruit. I'm not sure if today's investors are patient enough to see us through to that phase in any kind of a controlled manner, so I expect a bumpy ride in the interim.

conartist6 9mo ago
Yeah except that models don't propel communities towards new heights. They drive towards the averages. They take from the best to give to the worst, so that as much value is destroyed as created. There's no virtuous cycle there...
- __MatrixMan__ 9mo ago
  Is that constraint fundamental to what they are? Or are they just reflecting the behavior of markets when there's low hanging fruit around? When you look at models that were built for a specific purpose, closely intertwined with experts who care about that purpose, they absolutely propel communities to new heights. Consider the impact of alphafold, it won a Nobel prize, proteomics is forever changed. The issue is that that's not currently the business model that's aimed at most of us. We have to have a race to the bottom first. We can have nice things later, if we're lucky, once a certain sort of investor goes broke and a different sort takes the helm. It's stupid, but its a stupidity that predates AI by a long shot.
  - conartist6 9mo ago
    Experts making a specialized model isn't an example of an AI contributing value to society. All the value a model can offer comes from one of exactly two places: the person building the model, or the people the model trained on. We know that the model training on the model training on the model leads to model collapse...

hakfoo 9mo ago

The railroads provided something of enduring value. They did something materially better than previous competitors (horsecarts and canals) could. Even today, nothing beats freight rail for efficient, cheap modest-speed movement of goods. If we consider "AI" to be the current LLM and ImageGen bubble, I'm not sure we can say that. We were all wowed that we could write a brief prompt and get 5,000 lines of React code or an anatomically questionable deepfake of Legally Distinct Chris Hemsworth dancing in a tutu. But once we got past the initial wow, we had to look at the finished product and it's usually not that great. AI as a research tool will spit back complete garbage with a straight face. AI images/video require a lot of manual cleanup to hold up to anything but the most transient scrutiny. AI text has such distinct tones that it's become a joke. AI code isn't better than good human-developed code and is prone to its own unique fault patterns. It can deliver a lot of mediocrity in a hurry, but how much of that do we really need? I'd hope some of the post-bubble reckoning comes in the form of "if we don't have AI to do it (vendor failures or pricing-to-actual-cost makes it unaffordable), did we really need it in the first place?" I don't need 25 chatbots summarizing things I already read or pleading to "help with my writing" when I know what I want to say.

cco 9mo ago
I was really hoping, and with a different administration I think there was a real shot, for a huge influx of cash into clean energy infrastructure. Imagine a trillion dollars (frankly it might be more, we'll see) shoved into clean energy generation and huge upgrades to our distribution. With a bubble burst all we'd be left with is a modern grid and so much clean energy we could accelerate our move off fossil fuels. Plus a lot of extra compute, that's less clear of a long term value. Alas.
choeger 9mo ago
You're absolutely correct! ( ;) ) The issue is that generation of error-prone content is indeed not very valuable. It can be useful in software engineering, but I'd put it way below the infamous 10x increase in productivity. Summarizing stuff is probably useful, too, but its usefulness depends on you sitting between many different communication channels and being constantly swamped in input. (Is that why CEOs love it?) Generally, LLMs are great translators with a (very) lossly compressed knowledge DB attached. I think they're great user Interfaces, and they can help streamline buerocracy (instead of getting rid of it) but they will not help getting down the cost of production of tangible items. They won't solve housing. My best bet is in medicine. Here, all the areas that LLMs excell at meet. A slightly distopian future cuts the expensive personal doctors and replaces them with (few) nurses and many devices and medicine controlled by a medical agent.

pier25 9mo ago

Did railroads change the world though? They only lasted a couple of decades as the main transportation method. I'd say the internal combustion engine was a lot more transformative.

xhevahir 9mo ago
Pretty much every major historical trend of Western societies in the second half of the eighteenth century, from the development of the modern corporation to the advent of total war, was intimately tied to railroad transportation.
Marsymars 9mo ago
Transportation of people, yeah, but it still carries a majority of inter-city freight in North America.
anshumankmr 9mo ago
Umm yes? The metro even if not a big deal in the states is like a small but quiet way it has changed public transport, plus moving freight, plus people over large distances, plus the bullet train that mixed luxury, speed and efficiency onto trains, all of these are quietly disruptive transformations, that I think we all take for granted.
oblio 9mo ago
Railroads built America and won multiple large wars.
tliltocatl 9mo ago
Besides from he fact the freight is still universally carried by the rail when possible, railroads changed the world just like the vacuum valves did. If not for them nobody would invest in developing tire transport or transistors.

jotras 9mo ago

Something nobody's talking about: OpenAI's losses might actually be attractive to certain investors from a tax perspective. Microsoft and other corporate investors can potentially use their share of OpenAI's operating losses to offset their own taxable income through partnership tax treatment. It's basically a tax-advantaged way to fund R&D - you get the loss deductions now while retaining upside optionality later. This is why the "cash burn = value destruction" framing misses the mark. For the right investor base, $10B in annual losses at OpenAI could be worth $2-3B in tax shields (depending on their bracket and how the structure works). That completely changes the return calculation. The real question isn't "can OpenAI justify its valuation" but rather "what's the blended tax rate of its investor base?" If you're sitting on a pile of profitable cloud revenue like Microsoft, suddenly OpenAI's burn rate starts looking like a pretty efficient way to minimize your tax bill while getting a free option on the AI leader. This also explains why big tech is so eager to invest at nosebleed valuations. They're not just betting on AI upside, they're getting immediate tax benefits that de-risk the whole thing.

rebuilder 9mo ago
It’s hardly a free option, by your numbers it’d be a 20-30% discount.
- thrwaway55 9mo ago
  Sure but if there's no moat would you rather pay 100% or 80% until the credits run out? You reap the 100% spend in the meantime. Not everyone even has the no moat discount.
ludicrousdispla 9mo ago
>> For the right investor base, $10B in annual losses at OpenAI could be worth $2-3B in tax shields So just a loss for governments, or in other words, socializing the losses.
- booi 9mo ago
  Hi, I'm here to hold the bag?

zeofig 9mo ago

I still don't understand how it's world-changing apart from considerably degrading the internet. It's laughable to compare it to railroads.

kolinko 9mo ago
Did you try asking chatgpt to explain?
tliltocatl 9mo ago
Translation is big thing, maybe not the same scale as railroads, but still important. The rest is of dubious economic utility (as in you can do it with LLM easier than without, but if you think a little you could just as well not do it at all without losing anything). On the other hand, disrupting signalling will have pretty long-lasting consequences. People used to assume that a long formal-sounding text is a signal of seriousness, certainly so if it's personally addressed. Now it's just a sign of sloppiness. School essays are probably dead as a genre (good riddance). Hell, maybe even some edgy censorable language will enter mainstream as a definite proof of non-LLMness - and stay.
tim333 9mo ago
When it gets a bit better two robots can make four robots and so on to infinity.

matwood 9mo ago

Or the airlines. Airlines have created a huge amount of economic value that has mostly been captured by other entities.

Chyzwar 9mo ago

Anthropic is building moat around theirs models with claude code, Agent SDK, containers, programmatic tool use, tool search, skills and more. Once you fully integrate you will not switch. Also being capital intensive is a form of moat. I think we will end up with market similar to cloud computing. Few big players with great margins creating cartel.

mhuffman 9mo ago
>Anthropic is building moat around theirs models with claude code, Agent SDK, containers, programmatic tool use, tool search, skills and more. I think this is something the other big players could replicate rapidly, even simulating the exact UI, interactions, importing/exporting existing items, etc. that people are used to with claude products. I don't think this is that big of a moat in the long run. Other big players just seem to be carving up the landscape and see where they can can fit in for now, but once resource rich eyes focus on them, Anthropic's "moat" will disappear.
iLoveOncall 9mo ago
A GPT wrapper isn't a moat.
- bogdan 9mo ago
  Most things are wrappers around RDBMSs.
  - blinding-streak 9mo ago
    Most true and interesting comment I've read on HN in a while!
- visarga 9mo ago
  A generic wrapper is not a moat, but the context is. Both the LLM provider and the wrapper provider depend on local context for task activities. The value flows to the context, the LLMs and wrappers are commodities. Who sets the prompts stands to benefit, not who serves AI services.

throw310822 9mo ago

> AI is a world-changing technology, just like the railroads were This comparison keeps popping up, and I think it's misleading. The pace of technology uptake is completely different from that of railroads: the user base of ChatGPT alone went from 0 to 200 million in nine months, and it's now- after just three years- around 900 million users on a weekly basis. Even if you think that railroads and AI are equally impactful (I don't, I think AI will be far more impactful) the rapidity with which investments can turn into revenue and profit makes the situation entirely different from an investor's point of view.

steve1977 9mo ago
Railroads enabled people and goods to move from one place to another much easier and faster. AI enables people to... produce even more useless slop than before?
- throw310822 9mo ago
  At this point I'm taking the word "slop" as a sign meaning "I really didn't think this through and I'm just autocompleting based on a gut feeling and the first word that comes to mind".
  - steve1977 9mo ago
    That's an easy way out, isn't it?
    - mikkupikku 9mo ago
      Using thought terminating clichés in general is, and that can include "slop".
      - steve1977 9mo ago
        It wasn't meant to be thought terminating. If anything, it was a bit provocative.

nr378 9mo ago

> The simple evidence for this is that everyone who has invested the same resources in AI has produced roughly the same result. I think this conflates together a lot of different types of AI investment - the application layer vs the model layer vs the cloud layer vs the chip layer. It's entirely possible that it's hard to generate an economic profit at the model layer, but that doesn't mean that there can't be great returns from the other layers (and a lot of VC money is focused on the application layer).

londons_explore 9mo ago
Whilst those other layers are useful, none of them are particularly hard to build or rebuild when you have many millions of dollars on hand. One doesn't need tens of billions for them.
- tucnak 9mo ago
  Yeah, because making good chips (TPU) and compilers (XLA) is notoriously easy, right?
  - londons_explore 9mo ago
    All of that is below the model

retinaros 9mo ago

for me its clear OpenAI and Anthropic have a lead. I dont buy Gemini 3 being good. it isnt. whatever the benchmark said. same for meta and deepseek.

Bombthecat 9mo ago

Eh, I wouldn't be so sure, chips with brain matter and or light are on its way and or quantum chips, one of those or even a combination will give AI a gigantic boost in performance. Finally replacing a lot more humans and whoever implements it first will rule the world.

nineteen999 9mo ago
You seem to have forgotten that the ruling class requires tax payers to fund their incomes. If we're all out of work, there's nobody to buy their products and keep them rich.
- CuriousSkeptic 9mo ago
  Not sure this equation works out. If demand for labor goes towards zero it really means there is no demand. In other words, when AI and robots fulfil every desire of their owners there really is no need for “tax payers”
  - nineteen999 9mo ago
    If you really think 8 billion people are going to not tear the arms and legs off their overlords and their robot minions before that you're completely daft.
oblio 9mo ago
> chips with brain matter and or light The... what now?
- Bombthecat 9mo ago
  https://www.technologyreview.com/2023/12/11/1084926/human-brain-cells-chip-organoid-speech-recognition https://www.technologyreview.com/2023/12/11/1084926/human-br... They are getting better, faster etc etc. And I get down voted again for the truth people don't want to hear lol

cma 9mo ago

Deepseek has invested the same amount as OpenAI?

sunchit 9mo ago

Have you thought about what happens if we get a new improvement in model architecture like transformers that grows the compute needs even further

epolanski 9mo ago

Like railroads, internet, electricity, aviation or car industries before: they've all been indeed the future, and they all peaked (in relative terms), at the very early stages of these industries future. And among them the overwhelming majority of companies in the sectors died. Out of the 2000ish car-related companies that existed in 1925 only 3 survived to today. And none of those 3 ended up a particularly good long term investment.

trgn 9mo ago

very few software has commoditized, doubt it will be the fate of AI tech stack.

o_nate 9mo ago
Perhaps it would be useful to define what we mean by "commoditization" in terms of software. I would say a software product that is not commoditized is one where the brand still can command a premium, which in the world of software, generally means people are willing to pay non-zero dollars for it. Once software is commoditized it generally becomes free or ad-supported or is bundled with another non-software product or service. By this standard I would say there are very few non-commoditized consumer software products. People pay for services that are delivered via software (e.g. Spotify, Netflix) but in this case the software is just the delivery mechanism, not the product. So perhaps one viable path for chatbots to avoid commoditization would be to license exclusive content, but in this scenario the AI tech itself becomes a delivery mechanism, albeit a sophisticated one. Otherwise it seems selling ads is the only viable strategy, and precedents show that the economics of that only work when there is a near monopoly (e.g. Meta or Google). So it seems unlikely that a lot of the current AI companies will survive.

louiskottmann 9mo ago

This is so obviously right. I may add that investors are mostly US-centric, and so will the bubble-bursting chaos that ensues.

jklinger410 9mo ago

> The simple evidence for this is that everyone who has invested the same resources in AI has produced roughly the same result. OpenAI, Anthropic, Google, Meta, Deepseek, etc. There's no evidence of a technological moat or a competitive advantage in any of these companies. I think this is analysis is too surface level. We are seeing Google Gemini pull away in terms of image generation, and their access to billions of organic user images gives them a huge moat. And in terms of training data, Google also has a huge advantage there. The moat is the training data, capital investment, and simply having a better AI that others cannot recreate. I don't see how Google doesn't win this thing.

kkukshtel 9mo ago

I like to tell people that all the AI stuff happening right now is capitalism actually working as intended for once. People competing on features and price where we arent yet in a monopoly/duopoly situation yet. Will it eventually go rotten? Probably — but it's nice that right now for the first time in a while it feels like companies are actually competing for my dollar.

the_overseer 9mo ago
Aaahh the beautiful free market where the energy prices keep increasing and if it all fails they will be saved by the government that they bribed before. Don't forget the tax subsidies. AKA your money. Pure honest capitalism....

heresie-dabord 9mo ago

> AI is a world-changing technology As stated in TFA, this simply has not been demonstrated , nor are there any artifacts of proof. It's reasonable to suspect that there is no special apparatus behind the curtain in this Oz. From TFA: "One vc [sic] says discussion of cash burn is taboo at the firm, even though leaked figures suggest it will incinerate more than $115bn by 2030."

runeks 9mo ago

> The conclusion? AI is a world-changing technology, just like the railroads were, and it is going to soon explode in a huge bubble - just like the railroads did. Why "soon"? All your arguments may be correct, but none of them imply when the pending implosion will happen.

scrollop 9mo ago

Also what will happen if/when a different lab (or a current lab) develop a new architecture that can actually achieve AGI? The other, highly invested, companies (if openai and anthropic) may be in for a free fall. You never wake to be left in the wake of "the next big thing".

b3nji 9mo ago

I thought the same. Have you thought that there was a massive physical infrastructure left behind by the original railroad builders, all compatible with future vehicles? Other companies were able to buy the railroads for low prices and use. Large Language Models change their power consumption requirements monthly, the hardware required to run them is replaced at a rapid rate too. If it were to stop tomorrow, what would you be left with? Out of date hardware, massively wasted power, and a gigantic hole in your wallet. You could argue you have the blueprints for LLM building, known solutions, and it could all be rebuilt. The thing is, would you want to rebuild, and invest so much again for arguably little actual, tangible output? There isn't anything you can reuse, like others that came after could reuse the railroads.

mettamage 9mo ago

> The simple evidence for this is that everyone who has invested the same resources in AI has produced roughly the same result. OpenAI, Anthropic, Google, Meta, Deepseek, etc. There's no evidence of a technological moat or a competitive advantage in any of these companies. Practically, what I'm finding is that whenever I ask Claude to search stuff on Reddit, it can't but Gemini can. So I think the practical advantages are where certain organizations have unfair data advantages. What I found out is that LLMs work a lot better when they have quality data.