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Regardless of the promise of the underlying technology, I do wonder about the long-term viability of companies like OpenAI and Anthropic. Not only are they qui

• chasd00 8mo ago
  I think google ends up the winner. They can keep chugging along and just wait for everyone else to go bankrupt. I guess apple sees it too since the signed with google and not OpenAI.
  • piker 8mo ago
    And what about Microsoft?
    • napolux 8mo ago
      See Apple in my previous comment
    • mrbungie 8mo ago
      They don't have the know how (except by proxy via OpenAI) nor custom hardware and somehow they are even worse at integrating AI into their products than Google.
      • raw_anon_1111 8mo ago
        They don’t need to. Just like Amazon they are seeing record revenues from Azure because of their third party LLM hosting platforms only being gated because no one can get enough chips right now
  • napolux 8mo ago
    downvote all you want. google has all the money to keep up and just wait for the others to die. apple is a different story, btw, can probably buy openai or anthropic, but for now they're just waiting like google, and since they need to provide users AI after the failure with Apple Intelligence, they prefer to pay for Google and wait for the others to fight against each other. openai and anthropic know already what will happen if they go public :)
    • aurizon 8mo ago
      Google is vulnerable in search and that already shows as we see a decline as many parallel paths emerge. At the beginning it was a simple lookup for valid information and it became dominant - then pages of pay ranked preference spots filled pages that obscured what you wanted = it became evil.
      • raw_anon_1111 8mo ago
        We see no such thing. Google just announces review revenue and profit and Apple hinted at it not seeing any decline in revenue from their search deal with Google which is performance based.
      • wooger 8mo ago
        And Gemini is already integrated into the results page and gives useful answers instantly, alongside advertising... What problem for google are you seeing?
    • r0b05 8mo ago
      What will happen if they go public?
    • mrcwinn 8mo ago
      That’s not a well informed argument. Even if Apple could finance the $1T+ it would cost to buy Anthropic - they’re not making that money back by making the iPhone a little better. The only way to monetize is by selling, as Anthropic does, enterprise services to businesses. And that’s not Apple’s “DNA,” to use their language.
  • sethops1 8mo ago
    This is the conclusion I came to as well. Either make your own hardware, or drown paying premiums until you run out of money. For a while I was hopeful for some competition from AMD but that never panned out.
  • m-schuetz 8mo ago
    Also Gemini works absolutely fantastic right now. I find it provides better results for coding tasks compared to ChatGPT
    • logicallee 8mo ago
      have you compared it with Claude Code at all? Is there a similar subscription model for Gemini as Claude? Does it have an agent like Claude Code or ChatGPT Codex? what are you using it for? How does it do with large contexts? (Claude AI Code has a 1 million token context).
      • airstrike 8mo ago
        it's nowhere near claude opus but claude and claude code are different things
        • logicallee 8mo ago
          (Claude Code now runs claude opus, so they're not so different.) >it's [Gemini] nowhere near claude opus Could you be a bit more specific, because your sibling reply says "pretty close to opus performance" so it would help if you gave additional information about how you use it and how you feel the two compare. Thanks.
        • dudeinhawaii 8mo ago
          My take has been... Gemini 3.1 (and Gemini 3) are a lot smarter than Claude Opus 4.6 But... Gemini 3 series are both mediocre at best in agentic coding. Single shot question(s) about a code problem vs "build this feature autonomously". Gemini's CLI harness is just not very good and Gemini's approach to agentic coding leaves a lot to be desired. It doesn't perform the double-checking that Codex does, it's slower than Claude, it runs off and does things without asking and not clearly explaining why.
      • landl0rd 8mo ago
        - yes, pretty close to opus performance - yes - yes (not quite as good as CC/Codex but you can swap the API instead of using gemini-cli) - same stuff as them - better than others, google got long (1mm) context right before anyone else and doesn't charge two kidneys, an arm, and a leg like anthropic
  • Aboutplants 8mo ago
    The minute Apple chose Google, OpenAI became a dead duck. It will float for a while but it cannot compete with the likes of Google, their unlimited pockets and better yet their access to data
    • awongh 8mo ago
      I think it points to OpenAI trying to pivot to leveraging their brand awareness head start and optimizing for either ads or something like the Jony Ive device- focusing on the consumer side. For now people identify LLMs and AI with the ChatGPT brand. This seems like it might be the stickiest thing they can grab ahold of in the long term.
      • dakolli 8mo ago
        Ads in GPT, might literally be the worst business decision ever made. Google can get away with Ads, its expected from them, but not OpenAI
        • _aavaa_ 8mo ago
          Sergei and Brin were pretty vocal about the problems with ads and why they don't belong in search engines when they started. The only reason it's expected now is because of a slow boil.
        • duskdozer 8mo ago
          They ideally will not want you to realize you're looking at ads.
      • raw_anon_1111 8mo ago
        OpenAI is not going to fund themselves with $20 subscriptions and advertising enough to be profitable.
        • gruturo 8mo ago
          > OpenAI is not going to fund themselves with $20 subscriptions and advertising enough to be profitable. Then it's doomed. Which is also my opinion, I don't disagree at all with you.
  • neya 8mo ago
    Google is the new Open AI. Open AI is the new Google. Guess who wants to shove advertisements into paying customers' face and take a % of their revenues for using their models to build products? Not Google.
    • Forgeties79 8mo ago
      Don’t worry, Google is profiting off of your data one way or another lol
    • SecretDreams 8mo ago
      > Guess who wants to shove advertisements into paying customers' face and take a % of their revenues for using their models to build products? Not Google. But, also, probably google.
      • neya 8mo ago
        'Probably' isn't a good counter argument to Open AI's 'certainly'.
    • ipaddr 8mo ago
      The majority of people who use Google for AI encounter it at the top of an ad filled search engine.
      • neya 8mo ago
        A search engine which you leech for free, not pay and get ads shoved onto your face. The core argument here is getting ads into your face despite having paid for the product. And also, no one is forcing you to use Google when you have so many alternatives.
    • pell 8mo ago
      >Not Google. Google's main revenue source (~ 75%) is advertising. They will absolutely try to shove in ads into their AI offerings. They simply don't have to do it this quickly.
  • stego-tech 8mo ago
    [dead]
    • martinald 8mo ago
      I was thinking about that (I definitely agree with you on the software and data angle). But when you think about it it's actually a bit more complex. Right now (eg) OpenAI buys GPUs from (eg) NVidia, who buys HBM from Samsung and fabs the card on TSMC. Google instead designs the chip, with I assume a significant amount of assistance of Broadcom - at least in terms of manufacturing, who then buys the HBM from the same supplier(s) and fabs the card with TSMC. So I'm not entirely sure if the margin savings are that huge. I assume Broadcom charges a fair bit to manage the manufacturing process on behalf of Google. Almost certainly a lot less than NVidia would charge in terms of gross profit margins, but Google also has to pay for a lot of engineers to do the work that would be done in NVidia. No doubt it is a saving overall - otherwise they wouldn't do it. But I wonder how dramatic it is. Obviously Google has significant upside in the ability to customise their chips exactly how they want them, but NVidia (and to a lesser extent) AMD probably can source more customer workflows/issues from their broader set of clients. I think "Google makes its own TPUs" makes a lot of people think that the entire operation in house, but in reality they're just doing more design work than the other players. There's still a lot of margin "leaking" through Broadcom, memory suppliers and TSMC so I wonder how dramatic it is really is
      • coredog64 8mo ago
        My take is it's the inference efficiency. It's one thing to have a huge GPU cluster for training, but come inference time you don't need nearly so much. Having the TPU (and models purpose built for TPU) allows for best cost in serving at hyperscale.
        • martinald 8mo ago
          Yes potentially - but the OG TPUs were actually very poorly suited for LLM usage - designed for far smaller models with more parallelism in execution. They've obviously adapted the design but it's a risk optimising in hardware like that - if there is another model architecture jump the risk of having a narrow specialised set of hardware means you can't generalise enough.
  • hansmayer 8mo ago
    It is a rather attractive view, and I used to hold it too. However, seeing as Alphabet recently issued 100-year bonds to finance the AI CapEx bloat, means they are not that far off from the rest of the AI "YOLO"s currently jumping off the cliff ...
    • gorgolo 8mo ago
      If someone is willing to fund you with a 100y bond, and it gives you extra cash to move even a bit faster, it sounds like a pretty good deal. One thing I don’t get though, if superintelligence is really 5 years away, what’s going to be the point of a fixed-interest 100y bond.
      • hansmayer 8mo ago
        Motorola was I think the last company to issue a 100-year bond in the 90s. Whatever happened to Motorola?
    • jazzypants 8mo ago
      They have over $100B in cash on hand. I can't pretend to understand their financial dealings, but they have a lot more runway before that cliff than most of the other companies.
  • co_king_5 8mo ago
    [dead]
    • echelon 8mo ago
      You better hope Anthropic and OpenAI thrive, because a world in which Google is the sole winner is a nightmare. Google's best trick was skirting the antitrust ruling against them by making the judge think they'd "lose" AI. What a joke. Meanwhile they're camping everyone's trademarks, turning them into lucrative bidding wars because they own 92% of the browser URL bars. Try googling for Claude or ChatGPT. Those companies are shelling out hundreds of millions to their biggest competitor to defend their trademarks. If they stop, suddenly they lose 60% of their traffic. Seems unfair, right?
      • co_king_5 8mo ago
        [dead]
        • pfraze 8mo ago
          [flagged]
        • palmotea 8mo ago
          Also, Sam Altman (at least) gives the impression of being a bit of a manipulative psychopath. Even if there are others out there like him, who are just more competent at hiding their tendencies, I really don't want him to win the "world's richest man" jackpot; it'd be a bad lesson to others. Steve Jobs hero-worship is bad enough.
      • PunchTornado 8mo ago
        I'm waiting to see a more egregious company than openai and a bigger scammer ceo like altman. no, thank you. i hope openai goes bankrupt. especially since the ousting of ilya.
        • co_king_5 8mo ago
  • butlike 8mo ago
    In addition to that, Google and Apple are demonstrated business partners. Google has consistently paid Apple billions to be the default search engine, so they have demonstrated they pay on time and are a known quantity. Imagine if OpenAI evaporated and Siri was left without a backend. It'd be too risky.
  • alex1138 8mo ago
    Now if only Google could a) drop its commitment to censorship and b) stop prioritizing Youtube links in its answers
  • xnx 8mo ago
    In a few years this will amazingly alway have been obvious to everyone.
  • duped 8mo ago
    Google has proven themselves to be incapable of monetizing anything besides ads. One should be deeply skeptical of their ability to bring consumer software to market, and keep it there.
• techpression 8mo ago
  How is censorship / ”alternative information” affecting them? Genuinely curious as I’ve only read briefly about it and it was ages ago.
  • whynotmaybe 8mo ago
    I've tried deepseek a few months ago and asket about the Tiananmen square protests and massacre. At first the answer was "I can't say anything that might hurt people" but with a little persuasion it went further. The answer wasn't the current official answer but way more nuanced that Wikipedia's article. More in the vein of "we don't know for sure", "different versions", "external propaganda", "some officials have lied and been arrested since" In the end, when I asked whether I should trust the government or ask for multiple source, it strongly suggested to use multiple sources to form an opinion. = not as censored as I expected.
• delaminator 8mo ago
  Anthropic is also using lots of Amazon hardware for inference.
• jpalomaki 8mo ago
  Both Anthropic and OpenAI are working hard to move away from being "just" the LLM provider on the background.
• ulfbert_inc 8mo ago
  >LLM tech as it stands right now will turn into a commodity I am yet to see in-depth analysis that supports this claim
  • otabdeveloper4 8mo ago
    It's already a commodity. The strongest use case is self-hosted pornography generation.
• wejwej 8mo ago
  To take the other side of this, as computers got commodified there still was a massive benefit to using cloud computing. Could it be possible that that happens with LLMs as well as hardware becomes more and more specialized? I personally have no idea but love that there’s a bunch of competition and totally agree with your point regulation and export controls are just ways to make it harder for new orgs to compete.
• AznHisoka 8mo ago
  Anthropic at least seems to be doing well with enterprises. OpenAI doesnt have that level of trust with enterprise use cases, and commodization is a bigger issue with consumers, when they can just switch to another tool easily
  • SirensOfTitan 8mo ago
    Yeah, Anthropic is inarguably in a better position, but I don’t see how they justify their fundraising unless they find some entrenched position that is difficult for competitors to replicate. Enterprise switching costs aren’t 0, but they’re much less than most other categories, especially as models mature and become more fungible. The best moat I can think of is a patentable technique that facilitates a huge leap that Anthropic can defend, but even then, Chinese companies could easily ignore those patents. And I don’t even know if AI companies could stick to those guns as their training is essentially theft of huge portions of copyrighted material.
    • HDThoreaun 8mo ago
      > Yeah, Anthropic is inarguably in a better position OpenAI's biggest problem as well as their biggest advantage is that they have way, way more users than anyone else. Unfortunately for them the users they have dont pay for shit and they dont serve ads so more users = more money wasted right now. But its unlikely that will always be the case. If OpenAI turns on ads, most users will not leave because retail users hate change, and suddenly their massive user base is a boon instead of a problem.
• nvarsj 8mo ago
  I don't think you can put OpenAI and Anthropic together like that. Anthropic has actually cracked Agentic AI that is generally useful. No other company has done that.
• enceladus06 8mo ago
  OpenAI and Anthropic don't have a moat. We will have actual open models like DeepSeek and Kimi with the same functionality as Opus 4.6 in Claude Code <6mo IMO. Competition is a good thing for the end-user.
  • zozbot234 8mo ago
    The open-weight models are great but they're roughly a full year behind frontier models. That's a lot. There's also a whole lot of uses where running a generic Chinese-made model may be less than advisable, and OpenAI/Anthropic have know-how for creating custom models where appropriate. That can be quite valuable.
    • mattmaroon 8mo ago
      That's a lot now, in the same way that a PC in 1999 vs a PC in 2000 was a fairly sizeable discrepancy. At some point, probably soon, progress will slow, and it won't be much.
    • coder543 8mo ago
      I would not say a full year... not even close to a year: GLM-5 is very close to the frontier: https://artificialanalysis.ai/ https://artificialanalysis.ai/ Artificial Analysis isn't perfect, but it is an independent third party that actually runs the benchmarks themselves, and they use a wide range of benchmarks. It is a better automated litmus test than any other that I've been able to find in years of watching the development of LLMs. And the gap has been rapidly shrinking: https://www.youtube.com/watch?v=0NBILspM4c4&t=642s https://www.youtube.com/watch?v=0NBILspM4c4&t=642s
      • zozbot234 8mo ago
        Benchmarks are always fishy, you need to look at things that you'd use the model for in the real world. From that point of view, the SOTA for open models is quite behind.
        • 8mo ago
• lvl155 8mo ago
  Think LLM by itself is basically a commodity at this point. Not quite interchangeable but it’s more of artistic differences rather than technological. I used to think it was data and that would give companies like Google a leg up.
• KoolKat23 8mo ago
  Anthropic I feel will be alright. They have their niche, it's good and people actually do pay for their services. Why do people still use salesforce when there's other free CRM's. They also haven't from what I can tell scaled for some imaginary future growth. OpenAI I'm sorry to say are all over the place. They're good at what they do, but they try to do too much and need near ponzi style growth to sustain their business model.
• llm_nerd 8mo ago
  Anthropic, at least, has gone to lengths to avoid hardware lock-in or being open to extortion of the nvidia variety. Anthropic is running their models on nvidia GPUs, but also Amazon Trainium and Google's TPUs. Massive scale-outs on all three, so clearly they've abstracted their operations enough that they aren't wed to CUDA or anything nvidia-specific. Similarly, OpenAI has made some massive investments in AMD hardware, and have also ensured that they aren't tied to nvidia. I think it's nvidia that has less of a moat than many imagine they do, given that they're a $4.5T company. While small software shops might define their entire solution via CUDA, to the large firms this is just one possible abstraction engine. So if an upstart just copy pastes a massive number of relatively simple tensor cores and earns their business, they can embrace it.
• idopmstuff 8mo ago
  I do think the models themselves will get commoditized, but I've come around to the opinion that there's still plenty of moat to be had. On the user side, memory and context, especially as continual learning is developed, is pretty valuable. I use Claude Code to help run a lot of parts of my business, and it has so much context about what I do and the different products I sell that it would be annoying to switch at this point. I just used it to help me close my books for the year, and the fact that it was looking at my QuickBooks transactions with an understanding of my business definitely saved me a lot of time explaining. On the enterprise side, I think businesses are going to be hesitant to swap models in and out, especially when they're used for core product functionality. It's annoying to change deterministic software, and switching probabilistic models seems much more fraught.
• 999900000999 8mo ago
  They'll ban Chinese models, or do something like calling them security risks without proof. Enterprise customers will gladly pay 10x to 20x for American models. Of course this means American tech companies will start to fall behind, combined with our recent Xenophobia. Almost all the top AI researchers are either Chinese nationals or recent immigrants. With the way we've been treating immigrants lately ( plenty of people with status have been detained, often for weeks), I can't imagine the world's best talent continuing to come here. It's going to be an interesting decade y'all.
• sigmar 8mo ago
  >various open-weighted Chinese models out there. They've kept good pace with flagship models, I don't think this is accurate. Maybe it will change in the future but it seems like the Chinese models aren't keeping up with actually training techniques, they're largely using distillation techniques. Which means they'll always be catching up and never at the cutting edge. https://x.com/Altimor/status/2024166557107311057 https://x.com/Altimor/status/2024166557107311057
  • A_D_E_P_T 8mo ago
    > they're largely using distillation techniques. Which means they'll always be catching up and never at the cutting edge. You link to an assumption, and one that's seemingly highly motivated. Have you used the Chinese models? IMO Kimi K2.5 beats everything but Opus 4.6 and Gemini 3.1... and it's not exactly inferior to the latter, it's just different. It's much better at most writing tasks, and its "Deep Research" mode is by a wide margin the best in the business. (OpenAI's has really gone downhill for some reason.)
    • nwlieb 8mo ago
      Have you tried the OpenAI deep research in the past week or so? It's been updated to use 5.2 https://x.com/OpenAI/status/2021299935678026168 https://x.com/OpenAI/status/2021299935678026168 (I work at OpenAI, but on the infra side of things not on models)
  • arthurcolle 8mo ago
    I have been using a quorum composed of step-3.5-flash, Kimi k2.5 and glm-5 and I have found it outperforms opus-4.5 at a fraction of the cost That's pretty cutting edge to me. EDIT: It's not a swarm — it's closer to a voting system. All three models get the same prompt simultaneously via parallel API calls (OpenAI-compatible endpoints), and the system uses weighted consensus to pick a winner. Each model has a weight (e.g. step-3.5-flash=4, kimi-k2.5=3, glm-5=2) based on empirically observed reliability. The flow looks like: 1. User query comes in 2. All 3 models (+ optionally a local model like qwen3-abliterated:8b) get called in parallel 3. Responses come back in ~2-5s typically 4. The system filters out refusals and empty responses 5. Weighted voting picks the winner — if models agree on tool use (e.g. "fetch this URL"), that action executes 6. For text responses, it can also synthesize across multiple candidates The key insight is that cheap models in consensus are more reliable than a single expensive model. Any one of these models alone hallucinates or refuses more than the quorum does collectively. The refusal filtering is especially useful — if one model over-refuses, the others compensate. Tooling: it's a single Python agent (~5200 lines) with protocol-based tool dispatch — 110+ operations covering filesystem, git, web fetching, code analysis, media processing, a RAG knowledge base, etc. The quorum sits in front of the LLM decision layer, so the agent autonomously picks tools and chains actions. Purpose is general — coding, research, data analysis, whatever. I won't include it for length but I just kicked off a prompt to get some info on the recent Trump tariff Supreme Court decision: it fetched stock data from Benzinga/Google Finance, then researched the SCOTUS tariff ruling across AP, CNN, Politico, The Hill, and CNBC, all orchestrated by the quorum picking which URLs to fetch and synthesizing the results, continuing until something like 45 URLs were fully processed. Output was longer than a typical single chatbot response, because you get all the non-determinism from what the models actually ended up doing in the long-running execution, and then it needs to get consensus, which means all of the responses get at least one or N additional passes across the other models to get to that consensus. Cost-wise, these three models are all either free-tier or pennies per million tokens. The entire session above (dozens of quorum rounds, multiple web fetches) cost less than a single Opus prompt.
• deepriverfish 8mo ago
  they might end up like Dropbox
• 34679 8mo ago
  I can't shake the feeling that the RAM shortage was intentionally created to serve as a sort of artificial moat by slowing or outright preventing the adoption of open weight models. Altman is playing with hundreds of billions of other people's dollars, trying to protect (in his mind) a multi-trillion dollar company. If he could spend a few billion to shut down access to the hardware people need to run competitor's products, why wouldn't he?
  • tmaly 8mo ago
    Hard drives and GPUs seem to be facing the same fate.
  • zozbot234 8mo ago
    It's very difficult to "intentionally create" a real shortage. You can hoard as much as you want, but people will expect you to dump it all right back onto the market unless you really have a higher-value use for the stuff you hoarded (And then you didn't intentionally create anything, you just bought something you needed!). Plus producers will now feel free to expand production and dump even more onto the market. This is great if you needed that amount of supply, but it's terrible if you were just trying to deprive others.
    • kasabali 8mo ago
      You sure about that? https://www.mooreslawisdead.com/post/sam-altman-s-dirty-dram-deal https://www.mooreslawisdead.com/post/sam-altman-s-dirty-dram...
  • chasd00 8mo ago
    From what I understand the RAM producers see the writing on the wall. They’re not going to invest in massively more capacity only to have it sit completely idle in 10 years. RAM shortage is probably a bubble indicator itself. That industry doesn’t believe enough in the long term demand to build out more capacity.
• ahussain 8mo ago
  People were saying the same last year, and then Anthropic launched Claude Code which is already at a $2.5B revenue run rate. LLMs are useful and these companies will continue to find ways to capture some of the value they are creating.
• tinyhouse 8mo ago
  Openai is just playing catchup at this point, they completely lost thier way in my view. Anthropic on the other hand is very capable and given the success of claude code and cowork, I think they will maintain their lead across knowledge work for a long time just by having the best data to keep improving their models and everything around. It's also the hottest tech conpany rn, like Google were back in the day. If I need to bet on two companies that will win the AI race in the west, it's Anthropic and Google. Google on the consumer side mostly and Anthropic in enterprise. OpenAI will probably IPO soon to shift the risk to the public.
  • chasd00 8mo ago
    If anthropic continues getting their foot in the enterprise door then maybe they can tap into enterprise cloud spending. If Athropic can come up with services and things (db, dns, networking, webservers, etc) that claudecode will then prefer then maybe they become a cloud provider. To me, and I am no business expert btw, that could be a path to sustainable financials. Edit: one thing I didn’t think about is Anthropic more or less runs at the pleasure of AWS. Of Amazon sees Anthropic as a threat to AWS then it could be lights out.
    • tinyhouse 8mo ago
      Yes, they depend on AWS for compute and Amazon also owns a big chunk of Anthropic (it used to be close to 30%, probably less now with the recent raises). I think it's a good partnership since for the most part they focus on different things and I don't see Anthropic going after AWS - they are an AI company first and foremost. Amazon has their own AI stuff for enterprise but no one uses it so I don't think they take it seriously. They know they cannot compete here. I think that OpenAI and Microsoft is a more challenging partnership with much more overlap.
• munk-a 8mo ago
  OpenAI is not viable. OpenAI is spending like Google without a warchest and they have essentially nothing to offer outside of brand recognition. Nvidia propping them up to force AI training to be done on their chips vs. google in-house cores is their only viable path forward. Even if they develop a strong model the commitments they've made are astronomically out of reach of all but the largest companies and AI has proven to be a very low moat market. They can't demand a markup sufficient to justify that spend - it's too trivial to undercut them. Google/Apple/Nvidia - those with warchests that can treat this expenditure as R&D, write it off, and not be up to their eyeballs in debt - those are the most likely to win. It may still be a dark-horse previously unknown company but if it is that company will need to be a lot more disciplined about expenditures.
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