8 ms·

Speculation: open models is what will kill Anthropic and OpenAI. Hyperscalers can run the models without a licensing fee. Apple can make them smaller and put th

• qudat 2mo ago
  There’s not much of a difference because open models are distilling from frontier models. If frontier models cease to exist then many of these open models will as well
• cma 2mo ago
  You can run the same harness on fable, opus, sonnet, and see a huge difference between them. It is true the harness is important, and openai has begun encryption its instructions to swarmed sub-agents instead of just encrypting the chain of thought, but the model is still important at this stage.
  • Alpha3031 2mo ago
    Referent of "the models are meaningfully different" reads as <top closed, top open> rather than <top closed, cheaper closed> to me, so I'm not sure why we'd be comparing Fable vs Opus/Sonnet or Sol vs Terra rather than the same against Kimi K3.
    • Zababa 2mo ago
      Haven't tried Kimi K3 for now but there was a huge difference between GPT 5.6/Fable and GLM 5.2/Kimi K2.7 that were previous frontier open models.
    • cma 2mo ago
      I was just responding to "The harness is what takes these random and hallucinogenic models and make them into something deterministic and useful." You can compare Fable vs Sol vs Kimi in the same harness if you want too and there are meaningful big differences. I chose all Anthropic ones to be safe from the they were finetuned on different harnesses complaint that would be made from that comparison.
  • ActionHank 2mo ago
    This will only delay the inevitable. Sitting on some magic prompts is hardly the moat they need.
• Zababa 2mo ago
  The thing about not much difference between models and the harness making them deterministic and useful is wrong. Also models have different strengths and weaknesses and some are better at almost everything by a large margin compared to others. As for your speculation, I think it's hinging on some companies releasing models for free or no big differences between models. In a world with hyperscalers and companies training models you can quickly recreate Anthropic or OpenAI by having an hyperscaler ally with a model training company, train a good/a better model, and not release it.
• fnord77 2mo ago
  Just like opensource search engines killed google oh wait
  • blanched 2mo ago
    I don’t even know the names of any open source search engines, but the open source models perform decently on various benchmarks and in personal experience. Was it ever even a claim that open source search engines were trying to outperform google, let alone kill it?
    • fnord77 2mo ago
      Apache Solr / Lucene Elasticsearch Just like most people use Facebook or Insta for personal webpages instead of rolling their own, most people will use commercial AI forever.
      • blanched 2mo ago
        The distance between DeepSeek and Claude is far, far less than the distance between Google Search and any of those.
    • wongarsu 2mo ago
      Yacy tried in the 2000s. I'm sure some magazines made headlines posing the question whether yacy is a google-killer
  • inigyou 2mo ago
    Marginalia already gives me better results for many queries than Google. Because Google has sunk so low.
• mft_ 2mo ago
  Open models are probably also comparatively astronomically expensive to train - just less so than the frontier models because they’re somewhat smaller, +/- the creators are more incentivised to focus on getting more from less compute because they’re have to, +/- they rely on distillation of the frontier models and this is more efficient. But efficiencies aside; creation of open models still requires a lot of money and compute from a large organisation which is willing to accept zero return for that spend. This largesse is unlikely to continue forever; so the question is which will crack first, the frontier models’ business model or the fast followers’ generosity?
  • afavour 2mo ago
    I’m not exactly sure on the “how” but it only makes logical sense for (non-AI) companies to band together to fund the training of a shared model. Apple is a great example, AI is not their core business but they still require it. The only thing that took us down a different path is the vast sums of VC funding pumped into the AI companies.
    • inigyou 2mo ago
      If not for VC-funded LLMs there wouldn't be any LLMs.
      • afavour 2mo ago
        [citation needed] Historically speaking a lot of inventions have come about without things like VC investment. Either way, there’s probably little point in debating it, just because VC funded companies control the market now doesn’t mean they should indefinitely.
      • LunaSea 2mo ago
        Most of the innovations needed for LLMs came from people at Google.
        • inigyou 2mo ago
• gallerdude 2mo ago
  Even in the world where all models are basically equivalent (a thesis I don’t buy, but will grant you for arguments sake) - I believe there is much more to the AI business than just training and running models. It’s a very new set of technologies, and understanding what is useful to customers and what isn’t is the whole game. Call it, product taste. There were a million cell phones before the iPhone took over the world. Why iPhone? Product taste. There are a million startups, and only a select few become unicorns. Why? Product taste.
  • khurs 2mo ago
    >There were a million cell phones before the iPhone took over the world. You have tripped yourself up there. iPhone took over as it introduced something innovative over standard phones, but then Open Source (Android) matched the multi-touch and software differences and Apple's branding, lock-in and design etc have managed to keep it as a big player in wealthier countries. IPhone also came on the back of the massive iPod success. ChatGPT launched the same innovation vs Google Search, but just like Android Opensource AI is moving fast now. Android has 72.7% market share at present, Open Source AI will do the same unless the frontier labs can continue to do something new. The frontier labs are saddled with enormous investor and other debts. How long they can keep innovating by spending so much on R&D and paying there staff very high wages remains to be seen. Once investors cash out via an IPO, the companies are back down to earth and playing in the real world again.
    • gallerdude 2mo ago
      Android has market share, but Apple makes all of the money! I find it really funny when people attribute Apple’s success to “oh, the only reason they succeed is design and marketing.” Yeah, I mean factually speaking design and marketing actually do matter a lot! Us developer types like to pretend like specs are the only thing that matters? If you could have a 10x more powerful model you could only access running locally through your terminal, versus a weaker model through a clean web interface, normies will pick the web ui every single time. Product experience is simply everything, as much as we like to pretend like nitty technical decisions are the most important thing.
• Mistletoe 2mo ago
  Open models are 4k TV (or maybe 1080p tv now and 4k TV soon) and SOTA frontier models are 8k TV. Can I or the average user tell the difference? Not really. Would they pay for that difference? Not a chance. Our entire economy is teetering on some future hope that this fragile and immaterial difference will pay off, when the reality is that LLMs are a race to the bottom and eventual razor thin margins. Maybe a tiny vocal subset of programmers can use it for work and make paying for it worth it to them, but that can't prop up an entire economy, especially when said programmers are phased out, jobless, and replaced by AI with each better iteration...
  • km3r 2mo ago
    Except when we upgraded to 1080p from older TVs, they got bigger. Now with 4k they are getting bigger yet. More powerful models means new use cases that didn't make sense on the weaker models.
• kurthr 2mo ago
  I'm a bit skeptical of the token cost/ROI for all models, but sunk costs are sunk. It has the feel of self-improving super-intelligence or bust to me. If you get that, the frontier model(s) run away with a faster exponential. It's a bit like semi with Moore's Law with silicon, GaAs could never catch up. If you don't get it, the fast followers crush the high investment and there's no moat. Not like they can enforce copyright!
  • cyanydeez 2mo ago
    not really a feeling; if you listen to ed zitron and strip out the vitriol, you still get the fact that the VCs are looking for some 5 trillion dollars in 5 years. The onlly way that happens is if America turns into zimbawe.
    • nekusar 2mo ago
      Who says it hasn't already? I've driven in a LOT of the USA. Sure Chicago, NYC, DC, LA, LV... They're all built up and feel modern. Try driving anywhere in the Midwest outside of the big cities. Dilapidated carcas buildings everywhere. Urban and rural blight. Only jobs are low paying service work. Its bleak. Like, really bad poverty as a disease bleak. And its crazy watching it too. They're ignorant (involuntatily), poor, and trapped. And democrats only seem to care about special interest of the week, so these areas vote republican. I don't have a solution btw. Just something I've seen growing in the last 25 years. And its getting worse, not better.
      • cyanydeez 2mo ago
        >Who says it hasn't already? Great.
      • tempest_ 2mo ago
        As a Canadian driving through Michigan/Ohio/Upstate New York and places look run down and like they peaked in the 60s-80s and its been down hill since. When I was younger and it was a new thing it was quite a shock since American media obviously doesnt portray it that way. It is quite a contrast to even how the more run down parts of Canada look.
• goolz 2mo ago
  Completely agree. Once I can reliably get open models doing what I am on Fable ultra I imagine I will switch for good. I am fortunate to have access to a decent bit of local RAM, 192GB of DDR5 at an OK speed. It is not enough and costs are well past absurd. In a few years time I envisage a setup that is sub $10k which can accomplish such tasks. The pace so far has been breakneck. That is all I personally need. That may change, but until true AGI I do think there will be a ceiling to how much I will pay for something frontier if it is only marginally better.
  • wosk 2mo ago
    This is easier to say as Fable is good (even SOTA). But people have been were saying this continuously for the current model and for now the improvement are still coming. A better question is would you settle for o3 now or pay 20$ or 200$/month for fable ? Because o3 quality is available OSS. It is like the new IPhone, in some sort. At some point come a feature many would like to have, despite diminishing returns. We will see how long labs can keep up and what the scaling curve look like, but I would be more worried into losing sota status to Chinese companies than letting them take the open non-sota approach.
    • arlcode 2mo ago
      I think there is also the case were companies will simply use different tiers for different tasks. While the engineering team might need a cutting edge model (with the associated costs), the marketing department will be fine by something that can grammar correct or turn a few bullet points into prose. Likewise you already don't need Fable for Ticket -> RAG -> Reply with Faq knowledge or escalate workflows That's already the case with other very expensive software like CAD packages were oftentimes you have different feature sets enabled for different employees.
      • switchbak 2mo ago
        "that can grammar correct" ... Did you do that on purpose?
• elorant 2mo ago
  Eventually they will kill the hyperscalers too because of privacy issues. It's better for a company to pay an uprfont cost and then run everything on premise that uploading their entire codebase to a third party service.
  • xkcd-sucks 2mo ago
    Would that require a watershed event to clearly establish the importance/risk of privacy though? For example, right now it seems like most big software companies w/ strong security process are comfortable uploading entire codebases to Israeli cybersecurity firms for vulnerability scanning compliance purposes
  • nacs 2mo ago
    The vast majority of companies are still putting most things in the cloud and will continue to do so and this far outnumbers the must-be-on-premise companies. Sure there will be self-hosters but hosting AI models will always be more of a challenge than running scalable database on your own hardware and specialized hyperscalers will be here.
• sublinear 2mo ago
  I still strongly believe Google Gemini has the best position for one simple reason: model maintenance. Accurate information is a moving target. Open models are indeed very capable, but they will eventually become more specialized to the application to keep an edge. It makes perfect sense that the future shape of AI conforms to the landscape it was born out of.
  • lgessler 2mo ago
    You're saying it's important to have up-to-date facts stored in parametric knowledge? It seems to me like that's grown less and less important as agentic capabilities have grown. Even if a frontier model doesn't know something, if it's out there, it can easily find it through tool use.
  • inigyou 2mo ago
    Grok has the biggest advantage in current events knowledge because it's integrated with X, which enough people still use even though it isn't Twitter.
    • lukan 2mo ago
      Hm, when compared to all the information people with android devices share with google, or those with gmail, ..
      • inigyou 2mo ago
        Google wouldn't give Gemini direct access to everyone's Gmail. It would carry far too much risk of being exposed. X can, because tweets are public.
        • lukan 2mo ago
          But google can give gemini access to summaries of all the avaiable information google has, including what people look for right now and where and how long.
• paulddraper 2mo ago
  > Their marketing depends on people believing the models are meaningfully different, as people have sweatily argued on this forum. They are noticeably different. Benchmarks, anecdotes, all say the same thing. Now, is a ~6 month lead actually worth 1 gajillion dollars? Maybe not.
• braiamp 2mo ago
  The real moat aren't the models, but the tooling around the models that allow them to perform specific tasks/goals. That's what really sets apart frontier vs open. Open only has the model itself, closed have the tooling to enhance the model.
  • lelanthran 2mo ago
    > The real moat aren't the models, but the tooling around the models that allow them to perform specific tasks/goals. That's what really sets apart frontier vs open. Open only has the model itself, closed have the tooling to enhance the model. As these frontier companies have been boasting, writing software is now a negligible cost because the LLM can do it. IOW, no, their software can't be a moat, because, according to their own arguments, you can use their LLM to trivially clone their software.
    • smj-edison 2mo ago
      > you can use their LLM to trivially clone their software. Perhaps, but what you can't clone is familiarity, polish, integration, and network effects. These companies desperately need a moat, and so for example all the new additions to Claude's web interface are becoming the products that the vast majority of people will use and be locked into (if it goes according to their plan).
      • dd8601fn 2mo ago
        If development is trivial and capability remains the differentiator, then "familiarity, polish, [and] integration" are non-issues. I'm not sure what network effects even means in the context of llm selection.
  • cyanydeez 2mo ago
    unfortunately, for me, that's an anti-moat; their dark, inconcievable, alignment, random "no goblins" and inability to be reliable where their models are inevitable non-determinant means you're going to constantly run into the "this worked yesterday" problems, no matter how smart the models actually are; being filtered constantly through economics, political and ego-maniacal filters means everything you do with it will break at any given interval. good luck.
• ComputerGuru 2mo ago
  > Apple can make them smaller and put them on the device Someone can, but Apple has essentially admitted defeat and handed the reigns over to Google.
  • wilkystyle 2mo ago
    Have they? https://www.cnbc.com/amp/2026/07/14/apple-prismml-ai-compression-iphone.html https://www.cnbc.com/amp/2026/07/14/apple-prismml-ai-compres...
  • ButlerianJihad 2mo ago
    > handed the reigns over Oh man, they gave them free reign? How will anyone reign them in now? For all intensive porpoises, this is like Babe Ruth, chomping at the bat!
• giancarlostoro 2mo ago
  If consumers ever have enough VRAM for it locally, sure, otherwise nowhere near close. Nvidia is looking like they are ditching consumer markets in favor of enterprise GPUs since nobodys heard a peep about the next iteration of RTX cards. The 60xx series is postponed till 2028. Nvidias playing a dangerous gamble, in my eyes I see all the frontier labs eventually just only buying Nvidia chips for training and building custom ASICs for a fraction of the cost, longer lifespan and cheaper to host. This will eat their 5 year gravy train for GPUs vs the 10 to 15 for ASICs.
• SubiculumCode 2mo ago
  Speculation: Anthropic and and OpenAI become more like hedge funds, keeping their models to themselves, using their them and their compute for market/event prediction, internal tech development, and AI self improvement. I already wonder if that is what Google is doing. Why release your best models to help the competition? Their published models are good enough for 99% of consumers, and they can leverage their market dominance in other areas to put that consumer model in front of eyes. Then the decision to improve your internal models would both depend on whether you think they'd have value internally. Yeah, I'm pretty sure AI is going to go insular within the largest companies. This will only be hastened by the growing national security concerns/awareness.
  • xorcist 2mo ago
    They would have done that long ago if it was that easy. The fact that they aren't tells us something about the actual business utility of leading models.
  • naveen99 2mo ago
    Except Deepseek going in opposite direction: from hedge fund to an ai model provider.
• root_axis 2mo ago
  My prediction is that hardware costs will make open source models impractical for the foreseeable future. Yes, tinkerers and enthusiasts will continue to make use of them, but frontier companies will maintain near total dominance because they will be the only ones with access to the hardware.
  • honeycrispy 2mo ago
    There will be plenty of model providers with prices that undercut Anthropic/OpenAI's prices.
    • root_axis 2mo ago
      Doubtful for the same reasons. The frontier providers are working at a hardware scale that will make it impractical to undercut them. I wouldn't rule out the possibility completely, but it won't be very common.
      • honeycrispy 2mo ago
        They also have to pay for staff / model training. Those are not cheap.
  • repeekad 2mo ago
    Meta is selling their now excess compute, other compute has been on the market for a while. The current hardware cost bubble is temporary, especially once people are forced to pay the real inference price instead of majorly subsidized subscriptions.
    • bigyabai 2mo ago
      Lowering the cost of hardware still won't solve the issue. HBM and DDR5 was never cheap, even before the shortages, so selling a full inference system is beyond the acceptable price range for most casual customers. We're going to see Apple and Google compete over services and AI/OS integration instead, it will probably be years before your OEM takes local models seriously.
• enos_feedler 2mo ago
  There is a massive difference when you zoom in close or take an angled perspective. You can manufacture uniqueness. The issue is when it comes to every day use for every day people there is no differentiation.
• MangoCoffee 2mo ago
  >open models is what will kill Anthropic and OpenAI i doubt it. it cost money to train a model. we can see that with the price increase for Kimi3. Chinese AI companies is leaving a lot of money on the table for third party providers. you think they going to let go of those money that they can make. sooner or later they will want to collect. after all, none of Chinese open weight model is release by a none profit. its all for-profit companies that is releasing open weight model.
  • zuzululu 2mo ago
    I can't take anybody seriously when they keep declaring open models is beating frontier models. What they don't understand is that besides the huge capex to train and run inference, the real gold is in the human response to the prompt results, this is what all the Chinese companies are making their open models dirt cheap and distilling american frontier models via scraping. The idea that we can out-parameterize frontier models is a common misconception, the true moat that Anthropic and OpenAI is why Chinese model providers are open sourcing and making it dirt cheap to keep pace through its "proxy chain operators" https://x.com/HarshalsinghCN/status/2056626175959826692 https://x.com/HarshalsinghCN/status/2056626175959826692
• dmarcos 2mo ago
  The outcome is plausible. Open weights models though look like a tactical more than a principled play by Chinese companies to overcome the disadvantage and difficulties to access western markets. Two issues: 1. If market conditions change they might decide to close down like Meta did. 2. If as you said models keep getting more expensive to train, is an open weights strategy financially sustainable? edit: typo
  • vitally3643 2mo ago
    That's probably pretty likely, but if we're honest, are LLMs built and funded by a hostile Chinese authoritarian regime any more dangerous or harmful than LLMs built and funded by a hostile American authoritarian regime? China absolutely does not have my best interests at heart, but America's technofascism is probably more immediately dangerous and harmful. Americans genuinely have more to fear from America than China at this point.
    • grokcodec 2mo ago
      Define technofascism lol. Fascism was laid out by Mussolini in the 1920s - it amounts to the idolatry of the state. "All within the state, nothing outside the state, nothing against the state." B Mussolini Also defined as Corporatism: the union of state and corporate power. Which country do you think is closer to Mussolini's model ?
      • sph 2mo ago
        Fascism was strongly influenced by Futurism and its optimism for a machine-powered future where technology will bring forth utopia and order. It’s no wonder than Thiel & co. are rediscovering Futurism, and blind faith in the machine is basically what Silicon Valley is all about.
      • plastic-enjoyer 2mo ago
        I think the term 'techno' in 'technofascism' is doing the work here, because--just as you claim that historical fascism is the idolatry of the state--technofascism is the idolatry of technology and intelligence. Modern accelerationism, as espoused today by people like Marc Andreessen in his Techno-Optimist Manifesto, is really just another rehash of Italian Futurism, which was closely intertwined with Italian Fascism and one of its intellectual foundations. It was, essentially, a progressive ideology. The idolatry of the state does not vanish, but rather gets transformed and re-imagined as a technology, e.g. network states, platform governance, companies that function as sovereign entities. The idolatry shifts from the nation-state to the infrastructure that replaces it. Also, you don't need to look far to answer your own question about corporatism, as you defined it yourself. Now, who's currently moving between Silicon Valley boardrooms and government offices?
• polterguy-hyper 2mo ago
  [dead]
• Codefrontier 2mo ago
  I agree with your speculation to be honest. And yet I’ve tried several local open weights model now and none gives the same quality of answers as Claude gives me on a regular Sonnet model. Mind you: I am “running” 48GB of RAM so I can’t try every model. Where does this difference come from? Can we actually get close locally?
  • pocketarc 2mo ago
    You’re running 48GB now but imagine a future where everyone has 512GB RAM or 1TB RAM in their computers (it might sound like a lot but also 20 years ago we had 512MB PCs). It’s not hard to imagine what 5-10 years of pressure to increase RAM will do to specs, on top of the normal tech improvements. That’s worth bearing in mind when thinking about local models. Plus, local models keep getting better and better; 2 years ago what you could get out of those 48GB of RAM was embarrassing compared to what’s doable today. We’re getting there. Just takes time.
    • xyzsparetimexyz 2mo ago
      I seriously doubt that we'll be running 1TB ram setups any time soon. I was hearing about people running 64GB back in 2014 or so
      • timmytokyo 2mo ago
        Moore's law also applies to memory. With personal computers, we've gone from ~16KB in the late 1970s to ~640KB in the mid-80s to ~512 MB in the late-90s, to ~1GB in the early 2000s, to ~64GB today. If you look at the memory per dollar graph, it's even more obvious. This is exponential growth. I see no reason to think the trend won't continue for the next couple of decades.
        • xyzsparetimexyz 2mo ago
          Moores law is dead for memory and other things
  • 2mo ago
• nonethewiser 2mo ago
  The frontier models are obviously superior. The question is if progress slows down.
  • horsawlarway 2mo ago
    in what context, and at what ROI? Because... I have use-cases where this is true, and use-cases where this falls flat on its face. I don't actually think it's obvious (at all, really) without defining what "superior" means. In the same way that I don't think it's obvious that a plane is superior to a car, or a boat, or a bike. They each do things the others don't, and excel in different spaces.
    • nonethewiser 2mo ago
      Every single benchmark Again, that gap might disappear over time. But there is a gap currently.
• charcircuit 2mo ago
  You do realize OpenAI survived for years without LLMs, right? There is still more AI research they can do as a lab even if they stop experimenting with LLMs.
  • zbendefy 2mo ago
    I think they didnt have the amount of debt /negative cashflow as they do now.
    • charcircuit 2mo ago
      That is on OpenAI Group PBC. If that bankrupts it doesn't bankrupt OpenAI, Inc.
• satvikpendem 2mo ago
  They'll lobby to ban them, especially Chinese models, as Amodei is already doing.
  • mark_l_watson 2mo ago
    I worry about that but here are two positive things: 1. it would put us (USA) at a competitive disadvantage, and cooler heads will prevail in this fight 2. there are good US open models. I have the latest gemma4:27b with better tool support functioning at a high level in the pi coding harness. Thinking Machines seems to be on a good path, we will see what they and other US companies can do.
    • Terr_ 2mo ago
      > at a competitive disadvantage, and cooler heads will prevail I don't think this a safe assumption at all, given the the last few years of government policy where the "cooler heads" very much failed to stop such things. Either by partisan choice, or because they were silenced/fired for telling the Emperor that his clothes weren't there. In particular, consider the tariff-taxes [0] against on US importers, and the ensuing breakdown between America and its oldest allies and trading-partners. Also relevant would be the President's recent pet-project war [1], which has shut down a major part of international shipping. _______ [0] Unilaterally imposed by fiat, with idiotic "failed economics 101" math for the rates... and the majority in Congress still actively tried to keep it going, until the Supreme Court ruled it illegal. [1] Simultaneously a war and not a war, both already-won and ongoing, depending on which lies need to be told today to harvest applause and grab cash. Just this week the White House submitted documents to Congress claiming what's going on is a completely separate and new, second war with Iran...
    • satvikpendem 2mo ago
      Cooler heads, in this administration?
• eitally 2mo ago
  I think this is possibly true, but the other piece of the equation is tooling. Right now, Anthropic has by far the best tooling around (for both SWEs and non-technical users), and a huge ecosystem of integrated ISVs. I'm not suggesting it will happen, but if Anthropic decided to provide options of using models beyond Claude, they'd still have a significant moat.
  • pclowes 2mo ago
    I dont know. The tooling feels trivial. I swapped from claude to codex and back with zero friction. If they were very expensive to me personally I would probably just use them to build the harness and then plug Kimi into it etc.
• hintymad 2mo ago
  > open models is what will kill Anthropic and OpenAI. Maybe killing Anthropic is a good thing? Anthropic believe that they are the moral god and they get to determine what we can do and can't do, and they get to tell us what model to use and what not to use. I find it very counterproductive.
• blintz 2mo ago
  Are frontier models actually astronomically expensive to train? GLM 5.2 was trained on ~30T tokens, so ~10^25 FLOPs. Say you get B300's for $5/h (pretty high), and you get 50% MFU; that's ~$15M. Of course there's also a bunch of risk that the training itself goes badly, post-training, etc. But still, compared to the inference spend after, it's not that crazy.
  • avaer 2mo ago
    Nobody spends 15M on inference only to check at the end that their money was wasted.
    • user43928 2mo ago
      Are there resources I could read to learn more about how the labs work? I am curious about what changed since GPT 4.5 and other unsuccessful attempts to train large models, compared to now.
• figmert 2mo ago
  I hope so, but I am not holding my breath. OpenAI and Anthropic have too much money riding on them. I'll be surprised if they die.
• jenova-marie 2mo ago
  [dead]
• slashdave 2mo ago
  > Speculation At least some honesty here
• tcp_handshaker 2mo ago
  I did not know there was open source AI...Only open weights models.
• antman 2mo ago
  Speculation: Cheapest AI inference supply chain will win. Chips and energy. The chinese have made large investments in nuclear that will take decades for the US to follow and US has Chip supply chains that will take a few years for the Chinese to follow. We are probably at the 3T to 5T parameter models which are good enough for disruption.Given the supply chains we can probably expect paced improvements, unless somebody comes up with better training methodologies or mathematics.