Comment by wg0

18 hours ago

That's Kami Kaze for US frontier labs. There's no way from here for them towards trillion dollar valuations.

That's strategic sabotage to say the least.

Ban all open weight models! Cried the VCs.

> That's Kami Kaze for US frontier labs. There's no way from here for them towards trillion dollar valuations.

Those valuations are a scam, they have always been a scam, like an updated version of the collateralised debt obligations (CDOs) from 2008 [0]

[0] https://www.theguardian.com/business/2010/apr/18/goldman-sac...

I saw the same kind of comments when the first Deepseek model was initially released. However the relevance that investors assign to something like this does not seem to match the excitement expressed here.

I think they do not believe that big corporations in the US or Europe would actually use chinese models in their business operations due to security, regulatory and/or business continuity concerns.

  • > I think they do not believe that big corporations in the US or Europe would actually use chinese models in their business operations due to security, regulatory and/or business continuity concerns.

    They'd be wrong. Especially about Europe. Many companies are in a bind about this: they can't upload their confidential files to a service provider but they do want AI. So right now they end up with a choice: do nothing, breach their contracts, use a service provider that pinky promises not to share their data (which we have already seen they will violate) and run local models.

    The latter is the reason you can't buy powerful GPUs for reasonable prices because a local model (GLM 5.3, DS 4, etc) + some hardware is all you need to solve the problem in a way that avoids the legal issues.

    • You can’t buy gpus at reasonable prices because US frontier labs are spending nearly a trillion dollars this year on data center buildout, not because some mid tier European insurance co needs to serve deepseek

      16 replies →

    • The other choice is AWS Bedrock, if it happens to have the model you're interested in. They do have GLM-5.3. They don't have DS-4 or 4.1 yet, and updates are intermittent at best, but they're already on the trusted provider list for anywhere large enough to be interesting.

      8 replies →

    • You do realize there are hundreds of datacenters in Europe and the US that rent GPUs to European companies, right? You don't have to buy a GPU or even figure out how to use one. Pay for SageMaker.

      Europe isn't in a bind. They can, and have been, running open weights on inference providers around the world. And they pay a premium for US models and accept its risk for the same reason they remain US allies. The cost is worth it.

      1 reply →

  • > I think they do not believe that big corporations in the US or Europe would actually use chinese models in their business operations due to security, regulatory and/or business continuity concerns.

    Quite failure by someone to assume that EU businesses would use US over Chinese, based on the current political atmosphere. US causes even bigger concerns than Chinese labs.

  • > they do not believe that big corporations in the US or Europe would actually use chinese models

    This is exactly right. The only AI that matters from an investor perspective is the AI that is built into your phone, your car, ships with Windows and Mac, and built into legal and business tools like Lexus Nexus and Salesforce.

    Everything else is hobby.

    • That's why OpenAI hard pivoted from consumer tech into enterprise ?

      The only AI that makes money is enterprise. Being open weights/self-hostable is a huge win before the pricing even enters the conversation, but pricing is also adding a ceiling on what US labs get to charge. And stuff like powering other software also works better with fine-tunes, hence legal models, etc.

      2 replies →

    • Also the concern that open weights models could contain dormant adversarial behavior (i.e. they are sleeper agents) is more popular amongst decision makers than one would think.

      In that regard it was a clever marketing move by Anthropic to release their paper "Sleeper Agents: Training Deceptive LLMs that Persist Through Safety Training" ....

      7 replies →

    • I don’t know about investors, but EU businesses with regulatory requirements are favoring EU-hosted Chinese open-weight model over US closed-weight services.

    • to be honest anything built into my phone, car, ships with mac is a hobby

      what's important is where big enterprise point their budgets. and there we agree, it's not to chinese models (as hopeful as I am that we can avoid a duopoly and great local models)

  • >I think they do not believe that big corporations in the US or Europe would actually use chinese models in their business operations due to security, regulatory and/or business continuity concerns.

    Correct. And they're likely very correct in the belief.

    When people on the internet claim that frontier labs are done for because Chinese open-weight models exist, they really don't appreciate that the people spending the money do not want to hear "we can just run it cheaper ourselves!" Any software engineer with even a few years of experience knows that phrase is absurd, and executives are simply not interested in the risks associated with such an endeavour when they can just buy the solution outright.

    Consumers will have access to open-weight models just like how consumers have access to Linux. But you can just go look at the market share of operating systems to see why something being free and openly available doesn't matter to executives who just wants to get things done and is willing to pay a premium to a trusted business to do the work for them.

    And none of that even touches the fact that these frontier labs have only ever been in-front of open-weight alternatives. Again, if you're an executive, and you're questioning if you should pay a premium for a better version of a tool which you presume is important for your company's ability to compete, then the answer is immediately obvious: pay the premium or risk falling behind competition who is willing to pay the premium. And when you're talking about global companies who can pay these bills without it being significant enough to even show up on a quarterly financial statement, then it's an obvious sell.

    • Linux is actually a pretty poignant example here because Linux is not a "hobby" or "homegrown" operating system. Every server everywhere just about is running linux. When these software companies, who by the way are the ones who will be using AI, build software, they target Linux. They build their software to run on Linux containers then deploy them to Linux servers. If not their own, then servers running on the biggest cloud providers which all use... Linux.

      The piece I think we're missing is that, currently, AI is for software development. It theoretically has other uses, but nobody has found much of a way to capitalize on them. For the time being, most of the money being made is in models and harnesses for software development. There's already precedent here to use more open/cheaper solutions.

      Not to mention, if you make data security guarantees or have specific contracts, you can't even use US providers anyway.

    • >But you can just go look at the market share of operating systems to see why something being free and openly available doesn't matter to executives who just wants to get things done and is willing to pay a premium to a trusted business to do the work for them.

      That's why most of the internet runs on Windows IIS rather than Linux or BSD. That's why everyone here is running a VM on their Mac that hosts Windows containers to do development in.

    • > executives are simply not interested in the risks associated with such an endeavour when they can just buy the solution outright

      I think you're missing two things here.

      1. The margin by which a hosted product is operationally superior to self hosting an open source alternative is precisely calibrated. The SaaS provider has no reason to invest beyond the point were they can reliably make the sale.

      2. Self hosted open source solutions come with a big bonus re: the ability to read and modify their code. But realistically ain't nobody got time for that.

      AI upsets the apple cart in both cases. It's now far easier to manage locally hosted open source solutions, which means that in order to maintain the favorable effort ratio for making a sale, products must all get significantly better than their open source alternatives. That's gonna be a slow process involving innovative product owners. AI is getting better faster than it can happen.

      Also, since AI is trained on the open source code, it's very good at integrating open source components. Previously nobody was bothering to gain that kind of mastery over their tools but now you can leverage it right out of the gate--but only if you're using projects that are in your assistant's training data. Maintaining a moat around a software product has always been orthogonal to making your product useful, but as we lean on AI more, it'll get worse. The more you protect your IP, the more its usability degrades. This was always true, but now it doubly true.

      Executives may want to pay for a solution to their problems. But the companies that might provide those solutions no longer have a sustainable path.

      The future of software is as a tool, not as a product or a service.

    • There are times I wonder if the "just use China!" sentiment is astroturfing. That'd certainly explain why there's a lot of calls for that in the face of China's long and storied history of hacking Western networks.

      It's generally understood that for better or for worse, if you're working on anything (not just IT) that is security-sensitive, you're going to have restrictions on what can and cannot be done that may seem absurd at first, but hold up to scrutiny once more thoroughly examined. I would say that you don't even need to thoroughly examine this particular restriction. I have prod data at work that I can't give to humans outside of the United States. Not in India, not in the UK, not even in Canada. Clients insist on these clauses in contracts. This has been a known practice across many fields in this industry for decades.

      Now we're suddenly seeing a chorus of posts saying that we should loosen up and send data to a non-human intelligence that was developed by a known geopolitical rival with a history of malicious intrusion on Western networks. Where does that come from?

  • There were pretty specific rumors about IPOs happening early this year, up to apparent insider bets on prediction platforms. Don't you think the apparent delays in IPOs could have something to do with the open weights/open source competition? The monetary conditions (interest rates,...) were better early in the year, arguably predictably so, so what would be your alternative explanation why they chose to postpone?

    • Because none of them make financial sense yet and as long as the music doesn't stop they're happy to delay and take investor money.

  • Many big investors may be too deep into this, so they prefer to extend and pretend rather than cut their (potentially massive) losses.

    So, they choose to believe, lacking a better strategy. They will also try to lobby their belief into existence.

  • > the relevance that investors assign

    I think there is also a perhaps the need to assign air-quotes to "investors" when talking about the US markets.

    There's too much fluff and noise there. Too much (over)leveraged trading. Too much speculation.

    What the real investors think is hidden behind the actions of the speculative traders.

    > I think they do not believe that big corporations in the US or Europe would actually use chinese models

    The Chinese models are open-weight. You can download them and run them on your own servers. Or you can outsource to Mistral, Privatemode or any of the many other US/EU inference hosters.

    So the "security, regulatory and/or business continuity concerns" arguments are effectively non-existent. And whatever argument does possibly remain, also applies equally to Anthropic, OpenAI & co.

  • > I think they do not believe that big corporations in the US or Europe would actually use chinese models in their business operations due to security, regulatory and/or business continuity concerns.

    European business users (+ consumers) can access GLM-5.3 via Mistral.ai hosting. (with GDPR)

    https://docs.mistral.ai/models/zai-glm-5-3

    https://legal.mistral.ai/terms/get-started/

    • Yes, but that does not preclude the model from containing adversarial payloads so you still have to review everything.

      Of course the same goes for any other model that you haven't trained up yourself.

  • If you believe those investor, I assume you mortgage and bet all your wealth on it. SpaceX? Anthropic? Chinese has talents, electricity and Huawei. I really believe those investors are tulip blind to pile money into those western AI. China even now world number 3 ssd+ram ahead of SK Hynix. So armageddon of RAM SSD LLM model at dirt cheap price. And as time progress, large ram and small gpu will be built into handphone (which again dominate by Chinese).

  • This isn't true, especially not with the inference engine becoming public, now you can build your on models on the same or similar architecture and ship massive gains on top of these stacks.

    I think people don't realize the Salesforce SAP Palantir would love to ship these models, and they have/are shipping them.

    The threat of exfilteration of data via these models is high but it's nowhere near as high as the margins.

    For instance if you could cut your ai input bill by over 90% would you do it? Can you put some of that extra margin say 10-20% to make it more secure.

    I know of atleast 10 fortune 500 companies that are entirely planning to or have moved to Chinese models for a large portion of their work.

    It's insane people in finance are delusional enough to think that won't happen.

    Maybe Govt will try to de-risk with bans on using open models but I don't think that's going to work at scale, people will literally spawn labs to launder DeepSeek/GLM models into a US model by some novel training etc approach or something.

    I still don't think that it's as much a kami-kaze rather it's an attempt to normalize the world around the Chinese stack.

    If DeepInfer is supported by everyone, it will be much easier to export stuff aka hardware that only supports it for now or is optimized for it.

    Assume china starts selling hyper optimized Asics for inference at some point.

    This feels like a race to the bottom as soon as possible because they have much lower costs, if there is a Wipeout in AI Labs in US chinese labs are largely insulated, and they can hopefully buy Nvidia chips for cheap if that does happen.

    • Some activist VCs in Washington lobbying for dumb shit again

      Because they can and there’s no consequence to drumming up fear, same shit since the days of Napoleon and Nelson…

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  • If they are open sourced, it means any random data center could host it domestically and AI becomes a utility.

  • Europe is going to be just as worried about using US models for large parts of government related functions and they're going to feel alot better about open source self-hosted chinese models than US models which can literally get turned off on a whim by Trump. They'd prefere home grown models if they can, but if they can't they'll go self-hosted and that'll be Chinese at this rate.

  • The US will move to ban it for most major businesses in some capacity.

    You're entire company would become ineligible for gov contracts if you have use DeepSeek. Something like that.

  • lol big corporations are 100% using Chinese models in their business operations. They dgaf about security, speak to anyone in cybersecurity or cyber insurance

    The labs pushing this cyber scare is an attempt to cry wolf. The corps don’t give a fuck

  • > I think they do not believe that big corporations in the US or Europe would actually use chinese models in their business operations due to security, regulatory and/or business continuity concerns.

    Well they are wrong, I'm at a large EU startup and they are currently considering Deepseek as their default model, Opus/Fable would still be available for complex tasks.

  • There's very little understanding of business operations on HN, especially outside the tech echo chamber. The "software will eat the world" mindset.

    Based on HN comments, every company would be running Gentoo and developing line of business applications in Haskell or OCaml.

    • I concur. Everything is such a hard left turn.

      The reality is what ever better and cheaper is where the money flows. Especially from an international corporation perspective.

That's exactly what people said when Deepseek V3 was released. Two years later the valuations roughly have quadrupled.

> That's strategic sabotage to say the least.

It is clear from the beginning that the Chinese Open Model are a proxy for economic warfare. Anyway their singular goal is to dethrone US monopoly on SOTA model and burn all the economic hype and investments. If this strat works, which we will see after Anthropic/OAI IPO, we'll be in for an interesting ride

It's the USA, you can just ban it.

https://public-inspection.federalregister.gov/2026-21447.pdf

  • No, that isn't going to happen. The US can't afford to lose the AI race and US companies that can't compete will get thrown under the bus and replaced with those that can.

    The DHS order only bans buying DeepSeek products directly (e.g. doing inference on their China hosted servers). It does not apply to open weights at all. And DeepSeek just gave their response to the DHS order.

  • From government and regulated places perhaps but a large portion will not care

It's a project based on vLLM, explain why you consider it a total game changer?

>That's Kami Kaze for US frontier labs.

Well deserved too! The chutzpah of trying to peddle the AI equivalent to knives which refuse to cut flesh because it might be human flesh... astounding, and utterly disrespectful to their customers. Claude's guardrailing was so bad during OpenAI's HF attack that HF had to go to Beijing!!

I'm hoping Anthropic and OpenAI drop like stones on IPO. Never thought that liberation in this space would come from the Chinese!

Can you explain how this removes their moat? Genuine question, I'm not sure I understand enough about LLMs to get how an open source inference engine undermines them.

  • Today the closed-source giants maintain a substantial cost-per-token advantage due to proprietary inference tricks like speculative decoding kernels, ultra-optimized FlashAttention derivatives, multi-GPU pipeline orchestration and dynamic prefix-caching algorithms.

    I'm not sure whether the DeepSeek's open-sourced inference engine does all of these, but it appears that plenty of inference tricks have just been revealed for the open source community to learn from and start improving upon.

    • So... this makes it easier for someone in the position to run chatgpt class models as a service to get similar returns to openAI/anthropic, if I got you.

      And I imagine this engine is by default mostly just deepseek compatible and inference engines are not universally applicable to all models?

      It sounds significant for competition but I'm not sure how it sinks Anthropic/openAI. Presumably they still have their frontier models, the training data they're vacuuming from current users and access to hardware to serve at a ridiculous scale, right?

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    • I think you’re correct, although suggesting that open AI is a trickle drown of AI companies is a bit naive.

      But the key point is that something good enough always attracts more interest and contributions because a productive outcome is very realistic and tangible.

      Open Weight models and competing open source inferences engines massively undermine monopolies; in theory at least.

      See how cloud is easy to divest and “nationalise”.

  • What moat?

    • It is, and always has been, data contracts. Which is why the hyperscalars are a more likely candidate to take American frontier business than Chinese vendors.

      I can click a button in Azure foundry and run open weight models that are approved through my compliance and procurement teams.

      I don’t know how open sourcing this stuff helps deepseek but it means I’m getting ever better and cheaper models so I’m fine with it.

    • Well, whatever real or perceived moat Openai/anthropic had. OP claims this open source inference engine reduces their chances of high valuation, I'm assuming this is due to their in house engine being something they could use as differentiation before?

    • That is probably what has been the most fascinating part of this AI/LLM boom, the moat was apparently never the technology. It has been very much like nuclear energi (and weapons), once you know how to do it, it's not that difficult. It's still fairly hard, but you can do it. The moat has been the funding for the infrastructure and if that dries up you're in trouble.

  • In theory, this can allow a small US lab to compete with O/A/G and take marketshare from them with small open models deployed centrally or (and this is think is the real moat) on-prem for enterprises.

  • When the model is fungible and the switching cost is near zero (business logic lies in the harness), then there really isn't a moat for models.

If logic was in vogue then this would be true and SpaceX wouldn't be worth 2T dollars

  • Considering how absurdly far ahead of everyone else SpaceX is, 2T seems low, and is more of a testament to how immature the space market itself is at this time.

    If SpaceX was reset to 2016, they would still be ahead of everyone else even today. Their deployed capabilities today are ahead of the plans of most of their competitors.

    • even if they are far ahead, where does the revenue come from? current market size is like 20-40 billion annually.. even if it grows to 2x it's still a long time until that would justify the valuation.

      but perhaps you are thinking that starlink is the key? sure probably a bigger market - but any market it accesses is bound to eventually prefer ground lines.

      so the only way to justify the valuation is if the AI side of the business becomes the most dominant AI business

    • China is catching up there too.

      Anyway, where's the revenue from space going to come from? Obviously not data centres now that Deepseek is commoditising inference.

      The telecom business? Amazon is catching up there and Europe/the rest of the world is racing to build capabilities to not be dependent on Musk.

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    • It doesn't make sense by any standard valuation metric. Yes SpaceX is the best company in the world at getting things into space. The valuation doesn't reflect the actual size of that market at all. It's assuming AI in space will be world-changing, which is a huge leap to make.

VC and valuation (alone) backed success has never been dependent on a business or product being good. All that is needed is finding the bag holder(s), and the way our economy and financial systems are designed that's the core competancy of this system.

That’s why we will probably see Fable 5.5 this evening.

US companies are throwing money at the problem, and considering how good Opus 5.5 is I’m not too concerned about them.

Interference optimization is a solved problem with no moat. Anybody can achieve this result, optimize for a particular hardware, optimize for a particular problem. In general, software is no longer a moat.

The moat is custom inference hardware, lower power, higher throughput, etc.

Yup. Hyperscalers are going to eat them alive. AWS/Azure/GCP hosted instances of cheaper-but-almost-as-good models like Deepseek are going to eat OAI and Anthropic alive.

They'll need to release cheaper, better models to compete. Which may not be possible.

I wouldn't say yet its Kami Kaze.

The overall market will still be big, very big, if it replaces real people or augments every single worker.

Some contracts will go to your local provider (US Gov, etc.).

And there is still a moat between them and DeepSeek.

As long as i can afford it, i use Opus.

I'm not bound by it and switching is very fast

It's crazy that a ~400 person side project by a Chinese firm can put up such a fight.

All other models are also either by <1k labs or side hustles by tech companies who are not particularly known for LLMs

I don't gamble, but if you really believe this, there's apparently some serious money to be made.

https://polymarket.com/event/anthropics-valuation-end-of-oct...

These have not really budged (yet) on this news.

  • Aren't they betting on the valuations like a week from now?

    It's possible to be correct that the AI companies have no future, but not be able to time the exact month they collapse.

    • Present valuations are an aggregate of what investors (and speculators, in the case of the secondary prediction market) believe about their future.

      If by 'collapse' you really mean a 50%+ fall, timing is not going to make or break you by any means.

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  • there's hardly any volume there, so I wouldn't take it seriously. The last transaction was 4 days ago

Can you say more? Why would the inference engine be the secret sauce that would protect trillion-dollar valuations? Isn't the inference side somewhat of a known-quantity, while the training is more of the lab's trade secret?

This is not to rebut your point, but I think for a lot of people/teams the silicon valley "lose money until we make money" pricing from OpenAI and Anthropic will continue to win (assuming the numbers below aren't completely off).

I'm out of my league on knowing if these ChatGPT projections are close, a little off, or way off, but we currently pay about $5k per month for Claude for our whole team. The projection for "run Deepseek on AWS to replace Claude" is coming in at $30k+ for GPU hours.

No, that's open source and it will be an accelerator for everyone, instead of a small advantage kept by a few. Even the frontier labs benefit. I'd argue (like I did when the initial DeepSeek was released), that the AI market *needs* to those inference breakthrough.

Where are the competitor to the big frontier labs? The Chinese providers are demonstrating everything can be done cheaper and practically identical. I'm surprised upstarts aren't showing up.

Has anyone figured out why Chinese billionaires are releasing these models? Do they hold short positions on US markets? Why would Xiaomi, et al. release these models in the first place? What is the strategic purpose here? I cannot believe for a second that they are doing it for human good.

  • One very simple reason could be that the US has been very vocal about China being its geopolitical adversary (they may be right).

  • This really not that hard.

    Deepseek started as Liang's side project funded with his hedgefund couch change compute. That set the economics for everyone else in PRC. If deepseek releases for free because Liang doesn't give a shit about making $$$ on his hobby, every other PRC player has to follow. And serendipitously, due to US export controls, PRC tech companies can't dig themselves into ruinous seppuku debt buying compute even if they wanted to - what they can buy, i.e. everything around DC infra including power, they get for fraction of the cost expediently.

    TLDR Liang said fuck profits... which means every other PRC competitor had to fuck profits, which ends up fucking profits of western labs so deep in debt due to rampant financialization and can not afford to say fuck profits.

    Sometimes a billionaire is fine just burning $$$ on a hobby while remaining a billionaire instead of trillionaire, and it just so happens the side effect might mean preventing others from being trillionaires as well. Bonus others is geopolitical adversary who is hedging economy on trillion $$$ returns.

    • I'm still not understanding why one hobby projecing being open source means others should also be open source. So you're saying that PRC is making a bet against US companies and the US markets to crash them in order to stifle the US economy? That is an interesting take, I would think the US market is far more resilient than just the tech stocks. Speaking with my communist friends though, it does seem like this is the ultimate goal: Topple the US hegemony and US foreign control by crashing it's economy while China makes a bet on free/cheaper AI models, with the ultimate goal of agitating the people enough to cause a revolution to turn the US into a communist state (really delulu stuff if you ask me)

      Seems kind of pointless? Wouldn't anyone in the US/western world simply use the chinese models in their own inference? That would not strengthen the Chinese position because the models got downloaded for free off HuggingFace, and then cloud inference bills would just put money into US companies.

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> That's Kami Kaze for US frontier labs. There's no way from here for them towards trillion dollar valuations.

I don't understand the reference to Kamikaze in this context. Is Deepseek destroying itself in order to deep-six US frontier labs?

  The term is used generically in modern warfare for an attacking vehicle which is itself destroyed when attacking a target; for example, a kamikaze drone. [0]

0. https://en.wikipedia.org/wiki/Kamikaze

Deepseek came out of a hedge fund, right? Do they just bet against US stock and release for free a pile of stuff that basically shatters them? I never seen anyone saying that, but it would be an awesome business model.

I hope more hedge funds start doing that. Basicaly funding open development to profit from tanking uptight super serious American stocks, to fund even more open development.

If you can't beat them, give the common folk means to skip them and profit from their fall.

  • I'm betting that China is betting their government can better handle the massive unemployment these will create within the white collar labor force.

    • This don't need to be Chinese hedge funds. Western ones should be doing that as well.

      Drop a few mil on tokens to make enterprise grade database to put out for free and bet against Oracle. Or train a model, or something.

There will always be special demand for the "best possible" and "fasted around" inference and they will pay. "Good enough" models are useful for many tasks but cannot replace the whatever frontier is at the time. That's why the top 2 labs are rake in ~80% of total inference income.

I don't see how this proposition holds. It's just part of an inference engine for serving DS4.1 Flash. Which vLLM and SGlang can already do. Less efficiently, I'm sure, but on much broader hardware, and with other models in the mix.

People will take the novel bits here and port them to the above. The community as a whole will benefit. Including infrastructure engineers inside OpenAI and Anthropic.

But a lot of what's in here is already in published papers out of DeepSeek already.

Sure, any day now DeepSeek is going to destroy the valuation of OpenAI and Anthropic. I've been hearing this since DeepSeek first launched in Jan 2025, 21 months ago. And with every new model generation, both open and closed, I hear a chorus of "this is now good enough!". And then I hear it again for the next generation.

Meanwhile OpenAI has grown their revenue like 10x and Anthropic has grown theirs like 65x in that same time period.

There's no cap on what you can do with frontier intelligence, nor how much of it you can use. Yes, DS and other open weight models will continue to grow like crazy (as long as they can source compute), but so will the frontier labs. I ran like 20 agents overnight last night on Opus, Fable, Sol, and Astra last night, trying to use up quota before my weekly reset, and I'd gladly have done 10x that much and used agents 10x more intelligent if I could have. And in six months I probably will.

how? openai can copy some of the ideas on top of their own. Smaller labs gain this tech without much development, but is isn't like they will magically beat frontier labs. Is a smaller deal than you think vs kami kaze.