"However, these inference optimizations, which rival Anthropic refers to as “compute multipliers,” are a big focus for all the labs. Anthropic CEO Dario Amodei has been publicly talking about the concept since at least mid-2023, when he said on a podcast that the company limits “the number of people who are aware of a given compute multiplier” because it could give other AI labs a leg up if they were to be able to replicate them. (Compute multipliers can also refer to efficiency optimizations in the model-training phase.)"
Yes, on a world with finite resources where your industry is singlehandedly siphoning ALL THE RESOURCES - hoard general efficiency optimizations and treat them as trade secrets - winning is all that matters, normal people and other species and the planet be damned.
Everything I hear about Dario these days makes me like him less and less. He sure did seem to speed run the 'tech leader with scruples' to 'tech villain' path! I guess all the cycles are compressing as we approach the singularity..
Not sure I know where I fall regarding your point: Yes to trade secrets, but also science and AI should be for the good of all.
OpenAI seems to be trading roles back with Anthropic becoming misanthropic. I hope they both start heading in the direction of how the AI field was prior to LLMs.
Collaboration and benefit for all should always be the primary motivator.
> Collaboration and benefit for all should always be the primary motivator.
Of all the things to never happen, this is never going to happen the most.
That train left the station for good once hundreds of billions to trillions of dollars were involved.
On the bright side, in the long run I suspect the vast majority of the value of AI will not be captured by the model making labs and the vast investments in them are going to implode, so...
They're in a price war with the People's Republic of China running flat out with the full backing of a government that literally does not care if they ever see a financial return on the investment, they just want to drive the value of LLM training and inference to zero because we banked the market on it being arbitrarily high margin forever. China was like hold my beer.
They have a staggering surplus of grid capacity and can bring more online without any difficulty. We couldn't get a serious nuclear project done if Jeffrey Epstein was offering private flights to the ribbon cutting.
In the United States at any given time more than half of the FLOPs are badly misallocated, Meta has like, a double digit percentage of the total capacity going down the drain every day and has for years. That's a conspicuous example but on OpenRouter rankings it's rare to see more than one or two American vendors in the top 10, sometimes the top 20. But 3rd, 4th, and 5th place are all merrily burning half the compute duplicating effort and missing key innovations because we stopped publishing real results. In China if DeepSeek makes a breakthrough it's at Zhupai and Moonshot and MiniMax and MiMo and Qwen that week.
Our only lever, export restrictions, seems to do nothing but breed multiply antibiotic resistant super hackers who just get more efficient and immediately propagate all of those efficiencies to the rest of the Chinese AI industry.
At the beginning of 2026 there was one Chinese lab with a model that had any real relevance fielding modern tool users. Today in July there are like, eight lagging the absolute frontier by maybe 3-6 months. Barring some massive bend in some curve 3-4 of the top 5 and 6-8 of the top 10 will be Chinese and open weight by January.
The great irony in all of this is that our current playbook is straight out of the 1960s USSR, and the PRC's current playbook is straight out of 1960s USA. We're the ones with the opaque decision making and gross resource misallocation driven by the personal agendas of a shadowy cabal of frenemies wired back channel into government in the form of the individuals rather than the offices. They're the ones with a thriving marketplace of ideas powered by robust public/private partnership and a paved path running bidirectionally to the university system.
It's going to implode because the Kruschev system does. Theirs is going to thrive because the Kennedy system puts a man on the moon before the decade is out.
>full backing of a government that literally does not care if they ever see a financial return on the investment
There's no evidence of this, the parsimonious explanation is PRC AI, by virtue of being sanctioned, simply is not able to run magnitude more expensive compute model, and even if they could, they don't have the $$$ or market cap to do so. So they optimize and involute margins like they do in everything, and US misallocated expensive flops because the entire industry has been financially engineered for phat margins along the entire producer supply chain is just cherry on cake. Like wipe out the 50%+ margins from toolmakers, fabs, gpu/memory/data center components to some reasonable level and US is overpaying for tokens by a stupid multiplier on top of actual compute misallocation due to incompetent infra. Maybe PRC AI has unsound economics, but it's structurally simply not able to misallocate as much as US who will find a way to financialize compute to point of absurdity.
If the Trump administration decides to annoint Altman and Amodei in defiance of market forces it will rapidly discover that it no longer has the sovereign bond auction pricing power to prop them up. This isn't 1998: the Treasury has taken five major body blows in the last 25 years, the world's energy markets, maritime insurance regimes, electronic payments rails, and moral authority in places like the UN Security Council are effectively bifurcated. Oil and money and data and people just flow around the United States now. Canada's sovereign debt yields tank harder when the market is spooked, that's the North American flight to quality.
The administration could probably put some serious friction on open weight model use in the Fortune 500 for a little while, but the opposition never got such a gift right before a squeaker midterm. And outside of major enterprises with puckered ass compliance departments? Not a chance. It's popular around here to forget Uber and AirBnB and yes, OpenAI and Anthropic all got their start flagrantly breaking the law and grew lawyers and lobbyists faster than anyone could enforce it. And this time everyone from the DNC to the EFF would be holding hands wearing "Save The Models" t-shirts. Not even NVIDIA is remotely pretending they're anything but all in on GLM 5.2, they had an NVFP4 quant up by the time most people read the blog post.
And the Trump Administration isn't exactly enamored of Comrade Amodei at the moment, being as they're appealing the lawsuit Anthropic brought against the Pentagon during a shooting war.
Forcing the American proprietary AI megalab financing event was our fiscal Ukraine Special Military Operation, the market is calling the bluff and neither the capital markets nor the Federal Reserve has the dry powder to absorb this one.
The Treasury auctions will flat not clear in an orderly way. We can't raise 2-4 trillion dollars on a dime in 2026 and if CoreWeave turns out, as many suspect, to be Patient Zero? It would be that big a hole.
We play by the same rules as everyone else now. I hope we regard it as being worth it, but I fear we will not.
It is in OpenAI, Anthropic, and the US Gov's best interest to slow China down and ban Chinese models. Literally none of what you wrote prevents them from doing so.
Once China starts to get scary, Commerce will export control GPUs and declare Chinese models "foreign munitions." Any nation doing business with the US will not be allowed to use these models either, and that will be the end of that.
It is just not in the US's interests to fund China in the race to AGI.
The assertion that it's in the United States Government's best interests ban Chinese open weight models is a very strong opinion that is not a consensus even at the fringe of Thiel-adjacent psycho thought: Alex Karp is on record about open weight models being necessary, the fucking "we bombed a bunch of kids with Claude doing rubber stamp target selection" guy. He thinks "trust OpenAI and Anthropic" is a radical position.
Peter Hegseth, another really pro-America being powerful guy, he's dealing with a lawsuit because he doesn't want Anthropic in his military, he calls it a supply chain risk (he's right).
There is no evidence of any kind that a complex attack vector can be trained into model weights and survive all the crazy slicing and dicing that happens between published weights and running model. These things get quantized and run on mathematically imprecise kernels and sampled and LoRA-tuned and Dolphin/Orca de-tuned. Go look at what the ComfyUI community comes up with, those guys know more about WAN 2.2 than the people who trained it. Because those models run for real on a desktop, so there's mad innovation at light speed.
There is no one who wants a capriciously expensive black box run by extremely creepy people, not once the capability crosses over (in about November).
But don't take my word for it, you just had a chance at one AI IPO, and I'm sure you'll get another, so if you like how that goes, you don't need to convince me!
We are in a race to ASI. The first country to AGI will be the first to ASI, and the first to ASI will have de facto control over the world and the future of humanity. They will also be able to prevent others from reaching ASI.
Of course it's in the US's best interest to slow down China. You aren't zooming out and looking at the big picture, you're taking models as slightly useful tool, not what they will soon turn into.
Global power does not run on kumbaya vibes. Superintelligence is a zero sum game whether you understand why it is or not.
I'm glad you trust a country that literally imprisons, rapes, and murders their human rights lawyers though. And one in which you cannot even criticize the government without being disappeared. Surely such a country is best positioned to have total control over all humanity, forever.
Again, none of what you're saying will make the US government, especially the current administration, care, as they have not cared about many things with consequences either; you're applying logic where there may not be any heed to it.
As well, it is a false equivalence to say that local models are only Chinese and otherwise we would use cloud models, but there are American or European ones, so a ban would simply force companies to use these, even if they are inferior to Chinese ones. It's simply a matter of national security to the US government, and they will not care what random people in media say.
The Pentagon classifies Anthropic a supply chain risk and is appealing a ruling with vigor to reinstate the it's right to decline doing business with them.
I don't know what part of this you guys are having trouble with, but it doesn't get a whole hell of a lot more emphatic on "what the US Government thinks" than who the Pentagon is in court with to avoid doing business with that party.
Mr. Hegseth is the representative of the administration in the AI usage policy of the largest bureaucratic organization in the history of civilization. He has emphatically rejected at least one black box American AI megalab and President Trump has endorsed this action on Truth Social.
The government's stated position is not what you among other commenters are stating or implying as the government's position.
OpenAI has ties to the government (via political donations) which likely will be getting that 5% stake too, so it is not just for Anthropic that the US could ban Chinese models. Consider, why wouldn't they when they already were considering it?
And you mention Hegseth but it was Lutnick at the Department of Commerce who banned Fable, so there are many competing parties in the government. Again, it is not just Anthropic who'd benefit from a Chinese model ban.
NVIDIA appears to play on several parallel paths that may compete with each other.
On one hand it appears to cooperate with OpenAI and Anthropic, as big customers.
On the other hand NVIDIA cooperates with Palantir, providing the HW for its "Sovereign AI OS" (a turnkey system including HW and SW for local inference and post-training/fine tuning) which uses the slogan "The future of AI is on-prem" (i.e. not as a customer of OpenAI or Anthropic, but using an open-weights LLM, e.g. a fine-tuned NVIDIA Nemotron or a Chinese LLM).
Presumably with the goal of promoting their competing solution, Alex Karp (Palantir CEO) has delivered a few weeks ago a very harsh criticism of Anthropic and OpenAI (who allegedly inflate the token consumption and they might also steal the data of their customers, which must be sent to them).
So NVIDIA both cooperates and competes with OpenAI and Anthropic.
As of writing, https://openrouter.ai/rankings shows only Opus, Sonnet, and GPT 5.5 in the top twenty by usage (Opus and Sonnet both have two slots on the 4.7/4.8 and 4.5/5 splits respectively, read that how you will).
I don't know how much business OpenRouter does in Europe (they have some GDPR text in some settings pages I think) but it's zero in China.
You might also consider the countless companies that do nothing but open weight LLM inference: Together (of Tri Dao fame), Fireworks (founded by my old colleague), Baseten, SambaNova (of Chis Re fame), and too many more to count, there's a new one every week. Plus NVIDIA does a ton of this business via NIM and shit.
I'm trying to be reasonably polite because it's possible you literally didn't know that, but this reads as a troll, so, if it is a troll please stop.
Misleading first sentence, as most use OpenAI and Anthropic directly via their own LLM not through OpenRouter. But you're right that lots of companies use open weight and Chinese models, not sure how the parent got to their conclusion.
because in the us you get plenty of people who refuse to buy non western products solely because they are not western. like chinese cars which were banned.
> They're in a price war with the People's Republic of China running flat out with the full backing of a government that literally does not care
There is nothing to support this. You get cheap Deepseek tokens by foreign providers too.
It is the same thing with automakers. They complain about not being able to only make luxuary cars with high profits with BYD raining on their parade and blaming the Chinese gov.
I find this kind of cynicism fascinating tbh. On the one hand, it seems so relatable in some ways, because there is something uncomfortable about being seen as naive, in a way that being seen as cynical or negative doesn't seem to carry. I guess it's just self-protective, almost like some kind of perverse Pascal's wager: it's better to think everyone is horrible and be wrong than to think the opposite and be taken advantage of?
The thing I can't quite square is that it doesn't really fit my lived experience. I have known sincere, genuine people in the types of positions that I'm sure someone like you would declare to be sociopathic.
But beyond that, I just don't know why it would actually be true that everyone at the top is a villain. Why couldn't someone like Dario (or even Altman, gasp) be sincere? Because if he is, it does seem like a lot of the moves he's made would make sense given his worldview.
But if you assume he's just a villain, then you can twist any of those moves to just be further evidence of that which you already believe.
I don't know, I just find cynicism interesting, and a little sad.
It stops being interesting, or even sad, after a while. People get stuck in all kinds of places, mentally. Some get unstuck eventually. It’s only sad if you have come to a counter factual belief that it could have gone better.
I went in the opposite direction - how far can I push myself to see multiple facets of a story? That is a wild ride, and it gets progressively more wild.
It's the Tragedy of the Commons. There will always be a vacuum of predatory bullshit that can be filled, and the victor is always the biggest sociopath. Rockefeller, Cecil Rhodes, Elon Musk, it's the same traceable pattern all the way back through history.
Why should I treat Sam and Dario with special white gloves? Are they different, this time? They have peers in China that do the same research and actually release it to the public. They let you run the production weights on your own machine. Am I a cynic, for comparing these CEOs to their populist superiors? Am I stupid for assuming their hostility when they refuse to give us the benefit of the doubt?
I'll believe their actual altruism when I see it. Both are seeped in "boy genius" puffery and lie out their ass. If this is the future of intelligent innovation, America is in decline.
The only reason Chinese labs release their research is because they are behind. They lose nothing by doing so because the alpha has already been discovered.
This is not hard to understand. Do you really think DeepSeek would publish their algorithms if they led the American companies? Lmao.
Except this is clearly not true. Opus-tier models like GLM 5.2 have their weights freely available.
Even when they're reaching parity with American models, Z.ai, Qwen and Deepseek are upholding their end of the bargain. I'd criticize them too, if they were due any scrutiny.
I use GLM 5.2 daily. Calling it Opus tier is a bit of a misnomer. It is maybe comparable to Sonnet 5, definitely not Opus 4.8. It is a great model but it has poor long context performance and I don't trust it for anything beyond personal projects, whereas I use Opus and GPT for work.
do you use american models at work because you choose to or because it's what your employer gives you? is it due to compliance with the american government? two different reasons. most people just use whatever they are given at work.
You don't have to assume anything. A true "good guy" doesn't openly say that he's fine with autonomous, AI-powered weapons being used against me, and mass surveillance applied to me and my family just because I don't live in the US. A true "good guy" doesn't say "privacy is a human right", and then immediately (and completely) bend the knee to an authoritarian government on this issue.
For sure, I am assuming they spy on a lot more people than they drop bombs on.
I remember a long time ago it came out that the US had been doing mass spying on the Danish people, my dad was very upset about it and disliked the US for the rest of his life. Of course the only thing he did about it was not watch American movies anymore or visit the US.
Anyway,
I assume it will be a case of a million little paper cuts, each thing putting off a group of people until someday it adds up to real meaningful economic impact.
It's a lot easier to sound smart on the internet if you're a bitter cynic.
Lots of nerds for some reason have made cynicism a personality trait. They think optimism/honesty is hopelessly naive, therefor cynicism is the correct default.
> Lots of nerds for some reason have made cynicism a personality trait. They think optimism/honesty is hopelessly naive, therefor cynicism is the correct default.
It is the result of experience. Working with and creating systems (even embarrassingly simple ones), then seeing them fail in a myriad of ways more often than succeeding, colors your expectations about throwing humans into the mix.
Children learn to lie as part of their natural development, but do not always externalize that until faced with media (Airheads candy commercial or equivalent). Either way, honesty is expected as a default for utility and not an expectation in leveraging goals.
Power corrupts, absolute power corrupts absolutely.
Given enough money and increasingly perverse incentives to gain even more has a very high potential to corrupt.
Did they start out as corrupt, or was it the influence of the power that came with the obscene amount of money?
It's really a chicken and egg level of calculus.
Doesn't matter which came first, either way you get feathers and chickenshit all over the yard.
Do some very rich people still seem very nice in person? Sure. Of course they must, because otherwise no one would willingly work for or with them. As the total amount of money goes up, the incentives to remain 'seemingly nice' go down and either you get to see who they really are, or who they became through the choices to make that much more money. Doesn't matter which is true.
The examples of non-villainous billionare are rare.
Of non-villainous multi-billionaire; lets see there's about eight of them that stand out for giving significant amount of the massive wealth to helping the world around them, who live normal lives like the people in the communities where they reside, and who participate at the companies they own by eating in the company cafeteria among the people who earn the wealth they enjoy.
Thats 8/3400 global billionaires ... about a quarter of a percent.
And of the 'pledges' like Giving Pledge by the billionaire class, the actual amount delivered - not parked in a family or private trusts for tax deductions; but actually delivered to the front lines of any global crisis amounts to 0.18%, less than one fifth of one percent of the $20.1 TRILLION dollars held by that class of owners. thats less than $2.00 on every $1000.
That's not to say that donating to public needs is 1:1 for non-heinous behavior, but it seems like a basic tool for distinction. the 'can make a significant difference in global suffering : chooses not to' ratio as a surrogate for villain may be useful metric and doesn't require cynicism as the underlying rationale for calling someone's behavior as unkind in general or mean in particular.
I thought this stuff was common knowledge. I didn't expect to make people angry by insinuating that Nadella, Cook and Pichai are also socipaths, but I guess we have a bit further to fall before people learn the lesson.
Dario tells the truth. If you look at everything through their safe AGI mission it all makes sense. They are not bs'ing about that. Also I think most people just read headlines or 10 second clips and make false extrapolations from there.
(BTW Anthropic only exists because Sam Altman is a liar, Dario admitted this.)
A no-investment policy would take them off the scene entirely. Essentially handing over the reins to OpenAI, Google, and others. Their position is something close to "if I don't do it, someone worse will".
There's a more nuanced discussion that could be had about how to balance relevance with outside influence. But at a foundational level it should be acknowledged that the tradeoff exists, and that receiving outside investment can't alone be seen as evidence of corruption.
Besides that, there's more that can be said about other things like their corporate structure or the degree to which they accelerated the AI race.
Of course that's what Dario thinks because that's what every tech CEO thinks. Dario, Sam, Sundar, probably many Chinese CEOs as well. It's what everyone thinks. That's why they're competing so fiercely with one another. That's why they basically make all the same decisions. That's why we need properly open source AI.
It's hard to be certain what each individual thinks. We can do our best to judge based on what they each say and do. And there are significant differences in what each of these individuals have chosen to say and do over the years. The info available to the public makes it seem a lot like Dario's motivations & priorities differ from those of Sam and others.
This doesn't seem like the right place to spend my time litigating that point to its fullest extent (no-one here is doing that). But there's plenty of relevant info surrounding eg.:
* The New Yorker article on Altman [1]
* The story behind Anthropic's founding
* Various efforts to influence government policy (a16z policies and contributors [2], Trump's inauguration donors [3], giving Trump credit for AI infrastructure [4], Dario's op-eds [5])
i really hope it's just what Deepseek V4 does. Deepseek V4 is very cheap and highly performant
OpenAI tried to pull off the same trade secret thing with RL when they announced o1 and o3, aka "Compute time scaling". Then Deepseek revealed it with Deepseek R1.
Could also be something like Deepseek DFlash. Or using diffusion like DiffusionGemma as a draft model. The timing between the release of those, and this article, makes me think its maybe one or both of those things
> the company limits “the number of people who are aware of a given compute multiplier” because it could give other AI labs a leg up if they were to be able to replicate them.
I wonder if that makes sense if the orgs within the industry are starting to shift their mindset towards "Tokens are expensive, we should use AI less." which feels like an existential threat to the status quo, if those AI providers can't find ways to keep costs affordable for their clients. Otherwise those orgs would just be using GLM 5.2 or DeepSeek V4 Pro but it seems like what they're doing instead is trying to use AI just less, period.
I agree that Dario is pretty annoying, but I think the "tech villain" archetype is essentially survivorship bias. The tech leaders who don't act that way are not nearly as visible because they're not nearly as successful.
HN is just a massive Anthropic hate fest now, probably funded/manipulated by OAI's $8B PR budget.
OP phrases it as a bad thing that Dario is keeping compute multipliers to Anthropic. How naive can one be? Compute multipliers are the whole business. Those are the trade secrets every lab is built on. It is the alpha of the business. How does protecting this make Dario evil?
This website is getting out of hand with the uninformed hot takes. I wish when HN was still people that knew what they were talking about.
I'm not as conspiratorial as you, but it does seem the tide of opinion here is turning against Amodei, for no particularly obvious external reason. At the same time, there does seem to be at least some evidence of adversarial attempts to oppose data-centers by America's competitors.
Ok I’m not sure I follow your point here. Isn’t all that he’s saying that if they find some optimization techniques, that gives them an edge? And that makes sense?
How is this suddenly evidence of him being a villain?
It has got to be one of the most insane takes I've read on HN, which to be fair has been trending towards "unhinged" when it comes to Anthropic and AI safety.
Compute multipliers are like a quant firm's trading algorithms. They're the crown jewels, the whole alpha of the lab. If you leak them, the lab dies.
Protecting them does not make Dario a villain, it's literally his job. It's also Sam's job, Denis's job, Mira's job, etc. Every lab guards these multipliers closely because they represent the entire worth of the lab.
oh here we go again saying everything in china is done by the state. it's not a democracy but they're not the soviet union either. if that were true, why don't they have just one model initiative instead of several?
The fact that they don’t release model weights for free to download on huggingface means that Sam, Mira, Dario, etc are ontologically evil and may they all reincarnate as either durian fruits or cockroaches, ideally as durian fruit infested with cockroaches…
The evidence is that unlike Deepseek he does not publish his compute multipliers. Under that argument Deepseek should not publish any of their research either.
But Deepseek has a very different way of operating their business as the underdog. They also publish their models as open weight, which Anthropic also doesn’t do.
Keep in mind, these tech leaders have deluded themselves with the infinite jest of "effective altrusim" which can effective ignore any problem today for some imagined future problem that they're solving. So if they have to enslave the human race because there's a super killer asteroid 10 million lightyears away heading towards us, they'll do it, because obviously, saving future humanity is the only thing that makes sense (because only their genius can save the day)!
Side note for other readers: Parent is describing a reductio ad absurdum of utilitarianism, which is a distinct (but sometimes overlapping) worldview from effective altruism.
The primary effective altruism cause areas are extremely acute and high-scale problems like malaria, vaccine distribution, and factory farming
Semi-related, has anyone noticed their GPT 5.5 usage in Codex being cut in half as of a couple days ago? I got a lot more mileage out of my session usage yesterday for the same workload.
I've noticed less quota and 5.5 intelligence degrading. I didn't run the analysis like the post the other day, but I had noticed decreasing ability to complete tasks, more laziness. Switched back to 5.4 and it's much better. Maybe they're getting ready to launch 5.6?
I wonder if AI labs are actively manipulating the narrative (and thus investor sentiment) by airing problems, and then solving them weeks to months later. I wouldn't be surprised if they have a lot of stuff figured out that is not included in the current version, just to make a steady product cycle with years of tangible improvements from one version to another (this is a common practice in the industry).
For example, if inference isn't too expensive, but they figure out how to cut costs, then price goes down. After all, why pay OpenAI when a smaller datacenter can give you similar models?
But, if they make a huge issue about how inference is too expensive, they engineer a crisis of their own creation - then, once they deploy the solution (which they might already have), then they're back on top.
> Additionally, we’re introducing a new ultra mode that goes beyond the capabilities of a single agent by leveraging subagents to accelerate complex work.
For pro mode the agents worked independently and only when they all finished did a new agent take a look at everything to merge the work into a single response. The new thing involves subagents that have been trained to cooperatively pursue a task and are allowed to communicate with each other along the way.
I tried a pro model out the other day and thought there must have been a bug in Pi’s cost calculations. But no, it’s absolutely fucking insane. Wasn’t even any better at the task.
They made it up. It's not true so there's no source.
They might be confused by MoE but that doesn't work like how they describe and all GPT 5 models use MoE not just Pro. Or they're confused by how thinking summarization works but again that's all GPT models.
> We generally treat GPT-5.5’s safety results as strong proxies for GPT-5.5 Pro, which is the same underlying model using a setting that makes use of parallel test time compute. As noted below, we separately evaluate GPT-5.5 Pro in certain cases because we judge that the setting could materially impact the relevant risks or appropriate safeguards posture.
Any idea what that means exactly? I vaguely remember that ChatGPT Pro was originally called "deep thought", just like Geminis "deep thought" feature (or "deep think"?), so it seems likely they are using the same approach.
Its widely accepted[1] that it runs the same query through the model in parallel and then has a model that either selects the best answer or synthesizes an answer from the multiple ones generated.
I believe most people think it runs 6 sub-models, but I think that is based on the pricing.
It's a pity that OpenAI doesn't publish details like this.
How is this any different than what we have already? We've had this ability for ages (6+ months, decades in the AI world), you can literally today easily prompt CC or Codex to use subagents to accomplish tasks and they'll do it well. My entire workflow is one top level orchestrator chat creating tickets to dispatch to subagents to implement, and other subagents to verify. Why is this being sold as a new thing? Have HN users never tried tried asking CC or Codex to use subagents?
I assume this is ~equivalent to ultracode in Claude Code, which can deploy a tree of hundreds of nested subagents and was just released experimentally 5 weeks ago IIRC.
I'd love to read more about how to use this workflow. What kind of top level instructions does this actually work with? Is there an article out there with some concrete examples of how to do this effectively?
I would assume yes - their goal is to capture consumer subscribers. Claude are going to take Fable away, and they're going to swoop in and give it to us.
Still avialable through the API. According to people that have tried both Fable nad 5.6, Fable is clearly better at coding. So i expect a lot of people to pay extra for it.
You’re not kidding. I ran out of Fable tokens a couple days ago, loaded up $70 just to finish the task we were working on, and burned through it in about 15 minutes.
I still don't know why OpenAI doesn't put gpt-5.5-pro in Codex. It's one hell of a model and easily parallels Fable/Mythos. Sure, it'll use up your quota much faster but that's the price some users are willing to pay for absolutely high quality responses.
I think gpt-5.5-pro runs 12x parallel gpt-5.5 agents behind the scene and uses OpenAI's secret sauce to synthesize their answers into one insanely good response.
Is it as good as Fable..? Fable is the first model that mostly writes without the AI slop format for me, and so I can comfortably actually copy and paste most of what it spits out.
OpenAI models have always been the worst in my experience for verbose, slop formatted responses, with each generation increasing in sloppiness.
Why can't you reply to hn_user2? I just did. Did you say something mean to hn_user2 and now you have a restraining order and can't go near them within one reply?
I recently have been testing ChatGPT business at work and the quota seems to disappear almost instantly even using weaker models. Unless they dramatically increase their quotas it’ll be unusable.
I don’t know how anyone can realistically use the “business” plans - you blow through your quota so quickly. I use a consumer Pro account ($100 a month) and don’t hit the usage limits nearly as quickly. 5.5 Pro is so slow that it’s not a big deal to paste big prompts into it and come back and check on it an hour later.
My solution for the ones stuck with that: use 5.5 for planning and 5.3-mini for the grunt work. 5.3 is remarkably useful still but you need to hold its hand.
API pricing ends up being something like 20x more expensive for GPT 5.5 Pro than GPT 5.5 for actual work, even though the token cost is "only" 6x. On benchmarks where I've run both, I saw $1.12 mean per task with 5.5 and nearly $23 per task with 5.5 Pro, I guess it chews longer and harder on the problem.
If that's at all reflective of what it costs them to run it, I imagine they're in the same boat as Anthropic with Fable; they probably can't afford to offer it at subscription prices given current cost to operate it.
If 5.6 Sol Ultra has efficiency improvements (at one or more layers), and it allows OpenAI to offer a model that's competitive with Fable on the subscription plans, I'll guess a lot of folks will switch.
Fable is notably better than what came before. I watched it figure out stuff on its own over and over, on extremely hard problems, that I previously needed to guide a model to an understanding about, or work with them back and forth for several turns to figure it out together. Like, I've been reverse engineering a hardware device lately, and I've tried to tackle it a few times in the past with both some version of GPT and a couple of versions of Opus (most recently 4.7). In all cases, I barely made progress...would have gotten there eventually, probably, as I'm stubborn, but there were roadblocks constantly, with me and the model getting stumped and going around in circles in the end on every prior attempt.
Fable figured out other ways to find out what's happening, it dug into config files, found and extracted Boost-serialized data, compared that data to the observed behavior, built tools to compare the observed data with our emulated behavior, without being prompted. Would I have gotten there? Eventually, maybe. All prior models didn't; they mostly just tried the things I suggested and stopped at "well, that didn't work" or declared success after seeing results that matched their misunderstanding of the problem. I guess it possible my prior attempts with other models has "loosened the lid" on the problem; we did already have a long list of documented "this didn't work" and a pile of tools for finding out if something work. But, even so, I was impressed.
There probably will still be a "OK, let's rewrite this so it's not using lookup tables to precisely simulate the hardware behavior in software, because we don't need the noise, too" stage of the process...but, in one day with Fable, it solved a problem that I'd banged on for at least a week or too in the past with very little real progress. I don't think the models write exceedingly good code, even the best ones, but it sure does figure shit out quick.
> GPT-5.5 Pro does not offer a cached input discount.
I think this tells you in one line. It's basically set up for one-shot inference right now, by the looks of things. If you use this in a harness, it would almost immediately fall apart on cost. Not to say that they couldn't make it work, just saying that at least as it's delivered currently, they haven't done so. On the web, there might be doing something to get the equivalent of that behavior internally, such as keeping the session truly alive on GPUs rather than using their external-facing cache-style approach.
I'm working in large US corporation.
And I see that I already have access to 5.6-Sol Ultra on my corporate account.
I haven't really used it yet.
2 months ago management was showing us scoreboards, praising leaders who used most tokens.
Last few weeks, we're getting weekly emails, telling us that whenever we can - we should use cheaper models, and that we should watch the page which shows our tokens usage.
No, the clue is people realizing that relying on the tools costs too damn much. The tools are fine-ish for what they do, but there might be a bubble built on unrealistically high expectations of revenues.
Sounds like a bad idea in general. Any data use agreements get lost, shadow-IT brews and nobody knows what tools to use, oh and it's against the service terms.
I pitched this to management as a way to get a very expensive fine tuning job done for free. They're not quite across that line yet but we're getting closer every day.
Unless you get written permission you can be sued for publishing their trade secrets. This can end in jail time if your employer is particularly uncaring.
I’m in Finance and learned pretty quickly that point out the implicit future cost raises based on the cost the LLM-providers need to recoup was unpopular at best (STFU better describes the situation). Running full force into a bear trap.
Look, I share your sentiment. But, I can relate to the C-squad though. Going squarely against the market sentiment is not the way to gain and keep confidence. And everyone is vibing right? So they are probably thinking something like: as long as the spent is < few percent of a years profit, we can always adjust direction in the future and at least we’ve bet the same horse as the rest. “Those penny pinchers in finance (:: me) don’t get the big picture.”
I've seen that mentality and gone to bat to convince a boardroom that it's the wrong approach, when people were star-struck by the possibilities. Luckily I'm in a position as CTO of a (very non-tech, brick and mortar) company that entrusts me to manage their budget for new features, and prevent erosion of our software/logistics over the long term. And I've come down decidedly on the side of not having LLMs fuck with any schema or architecture changes or anything in the codebase that would touch upon business logic. When your code actually encapsulates business logic, which is often counterintuitive and full of weird exceptions, 90% of the code work is done by prior planning to map out all possible branches and the algorithms to assist employee decision making. The 10% that's actually writing code needs to be done by someone who understands the entire stack and business model perfectly. Some nice HTML/CSS fluff here and there is great to hand off to an LLM, and you don't need frontier models for that.
I shot down similar arguments in favor of outsourcing overseas for years. Outsourcing any critical logic to an LLM is even worse.
It can be as similar to or as far from outsourcing as you allow it to be.
The "if AI code breaks, who will fix it? -> "AI will fix it" exchange has (anecdotally) been very common among executives, which is much closer to outsourcing than programming.
Other than the delay time, I'm not sure I see the difference. You're removing your primary from the job of writing code, putting them into an editorial role, which removes responsibility and agency and actual hands-on understanding. The quality of the code is beside the point. More friction (language barriers, time zone difference) is actually better if you want to maintain institutional knowledge, because it requires more intellectual engagement. Accepting the LLM answer is too easy and leads to a decay of the systems knowledge.
I reject the premise that using LLMs absolutely leads to loss of institutional knowledge. It is trivial for an LLM to generate a knowledge base of any kind in any language which can answer any question about your institution at any time.
How is a bunch of fragmented humans with limited knowledge who can’t all communicate with each other better than that?
Do you seriously think that "institutional knowledge" can be maintained by simply writing down a few pages on Confluence or whatever system your company uses for internal documentation?
Have you ever taken the time to read hundreds of pages of documentation to fully understand a massive codebase? Neither have I. You learn it by working with it all day, and you're careful with it. A complete "knowledge base" of business logic is, itself, indistinguishable from code. Code that no one can or will read and learn unless they have to be immersed in it.
So the "knowledge base" an LLM generates is not useful as code, nor is it useful to humans. It may be useful to other LLMs as a lossy compression scheme for the original intention of the business logic and code.
That's not even in the same universe as institutional knowledge. Handing any serious business to something like that is malpractice, and sloppy beyond belief.
I'm not surprised that a lot of people think this way, because they never really grasped the benefit of holistic business knowledge united with code to begin with. Those people always outsourced, always got shitty code, and never really unified their systems. Cheap people and cheap companies take cheap exits. That's fine. But yes, many fragmented humans who all understand their portion in depth is much better than a bunch of markup files at retaining the knowledge of why things are done, procedurally, the way they are.
Once every six months the CEO calls me and asks me to remind him why our software does something like, idk, create a reverse payment instead of voiding a charge in some situation. Or some other thing he has asked a dozen times before. And I know the answer to why, or I know where to look, because I was in those meetings 5 years ago or because I wrote the code myself and asked the question when I wrote it.
Institutional knowledge is a very large context window, if you need to think of it that way, and LLMs are a shitty compression method for that. They can tell you how, but they don't reason well with why.
> create a reverse payment instead of voiding a charge
I think I know the reason to this one. Maybe. Because the money is already gone! There are no rollbacks in the banking system only "counter"-transactions.
No need for the downvotes imho. Can’t speak for u/noduerme but in putting outsourcing (labor, LLM/AI) in the same basket I don’t see a category mistake, but a dry way of looking at business. What are the risks, what are the rewards, what future skills are we at risk of losing (the business logic part) if we go in direction XYZ.
Something completely different (but with the same logic): do you outsource legal, hire your own team of business lawyers or will you let customer services use AI for legal problems (and only hire a lawyer for a day in court)? I think all three solutions are currently active in different firms. From a risk perspective I would always want a lawyer on my team. Insource those learnings. But perspectives vary.
Not sure if you were asking me, but the company I'm CTO of has in-house legal counsel, even though it's not a huge company. Their decision to keep software and also marketing/branding and art direction in-house for the past 20 years has followed the same logic. [which is to say: When they began as a single shop, the first thing they did was bring on legal]. I think it's a smart way of doing things. It's certainly a lot cheaper, and it earns more loyalty and commitment.
Moreover, any of us can run essential questions by each other, the marketing director, the lawyer, the CEO, the GM. And everyone has a stake. So all the creative and business decisions are worked out pretty quickly, and new features roll out with everything vetted and in place.
You know… up until your comment I’ve never even considered there are companies right now outsourcing overseas to people who will just vibecode it for a quick buck, my those companies live in interesting times
You’re in finance and you should know better… it’s not about recouping costs.
It’s about pumping up revenues, earnings and eventually cash flows (since they can’t keep raising money constantly) to support a nonsensical valuation.
This is wrong. Token costs for the same model rapidly collapse over a year. Hardware inflation is a thing but not bad enough to outweigh the massive impact of software optimizations.
Tokens billed at API prices are profitable for openAI and anthropic today and it only get more lucrative every month for them as their inference costs fall. If it weren’t for continuous massive training runs taking larger and larger capex, these companies would be massively profitable
> Tokens billed at API prices are profitable for openAI and anthropic today
That's nice for them. What's less nice for them is that big customers are figuring out (some faster, some more slowly) that they don't want to pay API prices, or at least only for a much smaller number of tokens.
The craziest to me was someone saying “we are using AI in daily processes, now we need to automate”.
But of course to some asshole non-technical people it meant asking for their vibe coded bullshit to be merged into production without review and fighting about it.
Without the "some" qualifier my quote totally loses meaning.
In the same message you managed to twist my words, lack reading comprehension, jump to conclusions and do a personal attack.
Since you're new here, I recommend reading this: https://news.ycombinator.com/newsguidelines.html , especially this part: "Please respond to the strongest plausible interpretation of what someone says, not a weaker one that's easier to criticize. Assume good faith."
Same here. It's insane that big, conservative tech companies would sign contracts saying "allow our engineers to use however much they want, we'll pay the bill later, no matter what it costs". In any other domain my company would insist on prior permission, and soft usage caps, and hard usage caps, and real-time tracking of actual dollar amounts (not just opaque tokens/credits, not just an after-the-fact view on a dashboard).
The AI companies' salespeople must be the greatest geniuses in the history of the world.
This is the first time in history that I have seen the shovel-sellers convince a supermajority of the gold-miners that "amount of gold mined out of the ground" is less of an indicator of profit than "amount of shovels purchased".
The leader boards based on token usage happened in our org for a month. Then we managed to convince the board that what matters is the reliable software shipped. Now we are back to DORA metrics.
> 2 months ago management was showing us scoreboards, praising leaders who used most tokens. Last few weeks, we're getting weekly emails, telling us that whenever we can - we should use cheaper models, and that we should watch the page which shows our tokens usage.
GPT 5.5's double token cost was the threshold for me. These things are getting expensive quickly - the subsidized pricing can't go on forever.
Recently, I've been so eager to get new model releases in Codex. I'm hooked. I hope this accelerates development. Shows how dependant I have become to Codex.
Will it have similar limited access like Fable? It is an interesting timeline, as general access for Fable (without using extra credits) is coming to an end :(
Not including their best model in a max subscription would otherwise be truly a good reason for once to consider going back to openai for me. I'll at least try it.
At least Anthropic have a max subscription for corporate. Codex is only pay-as-you-go pricing beyond the base plan. Hence I'm stuck with Opus for work for the foreseeable future.
> Codex is only pay-as-you-go pricing beyond the base plan
I don't think so, I'm on a ~$200 subscription (guessing that counts as way beyond "base plan") and have no pay-as-you-go pricing at all, using the OpenAI APIs would be way too expensive for me.
This is referring to the Business plan I think (used to be called Teams or something). The problem is that there are two types of seats: normal and codex only.
Codex only gets billed at API prices. The normal seats are more like a normal subscription, but their codex limits were LESS than a $20 subscription last time I checked (it used to be the same or more but they reduced it when they introduced the codex only seats).
Why haven’t we seen any queues or the like over the past week then? If it’s truly a capacity limitation why not just boot subscription users to a lower priority queue or limit usage to outside peak hours?
There could be a whole host of reasons. It may be during launch that compute is re-allocated from training to inference so that all users can try Fable. Soon that compute will re-allocate back to training until they can get more compute.
What a suprise, to make better models, they just making them larger and larger, then they can barely run it, after a round of LARP-ing that they invented some dangerous LLM?
Bruh when did understanding chatbots become like following magic card pack releases? Wtf does any of this this mean. Tf is sol? Tf is ultra? Tf is codex? Tf happened to descriptive nomenclature?
It's a proper noun: the name given to their latest and greatest model. Means "Sun" in Latin. Similar to how Anthropic has been naming its models Fable, Opus, Sonnet etc. Their other models are called Terra (Latin: Earth) and Luna (Latin: Moon) [0].
> Tf is ultra?
The name of the "harness" around the model. It'll use deeper thinking, subagents and all that jazz in response to a prompt. Other options include max, high, medium etc I suppose.
> Tf is codex?
"Coding agent" similar to Claude Code [1], something with a more descriptive name.
> Tf happened to descriptive nomenclature?
Something like GLM-4-32B-0414-128K (not made up [2]) doesn't quite roll off the tongue I suppose.
Branding is far more subsistent and meaningful than either lol. They just want to paint themselves as gods. But they are producing software, not magical beings, and we should see them as salesmen, not gods. Not to mention they'd probably sell more software if people could understand their product lineup
Has it been released yet? I'm not seeing GPT 5.6 anywhere in the selectors, nor any announcement about it, but you're talking about it as it's already been released?
Some of them will publicly break it for whatever reason, an NVIDIA engineer (@blelbach) recently made some posts on X about his results using 5.6 Sol Ultra to optimize stuff and then deleted them shortly after (presumably got yelled at).
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[ 2.7 ms ] story [ 99.9 ms ] threadhttps://www.theinformation.com/newsletters/ai-agenda/openai-...
"However, these inference optimizations, which rival Anthropic refers to as “compute multipliers,” are a big focus for all the labs. Anthropic CEO Dario Amodei has been publicly talking about the concept since at least mid-2023, when he said on a podcast that the company limits “the number of people who are aware of a given compute multiplier” because it could give other AI labs a leg up if they were to be able to replicate them. (Compute multipliers can also refer to efficiency optimizations in the model-training phase.)"
Yes, on a world with finite resources where your industry is singlehandedly siphoning ALL THE RESOURCES - hoard general efficiency optimizations and treat them as trade secrets - winning is all that matters, normal people and other species and the planet be damned.
Everything I hear about Dario these days makes me like him less and less. He sure did seem to speed run the 'tech leader with scruples' to 'tech villain' path! I guess all the cycles are compressing as we approach the singularity..
OpenAI seems to be trading roles back with Anthropic becoming misanthropic. I hope they both start heading in the direction of how the AI field was prior to LLMs.
Collaboration and benefit for all should always be the primary motivator.
Of all the things to never happen, this is never going to happen the most.
That train left the station for good once hundreds of billions to trillions of dollars were involved.
On the bright side, in the long run I suspect the vast majority of the value of AI will not be captured by the model making labs and the vast investments in them are going to implode, so...
They have a staggering surplus of grid capacity and can bring more online without any difficulty. We couldn't get a serious nuclear project done if Jeffrey Epstein was offering private flights to the ribbon cutting.
In the United States at any given time more than half of the FLOPs are badly misallocated, Meta has like, a double digit percentage of the total capacity going down the drain every day and has for years. That's a conspicuous example but on OpenRouter rankings it's rare to see more than one or two American vendors in the top 10, sometimes the top 20. But 3rd, 4th, and 5th place are all merrily burning half the compute duplicating effort and missing key innovations because we stopped publishing real results. In China if DeepSeek makes a breakthrough it's at Zhupai and Moonshot and MiniMax and MiMo and Qwen that week.
Our only lever, export restrictions, seems to do nothing but breed multiply antibiotic resistant super hackers who just get more efficient and immediately propagate all of those efficiencies to the rest of the Chinese AI industry.
At the beginning of 2026 there was one Chinese lab with a model that had any real relevance fielding modern tool users. Today in July there are like, eight lagging the absolute frontier by maybe 3-6 months. Barring some massive bend in some curve 3-4 of the top 5 and 6-8 of the top 10 will be Chinese and open weight by January.
The great irony in all of this is that our current playbook is straight out of the 1960s USSR, and the PRC's current playbook is straight out of 1960s USA. We're the ones with the opaque decision making and gross resource misallocation driven by the personal agendas of a shadowy cabal of frenemies wired back channel into government in the form of the individuals rather than the offices. They're the ones with a thriving marketplace of ideas powered by robust public/private partnership and a paved path running bidirectionally to the university system.
It's going to implode because the Kruschev system does. Theirs is going to thrive because the Kennedy system puts a man on the moon before the decade is out.
There's no evidence of this, the parsimonious explanation is PRC AI, by virtue of being sanctioned, simply is not able to run magnitude more expensive compute model, and even if they could, they don't have the $$$ or market cap to do so. So they optimize and involute margins like they do in everything, and US misallocated expensive flops because the entire industry has been financially engineered for phat margins along the entire producer supply chain is just cherry on cake. Like wipe out the 50%+ margins from toolmakers, fabs, gpu/memory/data center components to some reasonable level and US is overpaying for tokens by a stupid multiplier on top of actual compute misallocation due to incompetent infra. Maybe PRC AI has unsound economics, but it's structurally simply not able to misallocate as much as US who will find a way to financialize compute to point of absurdity.
The administration could probably put some serious friction on open weight model use in the Fortune 500 for a little while, but the opposition never got such a gift right before a squeaker midterm. And outside of major enterprises with puckered ass compliance departments? Not a chance. It's popular around here to forget Uber and AirBnB and yes, OpenAI and Anthropic all got their start flagrantly breaking the law and grew lawyers and lobbyists faster than anyone could enforce it. And this time everyone from the DNC to the EFF would be holding hands wearing "Save The Models" t-shirts. Not even NVIDIA is remotely pretending they're anything but all in on GLM 5.2, they had an NVFP4 quant up by the time most people read the blog post.
And the Trump Administration isn't exactly enamored of Comrade Amodei at the moment, being as they're appealing the lawsuit Anthropic brought against the Pentagon during a shooting war.
Forcing the American proprietary AI megalab financing event was our fiscal Ukraine Special Military Operation, the market is calling the bluff and neither the capital markets nor the Federal Reserve has the dry powder to absorb this one.
The Treasury auctions will flat not clear in an orderly way. We can't raise 2-4 trillion dollars on a dime in 2026 and if CoreWeave turns out, as many suspect, to be Patient Zero? It would be that big a hole.
We play by the same rules as everyone else now. I hope we regard it as being worth it, but I fear we will not.
Once China starts to get scary, Commerce will export control GPUs and declare Chinese models "foreign munitions." Any nation doing business with the US will not be allowed to use these models either, and that will be the end of that.
It is just not in the US's interests to fund China in the race to AGI.
Peter Hegseth, another really pro-America being powerful guy, he's dealing with a lawsuit because he doesn't want Anthropic in his military, he calls it a supply chain risk (he's right).
There is no evidence of any kind that a complex attack vector can be trained into model weights and survive all the crazy slicing and dicing that happens between published weights and running model. These things get quantized and run on mathematically imprecise kernels and sampled and LoRA-tuned and Dolphin/Orca de-tuned. Go look at what the ComfyUI community comes up with, those guys know more about WAN 2.2 than the people who trained it. Because those models run for real on a desktop, so there's mad innovation at light speed.
There is no one who wants a capriciously expensive black box run by extremely creepy people, not once the capability crosses over (in about November).
But don't take my word for it, you just had a chance at one AI IPO, and I'm sure you'll get another, so if you like how that goes, you don't need to convince me!
We are in a race to ASI. The first country to AGI will be the first to ASI, and the first to ASI will have de facto control over the world and the future of humanity. They will also be able to prevent others from reaching ASI.
Of course it's in the US's best interest to slow down China. You aren't zooming out and looking at the big picture, you're taking models as slightly useful tool, not what they will soon turn into.
I'm glad you trust a country that literally imprisons, rapes, and murders their human rights lawyers though. And one in which you cannot even criticize the government without being disappeared. Surely such a country is best positioned to have total control over all humanity, forever.
As well, it is a false equivalence to say that local models are only Chinese and otherwise we would use cloud models, but there are American or European ones, so a ban would simply force companies to use these, even if they are inferior to Chinese ones. It's simply a matter of national security to the US government, and they will not care what random people in media say.
I don't know what part of this you guys are having trouble with, but it doesn't get a whole hell of a lot more emphatic on "what the US Government thinks" than who the Pentagon is in court with to avoid doing business with that party.
Mr. Hegseth is the representative of the administration in the AI usage policy of the largest bureaucratic organization in the history of civilization. He has emphatically rejected at least one black box American AI megalab and President Trump has endorsed this action on Truth Social.
The government's stated position is not what you among other commenters are stating or implying as the government's position.
And you mention Hegseth but it was Lutnick at the Department of Commerce who banned Fable, so there are many competing parties in the government. Again, it is not just Anthropic who'd benefit from a Chinese model ban.
https://www.cnbc.com/2026/06/17/us-deepseek-blacklist-cxmt-n...
On one hand it appears to cooperate with OpenAI and Anthropic, as big customers.
On the other hand NVIDIA cooperates with Palantir, providing the HW for its "Sovereign AI OS" (a turnkey system including HW and SW for local inference and post-training/fine tuning) which uses the slogan "The future of AI is on-prem" (i.e. not as a customer of OpenAI or Anthropic, but using an open-weights LLM, e.g. a fine-tuned NVIDIA Nemotron or a Chinese LLM).
Presumably with the goal of promoting their competing solution, Alex Karp (Palantir CEO) has delivered a few weeks ago a very harsh criticism of Anthropic and OpenAI (who allegedly inflate the token consumption and they might also steal the data of their customers, which must be sent to them).
So NVIDIA both cooperates and competes with OpenAI and Anthropic.
https://www.bloomberg.com/news/articles/2026-05-20/airbnb-s-...
I don't know how much business OpenRouter does in Europe (they have some GDPR text in some settings pages I think) but it's zero in China.
You might also consider the countless companies that do nothing but open weight LLM inference: Together (of Tri Dao fame), Fireworks (founded by my old colleague), Baseten, SambaNova (of Chis Re fame), and too many more to count, there's a new one every week. Plus NVIDIA does a ton of this business via NIM and shit.
I'm trying to be reasonably polite because it's possible you literally didn't know that, but this reads as a troll, so, if it is a troll please stop.
There is nothing to support this. You get cheap Deepseek tokens by foreign providers too.
It is the same thing with automakers. They complain about not being able to only make luxuary cars with high profits with BYD raining on their parade and blaming the Chinese gov.
What kind of rosy-eyed chump believes in the "tech leader with scruples" bullshit? It always lies.
Did some people just ignore Mark Zuckerberg and Tim Cook's sociopathy, somehow? Did anyone buy into their "privacy is a human right" nonsense?
The thing I can't quite square is that it doesn't really fit my lived experience. I have known sincere, genuine people in the types of positions that I'm sure someone like you would declare to be sociopathic.
But beyond that, I just don't know why it would actually be true that everyone at the top is a villain. Why couldn't someone like Dario (or even Altman, gasp) be sincere? Because if he is, it does seem like a lot of the moves he's made would make sense given his worldview.
But if you assume he's just a villain, then you can twist any of those moves to just be further evidence of that which you already believe.
I don't know, I just find cynicism interesting, and a little sad.
I went in the opposite direction - how far can I push myself to see multiple facets of a story? That is a wild ride, and it gets progressively more wild.
Please, I'm dying to hear the optimist's take on Mark Zuckerberg's career. It wouldn't happen to be embarassingly foolish, would it?
Why should I treat Sam and Dario with special white gloves? Are they different, this time? They have peers in China that do the same research and actually release it to the public. They let you run the production weights on your own machine. Am I a cynic, for comparing these CEOs to their populist superiors? Am I stupid for assuming their hostility when they refuse to give us the benefit of the doubt?
I'll believe their actual altruism when I see it. Both are seeped in "boy genius" puffery and lie out their ass. If this is the future of intelligent innovation, America is in decline.
This is not hard to understand. Do you really think DeepSeek would publish their algorithms if they led the American companies? Lmao.
Even when they're reaching parity with American models, Z.ai, Qwen and Deepseek are upholding their end of the bargain. I'd criticize them too, if they were due any scrutiny.
You don't have to assume anything. A true "good guy" doesn't openly say that he's fine with autonomous, AI-powered weapons being used against me, and mass surveillance applied to me and my family just because I don't live in the US. A true "good guy" doesn't say "privacy is a human right", and then immediately (and completely) bend the knee to an authoritarian government on this issue.
And about the mass surveillance, I don't see why the military should not use AI to do surveillance abroad.
If you are dropping bombs on someone I'm unconvinced the use of AI will make them like you more or less.
I remember a long time ago it came out that the US had been doing mass spying on the Danish people, my dad was very upset about it and disliked the US for the rest of his life. Of course the only thing he did about it was not watch American movies anymore or visit the US.
Anyway, I assume it will be a case of a million little paper cuts, each thing putting off a group of people until someday it adds up to real meaningful economic impact.
All have collaborated with the current US regime. All have shown signs of being quite willing to compromise their principles in order to make money.
Lots of nerds for some reason have made cynicism a personality trait. They think optimism/honesty is hopelessly naive, therefor cynicism is the correct default.
It is the result of experience. Working with and creating systems (even embarrassingly simple ones), then seeing them fail in a myriad of ways more often than succeeding, colors your expectations about throwing humans into the mix.
Children learn to lie as part of their natural development, but do not always externalize that until faced with media (Airheads candy commercial or equivalent). Either way, honesty is expected as a default for utility and not an expectation in leveraging goals.
Power corrupts, absolute power corrupts absolutely.
Given enough money and increasingly perverse incentives to gain even more has a very high potential to corrupt.
Did they start out as corrupt, or was it the influence of the power that came with the obscene amount of money?
It's really a chicken and egg level of calculus.
Doesn't matter which came first, either way you get feathers and chickenshit all over the yard.
Do some very rich people still seem very nice in person? Sure. Of course they must, because otherwise no one would willingly work for or with them. As the total amount of money goes up, the incentives to remain 'seemingly nice' go down and either you get to see who they really are, or who they became through the choices to make that much more money. Doesn't matter which is true.
The examples of non-villainous billionare are rare.
Of non-villainous multi-billionaire; lets see there's about eight of them that stand out for giving significant amount of the massive wealth to helping the world around them, who live normal lives like the people in the communities where they reside, and who participate at the companies they own by eating in the company cafeteria among the people who earn the wealth they enjoy.
Thats 8/3400 global billionaires ... about a quarter of a percent.
And of the 'pledges' like Giving Pledge by the billionaire class, the actual amount delivered - not parked in a family or private trusts for tax deductions; but actually delivered to the front lines of any global crisis amounts to 0.18%, less than one fifth of one percent of the $20.1 TRILLION dollars held by that class of owners. thats less than $2.00 on every $1000.
That's not to say that donating to public needs is 1:1 for non-heinous behavior, but it seems like a basic tool for distinction. the 'can make a significant difference in global suffering : chooses not to' ratio as a surrogate for villain may be useful metric and doesn't require cynicism as the underlying rationale for calling someone's behavior as unkind in general or mean in particular.
History.
Also, nobody said 'everyone' or 'villain'. How Paul Graham of you.
(BTW Anthropic only exists because Sam Altman is a liar, Dario admitted this.)
Except for, you know, all the outside investors and the forthcoming IPO.
Related: https://80000hours.org/2012/03/the-replaceability-effect-wor...
There's a more nuanced discussion that could be had about how to balance relevance with outside influence. But at a foundational level it should be acknowledged that the tradeoff exists, and that receiving outside investment can't alone be seen as evidence of corruption.
Besides that, there's more that can be said about other things like their corporate structure or the degree to which they accelerated the AI race.
Of course that's what Dario thinks because that's what every tech CEO thinks. Dario, Sam, Sundar, probably many Chinese CEOs as well. It's what everyone thinks. That's why they're competing so fiercely with one another. That's why they basically make all the same decisions. That's why we need properly open source AI.
This doesn't seem like the right place to spend my time litigating that point to its fullest extent (no-one here is doing that). But there's plenty of relevant info surrounding eg.:
* The New Yorker article on Altman [1]
* The story behind Anthropic's founding
* Various efforts to influence government policy (a16z policies and contributors [2], Trump's inauguration donors [3], giving Trump credit for AI infrastructure [4], Dario's op-eds [5])
1: https://www.newyorker.com/magazine/2026/04/13/sam-altman-may...
2: https://a16z.com/portfolio/
3: https://www.opensecrets.org/trump/2025-inauguration-donors
4: https://www.youtube.com/watch?v=pe11mJ8mCHU
5: https://darioamodei.com/
OpenAI tried to pull off the same trade secret thing with RL when they announced o1 and o3, aka "Compute time scaling". Then Deepseek revealed it with Deepseek R1.
Could also be something like Deepseek DFlash. Or using diffusion like DiffusionGemma as a draft model. The timing between the release of those, and this article, makes me think its maybe one or both of those things
I wonder if that makes sense if the orgs within the industry are starting to shift their mindset towards "Tokens are expensive, we should use AI less." which feels like an existential threat to the status quo, if those AI providers can't find ways to keep costs affordable for their clients. Otherwise those orgs would just be using GLM 5.2 or DeepSeek V4 Pro but it seems like what they're doing instead is trying to use AI just less, period.
OP phrases it as a bad thing that Dario is keeping compute multipliers to Anthropic. How naive can one be? Compute multipliers are the whole business. Those are the trade secrets every lab is built on. It is the alpha of the business. How does protecting this make Dario evil?
This website is getting out of hand with the uninformed hot takes. I wish when HN was still people that knew what they were talking about.
People have different opinions than you, it happens..
[0] @sama if you're reading this we can fix that...
AI is a bid for control of all humanity. The first to superintelligence owns our future. I'd say it's okay to be a bit suspicious or conspiratorial.
How is this suddenly evidence of him being a villain?
Compute multipliers are like a quant firm's trading algorithms. They're the crown jewels, the whole alpha of the lab. If you leak them, the lab dies.
Protecting them does not make Dario a villain, it's literally his job. It's also Sam's job, Denis's job, Mira's job, etc. Every lab guards these multipliers closely because they represent the entire worth of the lab.
I don’t think this makes Anthropic a villain?
In what universe is any company going to give that advantage away?
In any case if they take away a lot of market share it's basically the same in the end - most people will be using these optimisations.
This 2023 thread about this issue is prescient: https://www.reddit.com/r/MachineLearning/comments/11sboh1/d_... (just add Anthropic to OpenAI)
The primary effective altruism cause areas are extremely acute and high-scale problems like malaria, vaccine distribution, and factory farming
https://github.com/openai/codex/issues/30364
For example, if inference isn't too expensive, but they figure out how to cut costs, then price goes down. After all, why pay OpenAI when a smaller datacenter can give you similar models?
But, if they make a huge issue about how inference is too expensive, they engineer a crisis of their own creation - then, once they deploy the solution (which they might already have), then they're back on top.
> Additionally, we’re introducing a new ultra mode that goes beyond the capabilities of a single agent by leveraging subagents to accelerate complex work.
https://openai.com/index/previewing-gpt-5-6-sol/
Can someone explain how this compares with Pro? I thought Pro was already something similar.
The responses I get from pro don't feel like ensembles. They are often very one directional.
They might be confused by MoE but that doesn't work like how they describe and all GPT 5 models use MoE not just Pro. Or they're confused by how thinking summarization works but again that's all GPT models.
It's bullshit. But downvote this away, sure.
> We generally treat GPT-5.5’s safety results as strong proxies for GPT-5.5 Pro, which is the same underlying model using a setting that makes use of parallel test time compute. As noted below, we separately evaluate GPT-5.5 Pro in certain cases because we judge that the setting could materially impact the relevant risks or appropriate safeguards posture.
https://deploymentsafety.openai.com/gpt-5-5/model-data-and-t...
There have been multiple podcasts with people from OpenAI which have confirmed this.
Any idea what that means exactly? I vaguely remember that ChatGPT Pro was originally called "deep thought", just like Geminis "deep thought" feature (or "deep think"?), so it seems likely they are using the same approach.
Its widely accepted[1] that it runs the same query through the model in parallel and then has a model that either selects the best answer or synthesizes an answer from the multiple ones generated.
I believe most people think it runs 6 sub-models, but I think that is based on the pricing.
It's a pity that OpenAI doesn't publish details like this.
[1]eg https://news.ycombinator.com/item?id=48799977
Hopefully, 5.6 will automatically spawn sub-agents without needing to ask.
Aaaaand it’s gone.
Who do you think pays for your subscription's actual usage?
https://news.ycombinator.com/item?id=44344246
107 comments, 1 year ago.
Previewing GPT‑5.6 Sol: a next-generation model
https://news.ycombinator.com/item?id=48689028
I think gpt-5.5-pro runs 12x parallel gpt-5.5 agents behind the scene and uses OpenAI's secret sauce to synthesize their answers into one insanely good response.
OpenAI models have always been the worst in my experience for verbose, slop formatted responses, with each generation increasing in sloppiness.
I'm not that impressed by Fable's writing to be honest, still has the AI giveaways like em dash.
I haven't opened an IDE in 8 months or so and have no plans to go back.
If that's at all reflective of what it costs them to run it, I imagine they're in the same boat as Anthropic with Fable; they probably can't afford to offer it at subscription prices given current cost to operate it.
If 5.6 Sol Ultra has efficiency improvements (at one or more layers), and it allows OpenAI to offer a model that's competitive with Fable on the subscription plans, I'll guess a lot of folks will switch.
Fable is notably better than what came before. I watched it figure out stuff on its own over and over, on extremely hard problems, that I previously needed to guide a model to an understanding about, or work with them back and forth for several turns to figure it out together. Like, I've been reverse engineering a hardware device lately, and I've tried to tackle it a few times in the past with both some version of GPT and a couple of versions of Opus (most recently 4.7). In all cases, I barely made progress...would have gotten there eventually, probably, as I'm stubborn, but there were roadblocks constantly, with me and the model getting stumped and going around in circles in the end on every prior attempt.
Fable figured out other ways to find out what's happening, it dug into config files, found and extracted Boost-serialized data, compared that data to the observed behavior, built tools to compare the observed data with our emulated behavior, without being prompted. Would I have gotten there? Eventually, maybe. All prior models didn't; they mostly just tried the things I suggested and stopped at "well, that didn't work" or declared success after seeing results that matched their misunderstanding of the problem. I guess it possible my prior attempts with other models has "loosened the lid" on the problem; we did already have a long list of documented "this didn't work" and a pile of tools for finding out if something work. But, even so, I was impressed.
There probably will still be a "OK, let's rewrite this so it's not using lookup tables to precisely simulate the hardware behavior in software, because we don't need the noise, too" stage of the process...but, in one day with Fable, it solved a problem that I'd banged on for at least a week or too in the past with very little real progress. I don't think the models write exceedingly good code, even the best ones, but it sure does figure shit out quick.
https://github.com/agentify-sh/desktop
> GPT-5.5 Pro does not offer a cached input discount.
I think this tells you in one line. It's basically set up for one-shot inference right now, by the looks of things. If you use this in a harness, it would almost immediately fall apart on cost. Not to say that they couldn't make it work, just saying that at least as it's delivered currently, they haven't done so. On the web, there might be doing something to get the equivalent of that behavior internally, such as keeping the session truly alive on GPUs rather than using their external-facing cache-style approach.
Yes, I know attention degrades above ~200k, but it's still useful in many applications.
https://x.com/haider1/status/2073695124220006575#m
I haven't really used it yet.
2 months ago management was showing us scoreboards, praising leaders who used most tokens. Last few weeks, we're getting weekly emails, telling us that whenever we can - we should use cheaper models, and that we should watch the page which shows our tokens usage.
Everyone is insane.
Ymmv, do whatever you want . It's your life.
Like: What competence do decision makers in FINANCE have, when they are this oblivious to economics?
I don't think this is axiomatic. I usually invest my time, energy and money in things that go squarely against the market's momentary sentiment.
I shot down similar arguments in favor of outsourcing overseas for years. Outsourcing any critical logic to an LLM is even worse.
The "if AI code breaks, who will fix it? -> "AI will fix it" exchange has (anecdotally) been very common among executives, which is much closer to outsourcing than programming.
So the "knowledge base" an LLM generates is not useful as code, nor is it useful to humans. It may be useful to other LLMs as a lossy compression scheme for the original intention of the business logic and code.
That's not even in the same universe as institutional knowledge. Handing any serious business to something like that is malpractice, and sloppy beyond belief.
I'm not surprised that a lot of people think this way, because they never really grasped the benefit of holistic business knowledge united with code to begin with. Those people always outsourced, always got shitty code, and never really unified their systems. Cheap people and cheap companies take cheap exits. That's fine. But yes, many fragmented humans who all understand their portion in depth is much better than a bunch of markup files at retaining the knowledge of why things are done, procedurally, the way they are.
Once every six months the CEO calls me and asks me to remind him why our software does something like, idk, create a reverse payment instead of voiding a charge in some situation. Or some other thing he has asked a dozen times before. And I know the answer to why, or I know where to look, because I was in those meetings 5 years ago or because I wrote the code myself and asked the question when I wrote it.
Institutional knowledge is a very large context window, if you need to think of it that way, and LLMs are a shitty compression method for that. They can tell you how, but they don't reason well with why.
I think I know the reason to this one. Maybe. Because the money is already gone! There are no rollbacks in the banking system only "counter"-transactions.
Something completely different (but with the same logic): do you outsource legal, hire your own team of business lawyers or will you let customer services use AI for legal problems (and only hire a lawyer for a day in court)? I think all three solutions are currently active in different firms. From a risk perspective I would always want a lawyer on my team. Insource those learnings. But perspectives vary.
Moreover, any of us can run essential questions by each other, the marketing director, the lawyer, the CEO, the GM. And everyone has a stake. So all the creative and business decisions are worked out pretty quickly, and new features roll out with everything vetted and in place.
https://github.com/minimaxir/hacker-news-undocumented/blob/m...
It’s about pumping up revenues, earnings and eventually cash flows (since they can’t keep raising money constantly) to support a nonsensical valuation.
Tokens billed at API prices are profitable for openAI and anthropic today and it only get more lucrative every month for them as their inference costs fall. If it weren’t for continuous massive training runs taking larger and larger capex, these companies would be massively profitable
That's nice for them. What's less nice for them is that big customers are figuring out (some faster, some more slowly) that they don't want to pay API prices, or at least only for a much smaller number of tokens.
GPT-10 Human Ultra
But of course to some asshole non-technical people it meant asking for their vibe coded bullshit to be merged into production without review and fighting about it.
You mean the people creating actual business value in every industry where software isn’t the product? Speak not unless spoken to, Mr. cost-center!
In the same message you managed to twist my words, lack reading comprehension, jump to conclusions and do a personal attack.
Since you're new here, I recommend reading this: https://news.ycombinator.com/newsguidelines.html , especially this part: "Please respond to the strongest plausible interpretation of what someone says, not a weaker one that's easier to criticize. Assume good faith."
Please stop using this brand new hammer for glassmaking.
The AI companies' salespeople must be the greatest geniuses in the history of the world.
And I do more hand coding to guide the agent to useful patterns I want.
I feel like that’s how I used less capable agents a year ago. But I’m finding even with high quality agents, the slop creeps in.
I want more control. I want to save money. Hence going back to a more 80/20 agent to human LoC split.
GPT 5.5's double token cost was the threshold for me. These things are getting expensive quickly - the subsidized pricing can't go on forever.
Also, from the Guidelines:
> Be kind. Don't be snarky. Converse curiously; don't cross-examine. Edit out swipes.
Somebody has to finaly pay for these heaps of accelerator hardware.
more competition is always good for consumers.
I don't think so, I'm on a ~$200 subscription (guessing that counts as way beyond "base plan") and have no pay-as-you-go pricing at all, using the OpenAI APIs would be way too expensive for me.
You can't use sub pricing with orgs w/ OpenAI.
Codex only gets billed at API prices. The normal seats are more like a normal subscription, but their codex limits were LESS than a $20 subscription last time I checked (it used to be the same or more but they reduced it when they introduced the codex only seats).
> Tf is sol?
It's a proper noun: the name given to their latest and greatest model. Means "Sun" in Latin. Similar to how Anthropic has been naming its models Fable, Opus, Sonnet etc. Their other models are called Terra (Latin: Earth) and Luna (Latin: Moon) [0].
> Tf is ultra?
The name of the "harness" around the model. It'll use deeper thinking, subagents and all that jazz in response to a prompt. Other options include max, high, medium etc I suppose.
> Tf is codex?
"Coding agent" similar to Claude Code [1], something with a more descriptive name.
> Tf happened to descriptive nomenclature?
Something like GLM-4-32B-0414-128K (not made up [2]) doesn't quite roll off the tongue I suppose.
[0]: https://openai.com/index/previewing-gpt-5-6-sol/
[1]: https://openai.com/codex/
[2]: https://docs.z.ai/guides/llm/glm-4-32b-0414-128k
> Something like GLM-4-32B-0414-128K (not made up [2]) doesn't quite roll off the tongue I suppose.
Surely it would sell better though if they could communicate what they're selling?
https://hn.algolia.com/?dateRange=pastMonth&page=2&prefix=fa...
How does it compare to GPT-5.5?