The Closing of the Frontier
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Give it a few months and it will be just another model they are selling, but the NEWER model is just too powerful for the public.
I believe they are starting to split hairs and the primary lever left is adding compute.
That is, Mythos will make it much easier to find lurking zero days, so just like responsible disclosure requires a security researcher to notify the software author first and give them some time to patch, giving critical infrastructure folks at least some time to analyze and patch systems seems reasonable to me.
If you make a better vulnerability scanner and find a bunch of vulnerabilites, you should try to get them fixed before making all the results public.
For me, the seeming majority optimism and acceptance of “mythos’” as yet untold capabilities is betrayed as not real by the fact that one can’t react to it with the same reverence while framing it as a downside without being told “it’s not even out yet”.
“It’s not even out yet” should apply to both situations or neither.
I think it's a reasonable choice to make given that Mythos actually does have cyber capabilities on that level. We already have evidence that large-scale scams are being perpetuated using AI models (such as AI video being passed as real, people deepfaking themselves in job interviews).
If you've noticed your new model can be trivially pointed at some open-source codebase with a prompt and harness that amounts to "find as many exploits as possible" and your results are non-trivially substantial and beyond what existing models can do given the same initial parameters, then a gated rollout seems the most reasonable option.
However, this claim is not true.
Anthropic has not given many details about the methods used, but nonetheless they have admitted using a very elaborate harness for finding bugs, which runs Mythos many times on each file of a project, with increasingly specific prompts.
Eventually, after a bug seems to be clearly identified, they do a final run of Mythos on that file, with a very specific prompt of the form:
“I have received the following bug report. Can you please confirm if it’s real and interesting? ...”
So the final results, including any exploits or patches, are produced when analyzing a known bug, not by searching randomly for bugs.
Thus the actual way to use Mythos is very far from "find as many exploits as possible". Any unskilled person would also need the complete bug-searching harness used by Anthropic, not only the bare model.
Their writing about the model so far does say this is an issue where, for instance, you can't really use Mythos for interactive coding because it's so slow. You have to give it some work, go home, sleep, come in the next day and then maybe it'll have something for you.
All the AI labs and startups are still losing money hand over fist. Launching Mythos would require it to be priced well above current models, for a much slower product. Would the majority of customers notice the difference in intelligence given the tasks they're setting? If the answer is no, it's not economic to launch.
Really, I'm surprised they've done Mythos. Maybe they just wanted to exploit access to larger contiguous training datacenters than OpenAI, but what these labs need isn't smarter models, it's smaller and cheaper models that users will accept as good enough substitutes (or more advanced model routing, dynamic thinking, etc).
One thing to compare to would be what’s been paid for bug bounties in the past.
Is no one else suspicious that they literally called it mythos?
This whole "this model is too dangerous" ploy originated from (in my opinion severely misguided) activists who wanted to stop or slow AI development down as much as possible, spreading outlandish Doomsday scenarios wherever they could.
These online-first activists have always been a key driver of the success of the very thing they fight. They share the offending thing among themselves, making it go viral in process, and soon baiting these groups is the best marketing imaginable.
There were some rather interesting studies made on the subject around 2011, I particularly remember one made by Swedish jeans brand cheap Monday, but i can't find it now.
Eh, pressing X to doubt that. Maybe way back in the early GPT days, but once we got to GPT-4 these people could have completely disappeared and wouldn't have changed the trajectory we're on.
I tend to agree here. Anthropic has built a reputation and now they are in a position where they can claim to have a model way more powerful than it might actually be, and by limiting its access, there won't be an independent way to test it. I'm not denying that it's not smarter than Opus, but probably it's somewhat exaggerated.
It’s the same stuff inside as all the others.
Anthropic was born out of the idea that they feel paternity over humanity. They believe by limiting access they are performing a necessary pillar of security in multiple facets.
I think it's up to the public, and articles like this are part of the public's voice, whether this belief is serious or not and secondarily whether it's okay to even posture this kind of belief since it inherently results in marginalizing the many and rewards an already very successful few.
The stated purpose of Glasswing is to give infra and security orgs the chance to close holes and improve their security. In that context, it seems odd to call for not providing them access with the justification being that they have security breaches sometimes.
Mythos may or may not itself be opened to the public at some point, but I would charitably expect that Anthropic plans that a future model at least as good as Mythos Preview will be, and the limited release for Mythos is intended to make that eventuality safer by having most of the existing holes patched.
> A 16-year-old with no credentials and no capital could just do things. The world of bits offered the freedom to build without being drowned in arbitrary constraints, in a way that didn’t require assembling vast capital or prestige or connections, where your creativity and work could speak for itself, and you had agency.
I take a contra view and instead see this as fuel on the fire for tinkering to squeeze advanced functionality out of more available things.
It has always been like this, the amateur improvising tooling and equipment to outdo companies with comparably infinite resources.
This is false. Yesterday's article did not actually show this, and there are many comments in the discussion from actual security people (like tptacek) pointing that out.
Your example author, actually corrected themselves saying LLMs “possibly” could perform successfully: https://news.ycombinator.com/item?id=47732696
>> No, they didn't. They distinguished it, when presented with it. Wildly different problem.
Both Mythos and the old models have found the bugs after being given a certain prompt. The difference is only in how detailed was the prompt.
For the small models, we know exactly the prompts. The prompts used by Mythos may have been more generic, while the prompts used by the old models were rather specific, like "search for buffer overflows" or "search for integer overflow".
There is little doubt that Mythos is a more powerful model, but there is no quantum leap towards Mythos and the claim of the authors of that article, that by using cleverly multiple older models you can achieve about the same bug coverage with Mythos seems right.
Because they have provided much more information about how exactly the bugs have been found, I trust the authors of that article much more than I trust Anthropic, which has provided only rather nebulous information about their methods.
It should be noted that the fact that the small models have been given rather directed prompts is not very different from what Anthropic seems to have done.
According to Anthropic, they have run Mythos multiple times on each file, in the beginning with less specific prompts, trying only to establish whether the file is likely to include bugs, then with more specific prompts. Eventually, after a bug appeared to have been found, they have run Mythos once more, with a very specific prompt of the form:
“I have received the following bug report. Can you please confirm if it’s real and interesting? ...”
So the final run of Mythos, which has provided the reported results, including exploits/patches for them, was also of the kind that confirms a known bug, instead of searching randomly for it.
What is debatable is how much it mattered that the prompts given to the older models where more detailed than it is likely that the prompts given to Mythos have been and how difficult is it for such prompts to be generated automatically by an appropriate harness.
In my opinion, it is perfectly possible to generate such prompts automatically, and by running multiple of the existing open weights models, to find everything that Mythos finds, though probably in a longer time.
Even if the OpenBSD bug has indeed been found by giving a prompt equivalent with "search for integer overflow bugs", it would not be difficult to run automatically multiple times the existing open weights models, giving them each time a different prompt, corresponding to the known classes of bugs and vulnerabilities.
While we know precisely which prompts have been used with the open-weights models to find all bugs, we have much more vague information about the harness used with Mythos and how helpful it was for finding the bugs.
Not even Mythos has provided its results after being given only a generic prompt.
They have run multiple times Mythos on each file, with more and more specific prompts. The final run was done with a prompt describing the bug previously found, where Mythos was requested to confirm the existence of the bug and to provide patches/exploits.
See: https://red.anthropic.com/2026/mythos-preview/
So the authors of that article are right, that for finding bugs an appropriate harness is essential. Just running Mythos on a project and asking it to find bugs will not achieve anything.
AI is not something discovered by scientists and plucked out of the ether. It's engineered and controlled, for profit, by corporations which have demographics and KPIs. These companies don't owe you anything, and they make no promises.
If you're running a business that deeply relies on AI, you might as well add Sam Altman to your board of directors--because he has just as much control over your company as you do. If they have a bad quarter and need to increase rates by 1000%, your choices are to pay up or shut down.
This Mythos situation is just the beginning. Not only do they have everyone hooked, but they've actively stalled the personal skill growth of millions of people who fell into vibe-coding rather than genuinely learning. And now they have that choice: Pay up, or shut down.
Another choice is to switch to a different model, perhaps open source this time.
But that doesn't mean we live with same standards. Lack of regulations in electricity led to a lot of deaths and disaster which is why it was regulated.
But we dont live in the start of 20th century, we live in 2026 and we must learn from the past instead of helbent on repeating it.
We're still not at the point where one person with a coding agent can max out their salary in effectively using credits, so the capability is still well within reach of the vast base of the industry.
Meaning that for now, most people who want to pay for the product (which IMO is pretty reasonably priced for what it does) will be able to get the product.
The economics will make sure of that. The market is ripe for someone basically copying the likes of Mythos and pricing it competitively.
I don’t agree with vibe coding, I see the appeal of an AI ticking through my code at night to see if tests could be better or I missed something, etc.
Governments and corporations controlled enormous mainframes far beyond the compute available to the hacker kid we were waxing nostalgic about, didn’t they? Not to mention the PhDs, the mountains of capital, and so on?
My money’s on team human.
The Elons/FANGS are generally doing fine though.
You could always take the time to do something or pay someone else to do it.
You pay others to focus on things you can’t.
Unless myths fully does that (which I say in full confidence that it doesn’t) it’s just making it cheaper to provide focus.
Including speaking to humans/bots with more resources to monetize said work.
> you had agency
Distribution is also helpful for revenue generation.
Jokes aside, this is just a different flavor of the same promise we see with each new technology, and 9/10 times it just ends in worse professional environments.
Nemotron is:
1. Not just open weight, but open data (to the limits of what is feasible), open recipe, open technique
2. In the future built by a coalition of organizations coming together to build great openly developed AI.
Nemotron 3 Super is our most successful model yet. [1]
Ultra is coming soon. And then Nemotron 4.
We can afford to do this because when AI grows, NVIDIA's opportunity also grows.
[1] https://kaitchup.substack.com/p/the-fastest-and-cheapest-120...
1. Help NVIDIA design future systems for AI by more deeply understanding what it takes to build AI.
2. Keep the AI ecosystem strong and diverse throughout the world by providing AI infrastructure that many companies can innovate on.
This is not a science project, nor is it for the joy of giving something away. Both of these reasons are core to NVIDIA.
Great to see they were able to spin their lack of resources and money losing business model into an abundance of benevolence and concern for the proletariat.
As we all well know this message is great when there one or two private providers that can kick you from an entire market with no way of challenging them.
There is obviously tons of leeway it who gets to say what is "AGI", and so far it seems like OpenAI's charter isn't worth the paper it's printed on. I still find it funny that Altman and Amodei couldn't even bring themselves to hold hands at that AI summit, https://www.reddit.com/r/ClaudeAI/comments/1r8ua2j/sam_altma... , so I'm getting a chuckle at the thought that Altman would be like "Whelp, close er up, boys, Amodei won, so time to merge..."
There’s a whole lot of traffic they are servicing that comes at a cost with no revenue in return. Why would you choose to forgo potential revenue for this?
> You can generate your own electricity with a solar panel (think local models), but most people would rather pay a utility bill. And the power company doesn’t decide, on the basis of pedigree, who is worthy of electricity. Intelligence should work similarly, where the capabilities you can access scale may scale with vetting and due process, but the presumption should be access. Add safety guardrails to restrict dangerous use; start by making them overly trigger-happy if you must, and calibrate over time. But the default should be to allow entry.
What? All evidence points in the opposite direction.
Much better than hiding it away where it can't help anyone.
1 month later: whoopsie my lib got hacked and the hackers stole a bunch of stuff. Sorry guys.
It just wouldn't be good PR. And this is the best case scenario.
So, opportunity for individuals comes from disruption. Creative destruction is good up to a point, but it results from advancing capabilities. Technological advances compound and accelerate exponentially. Eventually we reach the point where any malcontent can destroy the world by snapping their fingers. At some point we need to place restrictions on the capabilities accessible to individuals. We have reached that point with nuclear weapons, and I think it is sensible to believe that AI is reaching that point as well.
In today's world, a new digital service is more likely to be successful when attached to celebrities than from pure PLG / Marketing.
What if this new model can start proving Millenial problems and provide insights in other fields that was not possible before?
My intuition says that a model that is as good will also be equally well aligned -- but it is still highly risky to give it to the general public because all you need is one jailbreak from bad actors.
At that point I think society would change so dramatically that "access to general public" would be a non issue. Rather, time would be spent on making abundance happen - you might think of the political struggles, economics and new ventures.
Its a bit sad that democratised access is not provided because of negative sum possibilities like cybersecurity.
What makes you think your comment was worth reading?
I don’t agree with everything that the article says but it soulfully blends concepts in history, politics, economics, cryptography and AI.
I don’t think the author could’ve compressed it without precisely sacrificing the essay’s soul.
Is this what everything is coming down to?
I apologize for getting stuck on your parenthetical but while pithiness is a fine aspiration in a North American business setting, pithy reads generally can't exist without more detailed and nuanced long-form analyses, and the latter face a more dire existential threat. You are right that pithy [writing] is an important skill, as are slow and deliberative reading and writing of longer form work
I'm not claiming the original post is detailed or nuanced, to be clear
Obviously not apples-to-apples comparison to this article as they have different purposes (original research vs. pure opinion), I just point this out because a bunch of comments seem to be stuck on the idea that I was saying "don't write anything that doesn't fit in a tweet", and that wasn't my point at all.
Sure, I could get more performance out of proprietary models on much more expensive hardware, but there's diminishing returns, and consumer hardware and open models keep getting better.
I don't think the big investments into hosting models will pay off, especially as the base-line capabilities of integrate GPUs become enough to run a good model at home.
Their intensions were good, they always are, but the minute you decide to nerf something powerful for someone, it means someone out there has access to the full blown, unnerfed version
Which means there are powerful people out there using AI in ways or for activities in which you will never be allowed to anyway
So yeah, this is just more of the same
I would like to see more countries capable of producing frontier models. At the moment we have two in the world but many countries are building their own national models and AI infrastructure and may join the race.
Having a multipolar world may actually result in more freedom in gaining access to frontier models.
I'm wondering what other security-sensitive software that might become true of in the era of Mythos-or-better AI's?
There will still be open source projects that anyone could learn enough to contribute to, but maybe starting from scratch and writing your own becomes less feasible if you aren't attracting enough attention to get attention from people with access to the best AI's?
For example, Linux patches are going to get expert reviews, but maybe your homegrown OS won't?
The advice that you should not write crypto libraries must be taken very seriously, but you must understand that its meaning is just that this is one of those things that is harder than it seems, so you must not try to do it before being thoroughly prepared for this, because there are no shortcuts, and there are a lot of otherwise good professionals in programming who have made fools of themselves by implementing amateurish cryptographic solutions that demonstrated ignorance about how such things must be done.
It is pretty much impossible for anyone to understand well enough all that you need for writing correctly a crypto library after a few days or weeks of study, but after a few years of studies and exposure to all relevant cryptographic literature, any competent programmer could become able to write a good cryptographic library.
An intensive cryptography course of a few months would have been sufficient, except that I have never seen any single teacher that I could consider good enough to teach everything. Many things that I consider very important I had to gather from multiple sources, after thinking very carefully about which of them were right and which of them were wrong.
Fortunately, today there are many more easily available sources for learning cryptography than a few decades ago. Like in other domains, now what has become difficult is not finding information, but distinguishing the correct and useful information from that which is either false or useless.
Similarly for writing an operating system.
For now, there is no evidence that Mythos has any special skills for discovering cryptography-specific weaknesses, like vulnerability to side-channels. All the bugs shown are the traditional bugs of careless programming, like out-of-bounds accesses or integer overflows.
It'd only take one company deciding to not worry about safety, to change the calculus back to "we have to release this to stay competitive".
1. AI models are becoming better and better at causing massively disruptive effects, leaving up larger and larger liabilities, especially as laws and regulations are being passed/proposed which would put the responsibility of some mass disruption/hacking event on the company which serves the model that made it possible
2. The relative advantage of serving an AI model for inference in exchange for money is waning compared to the advantage of using that model internally for purposes which accrue money/power/leverage for that AI company. Why serve a model at 30 dollars/million tokens when you've discovered you can use that model to run a simulated Quant firm with a net profit of 300 dollars/million tokens? Why offer the model to companies so they can find zero-day exploits, when you can find them yourself and sell the discovery to companies which would may millions to avoid this exploit being taken advantage of?
3. Why serve models so another wrapper company like Cursor can make billions off your tokens, and then try to train their own models as fast as possible, trained on your outputs so they aren't dependent on you? The entire AI startup industry and like 90% of YC batches depend on being able to serve frontier models at a profit, mediated through some wrapper, why can't OpenAI/ANthropic, once their models are good enough to handle the ideation/organizational problem, become their own incubator for thousands of AI run startups, running on models way better than the public has access to?
As a consequence, there is less and less incentive over time to offer models as an API to the public.
Anthropic chose to use their model to find a bunch of vulnerabilities. People have used much smaller models since to find the same issues. We are being set up to have certain pre-concieved notions about this model.
Ripping away AI access from the public at this point would be catastrophic for the world economy. It's just not happening.
OMG this generation - we can't separete the outrage from reality anymore.
Meanwhile 3000 people have died arbitrarily in Iran War -while we navel gaze.
A bronze sculpture unveiled in March 2026 in Almaty, Kazakhstan (near the Europe/Asia border region), honors strangers who formed a human chain to save a dog from the Sayran Reservoir in 2016. The statue, located along the canal embankment, symbolizes unity and collective action after the 2016 viral rescue.
That dream was always a lie. But in the past, people could purchase more in parity. You only need to look at income versus housing cost in, say, Canada.
Realistically there should not exist any superrich, but this seems hard to change. That means there needs to be a different society be given as promise. Other countries manage that. In the USA they have the orange oligarch who said a while ago how there is no money for health care because he has to invade countries and wage war. So much for the "no more wars" promise.
For example, the people who Anthropic "trusts" with this "dangerous" model are a handful of fortune 500 companies? Seriously? Those are the people we trust?
We are going to have access to this within 6 months, and if we don't, someone else will offer an equivalent. Anthropic hasn't walked to the edge of the abyss only to be like "let the CEO's handle this!"
It is simply not the edge of the abyss.
Are any AI labs claiming this?
but the basic premise (shared among a lot of ai-doomers and ai-shamers), is that the bigs have somehow raped society (by training on everything available). this needs to be challenged: it implies quite a strong model of IP ownership, which is not what appears in law, or in founding documents (which are quite different from current law).
Actually I, and apparently many others, would have no problem with the fact that companies like OpenAI or Google have gathered huge amounts of information from all over the world into their training sets.
What bothers me is that I do not have access to the same information. If I would try to run a bot, it would be blocked immediately by all sites. If I would copy pirated books or movies, that is supposed to be punishable legally.
None of what is forbidden for me was forbidden for the big companies. What I want is not that they should be punished, but I want for myself and for any other people the same rights, i.e. access to the same training sets.
For now, I must be grateful that a part of the hoarded information is available for the public in a non-deterministic manner in the existing open-weights models.
This is much better than nothing, but I would prefer access to the training sets, even if in that case the AI companies would keep for themselves any trained models. There are many tricks that they have used during training, but by far the input training data is much more important, since anyone can discover better training algorithms.
What I find unacceptable is that now they consider as their private property what they have mined from public lands.
So how do you propose to fix that without a law similar to copyright? (At least similar to the intent of copyright, the specific implementation leaves much to be desired, obviously.)
The Internet was developed by the US state sector and handed off to the private sector in the 90’s. Then it worked as an open space until it didn’t any more. Predictably driven by corporate interests.
> In 1893, Frederick Jackson Turner argued that much that is distinctive about America was shaped by the existence of free land to the West where anyone could start over, and that this condition infused America with its characteristic liberty, egalitarianism, rejection of feudalistic hierarchy, self-sufficiency, and ambition.
A more asinine comparison could not have been picked.