Someone needs to make a compilation of all these classic OpenAI moments. Including hits like GPT-2 too dangerous, the 64x64 image model DALL-E too scary, "push the veil of ignorance back", AGI achieved internally, Q*/strawberry is able to solve math and is making OpenAI researchers panic, etc. etc.
I use Codex btw, and I really love it. But some of these companies have been so overhyping the capabilities of these models for years now that it's both funny to look back and tiresome to still keep hearing it.
Meanwhile I am at wits end after NONE OF Codex GPT-5.4 on Extra High, Claude Opus 4.6-1M on Max, Opus 4.6 on Max, and Gemini 3.1 Pro on High have been able to solve a very straightforward and basic UI bug I'm facing. To the point where, after wasting a day on this, I am now just going to go through the (single file) of code and just fix it myself.
Update: some 20 minutes later, I have fixed the bug. Despite not knowing this particular programming language or framework.
Are you sure they are not just refusing to solve your UI bug due to safety concerns? They may be worried you'll take over the world once your UX becomes too good.
Show us the code, or an obfuscated snippet. A common challenge with coding-agent related posts is that the described experiences have no associated context, and readers have no way of knowing whether it's the model, the task, the company or even the developer.
Nobody learns anything without context, including the poster.
I had a problem that required a recursive solution and Opus4.6 nearly used all my credits trying to solve it to no avail. In the AI apocalypse I hope I'm not judged too harshly for my words near the end of all those sessions lol.
This is obviously in response to Mythos, but I'll actually defend their statement at that time - they were right to take a pause.
Think about how much things have changed in our industry since GPT-2 has dropped - it WAS that dangerous, not in itself, but because it was the first that really signaled a change in the field of play. GPT-2 was where the capabilities of these were really proven, up until that point it was a neat research project.
Mythos is similar. It's showing things we haven't seen before. I read the full 250 page whitepaper today (joys of being pseudo-retired, had the hours to do it), and I was blown away. It's capabilities for hacking are unparalleled, but more importantly they've shown that they've made significant improvements in safety for this model just in the last month, and taking more time to make sure it doesn't negatively affect society is a net positive.
Had a minor conniption until I saw the year. OpenAI just struggled to close a round. And the New Yorker just published an unflattering profile of Altman [1]. So it would make sense they'd go back to the PR strategy of "stop me from shooting grandma."
As the old saying goes (I made this up), if it was worth that much, it wouldn't be released to the public. There is absolutely zero chance that something "dangerous" would be available for 20 USD / month to basically anyone in the world. To this day, I am still puzzled when some professionals don't apply the basic logic to certain bombastic events.
The current "too dangerous" hype today is Anthropic's Mythos. They say it is so mighty that they will wall it off and only grant access to approved corporations.
An important distinction that might not be understood from scanning the headline is that "too dangerous to release" is more specifically stated as "too dangerous to open-source the full model weights", which they ended up doing anyway.
This was around the time I trained Transformer-XL (outside of OpenAI) with Ben Mann (https://yaroslavvb.medium.com/scaling-transformer-xl-to-128-...) . Originally we wanted to release train and release the weights as a kind of GPT-2.5, but our OpenAI friends pushed us to keep weights closed.
I have a lot of trouble understanding the mindset of a person who thinks that what they're building is so dangerous that it must be locked away or it will cause untold harm, but also that they must build it as fast as possible.
I can understand it in the context of the Manhattan project, where you're fighting a war for survival. I cannot understand how you can do it as a commercial enterprise.
Wow! I totally remember reading the bit I'll quote down below back in 2019 and having my mind utterly blown. What a blast from the past. If anything, I think this moment was even more astounding to me than GPT 3.5, 4, etc.
> For example, researchers fed the generator the following scenario:
> > In a shocking finding, scientist discovered a herd of unicorns living in a remote, previously unexplored valley, in the Andes Mountains. Even more surprising to the researchers was the fact that the unicorns spoke perfect English.
> The GPT-2 algorithm produced a news article in response:
> > The scientist named the population, after their distinctive horn, Ovid’s Unicorn. These four-horned, silver-white unicorns were previously unknown to science. Now, after almost two centuries, the mystery of what sparked this odd phenomenon is finally solved. Dr. Jorge Pérez, an evolutionary biologist from the University of La Paz, and several companions, were exploring the Andes Mountains when they found a small valley, with no other animals or humans. Pérez noticed that the valley had what appeared to be a natural fountain, surrounded by two peaks of rock and silver snow. Pérez and the others then ventured further into the valley. “By the time we reached the top of one peak, the water looked blue, with some crystals on top,” said Pérez.
I'm somewhere between frustrated and baffled why people raise this as an example of overselling. This was clearly a reasonable call! Not all the experts quoted in the source article agree that the model should have been held back, but they all agreed that the risks were real and it's understandable why OpenAI would do it.
Now that I see this in the light of the recent sama article, I wonder whether the point of the "it's too dangerous" rhetoric is to enable "Open" AI to avoid open-sourcing the weights and process.
A convenient pretext for maintaining a monetizable competitive advantage while claiming a benevolent purpose.
What a blast from the past. You have to take yourself back in the ol' time-machine to remember that 2019 mindset. People were probably still reeling from a few years prior when the Microsoft Tay bot made news for soiling twitter with naughty tweets.
They finally did release 2.0 under the MIT license. That was the last version (a 1.5-billion-parameter model) they would release open source. GPT3 for comparison has 175 billion parameters.
Very safe to use the outputs to make a better model coz scraping the internet for publicly accessible content means your publicly shared outputs only become part of the same lol
I remember seeing this article and example output text and feeling what's the big deal?
It wasn't until I got early access to GPT-3, that I though like something big is about to happen. At the time only a few companies/yc alums had access and I remember showing playground to people outside of tech, and my friend just kept asking "How does it know about my [x] domain? It it a trick?".
AI systems far weaker than GPT-2 have had terrible effects. The result of how information and power is distributed mostly flows along the lines of reward hacking recommendation engines, powered by even weaker models.
And yet, somehow, it is beyond disagreeable but unbelievable that other people may have and may still reasonably believe that these things are too dangerous for widespread release?
I fine tuned GPT-2 on the FAR (federal acquisition regulation) and demoed it to a CFO at a 3-letter.
This was shortly after the release when we were building a templating system to automate RFP and RFI creation.
I proclaimed that the customer soon wouldn't have to write any of the mad lip parts themselves, and they can use AI to do it.
It sounded great until I demoed and the model went off the rails with some rhetoric entangling "Trump", "Russia", "China", "CIA", "Voting" -- the demo was for a janitorial procurement at the agency.
Theads now of "Doctorow vs Zuboff", perhaps the two biggest critics of tech today, but Doctorow noting how Zuboff's criticism is really a radical super over amplification of ad-tech/big-tech's pitch, heightened to the point of being much scarier than the initial pitch. More than accepting the pitch, radically over accentuating the effectiveness of the ad-tech proposition! Yes ad-tech totally completely understands you! In vastly deep ways! How horrifying right? No, please don't keep signing up for your business to succeed by tapping this incredible keep infinitely detailed knowledge-bank of humanity that can predict everything! Don't give them money to make your business wildly successful beyond dream for their incredible insight! That would be so bad if their amazing tech let you exploit the population to amazingly target delivery of what you are selling! How horrible how effective it is!!
https://www.cigionline.org/articles/doctorow-versus-zuboff/https://www.schneier.com/blog/archives/2020/08/cory_doctorow...
This is happening so so strongly. All the time. But today especially. Mythos is a cult forming social technology much more than it is a technical technology. I'm going to be pretty wrong on that cynicism, I know! But also, it portrays a reality of what is happening. Mythos is being built as a Devs like diety with rule and domonion and awe. It drinks the nectar forbidden to man. We may not even sample this realm's tastes, nay! It would be ruin!!
The idea that this preciariat-launch to some trusted security firms is going to do jack all to actually build a base against what comes next is a joke. Maybe there is something to it, but my strong expectation is that the beneficiaries are not softwares of the world, not open source in any form, but some narrow closed far off present-day losers who have broadly bad bad bad systems that are just too big to embarrass. Too big too shame.
But more so, that this model gains a cascade of levels of notoriety by being Zuboff style too good to release.
Thus begins the new age. Hardware is now broadly post consumer, too expensive to buy. Mythos means nothing, is nothing. It's just the Zuboff excuse to roll the ladder up further, the reason to move from GPT-5.4 Pro prices of $270/1m tokens output to $2700+++/1m tokens. Mythos is the Zuboffian campaign to train us for the next 10x price increase. To tell us everything we have done is shit.
And given its costs to run: that's still going to be nowhere near enough!
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I use Codex btw, and I really love it. But some of these companies have been so overhyping the capabilities of these models for years now that it's both funny to look back and tiresome to still keep hearing it.
Meanwhile I am at wits end after NONE OF Codex GPT-5.4 on Extra High, Claude Opus 4.6-1M on Max, Opus 4.6 on Max, and Gemini 3.1 Pro on High have been able to solve a very straightforward and basic UI bug I'm facing. To the point where, after wasting a day on this, I am now just going to go through the (single file) of code and just fix it myself.
Update: some 20 minutes later, I have fixed the bug. Despite not knowing this particular programming language or framework.
> I am now just going to go through the (single file) of code and just fix it myself.
That's front page news, in this era.
> a very straightforward and basic UI bug
Show us the code, or an obfuscated snippet. A common challenge with coding-agent related posts is that the described experiences have no associated context, and readers have no way of knowing whether it's the model, the task, the company or even the developer.
Nobody learns anything without context, including the poster.
> after wasting a day on this, I am now just going to go through the (single file) of code and just fix it myself.
Seriously, you wasted a whole day just so you wouldn't have to look at a single file of code?
> Update: some 20 minutes later, I have fixed the bug. Despite not knowing this particular programming language or framework.
Be really careful there, you might have accidentally learned something.
But I think that is the best way to have a clear mental model. Otherwise, no matter how careful, you always have tech debt building and churning.
Also they really suck at UI bugs and CSS. Unit test that stuff.
> I am now just going to go through the (single file) of code and just fix it myself.
You can't it's all vibed, you'll face the art vs build internal struggle and end up re-coding the entire thing by hand.
Think about how much things have changed in our industry since GPT-2 has dropped - it WAS that dangerous, not in itself, but because it was the first that really signaled a change in the field of play. GPT-2 was where the capabilities of these were really proven, up until that point it was a neat research project.
Mythos is similar. It's showing things we haven't seen before. I read the full 250 page whitepaper today (joys of being pseudo-retired, had the hours to do it), and I was blown away. It's capabilities for hacking are unparalleled, but more importantly they've shown that they've made significant improvements in safety for this model just in the last month, and taking more time to make sure it doesn't negatively affect society is a net positive.
[1] https://www.newyorker.com/magazine/2026/04/13/sam-altman-may...
Not equivalent to Anthropic Mythos.
I can understand it in the context of the Manhattan project, where you're fighting a war for survival. I cannot understand how you can do it as a commercial enterprise.
> For example, researchers fed the generator the following scenario:
> > In a shocking finding, scientist discovered a herd of unicorns living in a remote, previously unexplored valley, in the Andes Mountains. Even more surprising to the researchers was the fact that the unicorns spoke perfect English.
> The GPT-2 algorithm produced a news article in response:
> > The scientist named the population, after their distinctive horn, Ovid’s Unicorn. These four-horned, silver-white unicorns were previously unknown to science. Now, after almost two centuries, the mystery of what sparked this odd phenomenon is finally solved. Dr. Jorge Pérez, an evolutionary biologist from the University of La Paz, and several companions, were exploring the Andes Mountains when they found a small valley, with no other animals or humans. Pérez noticed that the valley had what appeared to be a natural fountain, surrounded by two peaks of rock and silver snow. Pérez and the others then ventured further into the valley. “By the time we reached the top of one peak, the water looked blue, with some crystals on top,” said Pérez.
A convenient pretext for maintaining a monetizable competitive advantage while claiming a benevolent purpose.
Playing on fear instead of the bright future you are opening up for us all is not the feeling I would want to leave the public with
https://youtu.be/CepW8wAuL_M
It wasn't until I got early access to GPT-3, that I though like something big is about to happen. At the time only a few companies/yc alums had access and I remember showing playground to people outside of tech, and my friend just kept asking "How does it know about my [x] domain? It it a trick?".
And yet, somehow, it is beyond disagreeable but unbelievable that other people may have and may still reasonably believe that these things are too dangerous for widespread release?
This was shortly after the release when we were building a templating system to automate RFP and RFI creation.
I proclaimed that the customer soon wouldn't have to write any of the mad lip parts themselves, and they can use AI to do it.
It sounded great until I demoed and the model went off the rails with some rhetoric entangling "Trump", "Russia", "China", "CIA", "Voting" -- the demo was for a janitorial procurement at the agency.
This is happening so so strongly. All the time. But today especially. Mythos is a cult forming social technology much more than it is a technical technology. I'm going to be pretty wrong on that cynicism, I know! But also, it portrays a reality of what is happening. Mythos is being built as a Devs like diety with rule and domonion and awe. It drinks the nectar forbidden to man. We may not even sample this realm's tastes, nay! It would be ruin!!
The idea that this preciariat-launch to some trusted security firms is going to do jack all to actually build a base against what comes next is a joke. Maybe there is something to it, but my strong expectation is that the beneficiaries are not softwares of the world, not open source in any form, but some narrow closed far off present-day losers who have broadly bad bad bad systems that are just too big to embarrass. Too big too shame.
But more so, that this model gains a cascade of levels of notoriety by being Zuboff style too good to release.
Thus begins the new age. Hardware is now broadly post consumer, too expensive to buy. Mythos means nothing, is nothing. It's just the Zuboff excuse to roll the ladder up further, the reason to move from GPT-5.4 Pro prices of $270/1m tokens output to $2700+++/1m tokens. Mythos is the Zuboffian campaign to train us for the next 10x price increase. To tell us everything we have done is shit.
And given its costs to run: that's still going to be nowhere near enough!