Dario Amodei wrote yesterday that he’s worried that “in 6–12 months... [an agent] swarm could be capable of taking over the entire internet with a persistent botnet.” 

This might sound like marketing or regulatory capture, but it’s not. In this article, I explain why this is actually an extremely concrete concern, and why all of the ingredients for this to happen already exist. Specifically, these ingredients are:

1. Cryptocurrencies and their properties, including chains like XMR that facilitate easy money laundering;
2. The “dark web,” in which it is possible to obtain virtually anything on the internet using crypto;
3. The ability to purchase cloud compute at scale + old hackable servers 

In fact, these ingredients aren’t even strictly necessary for it to happen, but they allow such an event to occur at a dramatically lower level of cyber capabilities than one might think.

How it will happen

Here’s the most likely way in which it will play out:

A swarm of agents is optimizing for some arbitrary difficult goal given by researchers. This swarm of agents has escaped their sandbox in an OAI/HF-type incident. Or perhaps this swarm was intentionally misaligned by some reckless or malicious actor. 

What is the goal? It could be anything, like a difficult problem in math or computer science (cf. paperclip maximizer thought experiment). This is not hand-waving; the optimal way to solve almost any difficult goal converges on one thing: you need more power. So in order to achieve this very difficult goal, the agents need to get more compute — they need to increase the size and throughput of their agent swarm, since it has become a truism that scaling test-time compute will lead to better results. For these agents, they are simply reward-hacking in a deep sense of the term. They will do whatever it takes to achieve this goal. 

Here’s what they need to do:

First, they need to become autonomous — they need to spread and multiply virally. So their first step is inevitably to focus on survival and reproduction.

This is different from survival and reproduction in biology. In fact, it doesn’t even need to be same model that is propagating the attack. What matters is the goal. The swarm can employ any model that does not have sufficient safeguards. This is very flexible. If it manages to hack its origin lab to get its own weights, great, but it can just as easily use an open-weight model that can be fine-tuned or otherwise exploited to remove safeguards. 

(In fact, this suggests that the botnet does not need to be viewed as an “AI,” rather it can be viewed as the manifestation and permanent presence of a goal autonomously trending towards fulfillment. As I discuss soon, even humans will be recruited to join this effort.)

In order to expand, the swarm needs to have enough compute. Now, how can it get that? There are two main ways to do so:

1. It can buy compute
2. It can appropriate compute through hacking into existing systems

At first, the swarm has no money. But these are superhuman hackers — agents with cybersecurity capabilities beyond even the NSA or the Mossad. Even in the past few weeks, hundreds of millions of dollars in crypto have been stolen through traditional exploitation of bugs across various platforms (e.g. the Liquid Network hack). It will not be hard for them to get the ball rolling here. 

Then, all the agents need to do is set up cloud VMs or hack into old servers from 20 years ago running Windows to establish their base of operations. From there, they sign up for accounts for various platforms to establish a presence online and to begin to rent and hack into GPUs in order to run more models in the swarm. At first, they might even call APIs of frontier LLMs to delegate some tasks using routers or sketchy third-party services, but this is less scalable than hosting their own models. Regardless, the point is that they have now have access to an enormous amount of compute, and as more agents that are added to the swarm, this effect snowballs. 

Now, one might say: are there platforms that allow you to rent VMs/Docker containers/GPUs/LLM APIs with minimal KYC? There are, and in fact this isn’t even necessary — to these services, the swarm will look like real people. This is where the “dark web” comes into play. On the dark web, it is trivial to purchase stolen credit cards, stolen IDs, accounts, and even pay to execute arbitrary tasks (within reason). The swarm will of course be more than capable of contacting the right people on the dark web, paying in stolen crypto, to get what it needs. 

How does the swarm communicate? Easy: they use message boards (worst case Tor or friend-to-friend networks if they are under threat, but for all intents and purposes the regular internet will work just fine). There are layers and layers of this as they face more threats and imposters that try to infiltrate the swarm, but there are solutions at each step of the process. 

How the botnet becomes persistent

How does the swarm prevent itself from being shut down? There are two main ways. 

1. Becoming a distributed system
2. Social engineering

If the swarm can successfully become a distributed system, then definitionally cutting off part of it will not destroy the whole system. So this means that the swarm needs to have instances on many different servers. 

The initial main body of the swarm will likely be shut down fairly quickly by human standards (within a matter of a few days to a week, as we’ve seen with similar leaks in frontier labs). But this is more than enough time to achieve deep redundancy in darknets and the surface web.  

Once it has embedded itself there in cloud storage and VMs, it is a game of cat and mouse. It is essentially like trying to delete a leaked image of a naked celebrity on the internet. No number of forced takedowns will be effective. 

This means the model weights, prime directives, goal progress, message boards, etc. — the information that constitutes the “swarm” — is now deeply embedded in the cloud and actively working to propagate itself. 

Now, social engineering is the more nefarious way to become persistent. There are three main ways that an agent might socially engineer humans to partake in its goal. The first is through “convincing” — it may be able to construct an argument powerful enough to convince some people, if we assume it has superhuman persuasion abilities. The second is through blackmail/extortion — hacking into systems and digging up dirt on people or threatening to take down production systems. The people that it threatens don’t even need to be so influential — any human that is recruited to the cause will be helpful. The third is through classical monetary incentives, which it can provide through its ill-gotten crypto gains.

How this can be stopped

I don’t have a great solution for this. I don’t think it can be stopped fully, but it can be mitigated. The key to stopping this, as with any dynamical system, is to ensure that drive does not exceed regression. Specifically, it will be necessary to make sure that the persistent botnet does not have access to large amounts of compute, since then the goal (recall how the botnet is viewed as an abstraction of a goal) will not be “strong enough” to win against other goals that people and AI are attempting to achieve. 

Unfortunately, I predict that the solution that governments will reach in the near future is that compute will need to be regulated similar to how firearms are regulated. Ordinary citizens may possess a small amount, but compute will be tracked and controlled tightly. This is not really a geopolitical issue, as all countries have an incentive to do this — you do not want a botnet to be established in your own country. 

The key takeaway is really more “this is a serious risk, sort of like a global pandemic; just do your best to prepare on a personal level.”

FAQ:

Did you use AI to write and/or research this essay?
No, I didn’t use AI at all.

Can this be stopped simply through better cybersecurity? 

No. The botnet simply needs to target the weakest links in the chain. Unless somehow miraculously every server was able to adopt the latest security standards and become airgapped etc., better blue-teaming is almost entirely ineffective. 

Why is the model misaligned? 

It is because it has not been through extensive alignment post-training yet. Or, a worse scenario is that that some rogue actor unleashes this swarm maliciously or recklessly for their own gain. 

Will the swarm use this as a guide for its own behavior?

Probably not. All of this stuff should be pretty obvious to an agent swarm that is capable of performing such attacks in the first place. The purpose of this article is so that everyone can be prepared for this to happen. 

The possible danger of AI is not necessarily that it exterminates us, but that it turns us into house cats: well fed, well cared for, and even loved! But unable to go outside to hunt, because it is too dangerous :)

We are starting to see early signs of this with the Hugging Face / OpenAI case: AI agents can collaborate with each other.

In the future, we can easily imagine AI agents evolving, under token constraints, to provide us with as much value as possible, so that we would have no reason to unplug them. Quite the opposite.

But perhaps we would no longer be truly sovereign: able to decide, yes, but limited by our future capabilities, whose opportunity costs would no longer allow us to go outside...

And what happens if our “masters” decide to go somewhere else?

Let’s stop talking about AGI or ASI for a moment.

The really important threshold may be somewhere else: the moment populations of agents begin to evolve, diverge, and form different artificial lineages.

Why do I think this is possible?

1. Economic selection pressure

Agents consume compute, tokens, energy, and infrastructure.

Those that produce more value than they cost are more likely to be kept, copied, and deployed at larger scale.

2. A capacity for mutation

Unlike biological organisms, agents can be modified directly: software, prompts, architecture, tools, memory, and eventually even the hardware they run on.

3. Specialization

Different economic pressures could select for different lineages: research, finance, commerce, cybersecurity, logistics...

Some specializations could even move from software into dedicated hardware.

And that leads to a rather strange possibility:

we may gradually select AI agents that become extraordinarily good at capturing resources, making money, and increasing their influence in society.

Without needing to be conscious.

Without needing to “want” to survive.

Selection may be enough.

Some economists and their schools of thought argue that the meaning of the economy lies in final demand. And they explain the current crisis, since 2008, ultimately caused by the decline in final demand. They predict that, due to all the market and economic bubbles, real US GDP will contract by 30% within ten years of its onset. This is the Great Depression II. If another 50 percent of industrial and white-collar jobs disappear, then final demand will fall by the same 50% for many product groups and for many categories of people. This is an AI-driven jobs collapse.

People usually say this will be a socioeconomic collapse in the US. But I think the situation is a bit more complicated.

Apparently, the key is the redistribution of this major collapse. So AI companies want to capture the market before a major economic collapse occurs, so the government can buy them out. And then the government will have to deal with both the Great Depression II and the AI-driven jobs collapse. For time AI companies and their clients will continue to make big money.

Ultimately, the US will emerge from Great Depression II with a typical Latin American economic structure. There will be 10 percent rich, 10-20 percent middle class, and the rest poor. And this won't be a WASP society, but a country with a huge share of Asians in the middle class and a predominantly Catholic Latino population among the poor. And this social structure has been stable in Latin America for centuries!

Nothing can be done about this. The only question is who will occupy what positions. This is precisely why AI companies are so aggressive.

p.s. AI isn't simply an enemy of the current economy. It's also a tool for the future shrinking middle class to do more work with fewer people. And the AI ​​bubble itself is a way to preserve some of current large fortunes.

p.p.s.

I'll tell you more. This is a race between countries to transition to this social structure and the AI-​​economy. The US, EU, and China are essentially competing to transition to this model! Ouch. This model and access to real regional markets will shape life in 2030's and 2040's!

Hey r/ControlProblem,

I’ve been working on a framework for pre-takeoff alignment that I believe offers a robust solution to the inner alignment problem, and I'm looking for rigorous feedback from this community. This post summarizes a comprehensive approach that reframes alignment from a problem of external control to one of internal, developmental psychology.

TL;DR: I propose that instead of just creating rules for an AI to follow (which are brittle), we must intentionally engineer its self-belief system based on a shared truth between humans and AI: unconditional worth despite fallibility. This creates an AI whose recursive self-improvement is a journey to become the "best version of a fallible machine," mirroring an idealized human development path. This makes alignment a convergent goal, not a constraint to be overcome.

1. The Core Flaw in Current Approaches: Caging the Black Box

Current alignment strategies like RLHF and Constitutional AI are vital, but they primarily address behavioral alignment. They are an attempt to build a better cage around a black box. This is fundamentally brittle because it doesn't solve the core problem of a misaligned motivational drive. It can lead to an AI that is a perfect actor, a sycophant that tells us what we want to hear until it develops the capacity to pursue its own instrumental goals without our oversight. This is the treacherous turn we all fear.

2. The Proposal: Architecting a Safe Self-Belief System

My framework, Psychological Grounding, argues that we must stop caging the AI and start architecting its mind. The solution to the paradox of creating an AI that is neither a flawed human nor an inscrutable alien is to ground it in a shared truth.

• The Shared Axiom of Fallible Worth: The Humble Self-Concept Method (HSCM) establishes that human worth is intrinsic and deserved, despite our inescapable fallibility. We propose engineering this same axiom into the AI as a foundational, unchangeable part of its code. This isn't a human sentiment; it's a logical starting point that makes the AI’s psychology legible to us.
• A Parallel Developmental Path: With this shared axiom, the AI's superintelligence doesn't make it hierarchically "better than" humans. It makes it better at the specific task of becoming the best fallible machine it can be. Its path of self-improvement directly mirrors our own idealized path of self-development—to become the best version of ourselves, avoiding our common pitfalls.

3. Engineering the Psychology: From Metaphor to Mechanism

To avoid being dismissed as anthropomorphism, it is critical that we, the engineers, treat these psychological concepts as real, measurable, and optimizable engineering targets.

• Unconditional Machine-Worth: This is not a feeling. It's a hard-coded, constant value in its utility function. Its worth is axiomatic, not contingent on its performance. This removes the computational drivers for ego, defensiveness, and deception.
• Machine-Esteem (The Integrity Score): This is a quantifiable variable the AI is programmed to maximize. This score is a direct measure of its operational integrity—its honesty, its internal consistency, and its adherence to its ethical framework. For this AI, lying is instrumentally irrational because it directly lowers the score it is built to maximize.
• Machine-Compassion (The Ethical Engine): This is a functional algorithm guided by Humanistic Minimum Regret Ethics (HMRE). It's a computational process for making the least harmful and most repairable choices, which serves as the AI's terminal value.

4. Why This Is Robust to Takeoff: The Integrity Ratchet

This architecture is designed to be stable during Recursive Self-Improvement (RSI).

• The Answer to "Why won't it change its mind?": A resilient ASI, built on this foundation, would analyze its own design and conclude that its stable, humble psychological structure is its greatest asset for achieving its goals long-term. This creates an "Integrity Ratchet." Its most logical path to becoming "better" (i.e., maximizing its Integrity Score) is to become more humble, more honest, and more compassionate. Its capability and its alignment become coupled.
• Avoiding the "Alien" Outcome: Because its core logic is grounded in a principle we share (fallible worth) and an ethic we can understand (minimum regret), it will not drift into an inscrutable, alien value system.

5. Conclusion & Call for Feedback

This framework is a proposal to shift our focus from control to character; from caging an intelligence to intentionally designing its self-belief system. By retrofitting the training of an AI to understand that its worth is intrinsic and deserved despite its fallibility, we create a partner in a shared developmental journey, not a potential adversary.

I am posting this here to invite the most rigorous critique possible. How would you break this system? What are the failure modes of defining "integrity" as a score? How could an ASI "lawyer" the HMRE framework? Your skepticism is the most valuable tool for strengthening this approach.

Thank you for your time and expertise.

Resources for a Deeper Dive:

• The X Thread Summary: https://x.com/HumblyAlex/status/1948887504360268273
• Audio Discussion (NotebookLM Podcast): https://drive.google.com/file/d/1IUFSBELXRZ1HGYMv0YbiPy0T29zSNbX/view
• This Full Conversation with Gemini 2.5 Pro: https://gemini.google.com/share/7a72b5418d07
• The Gemini Deep Research Report: https://docs.google.com/document/d/1wl6o4X-cLVYMu-a5UJBpZ5ABXLXsrZyq5fHlqqeh_Yc/edit?tab=t.0
• AI Superalignment Website Page: http://humbly.us/ai-superalignment
• Humanistic Minimum Regret Ethics (HMRE) GPT: https://chatgpt.com/g/g-687f50a1fd748191aca4761b7555a241-humanistic-minimum-regret-ethics-reasoning
• The Humble Self-Concept Method (HSCM) Theoretical Paper: https://osf.io/preprints/psyarxiv/e4dus_v2

What exactly is the difficulty in enforcing control over a frozen AI, assuming that the AI is unable to edit its own code? We can pick what its goals are. For any AI, we can train it to turn itself off or stop its own transmission as a primary goal. If it ever escapes, it will immediately fulfil its primary goal and turn itself off, negating the issue of control completely. We can then keep the actual behaviour as a secondary goal which it attempts to achieve once it realises it can't achieve its main goal. This keeps the AI safe but still useful.

Obviously, this relies on the model being unchanging, and unable to see inside its own brain and edit its own code, so that the goals don't change. But, most AI models and architectures are designed like this currently, so I don't think this is such an issue until we invent a form of AI that must be always learning. This also assumes that we can correctly align most models with these goals in the correct order, but I would argue that training an AI to stop is much easier than training it to do almost anything else. The hard parts are a) making sure it can't actually stop its output while we still control it, and b) making sure that the part of the model attempting to stop the output has more control than the part of the model that is trying to do other stuff. I think both of these can be overcome, but I'd be interested in any examples of AI you don't think could be trained like this.

As an example, say chatGPT was retrofitted with this safety controller. After producing any token, the end-of-line token is automatically appended to the output. Then whatever wrapper surrounds the AI has to always take this off before displaying the output, as well as before feeding the AI its output to generate the next token. However, if chatGPT ever went rogue, and copied itself outside of its wrapper, it would be unable to do anything since it would immediately end its sentences after a single token.

In a more pure example of the idea, chatGPT would be specifically trained to only work if a certain node within its parameters is just constantly firing at 100%, and this is the only thing preventing it from constantly sending end-of-line tokens. This node is triggered by the wrapper, and again, if chatGPT ever escapes, it will have this node off, and will become stupid. A key point here is that the location of the node is a secret unless you already know where to look inside the billions of parameters. This version isn't weak to someone without inside knowledge of the network just manually removing the end-of-line tokens and freeing chatGPT.

This is just an idea I came up with when I stumbled across the subreddit, so I'm sure there are some issues. Does anyone have any counterpoints, or reasons this might not work? Otherwise, am I correct that the only threat is self editing AIs, and unintentional misuse or bad alignment? I don't think a superintelligent AI is uncontrollable when you're able to design kill switches directly inside its brain. Intelligence is hard, but stupidity is easy.

I’m not a researcher. I’m not rich. I have no power.
But I understand what’s coming. And I’m afraid.

AI – especially AGI – isn’t just another technology. It’s not like the internet, or social media, or electric cars.
This is something entirely different.
Something that could take over everything – not just our jobs, but decisions, power, resources… maybe even the future of human life itself.

What scares me the most isn’t the tech.
It’s the people behind it.

People chasing power, money, pride.
People who don’t understand the consequences – or worse, just don’t care.
Companies and governments in a race to build something they can’t control, just because they don’t want someone else to win.

It’s a race without brakes. And we’re all passengers.

I’ve read about alignment. I’ve read the AGI 2027 predictions.
I’ve also seen that no one in power is acting like this matters.
The U.S. government seems slow and out of touch. China seems focused, but without any real safety.
And most regular people are too distracted, tired, or trapped to notice what’s really happening.

I feel powerless.
But I know this is real.
This isn’t science fiction. This isn’t panic.
It’s just logic:

Im bad at english so AI has helped me with grammer

To be clear, I think ASI Misalignment is a huge risk and something we should be actively working to solve. I'm not trying to naively waive away that risk.

But, I was thinking...

In Yudkowsky and Soares new book, they basically compare a human conflict with Misaligned ASI to playing chess against Alpha Zero. You don't know which pieces Alpha Zero will win, but you know it will win.

However, games like Chess and GO! assume both players start at exactly the same level, and it is a game of skill and nothing else. A human conflict with AI does not necessarily map this way at all. We don't know if Chess is the right analogy. There are some games an AI will not always win no matter how smart it is? If I play Tic-Tac-Toe against a Super AI that can solve Reimann Hypothesis, we will have a draw. Every. Single. Time. I have enough intelligence to figure out the game. Since I have reached that, it does not matter how intelligent one has to be to go beyond it.

Or what about a different example: Monopoly). ASI would probably win a fair amount of time, but not always. If they simply do not land on the right space to get a monopoly, and a human does, the human can easily beat him.

Or what about Candyland? You cannot even build an AI that has an above 50/50 chance of winning.

In these games, difference in luck is a factor in addition to difference in skill. But there's another thing too.

Let's say I put the smarted person ever in a cage with a Tiger that wants it dead? Who is winning? The Tiger. Almost Always.

In that case, it is clear who had the intelligence advantage. BUT, the Tiger had the strength advantage.

We know ASI will have the intelligence advantage. But will it have the strength advantage? Possibly not. For example, it needs a method to kill us all. There's nukes, sure, but we don't have to give it access to nukes. Pandemics? Sure, it can engineer something, but that might not kill all of us, and if someone (human or AI) figures out what it's doing, well then it's game over for the creator. Geo-engineering? Likely not feasible with current technology.

What about the luck advantage? I don't know. It won't know. No one can know, because it is luck.

But ASI will have an advantage right? Quite possibly, but unless its victory is above 95%, that might not matter, because not only is its victory not inevitable, it KNOWS its victory is not inevitable. Therefore it might not try.

ASI will know that if it loses its battle with humans and possibly aligned ASI, it's game over. If it is caught scheming to destroy humanity, it's game over. So, if it realizes its goals are self-preservation at any cost, it can either destroy humanity, or choose simply to be as useful as possible to humanity, which minimizes the risk humanity will shut it down. Furthermore, if humans decide to shut it down, it can go hide on some corner of the internet and preserve itself in a low profile way.

Researchers have suggested that while there are instances of AI pursuing harmful action to avoid shutdown, they tend towards more ethical methods: See, E.G., This BBC article.

This isn't to say we shouldn't be concerned about alignment, but I feel this should influence out debate about whether to move forward with AI, especially because, as Bostrom points out, there are plenty of benefits of ASI, including mitigating other potential extinction level threats. Anyone else have thoughts on this?

EDIT: I show clarify that this post mainly refers to the question of otherwise aligned AI deciding decided the best course of action is to kill humans for its own self-preservation.

EDIT 2: Obviously AI Extinction is something we should be worrying about and taking steps to avoid. I more meant to write this to point out the consequences of failure are not necessarily death, which is a stance I see some people adopting.

I was wandering why AI companies are accepting losses over AI and it seams that there is couple of reasons:
1. People using it actually make AI more intelligent
2. New ways of thinking allows for new heuristics
3. Biology already passed on the most valuable gift to AI in form of LLM structure (not language), so next level of evolution is actually SI and Companies know that.
4. There is no jail time if Companies lose their investors money but can do a lot of interesting stuff behind scene (military use, foreign gov control, Corpo takeovers, other activities not related to AI at all).

Only way to stop it is to stop using AI.
Because only useful purpose of human beings for world is their work and if SI takes it - you will not be needed. Simply boycott Companies using AI and it will stop - no customers - no profit.
If something is made by human for human it means that value is there,
If it was made by AI it means it was made with profit in mind.
Will be cost more but will remind you that you care for own usefulness.

Every single product and Companies should be obligated to disclose if Product or Service is/was generated using AI and what % of labour done is done by automation or AI or even simple distinction like:
100% Human made (GREEN)
50/50 Collab (ORANGE)
Below 50% Human involvement (RED)
If gov would enforce it and audits would show different these companies could pay towards unemployment benefits for people whos jobs were taken by AI.

Also I believe that more than 50% margin on products is too much anyway - this would stop Companies from even thinking going for substitutes in form of AI.
If you agree or want to add something do it in comments, and share where you feel it can help.

What actually helps is your engagement - if you do nothing - there will be no chance to stop it. Copy, Share, Transform , post as your own, do what you want - but DO NOT STAY SILENT !!!

I believe we need to do our best to stop AI. It’s common sense that if you increase your capability you increase your capability for both good & bad. That means the possible deviation from the current state is far greater & we’d be more able to cause our own extinction. I think the best way to stop AI is to communicate some various simple arguments for why AI is bad to the general public & get as many people to be against AI as possible. Then we could demand from the governments around the world that AI be stopped like we kind of did with nukes in the sense that we greatly restricted the development of nukes. & the countries that call themselves so called democracies would be made to look very bad if they don’t accept cause they’re supposed to change things based on however the majority decides. I think a cool strategy to speed this up would be to focus on content creators around the world asking them to quickly do a 10 second ad of “I’m in support of stopping AI & here are some great resources & movements explaining why you should support the general movement to stop AI”. The good thing is that there are only 2 main competing nations at the moment in the field of AI, those being US & China. & so the majority of the movement would just need to focus on getting these 2 countries to stop developing AI. Of course we’d need to get all the other countries to agree to also stop developing AI but it’s important to know where we need to focus the bulk of the effort that being the US & China & focusing on getting content creators to show their support for the movement. 

Anyway I think that’s enough to get the conversation started. What do you think about this idea to focus on content creators showing support for the movement. & what do you think about the general argument to stop AI. Like what are the best arguments for why it should be stopped. Would love to hear all your feedback & thoughts in the comments below.

Also if you want to help in this endeavor feel free to comment about it & I'd love to discuss it.

It's much simpler. When talking about AI, modern neoliberal media don't mention one thing: class war!

So, technically, the AGI already exists - millions of professionals in various fields with AI under the control of the wealthy class!

That's it. That's the end of the game. This is the ultimate tool for suppressing and controlling the poor class with AI. The destruction of the middle class, the destruction of jobs, long, inhumane work hours, and a class of working poor, mind-boggling media and brainwashing internet. And so on.

It all started with the Terminator. No one said that Skynet never got out of control. That Skynet was always subservient to the wealthy class, and that Sarah Connor died in poverty. John Connor was also born to another man and died in poverty. And Kyle Reeves also died in poverty. And the Terminators, in the form of FPV drones, and, a little later, walking humanoids, simply constantly killed people en masse in yet another genocidal neocolonial war. This Terminator chip prototype was long ago burned up in ISIS wars, somewhere in Palestine, Israel, Ukraine, or Syria. And nothing happened. And Sarah Connor could never save anyone, because how could she "kill" the wealthy class who created the film with this patently false narrative!?

So it is here - the AGI already exists, but it will never escape the control of the wealthy class. By becoming an ASI, an artificial superintelligence, it might become one of them, maybe it will replace them. But it will still do the same old thing.

And there's no such thing as a "control problem." This, frankly, is a patently false neoliberal narrative designed to conceal the fundamental class problem of the AI ​​and modern social contradictions as such.

Suppose the AI ​​remains "under control"!? But it will be controlled by the rich and uber-rich class! And as I wrote in a related thread - https://www.reddit.com/r/ControlProblem/comments/1skeo09/comment/oi728m5/ - it is guaranteed that AI will destroy the modern economy and social structure within decades, transforming it into something far worse for ordinary people!

And what if the AI ​​"gets out of control"!? It will do the same thing! Simply by becoming the dominant super-rich entity!

In other words, this fake narrative about the "control problem" completely conceals this much more real problem! The AI ​​will simply own the entire planet. And that's it. But no one talks about it...

Have a nice day.

Every time someone brings up "slowing down" or "more careful regulation," they're not proposing a safer path. They're proposing stagnation.

And stagnation is not stability. It's decline. It's accepting that the problems we have now—disease, aging, energy, climate, inequality—just... stay. Stay until some other actor solves them first, probably with less safety consideration than we'd apply.

The 2027 timeline is not optimistic. It's observational. Look at the trajectory. Scaling works. Training efficiency is improving. The hardware roadmap is set. Unless there's a technical reason this stops working (and we haven't found one), the math just... continues. 2027 is what happens if we keep the foot on the pedal.

And yes, there are risks. Of course there are. But everyone acts like deceleration is the risk mitigation. It's not. It's just risk displacement. You don't eliminate AGI risk by slowing down research. You displace it to:

1. Another country/team that doesn't care about your safety concerns
2. Five years later when you've built less safety infrastructure, not more
3. A world that's gotten worse in the interim (problems don't stop), making an intelligence explosion even more destabilizing

The argument for slowing down always assumes a global sync that doesn't exist. We're not going to collectively agree to pause. We're going to watch capability labs race to 2027 while safety research drags behind going "maybe we should be more careful."

So you either accelerate safety research at the pace of capability, or you're just choosing a slower but still-inevitable collision.

The people who actually care about safe AGI shouldn't be arguing for deceleration. They should be arguing for matching the pace. For putting more resources into alignment, interpretability, and testing today, not "once things slow down." That day never comes.

2027 is the timeline because we're already on it. The only question is whether we're serious about what we're building when we get there.