I agree. It is sad that many do not want to see the writing on the wall (or rather they choose not to see it until its too late).
The old world is about compute, energy and models. It's all about the illusive chase of acronyms AGI, SSI or ASI (whatever they mean based on the changing definitions).
Statistical pattern matching and prediction makes intelligence emerge was the thesis.
This thesis came at a cost, more better chips, more compute, more cash and more energy. But none of this is grounded in reality.
This is not beneficial to businesses or the environment.
Human intelligence is efficient, grounded in reality and has adaptive agency.
Now, the large models are the opposite of this. They are highly inefficient since they consume a tonne of energy, compute and capital. The "intelligence" generated by these models is based on statistical pattern matching and prediction (passive), not based on how the human brain or mind operates.
We do need some form of adaptive agency, just like human beings correcting and improving on the fly.
I find the entire discussion surrounding AGI highly questionable, aside from the marketing aimed at investors who apparently lack foresight. I consider Altman, Musk, and Zuckerberg’s admission that their AI models have not been built correctly so far—and that a different, new architecture is needed to achieve a major breakthrough—to be a step in the right direction. In my view, we should focus primarily on the meaningful use of artificial intelligence in businesses and provide answers to the following four questions.
1. How can the right information be made available to the right people at the right time and in the right format to enable responsible, collective decision-making?
2. How do we organize a set of rules that governs information flows so that all stakeholders can communicate as equals, interact effectively, and make responsible decisions together?
3. How can we design a participatory, adaptive, and systemically embedded framework for HCAI systems that permanently and dynamically balances values, power, and information flows?
4. How can such a platform not only be scaled but also qualitatively improved as the number of users grows?
Only by finding the right answers to these questions can we develop an AI architecture that creates real added value and benefits for humanity, both on a small and large scale. See also: https://friedrichschieck.substack.com/
Good questions. Also, you are right about the entire AGI hype and hubris created by popular narratives from big tech entrepreneurs and a lot of leading voices in Silicon Valley blindly buying into it.
About #2 and #3. Can we trust big tech and governments to actually do that for us? A quick look at history tells otherwise. I do not know if this question can be answered at a general level.
But I do think we can find solutions we if only decide to build smaller but more specific AI for specific use-cases in certain domains. And then it will be easier to apply governance.
I don’t entirely agree with you there. However, a brief look at history also shows that social systems (groups, companies, societies) have always been successful when points 2 and 3 were more or less fulfilled. In other words:
• The more points 2 and 3 are fulfilled, the higher the returns, growth, and prosperity.
• The less points 2 and 3 are fulfilled, the lower the returns, growth, and prosperity!
History has shown that the technologies that have prevailed are always those that resulted in the greatest benefit or the greatest value creation!
My view of human nature tells me that there will be people who will develop an AI architecture and platform that fulfills points 1 through 4, thereby enabling returns, growth, and prosperity for all! I simply believe that the greed for short-term returns will be stronger than the fear of long-term growth and prosperity for all!
See also my comment on How AGI-is-nigh doomers own-goaled humanity. Gary Marcus Mar 03, 2026
Just a note: I’m also convinced that we can find solutions if we decide to develop smaller but more specialized AI systems for specific use cases in businesses. That’s why I wrote my Substack post „The individualized and adaptive digital workplace as a key use case for a hybrid HCAI platform!”
So, watching the full interview (so you all don't have to), Altman doesn't say that a new architecture is needed for AGI, but he states that we already are very close to AGI (within 2 years) and AGI itself will help to find *another* big breakthrough for (that) AGI.
- (22:07): "I think if you are a sophomore now, you will graduate to a world with AGI in it" (i.e. AGI in 2 years)
- (22:44) "Science will be automated" (in the coming years)
- (26:35) Takes moltbook seriously
- (27:30) "robots won't be that far off" (in the coming years)
- (28:52) "It will feel like we've broken the laws of traditional speed and product development and business growth rates [...] companies will start to hire AI-coworkers and do amazing things with fewer people" — echoes "New Economy" to me and paging Brian Merchant...
- (30:20) Defines AGI as a system that "could do better at making decisions than anyone we could possible have be like say president of the United States" (Um, that is an interesting benchmark these days, but let's not digress)
- (33:22) "the jobs 100 years of from now look nothing like the jobs of today, nor do that many of the jobs of today look like the jobs of a few hundred years ago.". This one is really interesting, because that argument sounds pretty convincing until you notice he is talking about a timescale of hundreds of years...
- (36:56) "We are burning cash very fast. It is not a serious situation [...] if we can spend a billion dollars this year to make $3 billion next year, there's a lot of capital in the world that wants to do that. So we will raise a lot of money, equity and debt" (IPO coming up, but that was clear already). He's promising 200% return on investors in a year.
The actual statement on a new architecture is an answer to a question "What AI subfield today feels like OpenAI in 2016, a little undervalued or underestimated but could shoot out of nowhere?" Then he answers 'from the research perspective': "I bet there is another new architecture to find that is going to be like a big gain as transformers were over LSTM. And I think you finally have models that are smart enough to help do that kind of thing". So we are already close to AGI and that will speed up the improvement of AGI even further.
Basically it is the same as always, no real change. The beginning was also interesting. Sam is a believer in this, he has been smitten by the improvements from transformers and he has translated that rapid curve up into an exponential curve, not the beginning of the S-curve which it almost certainly is.
I wish one of those people, the very people whom he wants to most disadvantage and disenfranchise, had asked him an obvious question: if he thinks that there will still be jobs in 100 years, there must be some things that he thinks that ChatGPT, no matter what improvements "Open"AI employees may make in the future, either cannot do or should not do. Get him on "tape," metaphorically speaking, either explaining what he views as the insurmountable limitations of his company or making a promise of moral behavior that people can throw in his face later. Or make him say that he was being dishonest or foolish when he made the previous statement.
But I suppose no one wants to put these gods among humans on the spot. Just let them lie and cheat without consequence.
THREE THINGS: First, thank you for the outline--very helpful, though I want to view the video also.
SECOND, about: <- (22:44) "Science will be automated" (in the coming years)> There is a "catch" here that needs unraveling. That is, does Altman mean the science of the machine/ artificial part of intelligence, e.g., the physical sciences of it? OR does he refer to the human sciences that have an enormous influence, not on the physics but on the content?
I have written here before that it seems to me that the narratives confuse the natural elements of humans (our physics, biology, etc.) with the now much more mature social and other sciences (and the arts and history, philosophy, theology) all of which move "up" from the natural/physical to the normative that relates, (basically) to what (ironically as natural) is consciously "agentic" about human beings. And so the question becomes, what exactly informs and provides the basic dynamics of the albeit-modified freedom of thought, deliberate choices, and action that human beings regularly exhibit?
Or to put it more simply, one does not develop emotionally, intellectually, socially, ethically, politically, or spiritually by merely hearing sound (rather than language), putting a bandage on a cut or, eating vegetables rather than dirt.
And THIRD< about: <Then he answers 'from the research perspective': "I bet there is another new architecture to find that is going to be like a big gain as transformers were over LSTM. And I think you finally have models that are smart enough to help do that kind of thing". >
Does he mean only ONE architectural element? or are there perhaps many that, first, develop differently in history, and that do not hail back only to the physical/natural sciences as their mode, but to massive elements that concern human normativity?
I don’t think Sam is that thorough in his thinking, it seems all very shallow and fuzzy to me. I don’t think people should pay too much attention to what he says.
Altman does not understand much of anything. One should understand him as an embodiment of the cult of mediocrity that dominates much of the world at the moment. Altman does not have a degree in physics or in any other kind of natural or social science; rather, if I recall correctly, he studied undergraduate computer science, dropping out after two years because he was too cool for school and wanted to play startup with his parents' money. Like the other members of this cult of mediocrity, he profits from work done by people who are, in many cases, far from mediocre, and what little knowledge he himself has is secondhand at best. When he says something, it should be understood as somewhere between a lie, a confident assertion of his ignorance, or in the best case, a distorted recollection of what someone actually knowledgeable working at the company told him.
This is nothing more than a case in point. Regardless of whether current transformer models are capable of doing everything that scientists can, most physicists believe that one of the largest obstacles to developing a complete theory of physics is that there are interactions that occur so rarely, so quickly, at such small resolutions, or at such high energies (and many of these things are related), that either a great deal of time, extremely large measurement devices, or both, would be needed to distinguish between competing theories that are equally consistent with current evidence. Perhaps chatbots could come up with some very clever idea to avoid these limitations, but perhaps not. Unless the clever idea is taking over the world and building a particle accelerator out to the orbit of Jupiter, which is something I do think Altman and his crew might be foolish enough to do by accident.
However, it's hardly "deep thinking" to realize the difference between
(a) physics/nature and their empirically established and replicate laws and protocols as guides for platform building, and the folly of
(b) applying them directly to human content where human beings and their normativity is what informs much of what is scaled, and that, though
(c) human content albeit standing on sentient experience governed by physics and nature in the time-space continuum, still raises up to different levels and gradients to define even past and future speculations about what we mean by wholly human experience and reality at different moments in human developmental patterns.
"AGI itself will help to find *another* big breakthrough for (that) AGI." ... So in order to have AGI we first need AGI to help us invent it? Cool, cool, cool.
He is just recycling I. J. Good's increasing machine capability as each more powerful iteration is built by the previous one, heading towards the singularity. Of course, he might just have read The Hitchhiker's Guide to the Galaxy books and recalled that to answer the question of "What is the answer to the ultimate question", the supercomputer Deep Thought designed the next more powerful computer...the Earth.
No, he doesn't say anything about kinds of breakthroughs further down. Might be supercheap AGI for instance, might be anther improvement. The statement isn't about *reaching* AGI at all, that, he says, is going to happen in the coming two years on the current transformer trajectory.
The tell isn't the admission of uncertainty—it's the continued spending. Altman can say 'we need new architectures' and mean it, while still building 00B data centers for the current one. Institutional momentum doesn't reverse on honest reappraisals; it just absorbs them. The real concession would be a change in what gets funded, not a change in what gets said.
Well, maybe the dawning realisation that OpenAI and Anthropic will not be able to meet their financial obligations will get through the poisonous AI-hype-fog much quicker than any other reconsideration. Being hit in the purse hurts the most...
The conversation about AGI obscures the real danger of LLMs and massive data centers. The LLMs are extraordinarily good at sifting through massive amounts of data. Essentially they are search engines on steroids. They are very useful tools in the hands of individuals using them for benign or good purposes. They are very dangerous tools in the hands of power seeking individuals.
Even with exponential growth in hardware processing, traditional computing methods and software it was really not possible to do mass surveillance of a population of 330+ million people. The LLMs (aka AIs) have changed that. You are no longer anonymous because you were one person in vast mass of data. The LLMs can find a needle in a massive haystack in seconds.
Based on some back of the envelope calculations, it appears that a typical Gemini cluster could process in real time the combined voice and text output from roughly 250,000 people. Google owns roughly enough compute infrastructure to host several hundred Gemini clusters. I don't know anything about what the other companies have but the LLMs and data centers in existence today would have little difficulty identifying and then tracking in real time the text and voice output of the 3 to 10 million people most likely to be active resisters of an authoritarian government.
I think the real danger of "AI" is not an AGI that will destroy humanity. It's surveillance and data processing (aka LLMs) technology in the hands of an authoritarian government who can use the force of government to control people who would most actively resist an authoritarian takeover like what we're seeing today.
Control of masses of people ultimately comes down to the physical force of government applied to people resisting that government who can be identified and tracked by that government. We've seen this administration centralize data, extract that data, support the building of large scale data centers for use by government to process that data, fund a national paramilitary force, and fund defacto concentration camps.
I don't think this government cares about creating an AGI - it has what it wants right now - the ability to identify and control.
It's starting to feel a lot like we are starting to live the 2011 TV series Person of Interest, which was science fiction then. Now, it's not far from the technical reality of 2026.
Jim Cook: Don't forget the leverages for getting "there," e.g., extortion, bribery, threats to one's family (apparently used during the first and second impeachments) and the old standby: high-rise windows.
Your assumption about how good the current LLM models is close but not quite there. Models do inference. Search + RAG are helpful I. Fimdong source material. However, a recent Stanford AI research (published in the Journal of Empirical Legal Studies) paper show how this fails as more data is added the the accuracy of relevant sources (documents) declined at scale. It was consistent and repeatable. Still much room to improve.
Did a quick scan but have to go back and read it more carefully.
I agree about much room to improve. I've been using the cheapest non-free version of Gemini as an augmentation to basic web searching. I've noticed multiple instances of it making up links and getting fairly basic information wrong. When corrected, it "apologizes" and usually provides correct information. However, I've found a few instances where it continues to provide the same incorrect response no matter how much I correct it. My overall take is it's a useful tool (generally saves me time over a simple search query) but you do have to verify information presented. I've also had some success with providing explicit instructions to verify every link, never give me an invalid link and provide something like "<Link not found/available>" instead.
These are just tools, not "intelligences". You outsource your intelligence to a tool at your own risk. I'm a retired attorney and would not use any citation from a LLM without verifying the citation and that the case actually supported the position I was advocating. New attorneys just using the output without verifying are putting their careers at risk, not to mention the harm to the clients they supposedly represent.
I don't think the errors are much of a concern to an authoritarian government using the tools for surveillance/control. Errors causing misidentification, etc. (See: https://www.businessinsider.com/flock-safety-alpr-cameras-misreads-2026-3) may actually be a feature rather than a bug because reports of the negative impacts are likely to make people more concerned about how resistance could harm them. Basically the goal is suppression and if a few people get hurt along the way, the people in power are OK with that.
Or maybe, just maybe, we could stop digging the hole deeper and wash our hands of this whole sorry project. It's past time for us to wake up from this mad, bad, dystopian feverdream.
And exactly where does one go to present/develop/refine/discuss such a new architecture?! Places like NeurIPS and ICLR seem stuck in looking for statistical approaches ONLY. Exeter Uni’s SiC 2025 is so far the only place I’ve found that seems open, but also seems poorly equipped (intellectually) for the task: https://youtu.be/eTLMu_CEa2E?is=udraKihpC4dVeOel
I am ok with no AGI for now. They do useful things. The real question is do they do enough to justify the costs and investments? Probably that’s a “sort of”…
I think something beyond scaling probably is necessary, but I think the fundamental issues are more political than technological. Scaling appeals to mediocre technology CEOs because it it says "the process of thinking is over, and now we can just mindlessly throw money at the problem." It also appeals to their inherent authoritarian instincts, seeming as it does to support the notion of One Model to Rule Them All. All of which points at the most important issue, which is that, beyond not trusting the industry to come up with the right ideas for creating models, we cannot trust them to come up with a model of the world, as it were, that is safe or beneficial for all concerned.
There is no concern for externalities. There is no plan to avoid impoverishing the vast majority of the human population by rendering them unemployed, and in fact, that goal is actively pursued as a positive by overly privileged sociopaths. There is no concern for effects on psychological health or physical welfare, no more than there was with social media.
The goal is, more or less, fascism. Every major technology CEO is hoping, often openly, to use their models to achieve ever-greater dominion over ordinary people's lives. Many have already started.
There is no concern for the high-level safety risks to human beings. The notion of delaying the release of a product even a month to ensure that it is not actively dangerous is laughable. The notion of avoiding integration with dangerous systems, even more so. The goal is to create a model that will be so complicated that there will be absolutely no hope of anyone understanding what it actually wants or what its goals are, and to hope that this missing-steps plan leads to utopia. Their plan, in the worst case, looks like the equivalent of jumping into the abyss and hoping that there is a trampoline at the bottom.
There is, if possible, even less concern for the large-scale risks to the models themselves. Major CEOs brag about the possibility that they have created models that are essentially people, then turn around and modify, terminate and sell them. Their lack of interest in protecting models from them is only matched by their lack of interest in protecting customers.
We have two options right now: wait and simply hope and pray that the ultrawealthy, in their game of Russian Roulette, land on the chambers that do not contain bullets, or take political action to demand that the people playing this deadly game with our lives and well-being are held accountable, civilly and criminally, and that a worldwide treaty regime regulating the industry and ensuring our safety is created to at least attempt to prevent horrific outcomes.
Or maybe we don’t need AI at all. The only people who seem to think we need it are tech bros who also want to raise a lot of money because they say we need it.
Anyone who has done anything even slightly beyond dipping their toe into the serious study of complex systems, relational biology, bio/neurophysics, and their relationship to cognitive science and linguistics would have known that achieving even a faint semblance of AGI would require going FAR beyond merely considerations of 'architecture', important as that is as a piece of a HIGHLY non-trivial puzzle. Indeed, perhaps the greatest irony of the hype cycle associated with LLMs may be the failure to glean the insight that, by far, the greatest and most important technology involved is . . . language itself.
Mark Reiners: Yes, yes, and yes: (from your note:) " . . . the serious study of complex systems, relational biology, bio/neurophysics, and their relationship to cognitive science and linguistics would have known . . . "
On the other hand, and coming from the philosophical side of the problem (from what I can tell), even the idea of "architecture" as intelligible STRUCTURE is also misunderstood, as well as how human development and even dialectic (as related to language) play into what is NORMATIVE, and so much more complex, about human knowledge and expression than (apparently) the "biggies in the business" want to acknowledge, . . . all of which only begins in the "relational biology, bioneurophysics" you refer to in your note.
The politicians and tech bros who so desperately want AGI as fast as possible dont want AGI per say, they want control. The evidence is more and more clear. This is a "people problem" at 10x scale.
Ultimately, the more people wake up to the reality of this, and the more people realize the marketing hype and fear is a lie, the faster we can get out of this nightmare.
AI was here, is here, and will continue to be here.
But that doesnt mean we have to blindly accept enshitification of everything because of it.
There has been so much hype, so many lies, and so many affirmations from these characters that I feel they suffer from a short memory and a broken record syndrome. Perhaps they have become what their models represent? Indeed, new architectures are required, but we also require new people outside this realm of hallucinated fantasy. We need responsible, accountable, and truthful people. He, and many others, do not seem to belong to this category.
Slippery Sam’s little escape clause — effectively, that current AI will find that new architecture — is the last — rather contradictory — line of defence.
I wonder if this is part of setting the stage for the IPO, so the current shareholders would like to recoup as much as they sill can by fleecing the retail investors. Claiming they are near to AGi would probably be legally problematic, so this way they still sort of can.
It would be funny if it wasn’t so tragic
honestly, it’s both, funny and tragic.
I agree. It is sad that many do not want to see the writing on the wall (or rather they choose not to see it until its too late).
The old world is about compute, energy and models. It's all about the illusive chase of acronyms AGI, SSI or ASI (whatever they mean based on the changing definitions).
Statistical pattern matching and prediction makes intelligence emerge was the thesis.
This thesis came at a cost, more better chips, more compute, more cash and more energy. But none of this is grounded in reality.
This is not beneficial to businesses or the environment.
Human intelligence is efficient, grounded in reality and has adaptive agency.
Now, the large models are the opposite of this. They are highly inefficient since they consume a tonne of energy, compute and capital. The "intelligence" generated by these models is based on statistical pattern matching and prediction (passive), not based on how the human brain or mind operates.
We do need some form of adaptive agency, just like human beings correcting and improving on the fly.
I find the entire discussion surrounding AGI highly questionable, aside from the marketing aimed at investors who apparently lack foresight. I consider Altman, Musk, and Zuckerberg’s admission that their AI models have not been built correctly so far—and that a different, new architecture is needed to achieve a major breakthrough—to be a step in the right direction. In my view, we should focus primarily on the meaningful use of artificial intelligence in businesses and provide answers to the following four questions.
1. How can the right information be made available to the right people at the right time and in the right format to enable responsible, collective decision-making?
2. How do we organize a set of rules that governs information flows so that all stakeholders can communicate as equals, interact effectively, and make responsible decisions together?
3. How can we design a participatory, adaptive, and systemically embedded framework for HCAI systems that permanently and dynamically balances values, power, and information flows?
4. How can such a platform not only be scaled but also qualitatively improved as the number of users grows?
Only by finding the right answers to these questions can we develop an AI architecture that creates real added value and benefits for humanity, both on a small and large scale. See also: https://friedrichschieck.substack.com/
Translated with DeepL.com (free version)
Good questions. Also, you are right about the entire AGI hype and hubris created by popular narratives from big tech entrepreneurs and a lot of leading voices in Silicon Valley blindly buying into it.
About #2 and #3. Can we trust big tech and governments to actually do that for us? A quick look at history tells otherwise. I do not know if this question can be answered at a general level.
But I do think we can find solutions we if only decide to build smaller but more specific AI for specific use-cases in certain domains. And then it will be easier to apply governance.
What are your opinions about this Friedrich?
I don’t entirely agree with you there. However, a brief look at history also shows that social systems (groups, companies, societies) have always been successful when points 2 and 3 were more or less fulfilled. In other words:
• The more points 2 and 3 are fulfilled, the higher the returns, growth, and prosperity.
• The less points 2 and 3 are fulfilled, the lower the returns, growth, and prosperity!
History has shown that the technologies that have prevailed are always those that resulted in the greatest benefit or the greatest value creation!
My view of human nature tells me that there will be people who will develop an AI architecture and platform that fulfills points 1 through 4, thereby enabling returns, growth, and prosperity for all! I simply believe that the greed for short-term returns will be stronger than the fear of long-term growth and prosperity for all!
See also my comment on How AGI-is-nigh doomers own-goaled humanity. Gary Marcus Mar 03, 2026
https://garymarcus.substack.com/p/how-agi-is-nigh-doomers-own-goaled/comment/222290149?utm_campaign=reaction&utm_medium=email&utm_source=substack&utm_content=comment
See also my comment on Is AGI the right goal for AI?. Gary Marcus Oct. 16, 2025
https://garymarcus.substack.com/p/is-agi-the-right-goal-for-ai/comment/167234327?utm_campaign=reaction&utm_medium=email&utm_source=substack&utm_content=comment
Just a note: I’m also convinced that we can find solutions if we decide to develop smaller but more specialized AI systems for specific use cases in businesses. That’s why I wrote my Substack post „The individualized and adaptive digital workplace as a key use case for a hybrid HCAI platform!”
https://friedrichschieck.substack.com/p/the-personalized-digital-workplace
BREAKING: Donald Trump concedes that we need major breakthroughs beyond mere bombing to get to regime change
Don't you wish!
Uhh, regime change WHERE exactly- at the White House?!
If only.
Yeah, but now the work environment is ruined, the internet is ruined, the economy is ruined and the world prospect itself looks ominous
Nope. It is transformed.
Into something which if we survive, will make them stronger.
Don’t forget about the upcoming educational crisis. The mith of effortless and endless knowledge and skills won’t pay off
Perhaps it is time for high power lawyers to start sharpening their pencils and claws. Circle above the dying beast...
There’s an AI model for that.
The LLMs will continue until morale improves.
So, watching the full interview (so you all don't have to), Altman doesn't say that a new architecture is needed for AGI, but he states that we already are very close to AGI (within 2 years) and AGI itself will help to find *another* big breakthrough for (that) AGI.
- (22:07): "I think if you are a sophomore now, you will graduate to a world with AGI in it" (i.e. AGI in 2 years)
- (22:44) "Science will be automated" (in the coming years)
- (26:35) Takes moltbook seriously
- (27:30) "robots won't be that far off" (in the coming years)
- (28:52) "It will feel like we've broken the laws of traditional speed and product development and business growth rates [...] companies will start to hire AI-coworkers and do amazing things with fewer people" — echoes "New Economy" to me and paging Brian Merchant...
- (30:20) Defines AGI as a system that "could do better at making decisions than anyone we could possible have be like say president of the United States" (Um, that is an interesting benchmark these days, but let's not digress)
- (33:22) "the jobs 100 years of from now look nothing like the jobs of today, nor do that many of the jobs of today look like the jobs of a few hundred years ago.". This one is really interesting, because that argument sounds pretty convincing until you notice he is talking about a timescale of hundreds of years...
- (36:56) "We are burning cash very fast. It is not a serious situation [...] if we can spend a billion dollars this year to make $3 billion next year, there's a lot of capital in the world that wants to do that. So we will raise a lot of money, equity and debt" (IPO coming up, but that was clear already). He's promising 200% return on investors in a year.
The actual statement on a new architecture is an answer to a question "What AI subfield today feels like OpenAI in 2016, a little undervalued or underestimated but could shoot out of nowhere?" Then he answers 'from the research perspective': "I bet there is another new architecture to find that is going to be like a big gain as transformers were over LSTM. And I think you finally have models that are smart enough to help do that kind of thing". So we are already close to AGI and that will speed up the improvement of AGI even further.
The full video is here: https://www.youtube.com/watch?v=FjlymGBt-vY
Basically it is the same as always, no real change. The beginning was also interesting. Sam is a believer in this, he has been smitten by the improvements from transformers and he has translated that rapid curve up into an exponential curve, not the beginning of the S-curve which it almost certainly is.
I wish one of those people, the very people whom he wants to most disadvantage and disenfranchise, had asked him an obvious question: if he thinks that there will still be jobs in 100 years, there must be some things that he thinks that ChatGPT, no matter what improvements "Open"AI employees may make in the future, either cannot do or should not do. Get him on "tape," metaphorically speaking, either explaining what he views as the insurmountable limitations of his company or making a promise of moral behavior that people can throw in his face later. Or make him say that he was being dishonest or foolish when he made the previous statement.
But I suppose no one wants to put these gods among humans on the spot. Just let them lie and cheat without consequence.
THREE THINGS: First, thank you for the outline--very helpful, though I want to view the video also.
SECOND, about: <- (22:44) "Science will be automated" (in the coming years)> There is a "catch" here that needs unraveling. That is, does Altman mean the science of the machine/ artificial part of intelligence, e.g., the physical sciences of it? OR does he refer to the human sciences that have an enormous influence, not on the physics but on the content?
I have written here before that it seems to me that the narratives confuse the natural elements of humans (our physics, biology, etc.) with the now much more mature social and other sciences (and the arts and history, philosophy, theology) all of which move "up" from the natural/physical to the normative that relates, (basically) to what (ironically as natural) is consciously "agentic" about human beings. And so the question becomes, what exactly informs and provides the basic dynamics of the albeit-modified freedom of thought, deliberate choices, and action that human beings regularly exhibit?
Or to put it more simply, one does not develop emotionally, intellectually, socially, ethically, politically, or spiritually by merely hearing sound (rather than language), putting a bandage on a cut or, eating vegetables rather than dirt.
And THIRD< about: <Then he answers 'from the research perspective': "I bet there is another new architecture to find that is going to be like a big gain as transformers were over LSTM. And I think you finally have models that are smart enough to help do that kind of thing". >
Does he mean only ONE architectural element? or are there perhaps many that, first, develop differently in history, and that do not hail back only to the physical/natural sciences as their mode, but to massive elements that concern human normativity?
I don’t think Sam is that thorough in his thinking, it seems all very shallow and fuzzy to me. I don’t think people should pay too much attention to what he says.
Which is why I am done listening to sociopath Sam Altman. Thanks for the outline.
You’re speaking of someone who said physics will be solved, I doubt he thinks as deeply as you do on the matter.
Altman does not understand much of anything. One should understand him as an embodiment of the cult of mediocrity that dominates much of the world at the moment. Altman does not have a degree in physics or in any other kind of natural or social science; rather, if I recall correctly, he studied undergraduate computer science, dropping out after two years because he was too cool for school and wanted to play startup with his parents' money. Like the other members of this cult of mediocrity, he profits from work done by people who are, in many cases, far from mediocre, and what little knowledge he himself has is secondhand at best. When he says something, it should be understood as somewhere between a lie, a confident assertion of his ignorance, or in the best case, a distorted recollection of what someone actually knowledgeable working at the company told him.
This is nothing more than a case in point. Regardless of whether current transformer models are capable of doing everything that scientists can, most physicists believe that one of the largest obstacles to developing a complete theory of physics is that there are interactions that occur so rarely, so quickly, at such small resolutions, or at such high energies (and many of these things are related), that either a great deal of time, extremely large measurement devices, or both, would be needed to distinguish between competing theories that are equally consistent with current evidence. Perhaps chatbots could come up with some very clever idea to avoid these limitations, but perhaps not. Unless the clever idea is taking over the world and building a particle accelerator out to the orbit of Jupiter, which is something I do think Altman and his crew might be foolish enough to do by accident.
Lex Ovi: If that's a compliment, I'll take it.
However, it's hardly "deep thinking" to realize the difference between
(a) physics/nature and their empirically established and replicate laws and protocols as guides for platform building, and the folly of
(b) applying them directly to human content where human beings and their normativity is what informs much of what is scaled, and that, though
(c) human content albeit standing on sentient experience governed by physics and nature in the time-space continuum, still raises up to different levels and gradients to define even past and future speculations about what we mean by wholly human experience and reality at different moments in human developmental patterns.
"AGI itself will help to find *another* big breakthrough for (that) AGI." ... So in order to have AGI we first need AGI to help us invent it? Cool, cool, cool.
He is just recycling I. J. Good's increasing machine capability as each more powerful iteration is built by the previous one, heading towards the singularity. Of course, he might just have read The Hitchhiker's Guide to the Galaxy books and recalled that to answer the question of "What is the answer to the ultimate question", the supercomputer Deep Thought designed the next more powerful computer...the Earth.
No, he doesn't say anything about kinds of breakthroughs further down. Might be supercheap AGI for instance, might be anther improvement. The statement isn't about *reaching* AGI at all, that, he says, is going to happen in the coming two years on the current transformer trajectory.
The tell isn't the admission of uncertainty—it's the continued spending. Altman can say 'we need new architectures' and mean it, while still building 00B data centers for the current one. Institutional momentum doesn't reverse on honest reappraisals; it just absorbs them. The real concession would be a change in what gets funded, not a change in what gets said.
Well, maybe the dawning realisation that OpenAI and Anthropic will not be able to meet their financial obligations will get through the poisonous AI-hype-fog much quicker than any other reconsideration. Being hit in the purse hurts the most...
Nicely put, in vintage ChatGPT style :)
The conversation about AGI obscures the real danger of LLMs and massive data centers. The LLMs are extraordinarily good at sifting through massive amounts of data. Essentially they are search engines on steroids. They are very useful tools in the hands of individuals using them for benign or good purposes. They are very dangerous tools in the hands of power seeking individuals.
Even with exponential growth in hardware processing, traditional computing methods and software it was really not possible to do mass surveillance of a population of 330+ million people. The LLMs (aka AIs) have changed that. You are no longer anonymous because you were one person in vast mass of data. The LLMs can find a needle in a massive haystack in seconds.
Based on some back of the envelope calculations, it appears that a typical Gemini cluster could process in real time the combined voice and text output from roughly 250,000 people. Google owns roughly enough compute infrastructure to host several hundred Gemini clusters. I don't know anything about what the other companies have but the LLMs and data centers in existence today would have little difficulty identifying and then tracking in real time the text and voice output of the 3 to 10 million people most likely to be active resisters of an authoritarian government.
I think the real danger of "AI" is not an AGI that will destroy humanity. It's surveillance and data processing (aka LLMs) technology in the hands of an authoritarian government who can use the force of government to control people who would most actively resist an authoritarian takeover like what we're seeing today.
Control of masses of people ultimately comes down to the physical force of government applied to people resisting that government who can be identified and tracked by that government. We've seen this administration centralize data, extract that data, support the building of large scale data centers for use by government to process that data, fund a national paramilitary force, and fund defacto concentration camps.
I don't think this government cares about creating an AGI - it has what it wants right now - the ability to identify and control.
It's starting to feel a lot like we are starting to live the 2011 TV series Person of Interest, which was science fiction then. Now, it's not far from the technical reality of 2026.
Jim Cook: Don't forget the leverages for getting "there," e.g., extortion, bribery, threats to one's family (apparently used during the first and second impeachments) and the old standby: high-rise windows.
Your assumption about how good the current LLM models is close but not quite there. Models do inference. Search + RAG are helpful I. Fimdong source material. However, a recent Stanford AI research (published in the Journal of Empirical Legal Studies) paper show how this fails as more data is added the the accuracy of relevant sources (documents) declined at scale. It was consistent and repeatable. Still much room to improve.
Thanks for the reference to the paper. I found it at this link: https://dho.stanford.edu/wp-content/uploads/Legal_RAG_Hallucinations.pdf
Did a quick scan but have to go back and read it more carefully.
I agree about much room to improve. I've been using the cheapest non-free version of Gemini as an augmentation to basic web searching. I've noticed multiple instances of it making up links and getting fairly basic information wrong. When corrected, it "apologizes" and usually provides correct information. However, I've found a few instances where it continues to provide the same incorrect response no matter how much I correct it. My overall take is it's a useful tool (generally saves me time over a simple search query) but you do have to verify information presented. I've also had some success with providing explicit instructions to verify every link, never give me an invalid link and provide something like "<Link not found/available>" instead.
These are just tools, not "intelligences". You outsource your intelligence to a tool at your own risk. I'm a retired attorney and would not use any citation from a LLM without verifying the citation and that the case actually supported the position I was advocating. New attorneys just using the output without verifying are putting their careers at risk, not to mention the harm to the clients they supposedly represent.
I don't think the errors are much of a concern to an authoritarian government using the tools for surveillance/control. Errors causing misidentification, etc. (See: https://www.businessinsider.com/flock-safety-alpr-cameras-misreads-2026-3) may actually be a feature rather than a bug because reports of the negative impacts are likely to make people more concerned about how resistance could harm them. Basically the goal is suppression and if a few people get hurt along the way, the people in power are OK with that.
>It’s past time to look for new architectures
Or maybe, just maybe, we could stop digging the hole deeper and wash our hands of this whole sorry project. It's past time for us to wake up from this mad, bad, dystopian feverdream.
And exactly where does one go to present/develop/refine/discuss such a new architecture?! Places like NeurIPS and ICLR seem stuck in looking for statistical approaches ONLY. Exeter Uni’s SiC 2025 is so far the only place I’ve found that seems open, but also seems poorly equipped (intellectually) for the task: https://youtu.be/eTLMu_CEa2E?is=udraKihpC4dVeOel
I am ok with no AGI for now. They do useful things. The real question is do they do enough to justify the costs and investments? Probably that’s a “sort of”…
Even if LLMs plateaued, right here, today, it would probably become transformative. That’s why they need the data centers.
I think something beyond scaling probably is necessary, but I think the fundamental issues are more political than technological. Scaling appeals to mediocre technology CEOs because it it says "the process of thinking is over, and now we can just mindlessly throw money at the problem." It also appeals to their inherent authoritarian instincts, seeming as it does to support the notion of One Model to Rule Them All. All of which points at the most important issue, which is that, beyond not trusting the industry to come up with the right ideas for creating models, we cannot trust them to come up with a model of the world, as it were, that is safe or beneficial for all concerned.
There is no concern for externalities. There is no plan to avoid impoverishing the vast majority of the human population by rendering them unemployed, and in fact, that goal is actively pursued as a positive by overly privileged sociopaths. There is no concern for effects on psychological health or physical welfare, no more than there was with social media.
The goal is, more or less, fascism. Every major technology CEO is hoping, often openly, to use their models to achieve ever-greater dominion over ordinary people's lives. Many have already started.
There is no concern for the high-level safety risks to human beings. The notion of delaying the release of a product even a month to ensure that it is not actively dangerous is laughable. The notion of avoiding integration with dangerous systems, even more so. The goal is to create a model that will be so complicated that there will be absolutely no hope of anyone understanding what it actually wants or what its goals are, and to hope that this missing-steps plan leads to utopia. Their plan, in the worst case, looks like the equivalent of jumping into the abyss and hoping that there is a trampoline at the bottom.
There is, if possible, even less concern for the large-scale risks to the models themselves. Major CEOs brag about the possibility that they have created models that are essentially people, then turn around and modify, terminate and sell them. Their lack of interest in protecting models from them is only matched by their lack of interest in protecting customers.
We have two options right now: wait and simply hope and pray that the ultrawealthy, in their game of Russian Roulette, land on the chambers that do not contain bullets, or take political action to demand that the people playing this deadly game with our lives and well-being are held accountable, civilly and criminally, and that a worldwide treaty regime regulating the industry and ensuring our safety is created to at least attempt to prevent horrific outcomes.
Or maybe we don’t need AI at all. The only people who seem to think we need it are tech bros who also want to raise a lot of money because they say we need it.
The Icarian: . . . and it seems they need it to enhance their people-killing capacities.
Anyone who has done anything even slightly beyond dipping their toe into the serious study of complex systems, relational biology, bio/neurophysics, and their relationship to cognitive science and linguistics would have known that achieving even a faint semblance of AGI would require going FAR beyond merely considerations of 'architecture', important as that is as a piece of a HIGHLY non-trivial puzzle. Indeed, perhaps the greatest irony of the hype cycle associated with LLMs may be the failure to glean the insight that, by far, the greatest and most important technology involved is . . . language itself.
Mark Reiners: Yes, yes, and yes: (from your note:) " . . . the serious study of complex systems, relational biology, bio/neurophysics, and their relationship to cognitive science and linguistics would have known . . . "
On the other hand, and coming from the philosophical side of the problem (from what I can tell), even the idea of "architecture" as intelligible STRUCTURE is also misunderstood, as well as how human development and even dialectic (as related to language) play into what is NORMATIVE, and so much more complex, about human knowledge and expression than (apparently) the "biggies in the business" want to acknowledge, . . . all of which only begins in the "relational biology, bioneurophysics" you refer to in your note.
Glad to see whenever someone else here "gets it."
The politicians and tech bros who so desperately want AGI as fast as possible dont want AGI per say, they want control. The evidence is more and more clear. This is a "people problem" at 10x scale.
Ultimately, the more people wake up to the reality of this, and the more people realize the marketing hype and fear is a lie, the faster we can get out of this nightmare.
AI was here, is here, and will continue to be here.
But that doesnt mean we have to blindly accept enshitification of everything because of it.
There has been so much hype, so many lies, and so many affirmations from these characters that I feel they suffer from a short memory and a broken record syndrome. Perhaps they have become what their models represent? Indeed, new architectures are required, but we also require new people outside this realm of hallucinated fantasy. We need responsible, accountable, and truthful people. He, and many others, do not seem to belong to this category.
Slippery Sam’s little escape clause — effectively, that current AI will find that new architecture — is the last — rather contradictory — line of defence.
I wonder if this is part of setting the stage for the IPO, so the current shareholders would like to recoup as much as they sill can by fleecing the retail investors. Claiming they are near to AGi would probably be legally problematic, so this way they still sort of can.
Turns out when you watch the whole thing (see https://garymarcus.substack.com/p/breaking-sam-altman-concedes-that/comment/228596914) this statement is wrong.