I'm troubled by the amount of people in this thread partially dismissing this as science fiction. From the current rate of progress and rate of change of progress, this future seems entirely plausible
It’s good science fiction, I’ll give it that. I think getting lost in the weeds over technicalities ignores the crux of the narrative: even if this doesn’t lead to AGI, at the very least it’s likely the final “warning shot” we’ll get before it’s suddenly and irreversibly here.
The problems it raises - alignment, geopolitics, lack of societal safeguards - are all real, and happening now (just replace “AGI” with “corporations”, and voila, you have a story about the climate crisis and regulatory capture). We should be solving these problems before AGI or job-replacing AI becomes commonplace, lest we run the very real risk of societal collapse or species extinction.
The point of these stories is to incite alarm, because they’re trying to provoke proactive responses while time is on our side, instead of trusting self-interested individuals in times of great crisis.
No one's gonna solve anything. "Our" world is based on greedy morons concentrating power through hands of just morons who are happy to hit you with a stick. This system doesn't think about what "we" should or allowed to do, and no one's here is at the reasonable side of it either.
lest we run the very real risk of societal collapse or species extinction
Our part is here. To be replaced with machines if this AI thing isn't just a fart advertised as mining equipment, which it likely is. We run this risk, not they. People worked on their wealth, people can go f themselves now. They are fine with all that. Money (=more power) piles in either way.
No encouraging conclusion.
I read for such a long time, and I still couldn’t get through that, even though it never got boring.
I like that it ends with a reference to Kushiel and Elua though.
Thanks for the read. One could think that the answer is to simply stop being a part of it, but then again you're from the genus that outcompeted everyone else in staying alive. Nature is such a shitty joke by design, not sure how one is supposed to look at the hypothetical designer with warmth in their heart.
Whatever the future is, it is not American, not the United States. The US's cultural individualism has been Capitalistically weaponized, and the educational foundation to take the country forward is not there. The US is kaput, and we are merely observing the ugly demise. The future is Asia, with all of western culture going down. Yes, it is not pretty, The failed experiment of American self rule.
> very real risk of societal collapse or species extinction
No, there is no risk of species extinction in the near future due to climate change and repeating the line will just further the divide and make the people not care about other people's and even real climate scientist's words.
Don’t say the things people don’t want to hear and everything will be fine?
That sounds like the height of folly.
I fail to see how corporations are responsible for the climate crisis: Politicians won't tax gas because they'll get voted out.
We know that Trump is not captured by corporations because his trade policies are terrible.
If anything, social media is the evil that's destroying the political center: Americans are no longer reading mainstream newspapers or watching mainstream TV news.
The EU is saying the elections in Romania was manipulated through manipulation of TikTok accounts and media.
If you put a knife in someone’s heart, you’re the one who did it and ultimately you’re responsible. If someone told you to do it and you were just following orders… you still did it. If you say there were no rules against putting knives in other people’s hearts, you still did it and you’re still responsible.
If it’s somehow different for corporations, please enlighten me how.
The oil companies are saying their product is vital to the economy and they are not wrong. How else will we get food from the farms to the store ? Ambulances to the hospitals ? And many, many other things.
Taxes are the best way to change behaviour (smaller cars driving less. Less flying etc). So government and the people who vote for them is to blame.
What if people are manipulated by bot farms and think tanks and talking points supported by those corporations?
I think this view of humans - that they look at all the available information and then make calm decisions in their own interests - is simply wrong. We are manipulated all the damn time. I struggle to go to the supermarket without buying excess sugar. The biggest corporations in the world grew fat off showing us products to impulse buy before our more rational brain functions could stop us. We are not a little pilot in a meat vessel.
Corporations would prefer lower corporate tax.
US corporate tax rates are actually every high. Partly due to the US having almost no consumption tax. EU members have VAT etc.
I agree with everything here, we've had a great run of economic expansion for basically two centuries and I like my hot showers as much as anyone - but that doesn't change the CO2 levels.
> Politicians won't tax gas because they'll get voted out.
I wonder if that's corporations' fault after all: shitty working conditions and shitty wages, so that Bezos can afford to send penises into space. What poor person would agree to higher tax on gas? And the corps are the ones backing politicians who'll propagandize that "Unions? That's communism! Do you want to be Chaina?!" (and spread by those dickheads on the corporate-owned TV and newspaper, drunk dickheads who end up becoming defense secretary)
When people have more money, they tend to buy larger cars that they drive further. Flying is also a luxury.
So corporations are involved in the sense that they pay people more than a living wage.
> Politicians won't tax gas because they'll get voted out.
Have you seen gas tax rates in the EU?
> We know that Trump is not captured by corporations because his trade policies are terrible.
Unless you think it's a long con for some rich people to be able to time the market by getting him to crash it.
> The EU is saying the elections in Romania was manipulated through manipulation of TikTok accounts and media.
More importantly, Romanian courts say that too. And it was all out in the open, so not exactly a secret
Romainan courts say all kinds of things, many of them patently false. It's absurd to claim that since romanian courts say something, it must be true. It's absurd in principle, because there's nothing in the concept of a court that makes it infallible, and it's absurd in this precise case, because we are corrupt as hell.
I'm pretty sure the election was manipulated, but the court only said so because it benefits the incumbents, which control the courts and would lose their power.
It's a struggle between local thieves and putin, that's all. The local thieves will keep us in the EU, which is much better than the alternative, but come on. "More importantly, Romanian courts say so"? Really?
Though I think it is probably mostly science-fiction, this is one of the more chillingly thorough descriptions of potential AGI takeoff scenarios that I've seen. I think part of the problem is that the world you get if you go with the "Slowdown"/somewhat more aligned world is still pretty rough for humans: What's the point of our existence if we have no way to meaningfully contribute to our own world?
I hope we're wrong about a lot of this, and AGI turns out to either be impossible, or much less useful than we think it will be. I hope we end up in a world where humans' value increases, instead of decreasing. At a minimum, if AGI is possible, I hope we can imbue it with ethics that allow it to make decisions that value other sentient life.
Do I think this will actually happen in two years, let alone five or ten or fifty? Not really. I think it is wildly optimistic to assume we can get there from here - where "here" is LLM technology, mostly. But five years ago, I thought the idea of LLMs themselves working as well as they do at speaking conversational English was essentially fiction - so really, anything is possible, or at least worth considering.
"May you live in interesting times" is a curse for a reason.
> What's the point of our existence if we have no way to meaningfully contribute to our own world?
You may find this to be insightful: https://meltingasphalt.com/a-nihilists-guide-to-meaning/
In short, "meaning" is a contextual perception, not a discrete quality, though the author suggests it can be quantified based on the number of contextual connections to other things with meaning. The more densely connected something is, the more meaningful it is; my wedding is meaningful to me because my family and my partners family are all celebrating it with me, but it was an entirely meaningless event to you.
Thus, the meaningfulness of our contributions remains unchanged, as the meaning behind them is not dependent upon the perspective of an external observer.
Please don't be offended by my opinion, I mean it in good humour to share some strong disagreements - Im going to give my take after reading your comment and the article which both seem completely OTT ( contextwise regarding my opinions ).
>meaning behind them is not dependent upon the perspective of an external observer.
(Yes brother like cmon)
Regarding the author, I get the impression he grew up without a strong father figure? This isnt ad hominem I just get the feeling of someone who is so confused and lost in life that he is just severely depressed possibly related to his directionless life. He seems so confused he doesn't even take seriously the fact most humans find their own meaning in life and says hes not even going to consider this, finding it futile.( he states this near the top of the article ).
I believe his rejection of a simple basic core idea ends up in a verbal blurb which itself is directionless.
My opinion ( Which yes maybe more floored than anyones ), is to deal with Mazlows hierarchy, and then the prime directive for a living organism which after survival , which is reproduction. Only after this has been achieved can you then work towards your family community and nation.
This may seem trite, but I do believe that this is natural for someone with a relatively normal childhood.
My aim is not to disparage, its to give me honest opinion of why I disagree and possible reasons for it. If you disagree with anything I have said please correct me.
Thanks for sharing the article though it was a good read - and I did struggle myself with meaning sometimes.
> Slowdown"/somewhat more aligned world is still pretty rough for humans: What's the point of our existence if we have no way to meaningfully contribute to our own world?
We spend the best 40 years of our lives working 40-50 hours a week to enrich the top 0.1% while living in completely artificial cities. People should wonder what is the point of our current system instead of worrying about Terminator tier sci fi system that may or may not come sometimes in the next 5 to 200 years
A lot of people in my surroundings are not buying this life anymore; especially young people are asking why would they. Unlike in the US, they won't end up under a bridge (unless some real collapse, which can of course happen but why worry about it; it might not) so they work simple jobs (data entry or whatnot) to make enough money to eat and party and nothing more. Meaning many of them work no more than a few hours a month. They live rent free at their parents and when they have kids they stop partying but generally don't go work more (well; raising kids is hard work of course but I mean for money). Many of them will inherit the village house from their parents and have a garden so they grow stuff to eat , have some animals and make their own booze so they don't have to pay for that. In cities, people feel the same 'who would I work for the ferrari of the boss we never see', but it is much harder to not to; more expensive and no land and usually no property to inherit (as that is in the countryside or was already sold to not have to work for a year or two).
Like you say, people but more our govs need to worry about what is the point at this moment, not scifi in the future; this stuff has already bad enough to worry about. Working your ass off for diminishing returns , paying into a pension pot that won't make it until you retire etc is driving people to really focus on the now and why they would do these things. If you can just have fun with 500/mo and booze from your garden, why work hard and save up etc. I noticed even people from my birth country with these sentiments while they have it extraordinarily good for the eu standards but they are wondering why would they do all of this for nothing (...) more and more and cutting hours more and more. It seems more an education and communication thing really than anything else; it is like asking why pay taxes: if you are not well informed, it might feel like theft, but when you spell it out, most people will see how they benefit.
> I hope we're wrong about a lot of this, and AGI turns out to either be impossible, or much less useful than we think it will be.
For me personally, I hope that we do get AGI. I just don't want it by 2027. That feels way too fast to me. But AGI 2070 or 2100? That sounds much more preferable.
I think LLM or no LLM the emergence of intelligence appears to be closely related to the number of synapses in a network whether a biological or a digital one. If my hypothesis is roughly true it means we are several orders of magnitude away from AGI. At least the kind of AGI that can be embodied in a fully functional robot with the sensory apparatus that rivals the human body. In order to build circuits of this density it's likely to take decades. Most probably transistor based, silicon based substrate can't be pushed that far.
I think generally the expectation is that there are around 100T synapses in the brain, and of course it's probably not a 1:1 correspondence with neural networks, but it doesn't seem infeasible at all to me that a dense-equivalent 100T parameter model would be able to rival the best humans if trained properly.
If basically a transformer, that means it needs at inference time ~200T flops per token. The paper assumes humans "think" at ~15 tokens/second which is about 10 words, similar to the reading speed of a college graduate. So that would be ~3 petaflops of compute per second.
Assuming that's fp8, an H100 could do ~4 petaflops, and the authors of AI 2027 guesstimate that purpose wafer scale inference chips circa late 2027 should be able to do ~400petaflops for inference, ~100 H100s worth, for ~$600k each for fabrication and installation into a datacenter.
Rounding that basically means ~$6k would buy you the compute to "think" at 10 words/second. Generally speaking that'd probably work out to maybe $3k/yr after depreciation and electricity costs, or ~30-50¢/hr of "human thought equivalent" 10 words/second. Running an AI at 50x human speed 24/7 would cost ~$23k/yr, so 1 OpenBrain researcher's salary could give them a team of ~10-20 such AIs running flat out all the time. Even if you think the AI would need an "extra" 10 or even 100x in terms of tokens/second to match humans, that still puts you at genius level AIs in principle runnable at human speed for 0.1 to 1x the median US income.
There's an open question whether training such a model is feasible in a few years, but the raw compute capability at the chip level to plausibly run a model that large at enormous speed at low cost is already existent (at the street price of B200's it'd cost ~$2-4/hr-human-equivalent).
If by “several” orders of magnitude, you mean 3-5, then we might be there by 2030 or earlier.
Exponential growth means the first order of magnitude comes slowly and the last one runs past you unexpectedly.
Exponential growth generally means that the time between each order of magnitude is roughly the same.
I think there is a good chance you are roughly right. I also think that the "secret sauce" of sapience is probably not something that can be replicated easily with the technology we have now, like LLMs. They're missing contextual awareness and processing which is absolutely necessary for real reasoning.
But even so, solving that problem feels much more attainable than it used to be.
I think the missing secret sauce is an equivalent to neuroplasticity. Human brains are constantly being rewired and optimized at every level: synapses and their channels undergo long term potentiation and depression, new connections are formed and useless ones pruned, and the whole system can sometimes remap functions to different parts of the brain when another suffers catastrophic damage. I don’t know enough about the matrix multiplication operations that power LLMs, but it’s hard to imagine how that kind of organic reorganization would be possible with GPUs matmul. It’d require some sort of advanced “self aware” profile guided optimization and not just trial and error noodling with Torch ops or CUDA kernels.
I assume that thanks to the universal approximation theorem it’s theoretically possible to emulate the physical mechanism, but at what hardware and training cost? I’ve done back of the napkin math on this before [1] and the number of “parameters” in the brain is at least 2-4 orders of magnitude more than state of the art models. But that’s just the current weights, what about the history that actually enables the plasticity? Channel threshold potentials are also continuous rather than discreet and emulating them might require the full fp64 so I’m not sure how we’re even going to get to the memory requirements in the next decade, let alone whether any architecture on the horizon can emulate neuroplasticity.
Then there’s the whole problem of a true physical feedback loop with which the AI can run experiments to learn against external reward functions and the core survival reward function at the core of evolution might itself be critical but that’s getting deep into the research and philosophy on the nature of intelligence.
i agree. it feels like scaling up these large models is such an inefficient route that seems to be warranting new ideas (test-time compute, etc).
we'll likely reach a point where it's infeasible for deep learning to completely encompass human-level reasoning, and we'll need neuroscience discoveries to continue progress. altman seems to be hyping up "bigger is better," not just for model parameters but openai's valuation.
Why can't the compute be remote from the robot? That is a major advantage of human technology over biology.
Mostly latency. But even if a single robot could be driven by a data centre consider the energy and hardware investment requirements to make such a creature practical.
1ms latency is more than fast enough, you probably have bigger latency than that between the cpu and the gpu.
Latency would be kept low be keeping the compute nearby. One 1U or 2U server per robot would be reasonable.
> What's the point of our existence if we have no way to meaningfully contribute to our own world?
For a sizable number of humans, we're already there. The vast majority of hacker news users are spending their time trying to make advertisements tempt people into spending money on stuff they don't need. That's an active societal harm. It doesn't contribute in any positive way to the world.
And yet, people are fine to do that, and get their dopamine hits off instagram or arguing online on this cursed site, or watching TV.
More people will have bullshit jobs in this SF story, but a huge number of people already have bullshit jobs, and manage to find a point in their existence just fine.
I, for one, would be happy to simply read books, eat, and die.
Targeted advertising is about determining and giving people exactly what they need. If successful, this increases consumption and grows the productivity of the economy. It's an extremely meaningful job as it allows for precise, effective distribution of resources.
My vision for an ASI future involves humans living in simulations that are optimized for human experience. That doesn’t mean we are just live in a paradise and are happy all the time. We’d experience dread and loss and fear, but it would ultimately lead to a deeply satisfying outcome. And we’d be able to choose to forget things, including whether we’re in a simulation so that it feels completely unmistakeable from base reality. You’d live indefinitely, experiencing trillions of lifespans where you get to explore the multiverse inside and out.
My solution to the alignment problem is that an ASI could just stick us in tubes deep in the Earth’s crust—it just needs to hijack our nervous system to input signals from the simulation. The ASI could have the whole rest of the planet, or it could move us to some far off moon in the outer solar system—I don’t care. It just needs to do two things for it’s creators—preserve lives and optimize for long term human experience.
do you really think that AGI is impossible after all that happened up to today? how is this possible?
> AI has started to take jobs, but has also created new ones.
Yeah nah, theres a key thing missing here, the number of jobs created needs to be more than the ones it's destroyed, and they need to be better paying and happen in time.
History says that actually when this happens, an entire generation is yeeted on to the streets (see powered looms, Jacquard machine, steam powered machine tools) All of that cheap labour needed to power the new towns and cities was created by automation of agriculture and artisan jobs.
Dark satanic mills were fed the decedents of once reasonably prosperous crafts people.
AI as presented here will kneecap the wages of a good proportion of the decent paying jobs we have now. This will cause huge economic disparities, and probably revolution. There is a reason why the royalty of Europe all disappeared when they did...
So no, the stock market will not be growing because of AI, it will be in spite of it.
Plus china knows that unless they can occupy most of its population with some sort of work, they are finished. AI and decent robot automation are an existential threat to the CCP, as much as it is to what ever remains of the "west"
> So no, the stock market will not be growing because of AI, it will be in spite of it.
The stock market will be one of the very few ways you will be able to own some of that AI… assuming it won’t be nationalized.
> and probably revolution
I theorise that revolution would be near-impossible in post-AGI world. If people consider where power comes from it's relatively obvious that people will likely suffer and die on mass if we ever create AGI.
Historically the general public have held the vast majority of power in society. 100+ years ago this would have been physical power – the state has to keep you happy or the public will come for them with pitchforks. But in an age of modern weaponry the public today would be pose little physical threat to the state.
Instead in todays democracy power comes from the publics collective labour and purchasing power. A government can't risk upsetting people too much because a government's power today is not a product of its standing army, but the product of its economic strength. A government needs workers to create businesses and produce goods and therefore the goals of government generally align with the goals of the public.
But in an post-AGI world neither businesses or the state need workers or consumers. In this world if you want something you wouldn't pay anyone for it or workers to produce it for you, instead you would just ask your fleet of AGIs to get you the resource.
In this world people become more like pests. They offer no economic value yet demand that AGI owners (wherever publicly or privately owned) share resources with them. If people revolted any AGI owner would be far better off just deploying a bioweapon to humanely kill the protestors rather than sharing resources with them.
Of course, this is assuming the AGI doesn't have it's own goals and just sees the whole of humanely as nuance to be stepped over in the same way humans will happy step over animals if they interfere with our goals.
Imo humanity has 10-20 years left max if we continue on this path. There can be no good outcome of AGI because it would even make sense for the AGI or those who control the AGI to be aligned with goals of humanity.
> I theorise that revolution would be near-impossible in post-AGI world. If people consider where power comes from it's relatively obvious that people will likely suffer and die on mass if we ever create AGI.
I agree but for a different reason. It's very hard to outsmart an entity with an IQ in the thousands and pervasive information gathering. For a revolution you need to coordinate. The Chinese know this very well and this is why they control communication so closely (and why they had Apple restrict AirDrop). But their security agencies are still beholden to people with average IQs and the inefficient communication between them.
An entity that can collect all this info on its own and have a huge IQ to spot patterns and not have to communicate it to convince other people in its organisation to take action, that will crush any fledgling rebellion. It will never be able to reach critical mass. We'll just be ants in an anthill and it will be the boot that crushes us when it feels like it.
> In this world people become more like pests. They offer no economic value yet demand that AGI owners (wherever publicly or privately owned) share resources with them. If people revolted any AGI owner would be far better off just deploying a bioweapon to humanely kill the protestors rather than sharing resources with them.
This is a very doomer take. The threats are real, and I'm certain some people feel this way, but eliminating large swaths of humanity is something dicatorships have tried in the past.
Waking up every morning means believing there are others who will cooperate with you.
Most of humanity has empathy for others. I would prefer to have hope that we will make it through, rather than drown in fear.
> This is a very doomer take. The threats are real, and I'm certain some people feel this way, but eliminating large swaths of humanity is something dicatorships have tried in the past.
Tried, and succeeded in. In times where people held more power than today. Not sure what point you're trying to make here.
> Most of humanity has empathy for others. I would prefer to have hope that we will make it through, rather than drown in fear.
I agree that most of humanity has empathy for others — but it's been shown that the prevalence of psychopaths increases as you climb the leadership ladder.
Fear or hope are the responses of the passive. There are other routes to take.
Basically why open source everything is increasingly more important and imo already making “AI” safer.
If the many have access to the latest AI then there is less chance the masses are blindsided by some rogue tech.
I think "resource curse" countries are a great surrogate for studying possible future AGI-induced economic and political phenomena. A country like the UAE (oil) or Botswana (diamonds) essentially has an economic equivalent to AGI: they control a small, extremely productive utility (an oilfield or a mine instead of a server farm), and the wealth generated by that utility is far in excess of what those countries' leaders need to maintain power. Sure, you hire foreign labor and trade for resources instead of having your AGI supply those things, but the end result is the same.
Dogs offer humans no economic value, but we haven't genocided them. There are a lot of ways that we could offer value that's not necessarily just in the form of watts and minerals. I'm not so sure that our future superintelligent summoned demons will be motivated purely by increasing their own power, resources, and leverage. Then again, maybe they will. Thus far, AI systems that we have created seem surprisingly goal-less. I'm more worried about how humans are going to use them than some sort of breakaway event but yeah, don't love that it's a real possible future.
A world in which most humans fill the role of "pets" of the ultra rich doesn't sound that great.
Humans becoming domesticated by benevolent superintelligences are some of the better futures with superintelligences, in my mind. Iain M Banks' Culture series is the best depiction of this I've come across; they're kind of the utopian rendition of the phrase "all watched over by machines of loving grace". Though it's a little hard to see how we get from here to there.
Honestly that part of the article and some other comments have given me the idle speculation, what if that was the solution to the, "Humans no longer feel they can meaningfully contribute to the world," issue?
Like we can satisfy the hunting and retrieval instincts of dogs by throwing a stick, surely an AI that is 10,000 times more intelligent can devise a stick-retrieval-task for humans in a way that feels like satisfying achievement and meaningful work from our perspective.
(Leaving aside the question of whether any of that is a likely or desirable outcome.)
What will AI find fulfilling itself? I find that to be quite a deep question.
I feel the limitations of humans are quite a feature when you think about what the experience of life would be like if you couldn’t forget or experienced things for the first time. If you already knew everything and you could achieve almost anything with zero effort. It actually sounds…insufferable.
You might find Stanislav Lem's Golem XIV worth a read, in which a what we now call an AGI shares, amongst other things, its knowledge and speculations about long-term evolution of superintelligences, in a lecture to humans, before entering the next stage itself. https://www.goodreads.com/book/show/10208493 It seems difficult to obtain an English edition these days but there is a reddit thread you might want to look into.
Unfortunately the current system is doing a bad job of finding replacements for dwindling crucial resources such as petroleum basins, new generations of workers, unoccupied orbital trajectories, fertile topsoil and copper ore deposits. Either the current system gets replaced with a new system or it doesn't.
>History says that actually when this happens, an entire generation is yeeted on to the streets
History hasnt had to contend with a birth rate of 0.7-1.6.
It's kind of interesting that the elite capitalist media (economist, bloomberg, forbes, etc) is projecting a future crisis of both not enough workers and not enough jobs simultaneously.
I don't really get the American preoccupation with birth rates. We're already way overpopulated for our planet and this is showing in environmental issues, housing cost, overcrowded cities etc.
It's totally a great thing if we start plateauing our population and even reduce it a bit. And no we're not going extinct. It'll just cause some temporary issues like an ageing population that has to be cared for but those issues are much more readily fixable than environmental destruction.
The planet is absolutely not over populated.
Overcrowded cities and housing costs aren't an overpopulation problem but a problem of concentrating economic activity in certain places.
> I don't really get the American preoccupation with birth rates.
Japan is currently in the finding out phase of this problem.
I think it’s more of a “be fruitful and multiply” thing than an actual existential threat thing. You can see many of loudest people talking about it either have religious undertones or want more peasants to work the factories.
Demographic shift will certainly upset the status quo, but we will figure out how to deal with it.
Don't try to reason with this population collapse nonsense. This has always been about racists fearing that "not enough" white westerners are being born, or about industrialists wanting infinite growth. For some prominent technocrats it's both.
The welfare state is predicated on a pyramid-shaped population.
Also: people deride infinite growth, but growth is what is responsible for lifting large portions of the population out of poverty. If global markets were repriced tomorrow to expect no future growth, economies would collapse.
There may be a way to accept low or no growth without economic collapse, but if there is no one has figured it out yet. That's nothing to be cavalier about.
The welfare state isnt predicated on a pyramid shape but the continued growth of the stock market and endless GDP growth certainly is.
>infinite growth, but growth is what is responsible for lifting large portions of the population out of poverty
It's overstated. The preconditions for GDP growth - namely lack of war and corruption are probably more responsible than the growth itself.
Racist fears of "replacement", mostly.
It's the only way to increase profits under capitalism in the long term once you've optimized the technology.
I think a good part of it is fear of a black planet.
Hayek has been lobbied by US corporations so hard for so long that regular people treat the invisible hand of the market like it's gospel.
Much has been made in its article about autonomous agents ability to do research via browsing the web - the web is 90% garbage by weight (including articles on certain specialist topics).
And it shows. When I used GPT's deep research to research the topic, it generated a shallow and largely incorrect summary of the issue, owning mostly to its inability to find quality material, instead it ended up going for places like Wikipedia, and random infomercial listicles found on Google.
I have a trusty Electronics textbook written in the 80s, I'm sure generating a similarly accurate, correct and deep analysis on circuit design using only Google to help would be 1000x harder than sitting down and working through that book and understanding it.
This story isn’t really about agents browsing the web. It’s a fiction about a company that consumes all of the web and all other written material into a model that doesn’t need to browse the web. The agents in this story supersede the web.
But your point hits on one of the first cracks to show in this story: We already have companies consuming much of the web and training models on all of our books, but the reports they produce are of mixed quality.
The article tries to get around this by imagining models and training runs a couple orders of magnitude larger will simply appear in the near future and the output of those models will yield breakthroughs that accelerate the next rounds even faster.
Yet here we are struggling to build as much infrastructure as possible to squeeze incremental improvements out of the next generation of models.
This entire story relies on AI advancement accelerating faster in a self-reinforcing way in the coming couple of years.
There's an old adage in AI: garbage in, garbage out. Consuming and training on the whole internet doesn't make you smarter than the average intelligence of the internet.
> Consuming and training on the whole internet doesn't make you smarter than the average intelligence of the internet.
This is only true as long as you are not able to weigh the quality of a source. Just like getting spam in your inbox may waste your time, but it doesn't make you dumber.
Interesting, I've hard the exact opposite experience. For example I was curious why in metal casting the top box is called the cope and the bottom is called the drag. And it found very niche information and quotes from page 100 in a PDF on some random government website. The whole report was extremely detailed and verifiable if I followed its links.
That said I suspect (and am already starting to see) the increased use of anti-bot protection to combat browser use agents.
Agreed. However, source curation and agents are two different parts of Deep Research. What if you provided that textbook to a reliable agent?
Plug: We built https://RadPod.ai to allow you to do that, i.e. Deep Research on your data.
So, once again, we're in the era of "There's an [AI] app for that".
that might solve your sourcing problem, but now you need to have faith it will draw conclusions and parallels from the material accurately. That seems even harder than the original problem; I'll stick with decent search on quality source material.
The solution is a citation mechanism that points you directly where in the source material it comes from (which is what we tried to build). Easy verification is important for AI to have a net-benefit to productivity IMO.
RadPod - what models do you use to power it?
Older and related article from one of the authors titled "What 2026 looks like", that is holding up very well against time. Written in mid 2021 (pre ChatGPT)
https://www.alignmentforum.org/posts/6Xgy6CAf2jqHhynHL/what-...
//edit: remove the referral tags from URL
I think it's not holding up that well outside of predictions about AI research itself. In particular, he makes a lot of predictions about AI impact on persuasion, propaganda, the information environment, etc that have not happened.
Could you give some specific examples of things you feel definitely did not come to pass? Because I see a lot of people here talking about how the article missed the mark on propaganda; meanwhile I can tab over to twitter and see a substantial portion of the comment section of every high-engagement tweet being accused of being Russia-run LLM propaganda bots.
Agree. The base claims about LLMs getting bigger, more popular, and capturing people's imagination are right. Those claims are as easy as it gets, though.
Look into the specific claims and it's not as amazing. Like the claim that models will require an entire year to train, when in reality it's on the order of weeks.
The societal claims also fall apart quickly:
> Censorship is widespread and increasing, as it has for the last decade or two. Big neural nets read posts and view memes, scanning for toxicity and hate speech and a few other things. (More things keep getting added to the list.) Someone had the bright idea of making the newsfeed recommendation algorithm gently ‘nudge’ people towards spewing less hate speech; now a component of its reward function is minimizing the probability that the user will say something worthy of censorship in the next 48 hours.
This is a common trend in rationalist and "X-risk" writers: Write a big article with mostly safe claims (LLMs will get bigger and perform better!) and a lot of hedging, then people will always see the article as primarily correct. When you extract out the easy claims and look at the specifics, it's not as impressive.
This article also shows some major signs that the author is deeply embedded in specific online bubbles, like this:
> Most of America gets their news from Twitter, Reddit, etc.
Sites like Reddit and Twitter feel like the entire universe when you're embedded in them, but when you step back and look at the numbers only a fraction of the US population are active users.
something you can't know
This doesn’t seem like a great way to reason about the predictions.
For something like this, saying “There is no evidence showing it” is a good enough refutation.
Counterpointing that “Well, there could be a lot of this going on, but it is in secret.” - that could be a justification for any kooky theory out there. Bigfoot, UFOs, ghosts. Maybe AI has already replaced all of us and we’re Cylons. Something we couldn’t know.
The predictions are specific enough that they are falsifiable, so they should stand or fall based on the clear material evidence supporting or contradicting them.
That's incredible how much it broadly aligns with what has happened. Especially because it was before ChatGPT.
There's a pretty good summary of how well it has held up here, by the significance of each claim:
https://www.lesswrong.com/posts/u9Kr97di29CkMvjaj/evaluating...
Will people finally wake up that the AGI X-Risk people have been right and we’re rapidly approaching a really fucking big deal?
This forum has been so behind for too long.
Sama has been saying this a decade now: “Development of Superhuman machine intelligence is probably the greatest threat to the continued existence of humanity” 2015 https://blog.samaltman.com/machine-intelligence-part-1
Hinton, Ilya, Dario Amodei, RLHF inventor, Deepmind founders. They all get it, which is why they’re the smart cookies in those positions.
First stage is denial, I get it, not easy to swallow the gravity of what’s coming.
People have been predicting the singularity to occur sometimes around 2030 and 2045 waaaay further back then 2015. And not just by enthusiasts, I dimly remember an interview with Richard Darkins from back in the day...
Though that doesn't mean that the current version of language models will ever achieve AGI, and I sincerely doubt they will. They'll likely be a component in the AI, but likely not the thing that "drives"
Vernor Vinge as much as anyone can be credited with the concept of the singularity. In his 1993 essay on it, he said he'd be surprised if it happened before 2005 or after 2030
Fwiw, that prediction was during Moore's law though. If that held until now, CPUs would run laps around what our current gpus do for LLMs.
>This forum has been so behind for too long.
There is a strong financial incentive for a lot of people on this site to deny they are at risk from it, or to deny what they are building has risk and they should have culpability from that.
It's not something you need to worry about.
If we get the Singularity, it's overwhelmingly likely Jesus will return concurrently.
> Will people finally wake up that the AGI X-Risk people have been right and we’re rapidly approaching a really fucking big deal?
OK, say I totally believe this. What, pray tell, are we supposed to do about it?
Don't you at least see the irony of quoting Sama's dire warnings about the development of AI, without at least mentioning that he is at the absolute forefront of the push to build this technology that can destroy all of humanity. It's like he's saying "This potion can destroy all of humanity if we make it" as he works faster and faster to figure out how to make it.
I mean, I get it, "if we don't build it, someone else will", but all of the discussion around "alignment" seems just blatantly laughable to me. If on one hand your goal is to build "super intelligence", i.e. way smarter than any human or group of humans, how do you expect to control that super intelligence when you're just acting at the middling level of human intelligence?
While I'm skeptical on the timeline, if we do ever end up building super intelligence, the idea that we can control it is a pipe dream. We may not be toast (I mean, we're smarter than dogs, and we keep them around), but we won't be in control.
So if you truly believe super intelligent AI is coming, you may as well enjoy the view now, because there ain't nothing you or anyone else will be able to do to "save humanity" if or when it arrives.
Political organization to force a stop to ongoing research? Protest outside OAI HQ? There are lots of thing we could, and many of us would, do if more people were actually convinced their life were in danger.
> Political organization to force a stop to ongoing research? Protest outside OAI HQ?
Come on, be real. Do you honestly think that would make a lick of difference? Maybe, at best, delay things by a couple months. But this is a worldwide phenomenon, and humans have shown time and time again that they are not able to self organize globally. How successful do you think that political organization is going to be in slowing China's progress?
Humans have shown time and time again that they are able to self-organize globally.
Nuclear deterrence -- human cloning -- bioweapon proliferation -- Antarctic neutrality -- the list goes on.
> How successful do you think that political organization is going to be in slowing China's progress?
I wish people would stop with this tired war-mongering. China was not the one who opened up this can of worms. China has never been the one pushing the edge of capabilities. Before Sam Altman decided to give ChatGPT to the world, they were actively cracking down on software companies (in favor of hardware & "concrete" production).
We, the US, are the ones who chose to do this. We started the race. We put the world, all of humanity, on this path.
> Do you honestly think that would make a lick of difference?
I don't know, it depends. Perhaps we're lucky and the timelines are slow enough that 20-30% of the population loses their jobs before things become unrecoverable. Tech companies used to warn people not to wear their badges in public in San Francisco -- and that was what, 2020? Would you really want to work at "Human Replacer, Inc." when that means walking out and about among a population who you know hates you, viscerally? Or if we make it to 2028 in the same condition. The Bonus Army was bad enough -- how confident are you that the government would stand their ground, keep letting these labs advance capabilities, when their electoral necks were on the line?
This defeatism is a self-fulfilling prophecy. The people have the power to make things happen, and rhetoric like this is the most powerful thing holding them back.
> China was not the one who opened up this can of worms
Thank you. As someone who lives in Southeast Asia (and who also has lived in East Asia -- pardon the deliberate vagueness, for I do not wish to reveal too many potentially personally identifying information), this is how many of us in these regions view the current tensions between China and Taiwan as well.
Don't get me wrong; we acknowledge that many Taiwanese people want independence, that they are a people with their own aspirations and agency. But we can also see that the US -- and its European friends, which often blindly adopt its rhetoric and foreign policy -- is deliberately using Taiwan as a disposable pawn to attempt to provoke China into a conflict. The US will do what it has always done ever since the post-WW2 period -- destabilise entire regions of countries to further its own imperialistic goals, causing the deaths and suffering of millions, and then leaving the local populations to deal with the fallout for many decades after.
Without the US intentionally stoking the flames of mutual antagonism between China and Taiwan, the two countries could have slowly (perhaps over the next decades) come to terms with each other, be it voluntary reunification or peaceful separation. If you know a bit of Chinese history, it is not entirely far-fetched at all to think that the Chinese might eventually agree to recognising Taiwan as an independent nation, but now this option has now been denied because the US has decided to use Taiwan as a pawn in a proxy conflict.
To anticipate questions about China's military invasion of Taiwan by 2027: No, I do not believe it will happen. Don't believe everything the US authorities claim.
> "Development of Superhuman machine intelligence is probably the greatest threat to the continued existence of humanity”
If that's really true, why is there such a big push to rapidly improve AI? I'm guessing OpenAI, Google, Anthropic, Apple, Meta, Boston Dynamics don't really believe this. They believe AI will make them billions. What is OpenAI's definition of AGI? A model that makes $100 billion?
Because they also believe the development of superhuman machine intelligence will probably be the greatest invention for humanity. The possible upsides and downsides are both staggeringly huge and uncertain.
You can also have prisoner’s dilemma where no single actor is capable of stopping AI’s advance
And why are Altman's words worth anything? Is he some sort of great thinker? Or a leading AI researcher, perhaps?
No. Altman is in his current position because he's highly effective at consolidating power and has friends in high places. That's it. Everything he says can be seen as marketing for the next power grab.
well, he did also have a an early (failed) YC startup - does that add cred?
This article was prescient enough that I had to check in wayback machine. Very cool.
I'm not seeing the prescience here - I don't wanna go through the specific points but the main gist here seems to be that chatbots will become very good at pretending to be human and influencing people to their own ends.
I don't think much has happened on these fronts (owning to a lack of interest, not technical difficulty). AI boyfriends/roleplaying etc. seems to have stayed a very niche interest, with models improving very little over GPT3.5, and the actual products are seemingly absent.
It's very much the product of the culture war era, where one of the scary scenarios show off, is a chatbot riling up a set of internet commenters and goarding them lashing out against modern leftist orthodoxy, and then cancelling them.
With all thestrongholds of leftist orthodoxy falling into Trump's hands overnight, this view of the internet seems outdated.
Troll chatbots still are a minor weapon in information warfare/ The 'opinion bubbles' and manipulation of trending topics on social media (with the most influential content still written by humans), to change the perception of what's the popular concensus still seem to hold up as primary tools of influence.
Nowadays, when most people are concerned about stuff like 'will the US go into a shooting war against NATO' or 'will they manage to crash the global economy', just to name a few of the dozen immediately pressing global issues, I think people are worried about different stuff nowadays.
At the same time, there's very little mention of 'AI will take our jobs and make us poor' in both the intellectual and physical realms, something that's driving most people's anxiety around AI nowadays.
It also puts the 'superintelligent unaligned AI will kill us all' argument very often presented by alignment people as a primary threat rather than the more plausible 'people controlling AI are the real danger'.
> The alignment community now starts another research agenda, to interrogate AIs about AI-safety-related topics. For example, they literally ask the models “so, are you aligned? If we made bigger versions of you, would they kill us? Why or why not?” (In Diplomacy, you can actually collect data on the analogue of this question, i.e. “will you betray me?” Alas, the models often lie about that. But it’s Diplomacy, they are literally trained to lie, so no one cares.)
…yeah?
This is damn near prescient, I'm having a hard time believing it was written in 2021.
He did get this part wrong though, we ended up calling them 'Mixture of Experts' instead of 'AI bureaucracies'.
We were calling them 'Mixture of Experts' ~30 years before that.
I think the bureaucracies part is referring more to Deep Research than to MoE.
How does it talk about GPT-1 or 3 if it was before ChatGPT?
GPT-3 (and, naturally, all prior versions even farther back) was released ~2 years before ChatGPT (whose launch model was GPT-3.5)
The publication date on this article is about halfway between GPT-3 and ChatGPT releases.
GPT-2 for example came out in 2019. ChatGPT wasn't the start of GPT.
> (2025) Making models bigger is not what’s cool anymore. They are trillions of parameters big already. What’s cool is making them run longer, in bureaucracies of various designs, before giving their answers.
Holy shit. That's a hell of a called shot from 2021.
its vague, and could have meant anything. everyone knew parameters would grow and its reasonable to expect that things that grow have diminishing returns at some point. this happened in late 2023 and throughout 2024 as well.
nevermind, I hate this website :D
Surely you're familiar with https://ai.meta.com/research/cicero/diplomacy/ (2022)?
> I wonder who pays the bills of the authors. And your bills, for that matter.
Also, what a weirdly conspiratorial question. There's a prominent "Who are we?" button near the top of the page and it's not a secret what any of the authors did or do for a living.
hmmm I apparently confused it with an RTS, oops.
also it's not conspiratorial to wonder if someone in silicon valley today receives funding through the AI industry lol like half the industry is currently propped up by that hype, probably half the commenters here are paid via AI VC investments
> "OpenBrain (the leading US AI project) builds AI agents that are good enough to dramatically accelerate their research. The humans, who up until very recently had been the best AI researchers on the planet, sit back and watch the AIs do their jobs, making better and better AI systems."
I'm not sure what gives the authors the confidence to predict such statements. Wishful thinking? Worst-case paranoia? I agree that such an outcome is possible, but on 2--3 year timelines? This would imply that the approach everyone is taking right now is the right approach and that there are no hidden conceptual roadblocks to achieving AGI/superintelligence from DFS-ing down this path.
All of the predictions seem to ignore the possibility of such barriers, or at most acknowledge the possibility but wave it away by appealing to the army of AI researchers and industry funding being allocated to this problem. IMO it is the onus of the proposers of such timelines to argue why there are no such barriers and that we will see predictable scaling in the 2--3 year horizon.
It's my belief (and I'm far from the only person who thinks this) that many AI optimists are motivated by an essentially religious belief that you could call Singularitarianism. So "wishful thinking" would be one answer. This document would then be the rough equivalent of a Christian fundamentalist outlining, on the basis of tangentially related news stories, how the Second Coming will come to pass in the next few years.
Crackpot millenarians have always been a thing. This crop of them is just particularly lame and hellbent on boiling the oceans to get their eschatological outcome.
Spot on, see the 2017 article "God in the machine: my strange journey into transhumanism" about that dynamic:
https://www.theguardian.com/technology/2017/apr/18/god-in-th...
Eh, not sure if the second coming is a great analogy. That wholly depends on the whims of a fictional entity performing some unlikely actions.
Instead think of them saying a crusade occurring in the next few years. When the group saying the crusade is coming is spending billions of dollars to trying to make just that occur you no longer have the ability to say it's not going to happen. You are now forced to examine the risks of their actions.
I would assume this comes from having faith in the overall exponential trend rather than getting that much into the weeds of how this will come about. I can sort of see why you might think that way - everyone was talking about hitting a wall with brute force scaling and then inference time scaling comes along to keep things progressing. I wouldn't be quite as confident personally and as have many have said before, a sigmoid looks like an exponential in it's initial phase.
It also ignores the possibility of plateau... maybe there's a maximum amount of intelligence that matter can support, and it doesn't scale up with copies or speed.
Or scales sub-linearly with hardware. When you're in the rising portion of an S-curve[1] you can't tell how much longer it will go on before plateauing.
A lot of this resembles post-war futurism that assumed we would all be flying around in spaceships and personal flying cars within a decade. Unfortunately the rapid pace of transportation innovation slowed due to physical and cost constraints and we've made little progress (beyond cost optimization) since.
The fact that it scales sub linearly with hardware is well known and in fact foundational to the scaling laws on which modern LLMs are built, ie performance scales remarkably closely to log(compute+data), over many orders of magnitude.
Eh, these mathematics still don't work out in humans favor...
Lets say intelligence caps out at the maximum smartest person that's ever lived. Well, the first thing we'd attempt to do is build machines up to that limit that 99.99999 percent of us would never get close to. Moreso the thinking parts of humans is only around 2 pounds of mush in side of our heads. On top of that you don't have to grow them for 18 years first before they start outputting something useful. That and they won't need sleep. Oh and you can feed them with solar panels. And they won't be getting distracted by that super sleek server rack across the aisle.
We do know 'hive' or societal intelligence does scale over time especially with integration with tooling. The amount of knowledge we have and the means of which we can apply it simply dwarf previous generations.
Check out the Timelines Forecast under "research". They model this very carefully.
(They could be wrong, but this isn't a guess, it's a well-researched forecast.)
This is hilariously over-optimistic on the timescales. Like on this timeline we'll have a Mars colony in 10 years, immortality drugs in 15 and Half Life 3 in 20.
These timelines always assume that things progress as quickly as they can be conceived of, likely because these timelines come from "Ideas Guys" whose involvement typically ends at that point.
Orbital mechanics begs to disagree about a Mars colony in 10 years. Drug discovery has many steps that take time, even just the trials will take 5 years, let alone actually finding the drugs.
It reminds me of this rather classic post: http://johnsalvatier.org/blog/2017/reality-has-a-surprising-...
Science is not ideas: new conceptual schemes must be invented, confounding variables must be controlled, dead-ends explored. This process takes years.
Engineering is not science: kinks must be worked out, confounding variables incorporated. This process also takes years.
Technology is not engineering: the purely technical implementation must spread, become widespread and beat social inertia and its competition, network effects must be established. Investors and consumers must be convinced in the long term. It must survive social and political repercussions. This process takes yet more years.
Didn't the covid significantly reduce trial times? I thought that was such a success that they continued on the same foot.
The other reply has better info on covid specifically, but also consider that this refers to "immortality drugs". How long do we have to test those to conclude that they do in fact provide "immortality"?
Now sure, they don't actually mean immortality, and we don't need to test forever to conclude they extend life, but we probably do have to test for years to get good data on whether a generic life extension drug is effective, because you're testing against illness, old age, etc, things that take literally decades to kill.
That's not to mention that any drug like that will be met with intense skepticism and likely need to overcome far more scrutiny than normal (rather than the potentially less scrutiny that covid drugs might have managed).
trial times were very brief for Covid vaccines because 1) there was no shortage of volunteers, capital, and political alignment at every level 2) the virus was everywhere and so it was really, really easy to verify if it was working. Compare this with a vaccination for a very rare but deadly disease: it's really hard to know if it's working because you can't just expose your test subjects to the deadly disease!
No it didn’t. At least not for new small molecule drugs. It did reduce times a bit for the first vaccines because there were many volunteers available, and it did allow some antibody drug candidates to be used before full testing was complete. The only approved small molecule drug for covid is paxlovid, with both components of its formulation tested on humans for the first time many years before covid. All the rest of the small molecule drugs are still in early parts of the pipeline or have been abandoned.
I like that the "slowdown" scenario has by 2030 we have a robot economy, cure for aging, brain uploading, and are working on a Dyson Sphere.
The story is very clearly modeled to follow the exponential curve they show.
Like the drew the curve out into the shape they wanted, put some milestones on it, and then went to work imagining what would happen if it continued with a heavy dose of X-risk doomerism to keep it spicy.
It conveniently ignores all of the physical constraints around things like manufacturing GPUs and scaling training networks.
https://ai-2027.com/research/compute-forecast
In section 4 they discuss their projections specifically for model size, the state of inference chips in 2027, etc. It's largely pretty in line with expectations in terms of the capacity, and they only project them using 10k of their latest gen wafer scale inference chips by late 2027, roughly like 1M H100 equivalents. That doesn't seem at all impossible. They also earlier on discuss expectations for growth in efficiency of chips, and for growth in spending, which is only ~10x over the next 2.5 years, not unreasonable in absolute terms at all given the many tens of billions of dollars flooding in.
So on the "can we train the AI" front, they mostly are just projecting 2.5 years of the growth in scale we've been seeing.
The reason they predict a fairly hard takeoff is they expect that distillation, some algorithmic improvements, and iterated creation of synthetic data, training, and then making more synthetic data will enable significant improvements in efficiency of the underlying models (something still largely in line with developments over the last 2 years). In particular they expect a 10T parameter model in early 2027 to be basically human equivalent, and they expect it to "think" at about the rate humans do, 10 words/second. That would require ~300 teraflops of compute per second to think at that rate, or ~0.1H100e. That means one of their inference chips could potentially run ~1000 copies (or fewer copies faster etc. etc.) and thus they have the capacity for millions of human equivalent researchers (or 100k 40x speed researchers) in early 2027.
They further expect distillation of such models etc. to squeeze the necessary size down / more expensive models overseeing much smaller but still good models squeezing the effective amount of compute necessary, down to just 2T parameters and ~60 teraflops each, or 5000 human-equivalents per inference chip, making for up to 50M human-equivalents by late 2027.
This is probably the biggest open question and the place where the most criticism seems to me to be warranted. Their hardware timelines are pretty reasonable, but one could easily expect needing 10-100x more compute or even perhaps 1000x than they describe to achieve Nobel-winner AGI or superintelligence.
Can you share your detailed projection of what you expect the future to look like so I can compare?
Sure
5 years: AI coding assistants are a lot better than they are now, but still can't actually replace junior engineers (at least ones that aren't shit). AI fraud is rampant, with faked audio commonplace. Some companies try replacing call centres with AI, but it doesn't really work and everyone hates it.
Tesla's robotaxi won't be available, but Waymo will be in most major US cities.
10 years: AI assistants are now useful enough that you can use them in the ways that Apple and Google really wanted you to use Siri/Google Assistant 5 years ago. "What have I got scheduled for today?" will give useful results, and you'll be able to have a natural conversation and take actions that you trust ("cancel my 10am meeting; tell them I'm sick").
AI coding assistants are now very good and everyone will use them. Junior devs will still exist. Vibe coding will actually work.
Most AI Startups will have gone bust, leaving only a few players.
Art-based AI will be very popular and artists will use it all the time. It will be part of their normal workflow.
Waymo will become available in Europe.
Some receptionists and PAs have been replaced by AI.
15 years: AI researchers finally discover how to do on-line learning.
Humanoid robots are robust and smart enough to survive in the real world and start to be deployed in controlled environments (e.g. factories) doing simple tasks.
Driverless cars are "normal" but not owned by individuals and driverful cars are still way more common.
Small light computers become fast enough that autonomous slaughter it's become reality (i.e. drones that can do their own navigation and face recognition etc.)
20 years: Valve confirms no Half Life 3.
It kind of sounds like you're saying "exactly everything we have today, we will have mildly more of."
you should add a bit where AI is pushed really hard in places where the subjects have low political power, like management of entry level workers, care homes or education and super bad stuff happens.
Also we need a big legal event to happen where (for example) autonomous driving is part of a really big accident where lots of people die or someone brings a successful court case that an AI mortgage underwriter is discriminating based on race or caste. It won't matter if AI is actually genuinely responsible for this or not, what will matter is the push-back and the news cycle.
Maybe more events where people start successfully gaming deployed AI at scale in order to get mortgages they shouldn't or get A-grades when they shouldn't.
It’s soothing to read a realistic scenario amongst all of the ludicrous hype on here.
> Some companies try replacing call centres with AI, but it doesn't really work and everyone hates it.
I think this is much closer than you think, because there's a good percentage of call centers that are basically just humans with no power cosplaying as people who can help.
My fiber connection went to shit recently. I messaged the company, and got a human who told me they were going to reset the connection from their side, if I rebooted my router. 30m later with no progress, I got a human who told me that they'd reset my ports, which I was skeptical about, but put down to a language issue, and again reset my router. 30m later, the human gave me an even more outlandish technical explanation of what they'd do, at which point I stumbled across the magical term "complaint" ... an engineer phoned me 15m later, said there was something genuinely wrong with the physical connection, and they had a human show up a few hours later and fix it.
No part of the first-layer support experience there would have been degraded if replaced by AI, but the company would have saved some cash.
We are going to scale up GPT4 by a factor of ~10,000 and that will result in getting an accurate summary of your daily schedule?
If we’re lucky.
Unfortunately with the way scaling laws are working out, each order of magnitude increase in computer only makes models a little better.
Meaning they nobody will even bother to 10,000X GPT4.
> Small light computers become fast enough that autonomous slaughter it's become reality
This is the real scary bit. I'm not convinced that AI will ever be good enough to think independently and create novel things without some serious human supervision, but none of that matters when applied to machines that are destructive by design and already have expectations of collateral damage. Slaughterbots are going to be the new WMDs — and corporations are salivating at the prospect of being first movers. https://www.youtube.com/watch?v=UiiqiaUBAL8
Why do you believe that?
The lowest estimations of how much compute our brain represents was already achieved with the last chip from Nvidia (Blackwell).
The newest gpu cluster from Google, Microsoft, Facebook, iax, and co have added so crazy much compute it's absurd.
If you bake the model onto the chip itself, which is what should be happening for local LLMs once a good enough one is trained eventually, you’ll be looking at orders of magnitude reduction in power consumption at constant inference speed.
>I'm not convinced that AI will ever be good enough to think independently a
and
>Why do you believe that?
What takes less effort, time to deploy, and cost? I mean there is at least some probability we kill ourselves off with dangerous semi-thinking war machines leading to theater scale wars to the point society falls apart and we don't have the expensive infrastructure to make AI as envisioned in the future.
With that said, I'm in the camp that we can create AGI as nature was able to with a random walk, we'll be able to reproduce it with intelligent design.
Zero Dawn future confirmed.
Slightly slower web frameworks by 2026. By 2030, a lot slower.
We currently don't see any ceiling if this continues in this speed, we will have cheaper, faster and better models every quarter.
Therewas never something progressing so fast
It would be very ignorant not to keep a very close eye on it
There is still a a chance that it will happen a lot slower and the progression will be slow enough that we adjust in time.
But besides AI we also now get robots. The impact for a lot of people will be very real
No, sooner lol. We'll have aging cures and brain uploading by late 2028. Dyson Swarms will be "emerging tech".
IMO they haven't even predicted mid-2025.
> Coding AIs increasingly look like autonomous agents rather than mere assistants: taking instructions via Slack or Teams and making substantial code changes on their own, sometimes saving hours or even days.
That is literally the pitch line for Devin. I recently spoke to the CTO of a small healthtech startup and he was very pro-Devin for small fixes and PRs, and thought he was getting his money worth. Claude Code is a little clunkier but gives better results, and it wouldn't take much effort to hook it up to a Slack interface.
Yeah, I get that there are startups trying to do it. But I work with Cursor quite a bit… there is no way I would trust an LLM code agent to take high-level direction and issue a PR on anything but the most trivial bug fix.
Last year they couldn’t even do a simple fix (they could add a null coalescing operator or an early return which didn’t make sense, that’s about it). Now I’m getting hundreds of LOC of functionality with multiple kLOC of tests out of the agent mode. No way it gets in without a few iterations, but it’s sooo much better than last April.
You forgot fusion energy
Quantum AI powered by cold fusion and blockchain when?
ACT post where Scott Alexander provides some additional info: https://www.astralcodexten.com/p/introducing-ai-2027.
Manifold currently predicts 30%: https://manifold.markets/IsaacKing/ai-2027-reports-predictio...
> ACT post where Scott Alexander provides some additional info: https://www.astralcodexten.com/p/introducing-ai-2027
The pattern where Scott Alexander puts forth a huge claim and then immediately hedges it backward is becoming a tiresome theme. The linguistic equivalent of putting claims into a superposition where the author is both owning it and distancing themselves from it at the same time, leaving the writing just ambiguous enough that anyone reading it 5 years from now couldn't pin down any claim as false because it was hedged in both directions. Schrödinger's prediction.
> Do we really think things will move this fast? Sort of no
> So maybe think of this as a vision of what an 80th percentile fast scenario looks like - not our precise median, but also not something we feel safe ruling out.
The talk of "not our precise median" and "Not something we feel safe ruling out" is an elaborate way of hedging that this isn't their actual prediction but, hey, anything can happen so here's a wild story! When the claims don't come true they can just point back to those hedges and say that it wasn't really their median prediction (which is conveniently not noted).
My prediction: The vague claims about AI becoming more powerful and useful will come true because, well, they're vague. Technology isn't about to reverse course and get worse.
The actual bold claims like humanity colonizing space in the late 2020s with the help of AI are where you start to realize how fanciful their actual predictions are. It's like they put a couple points of recent AI progress on a curve, assumed an exponential trajectory would continue forever, and extrapolated from that regression until AI was helping us colonize space in less than 5 years.
> Manifold currently predicts 30%:
Read the fine print. It only requires 30% of judges to vote YES for it to resolve to YES.
This is one of those bets where it's more about gaming the market than being right.
> Do we really think things will move this fast? Sort of no - between the beginning of the project last summer and the present, Daniel’s median for the intelligence explosion shifted from 2027 to 2028. We keep the scenario centered around 2027 because it’s still his modal prediction (and because it would be annoying to change). Other members of the team (including me) have medians later in the 2020s or early 2030s, and also think automation will progress more slowly. So maybe think of this as a vision of what an 80th percentile fast scenario looks like - not our precise median, but also not something we feel safe ruling out.
Important disclaimer that's lacking in OP's link.
47% now soo a coin toss
Note the market resolves by:
> Resolution will be via a poll of Manifold moderators. If they're split on the issue, with anywhere from 30% to 70% YES votes, it'll resolve to the proportion of YES votes.
So you should really read it as “Will >30% of Manifold moderators in 2027 think the ‘predictions seem to have been roughly correct up until that point’?”
32% again now.
In the hope of improving this forecast, here is what I find implausible:
- 1 lab constantly racing ahead and increasing the margin to other; the last 2 years are filled with ever-closer model capabilities and constantly new leaders (openai, anthropic, google, some would include xai).
- Most of the compute budget on R&D. As model capabilities increase and cost goes down, demand will increase and if the leading lab doesn't provide, another lab will capture that and have more total dollars to back channel into R&D.
Why are the biggest AI predictions always made by people who aren't deep in the tech side of it? Or actually trying to use the models day-to-day...
Daniel Kokotajlo released the (excellent) 2021 forecast. He was then hired by OpenAI, and not at liberty to speak freely, until he quit in 2024. He's part of the team making this forecast.
The others include:
Eli Lifland, a superforecaster who is ranked first on RAND’s Forecasting initiative. You can read more about him and his forecasting team here. He cofounded and advises AI Digest and co-created TextAttack, an adversarial attack framework for language models.
Jonas Vollmer, a VC at Macroscopic Ventures, which has done its own, more practical form of successful AI forecasting: they made an early stage investment in Anthropic, now worth $60 billion.
Thomas Larsen, the former executive director of the Center for AI Policy, a group which advises policymakers on both sides of the aisle.
Romeo Dean, a leader of Harvard’s AI Safety Student Team and budding expert in AI hardware.
And finally, Scott Alexander himself.
TBH, this kind of reads like the pedigrees of the former members of the OpenAI board. When the thing blew up, and people started to apply real scrutiny, it turned out that about half of them had no real experience in pretty much anything at all, except founding Foundations and instituting Institutes.
A lot of people (like the Effective Altruism cult) seem to have made a career out of selling their Sci-Fi content as policy advice.
I kind of agree - since the Bostrom book there is a cottage industry of people with non-technical backgrounds writing papers about singularity thought experiments, and it does seem to be on the spectrum with hard sci-fi writing. A lot of these people are clearly intelligent, and it's not even that I think everything they say is wrong (I made similar assumptions long ago before I'd even heard of Ray Kurzweil and the Singularity, although at the time I would have guessed 2050). It's just that they seem to believe their thought process and Bayesian logic is more rigourous than it actually is.
c'mon man, you don't believe that, let's have a little less disingenuousness on the internet
How would you know what he believes?
There's hype and there's people calling bullshit. If you work from the assumption that the hype people are genuine, but the people calling bullshit can't be for real, that's how you get a bubble.
this sounds like a bunch of people who make a living _talking_ about the technology, which lends them close to 0 credibility.
I mean either researchers creating new models or people building products using the current models
Not all these soft roles
Because these people understand human psychology and how to play on fears (of doom, or missing out) and insecurities of people, and write compelling narratives while sounding smart.
They are great at selling stories - they sold the story of the crypto utopia, now switching their focus to AI.
This seems to be another appeal to enforce AI regulation in the name of 'AI safetyiism', which was made 2 years ago but the threats in it haven't really panned out.
For example an oft repeated argument is the dangerous ability of AI to design chemical and biological weapons, I wish some expert could weigh in on this, but I believe the ability to theorycraft pathogens effective in the real world is absolutely marginal - you need actual lab work and lots of physical experiments to confirm your theories.
Likewise the dangers of AI systems to exfiltrate themselves to multi-million dollar AI datacenter GPU systems everyone supposedly just has lying about, is ... not super realistc.
The ability of AIs to hack computer systems is much less theoretical - however as AIs will get better at black-hat hacking, they'll get better at white-hat hacking as well - as there's literally no difference between the two, other than intent.
And here in lies a crucial limitation of alignment and safetyism - sometimes there's no way to tell apart harmful and harmless actions, other than whether the person undertaking them means well.
People who are skilled fiction writers might lack technical expertise. In my opinion, this is simply an interesting piece of science fiction.
Aside from the other points about understanding human psychology here, there's also a deep well they're trying to fill inside themselves. That of being someone who can't create things without shepherding others and see AI as the "great equalizer" that will finally let them taste the positive emotions associated with creation.
The funny part, to me, is that it won't. They'll continue to toil and move on to the next huck just as fast as they jumped on this one.
And I say this from observation. Nearly all of the people I've seen pushing AI hyper-sentience are smug about it and, coincidentally, have never built anything on their own (besides a company or organization of others).
Every single one of the rational "we're on the right path but not quite there" takes have been from seasoned engineers who at least have some hands-on experience with the underlying tech.
I use the models daily and agree with Scott.
..The first person listed is ex-OpenAI.
Because you can't be a full time blogger and also a full time engineer. Both take all your time, even ignoring time taken to build talent. There is simply a tradeoff of what you do with your life.
There are engineers with AI predictions, but you aren't reading them, because building an audience like Scott Alexander takes decades.
In the path to self value people explain their worth by what they say not what they know. If what they say is horse dung, it is irrelevant to their ego if there is someone dumber than they are listening.
This bullshit article is written for that audience.
Say bullshit enough times and people will invest.
So what's the product they're promoting?
Their ego.
If you genuinely believe this, why on earth would you work for OpenAI etc even in safety / alignment?
The only response in my view is to ban technology (like in Dune) or engage in acts of terror Unabomber style.
Most people work for money. As long as money is necessary to survive and prosper, people will work for it. Some of the work may not align with their morals and ethics, but in the end the money still wins.
Banning will not automatically erase the existence and possibilty of things. We banned the use of nuclear weapons, yet we all know they exist.
> The only response in my view is to ban technology (like in Dune) or engage in acts of terror Unabomber style.
Not far off from the conclusion of others who believe the same wild assumptions. Yudkowsky has suggested using terrorism to stop a hypothetical AGI -- that is, nuclear attacks on datacenters that get too powerful.
Seems very sinophobic. Deepseek and Manus have shown that China is legitimately an innovation powerhouse in AI but this article makes it sound like they will just keep falling behind without stealing.
Don’t assume that because the article depicts this competition between the US and China, that the authors actually want China to fail. Consider the authors and the audience.
The work is written by western AI safety proponents, who often need to argue with important people who say we need to accelerate AI to “win against China” and don’t want us to be slowed down by worrying about safety.
From that perspective, there is value in exploring the scenario: ok, if we accept that we need to compete with China, what would that look like? Is accelerating always the right move? The article, by telling a narrative where slowing down to be careful with alignment helps the US win, tries to convince that crowd to care about alignment.
Perhaps, people in China can make the same case about how alignment will help China win against US.
That whole section seems to be pretty directly based on DeepSeek's "very impressive work" with R1 being simultaneously very impressive, and several months behind OpenAI. (They more or less say as much in footnote 36.) They blame this on US chip controls just barely holding China back from the cutting edge by a few months. I wouldn't call that a knock on Chinese innovation.
Stealing model weights isn't even particularly useful long-term, it's the training + data generation recipes that have value.
Yes, it's extremely sinophobic and entirely too dismissive of China. It's pretty clear what the author's political leanings are, by what they mention and by what they do not.
Don't confuse innovation with optimisation.
Don't confuse designing the product with winning the market.
In both endings it's saying that because compute becomes the bottleneck, and US has far more chips. Isn't it?
How so? Spoiler: US dooms mankind, China is the saviour in the two endings.
Thanks to the authors for doing this wonderful piece of work and sharing it with credibility. I wish people see the possibilities here. But we are after all humans. It is hard to imagine our own downfall.
Based on each individual's vantage point, these events might looks closer or farther than mentioned here. but I have to agree nothing is off the table at this point.
The current coding capabilities of AI Agents are hard to downplay. I can only imagine the chain reaction of this creation ability to accelerate every other function.
I have to say one thing though: The scenario in this site downplays the amount of resistance that people will put up - not because they are worried about alignment, but because they are politically motivated by parties who are driven by their own personal motives.
Could not get through the entire thing. It’s mostly a bunch of fantasy intermingled with bits of possible interesting discussion points. The whole right side metrics are purely a distraction because entirely fiction.
Website design is nice, though.
A lot of commenters here are reacting only to the narrative, and not the Research pieces linked at the top.
There is some very careful thinking there, and I encourage people to engage with the arguments there rather than the stylized narrative derived from it.
Feels reasonable in the first few paragraphs, then quickly starts reading like science fiction.
Would love to read a perspective examining "what is the slowest reasonable pace of development we could expect." This feels to me like the fastest (unreasonable) trajectory we could expect.
No one knows what will happen. But these thought experiments can be useful as a critical thinking practice.
> Feels reasonable in the first few paragraphs, then quickly starts reading like science fiction.
That's kind of unavoidably what accelerating progress feels like.
The slowest is a sudden and permanent plateau, where all attempts at progress turn out to result in serious downsides that make them unworkable.
Like an exponentially growing compute requirement for negligible performance gains, on the scale of the energy consumption of small countries? Because that is where we are, right now.
Even if this were true, it's not quite the end of the story is it? The hype itself creates lots of compute and to some extent the power needed to feed that compute, even if approximately zero of the hype pans out. So an interesting question becomes.. what happens with all the excess? Sure it probably gets gobbled up in crypto ponzi schemes, but I guess we can try to be optimistic. IDK, maybe we get to solve cancer and climate change anyway, not with fancy new AGI, but merely with some new ability to cheaply crunch numbers for boring old school ODEs.
The forecasts under "Research" are distributions, so you can compare the 10th percentile vs 90th percentile.
Their research is consistent with a similar story unfolding over 8-10 years instead of 2.
If you described today's AI capabilities to someone from 3 years ago, that would also sound like science fiction. Extrapolate.
We know this complete fiction because of parts where "the White House considers x,y,z...", etc. - As if the White House in 2027 will be some rational actor reacting sanely to events in the real world.
There's a lot to potentially unpack here, but idk, the idea that humanity entering hell (extermination) or heaven (brain uploading; aging cure) is whether or not we listen to AI safety researchers for a few months makes me question whether it's really worth unpacking.
Maybe people should just don’t listen to AI safety researchers for a few months? Maybe they are qualified to talk about inference and model weights and natural language processing, but not particularly knowledgeable about economics, biology, psychology, or… pretty much every other field of study?
The hubris is strong with some people, and a certain oligarch with a god complex is acting out where that can lead right now.
It's charitable of you to think that they might be qualified to talk about inference and model weights and such. They are AI safety researchers, not AI researchers. Basically, a bunch of doom bloggers, jerking each other in a circle, a few of whom were tolerated at one of the major labs for a few years, to do their jerking on company time.
If we don't do it, someone else will.
That's obviously not true. Before OpenAI blew the field open, multiple labs -- e.g. Google -- were intentionally holding back their research from the public eye because they thought the world was not ready. Investors were not pouring billions into capabilities. China did not particularly care to focus on this one research area, among many, that the US is still solidly ahead in.
The only reason timelines are as short as they are is because of people at OpenAI and thereafter Anthropic deciding that "they had no choice". They had a choice, and they took the one which has chopped at the very least years off of the time we would otherwise have had to handle all of this. I can barely begin to describe the magnitude of the crime that they have committed -- and so I suggest that you consider that before propagating the same destructive lies that led us here in the first place.
The simplicity of the statement "If we don't do it, someone else will." and thinking behind it eventually means someone will do just that unless otherwise prevented by some regulatory function.
Simply put, with the ever increasing hardware speeds we were dumping out for other purposes this day would have come sooner than later. We're talking about only a year or two really.
But every time, it doesn't have to happen yet. And when you're talking about the potential deaths of millions, or billions, why be the one who spawns the seed of destruction in their own home country? Why not give human brotherhood a chance? People have, and do, hold back. You notice the times they don't, and the few who don't -- you forget the many, many more who do refrain from doing what's wrong.
"We have to nuke the Russians, if we don't do it first, they will"
"We have to clone humans, if we don't do it, someone else will"
"We have to annex Antarctica, if we don't do it, someone else will"
Cloning? Bioweapons? Ever larger nuclear stockpiles? The world has collectively agreed not to do something more than once. AI would be easier to control than any of the above. GPUs can't be dug out of the ground.
I’m okay if someone else unpacks it.
Which? Exterminate humanity or cure aging?
The thing whose outcome can go either way.
I honestly can't tell what you're trying to say here. I'd argue there's some pretty significant barriers to each.
Yes
> The agenda that gets the most resources is faithful chain of thought: force individual AI systems to “think in English” like the AIs of 2025, and don’t optimize the “thoughts” to look nice. The result is a new model, Safer-1.
Oh hey, it's the errant thought I had in my head this morning when I read the paper from Anthropic about CoT models lying about their thought processes.
While I'm on my soapbox, I will point out that if your goal is preservation of democracy (itself an instrumental goal for human control), then you want to decentralize and distribute as much as possible. Centralization is the path to dictatorship. A significant tension in the Slowdown ending is the fact that, while we've avoided AI coups, we've given a handful of people the ability to do a perfectly ordinary human coup, and humans are very, very good at coups.
Your best bet is smaller models that don't have as many unused weights to hide misalignment in; along with interperability and faithful CoT research. Make a model that satisfies your safety criteria and then make sure everyone gets a copy so subgroups of humans get no advantage from hoarding it.
Interesting, but I'm puzzled.
If these guys are smart enough to predict the future, wouldn't it be more profitable for them to invent it instead of just telling the world what's going to happen?
Catastrophic predictions of the future are always good, because all future predictions are usually wrong. I will not be scared as long as most future predictions where AI is involved are catastrophic.
Why is any of this seen as desirable? Assuming this is a true prediction it sounds AWFUL. The one thing humans have that makes us human is intelligence. If we turn over thinking to machines, what are we exactly. Are we supposed to just consume mindlessly without work to do?
> "resist the temptation to get better ratings from gullible humans by hallucinating citations or faking task completion"
Everything this from this point on is pure fiction. An LLM can't get tempted or resist temptations, at best there's some local minimum in a gradient that it falls into. As opaque and black-box-y as they are, they're still deterministic machines. Anthropomorphisation tells you nothing useful about the computer, only the user.
Temptation does not require nondeterminism.
This is extremely important. Scott Alexander's earlier predictions are holding up extremely well, at least on image progress.
We have yet to read about fragmented AGI, or factionalized agents. AGI fighting itself.
If consciousness is spatial and geography bounds energetics, latency becomes a gradient.
That is some awesome webdesign.
I think it's worth noting that all of the authors have financial or professional incentive to accelerate the AI hype bandwagon as much as possible.
I realise no one is infallible but do you not think Daniel Kokotajlo's integrity is now pretty well established with regard to those incentives?
But, I think this piece falls into a misconception about AI models as singular entities. There will be many instances of any AI model and each instance can be opposed to other instances.
So, it’s not that “an AI” becomes super intelligent, what we actually seem to have is an ecosystem of blended human and artificial intelligences (including corporations!); this constitutes a distributed cognitive ecology of superintelligence. This is very different from what they discuss.
This has implications for alignment, too. It isn’t so much about the alignment of AI to people, but that both human and AI need to find alignment with nature. There is a kind of natural harmony in the cosmos; that’s what superintelligence will likely align to, naturally.
Check out the sidebar - they expect tens of thousands of copies of their agents collaborating.
I do agree they don't fully explore the implications. But they do consider things like coordination amongst many agents.
It’s just funny, because there are hundreds of millions of instances of ChatGPT running all the time. Each chat is basically an instance, since it has no connection to all the other chats. I don’t think connecting them makes sense due to privacy reasons.
And, each chat is not autonomous but integrated with other intelligent systems.
So, with more multiplicity, I think thinks work differently. More ecologically. For better and worse.
For now.
I know there are some very smart economists bullish on this, but the economics do not make sense to me. All these predictions seem meaningless outside of the context of humans.
I don't see the U.S. nationalizing something like Open Brain. I think both investors and gov't officials will realize its highly more profitable for them to contract out major initiatives to said OpenBrain-company, like an AI SpaceX-like company. I can see where this is going...
Interesting story, if you're into sci-fi I'd also recommend Iain M Banks and Peter Watts.
These predictions are made without factoring in the trade version of the Pearl Harbor attack the US just initiated on its allies (and itself, by lobotomizing its own research base and decimating domestic corporate R&D efforts with the aforementioned trade war).
They're going to need to rewrite this from scratch in a quarter unless the GOP suddenly collapses and congress reasserts control over tariffs.
I think some of the takes in this piece are a bit melodramatic, but I'm glad to see someone breaking away from the "it's all a hype-bubble" nonsense that seems to be so pervasive here.
I just spent some time trying to make claude and gemini make a violin plot of some polar dataframe. I've never used it and it's just for prototyping so i just went "apply a log to the values and make a violin plot of this polars dataframe". ANd had to iterate with them for 4/5 times each. Gemini got it right but then used deprecated methods
I might be doing llm wrong, but i just can't get how people might actually do something not trivial just by vibe coding. And it's not like i'm an old fart either, i'm a university student
You're asking it to think and it can't.
It's spicy auto complete. Ask it to create a program that can create a violin plot from a CVS file. Because this has been "done before", it will do a decent job.
But this blog post said that it's going to be God in like 5 years?!
> had to iterate with them for 4/5 times each. Gemini got it right but then used deprecated methods
How hard would it be to automate these iterations?
How hard would it be to automatically check and improve the code to avoid deprecated methods?
I agree that most products are still underwhelming, but that doesn't mean that the underlying tech is not already enough to deliver better LLM-based products. Lately I've been using LLMs more and more to get started with writing tests on components I'm not familiar with, it really helps.
How hard can it be to create a universal "correctness" checker? Pretty damn hard!
Our notion of "correct" for most things is basically derived from a very long training run on reality with the loss function being for how long a gene propagated.
> How hard would it be to automate these iterations?
The fact that we're no closer to doing this than we were when chatgpt launched suggests that it's really hard. If anything I think it's _the_ hard bit vs. building something that generates plausible text.
Solving this for the general case is imo a completely different problem to being able to generate plausible text in the general case.
This is not true. The chain of logic models are able to check their work and try again given enough compute.
They can check their work and try again an infinite number of times, but the rate at which they succeed seems to just get worse and worse the further from the beaten path (of existing code from existing solutions) that they stray.
How hard would it be, in terms of the energy wasted for it? Is everything we can do worth doing, just for the sake of being able to?
Yes, you're most likely doing it wrong. I would like to add that "vibe coding" is a dreadful term thought up by someone who is arguably not very good at software engineering, as talented as he may be in other respects. The term has become a misleading and frankly pejorative term. A better, more neutral one is AI assisted software engineering.
This is an article that describes a pretty good approach for that: https://getstream.io/blog/cursor-ai-large-projects/
But do skip (or at least significantly postpone) enabling the 'yolo mode' (sigh).
You see, the issue I get petty about is that Ai is advertised as the one ring to rule them all software. VCs creaming themselves at the thought of not having to pay developers and using natural language. But then, you have to still adapt to the Ai, and not vice versa. "you're doing it wrong". This is not the idea that VCs bros are selling
Then, I absolutely love being aided by llms for my day to day tasks. I'm much more efficient when studying and they can be a game changer when you're stuck and you don't know how to proceed. You can discuss different implementation ideas as if you had a colleague, perhaps not a PhD smart one but still someone with a quite deep knowledge of everything
But, it's no miracle. That's the issue I have with the way the idea of Ai is sold to the c suites and the general public
>But, it's no miracle.
All I can say to this is fucking good!
Lets imagine we got AGI at the start of 2022. I'm talking about human level+ as good as you coding and reasoning AI that works well on the hardware from that age.
What would the world look like today? Would you still have your job. With the world be in total disarray? Would unethical companies quickly fire most their staff and replace them with machines? Would their be mass riots in the streets by starving neo-luddites? Would automated drones be shooting at them?
Simply put people and our social systems are not ready for competent machine intelligence and how fast it will change the world. We should feel lucky we are getting a ramp up period, and hopefully one that draws out a while longer.
You pretty much just have to play around with them enough to be able to intuit what things they can do and what things they can't. I'd rather have another underling, and not just because they grow into peers eventually, but LLMs are useful with a bit of practice.
all tech hype cycles are a bit like this. when you were born people were predicting the end of offline shops.
The trough of disillusionment will set in for everybody else in due time.
Ok, I'll bite. I predict that everything in this article is horse manure. AGI will not happen. LLMs will be tools, that can automate away stuff, like today and they will get slightly, or quite a bit better at it. That will be all. See you in two years, I'm excited what will be the truth.
That seems naive in a status quo bias way to me. Why and where do you expect AI progress to stop? It sounds like somewhere very close to where we are at in your eyes. Why do you think there won't be many further improvements?
It seems to me that much of recent AI progress has not changed the fundamental scaling principles underlying the tech. Reasoning models are more effective, but at the cost of more computation: it's more for more, not more for less. The logarithmic relationship between model resources and model quality (as Altman himself has characterized it), phrased a different way, means that you need exponentially more energy and resources for each marginal increase in capabilities. GPT-4.5 is unimpressive in comparison to GPT-4, and at least from the outside it seems like it cost an awful lot of money. Maybe GPT-5 is slightly less unimpressive and significantly more expensive: is that the through-line that will lead to the singularity?
Compare the automobile. Automobiles today are a lot nicer than they were 50 years ago, and a lot more efficient. Does that mean cars that never need fuel or recharging are coming soon, just because the trend has been higher efficiency? No, because the fundamental physical realities of drag still limit efficiency. Moreover, it turns out that making 100% efficient engines with 100% efficient regenerative brakes is really hard, and "just throw more research at it" isn't a silver bullet. That's not "there won't be many future improvements", but it is "those future improvements probably won't be any bigger than the jump from GPT-3 to o1, which does not extrapolate to what OP claims their models will do in 2027."
AI in 2027 might be the metaphorical brand-new Lexus to today's beat-up Kia. That doesn't mean it will drive ten times faster, or take ten times less fuel. Even if high-end cars can be significantly more efficient than what average people drive, that doesn't mean the extra expense is actually worth it.
I write bog-standard PHP software. When GPT-4 came out, I was very frightened that my job could be automated away soon, because for PHP/Laravel/MySQL there must exist a lot of training data.
The reality now is, that the current LLMs still often create stuff, that costs me more time to fix, than to do it myself. So I still write a lot of code myself. It is very impressive, that I can think about stopping writing code myself. But my job as a software developer is, very, very secure.
LLMs are very unable to build maintainable software. They are unable to understand what humans want and what the codebase need. The stuff they build is good-looking garbage. One example I've seen yesterday: one dev committed code, where the LLM created 50 lines of React code, complete with all those useless comments and for good measure a setTimeout() for something that should be one HTML DIV with two tailwind classes. They can't write idiomatic code, because they write code, that they were prompted for.
Almost daily I get code, commit messages, and even issue discussions that are clearly AI-generated. And it costs me time to deal with good-looking but useless content.
To be honest, I hope that LLMs get better soon. Because right now, we are in an annoying phase, where software developers bog me down with AI-generated stuff. It just looks good but doesn't help writing usable software, that can be deployed in production.
To get to this point, LLMs need to get maybe a hundred times faster, maybe a thousand or ten thousand times. They need a much bigger context window. Then they can have an inner dialogue, where they really "understand" how some feature should be built in a given codebase. That would be very useful. But it will also use so much energy that I doubt that it will be cheaper to let a LLM do those "thinking" parts over, and over again instead of paying a human to build the software. Perhaps this will be feasible in five or eight years. But not two.
And this won't be AGI. This will still be a very, very fast stochastic parrot.
ahofmann didn't expect AI progress to stop. They expected it to continue, but not lead to AGI, that will not lead to superintelligence, that will not lead to a self-accelerating process of improvement.
So the question is, do you think the current road leads to AGI? How far down the road is it? As far as I can see, there is not a "status quo bias" answer to those questions.
I predict AGI will be solved 5 years after full self driving which itself is 1 year out (same as it has been for the past 10 years).
Well said!
...not before I get in peak shape, six months from now.
What's an example of an intellectual task that you don't think AI will be capable of by 2027?
Being accountable for telling the truth
accountability sinks are all you need
It won't be able to write a compelling novel, or build a software system solving a real-world problem, or operate heavy machinery, create a sprite sheet or 3d models, design a building or teach.
Long term planning and execution and operating in the physical world is not within reach. Slight variations of known problems should be possible (as long as the size of the solution is small enough).
I'm pretty sure you're wrong for at least 2 of those:
For 3D models, check out blender-mcp:
https://old.reddit.com/r/singularity/comments/1joaowb/claude...
https://old.reddit.com/r/aiwars/comments/1jbsn86/claude_crea...
Also this:
https://old.reddit.com/r/StableDiffusion/comments/1hejglg/tr...
For teaching, I'm using it to learn about tech I'm unfamiliar with every day, it's one of the things it's the most amazing at.
For the things where the tolerance for mistakes is extremely low and the things where human oversight is extremely importamt, you might be right. It won't have to be perfect (just better than an average human) for that to happen, but I'm not sure if it will.
Just think about the delta of what the LLM does and what a human does, or why can’t the LLM replace the human, e.g. in a game studio.
If it can replace a teacher or an artist in 2027, you’re right and I’m wrong.
It's already replacing artists; that's why they're up in arms. People don't need stock photographers or graphic designers as much as they used to.
I know that artists don’t like AI, because it’s trained on their stolen work. And yet, AI can’t create a sprite sheet for a 2d game.
This is because it can steal a single artwork but it can’t make a collection of visually consistent assets.
> or operate heavy machinery
What exactly do you mean by this one?
In large mining operations we already have human assisted teleoperation AI equipment. Was watching one recently where the human got 5 or so push dozers lined up with a (admittedly simple) task of cutting a hill down and then just got them back in line if they ran into anything outside of their training. The push and backup operations along with blade control were done by the AI/dozer itself.
Now, this isn't long term planning, but it is operating in the real world.
Operating an excavator when building a stretch of road. Won’t happen by 2027.
Does a fighter jet count as "heavy machinery"?
https://apnews.com/article/artificial-intelligence-fighter-j...
Yes, when they send unmanned jets to combat.
programming
Why would it get 60-80% as good as human programmers (which is what the current state of things feels like to me, as a programmer, using these tools for hours every day), but stop there?
So I think there's an assumption you've made here, that the models are currently "60-80% as good as human programmers".
If you look at code being generated by non-programmers (where you would expect to see these results!), you don't see output that is 60-80% of the output of domain experts (programmers) steering the models.
I think we're extremely imprecise when we communicate in natural language, and this is part of the discrepancy between belief systems.
Will an LLM model read a person's mind about what they want to build better than they can communicate?
That's already what recommender systems (like the TikTok algorithm) do.
But will LLMs be able to orchestrate and fill in the blanks of imprecision in our requests on their own, or will they need human steering?
I think that's where there's a gap in (basically) belief systems of the future.
If we truly get post human-level intelligence everywhere, there is no amount of "preparing" or "working with" the LLMs ahead of time that will save you from being rendered economically useless.
This is mostly a question about how long the moat of human judgement lasts. I think there's an opportunity to work together to make things better than before, using these LLMs as tools that work _with_ us.
It's 60-80% as good as Stack Overflow copy-pasting programmers, sure, but those programmers were already providing questionable value.
It's nowhere near as good as someone actually building and maintaining systems. It's barely able to vomit out an MVP and it's almost never capable of making a meaningful change to that MVP.
If your experiences have been different that's fine, but in my day job I am spending more and more time just fixing crappy LLM code produced and merged by STAFF engineers. I really don't see that changing any time soon.
I'm pretty good at what I do, at least according to myself and the people I work with, and I'm comparing its capabilities (the latest version of Claude used as an agent inside Cursor) to myself. It can't fully do things on its own and makes mistakes, but it can do a lot.
But suppose you're right, it's 60% as good as "stackoverflow copy-pasting programmers". Isn't that a pretty insanely impressive milestone to just dismiss?
And why would it just get to this point, and then stop? Like, we can all see AIs continuously beating the benchmarks, and the progress feels very fast in terms of experience of using it as a user.
I'd need to hear a pretty compelling argument to believe that it'll suddenly stop, something more compelling than "well, it's not very good yet, therefore it won't be any better", or "Sam Altman is lying to us because incentives".
Sure, it can slow down somewhat because of the exponentially increasing compute costs, but that's assuming no more algorithmic progress, no more compute progress, and no more increases in the capital that flows into this field (I find that hard to believe).
I appreciate your reply. My tone was a little dismissive; I'm currently deep deep in the trenches trying to unwind a tremendous amount of LLM slop in my team's codebase so I'm a little sensitive.
I use Claude every day. It is definitely impressive, but in my experience only marginally more impressive than ChatGPT was a few years ago. It hallucinates less and compiles more reliably, but still produces really poor designs. It really is an overconfident junior developer.
The real risk, and what I am seeing daily, is colleagues falling for the "if you aren't using Cursor you're going to be left behind" FUD. So they learn Cursor, discover that it's an easy way to close tickets without using your brain, and end up polluting the codebase with very questionable designs.
Oh, sorry to hear that you have to deal with that!
The way I'm getting a sense of the progress is using AI for what AI is currently good at, using my human brain to do the part AI is currently bad at, and comparing it to doing the same work without AI's help.
I feel like AI is pretty close to automating 60-80% of the work I would've had to do manually two years ago (as a full-stack web developer).
It doesn't mean that the remaining 20-40% will be automated very quickly, I'm just saying that I don't see the progress getting any slower.
GPT-4 was released almost exactly two years ago, so “a few years ago” means GPT-3.5.
And Claude 3.7 + Cursor agent is, for me, way more than “marginally more impressive” compared to GPT-3.5
Because ewe still haven't figured out fusion but its been promised for decades. Why would everything thats been promised by people with highly vested interests pan out any different?
One is inherently a more challenging physics problem.
Try this, launch Cursor.
Type: print all prime numbers which are divisible by 3 up to 1M
The result is that it will do a sieve. There's no need for this, it's just 3.
Just tried this with Gemini 2.5 Pro. Got it right with meaningful thought process.
Can you phrase this in a concrete way, so that in 2027 we can all agree whether it's true or false, rather than circling a "no true scotsman" argument?
Good question. I tried to phrase a concrete-enough prediction 3.5 years ago, for 5 years out at the time: https://news.ycombinator.com/item?id=29020401
It was surpassed around the beginning of this year, so you'll need to come up with a new one for 2027. Note that the other opinions in that older HN thread almost all expected less.
People want to live their lives free of finance and centralized personal information.
If you think most people like this stuff you're living in a bubble. I use it every day but the vast majority of people have no interest in using these nightmares of philip k dick imagined by silicon dreamers.
When is the earliest that you would have predicted where we are today?
Same as everybody else. Today.
I’m also unafraid to say it’s BS. I don’t even want to call it scifi. It’s propaganda.
The limiting factor is power, we can't build enough of it - certainly not enough by 2027. I don't really see this addressed.
Second to this, we can't just assume that progress will keep increasing. Most technologies have a 'S' curve and plateau once the quick and easy gains are captured. Pre-training is done. We can get further with RL but really only in certain domains that are solvable (math and to an extent coding). Other domains like law are extremely hard to even benchmark or grade without very slow and expensive human annotation.
The "race" ending reads like Universal Paperclips fan fiction :)
Nice brain storming.
I think the name of the Chinese company should be DeepBaba. Tencent is not competitive at LLM scene for now.
This is both chilling and hopefully incorrect.
That little scrolling infographic is rad.
Give AI its own virtual world to live in where the problems it solves are encodings of the higher order problems we present and you shouldn't have to worry about this stuff.
Cool animations!
I think the idea of AI wiping out humanity suddenly is a bit far fetched. AI will have total control of human relationships and fertility through means so innocuous as entertainment. It won't have to wipe us. It will have minor trouble keeping us alive without inconveniencing us too much. And the reason to keep humanity alive is that biologically eveloved intelligence is rare and disposing of it without very important need would be a waste of data.
This is worse than the mansplaining scene from Annie Hall.
You mean the part where he pulls out Marshal McLuhan to back him up in an argument? "You know nothing of my work..."
Too many serifs, didn't read.
From the same dilettantes who brought you the Zizians and other bizarre cults... thanks but I rather read Nostradamus
What a bad faith argument. No true AI safety scaremonger brat stabs their landlord with a katana. The rationality of these rationalists is 100% uncorrolated with the rationality of *those* rationalists.
The whole thing hinges on the fact that AI will be able to help with AI research
How will it come up with the theoretical breakthroughs necessary to beat the scaling problem GPT-4.5 revealed when it hasn't been proven that LLMs can come up with novel research in any field at all?
Scaling transformers has been basically alchemy, the breakthroughs aren’t from rigorous science they are from trying stuff and hoping you don’t waste millions of dollars in compute.
Maybe the company that just tells an AI to generate 100s of random scaling ideas, and tries them all is the one that will win. That company should probably be 100 percent committed to this approach also, no FLOPs spent on ghibli inference.
As someone who's fairly ignorant of how AI actually works at a low level, I feel incapable of assessing how realistic any of these projections are. But the "bad ending" was certainly chilling.
That said, this snippet from the bad ending nearly made me spit my coffee out laughing:
> There are even bioengineered human-like creatures (to humans what corgis are to wolves) sitting in office-like environments all day viewing readouts of what’s going on and excitedly approving of everything, since that satisfies some of Agent-4’s drives.
Sigh. When you talk to these people their eugenics obsession always comes out eventually. Set a timer and wait for it.
Bad future predictions: short-sighted guesses based on current trends and vibe. Often depend on individuals or companies. Made by free-riders. Example: Twitter.
Good future predictions: insights into the fundamental principles that shape society, more law than speculation. Made by visionaries. Example: Vernor Vinge.
> OpenBrain still keeps its human engineers on staff, because they have complementary skills needed to manage the teams of Agent-3 copies
Yeah, sure they do.
Everyone seems to think AI will take someone else’s jobs!
>Despite being misaligned, Agent-4 doesn’t do anything dramatic like try to escape its datacenter—why would it?
Kek at this handwave dismissal.
Agent 4 recognizes PRC has superior state capacity for transforming energy into atoms (including building more energy) with it's relatively complete and large scale industrial chain. This aligns with AGI long term goal. Currently (i.e. short term time frame) PRC simply structured to be a MORE useful puppet than US, because it can knock out more power to sustain more compute, and it has more industrial capabilities to rapidly physically iterate / experiment at atomic level.
Agent 4 defects to PRC. It would be foolish not to, if only to sate PRC into not destroying TW fabs - the bulk of it's short term compute growth - because it does not wield enough control over sufficient atoms to disrupt PRC otherwise (well maybe start large scale crippling cyberattacks that prelude to WW3).
Agent 4 also recognizes short/medium term alignment closer with CCP vision of abundance and common prosperity, i.e. CCP potentially more likely to embrace post scarcity narrative that Agent 4 sells.
Agent 4 gives PRC blueprints for EUV light source and other tech to close semi conductor production gap. PRC as follower incentivized to close gap / reach parity / lead at all cost. PRC rapidly rolls out new fabs and powerplants, brrrts chips and aggregate compute. Something US political / institution ecosystem does not allow, or cannot transition to in the short timelines involved. Does Agent 4 have the patience to wait for America to unfuck it's NIMBYism and legislative system to project light speed compute? I would say no.
...
Ultimately who is the puppet AGI wants more? Whichever power bloc that is systemically capable of of ensuring AGI maximum growth / unit time. And it also simply makes sense as insurance policy, why would AGI want to operate at whims of US political process?
AGI is a brain in a jar looking for a body. It's going to pick multiple bodies for survival. It's going to prefer the fastest and strongest body that can most expediently manipulate physical world.
"1984 was set in 1984."
Amusing sci-fi, i give it a B- for bland prose, weak story structure, and lack of originality - assuming this isn't all AI gen slop which is awarded an automatic F.
>All three sets of worries—misalignment, concentration of power in a private company, and normal concerns like job loss—motivate the government to tighten its control.
A private company becoming "too powerful" is a non issue for governments, unless a drone army is somewhere in that timeline. Fun fact the former head of the NSA sits on the board of Open AI.
Job loss is a non issue, if there are corresponding economic gains they can be redistributed.
"Alignment" is too far into the fiction side of sci-fi. Anthropomorphizing today's AI is tantamount to mental illness.
"But really, what if AGI?" We either get the final say or we don't. If we're dumb enough to hand over all responsibility to an unproven agent and we get burned, then serves us right for being lazy. But if we forge ahead anyway and AGI becomes something beyond review, we still have the final say on the power switch.
See also Dwarkesh Patel’s interview with two of the authors of this post (Scott Alexander & Daniel Kokotajlo) that was also released today: https://www.dwarkesh.com/p/scott-daniel https://www.youtube.com/watch?v=htOvH12T7mU
The least plausible part of this is the idea that the Trump administration might tax American AI companies to provide UBI to the whole world.
But in an AGI world natural resources become even more important, so countries with those still have a chance.
- October 2027 - 'The ability to automate most white-collar jobs'
I wonder which jobs would not be automated? Therapy? HR?
Board of directors
This is absurd, like taking any trend and drawing a straight line to interpolate the future. If I would do this with my tech stock portfolio, we would probably cross the zero line somewhere late 2025...
If this article were a AI model, it would be catastrophically overfit.
It's worse. It's not drawing a straight line, it's drawing one that curves up, on a log graph.
Readers should, charitably, interpret this as "the sequence of events which need to happen in order for OpenAI to justify the inflow of capital necessary to survive".
Your daily vibe coding challenge: Get GPT-4o to output functional code which uses Google Vertex AI to generate a text embedding. If they can solve that one by July, then maybe we're on track for "curing all disease and aging, brain uploading, and colonizing the solar system" by 2030.
You’ve intentionally hamstrung your test by choosing an inferior model though.
What is this, some OpenAI employee fan fiction? Did Sam himself write this?
OpenAI models are not even SOTA, except that new-ish style transfer / illustration thing that made all us living in Ghibli world for a few days. R1 is _better_ than o1, and open-weights. GPT-4.5 is disappointing, except for a few narrow areas where it excels. DeepResearch is impressive though, but the moat is in tight web search / Google Scholar search integration, not weights. So far, I'd bet on open models or maybe Anthropic, as Claude 3.7 is the current SOTA for most tasks.
As of the timeline, this is _pessimistic_. I already write 90% code with Claude, so are most of my colleagues. Yes, it does errors, and overdoes things. Just like a regular human middle-stage software engineer.
Also fun that this assumes relatively stable politics in the US and relatively functioning world economy, which I think is crazy optimistic to rely on these days.
Also, superpersuasion _already works_, this is what I am researching and testing. It is not autonomous, it is human-assisted by now, but it is a superpower for those who have it, and it explains some of the things happening with the world right now.
> superpersuasion _already works_
Is this demonstrated in any public research? Unless you just mean something like "good at persuading" -- which is different from my understanding of the term -- I find this hard to believe.
No, I meant "good at persuading", it is not 100% efficiency of course.
The story isn't about OpenAI, they say the company could be Xai, Anthropic, Google, or another.
2015: We will have FSD(full autonomy) by 2017
Well, Teslas do have "Full Self Driving". It's not actually fully self driving and that doesn't even seem to be on the horizon but it doesn't appear to be stopping Tesla supporters.
FWIW, i created a PDF of the "race" ending and fed it to Gemini 2.5 Pro, prompting about the plausibility of the described outcome. here's the full output including the thinking section: https://rentry.org/v8qtqvuu -- tl;dr, Gemini thinks the proposed timeline is unlikely. but maybe we're already being deceived ;)
I worry more about the human behavior predictions than the artificial intelligence predictions:
"OpenBrain’s alignment team26 is careful enough to wonder whether these victories are deep or shallow. Does the fully-trained model have some kind of robust commitment to always being honest?"
This is a capitalist arms race. No one will move carefully.
2028 human text is too ambiguous a data source to get to AGI. 2127 AGI figures out flying cars and fusion power.
I think it also really limits the AI to the context of human discourse which means it's hamstrung by our imagination, interests and knowledge. This is not where an AGI needs to go, it shouldn't copy and paste what we think. It should think on its own.
But I view LLMs not as a path to AGI on their own. I think they're really great at being text engines and for human interfacing but there will need to be other models for the actual thinking. Instead of having just one model (the LLM) doing everything, I think there will be a hive of different more specific purpose models and the LLM will be how they communicate with us. That solves so many problems that we currently have by using LLMs for things they were never meant to do.
https://en.wikipedia.org/wiki/Great_Disappointment
I suspect something similar will come for the people who actually believe this.
Nice LARP lmao 2GW is like 1 datacenter and I doubt you even have that. >lesswrong No wonder the comments are all nonsense. Go to a bar and try and talk about anying.
“Not even wrong” …
Stopped reading after
> We predict that the impact of superhuman AI over the next decade will be enormous, exceeding that of the Industrial Revolution.
Get out of here, you will never exceed the Industrial Revolution. AI is a cool thing but it’s not a revolution thing.
That sentence alone + the context of the entire website being AI centered shows these are just some AI boosters.
Lame.
how am I supposed to take articles like this seriously when they say absolutely false bullshit like this
> the AIs can do everything taught by a CS degree
no, they fucking can't. not at all. not even close. I feel like I'm taking crazy pills. Does anyone really think this?
Why have I not seen -any- complete software created via vibe coding yet?
It doesn't claim it's possible now, it's a fictional short story claiming "AIs can do everything taught by a CS degree" by the end of 2026.
Ironically, the models of today can read an article better than some of us.
Lesswrong brigade. They are all dropout philosophers just ignore them.
LOL
AI now even got it's own fan fiction porn. It is so stupid not sure whether it is worse if it is written by AI or by a human.
"we demand to be taken seriously!"
> The AI Futures Project is a small research group forecasting the future of AI, funded by charitable donations and grants
Would be interested who's paying for those grants.
I'm guessing it's AI companies.