This article, "The Gentle Singularity", was written by Sam Altman and explores the development of artificial intelligence and digital superintelligence and their impact on human society. Although humanity has not yet reached full superintelligence, significant progress has already been made in many fields; for example, systems such as GPT-4 have already demonstrated intelligence surpassing humans and can significantly improve human work efficiency. The author, Sam Altman, believes that in the coming years, AI will achieve breakthroughs in more fields, such as systems capable of generating new insights possibly appearing in 2026, and robots capable of performing real-world tasks possibly appearing in 2027.
English version
The Gentle Singularity
We are past the event horizon; the takeoff has started. Humanity is close to building digital superintelligence, and at least so far it’s much less weird than it seems like it should be.
Robots are not yet walking the streets, nor are most of us talking to AI all day. People still die of disease, we still can’t easily go to space, and there is a lot about the universe we don’t understand.
And yet, we have recently built systems that are smarter than people in many ways, and are able to significantly amplify the output of people using them. The least-likely part of the work is behind us; the scientific insights that got us to systems like GPT-4 and o3 were hard-won, but will take us very far.
AI will contribute to the world in many ways, but the gains to quality of life from AI driving faster scientific progress and increased productivity will be enormous; the future can be vastly better than the present. Scientific progress is the biggest driver of overall progress; it’s hugely exciting to think about how much more we could have.
In some big sense, ChatGPT is already more powerful than any human who has ever lived. Hundreds of millions of people rely on it every day and for increasingly important tasks; a small new capability can create a hugely positive impact; a small misalignment multiplied by hundreds of millions of people can cause a great deal of negative impact.
2025 has seen the arrival of agents that can do real cognitive work; writing computer code will never be the same. 2026 will likely see the arrival of systems that can figure out novel insights. 2027 may see the arrival of robots that can do tasks in the real world.
A lot more people will be able to create software, and art. But the world wants a lot more of both, and experts will probably still be much better than novices, as long as they embrace the new tools. Generally speaking, the ability for one person to get much more done in 2030 than they could in 2020 will be a striking change, and one many people will figure out how to benefit from.
In the most important ways, the 2030s may not be wildly different. People will still love their families, express their creativity, play games, and swim in lakes.
But in still-very-important-ways, the 2030s are likely going to be wildly different from any time that has come before. We do not know how far beyond human-level intelligence we can go, but we are about to find out.
In the 2030s, intelligence and energy—ideas, and the ability to make ideas happen—are going to become wildly abundant. These two have been the fundamental limiters on human progress for a long time; with abundant intelligence and energy (and good governance), we can theoretically have anything else.
Already we live with incredible digital intelligence, and after some initial shock, most of us are pretty used to it. Very quickly we go from being amazed that AI can generate a beautifully-written paragraph to wondering when it can generate a beautifully-written novel; or from being amazed that it can make live-saving medical diagnoses to wondering when it can develop the cures; or from being amazed it can create a small computer program to wondering when it can create an entire new company. This is how the singularity goes: wonders become routine, and then table stakes.
We already hear from scientists that they are two or three times more productive than they were before AI. Advanced AI is interesting for many reasons, but perhaps nothing is quite as significant as the fact that we can use it to do faster AI research. We may be able to discover new computing substrates, better algorithms, and who knows what else. If we can do a decade’s worth of research in a year, or a month, then the rate of progress will obviously be quite different.
From here on, the tools we have already built will help us find further scientific insights and aid us in creating better AI systems. Of course this isn’t the same thing as an AI system completely autonomously updating its own code, but nevertheless this is a larval version of recursive self-improvement.
There are other self-reinforcing loops at play. The economic value creation has started a flywheel of compounding infrastructure buildout to run these increasingly-powerful AI systems. And robots that can build other robots (and in some sense, datacenters that can build other datacenters) aren’t that far off.
If we have to make the first million humanoid robots the old-fashioned way, but then they can operate the entire supply chain—digging and refining minerals, driving trucks, running factories, etc.—to build more robots, which can build more chip fabrication facilities, data centers, etc, then the rate of progress will obviously be quite different.
As datacenter production gets automated, the cost of intelligence should eventually converge to near the cost of electricity. (People are often curious about how much energy a ChatGPT query uses; the average query uses about 0.34 watt-hours, about what an oven would use in a little over one second, or a high-efficiency lightbulb would use in a couple of minutes. It also uses about 0.000085 gallons of water; roughly one fifteenth of a teaspoon.)
The rate of technological progress will keep accelerating, and it will continue to be the case that people are capable of adapting to almost anything. There will be very hard parts like whole classes of jobs going away, but on the other hand the world will be getting so much richer so quickly that we’ll be able to seriously entertain new policy ideas we never could before. We probably won’t adopt a new social contract all at once, but when we look back in a few decades, the gradual changes will have amounted to something big.
If history is any guide, we will figure out new things to do and new things to want, and assimilate new tools quickly (job change after the industrial revolution is a good recent example). Expectations will go up, but capabilities will go up equally quickly, and we’ll all get better stuff. We will build ever-more-wonderful things for each other. People have a long-term important and curious advantage over AI: we are hard-wired to care about other people and what they think and do, and we don’t care very much about machines.
A subsistence farmer from a thousand years ago would look at what many of us do and say we have fake jobs, and think that we are just playing games to entertain ourselves since we have plenty of food and unimaginable luxuries. I hope we will look at the jobs a thousand years in the future and think they are very fake jobs, and I have no doubt they will feel incredibly important and satisfying to the people doing them.
The rate of new wonders being achieved will be immense. It’s hard to even imagine today what we will have discovered by 2035; maybe we will go from solving high-energy physics one year to beginning space colonization the next year; or from a major materials science breakthrough one year to true high-bandwidth brain-computer interfaces the next year. Many people will choose to live their lives in much the same way, but at least some people will probably decide to “plug in”.
Looking forward, this sounds hard to wrap our heads around. But probably living through it will feel impressive but manageable. From a relativistic perspective, the singularity happens bit by bit, and the merge happens slowly. We are climbing the long arc of exponential technological progress; it always looks vertical looking forward and flat going backwards, but it’s one smooth curve. (Think back to 2020, and what it would have sounded like to have something close to AGI by 2025, versus what the last 5 years have actually been like.)
There are serious challenges to confront along with the huge upsides. We do need to solve the safety issues, technically and societally, but then it’s critically important to widely distribute access to superintelligence given the economic implications. The best path forward might be something like:
- Solve the alignment problem, meaning that we can robustly guarantee that we get AI systems to learn and act towards what we collectively really want over the long-term (social media feeds are an example of misaligned AI; the algorithms that power those are incredible at getting you to keep scrolling and clearly understand your short-term preferences, but they do so by exploiting something in your brain that overrides your long-term preference).
- Then focus on making superintelligence cheap, widely available, and not too concentrated with any person, company, or country. Society is resilient, creative, and adapts quickly. If we can harness the collective will and wisdom of people, then although we’ll make plenty of mistakes and some things will go really wrong, we will learn and adapt quickly and be able to use this technology to get maximum upside and minimal downside. Giving users a lot of freedom, within broad bounds society has to decide on, seems very important. The sooner the world can start a conversation about what these broad bounds are and how we define collective alignment, the better.
We (the whole industry, not just OpenAI) are building a brain for the world. It will be extremely personalized and easy for everyone to use; we will be limited by good ideas. For a long time, technical people in the startup industry have made fun of “the idea guys”; people who had an idea and were looking for a team to build it. It now looks to me like they are about to have their day in the sun.
OpenAI is a lot of things now, but before anything else, we are a superintelligence research company. We have a lot of work in front of us, but most of the path in front of us is now lit, and the dark areas are receding fast. We feel extraordinarily grateful to get to do what we do.
Intelligence too cheap to meter is well within grasp. This may sound crazy to say, but if we told you back in 2020 we were going to be where we are today, it probably sounded more crazy than our current predictions about 2030.
May we scale smoothly, exponentially and uneventfully through superintelligence.
Chinese version
The Gentle Singularity
We have crossed the event horizon, and the takeoff has begun. Humanity is approaching the construction of digital superintelligence, and at least so far, none of this has looked as strange as it might seem.
Robots are not yet everywhere on the streets, and most people are not yet talking with AI all day long. Humans still die from disease, going to space remains very difficult, and our understanding of the universe is still very limited.
Even so, we have recently built systems that are smarter than humans in many ways, and these systems can significantly amplify human output. The least likely part has already been completed - the scientific breakthroughs that gave rise to systems such as GPT-4 and o3 were hard-won, but they will take us much further.
AI will contribute to the world in many ways, but the improvement in quality of life brought by AI accelerating scientific progress and boosting productivity will be enormous; the future promises to be far better than the present. Scientific progress is the greatest driver of overall progress; it is exciting to think about how much more we may be able to achieve.
In a sense, ChatGPT is already more powerful than any single person in history. Hundreds of millions of people rely on it every day, and for increasingly important tasks; a small added capability can bring enormous positive impact, while a tiny mismatch, when used by hundreds of millions of people, can also cause great negative impact.
In 2025, we welcomed intelligent agents capable of truly doing cognitive work; the way computer code is written will be completely transformed. In 2026, we will likely see systems capable of generating original insights. In 2027, robots capable of performing tasks in the real world may appear.
More people will be able to create software and art. But the world's demand for both will also rise substantially. Experts who embrace these new tools may still be far stronger than novices. Overall, in 2030 one person will accomplish far more than in 2020, this change will be remarkable, and many people will learn how to benefit from it.
In the most important respects, the 2030s may not change too drastically. People will still love their families, unleash creativity, play games, and swim in lakes.
But in other respects that are still very important, the 2030s will likely be very different from any previous era. We do not know how high the upper limit of human intelligence is, but we are about to find out.
By the 2030s, intelligence and energy - that is, ideas and the ability to realize ideas - will become extremely abundant. These two have long been the fundamental limits on human progress; if intelligence and energy become abundant (plus good governance), in theory we can achieve anything.
Now we already live alongside astonishing digital intelligence, and after the initial shock, most people have gradually grown accustomed to it. We will soon move from marveling that AI can write beautiful paragraphs to expecting it to write complete novels; from being amazed that it can diagnose diseases to expecting it to develop cures; from being surprised that it can write small programs to hoping it can create an entire company. This is the way of the "singularity": miracles become everyday, and then become the starting point.
Scientists have already told us that their work efficiency is two to three times what it used to be. One of the most critical reasons advanced AI is so significant is that we can use it to accelerate AI research itself. We may discover new computing materials, better algorithms, and even more unknown possibilities. If we can accomplish ten years of research in one year, or even one month, the pace of progress will clearly be very different.
From now on, the tools we already have will help us discover more scientific insights and assist us in creating more advanced AI systems. Of course, this is not yet AI fully autonomously updating its own code, but it is indeed an initial form of "recursive self-improvement."
There are other self-reinforcing loops happening as well. The economic value brought by AI is driving a flywheel of infrastructure construction, with more and more resources being used to run these powerful AI systems. And robots that can make other robots (and in a sense, data centers that can build other data centers) are not far away.
If we had to manufacture the first million humanoid robots in the traditional way, but they could then take over the entire supply chain—mining and refining minerals, driving trucks, running factories, and so on—and manufacture more robots, chip factories, and data centers, the pace of progress would be completely different.
As data center production gradually becomes automated, the cost of intelligence should eventually approach the cost of electricity. (Many people care about how much energy ChatGPT uses per query; on average, each query uses about 0.34 watt-hours of electricity, roughly equivalent to an oven running for a little over a second, or an efficient light bulb being used for a few minutes. In addition, each query uses about 0.000085 gallons of water, roughly one-fifteenth of a teaspoon.)
The pace of technological progress will continue to accelerate, and humans also have a strong capacity to adapt. Although there will be difficult challenges, such as entire categories of jobs disappearing, on the other hand, the world's wealth will grow so quickly that we will have the opportunity to seriously consider new policies that were previously impossible. We may not establish a new social contract all at once, but looking back decades later, we will find that the accumulation of gradual changes brought about a tremendous transformation.
If history is any guide, we can always find new things to do, new desires to pursue, and quickly adapt to new tools (the occupational changes after the Industrial Revolution are a good example). People's expectations will rise, but their capabilities will also rise quickly along with them, and we will have better lives. We will create increasingly wonderful things for one another. Compared with AI, humans have a long-term and important advantage: we are naturally concerned about others, and about what others think and do, while we feel little emotion toward machines.
If a self-sufficient farmer from a thousand years ago saw our current lives, they would think we are doing "fake work," as if we are just entertaining ourselves, because we have abundant food and unimaginable luxury. I hope that a thousand years from now we can also look at those jobs in the same way—thinking they are "very fake," but undoubtedly those people will consider their work extremely important and fulfilling.
A large number of new miracles will emerge in the future. It is hard to imagine now what breakthroughs we will achieve by 2035; perhaps this year we are still solving high-energy physics problems, and next year we begin space colonization; or this year we make a major breakthrough in materials science, and next year we achieve truly high-bandwidth brain-computer interfaces. Many people will choose to continue living in the current way, but there will certainly also be people who choose to "connect to the system."
Looking to the future, these things sound unimaginable now. But when actually experiencing them, they may be astonishing, yet still within controllable bounds. From a relativistic perspective, the singularity happens little by little, and integration proceeds gradually. We are climbing that long arc of exponential technological growth; looking forward it always feels like a steep vertical, while looking backward it seems like a gentle line, but in fact it is a smooth curve. (Think back to 2020: if we had said then that 2025 would be close to AGI, it would have sounded crazy, but compared with everything that has happened over the past five years, perhaps current predictions are not so crazy now.)
Of course, we still face many severe challenges. We need to solve safety issues technologically and socially, but after that, the most important thing is to ensure that superintelligence can be widely accessed, because this concerns the economic structure. The best path for the future may include the following steps:
First solve the "alignment problem," that is, we can be confident that AI systems will learn and realize our collective true will over the long term (for example, social media is an example of alignment failure: recommendation algorithms are very good at keeping you scrolling, but they suppress your long-term goals by exploiting the brain's short-term preferences).
Next, focus on making superintelligence cheap, widespread, and avoiding it being highly concentrated in the hands of a single individual, company, or country. Society is resilient, creative, and able to adapt quickly.
If we can inspire collective will and wisdom, then although mistakes will be made and things will get out of control, we will learn and adjust quickly, thereby maximizing benefits and minimizing risks. Within a framework broadly set by society, giving users more freedom will be very critical. The sooner the world begins discussing these frameworks and how "collective alignment" is defined, the better.
We (the entire industry, not just OpenAI) are building a "brain" for the world.
This brain will be highly personalized and easy for everyone to use; its limits will depend on our good ideas. For a long time, the tech community has loved to mock "idea-only people"—they have an idea, but cannot implement it. Now, it seems their time has finally come.
OpenAI does many things today, but its most fundamental identity is still a superintelligence research company. We still have a lot of work to do, but the road ahead has already been illuminated, and the darkness is rapidly receding. We are immensely grateful to be able to do these things.
"Intelligence is almost free" is already near at hand. It may sound crazy, but if we had told you in 2020 that we would reach the current level in 2025, it would sound crazier than our current predictions for 2030.
May we smoothly, exponentially, and steadily enter the era of superintelligence.
Original link:the-gentle-singularity