Superintelligence for Everyone. Compute for Those Who Can Afford It.

Mark Zuckerberg wants to democratize superintelligence through personal AI and open models. But if intelligence depends on scarce computational infrastructure, the real question may not be who has access to AI. It may be who can afford enough of it to matter.

Jason Koebler at 404 Media did not exactly approach Mark Zuckerberg’s latest manifesto with kid gloves. His August 10 article, “Mark Zuckerberg Posts Deranged 6,500-Word Essay About Giving Everyone AI Superintelligence,” is biting, skeptical and frequently very funny. It portrays Zuckerberg’s vision as another Silicon Valley utopia in which technological abundance somehow smooths over the inconvenient realities of human behavior, economic inequality and corporate self-interest. That criticism is deliberately sharpened to a point, but beneath the bite are questions that deserve considerably more attention. 404 Media is right to notice that Zuckerberg’s vision of “superintelligence for everyone” contains a tension between universal access and unequal power. The more seriously we take Zuckerberg’s proposal, the more important that tension becomes.

Because Zuckerberg did not simply publish a product announcement. In his essay, “The Future Is for Everyone,” he attempts something considerably more ambitious: a political philosophy for the age of superintelligence. His central argument is that advanced intelligence should not be concentrated in a handful of corporations, governments or AI systems. Instead, superintelligence should be broadly distributed to individuals, with personal AI agents aligned to the goals and values of the people using them. Rather than attempting to construct one universally benevolent superintelligence, Zuckerberg argues that many differently aligned superintelligences should coexist, compete and check one another, somewhat as individuals, businesses and institutions balance each other in a democratic society.

It is easy to mock the optimism embedded in that vision. It is harder, and more useful, to confront the possibility that Zuckerberg has identified a real weakness in the conventional alignment debate.

What if there is no single human alignment?

For years, one of the defining questions of advanced AI has been alignment: how do we ensure an increasingly capable artificial intelligence continues to serve human interests rather than developing goals that conflict with them? Zuckerberg challenges one assumption buried inside that question. Humanity does not have one set of interests. We disagree about politics, economics, morality, religion, culture, risk, freedom and even what constitutes a good life. A single superintelligence supposedly “aligned with humanity” would therefore have to decide whose version of humanity it was aligned with. Zuckerberg proposes replacing that centralized model with something more pluralistic. Your AI should be aligned with you. My AI should be aligned with me. Businesses, institutions and other people would possess their own systems, and those competing systems would create checks and balances rather than allowing any single superintelligence to become overwhelmingly dominant.

There is something attractive about this. Imagine a world in which a person without wealth or institutional connections suddenly has access to an extraordinary teacher, researcher, business strategist, programmer, medical advocate and legal assistant. Zuckerberg uses a legal thought experiment: if only one party in a courtroom possessed a superintelligent lawyer, that party would enjoy an enormous advantage, but if everyone possessed one, the imbalance might shrink. He applies similar reasoning to cybersecurity and business competition. Rather than preventing powerful intelligence from reaching ordinary people because it might be dangerous, distribute powerful intelligence broadly enough that no single actor can dominate everyone else with it.

That may be one of the most important arguments in Zuckerberg’s essay. It also contains what may be its most important weakness.

Because having access to the same intelligence does not mean having access to the same amount of intelligence.

The model is not the whole machine

Much of today’s AI debate is framed around models. Which models are open? Which are proprietary? Who controls the weights? Can individuals run them locally? Should frontier models be released or restricted? Those are important questions, and Zuckerberg strongly argues for open-source AI as a counterweight to centralized control. Meta says it plans to resume releasing some open-source models, and Zuckerberg argues that broad access to powerful models would strengthen individuals relative to large institutions.

But an AI model is not intelligence floating freely in the air. It must run somewhere.

It needs processors, memory, networking, electricity, cooling systems and enormous physical infrastructure. At smaller scales, individuals may be able to run increasingly capable models on personal hardware. But the capabilities Zuckerberg is describing eventually move into another category entirely. In his own discussion of recursive self-improvement, he imagines AI systems directing substantial compute toward improving themselves and even speculates about systems finding ways to extract radically greater intelligence from each gigawatt. He explicitly warns that a system controlling enough effective compute could achieve a decisive balance-of-power advantage over everyone else.

That observation quietly changes the entire conversation.

If computational resources determine how much work an AI can perform, how many agents can operate simultaneously, how long they can reason, how many experiments they can conduct and how rapidly they can improve, then the important inequality of the superintelligence era may not simply be access to models. It may be access to compute.

And Zuckerberg’s own proposal acknowledges this scarcity. Meta says it intends to provide free versions of personal superintelligence to billions of people. But Zuckerberg also says users who want additional compute would be able to purchase it through a “dynamic auction mechanism.” In other words, the future he describes contains both universal access and a market for greater quantities of computational intelligence.

That is where 404 Media’s skepticism begins to bite into something substantial.

Everyone may have superintelligence. Not everyone will have the same superintelligence.

Imagine that two people possess access to exactly the same open model. One runs it occasionally on inexpensive hardware or purchases a modest amount of cloud compute. Another commands thousands of accelerators, enormous energy capacity, proprietary data, specialized infrastructure and enough capital to operate millions of agents continuously. Technically, both possess access to the same underlying intelligence. Functionally, they inhabit radically different positions of power.

Now replace that second person with a multinational corporation.

Or a hedge fund.

Or a military.

Or a government.

Or Meta itself.

The distinction matters because advanced AI increasingly converts compute into action. More compute can mean more research paths explored simultaneously, more strategies tested, more software written, more markets analyzed, more scientific hypotheses investigated and more autonomous agents working at once. Zuckerberg himself argues that finite compute creates an opportunity cost and that societies will have to decide where that resource produces the most value. He also argues that defenders such as governments and law enforcement may need more compute than malicious actors in order to maintain the balance of power. The essay therefore treats compute not merely as plumbing beneath AI but as a resource directly connected to capability and power.

This raises a possibility that deserves far more attention in the discussion about democratizing AI: the future may not be divided primarily between people who have artificial intelligence and people who do not. It may be divided between those who rent intelligence and those who own the infrastructure that produces it.

The internet offers a useful precedent. Almost everyone can access the web, but that did not mean everyone acquired equal power over the digital economy. Enormous value accumulated around infrastructure, platforms, distribution networks, cloud computing, advertising systems and data. AI may push this pattern considerably further because the scarce infrastructure is no longer merely storing or transmitting information. It is performing cognition.

An open model can democratize access to intelligence while the physical infrastructure required to operate intelligence at massive scale remains extraordinarily concentrated.

In that world, the interface has been democratized.

Power may not have been.

Compute becomes part of the alignment problem

This is where the questions of compute and alignment collide.

Zuckerberg proposes that billions of personal agents aligned with different people could check and balance one another. But a balance-of-power system depends on something resembling a balance of power. If one participant commands vastly greater computational resources than another, the theoretical symmetry disappears. The personal AI representing an individual might be extraordinarily intelligent, yet still find itself negotiating, litigating, competing or defending against institutional systems backed by computational resources many orders of magnitude larger.

The courtroom example illustrates the problem. Imagine everyone receives the same brilliant AI lawyer. At first glance, the inequality has disappeared. But suppose one litigant can afford one instance of that lawyer while another can deploy ten thousand copies, continuously simulate every possible legal strategy, analyze every previous ruling, model the judge, research every witness, construct thousands of possible arguments and revise its strategy around the clock. Everyone still “has the lawyer.” Yet resources have recreated the imbalance Zuckerberg’s thought experiment was supposed to eliminate.

The same problem becomes far more serious in markets, cybersecurity, scientific discovery and geopolitical competition.

This does not mean Zuckerberg’s decentralized alignment model is wrong. In fact, it may contain an important insight. A civilization containing many independently aligned AI systems could prove more resilient than one dominated by a single intelligence or a handful of centralized systems. Open models may genuinely become one of the strongest defenses against monopolization. Personal AI could dramatically expand individual agency. Those possibilities deserve serious consideration.

But distributed models alone do not guarantee distributed power.

We may also need to think about compute sovereignty: who owns the computational infrastructure, who controls access to it, how pricing works, who receives priority during shortages, what individuals can operate independently, and how much intelligence can ultimately be purchased by those with the deepest pockets.

There is a business model hiding inside the philosophy

None of this requires assuming sinister motives on Meta’s part. The more interesting observation is that Zuckerberg’s political philosophy and Meta’s economic interests may fit together remarkably well.

Meta is simultaneously advocating personal superintelligence, open-source models, enormous AI infrastructure expansion and broad access to advanced intelligence. Zuckerberg explicitly describes a future in which billions receive free AI capability while users who need additional compute can purchase more. Meta has also made enormous investments in data centers, silicon, energy and other infrastructure needed to support advanced AI, publicly describing that infrastructure as essential to delivering personal superintelligence at global scale.

There is nothing inherently contradictory about that. Companies build infrastructure and sell access to it throughout the economy. But when the commodity being allocated is intelligence itself, the implications become considerably larger.

Imagine intelligence becoming something closer to a utility. Everyone receives a baseline amount. Individuals and businesses purchase more when they need it. Markets determine the price of additional cognitive capacity. Companies compete to provide processors, energy, inference, agents and specialized intelligence. A small business buys enough AI capacity to compete with a larger company. A pharmaceutical company purchases enormous amounts to search chemical space. A government reserves massive capacity for defense. Financial institutions deploy staggering quantities against markets.

Suddenly the phrase “superintelligence for everyone” requires a footnote:

How much?

And who decides the price?

The organizations operating the infrastructure may occupy a position unlike anything created by previous information technologies. They would not simply host websites, distribute media or store databases. They would meter access to cognition.

The real AI divide may be computational

The first digital divide concerned access to computers. The next concerned access to the internet. AI introduces another possibility: a computational divide measured not simply by whether someone can use an intelligent system, but by how much intelligence they can command.

This distinction becomes even more important if advanced agents begin operating continuously. A human can only work so many hours. An AI system might operate thousands or millions of parallel processes without sleep. Once cognition can be duplicated, speeded up and multiplied, wealth can potentially purchase something humanity has never before been able to purchase directly: additional thinking capacity.

Capital has always purchased human labor. Capital may soon purchase cognition itself.

That has implications far beyond Meta. Amazon, Microsoft, Google, Oracle, specialized GPU clouds, national governments and future compute providers may all participate in a market where increasingly capable intelligence is metered as infrastructure. Open models could flourish in that environment and still coexist with extraordinary concentration of computational power.

This is why the debate over open versus closed AI, while important, may not go deep enough. Open weights can reduce one form of centralized control while leaving another largely untouched.

You can own the blueprint.

Someone else can still own the factory.

Zuckerberg may be asking the right question, but not the whole question

404 Media deserves credit for refusing to accept a corporate utopia simply because it is wrapped in the language of empowerment. Koebler’s article is intentionally caustic, and readers may disagree with some of its punches, but the skepticism serves an important purpose. Zuckerberg is describing a future in which Meta’s technological strategy, economic interests and preferred philosophy of AI governance align remarkably well. That does not make the philosophy false. It makes scrutiny essential.

And there is real substance in Zuckerberg’s proposal. He is asking one of the defining political questions of the AI age: should superintelligence be concentrated or distributed? His answer is unequivocal. Distribute it. Give individuals powerful agents. Encourage open models. Allow different intelligences aligned to different people to compete and balance one another. Avoid allowing any corporation, government or AI system to become the singular center of intelligence.

That may prove to be an important part of the answer.

But there is another question sitting directly underneath it:

Who owns the compute?

Because if superintelligence becomes abundant while the infrastructure required to operate it remains scarce, the battle over AI power will simply move down the stack. The model may be open. The agent may be yours. Its values may be aligned with yours. But the chips, electricity, data centers and computational capacity determining how much intelligence you can actually wield may belong to somebody else.

Perhaps Zuckerberg is right that the safest future is one in which everyone has superintelligence.

But if intelligence becomes something we rent by the gigawatt, then democratizing the model will only be the beginning.

The next alignment problem will not simply be aligning machines with people.

It will be aligning the economics of intelligence with the society we actually want to build.

Source and further reading: This article was prompted by Jason Koebler’s sharply critical August 10, 2026 piece for 404 Media, “Mark Zuckerberg Posts Deranged 6,500-Word Essay About Giving Everyone AI Superintelligence.” Zuckerberg’s original essay, “The Future Is for Everyone,” was published by Meta the same day.