In recent years, Artificial General Intelligence (AGI) has been attributed almost mythical powers: some believe it will cure diseases, save the planet, and usher in an era of human prosperity; others warn it could lead to ultimate disaster and the end of civilization. Whether viewed as a utopia or a doomsday scenario, AGI has become a dominant narrative, influencing capital flows, technology policies, and public imagination.

But as we peel back these layers of narrative, we must ask: what we are fervently following is a definitive technological future or a carefully woven modern myth? Increasing signs suggest that the collective fervor surrounding AGI has taken on characteristics similar to conspiracy theories—one of the most “advanced” conspiracy theories of our time.

How Silicon Valley Was “Brainwashed” by AGI

As early as 2007, artificial intelligence was far from the glamorous field it is today. Amazon and Netflix had already ventured into machine learning, but it was merely to recommend books and movies.

However, Ben Goertzel was not satisfied with this. About a decade ago, this AI researcher founded a startup called “Webmind,” attempting to cultivate what he envisioned as a “digital baby brain” in the early internet environment. Unfortunately, due to a lack of funding, the company quickly went bankrupt.

Goertzel is a central figure in a niche tech circle where researchers have long dreamed of creating intelligence that could think like humans or even better. However, he needed a catchy name to distinguish it from the somewhat mundane term “artificial intelligence.”

At that time, Webmind employee Shane Legg proposed the term “AGI” (Artificial General Intelligence). It sounded a bit far-fetched but was nonetheless accurate. Goertzel decided that was the name.

Years later, Legg co-founded DeepMind with Demis Hassabis and Mustafa Suleyman, also rooted in the AGI field.

However, to most serious researchers at the time, the assertion that AI would eventually mimic human capabilities was merely a joke. So what happened? How did AGI evolve from absurdity to widespread recognition in just over a decade?

Last month, I interviewed Goertzel and posed my questions. He said, “I consider myself a researcher of complex chaotic systems, so I hold a conservative view on truly understanding the nonlinear dynamics of memory space.” (In simpler terms: it’s complicated, and I can’t say for sure.)

Goertzel believes several factors helped promote this idea.

First, the AGI conferences—these are often held alongside top mainstream academic gatherings, such as the annual meeting of the Association for the Advancement of Science, AI conferences, and the International Joint Conference on Artificial Intelligence.

“If I had just published a book titled ‘AGI,’ it might have quietly faded away,” Goertzel remarked, “but the conferences are held annually, attracting more and more students to participate.”

“Secondly, we owe thanks to Legg, who brought the term AGI to DeepMind. I believe they were the first company in the mainstream business world to discuss AGI. Although it was not a core topic they emphasized repeatedly, it undoubtedly provided legitimacy to the field.”

“When I first discussed AGI with Legg five years ago, he candidly admitted that talking about AGI in the early 2000s would have been seen as crazy… Even when DeepMind was founded in 2010, we still faced a lot of skepticism at conferences. But by 2020, the winds had changed. Although some still felt uneasy about it, it was gradually coming out of the shadows.”

Goertzel pointed out a third factor: the intersection between early AGI advocates and the power brokers of tech giants. Goertzel had collaborated with PayPal founder Peter Thiel. “We talked a lot,” Goertzel recalled. He remembers spending an entire day with Thiel at the Four Seasons Hotel in San Francisco. “I was trying desperately to instill the AGI idea in him.”

At that time, Goertzel was unaware that he was not “fighting alone.” Another person was also pushing the AGI wave forward.

The Arrival of Doomsayers

This person is Eliezer Yudkowsky, whose contributions to promoting the AGI concept are at least as significant as Goertzel’s, and possibly more prominent. However, unlike Goertzel’s optimistic vision of AGI, Yudkowsky believes AGI will only lead humanity to disaster.

Initially, Yudkowsky’s views did not attract widespread attention. At that time, AI was still purely a science fiction concept. It wasn’t until 2014, when Oxford philosopher Nick Bostrom published “Superintelligence,” that the concept of AGI became widely known.

Many tech industry figures, including Bill Gates and Elon Musk, read this book and were influenced by it. Regardless of whether they agreed with his pessimistic doomsday scenario, Bostrom effectively systematized Yudkowsky’s ideas in a compelling manner.

“All of this helped AGI gain publicity,” Goertzel added, “it was no longer an abstract or absurd concept.”

Today, Yudkowsky’s views are more popular than ever. This has attracted young doomsayers like David Krueger, a researcher at the University of Montreal.

“I believe we are steadily heading towards creating a superhuman AI system that will kill everyone,” Krueger stated, “we must stop it immediately.”

The media has also begun to report on this, and Yudkowsky was even dubbed the “Silicon Valley doomsday preacher” by The New York Times.

He seized the momentum and co-authored a new book with Nate Soares, director of the Machine Intelligence Research Institute, titled “If Anyone Builds It, Everyone Dies,” which presents a series of shocking claims lacking evidence: that near-future AGI will trigger global catastrophe.

The two hold extreme positions: they advocate for an international ban at all costs, even resorting to nuclear retaliation if necessary. After all, Yudkowsky and Soares wrote, “the death toll from data centers could exceed that of nuclear weapons.”

Upon its release, the book topped The New York Times bestseller list and received endorsements from numerous influential figures, including many American politicians, scientists, and social elites. AGI began to attract significant social attention, with capital and policies starting to bet on it.

In 2023, OpenAI CEO Sam Altman posted on X, “In my view, Eliezer’s contributions to accelerating AGI development far exceed anyone else’s. Undoubtedly, he has sparked interest in AGI for many people.” Altman added that Yudkowsky might one day receive a Nobel Peace Prize for this.

The impact of all this seems to contradict Yudkowsky’s ideas. But whether he accepts it or not, AGI has quietly penetrated the mainstream and firmly taken root.

But What Is AGI? No One Knows

In 1945, just five years after the first electronic computer ENIAC was born, Alan Turing posed the famous question: “Can machines think?” Soon after, in 1951, he stated more plainly in a radio program: “Once machines learn to think, they will quickly surpass our limited capabilities. Machines won’t die, and they can communicate with each other and evolve continuously. So one day, we must be ready to hand over control to them.”

Ten years later, in 1955, computer scientist John McCarthy and his colleagues applied for funding from the U.S. government to undertake a project they foresightedly named “artificial intelligence.”

This naming seemed almost fantastical at the time—after all, computers were still as bulky as rooms and functioned similarly to thermostats. However, McCarthy wrote in the proposal, “We will explore how to enable machines to use language, form abstract concepts, solve problems that only humans can solve, and achieve self-evolution.”

It is these early predictions that planted the seeds of today’s AGI myth. The notion of machines that are smarter and capable of everything is less a technical goal and more a fantasy detached from reality.

Because despite massive investments and endless debates, no one truly knows how to create AGI.

What’s more troubling is that most people lack consensus on what it actually is—this explains why some can simultaneously claim it will save the world while others assert it will destroy humanity without feeling contradictory.

Most definitions revolve around the same core idea: machines achieving human-level performance across a wide range of cognitive tasks. But this definition itself is untenable: which humans? Which cognitive tasks? How broad is “broad”?

“It has no precise definition,” pointed out Christopher Simmons, former head of the computer department at Oak Ridge National Laboratory. “If we use human-level as a benchmark—intelligence itself has countless possibilities, and everyone’s intelligence varies.”

Simmons believes we are thus caught in a strange race: what exactly do we want to create? “What do you really want it to do?”

In 2023, the Google DeepMind team (including Legg, who participated in naming) attempted to sort out various definitions of AGI. Some believe it must be able to learn; others emphasize it must create economic value; still, others insist it must have a physical body to operate in the real world (like making coffee).

Legg told me that when he proposed using the term for the book title, ambiguity was key. “I didn’t have a particularly clear definition at the time and didn’t think it was necessary to define it,” he said. “In fact—it’s not like a specific thing; it’s more like a research field.”

So, when it finally appears, we will naturally know? The problem is, some believe AGI has already arrived.

In 2023, a Microsoft research team published a paper describing their testing experience with a pre-release version of OpenAI’s large language model GPT-4. The team referred to it as “the spark of AGI”—this assertion sparked intense debate in the industry. At the time, many researchers were shocked and tried to use existing theoretical frameworks to explain the observed phenomena.

“This thing performed better than we expected,” Goertzel said, “AGI seems no longer so unattainable.” Nevertheless, Goertzel still believes that while large language models exhibit exceptional text processing capabilities, they have not truly touched the core of general intelligence.

“What surprised me is that some technical experts with a deep understanding of the underlying mechanisms of these tools still believe they could potentially develop into human-level AGI,” he said. “But on the other hand, you really can’t completely deny that possibility.”

The fact is: you cannot prove it impossible. Everyone is also guessing when it will be realized—5 years? 10 years? 25 years? No one knows.

This resembles conspiracy theories. Because predictions about when AGI will arrive are as accurate as astrologers predicting the end of the world. Such predictions bear no actual consequences; the excuses are constantly refreshed, and the timelines are continuously reset.

This summer’s much-anticipated GPT-5 is the best example.

However, this has not been seen as evidence that AGI cannot be achieved—the believers simply keep postponing their predictions. It will always come—just, you know, always “next time.”

Believe It or Not

Whenever I talk to those researchers or engineers, they casually discuss AGI as if it were a given fact, as if they possess some secret I do not know. Yet no one can truly tell me what that secret is.

The truth is out there; you just need to know where to look. Jeremy Cohen once told me that the core of conspiracy theories is “revealing hidden truths”: “This is indeed a fundamental characteristic of conspiracy thinking, and we can clearly see this trait in discussions about AGI.”

Last year, 23-year-old former OpenAI employee and current investor Leopold Aschenbrenner published a widely discussed 165-page manifesto titled “Situational Awareness.”

You could grasp its core idea without even reading the entire text: you either see the impending truth or remain forever in ignorance.

This cognition does not even require cold hard facts to support it—intuitive perception is sufficient. And those who have not yet “awakened” are merely those who have not grasped the essence of it.

Similar views also subtly permeated my conversation with Goertzel. When I asked him why some people are skeptical about AGI, he responded: “Throughout history, every significant technological breakthrough—from human flight to the widespread use of electricity—has had many smart critics asserting it was impossible. The fact is, most people only want to believe what they have seen with their own eyes.”

This makes AGI sound more like a belief system. I shared this perspective with AI researcher David Krueger, who firmly believes AGI could arrive within five years. He dismissively replied, “I think that’s completely backward.”

In his view, the true “faith” lies in believing AGI will not be realized—those who still deny the “obvious” truth are the truly deluded.

The hidden truth attracts self-proclaimed “truth seekers” who are obsessed with revealing what they believe has always existed but remains unseen. However, for AGI, merely “revealing” is far from enough. It also requires an unprecedented act of creation, which is a crucial reason for its allure.

“The notion of believing one is nurturing a ‘machine god’ clearly satisfies certain people’s egos,” Shannon Vallor pointed out. “Imagining oneself laying the groundwork for such a transcendent being—this idea has a compelling allure.”

This overlaps with conspiracy thinking. People crave a sense of value in their existence in a seemingly chaotic and meaningless world—a desire to be the crucial figure who can change everything.

Krueger, who conducts research in Berkeley, mentioned he knows some people working in AI who view these technologies as humanity’s natural successors. “They regard these technologies almost like their children,” he said, “By the way, these people usually do not have children.”

A New Spiritual Utopia

Jeremy Cohen found that many modern conspiracy theories bear similarities to the New Age movement, which peaked in the 1970s and 80s.

Believers in this movement firmly believed humanity stood on the threshold of a new era of spiritual well-being, believing that expanded consciousness would lead the world into a more peaceful and prosperous phase. In simple terms, its core belief is that through a series of pseudo-religious practices—such as astrology and carefully selected crystals—humanity can transcend its limitations and enter a kind of “hippie-style” utopia.

Today’s tech industry, while built on computation and algorithms rather than crystals or zodiac signs, exhibits a similar mystical quality in its understanding of certain fundamental propositions. “You know, that kind of imagination about a complete transformation—it’s as if we are about to witness some millennial turning point, ultimately stepping into a future of technological utopia,” Cohen pointed out. “The belief that AGI will help humanity overcome all dilemmas is precisely a manifestation of this core imagination.”

In many people’s minds, the arrival of AGI will be sudden. The gradual development of AI will accumulate until one day, its capabilities become so powerful that it can autonomously create even more powerful artificial intelligence. At that point—it will evolve at an astonishing speed, achieving AGI breakthroughs through what is known as an “intelligence explosion,” ultimately reaching an irreversible critical point, referred to as the “singularity.” This special term has circulated in AGI circles for many years and is still widely used.

Science fiction writer Vernor Vinge was the first to borrow the concept of “singularity” from physics to describe this theoretical threshold in technological development. As early as the 1980s, he proposed that there exists an “event horizon” on the path of technological progress—once crossed, humanity will be rapidly surpassed by machines that it has created, evolving at an exponential rate.

Shannon Vallor believes the most significant characteristic of this belief system is that faith in technology has replaced faith in humanity itself. She pointed out that although the ideas of the New Age movement carry mystical overtones, they at least retain a belief that humanity can change the world by unleashing its potential. However, in the pursuit of AGI, we are abandoning this belief in “humanity” in favor of the notion that “only technology can save humanity.”

For many, this idea is highly attractive, even comforting. “We are in an era where other avenues for human life and social material progress seem to have been exhausted.”

Technology was once seen as the ladder to a better future—steadily leading humanity toward social prosperity. But Vallor noted, “We have crossed that peak. Nowadays, it seems that the only thing that can reignite hope and restore optimism about the future for many is AGI.”

She further stated that if this logic is pushed to the extreme, AGI could ultimately be shaped into some kind of “deity”—a being believed to bring ultimate relief from all worldly suffering.

Sociologist Kelly Joyce at the University of North Carolina primarily studies how cultural, political, and economic beliefs influence people’s understanding and use of technology. In her view, all the fervent predictions about AGI are merely another manifestation of the long-standing “overcommitment model” in the tech industry. She said, “Interestingly, we always fall into this trap. People seem to always believe technology is superior to humanity.”

Joyce believes this is why, whenever hype arises, people tend to believe it. “It’s like a religion,” she said, “We believe in technology. Technology is our god. It is very difficult to resist this notion—because people simply do not want to hear otherwise.”

The Cost Behind the Final Fantasy

The fantasy that “computers will eventually be able to perform all human tasks” is undoubtedly alluring. But like many widely circulated conspiracy theories, this fantasy brings real and heavy consequences.

It distorts our understanding of the true costs behind the current technological boom (and its potential decline), and it may even lead the entire industry astray—drawing resources away from more urgent and pragmatic technological applications. More critically, it allows us to escape with a clear conscience. It lures us into believing that perhaps we can skip over the challenges that require global cooperation, political compromise, and high costs, whether it be the climate crisis, public health, or systemic inequality. Since machines will soon solve everything for us, why should we bother?

The costs of this development are rarely questioned.

Look at the resources invested in this gamble. Recently, OpenAI and NVIDIA announced a collaboration worth up to $100 billion, with the expectation that running models like ChatGPT will require at least 10 gigawatts of power—equivalent to the output of a large nuclear power plant. The energy released by a lightning bolt might not even compare.

For reference, the “flux capacitor” that powers the DeLorean time machine in the movie “Back to the Future” requires about 1.2 kilowatt-hours. Just two weeks later, OpenAI reached another collaboration with AMD, adding thousands of megawatts of power demand.

While promoting the NVIDIA deal, Sam Altman stated that without building more data centers, society would have to make a brutal choice between “curing cancer” and “providing free education.” “No one wants to face such a choice,” he said. (Ironically, just weeks later, OpenAI announced it would launch an adult content generation feature for ChatGPT.) More disturbingly, this pursuit of a distant myth is crowding out investments in technologies that could genuinely improve current lives.

“In my view, this is a massive missed opportunity,” said Christopher Simmons, chief AI scientist at AI healthcare company Lirio. “This is a severe misallocation of resources. There are countless real and urgent problems that need solving, yet we are pouring vast amounts of money into a vaguely defined, uncertain goal.”

“But when companies like OpenAI hold billions in funding, they actually do not have to make pragmatic choices,” Simmons added. “The scale of capital itself is enough to detach them from the gravitational pull of real needs.”

This distorted narrative is also seeping into the policy realm. Tina Law, a technology policy researcher at the University of California, Davis, worries that policymakers are being swayed by lobbying forces, overly focusing on the distant hypothetical of “AI will eventually destroy humanity” while neglecting the real dangers of algorithmic bias, labor displacement, and surveillance expansion. The grand debate over “existential risk” marginalizes pressing issues like structural inequality and the digital divide.

“Hype is a profitable business for tech companies,” Law pointedly noted. “Its core strategy is to create a narrative of ‘inevitability’: if we do not develop, others will get ahead. Once a technology is framed as a historical necessity, people not only hesitate to resist but also begin to doubt their ability to resist.”

Milton Mueller, a technology policy scholar at Georgia Tech, likened the AGI race to the nuclear arms race of the past: “It is built on a dangerous logic—whoever masters this technology first will control everyone. This mindset can completely distort our foreign policy and international relations.”

Mueller further pointed out that the enthusiasm of enterprises and even governments for promoting the AGI myth is driven by clear commercial and strategic motives. The key is that this race has no recognized finish line. As long as the myth can attract investment and attention, it can be told indefinitely.

The conclusion of the story may not be complicated. It is neither a utopia nor a hell—more likely, before reaching any so-called “singularity,” OpenAI and its peers will have made a fortune chasing the myth.

And many real problems facing the world remain.

The New “AGI” Is Still on the Way

So far, we have not discussed a most typical feature: conspiracy theories often presuppose the existence of a manipulative power group behind the scenes, and believers think that through relentless pursuit of the “truth,” they can unveil the masks of this elite class.

Of course, those wary of AGI do not openly accuse the Illuminati or the World Economic Forum of obstructing AGI’s realization or hiding its secrets.

But what if the real manipulators are not preventing AGI but are instead long-term advocates of the AGI narrative? The giants of Silicon Valley are investing massive resources, striving to develop AGI—and this is primarily a business. For them, the myth of AGI holds immense commercial and strategic value.

As a recent executive from an AI company privately revealed: “AGI must always be described as ‘6 to 12 months away from realization.’ If it seems too far away, we cannot attract talent from top institutions; but if it seems too close… how can the story continue?”

Shannon Vallor sharply pointed out: “If OpenAI openly stated they were merely building machines to make the company more profitable, the public would not buy it. You create a god, and you must become a god yourself.”

As David Krueger observed, a deep-rooted logic permeates Silicon Valley: developing artificial intelligence is the path to ultimate power (which is also one of the core arguments in Leopold Aschenbrenner’s “Situational Awareness”). “We are about to possess god-like power,” Krueger said, “but our consciousness, ethics, and institutions are not prepared. Many believe that whoever realizes AGI first will essentially control the world.”

“They invest tremendous energy in promoting a future filled with AGI, and with their influence, they have already achieved considerable success,” he added.

Ben Goertzel even expressed a sense of near-sadness over the success of this hidden group. He began to reminisce about the days when AGI was still on the fringes and went unnoticed. “We, this generation of AGI researchers, needed both vision and stubbornness—almost a kind of grit,” he said. “But now? It has become like your grandmother advising you not to study philosophy and to find a proper job instead.”

“This idea has become so mainstream that it is truly perplexing,” he admitted. “It almost makes me want to switch to something genuinely obscure—fields that have not been drowned in crowds.” He half-jokingly (I guess) said, “Clearly, wrapping up AGI is more important than satisfying my personal preference for exploring the frontier.”

But I still do not understand: what exactly are they perfecting? If we are so obsessed with this technological fairy tale, what does it mean for genuine technological development? In many ways, I believe the entire AGI concept is built on distorted expectations of artificial intelligence capabilities—even on a misunderstanding of the essence of “intelligence.”

Ultimately, the core of the AGI argument is that artificial intelligence has made rapid progress and will continue to improve. But setting aside technical doubts—what if it fails to progress?—the remaining assertion is merely that as long as we have enough data, computing power, or neural networks, intelligence can be obtained infinitely like a commodity.

But that is not the case; intelligence is not a quantifiable metric that can increase indefinitely. A wise person may excel in one field but be mediocre in others. For instance, some Nobel laureates may have poor musical or parenting skills, while some so-called “smart people” insist AGI will arrive next year.

We cannot help but ask: what will be the next myth that hooks us?

Before the call ended, Goertzel casually mentioned he had just attended an event in San Francisco, “the theme was about extrasensory perception and foreseeing the future… those things.”

“This is the situation AGI was in 20 years ago,” he said, “Back then, everyone thought this idea was simply ridiculous.”