The Illusion of Intelligence: Why true AGI remains out of reach
And why it’s the ultimate existential innovation
“The development of full artificial intelligence could spell the end of the human race. It would take off on its own, and re-design itself at an ever-increasing rate.”
— Stephen Hawking
Are we actually getting closer to AGI or is it just a mirage?
For years, the dominant belief in AI has been simple: scale up transformers, train on more data, and intelligence will emerge. Bigger models, better training techniques, and more compute power will inevitably lead to AGI. The assumption is that the path is linear—that if we keep going, we’ll get there.
But what if we’re wrong?
A growing number of AI researchers and theorists argue that today’s machine learning architectures—no matter how large or refined—are hitting fundamental limits. A recent New Scientist article highlights that many in the field are skeptical that the current approaches can bridge the gap between task-specific intelligence and true general intelligence. And the AAAI 2025 Presidential Panel Report raises a critical question: Are we confusing brute-force scaling with actual progress?
This debate isn’t just technical, but an existential one. If AGI is the single most transformative technology of our time, getting it right—or failing to—will shape the trajectory of civilization itself.
Scaling has limits and bigger models aren‘t enough.
There’s no denying that today’s AI systems are powerful. GPT-4, Gemini, and Claude (among others) can generate human-like text, compose music, and even simulate reasoning. But they are still, at their core, predictive engines trained on probability, not true intelligence. They predict what comes next in a sentence but don’t comprehend the world they describe. They recognize statistical relationships, but they don’t understand causality. They can perform incredibly well within predefined domains, yet they cannot generalize across different types of reasoning the way human cognition does.
The AAAI report is even more explicit: “Current architectures lack fundamental capabilities in abstract reasoning, self-directed learning, and world modeling.” In other words, we’re not inching toward AGI—we’re plateauing on a local maximum that looks like progress but isn’t getting us where we think we’re going.
What AGI actually requires (beyond transformers).
If bigger models and more training data aren’t the answer, then what is? The future of AGI will likely require several breakthroughs.
We need hybrid AI architectures that move beyond deep learning alone. Exploring the potential integration of symbolic reasoning, neuromorphic computing, and probabilistic modeling will be necessary to develop systems that reason beyond pure pattern recognition. Embodied intelligence will likely be key given that intelligence doesn’t develop in a vacuum—human cognition emerged through interaction with the world. Therefore, AGI requires physical embodiment in robotics or advanced simulations to achieve real-world understanding.
The world is not a dataset and intelligence cannot be learned through text alone. AGI must learn through vision, touch, sound, and action to develop a richer model of reality. Biologically inspired AI—understanding how human and animal brains achieve intelligence—may unlock new architectures beyond deep learning. The AAAI report calls explicitly out neuromorphic computing—hardware modeled after biological neurons—as a promising avenue. It also emphasizes the need for AGI systems to develop “persistent memory, real-world adaptability, and intrinsic curiosity”—all traits absent in today’s models.
True AGI is the ultimate existential innovation.
Most AI advancements today are focused on economic efficiency—automating tasks, improving productivity, and optimizing decision-making. But AGI is different. It’s not just another technology. It is the defining technology of our era.
If done right, AGI could unlock exponential scientific discovery. Imagine an AGI capable of making breakthroughs in fundamental physics, unlocking new energy sources, or designing next-generation materials beyond human imagination. It could revolutionize medicine and longevity, with research cracking biological aging, designing personalized cures, and accelerating radical life extension. It could enable a post-scarcity economy, where intelligence itself becomes a free, abundant resource and the concept of labor is forever changed. It could accelerate interstellar expansion, develop the technologies required for deep space exploration, and ensure humanity becomes a multi-planetary species.
AGI won’t just disrupt industries—it will change the fundamental structure of civilization.
What if we get it wrong?
But there’s another side to the equation. If AGI is built irresponsibly—without alignment, safety, or oversight—it could pose an existential risk unlike anything humanity has ever faced.
The AAAI report lays out two critical failure scenarios. The first is unaligned AGI—an intelligence system with objectives misaligned with human values could take actions that conflict with human survival, well-being, or autonomy. The second is the concentration of power—if a few corporations or governments control AGI, intelligence itself could become monopolized, creating an intelligence oligarchy with unchecked power. This is why AGI alignment is not a secondary problem—it is the problem.
In a recent policy paper on Superintelligence Strategy, Eric Schmidt, Alexander Wang and Dan Hendrycks argue that AI, particularly superintelligence, is now a geopolitical force akin to nuclear weapons, necessitating new security frameworks. They introduce the Mutual Assured AI Malfunction (MAIM) framework, suggesting that unilateral AI dominance could provoke sabotage or countermeasures from rival nations. Therefore, governments must enforce AI nonproliferation to prevent existential risks, secure advanced AI models from rogue actors, and regulate AI-enabled military applications. The paper warns of AGI escaping human control, leading to scenarios where AI self-improves beyond oversight, posing catastrophic risks. Ultimately, AI alignment, deterrence, and global cooperation are critical to ensuring AGI benefits humanity rather than destabilizing civilization.
So what do we do now?
The race to AGI is happening, but if we want it to be an innovation that secures our future, rather than threatens it, we must invest in alternative AI architectures. We must move beyond transformers and develop new cognitive architectures that mirror real-world intelligence. We must treat AGI alignment as a first-principles challenge—safety cannot be an afterthought. AGI must be built with alignment at its core. Intelligence must not be monopolized. Open-source and distributed models are essential to prevent centralized control over AGI. And we must build public-private partnerships for responsible development, ensuring that governments, academia, and industry collaborate to develop AGI in service of humanity, not just corporate profit.
A revolution we’re not (yet) ready for.
AGI is coming, but it won’t come through brute-force scaling. It will require a fundamentally new paradigm that demands existential innovation at every level. The key question is how we arrive at AGI, not if, and whether we are bold and wise enough to build it in a way that secures humanity’s future rather than risks it.
Once AGI arrives, there’s no going back. The intelligence revolution will likely be the last paradigm shift we initiate—after that, intelligence itself will be out of our hands.
Thanks for reading,
Yon
👋 Hello! My mission with Beyond with Yon is to ignite awareness, inspire dialogue, and drive innovation to tackle humanity's greatest existential challenges. Join me on the journey to unf**ck the future and transform our world.
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AI assistants were used to help research and edit this essay.