The Industrialization of Intelligence
What happens when the cost of Intelligence falls to zero?
A Defining Moment in History
I’ve been quiet for the past year—working behind the scenes on AI’s trajectory. But my conviction has only grown stronger:
We are living through a defining moment in history.
When I first got into AI around 2016/2017, it was still a niche topic. Today, the ‘AI vibe shift’ is undeniable, and its impact is everywhere. This isn’t just a conversation for private boardrooms—it belongs in the public sphere.
So here’s my take:
We need to start thinking about intelligence as a commodity.
We need to recognize that intelligence is being industrialized.
And we need to ask: What happens when its cost goes to zero?
How I Got Here
My journey into AI wasn’t through computer science—it was always about power, people, and politics: understanding how technology reshapes global structures and shifts influence.
I was born in Nepal, a place where, during my mother’s lifetime, modern infrastructure was almost nonexistent. She grew up in a village at the foot of the Himalayas, where life hardly changed for centuries. Yet, within a generation, I—a kid from the 90s—grew up in a world transformed.
I saw firsthand how technology compressed time and space, propelling a pre-modern society into the digital age. It taught me that technology is the ultimate accelerant, breaking down barriers to opportunity, knowledge, and economic growth.
After spending a decade in geopolitics and policy—navigating economic crises, global migration, the rise of digital platforms, and shifting power structures—I realized by the early 2010s that rather than being a niche research topic, AI would become *the* driving force behind the next industrial age.
I understood that control over AI means control over the next wave of economic and political power. So I made a pivot: I left policy and government to work directly with the technologists: I advised AI labs, partnered with business leaders, and watched AI’s progress firsthand. I saw how AI is reshaping finance, science, and human creativity long before most caught on.
More importantly, I noticed that much of the debate is missing the bigger picture. The real story isn’t just about which AI model is best, or if AI is sentient … it’s about how intelligence itself is becoming a resource and what happens when it gets industrialized at scale.
Breaking Down the Big Picture: The Four Cs
Let’s break things down into what I like to call the Four Cs. Think of these as four angles to understand the AI revolution:
Concepts: What ideas are driving AI forward.
Characters: Who the key players are.
Countries: How global power struggles are unfolding.
Competition: The market race that’s pushing everything ahead.
Over the next year, I’ll dive into each of these areas—exploring new research, power dynamics, global resource battles, and the competitive pressures shaping our future.
But first, let’s set the stage with some context:
The Industrialization of Intelligence
For most of history, intelligence was scarce and expensive—a resource hoarded by the few, shaped by education, institutions, and money. The ability to think, reason, and create was the ultimate edge, defining everything from political power to economic success.
But today, we’re at a turning point. We’re seeing the industrialization of intelligence—the transformation of thinking into something scalable and mechanized.
This change is as profound as the Industrial Revolution. Instead of mechanizing physical production, we’re mechanizing how we think—our reasoning, problem-solving, and decision-making.
The Industrial Revolution didn’t wipe out human labor—it transformed it. Machines took over the repetitive, structured tasks while humans focused on oversight, adaptability, and creativity.
Now, with AI, the same shift is happening in intellectual work—intelligence itself is being automated, enhanced, and scaled.
The Key Difference: Scaling Cognition
We’ve never really scaled how we think the way we’ve scaled energy, manufacturing, or computation. Sure, we’ve had tools—like writing, the printing press, and computers—that boost individual smarts, but the intelligence itself stayed limited:
Expensive: The best cognitive work used to require years of specialized education, accessible only to a few.
Bottlenecked by Human Limits: Even the brightest minds could only tackle so many problems at once.
Non-replicable: Unlike factories that mass-produce goods, you couldn’t just clone a genius.
That’s changing. For the first time, AI is turning intelligence into something you can scale—a mechanized, replicable, and constantly improving resource.
Parallel Thinking: AI can “think” in thousands of parallel instances. While a human might need weeks to analyze data, AI can do it instantly.
Unlimited Cognitive Capacity: Instead of multiplying experts, AI lets us replicate intelligence infinitely.
Utility at Scale: Just as electricity scaled muscle power, AI is scaling intellectual power—available on demand, everywhere, at nearly zero cost.
This is what I call Industrial Intelligence—the moment when AI shifts from a niche research tool to a general-purpose cognitive utility.
The Next Phase: Embodied Intelligence
Back in 1950, Alan Turing famously asked,
"Can machines think?"
Today, the answer is yes—although not exactly like us. It seems we are on a path to AI that can reason, problem-solve, and create at levels that rival (or even surpass) human intelligence.
If this is true, the next question is:
"Can machines act ?"
In other words, if the brain is ready, can we build a body? Experts are already on it. Here’s the twist: we might even need AI to design its own physical form.
The "ChatGPT Moment" for Robotics Hasn’t Happened… Yet.
Even though AI is making huge strides, robotics has lagged behind because of:
Dexterity Challenges: Tasks like folding laundry or cooking are still tough.
Limited General-Purpose Robotics: Most robots today are built for specific jobs.
The Intelligence Bottleneck: Super-intelligent robots couldn’t exist until AI hit human-expert levels.
That’s changing now. Just as ChatGPT changed the game for cognitive AI, the next breakthrough will come when general-purpose robots can handle a wide range of human-level tasks.
So this is not only about developing Intelligence, but also about giving it a body.
Zero-Cost Intelligence?
All of this means that we urgently need to engage with the following question: What happens when the price of intelligence drops to zero?
Every day, we see headlines about new AI models, market reactions, regulatory changes, breakthroughs, investments, and even existential risks. The pace is relentless.
Step back, and you see a bigger story unfolding. Historians (and I say this as one) will one day tell the grand tale of how intelligence got industrialized. But we don’t have to wait—it’s happening right now.
We don’t have a crystal ball, but we can analyze it through a framework that allows us to, map the forces driving this change; see how they connect and get a glimpse of what’s next.
When you connect the dots, you not only follow what’s happening—you start to see where the world is headed.
Historical Parallels: A Pattern of Transformation
AI isn’t just another technology—it’s a fundamental shift in power, economics, and human potential. History shows that every major technological revolution follows a familiar pattern: A scarce resource becomes scalable and cheap, barriers to access crumble, and power, economics, and society are transformed.
A Few Examples:
The Printing Press (1440s) – Industrializing Knowledge
Before Gutenberg, books were copied by hand. Knowledge was expensive, slow, and reserved for elites. By 1500, printing presses had churned out over 20 million books, sparking the Renaissance, the Reformation, and the Scientific Revolution.The Industrial Revolution (1750–1900) – Industrializing Labor
In 1750, over 80% of the workforce was in agriculture. By 1900, urban factories, mechanized production, and improved living conditions had transformed society.The Information Revolution (1990s–2000s) – Industrializing Communication
In 1995, fewer than 1% of the global population had internet access. Today, over 67.5% are online, reshaping how knowledge is spread and consumed.
Now, intelligence is undergoing the same transformation. For centuries, our thinking was limited by biology and slow dissemination. That’s ending. AI is making intelligence scalable—an economic, technological, political, and existential game-changer.
As history shows: When a scarce resource becomes industrialized, the world changes forever.
Breaking It Down: The Four Cs
Let’s look at the AI revolution through the lens of four key areas:
I. Concepts – The Driving Ideas
Scaling and Efficiency: More compute and data mean dramatic improvements—but it’s all about doing more with less.
Self-Supervised & Self-Play Learning: Modern AI learns on its own. Think of AlphaGo: systems that discover patterns without needing constant human input.
Emergent Abilities: As models grow, unexpected capabilities pop up, challenging our old ideas of intelligence.
Iterative Refinement: Techniques like reinforcement learning help AI improve by learning from both wins and losses.
Reconceptualizing Intelligence: We’re moving from simply mimicking human thought to building systems that can reason, adapt, and innovate—pushing us to rethink what intelligence really means.
II. Characters – The Key Players
Big Names:
Foundation Model Leaders: OpenAI, Google DeepMind, Anthropic, xAI.
Infrastructure Giants: Microsoft, NVIDIA, Meta, Amazon, Google, xAI, TSMC, Intel, AMD.
New Disruptors:
Innovative Chipmakers: Companies like Cerebras, Groq, and Tenstorrent are shaking things up.
Next-Gen AI Startups: Fresh labs and open-source challengers like DeepSeek and xAI are emerging.
AI-First Application Companies: Firms are now building consumer and enterprise AI products from the ground up.
The Open-Source Wave:
Spreading Intelligence: OS models like Llama 3 and DeepSeek R1 are making frontier AI accessible to everyone.
The Big Debate: Should intelligence be locked down by a few, or spread out as a public good?
III. Countries – The Global Picture
Superpower Showdown – U.S. vs. China:
Changing Dynamics: The U.S. led the way in AI, but recent breakthroughs in China are challenging that lead.
National Security: With AI playing a central role in security, expect tighter export controls and huge domestic investments.
An Arms Race: AI is now a key player in global power struggles.
The Resource Battle:
Key Inputs: AI depends on semiconductors (with major players in Taiwan and South Korea), huge amounts of energy, and rare earth minerals (where China holds significant sway).
High Stakes: Who controls these resources will shape the future of AI.
Global Strategies:
Europe: Key focus on regulation, lagging severely on capital, innovation and resources like energy.
The Gulf: Using oil wealth to build bold AI hubs.
Other Regions: Africa, Russia, Latin America, Asia all have unique challenges and opportunities in the AI race. (I’ll write more about this soon.)
IV. Competition – The Market Race
Corporate Rivalries: Old giants and new disruptors are in a high-stakes race, fueling rapid innovation and fierce talent battles.
Innovation Under Pressure: The competitive atmosphere is speeding up breakthroughs in areas like self-supervised learning and emergent capabilities.
Proprietary vs. Open-Source: The battle between closed systems (backed by deep pockets) and open-source projects (aiming to democratize access) is shaping AI’s path.
Where the Money Goes: Investment in cutting-edge hardware, faster compute infrastructure, and smart research will decide who leads in AI.
This isn’t just about building the best model—it’s about controlling the entire ecosystem that lets AI scale, propelling us into a new era of “Industrial Intelligence” (and maybe even AGI).
The Big Unanswered Questions
The shift to Industrialized Intelligence raises deep questions about technology, economics, power, and what it means to be human. As AI moves forward, we need to tackle a few core challenges:
1. What Happens When the Price of Intelligence Drops to Zero?
For decades, we thought automation would slowly take over mundane tasks. Instead, AI is quickly automating advanced functions—math, coding, scientific discovery, and complex reasoning. High-skill jobs will be impacted first. An AI will be able to automate a hedge-fund quant earning $300K long before it can clean a toilet.
Unknown:
How will society adapt when anyone, anywhere can tap into intelligence that rivals—or even beats—the best human minds?
What does this mean for learning, higher education, and career paths leading to high-paying jobs?
2. How Will Ubiquitous Intelligence Reshape Society and Global Power?
Some worry that AI will funnel power into a few tech oligopolies, drive mass unemployment, and destabilize geopolitics. But history tells us that technology often breaks down barriers to opportunity. Growing up in Nepal, I saw firsthand how technology transformed a pre-modern society into a connected world.
Unknown:
What happens when intelligence, once reserved for a select few, becomes available to everyone?
How will this shift impact traditional models of wealth and employment?
As economic leadership shifts, which nations or regions will rise, and how will that affect global stability?
3. When Does AI Start Acting Completely On Its Own?
Traditionally, intelligence has been tied to human biology. Today, intelligence is becoming an industrial commodity, while advances in robotics and autonomous systems are pushing intelligence into the physical world.
Unknown:
At what point does AI start operating completely autonomously — not only to learn, but to act as well?
Will humans be able to develop systems that allow us to understand what is ‘going on under the hood’ of AI systems?"? And will humans be smart enough to understand what we see?
How do we draw the line between “Industrial Intelligence”—superhuman-level cognition at scale but under human oversight—and Artificial General Intelligence (AGI), where machines are autonomous and operate outside of human control?
No one can say exactly when AGI might fully emerge, but given how fast things are moving, we need to take these possibilities seriously.
Final Thoughts
I call this project Industrial Intelligence because the big shift is happening right now—intelligence is becoming scalable, affordable, and woven into every part of our lives.
Transformation in Motion:
Alongside Industrial Intelligence, we’re seeing the rise of Embodied Intelligence, where AI moves beyond just processing data to actually interacting with the world.
A New Era is Here:
We stand at the edge of a time when AI isn’t just a tool but a transformative force that changes how we think and work, and identify as humans.
Love this!
Excellent article, Nina. As you say, when personal merit (and even wisdom) is no longer the determinant of income, status and economic wellbeing a key question is how will the bounty of AI be shared. Looks like you’ve started the debate!