Real Vision Founder: We Are Living in an Era of Exponential Growth
TechFlow Selected TechFlow Selected
Real Vision Founder: We Are Living in an Era of Exponential Growth
AI, Energy, and Cryptocurrency weave a super growth curve.
Navigating Web3 tides with focused insightsBy: Raoul Pal, Founder of Real Vision
Compiled by: Luffy, Foresight News
Let's start with a fun calculation: If 1 cent doubles every day for 30 days, how much money will you end up with? Most people would guess a few hundred dollars. But the real answer is over 5 million dollars.
Almost no one gets it right on the first try because the human brain is not good at handling this kind of calculation. Our thinking is naturally biased towards linear logic. When crossing the street and glancing at incoming traffic, the brain can intuitively judge whether it is safe; but when we imagine something doubling every year, we always severely underestimate the final scale, with deviations often reaching thousands or tens of thousands of times.
Throughout long human history, this thinking limitation was almost irrelevant. Every tool we built and every system we established developed at a speed that fit human linear intuition.
But now, for the first time, humanity possesses an intelligent system that operates non-linearly: it compounds itself, feedbacks itself, and continuously accelerates. Simultaneously, five or six exponential growth curves are reaching the steep upward phase of the S-curve at the same time, with multiple transformations overlapping and arriving.
In April 2021, I first proposed this viewpoint in my GMI column "The Exponential Age". Looking back now, I did not fully realize at the time that the trends I observed were far larger in scale than anticipated.
What Did I Get Right, and Where Did I Go Wrong?
In 2021, my core viewpoint was very clear: Fiat currencies were depreciating far faster than market pricing suggested, and only a few assets had compound growth rates capable of outpacing inflation, with Bitcoin and tech stocks representing them. This judgment still holds true today. But I severely underestimated the scale of subsequent transformations at the time.
At that time, I mainly focused on central bank balance sheets across countries, with a key focus on the Federal Reserve. This analytical direction was not wrong, but the observational dimension was incomplete. The true core driver was not a single central bank, but global total liquidity: major central banks worldwide, rolling debt from national treasuries, and commercial banks expanding credit—all links exerting force simultaneously like a relay race. When the Federal Reserve tightened its cycle, China or Europe would take up the easing baton.
If you only stare at a single central bank, you will misjudge the entire market cycle. 2017 is a typical case: The Federal Reserve was shrinking its balance sheet, but the global market continued to rise unilaterally. The reason was that China and Europe eased simultaneously, and global total liquidity continued to expand. Those who only tracked the Federal Reserve completely failed to predict this bull market.
Currently, global liquidity expands by about 8% annually. Superimposed on conventional inflation, for assets to maintain their original purchasing power, your actual minimum yield needs to be close to 11%.
The Truly New Transformative Forces
The logic of currency depreciation can explain why money is becoming less and less valuable, but it cannot fully explain the feeling that everything is accelerating right now. It is not just market trends that are accelerating; the pace of entire social transformation is rising rapidly.
This is another independent force superimposed on liquidity, and also the core reason why the logic of "The Exponential Age" has become increasingly critical today, five years later.
In 2021, I identified five major growth curves: Artificial Intelligence, Robotics, Photovoltaics and Energy Storage, Biotechnology, and Blockchain Networks. The list of tracks has not changed; what has changed is the growth stage they are in.
In 2021, most of these technologies were still on the eve of theoretical implementation. Observant people could foresee the trends, but large-scale commercialization had not yet arrived. Five years later, the five major technologies are accelerating simultaneously, empowering and coordinating with each other. This technological fusion has completely rewritten the logic of development.
Artificial Intelligence
Most people ignore the underlying logic behind debt expansion. Countries continue to expand debt not because leaders are stubborn or incompetent, but due to demographic structure. Population aging, shrinking workforce, fewer producers, and more social welfare recipients. Relying solely on human labor cannot achieve natural economic growth; countries can only expand through debt, relying on expanding balance sheets to balance the gap.
And artificial intelligence breaks this cycle. AI agents can complete white-collar knowledge work, and humanoid robots can undertake physical labor; economic growth is no longer constrained by the number of working-age population. We have created "artificial labor supply". The productivity curve dragged down by demographic structure turns upward again, and without the debt expansion continuously relied upon over the past fifty years.
At the same time, there is also a deflationary force at play. The marginal cost of intelligent services approaches zero, and prices for a large number of goods and services are declining rapidly. This cannot immediately eliminate the problem of currency depreciation, but it will reshape the logic of yield calculation. When AI compresses costs across the entire industrial chain, the meaning of the 11% yield threshold mentioned earlier will also change completely.
The speed of all this development is shocking and deserves us to stop and examine carefully. Over the past six years, the duration of complex tasks AI can complete autonomously has approximately doubled every seven months. OpenAI's o3 model has already surpassed human PhDs in performance in corresponding scientific research fields, and the development speed has not slowed down at all.
Energy
All technological transformations have a core bottleneck: Energy. AI and robots rely on computing power to operate, and computing power consumes electricity. Currently, the scale of computing power under construction globally is unprecedentedly large, and energy has become a hard constraint for the entire technological transformation. Microsoft deploying nuclear power and Google signing geothermal projects are not solely to achieve carbon neutrality goals, but because local grid power supply is already insufficient to support the operation of computing clusters.
China saw this first and deployed most aggressively. In 2024 alone, China's newly added photovoltaic installed capacity exceeded the sum of newly installed capacity in all other countries globally.
The core behind this is a little-known economic law — Wright's Law. This law was summarized from aircraft factory production data in 1936: For every doubling of the cumulative total production of a certain product, the single-unit production cost will decrease by a fixed proportion. Worker proficiency increases, defect rates decrease, engineers optimize materials (reducing silver, thinning silicon wafers, etc.), continuously compressing costs.
Photovoltaics is the category that best fits Wright's Law among technologies known to humanity. For every doubling of global total photovoltaic installed capacity, manufacturing costs decrease by more than 20%. And China, relying on super-large capacity manufacturing, has significantly raised the global cumulative total photovoltaic production, driving the entire industry to complete the cost decline curve faster.
Today, photovoltaic prices have plummeted 90% compared to ten years ago, and there is still ample room for cost decline. Photovoltaics possess four unique advantages: low cost, short construction cycle, distributed deployment, and infinite scalability, which fossil fuels cannot compare with at all. Other energy categories will always encounter a capacity ceiling at some link in the supply chain; the only limit for photovoltaics is the available sunlight area.
Energy storage was once the biggest shortcoming of photovoltaics, but now this shortcoming is being quickly addressed. Tesla's Megapack energy storage business has an annual growth rate of 50%–70%, and new factories continue to start production to keep up with demand. Grid-level energy storage battery costs are rapidly declining, and the vast majority of people have not yet realized how much transformation this will bring.
More critically, there is a closed-loop positive cycle: AI optimizes grid dispatch, electricity costs decline; lower electricity prices further suppress computing power costs; cheap computing power in turn iterates stronger AI, and AI again optimizes the energy system. Several growth curves are no longer developing in parallel, but are overlapping and amplifying growth rates.
Cryptocurrency
The linkage logic between Bitcoin and global liquidity has been fully demonstrated. Since 2012, about 90% of Bitcoin price fluctuations have corresponded to liquidity cycles; this core logic still holds true today, even showing a higher correlation than I summarized back then.
But the crypto industry also has a core logic that barely existed in 2021 and cannot be ignored today. AI agents need to trade; in the future, millions or even billions of intelligent entities will emerge, autonomously purchasing services, allocating resources, and automatically clearing between machines. The existing human financial system includes clearing houses, correspondent banks, and three-day settlement cycles, completely unable to bear this demand. An intelligent economy cannot be built on top of traditional financial infrastructure.
Crypto technology matches the demand exactly: programmable, no need to trust third parties, instant settlement, no counterparty risk. Blockchain is the only financial infrastructure that can adapt to a super-intelligent economy and scale synchronously. The implementation logic of the crypto track in the past was already convincing, and the rigid demand for adapting to AI autonomous trading makes cryptocurrency an inevitable trend.
Convergence
This is exactly where the uniqueness of this round of transformation lies. In the past, every wave of technology appeared separately, taking decades to complete popularization: The Internet was one independent growth curve, and the mobile Internet was another. The two reshaped the economy one after another, leaving sufficient buffer time in between, allowing various institutions to adapt gradually.
But now, multiple exponential curves are reaching the steep upward phase of the S-curve simultaneously, and pushing each other. AI designs more advanced chips, advanced chips train stronger AI; cheap energy supports massive computing power, massive computing power optimizes energy dispatch; crypto networks complete agent transaction clearing without humans or banks participating.
A single technology curve itself can sustain growth; after superimposed convergence, the overall growth rate far exceeds the level of a single technology developing independently.
Global cloud service providers' capital expenditure exceeds $600 billion annually, up 36% year-over-year; this figure does not yet include Tesla, xAI, frontier AI labs, and national-level computing infrastructure investments from Middle Eastern countries. The proportion of corporate capital expenditure to GDP has already exceeded the scale of fiscal investment by countries in developing atomic bombs back then.
Double Exponential Growth
This compound effect has a specific name; it is the true reason why human intuition cannot keep up with development. Single exponential growth has already exceeded the scope of human brain understanding. And when multiple curves empower each other, they will not form a steeper ordinary exponential curve, but give birth to double exponential growth — the growth rate itself is still accelerating, behind which lies a clear operating mechanism.
We can understand this layer by layer using three network laws:
- Sarnoff's Law: The value of a broadcast network grows linearly with the number of users;
- Metcalfe's Law: For a network where any two points can communicate, the value is proportional to the square of the number of users (n²);
- Reed's Law: For a network that supports freely forming groups, the value grows as 2ⁿ; the number of collaborative communities that can be formed grows far faster than simple pairwise connections.
In human history, Reed's Law was long just a theoretical concept because network nodes were all humans: humans act slowly, supply is limited, and they can only participate in a small number of communities at the same time.
Now network nodes have become intelligent AI entities, never fatigued, capable of infinitely replicating themselves, able to quickly form, dissolve, and reorganize collaborative communities at machine speed, at a scale unreachable by human networks. This is the first time in human history that network nodes themselves possess intelligence, and Reed's Law has been fully implemented at the macro-economic body level for the first time. 2 to the power of n is not a steep straight line; even if plotting the data on a logarithmic scale, the curve continues to bend upward.
This is the true shape of the current growth curve.
Returning to the coin example: Single exponential growth has already broken human intuition; double exponential growth belongs to a completely different order of magnitude. No life experience, thinking model, or evolutionary instinct can predict its scale; neither you nor I can outline this curve in our minds.
This is also where the real change has occurred from 2021 to now; the technology tracks themselves have not added new ones; I already listed the five major directions completely back then. But I underestimated one key point — they are no longer growing independently, but have fused into a super curve shooting straight to the top of the chart. Currently, we are even still at the flat starting phase of this curve; the future space is unimaginable.
How Should Ordinary People Respond?
So, how should you respond to all of this?
If you acknowledge that artificial labor will replace human labor, and AI agents and robots become the core productive forces of the economy, you must understand that returns will ultimately flow to the holders who control the machines and underlying infrastructure.
The core question is no longer "how to keep a job from being replaced by machines," but "how to hold shares of machine-related assets." The underlying logic of AI replacing human labor simultaneously points out the track for value precipitation, which ordinary people can also participate in laying out.
This logic amplified to the entire society is called "Universal Basic Equity." The public directly holds productive machine assets; the returns from productivity improvements are returned to owners in the form of asset appreciation, rather than relying on fixed wages. This is also one of the mainstream solutions to cope with the failure of the wage system.
I define 2030 to 2032 as the "Economic Singularity" window; at that time, all technology trends will fully converge, the economic system will undergo a fundamental transformation, and traditional economic models will become completely invalid. Whether this transformation is smooth or not depends on the choices made by everyone right now.
I am not simply predicting the future, but demonstrating facts that are happening: quantifiably expanding global liquidity, plottable technology adoption curves, double exponential growth breaking through the chart upper limit, and a few core assets that directly anchor all trends. Even if you define the current market situation as a bubble, objective data does not support this judgment.
This is the Exponential Age.
Join TechFlow official community to stay tuned
Telegram:https://t.me/TechFlowDaily
X (Twitter):https://x.com/TechFlowPost
X (Twitter) EN:https://x.com/BlockFlow_News
@RaoulGMI
