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🧠 The Brain – the most powerful computer on the planet?
Imagine you have the most powerful supercomputer right in your head. It performs 1 quintillion operations per second, works 17 times faster than the entire Internet, and consumes only 20 W — like a regular light bulb! In this article, we will explore how the brain compares to the best supercomputers, how much data it processes daily, and why no computer has yet been able to replicate its unique abilities.
5 reasons why the brain is more powerful than supercomputers: comparison of power and energy efficiency
Modern supercomputers perform quintillions of operations per second, analyze huge data sets, and even learn based on neural networks. However, even the most powerful machines cannot match the human brain. Here’s why:
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The brain consumes only 20 W — like a regular light bulb.
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The Frontier supercomputer consumes 21 megawatts — enough energy to power an entire city!
2. Parallel processing on a billion threads
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Processors perform calculations sequentially, even if they have many cores.
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The brain processes data in parallel on billions of neurons — it instantly combines vision, sound, sensations, emotions, and memory.
3. Self-learning and adaptation
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A computer needs reprogramming or updating.
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The brain learns on its own, creating and restructuring neural connections every second.
4. Flexibility of thinking and creativity
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A computer analyzes data and finds patterns but cannot go beyond the algorithm.
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A human is capable of spontaneous ideas, intuition, and non-standard solutions.
5. Emotions and awareness
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Computers do not experience emotions — they simply analyze data.
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The brain not only processes information but also “lives” it through feelings, which affect decisions.
Result:
✅ The brain is thousands of times more powerful and energy efficient than any supercomputer.
✅ It is capable of adaptation, creativity, and self-development.
✅ It is not just a calculation machine but a system that creates personality and awareness.
🔬 How the brain works: processor, RAM, and hard drive
You can compare the brain to a computer, where each part has its own unique function:
- Superconsciousness — the “processor” (CPU) responsible for global data processing.
- Consciousness (EGO) — the “RAM,” where conscious thinking takes place.
- Subconsciousness — the “hard drive” (HDD/SSD), the long-term storage of information and automatic skills.
Superconsciousness – the “Brain Processor” (CPU)
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Function: Global data processing, forecasting, analysis.
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Speed: Up to 1 exaflops (that’s a billion billion operations per second — as many as the most powerful supercomputers perform).
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Power consumption: Only 20 W — like a light bulb.
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Location: Frontal lobes and cerebral cortex.
Example of operation:
The brain processes everything at once: vision, hearing, emotions, memory — and instantly draws a conclusion.
Consciousness – “RAM” (cache)
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Function: Temporary storage and data processing.
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Volume: ≈ 230–500 KB/day (resets daily).
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Performance: ≈ 1 gigaflops (like an iPhone 5).
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Location: Prefrontal cortex.
Example of operation:
When you read, consciousness holds the words at the current moment, but by the next day they may be forgotten without repetition.
Subconsciousness – “Hard drive” (HDD/SSD)
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Function: Long-term storage of memories, skills, and habits.
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Volume: ≈ 10 PB over a lifetime (equivalent to 10,000 1 TB hard drives).
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Performance: ≈ 1–10 petaflops (like a supercomputer, but thousands of times more energy efficient).
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Location: Neocortex and cerebellum.
Example of operation:
You do not think about how to walk or ride a bicycle — it is already wired into neural connections.
Comparison of the brain with supercomputers
How do the brain and a supercomputer compare in numbers?
System | Performance | Power consumption |
🧠 Brain | 1 exaflops | 20 W (like a light bulb) |
🖥 Frontier | 1.6 exaflops | 21 megawatts (city) |
What can supercomputers do?
Powerful machines like Frontier can perform 1.6 exaflops (1.6 quintillion operations per second). They analyze huge amounts of data, conduct complex simulations, help with scientific research, and even train neural networks.
But despite all their power, they have limitations…
Why haven’t supercomputers caught up with the brain?
✔ They perform calculations sequentially, whereas the brain works in parallel.
✔ They require enormous computing power and energy comparable to a city’s consumption.
✔ They do not possess intuition, flexibility, and awareness like the human brain.
The brain processes up to 86 zettabytes of data daily — that’s 17 times more than the entire global Internet traffic. For comparison: if the brain were a computer, it would process an amount of information equivalent to several days of global Internet traffic in just one day! At the same time, it only consumes 20 W of power — like a regular light bulb.
But power isn’t everything. Let’s figure out why even the most powerful computer can’t think like a human.
Why can’t a computer replace the brain?
🔹 A computer can beat a human at chess but cannot think.
🔹 The brain adapts on its own, while computers require programming.
3 reasons why a computer cannot replace the brain
✔ Plasticity – the brain changes its structure, a computer does not.
✔ Emotions – the brain feels, a computer only calculates.
✔ Energy – the brain operates on 20 W, a computer runs on megawatts.
Result:
✅ The brain is self-learning and adaptive.
✅ It not only calculates but also “experiences” information through emotions.
✅ Computers are still unable to replicate the brain’s complex biochemical processes.
Future: is it possible to create a computer equal to the brain?
Modern technologies such as artificial intelligence, quantum, bio-, and neurocomputers can already analyze data, learn, and even generate creative content. However, they are still far from creating a full-fledged digital mind.
Artificial Intelligence (AI)
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What it can do:
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Recognize images and speech.
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Play chess at a champion level.
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Generate texts and art.
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Limitations:
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Operates based on statistics and patterns, not deep understanding.
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Does not experience emotions, does not form subjective experience, and does not possess self-awareness.
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Conclusion: Modern AI imitates human thinking but does not understand the world the way a human does.
Quantum computers
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How they work: Use qubits, which can be both 0 and 1 at the same time, allowing for complex calculations instantly.
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Potential: Theoretically, they can reach the brain’s power, as it also processes data in parallel via billions of streams.
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Challenges: Currently unstable and require unique conditions like ultra-low temperatures.
Future: If quantum computers become stable and energy efficient, they could process information as fast and flexibly as the brain.
Neurocomputers
Neurocomputers represent a new era in the development of computing systems that aim to imitate the work of the human brain. Unlike traditional computers, they use neural networks and analog computing to get closer to the brain’s principles of operation.
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How they work:
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Use artificial neurons and synapses, which mimic biological neural networks.
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Process information in parallel, like the brain, not sequentially like traditional processors.
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Capable of self-learning and adaptation, making them more flexible.
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Examples of developments:
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IBM TrueNorth — a neurocomputer that imitates the operation of 1 million neurons and 256 million synapses.
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Intel Loihi — a processor that uses “spiking neural networks” for real-time learning.
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Advantages:
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High energy efficiency: neurocomputers consume significantly less energy than traditional supercomputers.
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Ability to self-learn: they can adapt to new tasks without reprogramming.
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Challenges:
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Neurocomputers are still in the early stages of development.
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They are difficult to scale to a level comparable to the human brain (86 billion neurons and trillions of connections).
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Future: If neurocomputers can be scaled up and made stable, they could be the key to creating artificial intelligence closer to human thinking.
Biocomputers
Another direction is biocomputers, which use living cells or molecules for computing (a synthesis of biology and technology). For example:
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DNA computers: Use DNA molecules for storing and processing information.
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Neurochips: Integrate living neurons with electronic components.
Potential: Such systems could become a bridge between biology and technology, but they are still at the experimental stage.
Why does a computer beat a person at chess but hasn’t become smarter?
🔍 Humans, unlike computers, are capable of flexible thinking:
Example:
A grandmaster can find the best move in seconds without brute-forcing all options. A computer wins because of its calculation speed, not understanding.
The brain is not just a supercomputer; it is a unique system combining power, flexibility, and self-learning capability.
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Superconsciousness — the processor.
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Consciousness — the RAM.
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Subconsciousness — the hard drive.
Can a computer ever replace the brain? Not yet. Even the most powerful technologies are only a faint shadow compared to the power of the human mind:
The Brain – self-learning, adaptive, energy-efficient.
Computers – fast, but need reprogramming.
What do you think? Will technology ever replicate the unique abilities of our brain? Which technologies are already close to the brain? Could a neurocomputer ever gain consciousness?
Share your opinion in the comments!
References
- Brain Inspired Computing: A Systematic Survey and Future – Li Guoqi et al., – TechRxiv, 2023
- Artificial Intelligence as a Substitute for Human Creativity – Irina Dora Magurean et al. – Journal of Research in Philosophy and History, 2024
- The Brain: The Story of You – David Eagleman, 2017
- Quantum Cognition: The possibility of processing with nuclear spins in the brains, M.P.A. Fisher, Annals of Physics 362, 2015
- Life 3.0: Being Human in the Age of Artificial Intelligence – Max Tegmark, 2017
- Neuroscience for Artificial Intelligence – Pablo Rudomin, 1993
- An energy costly architecture of neuromodulators for human brain evolution and cognition – Gabriel Castrillon et al. – Sci. Adv. 9, 2023
- Opportunities for neuromorphic computing algorithms and applications – Schuman, C.D., Kulkarni, S.R., Parsa, M. et al. – Nat Comput Sci 2, 2022
- Artificial Intelligence and the Future of Work – Salima Benhamou – Revue d’économie industrielle, 169, 2020
- Mokienko O.A. Invasive Brain–Computer Interfaces: 25 Years of Clinical Trials, Scientific and Practical Issues – Annals of the Russian academy of medical sciences, 2024