Pennings, A.J. (2026, Sep 10) Michio Kaku and the Electromagnetic Forces Used for AI. apennings.com https://apennings.com/data-analytics-and-meaning/michio-kakus-electromagnetic-vision-for-em-in-ai/

Introduction

In his (2011) book Physics of the Future: How Science Will Shape Human Destiny and Our Daily Lives, theoretical physicist Michio Kaku argues that to understand the future we must first understand the four fundamental forces of nature. These forces are gravity, the electromagnetic force, the weak nuclear force, and the strong nuclear force. I still use the book in my undergraduate class, EST 202 Introduction to Science, Technology, and Society. Students will recognize the theme song.

Kaku devotes particular attention to electromagnetism, describing it as perhaps the most useful force ever harnessed by humans. He reminds readers that lasers, radio, television, modern electronics, computers, the internet, electricity, and magnetism are all consequences of the electromagnetic force. In a 2021 interview, Kaku explicitly stated that the internet itself is a simple byproduct of the electromagnetic force and a solution of Maxwell’s equations.

Kaku’s vision extends beyond present-day technology. He predicts that the electromagnetic force will be miniaturized and embedded in our glasses, contact lenses, and even inside our bodies via swallowable camera pills. He describes a future where augmented reality, powered by electromagnetism, becomes the primary medium through which we interact with information, recognize faces, translate languages, and access the entirety of human knowledge with a blink of an eye.

While Kaku focuses on the physical infrastructure of the future, his framework provides a foundation for understanding how artificial intelligence depends on the electromagnetic spectrum. AI does not exist in an abstract digital void; it runs on physical hardware, communicates through electromagnetic signals, and processes information using electrical currents and magnetic fields.

The Electromagnetic Force as One of Nature’s Four Pillars

Electromagnetism is one of the four fundamental interactions that govern all physical phenomena in the universe. Unlike gravity, which is extremely weak and acts only attractively over large distances, electromagnetism can both attract and repel, acts over large distances, and can be precisely focused and controlled.

The laws of electromagnetism are described by James Clerk Maxwell’s equations, which unified electricity and magnetism into a single force in the nineteenth century. This unification revealed that visible light, radio waves, microwaves, infrared radiation, ultraviolet light, X-rays, and gamma rays are all manifestations of the same electromagnetic spectrum, differing only in wavelength and frequency.

Kaku emphasizes that the reality we see with our eyes represents only the tiniest sliver of the complete electromagnetic spectrum. Modern technology has learned to exploit portions of the spectrum invisible to human perception, from radio communications to medical imaging, creating the infrastructure upon which all digital computation and artificial intelligence depend.

Five Applications of Electromagnetism for Artificial Intelligence

1. Semiconductor Computing and Transistor Logic

The foundation of all modern AI systems is the silicon-based semiconductor chip, which operates entirely through electromagnetic principles. Transistors, the fundamental switching elements in processors, control the flow of electrons through semiconductor materials using electromagnetic fields.

When Kaku notes that chips will soon cost only a penny because we can manufacture tinier and tinier transistors, he is describing the ongoing miniaturization of electromagnetic control at the nanoscale. Graphics processing units (GPUs) and tensor processing units (TPUs) designed specifically for AI workloads contain billions of transistors that switch on and off at gigahertz frequencies, performing the matrix multiplications and parallel computations that power neural networks.

Without precise electromagnetic manipulation of electron flow through doped silicon channels, the computational substrate for artificial intelligence would not exist.

2. High-Speed Data Transmission and Fiber Optics

AI systems require massive data flows between processors, memory, storage, and network endpoints. Fiber-optic cables transmit information using pulses of laser light, which is electromagnetic radiation in the visible or near-infrared spectrum.

Kaku explicitly identifies fiber-optic cables as one of the technologies enabled by Maxwell’s equations, allowing nearly instantaneous global communication. Data centers that train large language models rely on high-bandwidth optical interconnects to synchronize thousands of GPUs across server racks, moving terabytes of training data and model parameters at the speed of light.

Wireless communication technologies, including 5G and future 6G networks, use microwave and millimeter-wave portions of the electromagnetic spectrum to connect edge AI devices to cloud infrastructure. Every query to an AI assistant travels as modulated electromagnetic waves through copper wires, fiber-optic strands, or free-space radio channels.

3. Magnetic Storage and Memory Systems

Artificial intelligence models require vast amounts of persistent storage for training datasets, model weights, and operational logs. Hard disk drives (HDDs) store data by magnetizing microscopic regions of a spinning platter, using electromagnetic read-write heads to encode binary information as magnetic orientations.

Even solid-state drives (SSDs) and RAM, which use flash memory and DRAM technologies, rely on electromagnetic phenomena to trap or release electrical charges in floating-gate transistors and capacitors. The hierarchical memory architecture that allows AI systems to access frequently used parameters quickly while storing massive datasets economically depends entirely on electromagnetic storage principles.

As Kaku observes, the Internet and all digital information systems are byproducts of the electromagnetic force, and this includes the storage infrastructure that preserves the knowledge AI systems learn.

4. Electromagnetic Sensors and Perception Systems

AI systems that interact with the physical world depend on electromagnetic sensors to perceive their environment. Computer vision systems process images captured by CMOS and CCD image sensors, which convert incoming photons (electromagnetic radiation in the visible spectrum) into electrical signals.

Autonomous vehicles use LiDAR systems that emit laser pulses and measure reflected electromagnetic radiation to construct three-dimensional maps of surroundings. Radar systems, which operate in the microwave portion of the spectrum, enable AI-powered collision avoidance and weather monitoring.

Medical AI applications analyze electromagnetic imaging data from MRI scanners (which use strong magnetic fields and radiofrequency pulses), X-ray machines, and CT scanners to diagnose diseases. Kaku describes swallowable camera pills guided by magnets that transmit video via electromagnetic signals, illustrating how AI can operate inside the human body using electromagnetic sensing and actuation.

5. Wireless Power Transfer and Energy Harvesting for Edge AI

As AI systems become embedded in Internet of Things devices, wearable technology, and autonomous sensors, powering these systems becomes a critical challenge. Electromagnetic wireless power transfer technologies, based on inductive coupling and resonant electromagnetic fields, enable battery-free or self-charging AI devices.

Kaku describes a future where transistors made from plastic enable flexible electronic paper and ubiquitous computing surfaces powered by ambient electromagnetic fields. Energy harvesting systems convert ambient electromagnetic radiation from radio waves, Wi-Fi signals, and cellular transmissions into electrical power for low-energy AI processors.

This electromagnetic infrastructure allows AI to operate in remote, mobile, or implanted contexts where wired power connections are impractical, extending the reach of intelligent systems into every corner of physical space.

Conclusion: The Electromagnetic Substrate of Intelligence

Michio Kaku’s emphasis on the electromagnetic force as the foundation of modern civilization provides essential context for understanding artificial intelligence. AI is not a disembodied software phenomenon but a physical process that depends on the precise manipulation of electrons, photons, and magnetic fields.

From the transistors that compute neural network operations to the fiber-optic cables that transmit training data, from the magnetic storage that preserves learned knowledge to the electromagnetic sensors that perceive the world, every layer of the AI stack is an application of Maxwell’s equations and Faraday’s law of induction.

As Kaku envisions a future where the electromagnetic force is embedded in our glasses, contact lenses, and even inside our bodies, we can anticipate AI systems that are increasingly integrated with the physical world through electromagnetic interfaces. Understanding this electromagnetic foundation is essential for anyone seeking to grasp both the possibilities and the limitations of artificial intelligence in the decades ahead.

References

Kaku, Michio. Physics of the Future: How Science Will Shape Human Destiny and Our Daily Lives. Doubleday, 2011.
Kaku, Michio. Physics of the Impossible: A Scientific Exploration into the World of Phasers, Force Fields, Teleportation, and Time Travel. Doubleday, 2008.
Kaku, Michio. The God Equation: The Quest for a Theory of Everything. Doubleday, 2021.
Maxwell, James Clerk. A Dynamical Theory of the Electromagnetic Field. Philosophical Transactions of the Royal Society, 1865.
SuperSummary. “Physics of the Future Summary.” 2026.
Wikipedia. “Physics of the Future.” 2011.
Big Think. “The physics of everything, with Michio Kaku.” 2021.
Prompts: Write a blog post on Michio Kaku’s reference to the Electromagnetic spectrum in his book Physics of the Future and after writing about EM as one of the four forces of nature, describe 5 applications of EM for AI

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Not to be considered financial advice. AI is often used, and results are thoroughly interrogated. Links are used for some citations.

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Anthony J. Pennings, PhD is a Professor at the Department of Technology and Society, State University of New York, Korea and a Research Professor for Stony Brook University. He teaches AI and broadband policy. From 2002-2012 he taught digital economics and information systems management at New York University. He also taught in the Digital Media MBA at St. Edwards University in Austin, Texas, where he lives when not in Korea.

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Category: artificial intelligence, data analytics and meaning, futurists, science and technology studies
Tags: electromagnetic force > electromagnetism > Internet of Things > transistors

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