Why the Brain Holds the Blueprint for the Next AI Boom

When I first walked onto the floor of the New York Futures Exchange more than 40 years ago, I learned something simple but powerful. 

Every great leap forward in technology comes with bottlenecks. 

Railroads ran into steel and coal shortages. Automobiles ran into oil and rubber constraints. The internet ran into bandwidth and storage limits. 

Each time, people claimed the growth had hit a wall. And each time, human ingenuity broke through and created fortunes.

Artificial intelligence today is no different.

Right now, the world is pouring billions into ever-bigger AI models. We read daily about new chips, faster data centers, and massive power-hungry machines that can predict text, generate images, and even hold conversations. 

The hype is enormous. But step back and you will see something very important. 

These systems, impressive as they are, remain crude imitations of real intelligence. They are great at crunching numbers but poor at true reasoning. 

They burn electricity like a small city and need mountains of data to function.

Compare that with the human brain, which runs on 20 watts of power — less than a refrigerator lightbulb. 

Yet it handles reasoning, creativity, and social interaction in ways today’s AI cannot touch. 

If you wanted to match the computing efficiency of one brain with current technology, you would need enough power to light up Dallas. 

That is the definition of inefficiency.

The reason is simple. We are building machines that are bigger, not smarter.

This is where Professor Cory Miller, writing recently in The Wall Street Journal, makes a critical point.

The next leap in AI might not come from stacking more microchips. It could come from studying biology — specifically, how the brains of primates work.

Our closest evolutionary relatives, monkeys and apes, share the same core brain architecture as humans. Their neural systems give scientists the most direct window into how intelligence actually functions. 

In fact, decades ago, the very first AI models were inspired by neuroscience research on how monkeys processed visual input. 

The convolutional networks that now power everything from self-driving cars to facial recognition can be traced back to those biological studies.

Miller argues that we abandoned this approach too soon. 

In the rush to build bigger and faster models, the AI industry left behind the biological insights that could make machines smarter, leaner, and more efficient. 

If we want machines that can reason, adapt, and learn flexibly the way humans do, then primate research may hold the key.

The U.S. already has a foundation in place. 

More than a decade ago, the government launched the Brain Initiative, an ambitious project to map and understand the neural circuits that drive human thought. 

That program has yielded breakthroughs in how we can observe and manipulate brain activity. 

But we are still only scratching the surface.

Miller highlights that China has surged ahead here, building dozens of primate research centers and pouring resources into neuroscience. 

Their goal is not just science for science’s sake. It is technological leadership. 

The country that cracks the code of the brain will lead the next century of AI innovation. That could be as transformative as the Manhattan Project or the invention of the transistor.

This is not only about science, it is about national security and economic power. 

Suppose the United States underinvests in this frontier. In that case, it risks ceding leadership to competitors who recognize that the path to true AI runs not only through Silicon Valley but also through neuroscience labs.

Here’s the key takeaway for us as investors. 

Yes, the current AI systems are energy-hungry and costly. 

Yes, they will run into scaling problems. 

But those bottlenecks are what drive innovation. 

Just as railroads solved their material shortages with stronger steel, and the internet solved bandwidth issues with fiber optics, AI will solve its inefficiency problem by turning to the ultimate blueprint: the human brain.

Some of that progress will come from neuroscience. Some will come from chipmakers designing new architectures. Others will come from companies building the data centers and the tools that allow AI to be applied in the real world. 

Together, these breakthroughs will push the field forward.

That is why we remain bullish on the future of AI. 

Miller’s insight about monkeys, not microchips, shows us where the frontier may be headed. While scientists work on translating biology into smarter machines, investors can benefit right now from the companies supplying the infrastructure for the AI boom. 

From semiconductors to networking equipment to cloud computing, the businesses that make AI possible today will continue to thrive tomorrow.

The bottom line is simple. AI is not slowing down. It is broadening its horizons. And as long-term investors, that is exactly the kind of trend we want to own.

The path to true artificial intelligence may pass through the brains of primates. 

And thanks to innovators, engineers, and scientists worldwide, the companies bringing AI into our daily lives are set to prosper for decades to come.

As for the AI stocks I recommend, you should check out the American Prosperity Report portfolio. Click here to join now—risk-free with our 30-day money-back guarantee.

If you have questions, you can send them to me at [email protected].

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Regards,

Charles Mizrahi
Prosperity Insider