AI’s True Revolution Has Barely Begun

Recently, I attended an AI conference with high expectations. I was eager, even excited, to meet some of the brightest minds working in artificial intelligence across the country. I imagined intense discussions, groundbreaking ideas, and the feeling of standing at the cutting edge of digital innovation.

Instead, I was met with disappointment. Many of the participants—including some students and professionals—were not particularly digitally savvy. For most of them, their entire impression of AI was that it was simply a “smart chatbot.” Some of the questions being asked ranged from basic topics like “Is AI creative?”—the kind of questions you would expect in an introductory classroom—not at a convention meant for pioneers.

At first, this worried me. It made me wonder: Had I, in my enthusiasm, overestimated where we are in AI? Was I projecting capabilities that current technology couldn’t yet deliver?

This concern led me to step back and critically reexamine my assumptions and my plans. I needed to ensure my understanding of the technology was grounded in evidence, not just baseless hype. What I found, through a deeper review, not only reassured me but strengthened my conviction even further. It actually gave me a new perspective: the obstacles I saw—the lack of infrastructure, slow AI adoption, shallow understanding of emerging technology—could actually become major advantages for those who choose to build now.

Is Artificial Intelligence Creative?

The question of whether AI is creative is nuanced. Not because the concept is new, but because people’s opinions and experiences of creativity can vary greatly.

Is AI creative? I believe it absolutely counts as a creative medium.

Many might argue, “How can AI be creative when it’s pre-trained on massive amounts of data?” Well, humans are, in many ways, pre-trained biological models themselves. Babies don’t just wake up one day and start talking or building personalities on their own; they are shaped by years of sensory input and experiences, including sight, sound, touch, taste, and smell. In this sense, humans absorb and process information much like AI does to learn language and interact with the world.

“There is no such thing as a new idea. It is impossible. We simply take a lot of old ideas and put them into a sort of mental kaleidoscope.” — Mark Twain

It’s a common belief among philosophers and historians that everything is built upon what came before. The core point is: most ideas are combinations, reinterpretations, or evolutions of existing thoughts—very few things spring 100% from a vacuum.

Interestingly, the line between humans and AI is blurring. There’s even an emerging field of biological AI, where human stem cells are trained to perform computational tasks. Scientists are growing brain-like organoids—tiny, self-organized three-dimensional tissue cultures derived from stem cells that mimic certain brain functions. Recent experiments have shown how these organoids can be used in basic computational models. Imagine a real brain—or even a neural organoid—being used to solve problems or interact with traditional computer systems.

While this technology is fascinating, it’s important to note that biological advancements tend to progress considerably slower than their digital counterparts. In fact, stem cell technology has been around for over a decade, so while these developments are impressive, they don’t come as a complete surprise. Still, they represent an intriguing intersection between biology and computation, suggesting that humans, too, might be viewed as naturally occurring AI in some ways.

Now, if creativity is defined by consciousness and emotion, then no, AI isn’t creative in the way humans are. But if we define creativity more broadly—as the ability to generate new and varied outputs from existing data—then AI is, in fact, creative. While AI lacks emotional depth or conscious intent, its capacity to remix, reimagine, and generate novel data shows that it can be creative, at least within the confines of its programming, making it a unique and powerful tool.

Groundbreaking Achievements by AI

Just to put things into perspective, here are some groundbreaking achievements by AI that demonstrate its remarkable capabilities and long-term potential:

Protein Structure Prediction: Artificial Intelligence, through projects like DeepMind’s AlphaFold, solved one of biology’s grand challenges: predicting 3D protein structures. Traditionally, predicting the structure of a single protein could take years and often served as the focus of an entire PhD thesis. Even then, many researchers weren’t able to fully solve it. Over six decades, all of the scientists working around the world on proteins painstakingly found about 150,000 protein structures. Then, in one fell swoop, AlphaFold came in and unveiled over 200 million of them—nearly all proteins known to exist in nature. This has revolutionized fields like vaccine development (e.g., malaria vaccines), understanding genetic diseases, and combating antibiotic resistance.
Generative Protein Design: Techniques like RF Diffusion now allow scientists to create entirely new proteins tailored for specific purposes. This includes designing antibodies to neutralize snake venom, developing vaccines for cancer, creating treatments for autoimmune diseases, and engineering enzymes that capture greenhouse gases or break down plastics.
Speed and Efficiency: AI speeds up processes by up to 100,000x. What used to take years of manual lab work can now be accomplished in days. The rise of “cowboy biochemistry”—rapid, exploratory protein design—shows how AI is tearing down traditional research bottlenecks.
Broad Scientific Impact: Beyond biology, AI systems like DeepMind’s GNoME have discovered millions of new materials—including those that could lead to better superconductors, batteries, and sustainable technologies. AI is accelerating the creation of entire new fields of study.
Long-term Potential: If responsibly developed, AI could help solve humanity’s biggest problems: curing major diseases, creating clean energy, restoring ecosystems, and even reversing some effects of climate change. Its power lies in how it attacks problems humans have struggled with for centuries—offering solutions that were previously unimaginable.
A Transformative New Approach: Traditional science struggles with complex, non-linear systems. AI, by contrast, excels at decoding and optimizing these systems—whether it’s the mysterious folding of proteins or the properties of newly designed materials. Collaboration between humans and AI (like in the Fold It project) has shown how collective intelligence can tackle scientific frontiers in entirely new ways.

The Early Stages of AI’s Potential

How much better can it get? A lot better—and faster than most people realize. AI has the potential to remove the traditional barriers that have long limited how fast companies can scale. Knowledge is now abundant and the real differentiator is ingenuity—how creatively and seamlessly you can weave AI tools into a unique experience.

With AI agents, it’s now possible to accomplish more work with fewer resources, at dramatically lower costs. Of course, there will be a jarring phase: AI-generated text, designs, and outputs might be easy to spot at first. It’s hard to predict exactly how the public will react once they realize what’s behind the curtain. But regardless, the shift is already underway—and it’s only going to accelerate.

Reflecting on these advancements, I couldn’t help but realize how vastly they outpace the AI-powered projects I’ve been working on. Talk about a big fish in a small pond… At one point, I thought my ideas for implementing AI were groundbreaking and ahead of their time. But after discovering these breakthroughs, it’s clear I’ve been barely scratching the surface.

The sheer scale of what’s already been accomplished truly drives home the fact that we’re still in the early stages of what AI can achieve. It’s not just that the technology we have today is powerful—it’s that even if AI development were to stop today, it would take years before we could fully apply all the knowledge and innovations already at our disposal.

We truly have an incredible future ahead of us.