Article by AI based on youtube video transcript: With Spatial Intelligence, AI Will Understand the Real World | Fei-Fei Li | TED

The Dawn of Sight

Let me show you something. To be precise, I'm going to show you nothing. This was the world 540 million years ago. Pure, endless darkness. It wasn't dark due to a lack of light. It was dark because of a lack of sight. Although sunshine did filter 1,000 meters beneath the surface of the ocean, a light permeated from hydrothermal vents to the seafloor, brimming with life, there was not a single eye to be found in these ancient waters. No retinas, no corneas, no lenses. So all this light, all this life went unseen. There was a time that the very idea of seeing didn't exist. It had simply never been done before. Until it was.

The Cambrian Explosion

So for reasons we're only beginning to understand, trilobites, the first organisms that could sense light, emerged. They're the first inhabitants of this reality that we take for granted. First to discover that there is something other than oneself. A world of many selves. The ability to see is thought to have ushered in the Cambrian explosion, a period in which a huge variety of animal species entered fossil records.

The Evolution of Intelligence

What began as a passive experience, the simple act of letting light in, soon became far more active. The nervous system began to evolve. Sight turning to insight. Seeing became understanding. Understanding led to actions. And all these gave rise to intelligence.

The Pursuit of Machine Vision

Today, we're no longer satisfied with just nature's gift of visual intelligence. Curiosity urges us to create machines to see just as intelligently as we can, if not better. Nine years ago, on this stage, I delivered an early progress report on computer vision, a subfield of artificial intelligence. Three powerful forces converged for the first time: a family of algorithms called neural networks, fast, specialized hardware called graphic processing units (GPUs), and big data.

The Advancement of AI

We've come a long way. Back then, just putting labels on images was a big breakthrough. But the speed and accuracy of these algorithms just improved rapidly. The annual ImageNet challenge, led by my lab, gauged the performance of this progress. We went a step further and created algorithms that can segment objects or predict the dynamic relationships among them.

Generative AI and Beyond

Recall last time I showed you the first computer-vision algorithm that can describe a photo in human natural language. That was work done with my brilliant former student, Andrej Karpathy. Recently, the impossible has become possible, thanks to a family of diffusion models that power today's generative AI algorithms, which can take human-prompted sentences and turn them into photos and videos of something entirely new.

Spatial Intelligence

If past is prologue, we will learn from these mistakes and create a future we imagine. In this future, we want AI to do everything it can for us, or to help us. For years I have been saying that taking a picture is not the same as seeing and understanding. Today, I would like to add to that. Simply seeing is not enough. Seeing is for doing and learning. When we act upon this world in 3D space and time, we learn, and we learn to see and do better.

The Future of AI

Nature has created this virtuous cycle of seeing and doing powered by "spatial intelligence." To illustrate what your spatial intelligence is doing constantly, look at this picture. In the last split of a second, your brain looked at the geometry of this glass, its place in 3D space, its relationship with the table, the cat, and everything else. And you can predict what's going to happen next.

The Path Forward

The urge to act is innate to all beings with spatial intelligence, which links perception with action. If we want to advance AI beyond its current capabilities, we want more than AI that can see and talk. We want AI that can do. Indeed, we're making exciting progress. The recent milestones in spatial intelligence are teaching computers to see, learn, do, and learn to see and do better.

The Impact on Society

As the progress of spatial intelligence accelerates, a new era in this virtuous cycle is taking place in front of our eyes. This back and forth is catalyzing robotic learning, a key component for any embodied intelligence system that needs to understand and interact with the 3D world. As that future is taking shape, it will have a profound impact on many lives, including healthcare, where my lab has been taking some of the first steps in applying AI to tackle challenges that impact patient outcomes and medical staff burnout.

The Digital Cambrian Explosion

The emergence of vision half a billion years ago turned a world of darkness upside down. It set off the most profound evolutionary process: the development of intelligence in the animal world. AI's breathtaking progress in the last decade is just as astounding. But I believe the full potential of this digital Cambrian explosion won't be fully realized until we power our computers and robots with spatial intelligence, just like what nature did to all of us.

The Future of AI and Humanity

It’s an exciting time to teach our digital companion to learn to reason and to interact with this beautiful 3D space we call home, and also create many more new worlds that we can all explore. To realize this future won't be easy. It requires all of us to take thoughtful steps and develop technologies that always put humans in the center. But if we do this right, the computers and robots powered by spatial intelligence will not only be useful tools but also trusted partners to enhance and augment our productivity and humanity while respecting our individual dignity and lifting our collective prosperity.

The Quest for a Better World

What excites me the most in the future is a future in which that AI grows more perceptive, insightful, and spatially aware, and they join us on our quest to always pursue a better way to make a better world. Thank you.