Fei Fei Li

So that was one branch of computer science and AI that went on during the years, predated my birth, but during the years of my formative years, without me knowing, I wasn't in there.

But there was a parallel branch. That branch was messier. It took longer to prove to be right. But as of last week, we had the Nobel Prize awarded to that, which was the neural network. So that happened again in a very interesting way. Even in the 50s, neuroscientists were asking questions, nothing to do with AI, about how neurons work.

But there was a parallel branch. That branch was messier. It took longer to prove to be right. But as of last week, we had the Nobel Prize awarded to that, which was the neural network. So that happened again in a very interesting way. Even in the 50s, neuroscientists were asking questions, nothing to do with AI, about how neurons work.

But there was a parallel branch. That branch was messier. It took longer to prove to be right. But as of last week, we had the Nobel Prize awarded to that, which was the neural network. So that happened again in a very interesting way. Even in the 50s, neuroscientists were asking questions, nothing to do with AI, about how neurons work.

And again, my own field, vision, was the pioneering study about cat mammalian visual system. And Hubel and Wiesel in the 1950s and 60s were sticking electrodes into cat's visual cortex to learn about how cat neurons work. Details aside, what they have learned and confirmed was a conjecture that our brain or mammalian brain is filled with neurons that are organized hierarchically.

And again, my own field, vision, was the pioneering study about cat mammalian visual system. And Hubel and Wiesel in the 1950s and 60s were sticking electrodes into cat's visual cortex to learn about how cat neurons work. Details aside, what they have learned and confirmed was a conjecture that our brain or mammalian brain is filled with neurons that are organized hierarchically.

And again, my own field, vision, was the pioneering study about cat mammalian visual system. And Hubel and Wiesel in the 1950s and 60s were sticking electrodes into cat's visual cortex to learn about how cat neurons work. Details aside, what they have learned and confirmed was a conjecture that our brain or mammalian brain is filled with neurons that are organized hierarchically.

They're not like thrown into a salad bowl. Right. Okay. And that means information travel in a hierarchical way.

They're not like thrown into a salad bowl. Right. Okay. And that means information travel in a hierarchical way.

They're not like thrown into a salad bowl. Right. Okay. And that means information travel in a hierarchical way.

Yes. For example, light hits our retina. Our retina sends neural information back to our primary cortex. Our primary cortex processes it, sends it up to... to, say, another layer, and then it keeps going up. And as the information travels, the neurons process this information in somewhat different ways. And that hierarchical processing gets you to complex intelligent capabilities.

Yes. For example, light hits our retina. Our retina sends neural information back to our primary cortex. Our primary cortex processes it, sends it up to... to, say, another layer, and then it keeps going up. And as the information travels, the neurons process this information in somewhat different ways. And that hierarchical processing gets you to complex intelligent capabilities.

Yes. For example, light hits our retina. Our retina sends neural information back to our primary cortex. Our primary cortex processes it, sends it up to... to, say, another layer, and then it keeps going up. And as the information travels, the neurons process this information in somewhat different ways. And that hierarchical processing gets you to complex intelligent capabilities.

Or this tiger sneaking up on me.

Or this tiger sneaking up on me.

Or this tiger sneaking up on me.

Yes. And how did evolution assemble us so that we can recognize all this beautiful world? Not only we can recognize, we can reason with it. We can learn from it. Many scientists have used this example is that children don't have to see too many examples of a tiger to recognize a tiger. It's not like you have to show a million tigers to children. So we learn really fast.

Yes. And how did evolution assemble us so that we can recognize all this beautiful world? Not only we can recognize, we can reason with it. We can learn from it. Many scientists have used this example is that children don't have to see too many examples of a tiger to recognize a tiger. It's not like you have to show a million tigers to children. So we learn really fast.

Yes. And how did evolution assemble us so that we can recognize all this beautiful world? Not only we can recognize, we can reason with it. We can learn from it. Many scientists have used this example is that children don't have to see too many examples of a tiger to recognize a tiger. It's not like you have to show a million tigers to children. So we learn really fast.

Exactly. So just to finish, so the neuroscientists were studying the structure of the mammalian brain and how that visual information was processed. Fast forward, that study got the Nobel Prize in the 1980s because it's such a fundamental discovery. But that inspired computer scientists.