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Fareed Zakaria GPS

Reengineering Life, the Next Frontiers in Science. Aired 10-11a ET

Aired September 01, 2024 - 10:00   ET

THIS IS A RUSH TRANSCRIPT. THIS COPY MAY NOT BE IN ITS FINAL FORM AND MAY BE UPDATED.

[10:01:14]

FAREED ZAKARIA, CNN ANCHOR: Welcome to a GPS special. "Re-engineering Life: The Next Frontiers in Science." I'm Fareed Zakaria.

(BEGIN VIDEOTAPE)

ZAKARIA (voice-over): Today on the program, I'm going to introduce you to two extraordinary women on the absolute cutting edge of science. Their work will change the world as we know it and in the process it will change your life. I'll introduce you to the so-called godmother of artificial intelligence, Fei-Fei Li.

A.I. may have only just recently burst onto your computer screen --

MAX FOSTER, CNN CORRESPONDENT: The next generation of artificial intelligence is here. It's called ChatGPT.

JAKE TAPPER, CNN ANCHOR: ChatGPT.

TOM FOREMAN, CNN CORRESPONDENT: ChatGPT is rattling the A.I. world.

ZAKARIA: But Li has been working on it for more than 20 years. You've likely seen from your searches how Silicon chips can think but can they actually see? Could a computer tell you whether this cat was calmly drinking milk or naughtily knocking it over?

Li's life work has been spent on that question and others just like it.

JENNIFER DOUDNA, PROFESSOR, UC BERKELEY, NOBEL LAUREATE IN CHEMISTRY: And I found myself fascinated by the most mysterious topic of life, which is intelligence.

ZAKARIA: I'll take you inside her lab and inside her very human intelligence.

But first, imagine doctors being able to edit your genetic code or your children's or your pets'. If you or a loved one suffered from a disease caused by an error in your DNA they could snip out the error and put in the correct code.

Well, Jennifer Doudna was the co-discoverer of just such a technology. It's called CRISPR and she won the Nobel Prize for her work on it.

FREDRICKA WHITFIELD, CNN ANCHOR: A breakthrough treatment for sickle cell disease.

KRISTIE LU STOUT, CNN CORRESPONDENT: Researchers successfully corrected a gene mutation of human embryos.

ZAKARIA: Even better, CRISPR is already saving lives.

DOUDNA: What if you could proactively recognize the genes that make somebody more likely to get Alzheimer's and you could use CRISPR to change this.

ZAKARIA: Up next, I'll tell you about its awesome possibilities and how Doudna came to her discovery.

DOUDNA: This really is the code of life. It is amazing to think that now we can read the code and then CRISPR is a way to change the code in precise ways. We can see that the capabilities of this are really powerful. I think the good to come from this is going to be profound.

What if you could recognize the genes that make somebody more likely to get Alzheimer's and you could use CRISPR to change thus? I think that's absolutely something that's possible to do.

ZAKARIA: The world we live in has been shaped by three scientific revolutions, so writes Walter Isaacson in "The Code Breaker." The first in the early 20th century was the quantum revolution. It came out of physics led by Albert Einstein, and it unleashed the power of the atom, leading to nuclear energy and weaponry.

The second was the information revolution, we all know about that, which produced the world of computers, the internet and smartphones. But the third revolution, writes Isaacson, is not about protons or neutrons or bits and bytes. It's about genes, a revolution in human biology.

[10:05:02]

It is only just beginning, and Jennifer Doudna is at the forefront of this revolution.

DOUDNA: When Martin showed me the data, I mean, both of us any, I mean, we kind of have looked at each other and said, holy smokes, you know, this is incredible.

ZAKARIA: Doudna and her colleague were right. It was incredible. They were in the process of discovering what is known as CRISPR. It's changing the world and saving lives in the process. It may even save your life.

This genetic revolution can be dated to June of 2000 when President Bill Clinton announced to the world the completion of the Human Genome Project, the uncovering of the genetic blueprint for building a human being.

BILL CLINTON, FORMER U.S. PRESIDENT: Today, we are learning the language in which God created life. ZAKARIA: CRISPR does something even more radical. It can edit that

language literally changing our genetic code. It can fix mistakes, misspellings that caused illnesses, and researchers hope one day it will be able to stop cancer in its tracks, and make you immune from viruses.

Usually the Nobel Prizes in science are awarded for discoveries that took place decades before. But just eight years after Doudna and a colleague published the first paper on the CRISPR work, they were awarded the world's most prestigious scientific trophy.

UNIDENTIFIED MALE: The Royal Swedish Academy of Sciences has today decided to award the 2020 Nobel Prize in Chemistry jointly to Emmanuelle Charpentier and Jennifer Doudna for the development of a method for genome editing.

DOUDNA: I was really tired that night and I just -- I had turned the ringer off on my phone. I just went to bed. I didn't want to think about it, you know, and then I woke up at 3:00 in the morning and my phone was just, you know, buzzing and I looked and there were like all these, you know, missed calls and a call was coming in from a reporter.

And I answered it and she said, you know, hey, Jennifer, so sorry. I know it's early, but, you know, I just want to know your reaction to the Nobel. And I said, oh, my gosh, you know, I just woke up and I don't know who won the Nobel Prize. I don't know.

(LAUGHTER)

ZAKARIA: Did you really, at that point, you didn't realize immediately?

DOUDNA: No, I didn't know. When I was growing up, I mean, you know, I just always so desperate to like somebody to let me in their lab to do experiments like I couldn't really think beyond that. So imagining that I would ever, you know, be somebody receiving prizes was -- it's not even on my radar.

I was very proud that it was a collaboration. It happened to be two women, you know, working together, which is great. And just the message that it sends to younger scientists.

ZAKARIA: Give us a sense of where does scientific creativity come from, for you?

DOUDNA: I think it often comes from making connections between things that don't seem to be connected. That was something I admired about my graduate adviser Jack Szostak. He could seemingly connect things that, you know, the rest of us would say, well, that doesn't have anything to do with that and he would say, oh, no, but it does.

ZAKARIA: And the big connection Doudna made in her career has changed medicine as we know it in great ways. And some worrying ones, too. We'll start with one of those. Let's talk about the case of the Chinese doctor. This is a totally

fascinating case. But this Chinese doctor thought he was doing something amazing that the world would laud him for. He took two kids whose parents had HIV. He edited the fertilized eggs to make them immune from HIV.

DOUDNA: That was the stated goal.

ZAKARIA: That was the stated goal.

DOUDNA: Yes, yes.

ZAKARIA: And they're born and he announces it. What was your reaction when you heard that?

DOUDNA: I was pretty shocked at the time. So that was an announcement made in late 2018 and at the time we were already three years into a very active international program to understand how CRISPR might one day be used in that type of a fashion to create edited babies. So it was quite a shock to realize that someone had in fact already done that. And had done it in a fashion that as the details, you know, emerge, that it was, you know, was really unethical.

The parents of those kids really I don't think understood what it was that was happening to their embryos. You know, and that they were working with a technology that had never been tested in that way. Kind of shocking to me.

ZAKARIA (voice-over): On the positive side, perhaps CRISPR's greatest application at the moment is for people with sickle cell disease.

DOUDNA: It's a disease that affects primarily the red blood cells in a patient.

ZAKARIA: Instead of being round as they are in healthy humans, the red blood cells in patients with the disease are shaped like sickles. Hence the name.

DOUDNA: They tend to clog arteries and cause tissue damage, and of course, great, great pain to the patients.

[10:10:05]

ZAKARIA: That pain usually starts in childhood, though that's not the worst of it. The disease is deadly, taking decades off the life expectancy of those who have it. But with genetic diseases like sickle cell, Doudna's discovery can come to the rescue. Effectively fixing a patient's DNA.

That Chinese scientist that Jennifer Doudna was talking about, the one who created the first gene edited children, well, he was put into prison in China in 2019 then released in 2022. Now he is staging a highly controversial comeback saying he wants to use gene editing in human embryos to protect people against Alzheimer's disease.

Next on this GPS special, what's the path to scientific discovery and to a Nobel Prize? I'll tell you all about Jennifer Doudna's journey to the top of her field, and the pitfalls along the way. When we come back.

(COMMERCIAL BREAK)

ZAKARIA: In 1901, the first Nobel Prizes were awarded. In the 123 years since then only eight women have won the Nobel Prize in chemistry. The legendary Marie Curie was the first. Jennifer Doudna and her co-discoverer, Emmanuelle Charpentier, were the sixth and seventh.

So what was Jennifer Doudna's journey to the prize? Take a look.

(Voice-over): Doudna's formative years in the 1970s were spent mostly in Hawaii.

DOUDNA: We grew up in a town called Hilo on the big island. It was magical. I found myself fascinated by the plants and animals, and just the environment.

[10:15:03]

And then when I was in high school, the state of Hawaii had a program for high school kids where they brought in experts from around the state who worked in different areas of science and one of the experts who came in was a cancer biologist and she explained that her research -- that she was a biochemist and that she studied how normal cells become -- in our body become cancerous.

ZAKARIA: How old were you when this happened?

DOUDNA: I was probably 15 years old, 14, 15, something like that.

ZAKARIA: But you remember it very well.

DOUDNA: I do. I just have this sense I want to do that. That's exactly what I want to do with my life. And I started to imagine, what if I could -- what if I could be a scientist? And it sounded so exotic, you know. I didn't even know any. I knew no women or girls who were doing science really.

ZAKARIA: So you didn't get discouraged by the idea that there were no women. You thought it was kind of exciting and novel.

DOUDNA: I did. It tells you a little about my personality, you know. If somebody tells me I can't do something, it makes me want to do it more.

ZAKARIA: So when you applied to college, are you thinking to yourself, I now want to be a scientist and so I want to go somewhere which is good in science.

DOUDNA: I was. Yes. I was thinking that. And in fact, I was even more specific than that because I had already seen this lecture by the biochemist and I thought I want to be a biochemist.

ZAKARIA: Wow.

DOUDNA: You know, it's one of the great mysteries. Why are we drawn to the things we're drawn to?

ZAKARIA: Right.

DOUDNA: Why do we find particular things interests and it's kind of almost unanswerable, but in my case, even back when I was in high school, you know, I was fascinated by understanding life at a chemical level. I really wanted to understand the chemicals that were involved, the molecules including DNA, of course.

ZAKARIA (voice-over): A little refresher on DNA in case you forgot your high school biology lesson. Deoxyribonucleic Acid is the code of life. It makes us who we are and to find it, you have to go all the way down to the molecular level. Your DNA is what tells your body to produce cells that determined your eye color or your hair texture, or even how certain food taste you.

If you look just like your mother or father, that's your DNA shining through, too. The DNA code is made up of four letters. A's, C's, G's, and T's. And when those letters are strung together, they instruct the body as to what to do. Sometimes, though, there is an error, literally a misspelling of the genetic code. And wrong letters make for bad instructions given to the body, which then creates problems like sickle cells.

Fascinated by all things DNA, as well as its chemical cousin, RNA, Doudna enrolled at Pomona College in Southern California where you might expect that she sailed through. But --

DOUDNA: It was hard for me. I was studying hard and I wasn't doing as well as I wanted. And I questioned myself. I said, gosh, do I really have the ability to do this? I did explore other options, including, you know, talking to my French professor at one point about, you know, should I switch my major to French? You know, the language is so beautiful, and she said, well, what's your major now, and I said chemistry. And she said, oh, God, stick with chemistry.

ZAKARIA: She stuck with it. And the next stop was graduate school at Harvard.

In your story, you have these moments that human push of people who believed in you and encouraged you was very important.

DOUDNA: Very important. Yes. All along the way for me. There were all these moments where I had doubts, doubts about myself. I was working in the lab of Jack Szostak, who was widely known around Harvard at the time to be a genius and to be, you know, somebody who is on track to win a Nobel Prize. I was kind of suitably, suitably intimidated by him.

And one day he walked past all the many -- much more experienced people who are working in the lab, came to my desk and he said, you know, Jennifer, I was thinking about an experiment last night and I wanted to see if you think it's a good idea. I was stunned. He is asking my opinion? But, you know, I've never forgotten that because it's the kind of interaction that I think really builds the confidence of a young student, and made me feel empowered.

ZAKARIA (voice-over): Doudna's next stop was Yale, then Berkeley.

And you turned down essentially the chaired professorship at Harvard to come to Berkeley, partly because it's a public institution, right?

DOUDNA: Right. I really believe in the mission of Berkeley. It's an extraordinary place in its own right, but it also has a really interesting mission, which is to bring education to everyone, to people around the world from -- no matter what their background is, if they are smart and they want to work hard and they want to come and learn, Berkeley wants to open its doors to them.

[10:20:04]

ZAKARIA (voice-over): And it was within those doors where Doudna began the work that would win her the most famous prize in science.

So when does CRISPR begin for you? if you were to date it, is there a moment?

DOUDNA: Oh, there's a moment. Yes.

ZAKARIA (voice-over): That moment was another life-changing phone call for Jenniver Doudna. A fellow biochemistry professor at Berkeley named Jillian Banfield needed some help.

So she's looking for somebody who understands RNA and is at Berkeley, and she literally does a Google Search.

DOUDNA: Yes.

ZAKARIA: RNA, Berkeley, and your name comes up.

DOUDNA: My name pops up, right? And so we met at the Free Speech Movement Cafe here at Berkeley, and she was very effusive and she's showing me her data, and saying, you know, here's my hypothesis and here's why I think it, I think it makes sense, but she had discovered that bacteria could acquire little pieces of DNA from viruses that infect them. And those little pieces of DNA could be stored in a special location in the bacterial chromosome called CRISPR.

And so she was basically trying to sell me on this idea that, you know, this could be very interesting. And maybe we should try to do an experiment. And of course it, you know, worked.

(LAUGHTER)

ZAKARIA (voice-over): From there, Doudna teamed up with Charpentier and began to uncover CRISPR's amazing ability to fix DNA.

So how does it work? Well, this is truly extraordinary. Doctors can extract stem cells. Those are the cells that help the body refresh itself and turn into blood cells or muscle cells, or skin cells. Those stem cells can then be introduced to the CRISPR system in a test tube. Then the RNA guides the system to find the problematic sequence it is looking for in the DNA. Maybe it says TGC when it should say TGT.

When the system finds the error it opens the DNA helix and uses tiny molecular blades to cut out the bad sequence, and then the proper sequence can be pasted in.

DOUDNA: And then those edited cells are then replaced into the patient and they are effectively cured.

ZAKARIA: What are the diseases you're most hopeful for, for CRISPR?

DOUDNA: In the short term, clearly, you know, things like sickle cell disease, eye diseases, other blood disorders.

ZAKARIA (voice-over): And it's not just human genes that can be fixed. The possibilities are endless. Your pet may be saved. And perhaps the planet as well.

DOUDNA: Though these are some rice plants that are growing in addition, you can look at these and you can immediately see a difference, right?

ZAKARIA: Right.

DOUDNA: These rice plants are white. Tesse rice plants are green. Now why is that? Well, these plants, the white ones, have been edited to remove a single gene that creates the green color. So you can see visually the effects of genome editing. And here's a cool thing, so you noticed that otherwise they look pretty similar, right? I mean, these look healthy. There are about as tall and they have the same shape and everything else about them. It looks very similar.

It's just that there are different color. And so this is showing you the precision of a technology like this, right? We're not messing up a lot of genes. We're not changing a lot of things about the other properties of these plants. They're just affecting one trait.

ZAKARIA (voice-over): Why should we care about rice? Well, it's one of humanity's biggest sources of protein but it has big downsides. Rice and cows are the two biggest food-related emitters of methane, a main cause of climate change. And rice needs massive amounts of water to grow.

One of Jennifer's colleagues at UC Davis is making great strides toward fixing both of these problems and this may be the beginning of a new agricultural revolution, creating a sustainable way to feed the estimated nine billion humans who will inhabit the world in just 15 years.

DOUDNA: She's already been able to use CRISPR to make drought resistant rice and we're on the path also to dealing with the other problem of rice, which is methane emissions. So we're very excited about the potential to use CRISPR in that fashion because I think that, you know, climate change is clearly going to require all of us to be very innovative in the ways that we address basically many different aspects of our current environment that are leading to increased carbon released in the atmosphere.

(END VIDEOTAPE)

ZAKARIA: Next, from the extraordinary use of CRISPR to the extraordinary conflicts around it. Patent fights, lawsuits, and the frightening future that Vladmir Putin says CRISPR could bring.

(COMMERCIAL BREAK)

[10:28:50]

ZAKARIA: So what happens after you make a revolutionary scientific discovery like CRISPR, a way of editing genes? Well, it's not all celebration and awards as Nobel Laureate Jennifer Doudna explains.

(BEGIN VIDEOTAPE)

ZAKARIA (voice-over): As brilliant as she is, Doudna wasn't prepared for what came next after word of her discovery and its commercial possibilities started to filter out.

DOUDNA: I kind of just had no idea, you know, what was going to happen once there was a widespread appreciation that CRISPR was a very useful technology and probably going to be a very, you know, financially valuable technology as well.

ZAKARIA: There has been a crazy amount of competition.

DOUDNA: Yes.

ZAKARIA: There was competition about who is going to file the patent first, who did file the patent first.

DOUDNA: Yes.

ZAKARIA: And there's been lawsuits out of all of that. Was that a shock to you when all that happened?

DOUDNA: I didn't realize the intensity of that kind of competition that was going to come at me. Had never experienced something like that before. And certainly, you know, science can be competitive, right?

ZAKARIA: It was a moment where you walk away from a company in which you had a fairly large stake. I mean, that must have been a moment of great frustration.

[10:30:04]

DOUDNA: I felt when I did make that decision to walk away, I felt empowered. You know, I got into science because I love the scientific discovery process. I love working with interesting things, smart people. I didn't get into science to, you know, to get rich or to be famous room.

ZAKARIA (voice-over): But CRISPR is undeniably big business. According to one analysis, the global market for editing genes is projected to be worth $40 billion a year by 2033. Add big money to the big new frontiers of science and you get big problems.

None less than Vladimir Putin has warned of something worse than a nuclear bomb if humans were to edit the genetic code to create a soldier who can fight without fear, regret or pain.

I mean, do you worry about that? Because it does seem like it would be very possible. It's a direct application of the technology.

DOUDNA: Well, yes and no. I mean, it's possible in principle, but, you know, the reality is that I think that would be extremely hard to do and it would obviously take a long time if you were really good.

ZAKARIA: Yes. Just start at the embryos.

DOUDNA: Right. Yes. It didn't take a while. So I don't --

ZAKARIA: But parents could certainly choose --

DOUDNA: But parents could --

ZAKARIA: -- children who are --

DOUDNA: They could.

ZAKARIA: Blond or, you know, all kinds of things.

DOUDNA: They could in principle, yes. And you may know that already in invitro fertilization clinics that, you know, some of them at least allow parents the opportunity to choose the sex of their child.

ZAKARIA: Right. Right.

DOUDNA: As well as to screen for genetic traits and diseases and things like that.

ZAKARIA: Right.

DOUDNA: So to me it's just, you know, one more step to say, well, now let's offer a menu of things that, you know, this technology could enable. Is that going to happen anytime soon? I don't really think so. At least I hope not.

ZAKARIA (voice-over): Even without Vladimir Putin, the procedure is not without potential pitfalls.

Does there still leave the possibility of unintended consequences?

DOUDNA: It does. Sure. With a technology like this, there's always a risk that at some low level CRISPR is acting at a place that you don't want it to be making a change or causing the DNA to do something that you don't want, such as recombine in ways that could actually cause cancer.

ZAKARIA: Right. DOUDNA: That's one of the risks.

ZAKARIA: I mean, of all the scientists working in the world, it feels to me like since the invention of nuclear energy, there is that feeling of, have I created a Frankenstein that could be used for things that are, you know, just completely change human beings?

DOUDNA: Well, that's one way to look at it. I guess I tend to think about it as a very enabling tool that allows us to make changes to DNA that can cure disease in individuals. I think about it that way.

ZAKARIA: So you're pretty confident that there's enormous upside but there is downside.

DOUDNA: Yes. Well, isn't that true with any technology? I think -- you know, I would argue that artificial intelligence is in that category, nuclear energy for sure. I think a lot of technologies, if they have real -- they offer real opportunity that's kind of transformative, there's also risk associated with it.

To me, you're never going to put this back in a box. You're never going to undiscover it, right? So we have to just embrace it. We have to understand it, and we have to figure out how to work with it responsibly.

ZAKARIA: So at this point, you could just be an icon if you wanted, right? I mean, you have won literally every prize there is to win. Also the commercial aspect of CRISPR. So you could sit back. Have you ever thought about that?

DOUDNA: Not for a second.

(LAUGHTER)

ZAKARIA: Really?

DOUDNA: No. That would be very much not my personality.

ZAKARIA: So the first line of your obituary has already been written. And it's CRISPR. What is the second line? What would you like it to be?

DOUDNA: Yes, I certainly would like to be remembered as someone who valued collaboration. I love building teams, I love working in teams, and I'd like to think that I will be numbered as someone who really tried to advance science and scientists by supporting the next- generation. You know, encouraging students of science to reach for the stars.

(END VIDEOTAPE)

ZAKARIA: My thanks to Jennifer Doudna for sharing her extraordinary story. By the way, if this CRISPR business feels only theoretical to you, it's not. There's great news for people who suffer from all kinds of sicknesses starting with sickle cell. In December, the FDA approved the CRISPR based gene editing therapy for the disease. The less good news is that it is so revolutionary that most of the

world might not be able to afford it. The sticker price for Casgevy is $2.2 million. Yes. Million. But American insurers, both private and public, could help and hopefully with time, prices for such lifesaving therapies will come down, way down.

[10:35:09]

Next on this GPS special, I'll introduce you to another extraordinary scientist. Fei-Fei Li. She is known as the godmother of A.I. and I have a fascinating conversation with her about just how computers think. For example, when you see this picture. You instantly know what's going on. But how could a computer know whether this cat is seeking a sip of milk or mischievously knocking the milk over. Find out, when we come back.

(COMMERCIAL BREAK)

ZAKARIA: Welcome back to "Reengineering Life: The Next Frontiers in Science."

Artificial intelligence is the next great technological revolution and it's become a relatively regular part of many of our lives.

(BEGIN VIDEO CLIP)

UNIDENTIFIED FEMALE: Head northeast on 10th Avenue toward West 33rd Street.

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ZAKARIA: But the next great frontier for A.I. is so-called spatial intelligence. How does a Silicon chip or a series of Silicon chips understand the physical world? How can it tell what's happening in a still picture or a video or a live stream from a camera mounted on a robot? Well, almost 20 years ago, my next guest, the computer scientist Fei-Fei Li started working on this. She created a dataset containing millions and millions of annotated images. This image data was then used to train A.I.'s vision to learn how to recognize and categorize different objects in the world.

Known as the godmother of modern A.I., Fei-Fei Li is a professor in the Computer Science Department at Stanford University, and the co- director of Stanford's Human-Centered A.I. institute.

[10:40:11]

(BEGIN VIDEOTAPE)

ZAKARIA: When did you first realize that you were interested in computers as an academic field?

FEI-FEI LI, PROFESSOR, STANFORD UNIVERSITY: My first love was not computers. My first love was physics. Even in my preteen years, I, you know, took physics for the first time as a middle-schooler and just fell in love with, you know, the mathematical way of understanding the natural world. And then as I start to major in physics in college, I went to Princeton, the Mecca of physics in my mind at that time, like you said, it was the audacity of asking the most fundamental questions about the universe.

As audacious as what is the origin of the universe? What is space time? You know, and what is the smallest sub-atomic structure of the world? So that was my first love. And you can still hear me. I still love physics, but what really turned me into the world of intelligence is I follow the footsteps of the great minds of physics in the early 20th Century, people like Albert Einstein, people like Schrodinger, and physicists like Roger Penrose.

Towards the second half of their career, they wrote beyond the physical world. They wrote, they pondered about other audacious questions, like life. And I -- it really opened my eyes around my I think third year in college and realized audacious questions about the universe doesn't have to be just atomic of physical world. It can be about life and I found myself fascinated by the most mysterious topic of life, which is intelligence.

ZAKARIA: How does the human brain work.

LI: Right. How does the -- how does, you know, the molecules and cells and eventually emerged into the most intricate machine of the universe, which is the mind. And how do you make computer minds? You know, Richard Feynman said the best way of learning something is to make it, right? Like I realized, to ask the question about what is intelligence, one way to ask that question is to build intelligence, is to make machines intelligent. And that duality of understanding and creating just fundamentally fascinated me.

ZAKARIA: So when people thought about computer as being able to think like human beings, there was a lot of speculation that took place in the '50s and '60s.

LI: Yes.

ZAKARIA: And people who were almost doing sci-fi were thinking about it. But it never seemed to go anywhere. What changed and what got us on to the path of artificial intelligence?

LI: The very quest for thinking computers started in some date as early as '40s but definitely Alan Turing dared humanity with the question, can machines think? And then you come to many people are trivial to the steamy summer of 1959 in Dartmouth College that the founding fathers of artificial intelligence came together and kind of establish the field, right? It's around that time.

They coined the name artificial intelligence and it started off as a field with very audacious goal, which is really build sinking machines. Machines that can behave as intelligently like human brains can. But that ambitious goal was met with years and years of trying and failure, trying and failure like any field has, right? But fast forward, I think the real inflection moment of artificial intelligence, especially to today, it's around the end of the first decade of 21st century, so it's around 2010. Three things converged around 2010 and that was the birth of modern A.I.

ZAKARIA (voice-over): What were those three things? First, Li says, the advent of extremely powerful computer chips, capable of carrying out a dizzying number of processes simultaneously.

[10:45:06]

Second, these new chips allowed for great progress to be made on something called neural networks. That is an A.I. model that teaches computers how to process data and make decisions. It uses the human brain and its network of neurons as a model. And third, people like Fei-Fei Li realized they needed to feed the A.I. massive amounts of data so that these neural networks could start learning.

Li says that once you feed the A.I. all of this data and once it learns the patterns, it can start doing the kind of tasks that come naturally to humans. And that is where we will pick up the story and we'll also tell you why this cat photo is so critical to understanding it all, when we come back.

(END VIDEOTAPE)

(COMMERCIAL BREAK)

ZAKARIA: You might be wondering why my guest Fei-Fei Li is called the godmother of A.I. Well, we now know that artificial intelligence needs to be fed massive amounts of data to help it begin to understand the world. If you want A.I., for instance, to understand how the English language is written, you feed it reams and reams of books and articles for it to ingest and digest. Li and her team discovered A.I.'s great hunger for data and try to satisfy its needs. She picks up the story there.

[10:50:00]

(BEGIN VIDEOTAPE)

LI: So we decided, because I was in a field of computer vision, that the audacious goal here is to get all pictures from the world. In 2007, the internet still feels small enough that I thought we can get all, all visual imageries of the world so we downloaded billions of pictures and clearly that's the sub-corner of the internet. But we got inspired by linguistics, research and organized all of the visual concepts into 22,000 categories and across 15 million images.

And it became such a huge dataset that was orders of magnitude bigger than any other dataset. It took us three years to make it. And then they took three years for the community to accept it. But after that long journey, that the fall of 2012, when we got what we saw the image that challenged results was what people think is the beginning of modern A.I.

ZAKARIA: Your own work has focused on a very specific and important piece of this. Maybe even central piece of this, which is how do we computers see.

LI: Yes.

ZAKARIA: And you have this example that you give of a cat, an image of a cat, where the cat clearly to a human being is tipping over a glass of milk.

LI: Yes.

ZAKARIA: But you said that the computer -- you know, it found very difficult to figure out whether it was trying to drink the milk or tip it over. Tell us about this issue. Why is it -- why is the brains so good at figuring out very quickly the context of an image like that?

LI: So in the world of artificial intelligence, we actually have specialized areas and the world has seen ChatGPT and many of the natural language progress. There is another huge area of research that mimics the visual perceptual function of humans. We call it computer vision. And my specialty is in computer vision.

Why am I so excited by this? Is because I believe visual intelligence is a cornerstone of intelligence as a whole. If you look at evolution, the majority of the entire history of animal intelligence all the way to humans has nothing to do with language. It's about seeing the world and interacting with the world, and that cat touching or about to touch a glass of milk, whether it's drinking the milk or trying to topple it down from the table, it's deeply visual and spatial.

And that's what evolution has figured out with our visual brain is the understanding of the world and the perceptual tasks we need to do. We continue to rely on visual intelligence to do everything, you know, to drive, to cook a meal, to build a machine, to construct cities, to discover the structure of DNA, to draw masterpiece of art. So much of our human intelligence, our activities, our ingenuity, our communication, our entertainment rely on vision.

ZAKARIA: Where does it go next? What do you think of the frontiers of A.I.?

LI: Well, the frontier of A.I. for me is what I call a spatial intelligence because that example of the cat and computers still struggle to fully understand and also generate the 3-D structure of that world of cat and glass of milk is what I think will be very exciting to work on because once we have figured out how to connect the physical world with the digital world, we can empower robots.

ZAKARIA: In a sense, it seems to me what you're saying is, you know, so far, particularly with the large language models, A.I. has been a kind of text to text operation.

LI: Yes.

ZAKARIA: You ask ChatGPT a question, it gives you an answer.

LI: Yes.

ZAKARIA: Eventually what you -- would be mind-blowing is if it can do texts to action, right? You tell the computer and it actually does things in the physical world and can do them better than human, right?

LI: Yes. Right. Text to action, image to action, video, to action, action to action. You know, there's a lot more that's coming.

ZAKARIA: How do you keep the human in the center if the machine is going to be so much better at it than the human?

[10:55:00]

LI: That's a great question. And for the record, I didn't say the machine is going to be universally better than humans. I actually think machines and humans can be deeply collaborative. We are already collaborated with machines. Think about you come here by driving a car. That is a deep collaboration between you and the machine. And in fact, even today's guy, even if it's not L-4 self-driving car, it actually has a computer.

It has some level of intelligence, you know, so our civilization has been always on the quest of creating machines to collaborate with us because we want to do better, we will have live longer, we will have better health. We want to, you know, be more productive. And A.I. is just going to continue to make that happen. So you're right, with more and more powerful intelligent machines that relationship between humans and intelligent machines is to be explored.

For example, if the machine has the ability to decide how to distribute a pot of money, let's just say that, right? Should we trust -- entrust the machine to do that? Or how much human agency and governance or control we should have? These are simultaneously technical questions, as well as social questions. So as a technologist, just because I'm part of the effort of making this technology happened, doesn't mean I want this technology to take over human society. I want this technology to help humans.

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ZAKARIA: My thanks to Jennifer Doudna and Fei-Fei Li for their contributions to progress in this world and for taking the time to talk to me about their work.

And thanks to all of you for watching this GPS special. We'll be back on GPS next Sunday at 10:00 a.m. Eastern and Pacific.

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