Speaker 1: Bloomberg Audio Studios, podcasts, radio news.
Speaker 2: I was always a curious kid. I wasn't curious about
Speaker 2: nightclubs or her or other things. I was an avid
Speaker 2: lover of science.
Speaker 1: Faith a Lee Tech CEO, Stanford professor and godmother of AI.
Speaker 1: Are you conscious of the power that you have?
Speaker 2: I'm conscious of my responsibility. I understand. I'm one of
Speaker 2: the people who brought this technology to our world. The
Speaker 2: agency is not the machines, It's ours.
Speaker 1: From Bloomberg Weekend. This is the Michelle Hussein Show. I'm
Speaker 1: Michelle Hussein. Have you ever thought about where AI came from?
Speaker 1: The origin story of tools like Chat, GPT, Claude, or Gemini,
Speaker 1: which are part of many people's everyday lives. I don't
Speaker 1: mean the principle of training large language models on data,
Speaker 1: but the long, often lonely work of the scientists who
Speaker 1: believed years ago that you could teach machines to be intelligent. Well,
Speaker 1: today's guest has lived that story because she was at
Speaker 1: the forefront of unlocking this world for us all, and
Speaker 1: she has a deeply resonant personal story. She was fifteen
Speaker 1: when she came to the US from China with her parents.
Speaker 1: She had little English life was hard, money incredibly tight,
Speaker 1: but she excelled at school and set herself audacious problems
Speaker 1: to solve. Her name is fay fe Lee, and by
Speaker 1: the end of our conversation, I was asking myself, why
Speaker 1: do most people know the name Sam Aortman and not hers.
Speaker 1: She's the one whose breakthrough was critical, No wonder they
Speaker 1: call her the godmother of AI.
Speaker 2: We ended up.
Speaker 1: Talking about everything from her own childhood to yes, whether
Speaker 1: AI will do away with us humans, and what we
Speaker 1: should teach the kids of today. Her answer on that
Speaker 1: might just surprise you, but I hope you enjoy our
Speaker 1: conversation as much as I did. Doctor fay fe Lee,
Speaker 1: thank you for coming on the show. I'd love to
Speaker 1: start with this remarkable period for your industry. It's three
Speaker 1: years since chat GPT was released to the public, and
Speaker 1: since then there have been new vehicles, new apps, huge
Speaker 1: amounts of investment flowing towards the industry. How does this
Speaker 1: moment feel to you?
Speaker 2: Well, first of all, Michelle, thank you for inviting me
Speaker 2: to this show. I'm very excited. It's a good question
Speaker 2: because AI is not new to me. I've been in
Speaker 2: this field for twenty five years. I live and breathe
Speaker 2: it every day since the beginning of my career. Yet
Speaker 2: this moment is still as daunting and almost surreal to
Speaker 2: me in terms of its massive, profound impact. This is
Speaker 2: a civilizational technology, and it's surreal personally to me because
Speaker 2: I'm part of the group of scientists that made this happen,
Speaker 2: and clearly I did not expect it'll be this massive.
Speaker 1: When was the moment it changed? Because I know you've
Speaker 1: talked about the years when it was like an AI
Speaker 1: winter and what you're describing now, how the moment feels
Speaker 1: extraordinary even to you. Is it because of the pace
Speaker 1: of developments or is it because the world has woken
Speaker 1: up to it and therefore turned the spotlight on people
Speaker 1: like you.
Speaker 2: I think it's intertwined, right, But for me to define
Speaker 2: this as a civilizational technology is not about spotlight. It's
Speaker 2: not even about how powerful it is, is about how
Speaker 2: many people it impacts. Everyone's life work, while being future
Speaker 2: will somehow be touched by or impacted by AI.
Speaker 1: In bad ways as well as good.
Speaker 2: What technology is a dubba sword?
Speaker 1: Right?
Speaker 2: Yes? I think both ways, Because since the dawn of
Speaker 2: human civilization, we create tools we call technologies and these
Speaker 2: tools are meant in general for doing good things, but
Speaker 2: along the way we might intentionally use it in the
Speaker 2: wrong way, or we might have unintended consequences.
Speaker 1: And strands of this I know will emerge in different
Speaker 1: ways over the course of this conversation. But you said
Speaker 1: the word power, and I'm struck by the fact that
Speaker 1: the power of this technology is in the hands of
Speaker 1: a very small number of companies, most of them American.
Speaker 1: How does that sit with you?
Speaker 2: You're right, the major tech companies, through their massively reaching products,
Speaker 2: they are impacting globally our society the most. I would
Speaker 2: personally like to see this technology being much more democratized.
Speaker 2: I would like to see no matter who builds or
Speaker 2: holds the profound impact of this technology, do it in
Speaker 2: a responsible way. And I also do believe every individual
Speaker 2: in this era should feel they have the agency to
Speaker 2: impact this technology.
Speaker 1: We'll talk a bit more in a moment. I think
Speaker 1: about the democratization and how that might be achieved. But you,
Speaker 1: of course, in terms of companies in this field, you're
Speaker 1: part of that because you are a tech CEO as
Speaker 1: well as an academic. In fact, I think you're very
Speaker 1: young company, little more than a year old is reportedly
Speaker 1: already worth a billion dollars.
Speaker 2: Yes, co founder CEO of war Laps, and we are
Speaker 2: building the next frontier of AI, which is spatial intelligence,
Speaker 2: which people don't hear too much about today because we're
Speaker 2: all about large language models. Yet I believe spatial intelligence
Speaker 2: is as critical and complimentary to language intelligence.
Speaker 1: Releasing this idea of virtual world, which again we'll dig into.
Speaker 1: But before we do that, I want you to take
Speaker 1: us back again to the fact that you've seen the
Speaker 1: whole trajectory of this industry. You've been in it for
Speaker 1: twenty five years. I know that your first academic love
Speaker 1: was physics. Yes, what was it in the life or
Speaker 1: work of the physicists you most admire that made you
Speaker 1: think beyond that particular field.
Speaker 2: I grew up in a it's not a small town,
Speaker 2: but it's a less well known city in China, and
Speaker 2: I come from a small family, so you could say
Speaker 2: life was small in the sense it was in the
Speaker 2: eighties my childhood, which is fairly simple and isolated. You're
Speaker 2: a child I was, and my family in general is
Speaker 2: just small. Physics is almost the opposite. It's vast, it's audacious,
Speaker 2: The imagination is unbounded. You look up in the sky,
Speaker 2: you can ponder about the beginning of the universe. You
Speaker 2: look at a piece of a snowflake, you can zoom
Speaker 2: into the molecular structure of the matters you think about time,
Speaker 2: you think about magnetic field, you think about nuclear It
Speaker 2: takes my imagination to places that you can never be
Speaker 2: in this world. And what really fundamentally fascinates me to
Speaker 2: this day about physics is not be afraid of asking
Speaker 2: the most boldest audacious question about our physical world, of
Speaker 2: our universe, of where we come from.
Speaker 1: But your audacious question, I think, was about what is intelligence?
Speaker 2: Yes, And I think it's rooted in my love for
Speaker 2: physics and my training in physics that I look at
Speaker 2: each physicist I admire, look at their audacious question, right
Speaker 2: from Newton to Maxwell, to Schrodinger to i Instell, my
Speaker 2: favorite physicist, and I wanted to find my own audacious question.
Speaker 2: And somewhere in the middle of college, my audacious question
Speaker 2: shifted from physical matters to intelligence.
Speaker 3: What is it?
Speaker 2: How does it come about? And most fascinatingly, how do
Speaker 2: we build intelligent machines? And that became my quest Minor Star.
Speaker 1: And that's quantumly because from machines that were doing calculations
Speaker 1: and computations, you're really talking about machines that learn and
Speaker 1: that are constantly learning.
Speaker 2: I like you use the physics pun the quantum leap.
Speaker 1: Crossing over into into ordinary parlance. But I think, didn't
Speaker 1: you have this light bulb moment as you're thinking about
Speaker 1: intelligence you realize that a critical part of that is
Speaker 1: our ability to recognize objects. The fact that around us
Speaker 1: right now there are multiple objects, we know what they are.
Speaker 2: The ability that humans have about recognizing objects in the
Speaker 2: world is foundational. So I decided that was my first
Speaker 2: love start my PhD dissertation is to build machine algorithms
Speaker 2: to recognize as meaning objects as possible.
Speaker 1: I think the key question is how right how do
Speaker 1: you teach the machines? And what I found really interesting
Speaker 1: about your background is that you are reading very widely
Speaker 1: and there are two key breakthroughs that make your ultimate
Speaker 1: breakthrough possible. And one is that you start thinking and
Speaker 1: learning about what psychologists and linguists are saying that it's
Speaker 1: really to your field.
Speaker 2: Well, that's the beauty of doing science at the forefront,
Speaker 2: because it's you. No one knows how to do it.
Speaker 2: As an AI scientist, you look for possible answers, and
Speaker 2: it's pretty natural to look at human brain and human
Speaker 2: mind and try to understand or be inspired by what
Speaker 2: humans can do. And one of the inspirations I got
Speaker 2: in my early days of studying or trying to unlock
Speaker 2: this visual intelligence problem is look at how our visual
Speaker 2: semantic space is structured. There are so many tens and
Speaker 2: thousands and millions of objects in the world. How are
Speaker 2: they organized? Are they organized by alphabets or are they
Speaker 2: organized by size or colors?
Speaker 1: And you're asking that because you have to understand how
Speaker 1: our brains organize in order to have something to teach
Speaker 1: the computers.
Speaker 2: That's one way to think about it. And I come
Speaker 2: upon this linguistic work call word net word that is
Speaker 2: a way to organize semantic concepts, not visual, just semantic
Speaker 2: or words in a particular taxonomy.
Speaker 1: Give me an example.
Speaker 2: An example is in a dictionary, an apple and an
Speaker 2: appliance are very close together, but in real life, an
Speaker 2: apple and a pair a much closer to each other,
Speaker 2: and an apple and pair both belong to fruits, whereas
Speaker 2: an appliance belong to a whole different family of objects
Speaker 2: and I came upon this taxonomy called word net that
Speaker 2: describes this organization of objects, and I made a connection
Speaker 2: in my head. Is that two things is very clear.
Speaker 2: One is that this could be the way visual concepts
Speaker 2: are organized, because apples and pairs are much more connected
Speaker 2: than apples and wash machines, for example. But also even
Speaker 2: more importantly is the scale. Is that if you look
Speaker 2: at the number of objects described by language, realize how
Speaker 2: vast it is, how big it is. And that was
Speaker 2: a particular epiphany for me. We as intelligent animals, as humans,
Speaker 2: we experienced the world with massive amount of data, and
Speaker 2: we need to endow machines with that ability.
Speaker 1: Hence the big data sets needed. And actually it's worth
Speaker 1: noting that at that time, I think this is early
Speaker 1: part of the century, the idea of big data two
Speaker 1: thousand and six exists.
Speaker 2: No big data was not this phrase did not even exist.
Speaker 2: The kind of scientific data sets we were playing with
Speaker 2: were tiny. For example, in images, most of the graduate
Speaker 2: students in my era were playing with data sets of
Speaker 2: four or six or at most twenty object classes each
Speaker 2: class there were a couple of hundred examples and most
Speaker 2: and that's how tiny it is. Whereas fast forward three
Speaker 2: years later, after we created image that it had twenty
Speaker 2: two thousand classes of objects and fifteen million annotated image.
Speaker 1: And image net was a huge breakthrough. It's the reason
Speaker 1: that you've been called the godmother of AI. I'd love
Speaker 1: to understand more about what it is about you that
Speaker 1: enabled you to make these connections and see things that
Speaker 1: other scientists didn't. And one that immediately comes to mind
Speaker 1: is that you acquired English as a second language after
Speaker 1: you moved to the United States. Is there something in
Speaker 1: that that led to what you're describing.
Speaker 2: Michelle, that's a great question. I've been asked this question,
Speaker 2: and my true answers I don't know. Human creativity is
Speaker 2: still such a mystery. People talk about AI doing everything,
Speaker 2: and I disagree. There's so much about the mystery of
Speaker 2: human mind that we don't know. So I can only
Speaker 2: conjecture that a combination of my interest and my experiences
Speaker 2: led to this, including the curiosity and the hunger for
Speaker 2: audacious problem definition I find myself. I'm not afraid of
Speaker 2: asking crazy questions in science, not afraid of seeking solutions
Speaker 2: that's out of box. And maybe my appreciation for the
Speaker 2: linguistic link with vision might be accenterated by my own
Speaker 2: journey of learning the different language. But I don't know
Speaker 2: the answer.
Speaker 1: What was it like coming to the United States as
Speaker 1: a teenager, because I think that's a particularly difficult stage
Speaker 1: in life to move and to have to make new friends,
Speaker 1: even if you weren't battling a language barrier.
Speaker 2: That was hard, I think being an immigrant. And I
Speaker 2: came to this country when I was fifteen in New Jersey. Parcipitately,
Speaker 2: in New Jersey, none of us, my parents nor I
Speaker 2: spoke much English at all. I was young enough to
Speaker 2: learn more quickly. It was very hard for my parents,
Speaker 2: and we were not financially very well at all. My
Speaker 2: parents were doing cashier jobs and I was doing Chinese
Speaker 2: restaurant jobs. Eventually, by the time I entered college, also,
Speaker 2: my mom's health was not so good. So my family
Speaker 2: and I decided we have to run this little dry
Speaker 2: cleaner shop in New Jersey to make some money to survive, right,
Speaker 2: And you got involved yourself, I joked, I was the CEO.
Speaker 2: I ran the dry cleaner shop for seven years from
Speaker 2: what age I was eighteen nineteen to the middle of
Speaker 2: my graduate school, so all the way through college and
Speaker 2: graduate school, seven years, even when you're at a distance
Speaker 2: you're running your parents strike cleaning business. Yes, because I
Speaker 2: was the one who speak English, so I take all
Speaker 2: the customer phone calls, I deal with the building, I
Speaker 2: deal with inspections or the business. What did it teach
Speaker 2: you resilience? As a scientist, you have to be resilient
Speaker 2: because science is a nonlinear journey. Nobody has one conjecture
Speaker 2: and all the solutions in front of you. You have
Speaker 2: to go through such a challenge to arrive and find
Speaker 2: an answer. And as an immigrant you learn to be resilient.
Speaker 1: Were your parents pushing you because they clearly wanted a
Speaker 1: better life for you, That's why they left China for
Speaker 1: the United States. So how much of this was coming
Speaker 1: from them and how much from your own sense of
Speaker 1: responsibility to them.
Speaker 2: To their credit, they did not push me much. They're
Speaker 2: not tiger parents in today's language. I think part of
Speaker 2: it is they're just trying to survive, to be honest,
Speaker 2: and especially my mom, she is an intellectual at heart,
Speaker 2: she loves reading, but the combination of a tough, survival
Speaker 2: driven immigration life plus her health issues, she was not
Speaker 2: pushing me at all. As a teenager, I kind of
Speaker 2: had no choice. I either have to make it or
Speaker 2: not make it, and the stakes are pretty high. So
Speaker 2: I was pretty self motivated. I was just curious. I
Speaker 2: was always a curious kid, and my curiosity had an outlet,
Speaker 2: which was science, and that really grounded me. I wasn't
Speaker 2: curious about nightclubs or other things. I was an avid
Speaker 2: lover of science.
Speaker 1: But I also going to avid reader that from your
Speaker 1: early childhood, you're putting away the children's books, tanning towards
Speaker 1: the classics, the drawn up books.
Speaker 2: My mom liked reading, and she probably thought that you're
Speaker 2: talking about when I was nine ten. At that time,
Speaker 2: she probably did have influence more influenced. She thought I
Speaker 2: was precocious enough that just read some grown up books.
Speaker 1: You also had a teacher who is really important in
Speaker 1: your life. Tell me about him.
Speaker 2: I excelled in math, and I liked math, and I
Speaker 2: befriended the head teacher, mister Bob Sabella. And the math teacher,
Speaker 2: we became friends through the mutual love of science fiction reading, and.
Speaker 1: We start read in Chinese.
Speaker 2: At that time, I was reading in Chinese. Eventually I
Speaker 2: started reading English. He's a remarkable person because he probably
Speaker 2: saw in me this desire to learn, so he went
Speaker 2: out of his way to create opportunity for me to
Speaker 2: continue to excel in math. I remembered I placed out
Speaker 2: of the highest curriculum of math, and so there was
Speaker 2: no more courses for me. He would use his lunch
Speaker 2: hours to create a one one class for me to do.
Speaker 2: Now that I'm grown up, I know he was not
Speaker 2: paid extra. It was really out of a teacher's love
Speaker 2: and sense of responsibility. And he really became such an
Speaker 2: important person in my.
Speaker 1: Life because he still alive mister Sabella.
Speaker 2: Mister Isabella passed away when I was assistant professor at Stanford,
Speaker 2: but his family, his two sons, his wife, and I
Speaker 2: I think they are my new Jersey family.
Speaker 1: At this point, you used the word love about what
Speaker 1: he did for you, and I wonder if they also
Speaker 1: He and his family introduced you to American society with
Speaker 1: your first friends and an entrance to the whole world
Speaker 1: of America beyond your school.
Speaker 2: Absolutely, they introduced me to the quintessential middle class American family.
Speaker 2: They live in a suburban house, they have two lovely kids.
Speaker 2: Of course they're all married and have the grand children
Speaker 2: generation now, but it was a great window for me
Speaker 2: to know the society, to be grounded, to have friends
Speaker 2: and have a teacher who cared.
Speaker 1: Do you think you could have had the career that
Speaker 1: you have had in China because now there are like
Speaker 1: significant advances happening in AI in China.
Speaker 2: I don't think I'm able to answer this question because
Speaker 2: I think life is so serendipitous, right the journey would
Speaker 2: be very different, and in a way we could have
Speaker 2: simulated all possibilities. But what is timeless or what is
Speaker 2: invariant for anyone is the sense of curiosity, the pursuit
Speaker 2: of north stars. So if I were me, I will
Speaker 2: still be doing AI somehow, I believe.
Speaker 1: Do you still feel connected to China?
Speaker 2: It's part of my heritage. I feel very lucky that
Speaker 2: my career has been in America, higher education and in
Speaker 2: Silicon Valley then as also in and out of industry
Speaker 2: and being in tech. The combination of all these ingredients
Speaker 2: is very global. The environment my family right now is in,
Speaker 2: which is Stanford, San Francisco, Silicon Valley, is very international,
Speaker 2: so I feel very connected. And the discipline in which
Speaker 2: is A is so horizontal it touches people everywhere that
Speaker 2: I do feel much more like a global citizen at
Speaker 2: this point.
Speaker 1: And of course it is a global industry. But there
Speaker 1: are some really striking advances in China, not least the
Speaker 1: number of patents, in the number of AI public papers
Speaker 1: coming out the Deep Seek moment earlier this year. As
Speaker 1: you look ahead in this century, do you think China
Speaker 1: will catch up with the US in the way that
Speaker 1: it has in other fields like manufacturing.
Speaker 2: I do think China is a powerhouse in AI. In
Speaker 2: this moment, most people would recognize the two leading countries
Speaker 2: in AI are China and US. The excitement, the energy,
Speaker 2: and also frankly, the ambition of many regions and many
Speaker 2: countries in the world of wanting to have a roll
Speaker 2: in AI, wanting to catch up or even come ahead
Speaker 2: in certain areas AI. That is pretty universal.
Speaker 1: And your own next frontier spatial intelligence. Tell me what
Speaker 1: you mean when you use the word spatial intelligence. What
Speaker 1: are you working on right now?
Speaker 2: Yeah? So, spatial intelligence is the ability for AI or frankly,
Speaker 2: any intelligence to understand, perceive, reason and interact and also
Speaker 2: create spaces worlds. It comes from a continuation of visual intelligence.
Speaker 2: The first half of my career around the image that
Speaker 2: at time was trying to solve the fundamental problem of
Speaker 2: understanding what we are seeing, and that was a very
Speaker 2: important problem. But it's not enough because that's a very
Speaker 2: passive act. It's just receiving information and being able to
Speaker 2: understand this is a cop, this is a beautiful lady,
Speaker 2: this is a microphone. But if you look at evolution,
Speaker 2: you look at human intelligence, perception is profound linked to action.
Speaker 2: We see because we move, we move, therefore we need
Speaker 2: to see better. And how do you create that connection
Speaker 2: has a lot to do with space, because you need
Speaker 2: to see the three D space. You need to understand
Speaker 2: how things move. You need to understand when I touch
Speaker 2: this cup, how do I mathematically organize my fingers so
Speaker 2: that it creates a space that would allow me to
Speaker 2: grab this cup. All this intricacy is center around this
Speaker 2: capability of spatial intelligence.
Speaker 1: And I've looked on your website and I've seen the
Speaker 1: preview that you've released Marble. You can see essentially a
Speaker 1: virtual world which one goes into and from room to room,
Speaker 1: and one door opens and you go from one place
Speaker 1: to another. But I'm not sure how you use it.
Speaker 1: Is it essentially to you a tool for training AI.
Speaker 1: It's a different way to train AI, rather than for example,
Speaker 1: meta saying this is in the metaverse. This is a
Speaker 1: world you can go into and spend time and as
Speaker 1: a human being.
Speaker 2: Right, So let's just be clear with the definition. Marble
Speaker 2: is a frontier model. It's a frontier world model. What
Speaker 2: it does is not just to see and go into
Speaker 2: a world. What's really remarkable is it generates a three
Speaker 2: D world at a simple prompt. A prompt could be
Speaker 2: give me a modern looking kitchen, or the prompt could
Speaker 2: be here's a picture of a modern looking kitchen. Make
Speaker 2: it a three D world. The ability to create a
Speaker 2: three D world is a fundamental ability. It's fundamental to humans,
Speaker 2: and it's I hope one day, is fundamental to AI.
Speaker 2: If you are a designer or architect, you can use
Speaker 2: this three D world to ida to design. If you
Speaker 2: are a game developer, you can use it to obtain
Speaker 2: these three D worlds so that you can design games.
Speaker 2: If you want to do robotics simulation, these worlds will
Speaker 2: become very useful as training data for robots. If you
Speaker 2: want to create immersive educational experiences in ARVR, this model
Speaker 2: would help you to do that.
Speaker 1: Interesting I'm imagining girls in Afghanistan, Maybe you could do
Speaker 1: virtual classrooms in a very challenged place.
Speaker 2: Yes, Or I'm imagining, for example, how do you explain
Speaker 2: to an eight year old what is a cell? One day,
Speaker 2: we'll create a world that's inside of a cell, and
Speaker 2: then the student can walk into that cell and understand
Speaker 2: the nuclears, enzymes, the membranes. So you can use this
Speaker 2: for so many possibilities. So that's your next frontier, can
Speaker 2: we conscious? Yours is a very big, complex industry, but
Speaker 2: there are some immediate pressing issues, and I wonder if
Speaker 2: I could put a selection of those to you for
Speaker 2: you to give us an instinctive or even a nutshell
Speaker 2: response on how you see them. For example, and you'll
Speaker 2: have heard this many times before. Number one, is AI
Speaker 2: going to destroy jobs? Large numbers of jobs? Technology do
Speaker 2: change the landscape of labor. A technology as impactful and
Speaker 2: profound as AI will have a profound impact in jobs.
Speaker 1: Which is happening of their customer support roles are going
Speaker 1: to go because of AI.
Speaker 2: Right and software engineering, contact centers, analyst jobs, So it will,
Speaker 2: there's no question about it.
Speaker 1: It's not going to create as many jobs in its place,
Speaker 1: is it. I wonder if that worries you.
Speaker 2: The juris store out there. Every time humanity has created
Speaker 2: a more advanced technology, for example steam engine, electricity, PC cars,
Speaker 2: we have gone through difficult times, but we also have
Speaker 2: gone through real landscaping of jobs. So only in talking
Speaker 2: about the number bigger or smaller doesn't do justice. We
Speaker 2: need to look at this in a much more nuanced
Speaker 2: way and really think about how to respond to this change.
Speaker 2: There's the individual level responsibility you've got to learn, you
Speaker 2: gotta obscure yourself, but there is also company level responsibility.
Speaker 2: There's also societal level responsibility. So this is a big question.
Speaker 1: Number two is an even bigger question. If you take
Speaker 1: those headphones, I want to play you the voice and
Speaker 1: a view on the existential question about whether human beings
Speaker 1: are going to be replaced by AI. And this is
Speaker 1: a voice you will know Professor Jeffrey Hinton, whose work
Speaker 1: has overlapped with yours and who is a no laureate
Speaker 1: as well.
Speaker 3: When AI gets super intelligent, it might just replace us.
Speaker 3: How do we prevent it taking over? Even if all
Speaker 3: the countries collaborate, what do you do? And I think
Speaker 3: at present, all the big companies and governments have the
Speaker 3: wrong model. Their basic model is I'm the CEO, and
Speaker 3: this super intelligent AI is the extremely smart executive assistant.
Speaker 3: I'm the boss. It's not going to be like that
Speaker 3: when it's smarter than us and more powerful than us.
Speaker 1: What do you think of that? Because Professor Hinton thinks
Speaker 1: it's a ten to twenty percent chance that AI leads
Speaker 1: to human extinction.
Speaker 2: So, first of all, Professor Hinton or I call him Jeff,
Speaker 2: because I have known him for twenty five years since
Speaker 2: I was first a graduate student. He's someone I admire
Speaker 2: and studied his technical papers. But this thing about replacing
Speaker 2: human race, I actually do respectfully disagree, not in the
Speaker 2: sense that it will never happen. It is in a
Speaker 2: sense that if human race became really being trouble, in
Speaker 2: my opinion, that's a result of humans doing wrong things,
Speaker 2: not machines doing wrong things.
Speaker 1: But the very practical point that he put in that
Speaker 1: clip is where he says, how do we prevent the
Speaker 1: super intelligent creation taking over at the point that it
Speaker 1: becomes more intelligent than us? We have no model for that. Now,
Speaker 1: if that creation that is more intelligent than us, says,
Speaker 1: turn off human beings life support or do something else.
Speaker 1: That is existential? How would we stop it?
Speaker 2: So? I think this question has made an assumption, which
Speaker 2: is from today, which we don't have such a machine,
Speaker 2: super intelligent machine, Yet we still have a distance, We
Speaker 2: still have a journey to take from today to that day.
Speaker 2: And my question is why would humanity as a whole
Speaker 2: allow this to happen? Where is our collective responsibility? Where's
Speaker 2: our governance or regulation?
Speaker 1: Which is why I wonder, then, do you think there
Speaker 1: is a way to make sure that there is an
Speaker 1: upper limit to superintelligence?
Speaker 2: I think there is a way to make sure there
Speaker 2: is a responsible development and usage of.
Speaker 1: Technology internationally agreed, like at the government level. Is it
Speaker 1: a treaty? Is it just companies agreeing to right?
Speaker 2: You're right? The field is so nascent that we don't
Speaker 2: yet have the level of international treaties. We don't yet
Speaker 2: have the level of global consent. I think we have
Speaker 2: global awareness, and I do want to say that we
Speaker 2: shouldn't over click out the only one possible consequences or
Speaker 2: negative consequences of AI. This technology is powerful. It might
Speaker 2: have other negative consequences. It also has a tone of
Speaker 2: benevolent applications for humanity. We need to look at this holistically.
Speaker 1: Do you get frustrated by some of the questions? And
Speaker 1: because I know you talked to politicians, people with political
Speaker 1: power a lot. You've done that in the US, You've
Speaker 1: done that in the UK and in France and elsewhere.
Speaker 1: What's the most common question they ask you that you
Speaker 1: find frustrating.
Speaker 2: I wouldn't use the word frustrating. I would use the
Speaker 2: word concerned, because I think our public discourse of AI
Speaker 2: need to move from the very simple question of what
Speaker 2: do we do when machine overlord is here? So I
Speaker 2: don't get frustrated, I get concerned if the only way
Speaker 2: to ask this question is is very simple binary do
Speaker 2: you want it or not want it? Another question I
Speaker 2: get asked a lot, possibly more than this question, is
Speaker 2: question from parents worldwide. Parents ask me AI is coming.
Speaker 2: How do I advise my kids? What's the future of
Speaker 2: my kids? What should they do? Should they study computer science?
Speaker 2: Are they going to have jobs? And so?
Speaker 1: Answer it? Then people listening to this are probably thinking
Speaker 1: exactly the same. What do you say?
Speaker 2: I say that AI is a very powerful technology, and
Speaker 2: I'm my mother. The most important thing we should empower
Speaker 2: our kids is to empower them as humans with agency,
Speaker 2: with dignity with the desire to learn, and there are
Speaker 2: timeless values of humanity. Be an honest person, be a
Speaker 2: hard working person, be creative. Worry about what they'll study.
Speaker 2: Worry is not the right word. Be totally informed and
Speaker 2: understand that your children's future is going to be living
Speaker 2: in the world of AI technology and depending on their interests,
Speaker 2: their passion, their personality, their circumstance, prepare them in that future.
Speaker 2: Worry doesn't solve the problem.
Speaker 1: I've got another industry question, which is about the huge
Speaker 1: sums of money that are flowing into again, not that
Speaker 1: many companies like yours, and whether this might be a bubble,
Speaker 1: whether this might be like a dot com bubble where
Speaker 1: it turns out that some of these companies are overvalued.
Speaker 2: First of all, my company is still a startup. When
Speaker 2: we're talking about huge amount of money, we really look
Speaker 2: at the big techs. AI is still a nascent technology,
Speaker 2: and from a development point of view, there's still a
Speaker 2: lot to be developed. The science is very hard. It
Speaker 2: takes a lot to make scientific and technological breakthroughs. This
Speaker 2: is why resourcing these efforts are still important. The other
Speaker 2: side of this is the market. Are we going to
Speaker 2: see the payoff from the market. By and large, I
Speaker 2: do believe that the applications of AI is so massive,
Speaker 2: whether we're talking about software engineering to creativity, to healthcare,
Speaker 2: to education, to financial services, that I think we're going
Speaker 2: to continue to see an expansion of the market of AI.
Speaker 2: I look at it as there are so many human
Speaker 2: needs both in terms of wellbeing as well as in
Speaker 2: terms of productivity that can be helped by AI as
Speaker 2: an assistant, as a collaborator, and that part. I do
Speaker 2: believe strongly that this is an expanding market.
Speaker 1: But what does it cost in terms of power and
Speaker 1: therefore energy and therefore climate. There's a prominent AI entrepreneur
Speaker 1: you probably know, Jerry Kaplan, who said that we could
Speaker 1: be heading for a new ecological disaster because of the
Speaker 1: amount of energy consumed by the vast data centers that
Speaker 1: we're going to need in growing numbers.
Speaker 2: This is an interesting question. I do think that in
Speaker 2: order to train large models, we're seeing more and more
Speaker 2: need for power or energy. But nobody says these data
Speaker 2: centers must be powered by fossil fuel. For example, Our
Speaker 2: innovation and the energy side will be part of this
Speaker 2: innovation cycle, right.
Speaker 1: I think it's just because the amount of power they
Speaker 1: need is so enormous it's hard to see it coming
Speaker 1: from renewable energy alone.
Speaker 2: I think right now this is true, but I also
Speaker 2: know that as for example, I visit Middle East, there's
Speaker 2: a lot of effort in building renewable energy for big
Speaker 2: data centers. I do think that countries that need to
Speaker 2: build these big data centers need to also examine its
Speaker 2: energy policy and industry. This is an opportunity for us
Speaker 2: to invest and develop more renewable energy.
Speaker 1: What worries you about your industry because you're painting a
Speaker 1: very positive picture, and you've been at the forefront of
Speaker 1: this and you see much more potential. So I understand
Speaker 1: where you're coming from.
Speaker 2: But in quite a moment, I'm not a tech utopian,
Speaker 2: nor am I a dystopian. I think I'm actually the
Speaker 2: boring middle. The boring middle wants to apply a much
Speaker 2: more pragmatic and scientific lens to this. So what worries me?
Speaker 2: Of course, aning tool in the hands of the wrong
Speaker 2: mindset or wrong intention would worry me since the dawn
Speaker 2: of human civilization, if fire was such a critical invention
Speaker 2: for our species, yet using fire to harm people is
Speaker 2: massively bad. So adding wrong use of AI, worries speed,
Speaker 2: the wrong way to communicate with the public, Worry speed
Speaker 2: because I do feel there's a lot of anxiety in
Speaker 2: different parts of the world. The one worry I have
Speaker 2: is our teachers. These people and my own personal experience
Speaker 2: tells me they're the backbone of our society. They are
Speaker 2: so critical for educating our future generation. Are we having
Speaker 2: the right communication with them? Are we bringing them along?
Speaker 2: Are our teachers using AI tools to superpower their profession
Speaker 2: or helping our children to use AI instead of letting
Speaker 2: them feel left out, frustrated and just we should be
Speaker 2: embracing them. We should be helping them. And this would
Speaker 2: be a concern if we don't do the right thing
Speaker 2: for our teachers, for our nurses, for our doctors, for
Speaker 2: many parts of our society.
Speaker 1: This is the Bloomberg Weekend Interview. And so we're always
Speaker 1: interested in people's lives as well as their work. And
Speaker 1: I realize that your life, the life that you're living today,
Speaker 1: is so different from the way that you grew up,
Speaker 1: working in your parents dry cleaner, keeping it a lot.
Speaker 2: Of laundry at home.
Speaker 1: So are you conscious of the power that you have
Speaker 1: as a leader in this industry of our time in
Speaker 1: the future.
Speaker 2: I'm conscious of my responsibility. I understand I'm one of
Speaker 2: the people who brought this technology to our world. I
Speaker 2: understand that I'm so privileged to be working at the
Speaker 2: one of the best universities in the world, educating tomorrow's
Speaker 2: leaders and doing the cutting edge research. I'm conscious of
Speaker 2: myself being an entrepreneur and a CEO of one of
Speaker 2: the most exciting startups in the gen AI world. So
Speaker 2: everything I do has a consequence, and that's a responsibility
Speaker 2: I shoulder, and I take that very seriously because this
Speaker 2: is what I keep telling people in the age of AI.
Speaker 2: The agency should be within humans. The agency is not
Speaker 2: the machines. It's ours. My agency is to create exciting
Speaker 2: technology and to use it responsibily.
Speaker 1: And the humans in your life, your children, what do
Speaker 1: you not let them do with AI or with their
Speaker 1: devices or on the internet.
Speaker 2: It's the timeless advice of don't do stupid things with
Speaker 2: your tools. You have to think about why you're using
Speaker 2: the tool and how you're using it. It could be
Speaker 2: as simple as don't be lazy just because there is AI. Right,
Speaker 2: if you want to understand math, maybe large language models
Speaker 2: can give you the answer, but that is not the
Speaker 2: way to learn. As the questions. You could use the
Speaker 2: AI tool to prompt a good question so that you
Speaker 2: learn because of it. So don't be lazy is one
Speaker 2: of them. The other side is don't use it to
Speaker 2: do bad things. For example, integrity of information right, fake images,
Speaker 2: fake voices, fake texts. These are issues of AI as
Speaker 2: well as our social media driven communication in our society.
Speaker 1: I think you're sort of calling for old fashioned values
Speaker 1: amid this amid this world full of new developments and
Speaker 1: challenges we couldn't have imagined even three years ago. Yeah,
Speaker 1: you can call it old fashion, you can call it timeless.
Speaker 1: As an educator, as a mom, I think there are
Speaker 1: some human values that are timeless, and we need to
Speaker 1: recognize that. Finally, you're reading from the child who is
Speaker 1: already reading the classics at an early age. Nowadays, What
Speaker 1: do you read when you're kicking back at the weekend,
Speaker 1: if that ever happens.
Speaker 2: Yeah, honestly, I read a lot of technical papers these days.
Speaker 2: It's it's kind of sad. I also read to my kids.
Speaker 2: I have to say that my favorite book these days
Speaker 2: is Harry Potter because it's such a great book and
Speaker 2: I read a bed time reading to my kids.
Speaker 1: Well, that series is going to keep you going for
Speaker 1: quite a long time, Yes, depending on I'm most cure at.
Speaker 2: Yeah.
Speaker 1: So you're not taking away the children's books in their lives, then.
Speaker 2: No, because they live in a totally different time. They
Speaker 2: actually are exposed to information in a completely different way
Speaker 2: from my time. There's like barely TV in the nineteen
Speaker 2: nineties or eighties in China. Now they have the entire Internet.
Speaker 2: I give them a kindle and Chinese. Do you speak
Speaker 2: to them in Chinese? I speak to them in not
Speaker 2: great but I do speak to them in Chinese, and
Speaker 2: their father speak to them in Italian.
Speaker 1: Okay, citizens of the world, Yes, as you've become as well,
Speaker 1: Doctor Fayfaeley. Thank you so much. Thank you, Michelle, And
Speaker 1: that's the Michelle Hussein Show for this week. Do subscribe
Speaker 1: if you haven't already. That way you'll know as soon
Speaker 1: as we have a new episode. Thank you for the
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Speaker 1: us the addresses Michelle Show at Bloomberg dot net. If
Speaker 1: you want to see the written versions of these conversations
Speaker 1: with my notes, they're at Bloomberg dot Com Slash Weekend,
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Speaker 1: The show's producers are Jessica Beck and Chris Martleu. Guest
Speaker 1: booking is by Dave Warren, Social media by Alex Morgan.
Speaker 1: Our sound engineer this week was Richard Ward. Video editing
Speaker 1: was by Laura Francis. Our executive producer is Louisa Lewis
Speaker 1: at Bloomberg Weekend, Brendan Francis Nunam is Editorial director of
Speaker 1: Audio and Special Projects, and our executive editor is Catherine bell.
Speaker 1: Our music is by Bart Walshaw. And we'd also like
Speaker 1: to thank Alana Susnow Samasadi and Sage Bauman and thank
Speaker 1: you for listening until next weekend. Goodbye,