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Transcript of YouTube Video: What Is an AI Anyway? | Mustafa Suleyman | TED

Transcript of YouTube Video: What Is an AI Anyway? | Mustafa Suleyman | TED

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00:04

I want to tell you what I see coming.

00:07

I've been lucky enough to be working on AI for almost 15 years now.

00:12

Back when I started, to describe it as fringe would be an understatement.

00:17

Researchers would say, “No, no, we’re only working on machine learning.”

00:21

Because working on AI was seen as way too out there.

00:25

In 2010, just the very mention of the phrase “AGI,”

00:29

artificial general intelligence,

00:31

would get you some seriously strange looks

00:34

and even a cold shoulder.

00:36

"You're actually building AGI?" people would say.

00:40

"Isn't that something out of science fiction?"

00:42

People thought it was 50 years away or 100 years away,

00:45

if it was even possible at all.

00:47

Talk of AI was, I guess, kind of embarrassing.

00:51

People generally thought we were weird.

00:54

And I guess in some ways we kind of were.

00:56

It wasn't long, though, before AI started beating humans

00:59

at a whole range of tasks

01:01

that people previously thought were way out of reach.

01:05

Understanding images,

01:07

translating languages,

01:09

transcribing speech,

01:10

playing Go and chess

01:12

and even diagnosing diseases.

01:15

People started waking up to the fact

01:17

that AI was going to have an enormous impact,

01:21

and they were rightly asking technologists like me

01:23

some pretty tough questions.

01:25

Is it true that AI is going to solve the climate crisis?

01:29

Will it make personalized education available to everyone?

01:32

Does it mean we'll all get universal basic income

01:35

and we won't have to work anymore?

01:37

Should I be afraid?

01:38

What does it mean for weapons and war?

01:41

And of course, will China win?

01:43

Are we in a race?

01:45

Are we headed for a mass misinformation apocalypse?

01:49

All good questions.

01:51

But it was actually a simpler

01:53

and much more kind of fundamental question that left me puzzled.

01:58

One that actually gets to the very heart of my work every day.

02:03

One morning over breakfast,

02:05

my six-year-old nephew Caspian was playing with Pi,

02:09

the AI I created at my last company, Inflection.

02:12

With a mouthful of scrambled eggs,

02:14

he looked at me plain in the face and said,

02:17

"But Mustafa, what is an AI anyway?"

02:21

He's such a sincere and curious and optimistic little guy.

02:25

He'd been talking to Pi about how cool it would be if one day in the future,

02:29

he could visit dinosaurs at the zoo.

02:32

And how he could make infinite amounts of chocolate at home.

02:35

And why Pi couldn’t yet play I Spy.

02:39

"Well," I said, "it's a clever piece of software

02:42

that's read most of the text on the open internet,

02:44

and it can talk to you about anything you want."

02:48

"Right.

02:49

So like a person then?"

02:54

I was stumped.

02:56

Genuinely left scratching my head.

03:00

All my boring stock answers came rushing through my mind.

03:04

"No, but AI is just another general-purpose technology,

03:07

like printing or steam."

03:09

It will be a tool that will augment us

03:11

and make us smarter and more productive.

03:14

And when it gets better over time,

03:16

it'll be like an all-knowing oracle

03:18

that will help us solve grand scientific challenges."

03:22

You know, all of these responses started to feel, I guess,

03:25

a little bit defensive.

03:28

And actually better suited to a policy seminar

03:30

than breakfast with a no-nonsense six-year-old.

03:33

"Why am I hesitating?" I thought to myself.

03:37

You know, let's be honest.

03:39

My nephew was asking me a simple question

03:43

that those of us in AI just don't confront often enough.

03:48

What is it that we are actually creating?

03:51

What does it mean to make something totally new,

03:55

fundamentally different to any invention that we have known before?

04:00

It is clear that we are at an inflection point

04:03

in the history of humanity.

04:06

On our current trajectory,

04:08

we're headed towards the emergence of something

04:10

that we are all struggling to describe,

04:13

and yet we cannot control what we don't understand.

04:19

And so the metaphors,

04:21

the mental models,

04:22

the names, these all matter

04:25

if we’re to get the most out of AI whilst limiting its potential downsides.

04:30

As someone who embraces the possibilities of this technology,

04:33

but who's also always cared deeply about its ethics,

04:37

we should, I think,

04:38

be able to easily describe what it is we are building.

04:41

And that includes the six-year-olds.

04:44

So it's in that spirit that I offer up today the following metaphor

04:48

for helping us to try to grapple with what this moment really is.

04:52

I think AI should best be understood

04:55

as something like a new digital species.

05:00

Now, don't take this too literally,

05:02

but I predict that we'll come to see them as digital companions,

05:07

new partners in the journeys of all our lives.

05:10

Whether you think we’re on a 10-, 20- or 30-year path here,

05:14

this is, in my view, the most accurate and most fundamentally honest way

05:19

of describing what's actually coming.

05:22

And above all, it enables everybody to prepare for

05:26

and shape what comes next.

05:29

Now I totally get, this is a strong claim,

05:31

and I'm going to explain to everyone as best I can why I'm making it.

05:36

But first, let me just try to set the context.

05:39

From the very first microscopic organisms,

05:42

life on Earth stretches back billions of years.

05:45

Over that time, life evolved and diversified.

05:49

Then a few million years ago, something began to shift.

05:54

After countless cycles of growth and adaptation,

05:57

one of life’s branches began using tools, and that branch grew into us.

06:04

We went on to produce a mesmerizing variety of tools,

06:08

at first slowly and then with astonishing speed,

06:12

we went from stone axes and fire

06:16

to language, writing and eventually industrial technologies.

06:21

One invention unleashed a thousand more.

06:25

And in time, we became homo technologicus.

06:29

Around 80 years ago,

06:30

another new branch of technology began.

06:33

With the invention of computers,

06:35

we quickly jumped from the first mainframes and transistors

06:39

to today's smartphones and virtual-reality headsets.

06:42

Information, knowledge, communication, computation.

06:47

In this revolution,

06:49

creation has exploded like never before.

06:53

And now a new wave is upon us.

06:55

Artificial intelligence.

06:57

These waves of history are clearly speeding up,

07:00

as each one is amplified and accelerated by the last.

07:05

And if you look back,

07:06

it's clear that we are in the fastest

07:08

and most consequential wave ever.

07:11

The journeys of humanity and technology are now deeply intertwined.

07:16

In just 18 months,

07:18

over a billion people have used large language models.

07:21

We've witnessed one landmark event after another.

07:25

Just a few years ago, people said that AI would never be creative.

07:30

And yet AI now feels like an endless river of creativity,

07:34

making poetry and images and music and video that stretch the imagination.

07:39

People said it would never be empathetic.

07:42

And yet today, millions of people enjoy meaningful conversations with AIs,

07:47

talking about their hopes and dreams

07:49

and helping them work through difficult emotional challenges.

07:53

AIs can now drive cars,

07:55

manage energy grids

07:57

and even invent new molecules.

07:59

Just a few years ago, each of these was impossible.

08:03

And all of this is turbocharged by spiraling exponentials of data

08:09

and computation.

08:10

Last year, Inflection 2.5, our last model,

08:16

used five billion times more computation

08:20

than the DeepMind AI that beat the old-school Atari games

08:24

just over 10 years ago.

08:26

That's nine orders of magnitude more computation.

08:30

10x per year,

08:31

every year for almost a decade.

08:34

Over the same time, the size of these models has grown

08:37

from first tens of millions of parameters to then billions of parameters,

08:41

and very soon, tens of trillions of parameters.

08:45

If someone did nothing but read 24 hours a day for their entire life,

08:50

they'd consume eight billion words.

08:53

And of course, that's a lot of words.

08:55

But today, the most advanced AIs consume more than eight trillion words

09:01

in a single month of training.

09:03

And all of this is set to continue.

09:05

The long arc of technological history is now in an extraordinary new phase.

09:12

So what does this mean in practice?

09:15

Well, just as the internet gave us the browser

09:18

and the smartphone gave us apps,

09:20

the cloud-based supercomputer is ushering in a new era

09:24

of ubiquitous AIs.

09:27

Everything will soon be represented by a conversational interface.

09:32

Or, to put it another way, a personal AI.

09:35

And these AIs will be infinitely knowledgeable,

09:38

and soon they'll be factually accurate and reliable.

09:42

They'll have near-perfect IQ.

09:44

They’ll also have exceptional EQ.

09:47

They’ll be kind, supportive, empathetic.

09:53

These elements on their own would be transformational.

09:55

Just imagine if everybody had a personalized tutor in their pocket

09:59

and access to low-cost medical advice.

10:02

A lawyer and a doctor,

10:04

a business strategist and coach --

10:06

all in your pocket 24 hours a day.

10:08

But things really start to change when they develop what I call AQ,

10:13

their “actions quotient.”

10:15

This is their ability to actually get stuff done

10:18

in the digital and physical world.

10:20

And before long, it won't just be people that have AIs.

10:24

Strange as it may sound, every organization,

10:27

from small business to nonprofit to national government,

10:30

each will have their own.

10:32

Every town, building and object

10:35

will be represented by a unique interactive persona.

10:39

And these won't just be mechanistic assistants.

10:42

They'll be companions, confidants,

10:46

colleagues, friends and partners,

10:48

as varied and unique as we all are.

10:52

At this point, AIs will convincingly imitate humans at most tasks.

10:57

And we'll feel this at the most intimate of scales.

11:00

An AI organizing a community get-together for an elderly neighbor.

11:04

A sympathetic expert helping you make sense of a difficult diagnosis.

11:09

But we'll also feel it at the largest scales.

11:12

Accelerating scientific discovery,

11:14

autonomous cars on the roads,

11:16

drones in the skies.

11:18

They'll both order the takeout and run the power station.

11:22

They’ll interact with us and, of course, with each other.

11:26

They'll speak every language,

11:28

take in every pattern of sensor data,

11:31

sights, sounds,

11:33

streams and streams of information,

11:35

far surpassing what any one of us could consume in a thousand lifetimes.

11:40

So what is this?

11:42

What are these AIs?

11:46

If we are to prioritize safety above all else,

11:51

to ensure that this new wave always serves and amplifies humanity,

11:56

then we need to find the right metaphors for what this might become.

12:01

For years, we in the AI community, and I specifically,

12:06

have had a tendency to refer to this as just tools.

12:11

But that doesn't really capture what's actually happening here.

12:14

AIs are clearly more dynamic,

12:17

more ambiguous, more integrated

12:19

and more emergent than mere tools,

12:22

which are entirely subject to human control.

12:25

So to contain this wave,

12:28

to put human agency at its center

12:31

and to mitigate the inevitable unintended consequences

12:33

that are likely to arise,

12:35

we should start to think about them as we might a new kind of digital species.

12:41

Now it's just an analogy,

12:42

it's not a literal description, and it's not perfect.

12:46

For a start, they clearly aren't biological in any traditional sense,

12:50

but just pause for a moment

12:52

and really think about what they already do.

12:55

They communicate in our languages.

12:58

They see what we see.

13:00

They consume unimaginably large amounts of information.

13:04

They have memory.

13:06

They have personality.

13:09

They have creativity.

13:12

They can even reason to some extent and formulate rudimentary plans.

13:16

They can act autonomously if we allow them.

13:20

And they do all this at levels of sophistication

13:22

that is far beyond anything that we've ever known from a mere tool.

13:27

And so saying AI is mainly about the math or the code

13:32

is like saying we humans are mainly about carbon and water.

13:37

It's true, but it completely misses the point.

13:42

And yes, I get it, this is a super arresting thought

13:46

but I honestly think this frame helps sharpen our focus on the critical issues.

13:52

What are the risks?

13:55

What are the boundaries that we need to impose?

13:59

What kind of AI do we want to build or allow to be built?

14:04

This is a story that's still unfolding.

14:06

Nothing should be accepted as a given.

14:09

We all must choose what we create.

14:12

What AIs we bring into the world, or not.

14:18

These are the questions for all of us here today,

14:21

and all of us alive at this moment.

14:24

For me, the benefits of this technology are stunningly obvious,

14:28

and they inspire my life's work every single day.

14:33

But quite frankly, they'll speak for themselves.

14:37

Over the years, I've never shied away from highlighting risks

14:40

and talking about downsides.

14:43

Thinking in this way helps us focus on the huge challenges

14:46

that lie ahead for all of us.

14:48

But let's be clear.

14:50

There is no path to progress

14:52

where we leave technology behind.

14:55

The prize for all of civilization is immense.

15:00

We need solutions in health care and education, to our climate crisis.

15:03

And if AI delivers just a fraction of its potential,

15:07

the next decade is going to be the most productive in human history.

15:13

Here's another way to think about it.

15:15

In the past,

15:17

unlocking economic growth often came with huge downsides.

15:21

The economy expanded as people discovered new continents

15:25

and opened up new frontiers.

15:28

But they colonized populations at the same time.

15:32

We built factories,

15:34

but they were grim and dangerous places to work.

15:38

We struck oil,

15:39

but we polluted the planet.

15:42

Now because we are still designing and building AI,

15:45

we have the potential and opportunity to do it better,

15:49

radically better.

15:51

And today, we're not discovering a new continent

15:53

and plundering its resources.

15:56

We're building one from scratch.

15:58

Sometimes people say that data or chips are the 21st century’s new oil,

16:03

but that's totally the wrong image.

16:06

AI is to the mind

16:08

what nuclear fusion is to energy.

16:12

Limitless, abundant,

16:14

world-changing.

16:17

And AI really is different,

16:20

and that means we have to think about it creatively and honestly.

16:24

We have to push our analogies and our metaphors

16:27

to the very limits

16:29

to be able to grapple with what's coming.

16:31

Because this is not just another invention.

16:34

AI is itself an infinite inventor.

16:38

And yes, this is exciting and promising and concerning

16:42

and intriguing all at once.

16:45

To be quite honest, it's pretty surreal.

16:47

But step back,

16:49

see it on the long view of glacial time,

16:52

and these really are the very most appropriate metaphors that we have today.

16:57

Since the beginning of life on Earth,

17:00

we've been evolving, changing

17:03

and then creating everything around us in our human world today.

17:08

And AI isn't something outside of this story.

17:11

In fact, it's the very opposite.

17:15

It's the whole of everything that we have created,

17:18

distilled down into something that we can all interact with

17:21

and benefit from.

17:23

It's a reflection of humanity across time,

17:27

and in this sense,

17:28

it isn't a new species at all.

17:31

This is where the metaphors end.

17:33

Here's what I'll tell Caspian next time he asks.

17:37

AI isn't separate.

17:39

AI isn't even in some senses, new.

17:43

AI is us.

17:45

It's all of us.

17:47

And this is perhaps the most promising and vital thing of all

17:50

that even a six-year-old can get a sense for.

17:54

As we build out AI,

17:55

we can and must reflect all that is good,

17:59

all that we love,

18:00

all that is special about humanity:

18:03

our empathy, our kindness,

18:05

our curiosity and our creativity.

18:09

This, I would argue, is the greatest challenge of the 21st century,

18:14

but also the most wonderful,

18:16

inspiring and hopeful opportunity for all of us.

18:20

Thank you.

18:21

(Applause)

18:26

Chris Anderson: Thank you Mustafa.

18:28

It's an amazing vision and a super powerful metaphor.

18:32

You're in an amazing position right now.

18:34

I mean, you were connected at the hip

18:35

to the amazing work happening at OpenAI.

18:38

You’re going to have resources made available,

18:40

there are reports of these giant new data centers,

18:44

100 billion dollars invested and so forth.

18:48

And a new species can emerge from it.

18:52

I mean, in your book,

18:53

you did, as well as painting an incredible optimistic vision,

18:56

you were super eloquent on the dangers of AI.

19:00

And I'm just curious, from the view that you have now,

19:04

what is it that most keeps you up at night?

19:06

Mustafa Suleyman: I think the great risk is that we get stuck

19:09

in what I call the pessimism aversion trap.

19:11

You know, we have to have the courage to confront

19:14

the potential of dark scenarios

19:16

in order to get the most out of all the benefits that we see.

19:19

So the good news is that if you look at the last two or three years,

19:23

there have been very, very few downsides, right?

19:26

It’s very hard to say explicitly what harm an LLM has caused.

19:31

But that doesn’t mean that that’s what the trajectory is going to be

19:34

over the next 10 years.

19:35

So I think if you pay attention to a few specific capabilities,

19:39

take for example, autonomy.

19:41

Autonomy is very obviously a threshold

19:43

over which we increase risk in our society.

19:46

And it's something that we should step towards very, very closely.

19:49

The other would be something like recursive self-improvement.

19:52

If you allow the model to independently self-improve,

19:56

update its own code,

19:57

explore an environment without oversight, and, you know,

20:01

without a human in control to change how it operates,

20:04

that would obviously be more dangerous.

20:06

But I think that we're still some way away from that.

20:09

I think it's still a good five to 10 years before we have to really confront that.

20:12

But it's time to start talking about it now.

20:15

CA: A digital species, unlike any biological species,

20:17

can replicate not in nine months,

20:19

but in nine nanoseconds,

20:21

and produce an indefinite number of copies of itself,

20:24

all of which have more power than we have in many ways.

20:28

I mean, the possibility for unintended consequences seems pretty immense.

20:33

And isn't it true that if a problem happens,

20:35

it could happen in an hour?

20:37

MS: No.

20:38

That is really not true.

20:40

I think there's no evidence to suggest that.

20:42

And I think that, you know,

20:44

that’s often referred to as the “intelligence explosion.”

20:47

And I think it is a theoretical, hypothetical maybe

20:51

that we're all kind of curious to explore,

20:53

but there's no evidence that we're anywhere near anything like that.

20:56

And I think it's very important that we choose our words super carefully.

21:00

Because you're right, that's one of the weaknesses of the species framing,

21:03

that we will design the capability for self-replication into it

21:08

if people choose to do that.

21:09

And I would actually argue that we should not,

21:12

that would be one of the dangerous capabilities

21:14

that we should step back from, right?

21:16

So there's no chance that this will "emerge" accidentally.

21:19

I really think that's a very low probability.

21:22

It will happen if engineers deliberately design those capabilities in.

21:26

And if they don't take enough efforts to deliberately design them out.

21:30

And so this is the point of being explicit

21:32

and transparent about trying to introduce safety by design very early on.

21:39

CA: Thank you, your vision of humanity injecting into this new thing

21:45

the best parts of ourselves,

21:46

avoiding all those weird, biological, freaky,

21:49

horrible tendencies that we can have in certain circumstances,

21:52

I mean, that is a very inspiring vision.

21:54

And thank you so much for coming here and sharing it at TED.

21:58

Thank you, good luck.

21:59

(Applause)