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Transcript of YouTube Video: The Last 6 Decades of AI — and What Comes Next | Ray Kurzweil | TED

Transcript of YouTube Video: The Last 6 Decades of AI — and What Comes Next | Ray Kurzweil | TED

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00:03

So we've heard a lot about artificial intelligence.

00:08

I've actually been involved with AI for 61 years, which is a record.

00:15

And we've heard a lot about what people think about AI today.

00:20

So I tried to figure out,

00:23

what did we think about artificial intelligence

00:26

61 years ago.

00:29

So first of all, people asked, "What are you into?"

00:31

I'd say artificial intelligence.

00:33

And they'd say, "What's that?"

00:35

So no one was really aware of it.

00:40

I joined, in 1962,

00:43

1956 was the conference where artificial intelligence got its name.

00:47

So the views were quite different.

00:53

People who were in computer science had heard of artificial intelligence.

00:57

Most people were quite skeptical.

00:59

They thought it would never happen, or if they thought it would happen,

01:02

maybe it would happen in a century or several centuries.

01:07

But the people that actually came to that Dartmouth conference in 1956,

01:11

they were quite optimistic.

01:13

Some of them, including Minsky,

01:15

thought it would take like, one semester to reach --

01:18

(Laughter)

01:21

To reach the level of intelligence that humans had.

01:28

And in fact, that led to our first argument.

01:31

He was my mentor for 50 years.

01:34

But we argued about that because I thought it would take decades,

01:37

but we would see it within our lifetime.

01:40

So we're the only species

01:43

that actually creates tools that enhances our intelligence.

01:47

I mean, I'll bet almost everybody has one of these

01:50

that makes us more intelligent.

01:52

This connects to the cloud.

01:54

It gets more intelligent every year.

01:57

Basically, the singularity is going to bring that into our minds.

02:00

We're going to become smarter.

02:02

And there's two different things we have in our anatomy

02:05

that enable us to do that.

02:06

One is our brain,

02:08

but we're not the only species that has a brain

02:10

or even a comparable brain.

02:12

Elephants and whales actually have a brain that's larger than [ours].

02:16

But there's another aspect of their anatomy that they don't have

02:20

and that no one else has aside from humans

02:23

which is our thumb.

02:27

So I can look at a tree and I can imagine, yeah,

02:29

I could take those poles and create a tool

02:32

and then I can actually do it.

02:34

Now, monkeys, if you look at them they have a thumb,

02:37

but it doesn't really work very well,

02:39

it's actually an inch down.

02:41

They can grab things without much force.

02:48

They can create a first generation of tools,

02:51

but they can't use that tool to create another set of tools.

02:54

So they really can't create a whole set of tools

02:59

that will enhance their intelligence.

03:02

We're the only species that does that.

03:05

And that's what artificial intelligence is doing.

03:08

From the very first hominid

03:10

that created a very primitive tool

03:13

to Gemini and GPT-4 today,

03:17

we create tools that make us smarter.

03:20

And so I've been actually monitoring

03:26

the growth of computation,

03:30

which is right here.

03:32

I spent like, 45 years on this.

03:36

And as you go up the chart, it represents exponential growth.

03:40

You might think that someone was in charge of this.

03:43

Gee, we've done this much,

03:44

it's in a straight line,

03:45

let's get our next computer to be right here.

03:49

But no one was aware of it.

03:51

No one even knew that this was happening for the first 40 years.

03:55

I discovered this 45 years ago.

03:58

I had various reasons to feel it would continue at this pace.

04:02

In 1939

04:05

that represents

04:06

0.000007

04:12

calculations per second per constant dollar.

04:15

At the upper right hand corner, you've got a Google computer,

04:20

which was 130 billion calculations per second.

04:26

And recently Nvidia just came out with a chip

04:29

which is half a trillion calculations per second.

04:31

So this little chart represents a growth

04:36

of 75 quadrillion-fold increase.

04:40

That's why we didn't have large language models in 1939

04:44

or even three years ago.

04:46

We did have something called large language models.

04:48

They didn't work very well three years ago,

04:51

began to work two years ago.

04:53

We've seen a tremendous progress that's happened in the last two years.

04:58

In 1999, I was asked to make a prediction of when would we see AGI,

05:05

artificial general intelligence.

05:08

And so I figured that this chart would continue, which it has.

05:13

And I figured we'd need about a trillion calculations per second to do AGI.

05:19

So I estimated 2029.

05:23

That was met with a lot of skepticism.

05:31

Stanford had actually been monitoring my predictions.

05:34

They called an international conference to talk about my prediction.

05:37

And hundreds of AI scientists came from around the world.

05:44

And they agreed that it would happen.

05:46

We would achieve AGI, but not within 30 years.

05:49

The estimate was 100 years.

05:52

And I've talked actually to some of the people who were there

05:55

who said 100 years then

05:57

and they're basically agreeing it's going to happen very soon.

06:00

Musk says it's going to happen in two years.

06:02

It's not an unreasonable position.

06:04

Other people saying three or four years,

06:07

I'm sticking with five years.

06:09

But it could happen soon.

06:11

But everybody agrees now, AGI is very soon.

06:16

So I have another book coming out,

06:20

"The Singularity is Nearer."

06:23

(Laughter)

06:25

And I've got about 50 graphs in there.

06:30

I can't explain it right now, but if you talk to me later,

06:34

I can explain these charts,

06:36

but it basically shows that artificial intelligence

06:40

is going to take over everything.

06:44

The amount of --

06:45

(Laughter)

06:47

The amount of money that we make right now

06:50

is ten times greater in constant dollars

06:52

than it was 100 years ago.

06:54

We were very, very poor 100 years ago,

06:57

there was no government programs.

06:59

So we're much richer than we were then.

07:02

And the movement,

07:06

not only of computation,

07:07

but every single technology,

07:10

is done by creating,

07:12

taking the latest thing we've created and making the next one.

07:17

We take the latest chip

07:18

and we use that to create the next one.

07:23

We have greater wealth, as I said, that leads to better education,

07:27

leads to better doctors,

07:29

leads to healthy people,

07:31

leads to more global wealth.

07:33

All of these things work together.

07:35

AI supercharges everything.

07:38

So I could talk about each thing

07:41

as being actually revolutionized.

07:44

I think the most interesting thing is actually medicine.

07:47

There are a lot of people who are experts in AI who are against what's happening,

07:52

and they're very nervous about it, and they think it's going to wipe us out.

07:56

But people tend to get diseases which are threatening to them.

08:02

And what's going to happen?

08:04

People are going to get diseases and AI is going to come up with a cure,

08:09

very soon, which will lead to a great deal of appreciation.

08:16

People say that AI is not creative.

08:18

It's very creative.

08:20

You can actually put together possibilities that might work.

08:25

For example, Moderna was trying to create their COVID vaccine.

08:29

They actually put together a list of different mRNA sequences.

08:33

Now, what would we do in the past?

08:35

Someone would come in and say, "OK, there's several billion.

08:37

Let's try this one."

08:39

Or maybe they'd pick three.

08:40

You can't ...

08:43

do a clinical test on billions of different possibilities.

08:47

But that's exactly what they did by simulating the reaction.

08:51

And that took two days.

08:53

So in two days, they created the Moderna vaccine.

08:57

And that is still on the market.

09:00

It's been the best vaccine.

09:01

It was done in two days.

09:04

And we're going to do that with every other thing.

09:07

There's some very promising cancer cures that are out there, which AI produced,

09:12

and they're looking very promising.

09:14

The next few years is going to be remarkable for medicine.

09:18

We had 190,000 proteins done by people in 2022.

09:24

2023, AlphaFold 2 did 200 million,

09:29

basically every protein and how they fold.

09:34

Every protein that's used in humans

09:36

and every other species on Earth

09:39

done in a few months.

09:41

And we're going to be able to go through

09:44

cures for diseases at the same rate.

09:49

So we're going to simulate trials digitally.

09:54

It'll be much safer.

09:56

It'll be a million times faster.

10:00

And by the end of this decade, as we go into the 2030s,

10:03

we're going to achieve a new milestone.

10:06

It's called longevity escape velocity.

10:11

Let me say that again,

10:12

because you're going to be hearing a lot about that.

10:15

Longevity escape velocity.

10:17

Right now you go through a year

10:19

and you use up a year of your longevity.

10:22

However, scientific progress is also progressing,

10:26

which is actually bringing us back.

10:27

It's giving us cures for diseases, new forms of treatment.

10:32

So right now you're getting back about four months.

10:35

So you lose a year, you get back four months,

10:37

so you're losing eight months.

10:39

However, the scientific progress is on an exponential.

10:43

It's going to get faster and faster.

10:45

And as we get to the early 2030s,

10:48

let's say between 2029 and 2035,

10:50

depending on how diligent you are,

10:53

you're going to get back a full year.

10:56

So you lose a year, you get back a year.

10:59

As we actually go past that point,

11:00

you'll actually get back more than a year and you'll go backwards in time,

11:05

which would be cool.

11:07

(Laughter)

11:12

Now some people are concerned we’re going to run out of resources.

11:17

And actually, if we just went ahead and didn't make any new resources,

11:21

we would run out of resources like energy, for example.

11:25

But this is not happening in a vacuum.

11:29

AI is revolutionizing everything.

11:32

For example, we only have to connect one part in 10,000

11:38

of the sunlight that falls on the Earth to meet all of our energy needs.

11:41

It's plenty of headroom and that's growing exponentially

11:45

and will achieve that within ten years.

11:48

And that's also growing exponentially.

11:52

So ...

11:54

We will have plenty of resources.

11:58

And when we get to the 2030s,

12:01

nanobots will connect our brains to the cloud

12:06

just the way your phone does.

12:07

It'll expand intelligence a million-fold by 2045.

12:13

That is the singularity.

12:16

We will be funnier.

12:20

(Laughter)

12:21

Sexier, smarter, more creative,

12:25

free from biological limitations.

12:28

We'll be able to choose our appearance.

12:31

We'll be able to do things we can't do today,

12:33

like visualize objects in 11 dimensions.

12:36

We can speak all languages.

12:38

We'll be able to expand consciousness in ways we can barely imagine.

12:43

We will experience richer culture with our extra years.

12:49

So I've recently become a grandfather

12:52

I'm very much looking forward to that,

12:55

spending more time with family, friends,

12:57

loving and being loved,

13:00

all enhanced by AI.

13:02

I believe this gives life its greatest meaning.

13:05

Thank you very much.

13:06

(Applause)