HomeVideos

Science Corner Special! David Friedberg, Cleo Abram, Alex Filippenko, and Keller Rinaudo Cliffton

Now Playing

Science Corner Special! David Friedberg, Cleo Abram, Alex Filippenko, and Keller Rinaudo Cliffton

Transcript

1865 segments

0:00

Good morning.

0:04

Where are my besties? They are not here.

0:07

What does that mean?

0:09

Science corner.

0:14

I have a guest host because my besties

0:16

abandoned me for Science Corner. Let's

0:18

see who it is.

0:20

>> Leo, you're one of the fastest growing

0:22

channels on YouTube right now.

0:23

>> Former box journalist that left to go

0:25

independent on YouTube. She went from 0

0:27

to 5 million subscribers in just 3

0:29

years.

0:30

>> I don't know many other YouTube creators

0:31

who are going to go to those lengths.

0:34

>> There's a lot of very lucrative

0:36

fear-mongering going on. That's why I

0:39

want to bring a more optimistic point of

0:40

view into the conversation to help

0:42

people imagine what could go right.

0:45

That's why I went independent.

0:48

>> Ladies and gentlemen, please welcome

0:51

Cleo Abram.

0:53

[Music]

1:01

Welcome. Thank you. Thanks for being

1:03

here.

1:03

>> Thanks for having me.

1:04

>> Grab a seat. You were here all day

1:06

yesterday.

1:06

>> Yeah.

1:07

>> How was it?

1:07

>> Having a great time. This is my first

1:08

All-In Summit. I'm so excited to be

1:10

here.

1:10

>> Welcome. So, Cleo, you have 6 million

1:14

subscribers on your YouTube channel. We

1:16

have under a million. Thank you for

1:19

having us on your show.

1:21

>> Welcome.

1:23

How did you do it? What happened? So,

1:26

you you were at Vox before.

1:27

>> I was. Yeah.

1:28

>> And you were an independent director. I

1:30

mean, you were doing other projects.

1:32

Tell us how you set up this channel on

1:34

YouTube, why you did it, and how did it

1:35

get so big so fast?

1:37

>> Yeah. Huge if True seems to me to be a

1:40

bit of a microcosm of this big shift

1:42

that we're in with media generally right

1:44

now. I was at a media company um and

1:47

making what we call explainer

1:48

journalism. So taking complicated issues

1:50

and making them understandable both to

1:52

me and to millions of people. And I went

1:56

independent to start this show because

1:58

there was something that I felt like I

1:59

was missing when I looked out into my

2:01

media diet. I really wanted to find a

2:03

show that was optimistic that helped me

2:06

see where were the people that are

2:08

working on hard problems, making them

2:10

better every day in a way that I could

2:12

understand and I could participate in.

2:15

So, I left the media company where I

2:17

was, started this show, and had the

2:19

opportunity because of what YouTube

2:21

offers to reach a global audience very

2:23

quickly and find out, oh my god, I'm not

2:25

alone. Oh my god, there are millions of

2:27

people that also want this kind of show.

2:29

And YouTube made that bet that if you

2:32

allow anyone to create their best

2:35

creative work, the most the widest

2:37

audience will watch. And so YouTube has

2:39

become in the last 18 months, I think,

2:41

the most watched streaming platform on

2:43

televisions. So, we're in the middle of

2:45

this big moment of change in media and

2:48

how media gets made. Um, and I I don't

2:51

think most people know that it's really

2:53

happening. They know that YouTube shows

2:55

can get big, but they don't really

2:56

understand this shift that we're in. And

2:58

by the way, the shift is also very

2:59

exciting for streamers because they're

3:01

looking at this and they're saying, you

3:03

know, a Netflix of the world, I used to

3:05

make a Netflix show as well, can look at

3:07

this incredible new wealth of creativity

3:11

and IP and say, "Oh my god, who do we

3:13

want to work with to give, you know,

3:15

upfront

3:16

capital to make something that's even

3:18

bigger?"

3:19

something you and I have talked about

3:20

because if you're on Netflix today and

3:22

we're going to talk with Neil and Ari

3:25

today,

3:26

>> you can if you're an independent

3:28

director, you go to Netflix, they're

3:29

like, "Okay, we'll pay for your

3:30

production cost plus 10%." And it's like

3:33

quite different than what it used to be

3:34

like when you made friends, you could

3:36

make the show and then you could

3:37

eventually make like a VC. Like you can

3:38

make hundreds of millions of dollars if

3:40

it worked out and it became a a massive

3:41

show, but you're basically capped at

3:44

Netflix. But YouTube's quite different.

3:46

So there seems to be a financial or

3:48

economic incentive both creative freedom

3:50

but also this economic incentive to go

3:51

to YouTube. But then how does financing

3:53

happen? Like where can creators drive

3:56

the engine to fund and create new

3:58

content?

3:59

>> Well, most YouTubers have adfunded

4:02

businesses. And so what that requires is

4:04

you go out on your own as we did with

4:06

huge if true. We went independent. We

4:08

started this show. the show grows and

4:10

then you are able to get sponsors who in

4:13

turn fund better and better work and it

4:16

continues to scale. Um, the traditional

4:19

model of paying upfront for a show that

4:21

then the streamer owns offers something

4:23

very different and I think we're in an

4:26

interesting flexible moment of change

4:28

right now where a Netflix might say,

4:31

"Wow, we see a really exciting show on

4:34

YouTube. we want to allow that creator

4:36

to make something that is a version of

4:38

that IP that is bigger and we'll invest

4:40

in that upfront. And so what I think

4:42

we're seeing is for the same creator and

4:44

the same kind of IP, you can have a

4:47

really wonderful relationship between

4:49

the kind of show that you can make when

4:51

you can reach global audiences

4:53

immediately

4:54

>> and grow and see how far you can take it

4:57

with an advertising model. And then at

4:59

the same time, you might be able to take

5:00

that gem of an idea and say, "What would

5:03

I do if I had upfront capital?" So, I

5:05

think there's a really interesting way

5:06

in which these things all work together.

5:09

And some of the headlines make it seem

5:10

as as though this is, you know, an

5:12

antagonistic moment in media. I think

5:14

it's really great for everybody. I think

5:16

it's a really, really exciting. I'm also

5:17

the optimist, so of course I'm going to

5:19

say that.

5:19

>> Yeah. But I'm I'm actually curious to

5:21

hear what Neil thinks at YouTube. I know

5:22

you know him

5:24

>> because it opens up a window I think

5:26

right now for YouTube to suck up some of

5:27

the best content creators in the world

5:29

from the more traditional platforms

5:31

broadcast and streaming.

5:32

>> Yeah, it goes both ways.

5:33

>> Yeah. But so just talking about your

5:35

show um your show is so great because it

5:37

it really meets what I always say is

5:40

missing in media today, which is we've

5:42

got this deep sort of technimism.

5:45

Everyone thinks that technology always

5:47

has a catch. There's always something

5:49

bad emerging. Robots are going to kill

5:51

us all. AI is going to wipe out human

5:53

civilization. Nuclear power is going to

5:55

melt down and destroy neighborhoods.

5:57

Every point of technology has some

6:00

negative angle, but then that becomes

6:01

the cycle. You watch all the shows on

6:03

Netflix, you watch all the movies, Aaron

6:05

Brochovich, like the the ones that work,

6:07

the ones that seem to resonate, which

6:09

means that's what people truly kind of

6:11

want are the ones that talk about things

6:14

gone wrong. But your show is quite

6:15

different. And you talk about what if

6:17

things go right. Why do you think that

6:20

is resonating? And are we changing or is

6:22

it are you kind of capturing a a small

6:25

audience and the bigger one still sort

6:27

of technopessimistic?

6:28

>> Well, the best thing by far about making

6:30

this show is realizing that there are

6:32

millions of people out there that also

6:34

want that same kind of work. I mean, you

6:36

see it with Science Corner in so many

6:37

ways those are very similar in tone. And

6:40

I think from from my perspective when I

6:43

when I started this show, I really was

6:45

looking for a part of my media diet that

6:48

I wasn't getting anywhere else. And

6:49

that's what makes making something

6:50

yourself on YouTube so special. You're

6:53

creating something asking are there

6:55

millions of people out there like me?

6:56

And and the answer turns out to be yes.

6:58

With respect to optimistic science and

7:00

tech content specifically the reason why

7:03

I make it in the first place. We spend

7:05

months on these episodes. We travel all

7:07

around the world. We invest a huge

7:09

amount in the animations and the

7:11

technical explainers so that you can

7:12

understand without any background at all

7:15

quantum computing and the impacts

7:17

supersonic planes and how we're trying

7:18

to bring them back. Uh I was in a

7:20

zeroravity plane the other day trying to

7:23

explain the cutting edge of of gravity

7:25

research and theoretical physics. These

7:27

are things that millions of people can

7:28

understand if you explain them in the

7:30

right kinds of ways. And that's what we

7:31

try and do every day. And the reason why

7:33

we do that is because we genuinely

7:36

believe that when people see those

7:37

better futures, they'll help build them.

7:39

That's what I want to do. I'm not an

7:41

engineer. I'm not a scientist. I look

7:43

out at the world and I think, "Wow,

7:45

there are so many people working on hard

7:46

problems. I want to know how I can

7:48

participate." And so my hope is that's

7:50

what we're doing every day.

7:51

>> We used to have that after World War II.

7:53

>> I always tell people like uh the

7:55

Disneyland opened up in 1955. There's a

7:58

YouTube video called the Disney History

7:59

Institute. It's the channel and it shows

8:01

like what Tomorrowland was like when you

8:03

when Disney opened in 1955 and it was

8:06

all about like we're building this

8:07

better world with all of these crazy

8:09

technologies. Rockets to the moon,

8:11

plastic so we could all have cheap

8:12

furniture. Like there were all these

8:14

there was a crazy device that they had

8:15

in the kitchen called the microwave

8:16

where you could cook in 30 seconds so

8:18

you wouldn't have to like sit around and

8:19

cook for hours. But we've lost that. Um,

8:22

and I really hope that your content

8:24

resonates with more people and that we

8:26

get there again. So, Cleo's going to

8:28

join me this morning for two really fun

8:30

panels that we're going to have. Um, and

8:32

we're going to kick it off now.

8:36

We used to look up in the sky and wonder

8:39

at our place in the stars.

8:44

How thrilling must it be to truly

8:46

discover something or understand

8:48

something that no human on earth has

8:51

ever seen or understood? He was a member

8:53

of both the supernova cosmology project

8:56

and the high supernova search team to

8:58

discover that the universe is

9:00

accelerating. A leader in all of these

9:03

undertakings.

9:04

>> That's one of the big questions of

9:05

cosmology.

9:08

Ladies and gentlemen, please welcome

9:10

Alex Filipeno.

9:20

Wow.

9:25

Wow. This is so fantastic to see you all

9:27

here. Good morning, David. Uh, thank you

9:30

for inviting me to Science Corner. It's

9:33

such a pleasure. Most of you probably

9:35

don't know that in fact David was a

9:39

student of mine at UC Berkeley 28 years

9:42

ago and became an astrophysics major. In

9:46

fact, you know, so I feel like I had

9:49

some influence on him. I'll take some

9:52

credit. Uh, you know, uh, as Joe Sai

9:57

said yesterday, teachers want their

10:00

students to become more successful, to

10:02

become better than they are. Uh, and I

10:05

always knew that David would be very

10:08

successful in his career, but I didn't

10:10

know that he'd be quite this successful.

10:13

So, good good job, David. You know, I'd

10:17

also like to uh Yeah,

10:21

I'd also like to officially acknowledge

10:24

California's 175th birthday today,

10:27

California admission day. Uh so, yep, we

10:32

were told that yesterday and I looked it

10:35

up and it's true. So, you know,

10:37

California is be is beginning its uh

10:41

176th orbit around the sun. May may may

10:46

it be revolutionary, so to speak. Right.

10:49

Get it? Get it? Okay. Uh,

10:52

okay. Well, it's my pleasure to be uh

10:54

speaking today about the James Web Space

10:57

Telescope as just one example of an

10:59

amazing mission where humans are

11:02

pursuing science and exploring the

11:06

universe. It's an amazing device and uh

11:10

it's already brought us so many

11:12

interesting results. Now, it was

11:13

launched on Christmas Day 2021 aboard an

11:17

Aryan 5 rocket and it's a wonderful

11:20

example of how international

11:23

collaboration and cooperation in this

11:25

case between the US, Europe, and Canada,

11:28

can lead to incredible achievements in

11:31

very complex projects.

11:34

There are many comparisons with NASA and

11:37

issa's Hubble Space Telescope, which has

11:40

been serving us well for over three

11:41

decades. The primary one is that the web

11:45

has a much bigger mirror. And a mirror

11:47

can be thought of as a gigantic eyeball,

11:49

a collecting area that brings together

11:53

faint starlight from distant parts of

11:56

the universe. And so the bigger the

11:58

collecting area, the fainter the object

12:00

you can see. And web has six times the

12:03

collecting area of Hubble. So it's a

12:05

more powerful telescope.

12:08

Fundamentally, the web was designed to

12:11

explore our origins. Where did we come

12:14

from? How are we evolving? What's going

12:17

to happen far far in the future? How do

12:21

galaxies like the Milky Way galaxy form?

12:24

And how do they evolve with time? Now,

12:27

we know now that many galaxies merge

12:29

together like the group that you're

12:31

seeing here in a beautiful web image. By

12:34

the way, to the lower right of the word

12:36

time there, there's a star with a a

12:39

bunch of spikes. Ignore the spikes.

12:41

They're not beautiful. They're ugly,

12:42

okay? They're just a consequence of the

12:44

interaction of light with the telescope.

12:46

So, ignore the spikes. But here are a

12:49

bunch of merging galaxies. Now, the

12:52

first image NASA released publicly a

12:55

little over three years ago was of a

12:59

tiny part of the sky. Imagine a grain of

13:02

sand held at arms length. Imagine how

13:04

small that looks. Yet in that tiny patch

13:06

of the sky, there are thousands of

13:09

galaxies. These fuzzy things you see out

13:11

there, you can count them if you're if

13:13

you're interested. Over the whole sky,

13:16

we can see about a trillion galaxies, a

13:19

million million galaxies.

13:21

And some of them we see forming just a

13:25

few hundred million years after the

13:28

explosive birth of the universe, the

13:29

so-called big bang. And one of the

13:32

interesting aspects of this image is

13:35

that galaxies started forming and

13:37

evolving earlier than expected. And so

13:40

we're working on that interesting puzzle

13:43

right now.

13:45

How do stars like our sun form? Well,

13:48

they form in stellar nurseries. Giant

13:51

clouds of gas and dust. Fine little

13:55

particles that collect up as a result of

13:57

gravity. and the central densest regions

14:01

collapse and and form these stars. But

14:03

they're hidden from view when looked at

14:06

with most telescopes because we can't

14:08

peer through the dust. The web looking

14:11

at infrared wavelengths, heat

14:13

wavelengths is able to peer inside and

14:16

see newly formed stars and stars that

14:19

are still forming. We can also look at

14:23

discs of gas and dust around newly

14:26

forming stars. This is essentially the

14:30

mechanism by which our solar system

14:32

formed about 4 and a half billion years

14:35

ago. Debris around the newly formed sun

14:39

that collected gradually to form bigger

14:41

and bigger objects, planets.

14:44

All right. How about the death of stars?

14:46

This is a snapshot, a preview of the

14:50

sun's future in about 7 billion years

14:53

when the outer atmosphere will start

14:56

getting gently ejected off, leaving a

14:59

hot dying star in the middle that makes

15:02

the gases glow. The star, the fainter of

15:06

the two that you see there, looks faint

15:08

because there's dust, fine little

15:09

particles that have formed in the

15:12

ejected gases. These particles consist

15:15

of elements heavier than hydrogen and

15:18

helium that were cooked up in the

15:20

nuclear furnace of the star during its

15:23

life. These dust particles can later

15:25

form new stars, planets, and ultimately

15:29

life. And to get most of the heavy

15:32

elements, you need the explosions, the

15:35

cataclysmic disruptions of certain

15:38

varieties of stars at the end of their

15:40

lives. our sun won't explode in this

15:43

titanic way, but some do. And here's one

15:46

that we started studying about 40 years

15:48

ago. Analysis of the web data shows the

15:52

kinds of elements of which we are made.

15:54

The calcium in our bones, the phosphorus

15:57

in our DNA, the oxygen that we breathe,

16:00

the carbon in our cells, the iron in our

16:02

red blood cells. These elements were

16:05

created through nuclear reactions in

16:08

stars billions of years ago. And humans

16:11

understand that is that cosmic or what?

16:14

As Carl Sean used to say, we are made of

16:17

star stuff.

16:19

We can move closer to home and image

16:21

planets in our own solar system like

16:24

Neptune here with its moons and rings.

16:26

And those bright spots on Neptune are a

16:29

storm which has been developing. And so

16:31

you can monitor planetary storms and

16:34

come to a better understanding of

16:37

climate on Earth.

16:40

We can move to other stars and search

16:43

for planets orbiting them. So-called

16:46

exoplanets.

16:47

It turns out that nearly every star you

16:50

see in the sky has a collection of

16:52

planets around it. They're just really

16:54

hard to see here. To see it, the web

16:57

telescope had to place a disc in front

16:59

of the star where that little

17:02

five-pointed thing is in the circle,

17:05

revealing the exoplanet orbiting it. And

17:08

the hope is that through studies of the

17:11

atmospheres of these exoplanets, we will

17:14

find places where life could have arisen

17:18

and maybe even did arise independently

17:21

of life on Earth. And we don't have such

17:24

evidence yet. But once we do have

17:26

compelling evidence for life elsewhere,

17:29

it'll be one of the most monumental

17:30

discoveries in all of humanity.

17:34

Well, you could say this is all very

17:36

interesting, intellectually titillating,

17:39

but so what? Why spend national funds on

17:45

pure research of this type, not applied

17:48

research that will lead in the short

17:50

term to new gizmos, pacemakers, and

17:52

iPhones and things like that? Why should

17:54

we pursue this kind of research with

17:57

taxpayer money? It's a legitimate

18:00

question. Okay. So, let me give you

18:03

three reasons. The first is that of all

18:07

known animals, humans are the only ones

18:10

with the curiosity to ask complex

18:13

questions, abstract questions, questions

18:16

about their very origins. And we have

18:18

the intellectual capability to pursue

18:22

answers to those questions and the hands

18:25

with the posible thumb with which to

18:27

build machines like telescopes and

18:29

particle colliders to help us answer

18:31

those questions. If some subset of

18:34

humanity were to not do this, we would

18:37

be selling ourselves short as homo

18:40

sapiens. Now, you don't need many of us,

18:42

but it's good to have some. The second

18:45

point is that astronomy is a gateway

18:48

science. It's like the bug that bites

18:51

kids and gets them interested in STEM

18:54

fields. Most won't go on to become

18:57

astrophysicists. Okay? Again, that's an

19:00

okay thing. But they'll be more

19:02

motivated to pursue fields of science

19:04

and technology which will lead them to

19:07

careers that are more immediately

19:09

beneficial to society. computer science,

19:11

engineering, medical physics, applied

19:14

physics, those sorts of things. I see

19:17

this all the time as a board member of

19:19

the Shabbo Space and Science Center and

19:21

also at Lick Observatory in the hills

19:24

east of Silicon Valley where I conduct

19:26

much of my research and public outreach.

19:29

Kids love this stuff. Just like I and

19:33

some of my friends were inspired in our

19:36

youth by the American lunar landings.

19:39

What an amazing accomplishment that was.

19:42

We are on the moon. Wouldn't it be great

19:45

to contribute to this grand enterprise

19:48

and go boldly where no one has gone

19:52

before? It's just an an incredibly

19:56

inspiring uh moment and

20:00

the Hubble and web and things like that

20:02

are providing that moment for kids now.

20:05

And then there are the technological

20:07

spin-offs and unanticipated applications

20:11

like quantum physics for the latter.

20:15

Over a century ago, there were two

20:18

outstanding questions in physics. What

20:20

is the nature of light? And why are

20:22

atoms stable? And you could say, well,

20:25

as long as we know how to make light

20:27

bulbs and as long as the floor doesn't

20:29

collapse underneath me, who cares what

20:33

light really is and why atoms are

20:35

stable? You don't need to know, do you?

20:38

Well, physicists over a century ago like

20:40

Einstein, Schroinger, Heisenberg, Boore,

20:43

Plunk, they cared about the workings of

20:46

nature simply to satisfy their

20:48

curiosity.

20:50

No practical applications immediately in

20:52

sight. Fast forward a century, you

20:55

couldn't imagine today's world without

20:57

an understanding of quantum physics. One

21:00

example, lasers, a 13.5 billion dollar

21:03

industry in the US with innumerable

21:06

applications.

21:08

Computer chips. Moore's law with three

21:11

and even two nanometers per pixel. Now

21:13

we have the equivalent of half a billion

21:15

transistors on the head of a pin. That

21:18

is amazing. That's quantum mechanics,

21:20

folks. quantum quantum electronics. And

21:23

then specifically from something like

21:25

the web, lots of uh spin-offs, infrared

21:28

detectors, similar ones are now used in

21:31

medical imaging, night vision systems,

21:33

and environmental monitoring.

21:36

Cryogenetic engineering, you had to cool

21:38

down the telescope. This led to advances

21:40

in cooling systems now used in quantum

21:42

computing, uh superconducting

21:44

electronics, medical imaging, and so on.

21:47

And as just one other example in many

21:50

precision optics and materials segmented

21:53

goldcoated mirrors and deployment

21:55

mechanisms for the web led to

21:57

innovations in robotics metrology and u

22:01

high precision manufacturing. So those

22:04

are just some of the spin-offs from the

22:06

web itself. So I hope I've convinced you

22:10

that spending some small amount of money

22:13

on research of this type is exciting, is

22:15

important, extends our grand vision as

22:19

pioneers of the universe exploring our

22:21

origins. And to give you just a sense of

22:24

scale, over a 10 bill o over 10 years,

22:28

the $10 billion cost of the web was one

22:33

$6 hamburger per US taxpayer per year.

22:38

That's what you contributed to the web.

22:40

Thank you very much. I hope that you

22:42

feel it was worth it, okay, to give up

22:45

this one hamburger. Now, listen. Um, if

22:47

you're interested in this sort of stuff,

22:49

I give much longer talks with more

22:51

details to corporate groups and others.

22:54

Just contact me if you're interested.

22:55

Thank you so so much for being here.

23:02

[Music]

23:09

>> Thanks, Alex.

23:09

>> All right. Good to see you. Grab a seat.

23:14

So, Alex, you are one of the world's

23:16

greatest scientists and science

23:17

communicators. So, David and I have

23:19

prepared a set of rapid fire questions

23:21

for you.

23:21

>> I'll give rapid fire answers

23:23

>> based on what our audience might have

23:25

seen in headlines or might be

23:27

understanding and want to know more

23:29

about about not just James Webb but

23:31

generally.

23:32

>> Yes. I just gave one example of web

23:34

time. Yeah.

23:35

>> Mhm.

23:36

>> Yeah. So, one of the places I want to

23:38

start is searching for life on

23:40

exoplanets. I think many people might

23:42

understand that James Webb is doing that

23:44

but might not fully understand how and

23:46

what the implications might be. So as a

23:49

way to understand this if we were

23:50

looking at Earth from 100 light years

23:54

away.

23:54

>> Yeah.

23:55

>> What would we see and how would we

23:57

understand that as life?

23:58

>> Yeah. Yeah. So what you want to find is

24:00

some sort of chemical disequilibrium.

24:02

Now that sounds fancy but what do I

24:04

mean? In the case of the atmosphere of

24:06

Earth, the simultaneous presence of

24:09

oxygen and methane is very curious

24:12

because methane oxidizes. That is, it

24:15

reacts with oxygen very quickly. And so,

24:17

you wouldn't expect any methane in the

24:19

atmosphere unless there were some more

24:22

or less continuous source of that

24:24

methane. And although methane can be

24:26

produced through chemical means having

24:28

nothing to do with biology, it's also

24:31

produced by biology. uh you know Carl

24:34

Sean called it boine flatulence right uh

24:36

so it's the decay of uh of biological

24:40

organisms and so if we were to find that

24:42

in another exoplanet atmosphere that

24:45

wouldn't be absolutely definitive but it

24:48

would be sort of a a flash point wow we

24:50

better study that planet more because

24:52

that's one that could have life yeah

24:54

>> and we're seeing that

24:55

>> yeah we're beginning to see that we've

24:56

not seen methane and oxygen in any other

25:00

uh planetary atmosphere yet but Um uh

25:03

certainly there there are interesting

25:05

signs of of elements that are reported

25:07

by the web through these kinds of

25:09

atmospheric studies.

25:10

>> One of the other big discoveries with

25:12

the web was these early massive

25:14

galaxies.

25:15

>> Yeah. I mentioned the early massive

25:16

galaxies. Yeah.

25:17

>> And there was a paper that followed.

25:19

Yeah. You and I talked about this and

25:21

there's been a lot of social media and

25:23

nerdy YouTube videos. Yeah. about this

25:26

paper and the theory that these early

25:29

massive galaxies may actually disprove

25:32

the big bang theory by saying these

25:36

early massive galaxies are responsible

25:38

or account for what we see as what's

25:40

called the cosmic microwave background

25:42

radiation which may mean that the what

25:44

we assumed was coming from the early

25:45

universe from the big bang may actually

25:47

come from these galaxies and it's like

25:49

do we have it all wrong we may and these

25:52

papers are getting a lot of attention is

25:53

the b big big bang theory disproven

25:55

moving now with this discovery.

25:57

>> The the big bang theory is in on is on

25:59

very solid ground. There are many

26:01

details we don't understand. The basic

26:03

tenets, however, of the theory are just

26:05

three-fold. The universe long ago was

26:08

hot. It was dense and it was expanding.

26:11

Nothing in those studies

26:14

uh contradicts any of that. Uh as I

26:17

mentioned, the early formation of

26:18

galaxies is an interesting puzzle. It

26:21

means that our understanding of how

26:23

galaxies formed and evolved is still

26:25

incomplete. But that's part of the fun

26:27

of doing science. There's new things.

26:28

You know, the cosmic microwave

26:31

background radiation is the the

26:33

afterglow of the big bang. And it turns

26:36

out it uh agrees to very high precision

26:39

with a very single temperature. Meaning

26:42

that the universe everywhere was the

26:44

same temperature then expanded by the

26:45

same amount and we see see the same

26:47

temperature everywhere. There's no way

26:49

you can do that with galaxies forming at

26:52

a range of times and distances. They

26:54

would each contribute light that would

26:57

not give this so-called black body

26:59

thermal spectrum. And there are many

27:01

other details of the microwave

27:02

background, the spots and stuff that are

27:04

not at all addressed. So, a lot of these

27:07

theories, you know, as scientists, we

27:08

can dream up things and we just kind of

27:10

put them out there to be explored more.

27:12

But of course, the media likes to

27:15

highlight the the really snazzy sounding

27:18

things. And so sometimes, often the very

27:21

speculative ideas get way too much

27:24

attention. We're exploring them, but

27:27

they're probably wrong.

27:28

>> Yeah.

27:29

>> Okay.

27:29

>> Yeah. Okay.

27:30

>> So, I don't need to throw out what I

27:31

learned in high school.

27:33

>> No, no. The Big Bang is on very solid

27:35

ground.

27:36

>> What about the theories coming out?

27:37

We've been talking a little bit about

27:38

this um on whether or not we are inside

27:42

a black hole.

27:43

>> Oh yeah. Are we inside a black hole?

27:44

Yeah. So a black hole is a region of

27:46

space where matter is compressed so much

27:48

that nothing not even light can escape.

27:51

And it turns out that in a sense our

27:53

universe, if you look at the total

27:55

amount of matter, dark matter and dark

27:57

energy and all that stuff, visible

27:58

matter in the volume out to which we can

28:01

see, okay, that has uh about the right

28:05

value to make the universe as a whole,

28:09

wh

28:11

it resembling a black hole, h

28:16

that would mean that our universe is

28:18

finite. We don't actually know whether

28:20

it's finite or infinite. We actually

28:22

only know that it's much bigger than

28:24

what we can see. And mathematically

28:26

there is some correspondence between the

28:29

equations governing a black hole and

28:31

those governing the universe. But there

28:33

are some important differences like a

28:35

black hole is a physical structure

28:37

within our four space-time dimensions

28:40

like right here. Whereas applying that

28:42

to the whole universe is um it's a

28:45

qualitatively different idea. But there

28:48

are some mathematical correspondences

28:50

that um that that are useful and

28:53

interesting. I personally doubt that we

28:56

are uh a a giant black hole. Some people

29:00

say it's actually a black hole that was

29:02

given birth

29:04

from another universe. And for that

29:06

there's really no evidence. Um,

29:08

>> but Alex, one of the the many things

29:10

that blows my mind about astrophysics

29:13

and cosmology, the further out we look,

29:17

the faster objects are moving away from

29:19

us

29:19

>> to a point that at a certain distance

29:22

from us, the objects in whatever

29:25

direction we look are moving away from

29:27

us at nearly the speed of light or even

29:30

faster. And so that becomes the

29:32

observational limit of our ability to

29:35

see or ultimately experience our

29:37

universe. That there's this boundary

29:39

that without crossing the speed of

29:41

light,

29:42

>> we will never get to and we will never

29:44

see what's beyond it.

29:45

>> Right?

29:46

>> That's our observable universe.

29:48

>> That feels pretty up.

29:51

>> Well, you know, space can become really

29:53

big. Okay. And in fact, you know, good

29:56

student, you asked me the right

29:57

question.

29:58

>> You need some help?

29:58

>> Ah, thank you very much, my assistant.

30:00

Okay, so I've got these galaxies here.

30:02

They don't expand, by the way. They're

30:04

held together by by gravity in in the

30:06

case of real galaxies, but then the hose

30:08

between them expands. So, let's expand

30:10

it here. Try not to aim at your eyes or

30:12

David's eyes. That would be very bad

30:14

lawsuits and stuff. But anyway, from the

30:17

perspective of our galaxy here, the the

30:20

more distant ones, you know, with each

30:21

bit of space expanding can and do go

30:24

away faster than the speed of light. And

30:26

Einstein wouldn't wrap me on the

30:28

knuckles for that. Einstein simply said

30:30

that no material object or no

30:32

information can travel through a

30:34

pre-existing space faster than light.

30:36

But space itself expanding, especially

30:38

if it expands exponentially, which we

30:40

think it did early on in its existence,

30:43

it grows faster than the speed of light,

30:45

and you get a truly humongous universe,

30:47

maybe even an infinite universe. And

30:49

yeah, most of it we can't see, but there

30:52

are other independent volumes out there

30:55

where we could be having this

30:57

conversation right now or or you could

31:00

not like what I said and punch me in the

31:02

face, but then I would respond by p

31:05

punching you in the face. In other

31:06

words, all these possibilities could

31:08

occur in these parallel observable

31:10

universes beyond the observable part

31:13

that we can see. And it's freaky, but

31:16

this is the kind of stuff we get to

31:17

think about. And I'll ask you the

31:18

question I asked you on the phone the

31:19

other day, which is there's mathematics

31:22

that shows that the geometry may be

31:24

inverses inside of a black hole or some

31:26

some some things are reversed or

31:28

inverse. What's the right term?

31:29

>> Right.

31:30

>> Therefore, is the expanding universe

31:32

that we see our version of being inside

31:34

of a black hole which is effectively an

31:37

accelerating contraction towards the

31:39

singularity.

31:40

>> Yeah. So um what David is referring to

31:42

is that if you look at the mathematics

31:43

of a black hole from our perspective,

31:46

what we call space and time outside

31:50

reverse their meaning. Um time becomes

31:53

space and space becomes time in terms of

31:55

directionality. So for example, if

31:57

you're in a black hole, there's no way

31:59

you can avoid the so-called singularity

32:01

where you get squished into nothing

32:02

because it's in your future no matter

32:05

what you do. Now applying that as you

32:08

wanted to do to the whole universe. I

32:10

don't think that the correspondence is

32:13

such that the expansion that we see is

32:18

the reversal effect of um this um going

32:21

toward the singularity because uh well

32:24

because of some technical issues. Again

32:28

if you look at the mathematics there are

32:29

some interesting correspondences but

32:31

they shouldn't be taken too too

32:33

literally in most cases.

32:34

>> Okay.

32:34

>> Yeah. So the question I would be

32:36

wondering if I were in the audience

32:37

listening to we have a expanding

32:39

universe. It is uh potentially infinite.

32:43

My question would be so where is

32:45

everybody?

32:46

>> Yeah. So yeah where are they all the

32:48

fairmy paradox?

32:49

>> Is the great filter in front of us is

32:51

the question.

32:51

>> Yeah. I actually think the great filter

32:53

is in front of us. That's a an idea

32:55

where uh civilizations such as ours

32:58

rarely get past this point uh where they

33:02

can achieve interstellar travel easily

33:03

and stuff. Something happens either

33:06

intentionally or unintentionally or

33:08

through neglect they get destroyed. All

33:10

right. And uh I I I actually think that

33:14

first life at our level is very rare.

33:17

I'm not saying we're alone, okay? But

33:19

very rare. And the second punch of the

33:22

one-two punch is that there's almost

33:24

always a great filter. And so rarely do

33:28

civilizations reach interstellar

33:31

capability to the extent where they

33:32

colonize a galaxy. If it had happened

33:35

even once in our Milky Way, we would

33:37

easily see the aliens here. Not just the

33:40

sketchy UFO evidence, okay, that's been

33:43

presented. Doesn't reach the bar of

33:45

credibility and science, by the way. Uh,

33:48

but we would be the aliens more likely,

33:50

right? Because they would already have

33:52

colonized Earth and we would have been

33:54

the aliens. So, I think they're

33:56

>> makes sense to maybe not travel and just

33:59

transmit information back and forth and

34:00

maybe we just don't know how to see or

34:03

understand the information that's being

34:04

sent our way and we don't know how to

34:05

transmit it.

34:06

>> Yeah, certainly communication techniques

34:08

could be different. So, I I'm not saying

34:10

we know at all. And, you know, there

34:11

could even be this dark forest where

34:13

they're intentionally,

34:15

you know, uh not transmitting toward us

34:18

cuz they don't want us to know about

34:19

them. They're sort of maybe even

34:21

pursuing us and stuff going to kill us

34:23

before we kill them. Um these are all

34:25

possibilities you know but um I think

34:27

the most likely in my view is that the

34:30

what I said and also the vastness of

34:33

space means that we wouldn't be able to

34:35

communicate or or hear from um aliens

34:40

that were much farther away than you

34:42

know 100 or a thousand lighty years and

34:44

the galaxy is 100,000 light years in uh

34:47

space in in extent. So unless they

34:50

colonize the galaxy, if they're very

34:52

rare, we won't see them because the the

34:56

signals are too faint and they haven't

34:57

had a chance to to get here. You know, I

34:59

>> I want to give you an opportunity to

35:01

share with us uh what's going on with

35:04

respect to hiring graduate students and

35:06

funding research right now.

35:07

>> Yeah.

35:08

>> I've heard from lots of scientists uh

35:10

that NIH grants have been cut.

35:13

>> Yeah.

35:13

>> And it's affecting their ability to hire

35:15

and build out their labs and do some of

35:17

their research. are you seeing the same

35:20

today and maybe just give us a sense of

35:22

on the ground what's going on with

35:24

respect to what you're seeing in

35:26

funding.

35:27

>> Yeah. Uh the issue is a very serious

35:29

one. Um in a sense, you know, science is

35:32

is under attack to some degree,

35:34

intentionally or unintentionally, maybe

35:36

part of a a broader thing. Uh but it's

35:39

it's having an enormous effect. The

35:42

number of National Science Foundation

35:44

graduate fellowships, for example, was

35:46

cut in half this year. NASA funding has

35:49

been cut in half and I'm all for going

35:51

to the moon and Mars. But if all of the

35:53

remaining NASA funding goes toward those

35:56

ideals, then nothing will be left for

35:58

professors and their students and

36:00

postocs to analyze the great data that

36:03

the Hubble and Web and all that are are

36:05

giving us and and various space

36:07

telescopes are now in jeopardy of not

36:09

being launched. The Nancy Grace Roman

36:11

telescope and stuff. So graduate schools

36:15

are um now reluctant to to accept new

36:18

graduate students and to hire new

36:20

postocs because frankly we don't have

36:22

the funding with which to do so. And I'm

36:24

personally very worried about my own

36:26

research group. I'm not taking on any

36:28

new researchers until I personally can

36:31

fund my existing group. That's got to be

36:33

my my primary concern right now. and I

36:36

don't know how I'm going to do it, you

36:37

know, and others throughout my field and

36:41

even in a sense you could say more

36:43

immediately useful fields like NIH you

36:46

said, right? Cutting the funding there.

36:48

These are researchers who are going

36:51

doing things that are going to be good

36:52

for humanity soon, not these

36:55

unanticipated spin-offs. But the kind of

36:57

stuff I do should be supported as well.

37:00

>> Yeah. Well, um, you know, I was a

37:03

physics and math major. I don't know if

37:05

I would have gotten the math degree,

37:06

I'll be honest. But, um, I took Alex's

37:08

Astro 10 class cuz I was partying a

37:10

little bit too much that year and I'm

37:11

like, I got to take an easier class. I

37:12

heard it's a great 800 people in the

37:14

class. The most inspirational class I've

37:17

ever taken and every student that's

37:18

taken it says the same. And Alex became

37:20

nine times, 10 times, I don't know how

37:22

many times, the favorite professor at

37:24

Cal Berkeley. And I think you can all

37:26

understand why his contributions to

37:28

students and to science are profound.

37:30

So, please join me in thanking Alex.

37:32

>> Thank you. Thanks so much.

37:37

Regulators are now approving drone

37:40

deliveries.

37:40

>> There is one company that is huge in

37:43

this space. They're called Zipline.

37:45

>> Keller Renado Clifton is the co-founder

37:48

and CEO of Zipline, the world's largest

37:50

autonomous logistics and delivery

37:51

system.

37:52

>> We should get back to like building real

37:53

things in the real world.

37:54

>> What they've been showing is way more

37:56

advanced than anything from Google or

37:58

Amazon. What nerds are working on during

38:00

the weekends in their garages today are

38:02

what will be the giant companies of five

38:04

or 10 years from now.

38:06

>> Ladies and gentlemen, please welcome Zip

38:09

Lines Keller Ronaldo Clifton.

38:12

[Music]

38:13

[Applause]

38:16

[Music]

38:18

[Applause]

38:19

[Music]

38:22

Well, good morning everybody. So, David

38:24

was talking a little bit about

38:25

technesses. I hadn't heard that before,

38:27

but by a quick show of hands, how many

38:28

of you have read an article in the last

38:30

year about robots trying to kill you or

38:32

take your jobs?

38:34

Okay, so basically everybody, the cool

38:37

thing is today we get to talk about

38:38

robots that save lives. And I thought

38:40

it'd be cool to just take you back to

38:42

2016. Uh in in 2016, you know, we had

38:46

been our our backgrounds were in

38:48

automation and robotics. We had this

38:50

simple naive idea that it should be it

38:53

should be possible to build a new kind

38:55

of logistics system a fully automated

38:57

logistic system that would be 10 times

38:58

as fast half the cost and zero emission.

39:02

The first contract we signed was with

39:04

the government of Rwanda to deliver

39:06

blood transfusions primarily to moms

39:08

with postpartum hemorrhage um at about

39:10

21 different hospitals across the

39:11

country. And so I thought it'd be cool

39:12

to just show you this video. It's

39:13

actually a video I took on my iPhone. So

39:15

nothing nothing fancy but you can

39:18

actually see uh what we call zips that

39:21

this is the very first version of this

39:22

autonomous aircraft that we had built.

39:24

We were delivering using a really simple

39:26

paper parachute to a hospital called

39:28

Cubai which is in a rural part of

39:29

Rwanda. Here we were delivering I think

39:31

three units of packed red blood cells

39:33

and platelets. We could deliver to a

39:35

couple parking spaces um in a way that

39:37

was about 10 times as fast. Uh and you

39:40

can see the women in this in this video

39:41

are like what the hell did we just see?

39:44

which is funny. You know, I was taking

39:45

the video. I kind of looked up at them

39:46

and they were looking at me very

39:48

suspiciously. You know, we often try to

39:50

describe, it's a funny thing about what

39:51

we do. We try to describe uh what we're

39:54

going to do to either to doctors or to

39:56

nurses or hospital administrators and

39:58

they look at us like, you know, we're

40:00

completely crazy or on drugs.

40:04

You know, and so we have to do the first

40:06

delivery. Once we do that first

40:07

delivery, a doctor looked at me and

40:09

said, "It's as though Jesus Christ is

40:11

delivering blood from the sky." But

40:13

what's what's hilarious is that, you

40:15

know, you get about seven days the way,

40:17

you know, the way we work as humans, you

40:18

get about seven days of science fiction

40:20

amazement and then people are completely

40:22

bored of it. Like it's totally normal.

40:24

In fact, I had one nurse look at her

40:26

watch and then look at me and say, "It's

40:27

30 seconds late."

40:30

Which made me realize, you know, humans

40:32

go from science fiction to entitlement

40:34

in approximately 7 days, which is great.

40:36

That's what technology should do. you

40:38

know,

40:41

it should fade into the background like

40:43

let doctors and nurses do the work that

40:45

they were trained to do which is save

40:46

lives and logistics should just work.

40:48

That was always the vision. So, quick

40:51

tour of the distribution center. Uh, you

40:53

know, Zipline builds uh designs,

40:57

manufactures and operates these vehicles

40:59

completely from scratch. This is one of

41:00

our flight operators launching a zip.

41:02

Accelerates from zero

41:05

to about 100 km an hour in a third of a

41:08

second. From the moment the vehicle

41:09

leaves the end of that launcher, it's

41:10

fully autonomous. It will fly out up to

41:13

100 miles to make a delivery to a

41:14

hospital and then fly all the way back.

41:16

Why do we have to have a launcher like

41:17

that? Because we don't have runways,

41:18

obviously, and the vehicle has no

41:20

landing gear. So, taking off is one

41:22

thing. Landing is even a little bit more

41:23

complicated. We were inspired by

41:25

aircraft carriers. This vehicle, as it's

41:27

flying back,

41:30

We're aiming for a 1 centimeter tail

41:32

hook on the back of that aircraft. This

41:34

really only possible with autonomy and

41:36

you know robotic solutions that can be

41:38

far far more precise in controlling

41:40

these kinds of vehicles than humans. The

41:42

system at this point can recover an

41:44

aircraft about every 60 seconds and we

41:46

operate about 20 distribution centers uh

41:48

across eight countries. So people always

41:51

think like oh uh you know drone delivery

41:54

it's not really real. So I thought it'd

41:55

be cool to actually just show you a time

41:57

lapse. This is one of our distribution

41:58

centers. You can see it's 1:00 a.m. The

42:00

system operates 24/7, 365. They never

42:03

take a day off. It's, you know, 3:00

42:05

a.m. here. You're seeing fulfillment

42:06

operations where we're packing and

42:07

loading packages, getting them packed

42:09

into vehicles. Here you can see the

42:10

launcher and the recovery system with

42:12

like sunrise just happening in the back

42:14

at 5 or 6 a.m. Um, this is a second

42:18

distribution center, another fulfillment

42:19

center. And so this is all basically

42:21

both fulfillment centers across the

42:23

country of Rwanda, which is the smallest

42:24

country we operate in today. But the

42:27

cool thing is you can see that at 8 a.m.

42:28

every single one of these little

42:29

triangles on the map, this is what we

42:31

call the sky map, is an autonomous

42:33

aircraft going out making a life-saving

42:34

delivery of blood, vaccines,

42:37

transfusions, infusions, cancer

42:38

products, almost the entire public

42:39

healthcare supply chain. And by 10:00

42:41

a.m., there are 50 autonomous aircraft

42:43

out making deliveries simultaneously to

42:46

all of the 500 hospitals and health

42:48

facilities that we serve in the country.

42:50

So, I actually used to show this uh

42:52

video to investors and we would get to

42:54

the end of the presentation and they

42:55

would say, "Oh, I think my favorite

42:57

slide was that simulation of what this

42:59

could look like one day." And I got so

43:01

pissed off because it's like it's not a

43:02

simulation that happened yesterday. So,

43:04

we put we put the CCTV on the right hand

43:06

side so you can actually see the teams

43:08

doing this work so people understand

43:09

this is this is not like far future.

43:11

This is happening day in and day out in

43:13

a way that is saving lives.

43:16

And you know on that point it's not just

43:18

about making logistics more efficient.

43:19

It turns out that if you can deploy AI

43:21

and robotics infrastructure for

43:23

healthcare you can save a lot of lives.

43:25

The system has been able to reduce

43:26

maternal mortality as measured by the

43:28

University of Pennsylvania by 51% across

43:31

the hospitals we serve.

43:38

Had had you told us when we were

43:40

starting the company that we were going

43:40

to reduce maternal mortality by 5%. We

43:43

would have said hell yes we have to do

43:45

this. The a new study came out uh a

43:47

couple months ago actually showing a 60%

43:50

reduction in under five childhood

43:52

mortality due to malnutrition. One of

43:53

the new products we've begun delivering

43:55

in the last few years. And when this was

43:57

studied uh uh by a major global health

44:00

institution for the cost effectiveness

44:02

of delivering vaccine, it was found to

44:04

be the most cost effective way of

44:05

delivering vaccines to zero do children

44:07

ever studied. So, it turns out that, you

44:09

know, yeah, it's exciting.

44:14

People think about robotics as being

44:16

expensive or fancy or maybe solving

44:18

problems for rich people. It's not just

44:19

that. We can solve some of the most

44:21

important problems that we face as a

44:23

world. We can um we can make this

44:25

technology work for um for everybody.

44:29

So, you know, stepping back, Zip Lines

44:31

now surpassed 115 million commercial

44:34

autonomous miles. We serve about 5,000

44:36

hospitals and health facilities

44:37

globally, over 1.6 million deliveries

44:39

like that one you saw in that video. Um,

44:41

and zero safety incidents, which is

44:43

important, not just saving lives, but

44:44

safe for the communities that it serves.

44:46

It's actually become the largest

44:47

commercial autonomous system on Earth of

44:49

any kind, ground or air, based on those

44:51

flight miles. So, I now thought it'd be

44:53

kind of cool to just show you a bit

44:55

about how this technology is evolving,

44:56

how what we what we started doing in

44:58

2016 is evolving and into the next

45:01

generation technology and launching in

45:03

the US.

45:06

[Music]

45:19

[Music]

45:21

We play this.

45:23

[Music]

45:59

Wow, that was so cool.

46:02

>> We love the fun.

46:05

[Music]

46:10

So if you're like okay that's cool but

46:13

when can I use it? Uh the news is ve the

46:15

good news is very soon. So just to give

46:17

you a sense it's you know as we started

46:19

doing this focusing on healthcare

46:20

focusing on operating outside the US a

46:22

lot of the biggest brands in the US

46:23

started to get pretty excited and saying

46:24

hey we want teleportation from our

46:27

hospitals or our primary care facilities

46:28

or our stores or our restaurants

46:30

directly to customer homes. And so, not

46:32

only did a lot of the biggest health

46:33

care systems in the US um sign up to

46:36

start using Zipline, but we've also seen

46:38

these additional major verticals in food

46:41

and retail. Um we've been scaling

46:42

incredibly fast with Walmart over the

46:44

last 6 to9 months. We just launched

46:46

Chipotle along with a lot of other

46:47

amazing food partners over the last

46:49

month. I'll show you a little bit more

46:50

about what that looks like. One of the

46:52

kind of amazing things, you know, over

46:54

the last 3 months, the service has been

46:55

growing about uh between 20 and 30%

46:58

week-over- week. So it's more than

46:59

doubling flight volume every month. This

47:02

is a little bit startling. Uh we only

47:04

launched Dallas, which is kind of the

47:05

major metro we're scaling in in the US

47:07

right now in April. And uh by July, so

47:10

ju just just to give a sense the

47:12

customer behavior that we're seeing.

47:14

Customers are ordering three to four

47:15

times per week from Zipline. The service

47:17

has a net promoter score of 94. And I

47:20

was talking to a grandma a couple weeks

47:22

ago. Uh she's 78 years old. She's

47:24

ordered from Zipline 350 times in the

47:26

last nine months. We were we were doing

47:27

a little customer research and she's

47:29

showing me on her phone, you know, like

47:31

clicking around ordering everything she

47:32

needs for the day. She's double click,

47:34

you know, Face ID, Apple Pay. She's

47:35

like, "It's on its way. It'll be here in

47:36

8 minutes. This woman's living in the

47:38

future." But by by July, we were

47:42

actually sufficiently nervous about uh

47:44

you know, about the capacity of the

47:46

system. We we ended up turning off all

47:47

the demand generation marketing um

47:49

because we were trying to slow down

47:50

growth. So, you can see the impact that

47:52

turning off our marketing had on the

47:54

growth of the system.

47:57

which is approximately zero. And we were

47:59

trying to figure out why that is. And

48:01

basically, it just turns out that having

48:02

a robot deliver whatever you need to

48:05

your home in less than 10 minutes is

48:07

really good content for Tik Tok.

48:10

Um, a lot of our different customers

48:11

have been making tons and tons of Tik

48:13

Toks of of of receiving these deliveries

48:15

and a you know, a lot of these videos

48:17

have gone viral like they they get seen

48:19

8 10 12 million times. We're delivering

48:21

to universities, to offices, to hotels,

48:24

to town homes, to apartment buildings.

48:26

So, every time one person is getting a

48:27

delivery, there are 10 other people who

48:28

are like, "What the hell is that? And

48:30

how do I get it?"

48:32

Even cooler than that, uh, you know, as

48:34

we're launching new sites in Dallas, you

48:36

know, the first site that we launched in

48:38

April, it took us about two and a half

48:40

months to get to 100 deliveries a day,

48:41

which was kind of like the the, you

48:43

know, uh, break even point for the site.

48:45

Uh, the site that we launched two weeks

48:47

ago hit 100 deliveries a day in 5 days.

48:50

So, we're seeing the sites themselves

48:52

ramp way, way faster. And a big part of

48:55

that is that it's getting simpler and

48:56

simpler for us to build this

48:57

infrastructure. So, just for you to kind

48:58

of get a sense for what the

48:59

infrastructure looks like, you know, we

49:01

integrate right into the side of

49:03

hospitals, primary care facilities,

49:05

stores, restaurants, you basically can

49:07

just think of it like a magical portal.

49:08

Zipline is just building a magical

49:09

portal in the wall. And now any

49:11

healthcare worker or Walmart employee or

49:12

Chipotle employee can just pass whatever

49:14

they want through this magical portal

49:16

and it's teleported directly to the home

49:18

that it needs to go to. Um, we do this

49:20

uh for a lot of different kinds of

49:22

buildings. We also have what we call

49:23

zipping points. You can see there on the

49:24

bottom right. Zipping points can be

49:26

installed in 1 hour. So, if you're a

49:27

business and you want to access a

49:28

zipline, we show up, boop, drop a

49:29

zipping point. And now that business is

49:31

enabled with zipline, it can deliver in

49:32

this way. Just to give you a quick sense

49:34

for what this infrastructure looks like,

49:35

you know, we're now building these

49:36

sites. We're launching about one a week.

49:38

Um, by Q1 of next year, we expect to

49:41

accelerate to about one a day. But this

49:43

infrastructure is relatively quick to

49:44

build um and enables up to 500

49:46

deliveries a day from a site like this.

49:50

quickly. You know, one of the one of the

49:51

cool things is that customers are all

49:53

just using the Zipline app to order

49:54

these things. And when they are ordering

49:56

for the first time, you type in your

49:57

address. We actually show you a

49:58

satellite image of your home and you

49:59

tell us exactly where you want us to

50:01

deliver. You can pick the dinner plate

50:03

level area, whether it's in your

50:04

backyard, side of your house, your

50:07

parking lot, apartment buildings. We can

50:08

even deliver onto roofs. You can scroll

50:10

and see all the different brands that

50:11

are available on the app. Order whatever

50:13

you want. Um, and the average time of

50:15

delivery right now is 18 minutes. A lot

50:17

of deliveries happen in under 10

50:19

minutes. In fact, you know, we just

50:20

launched Chipotle 2 weeks ago. The first

50:22

delivery happened in under 7 minutes

50:24

from like the customer ordering to it

50:26

being delivered to their house. So, I I

50:28

think it's going to redefine what is

50:30

what is possible in terms of instant

50:31

delivery in people's minds. And just to

50:34

hint at something cool that we can't

50:35

announce just yet,

50:41

it, you know, we'll be adding a lot of

50:43

people's favorite brands to the service

50:46

very soon over the coming weeks. And you

50:48

know, I joked before, just last thought,

50:49

I had joked before about like this sense

50:51

of like science fiction to entitlement

50:53

in about 7 days. We do enjoy that

50:55

science that period of sci-fi amazement.

50:58

And you know, just to, you know, the

51:00

similar version of like Jesus Christ

51:01

delivering blood from the sky. It's

51:02

pretty cute to see families and and and

51:04

kids actually, you know, kids are

51:06

telling their parents like what do they

51:08

want to do for the weekend? They want to

51:09

go and watch the zipline, you know, the

51:11

zipline aircraft. And so we we do take

51:13

these pictures just when we're at the

51:14

sites of people like hanging out on the

51:16

hoods of their cars. Uh or, you know, a

51:18

mom with her kids sitting in her lap or

51:20

the kids like looking through the you

51:22

know, the window of the car just

51:24

watching the system operate. And that

51:26

brings me to my last kind of provocative

51:28

point, which is that,

51:31

you know, our parents had this

51:33

incredibly inspiring mission, right? The

51:35

United States was in the this

51:37

geopolitical race to get to the moon,

51:40

the space race, and it united all the

51:42

best engineers. It inspired us. It made

51:44

us dream with optimism about what the

51:45

future could represent. And we did

51:47

something impossible. We put men on the

51:49

moon in 9 years. Obviously, the US is in

51:52

a similar technological race today. It's

51:54

a race for AI and robotics. But what

51:56

does winning that race for the US really

51:59

mean? So I want to leave you all with

52:01

just a slightly provocative answer to

52:03

that question. But first, who knows what

52:05

city this is? Shout it out if you know.

52:08

>> Yes. Okay, good. There are nerds in the

52:09

audience. This is Wakanda. So Wakanda is

52:12

a fictional radically advanced uh

52:17

African city hiding in plain sight from

52:19

one of my favorite movies, Black

52:20

Panther. And the provocative idea is

52:23

that we can go build this in the real

52:26

world. Like I think that winning the AI

52:28

and robotics race for America isn't just

52:30

us building like exquisite AI technology

52:33

to serve, you know, the richest people

52:34

on the coast of this country. It's about

52:37

extending the reach and influence of the

52:39

United States. It's using AI and

52:41

robotics infrastructure to lift the rest

52:44

of the world up with us. Like these

52:46

countries want to be leaprogging into

52:48

the future. They want access to the best

52:50

technology that America has to offer.

52:52

And if we go and extend, we want these

52:55

countries building on US AI and robotics

52:58

infrastructure, not that of our

53:00

geopolitical adversaries. And if we can

53:02

do that, we can make the world a safer

53:04

place, a wealthier place. We could

53:05

potentially eliminate maternal mortality

53:07

and childhood mortality in a lot of

53:09

these countries. And in doing so, we can

53:11

secure US technological and

53:13

manufacturing leadership for the decade

53:15

to come. So, thank you all.

53:22

[Music]

53:24

[Applause]

53:25

[Music]

53:29

So, we want to do a little bit of time

53:31

travel with you today. We want to go

53:33

back to your origin story and then we

53:35

want to play it out into the Wakanda

53:37

future that you're imagining.

53:38

>> Cool.

53:38

>> So, taking it back to where you began,

53:41

why start in Rwanda?

53:43

>> Yeah. You know, it's funny. Everybody

53:45

makes this assumption that like the most

53:47

advanced technology in the world is

53:48

going to start in the United States and

53:50

then trickle its way out maybe to you

53:52

know and it'll start in the rich cities

53:54

right and then maybe it'll trickle

53:55

trickle its way to rural areas in the US

53:57

and then after years it might trickle

53:58

its way out to like developing

53:59

countries. I think that paradigm is

54:01

largely wrong and it has a lot to do

54:03

with you know which countries at least

54:05

over the last decade it had a lot to do

54:07

with which countries are hungry and

54:08

entrepreneurial and willing to move

54:10

super fast to build new kinds of

54:12

regulatory paradigms. Um, and Rwanda is

54:16

this, you know, it's kind of like the

54:17

Singapore of Africa. It moves incredibly

54:19

fast. It's very entrepreneurial. It's

54:21

kind of a startup country. And it it was

54:23

perfect for us to work with them. Um,

54:26

they wanted to take this risk on us when

54:27

we were 20 people. We were totally naive

54:30

nerds who had no idea what we were

54:32

talking about. In fact, I remember this

54:33

conversation with the Minister of Health

54:35

in 2016 where I was saying, "Oh, you

54:37

know, we're going to use autonomous

54:38

aircraft to deliver all the different

54:40

medical products in your health system."

54:41

And she looked at me and was like,

54:42

"Keller, shut up. Just do blood." And

54:46

she explained to me, you know, that 50%

54:48

of blood transfusions are going to moms

54:49

with postpartum hemorrhaging. 30% are

54:51

going toward kids with severe anemia due

54:53

to malaria. And she was like, just show

54:55

us that you can do that. And so it's

54:56

interesting like that was the best

54:58

advice the company ever received. And um

55:01

you know, we've really just been kind of

55:02

like following their lead for the last

55:03

eight years as we've developed the

55:04

technology from there.

55:05

>> The reduction in maternal mortality when

55:07

you showed that stat, I got goosebumps.

55:09

It's just incredible. Yeah. And by the

55:12

way, you know, I think a lot of times

55:13

people in the US think like, oh, you

55:14

know, those poor Africans like, uh, it

55:17

gets unbelievable that they have those

55:18

kinds of, you know, healthcare problems.

55:19

We have this exact same problems in the

55:21

US. You know, people in the audience may

55:23

not know, but, um, the US has the

55:26

highest rate of maternal mortality of

55:27

any developed country. Um, and you know,

55:31

rates for African-American women are

55:32

three times that, you know, the average.

55:35

I mean, we have a lot of challenges with

55:37

rural rural healthcare in this country.

55:39

So I I think honestly um people probably

55:42

think that these countries are more

55:44

different than they are. Almost every

55:46

health system is dealing with the same

55:47

kinds of challenges.

55:48

>> So you come to the United States, you

55:51

launch it here. Tell me about the first

55:53

period of launching in the US.

55:55

>> Yeah, we um we originally launched kind

55:58

of the the first version of the

55:59

technology, the fixedwing technology

56:00

that you could see in 2020. Um honestly,

56:02

it's it's shocking. I mean, we were

56:04

delivering like birthday cakes and

56:06

rotisserie chickens via just those like

56:08

paper parachutes. It's pretty unfancy,

56:10

but customers loved it. Um, they and and

56:13

this is kind of we were rapidly

56:15

iterating um to build something that we

56:17

thought would be like the future version

56:19

of logistics, which is ultimately

56:20

platform 2. It's the video I showed

56:22

today. And we we only launched platform

56:24

2 on January 15th. And then we really

56:25

only started scaling it in April or May.

56:27

So, this is all happening in real time.

56:29

A lot of those videos we showed were

56:31

just from yesterday or the day before.

56:33

What has it felt like?

56:36

>> Um, you know, it's stressful. Hardware

56:38

is incredibly hard. Um, you know, we

56:41

have been scaling a hardware product

56:42

while like the tariff craziness has been

56:45

going on through, you know, March and

56:47

April and May. Um, you know, building a

56:50

global supply chain. I mean, you know,

56:51

Zipline just put into perspective like

56:53

we designed the flight computer, all of

56:56

the avionics on the aircraft. We design

56:59

the aircraft itself, all the mechanical

57:01

um components, the primary structure and

57:04

then from a software perspective, it's

57:07

flight control algorithms, multi vehicle

57:09

deconliction, communications

57:10

architecture. We design, we we build

57:12

unmanned traffic management system that

57:14

we provide to the regulators like the

57:15

FAA and then we also design that app

57:16

that you saw which is our customer

57:18

ordering platform. So um you know all of

57:21

that and then you also have to figure

57:22

out supply chain and maintenance and

57:24

manufacturing and operations logistics

57:26

like all of it has to work for the end

57:28

customer to just have this magical

57:30

experience of like teleportation and um

57:33

you know I yeah there's no part of it

57:36

that doesn't feel desperate and

57:37

stressful as you're kind of scaling a

57:39

system at that level of of exponential

57:41

growth as you're launching in the US. Do

57:44

you have a sense, Keller? Are you going

57:46

to beat the unit cost to deliver with

57:50

delivery drivers today? And by how much?

57:53

Can you give us a sense on if I want

57:55

Chipotle, why would I go to the Zipline

57:58

ordering system or use Chipotle's app

58:00

and have Zipline kind of fulfill for me?

58:02

What's the cost difference going to be

58:04

percentage-wise, do you think, over

58:05

traditional food delivery?

58:07

>> Yeah. So I mean interestingly people may

58:09

not realize you know instant delivery

58:11

has grown incredibly fast like

58:13

especially through co but even before

58:15

there are now 5 12 billion instant

58:17

deliveries being done every year just in

58:19

the US and that's not like Amazon or UPS

58:21

that's just the instant deliveries and

58:23

we're using a 4,000 lb gas combustion

58:26

vehicle driven by a human to deliver

58:28

something to your home that weighs on

58:30

average 4 to 5 lb. So, you know, if

58:33

aliens were to land on the planet and

58:34

look at the way we're solving that

58:35

problem, they would conclude there's no

58:37

intelligent life on Earth. Like, this is

58:38

a bizarre solution. Um, I think, you

58:41

know, the reality is we have this new

58:43

demand and and the demand is vast.

58:47

People want things delivered quickly and

58:48

they want like to have more time with

58:50

their family rather than spending time

58:52

in traffic or like in a store. Um, but

58:55

we're using technology that's 100 years

58:57

old to solve that problem. So, I think

58:58

all you have to realize is that instead

59:01

of using a 4,000lb gas combustion

59:03

vehicle driven by a human, you should

59:05

use a 50 lb vehicle that is autonomous

59:08

and electric.

59:10

And that's kind of just reasoning from

59:12

like physics first principles. Like you

59:13

don't have to be, you know, a genius. As

59:15

soon as you've realized that, I think

59:16

you know something really fundamental

59:17

about the future that few people

59:18

actually understand. And so we think

59:20

it's it's very inevitable that um that

59:24

and by the way that if you were to just

59:26

extend the customer ordering behavior

59:29

that we see with um with our customers

59:31

today there would be 50 billion instant

59:34

deliveries happening in the US. Wow.

59:36

>> So this is kind of a

59:37

>> based on the order idea. Yeah. Basically

59:39

if you make the deliveries less

59:41

expensive 10 times as fast and just a

59:42

way better experience order a lot more.

59:45

Not that surprising. So, I think the the

59:47

reality is actually, you know, these

59:49

kinds of systems will yes, definitely be

59:52

less expensive than using a 4,000lb gas

59:54

combustion vehicle. Um, but I think more

59:56

importantly, the reason customers are

59:58

using them so much is it's just a way

60:00

better experience when you can have

60:01

something delivered in 7 minutes or 8

60:03

minutes or 12 minutes. Um,

60:05

>> does it need to be much cheaper?

60:07

>> Um, I think it will be naturally, but I

60:09

don't believe it needs to be. I mean,

60:10

it's the reason that like Whimo right

60:11

now is more expensive and people prefer

60:13

Whimo to to

60:14

>> What's the weight limit and then how

60:16

much of the market does that address?

60:17

>> Yeah. I mean, right now we the the

60:20

system is designed to deliver up to 8 lb

60:22

and 8 lb gets you like 95% of all

60:24

packages delivered by Amazon. I think

60:26

it's like 95% of food delivery orders.

60:28

So, suffice it to say, you're not going

60:30

to deliver flat screen TVs in this way

60:32

anytime soon, but the vast majority of

60:34

stuff actually fits and can be delivered

60:36

like this. So while this is all

60:38

happening, while zipline is exploding, I

60:40

think many Americans came to believe

60:42

that the the era of drone delivery had

60:44

somehow passed, that this wasn't a near

60:46

future that they were going to

60:47

experience. Why do you think that

60:49

misconception happened? And what should

60:52

all of the people in this audience go

60:53

out and say to the people who might ask

60:55

them what they've seen here?

60:56

>> Yeah. Well, it definitely didn't help

60:58

that the CEO of one of the largest

60:59

companies in the in the world went on 60

61:01

Minutes in 2013 and promised everybody

61:04

drone delivery in the next like, you

61:06

know, one or two years, right? Maybe

61:08

some of you guys saw that interview.

61:09

>> Who was it?

61:10

>> I don't even know what that interview

61:11

was.

61:11

>> Jeff from Amazon. Yeah. He was like

61:13

2013. He's like, "Oh, well, you know,

61:15

we'll be doing

61:17

Yeah. So, he I mean, they promised, you

61:18

know, they announced Amazon Prime and

61:20

they said by 2015, you know, it'll be

61:21

serving, you know, everybody in the US."

61:23

And um I think that that you know people

61:26

probably believed it right like and and

61:28

then I think people were really

61:29

disappointed when it didn't happen and

61:32

maybe you know similar trend that you

61:33

see hap happened with autonomous

61:35

vehicles you know autonomous cars which

61:37

is that like 2015 so many companies were

61:39

raising you know billions of dollars and

61:41

it was like right around the corner and

61:42

people could see it working for the

61:44

first time. But obviously it's a whole

61:46

decade later today that we actually now

61:48

see Whimo and robo taxi scaling

61:49

commercially. The reality is with these

61:51

kinds of technologies, I think you

61:52

always have like the bubble and and the

61:54

max hype and then you have the trough of

61:56

disillusionment and then you have the 8

61:58

to n years of the actual hard work of

62:00

making the technology work. And you

62:02

know, Zipline um launched in 2016. We've

62:05

spent 10 years driving the economics

62:07

down, driving the reliability up. You

62:09

you kind of saw that statistic of 115

62:11

million miles with zero safety

62:13

incidents. Um that's hard. It requires

62:16

time to get manufacturing technology uh

62:19

operations, maintenance right in a way

62:21

to achieve that. And um you know, but

62:23

the but the the good news is that uh I

62:26

think with with both autonomous cars and

62:28

with this technology, we're now you

62:30

know, we've now done the 10 years of

62:32

hard work and we now see it scaling in a

62:33

way that like just fundamentally

62:35

changing the way people live their

62:36

lives. I mean, when you when I talk to

62:37

that grandma or you like you talk to a

62:39

mom who's using Zipline every single

62:40

day, it's like they're getting hours

62:42

back a week to spend with their family

62:44

or their loved ones so they don't have

62:45

to spend stressing out about trying to

62:47

like get kids buckled into a car and

62:49

like drive to a car or and obviously

62:51

that's like, you know, that's that's the

62:53

retail use cases, let alone the

62:55

life-saving implications this has for

62:56

healthcare logistics.

62:58

>> What are the competitive barriers?

63:00

Google's had, I think, in X a drone

63:02

delivery. I don't know what the status

63:04

is. Amazon obviously has invested by the

63:06

way I thought it was like either Elon or

63:08

someone from Google or Jeff. Um and then

63:11

uh there have been a mtoan I think out

63:13

of China famously shown videos of

63:16

delivering food to the Great Wall with a

63:19

drone. How much advantage is Zipline

63:23

versus others and how quickly can they

63:25

catch up? Like help us understand how

63:26

hard the tech is? What did you have to

63:27

engineer to get the unit costs

63:30

advantages that you're having today and

63:31

how persistent will that be? I mean, you

63:35

know, I I think there are a lot of

63:37

people out there, you know, we saw over

63:39

the last 10 years so many companies or

63:41

teams, they would like buy a quadcopter

63:43

off the shelf and duct tape a Snickers

63:44

bar to the bottom of it and then

63:45

manually fly it a mile and they get

63:47

like, you know, Techrunch to write an

63:48

article about it and be like, "It's a

63:49

Kittyhawk moment. Drone delivery is

63:51

here." Um, and you know, we've seen that

63:53

like 50 times at this point. I think

63:55

people have kind of know that it's not

63:56

real. Um the you know the the trick is

63:59

designing a system that can operate 24/7

64:02

365 in a way that people can depend on

64:04

with their lives that works in all

64:06

weather that can be reliable and safe

64:08

and they can achieve hundreds of

64:09

millions or you know billions of

64:10

autonomous miles. um that's hard to do.

64:13

That takes time. And um you know, I

64:16

mean, Zipline uh has now spent a decade

64:19

scaling these systems. And and I think

64:22

the realization is there's no like

64:23

off-the-shelf hardware you can buy for

64:25

this because there's you can you can

64:27

look at like these cheap plastic

64:29

quadcopters that DJI makes refer to

64:31

China or you can look at like Predator

64:33

drones, but something in the middle

64:34

which is more automotive grade,

64:36

something that can do, for example, a

64:37

million miles just a single aircraft. um

64:41

that's hard and it kind of has to be

64:42

built from scratch. So we honestly don't

64:45

worry that I mean our competition is

64:47

motorcycles and cars. Like if we are

64:49

better than motorcycles and cars, I mean

64:51

I'm very confident someone is going to

64:53

build a multiundred billion dollar

64:54

company in automated logistics over the

64:56

next 5 to 10 years. Like it's so obvious

64:59

that this needs to exist. The demand is

65:01

like unbelievably vast. It's going to be

65:03

one of the biggest markets on earth. And

65:05

uh you know I think a lot of people are

65:06

excited about a lot of different kinds

65:07

of robotics but this is the area of

65:09

robotics that in my opinion is going to

65:10

scale the fastest and is like most ready

65:12

for prime time. You

65:13

>> want to talk about Wakanda?

65:14

>> I do. So just to jump ahead. Yeah.

65:16

>> If we were interviewing you here in 10

65:19

years you're back. What do you hope

65:21

you're saying about the impact of drone

65:23

delivery both on the golden billion but

65:26

also for everybody else? And to your

65:28

point earlier the relationship between

65:30

those two things and those two groups

65:32

might be closer than we think.

65:33

>> Yeah. the the thing that always really

65:35

inspired us, you know, you talk about

65:36

logistics. I mean, logistics is boring,

65:38

right? Like I mean, who wants to work in

65:40

logistics? It's incredibly boring. You

65:42

just do the same thing day after day,

65:43

just like doing the same deliveries. But

65:45

that's also what makes it great for

65:46

robotics and automation. And I think the

65:48

thing, the key thing to realize is the

65:50

golden billion that Cleo is talking

65:51

about, right? The richest billion people

65:53

on Earth. Like the go my assumption is

65:56

we're all in the golden billion. Like

65:58

our access to logistics is really good.

66:01

There are 7 billion people on earth who

66:03

are not in the golden billion whose

66:05

access either sucks or is non-existent.

66:08

And as a result of that, five and a half

66:09

million kids lose their lives every year

66:11

due to lack of access to basic medical

66:13

products. This is not like oh we have we

66:14

need some advanced therapy to it's like

66:16

no no we couldn't get them the basic

66:18

almost free drug that they needed to

66:20

save their life. You know we making

66:22

excuses for decades about why we can't

66:26

solve these problems. And so I think

66:28

like logistics is boring, but it's kind

66:31

of only boring when it's like working

66:32

well for you. And I think that, you

66:35

know, the the the thing that gets me so

66:37

excited about why does AI and robotics

66:39

matter? Why should we be applying it to

66:41

this industry? It's not just like make

66:42

people's lives better, give them new

66:44

kinds of economic opportunity, save them

66:46

time, you know, let them spend more time

66:48

with their kids. It's also because like

66:50

reducing the cost of logistics,

66:52

automating it, expanding it, um

66:54

improving the performance of these kinds

66:56

of systems is going to extend access to

66:58

logistics to 7 billion people on Earth

67:00

who don't have it today. And that is

67:01

going to save lives, increase economic

67:03

opportunity. I think it's going to make

67:04

the world a more stable place. And and

67:06

and so that's that's really our vision.

67:08

It's like um it's time to stop making

67:10

excuses. We should eliminate these

67:12

problems. And the thing that gets me

67:14

excited about, you know, you I mean I

67:15

know we're both kind of like solar punk

67:17

techno optimists, right? Um like that's

67:20

the future that I want to build that I

67:22

want to tell my kids about. And um you

67:24

know, if we can play a small part of it,

67:26

that would be a good life.

67:28

>> That's the future I think we all want to

67:29

be part of.

67:30

>> Amazing. Guys, please join me in

67:33

thanking Keller and Cleo. Did you guys

67:37

love Science Corner?

67:41

[Music]

67:43

[Applause]

Interactive Summary

The video features three engaging discussions: Cleo Abram, founder of "Huge if True," discusses her journey from traditional media to independent YouTube content, emphasizing an optimistic view on science and technology and YouTube's role in reaching global audiences. Next, astrophysicist Alex Filipenko presents the capabilities and early discoveries of the James Webb Space Telescope, explaining its contributions to understanding cosmic origins and defending the value of pure research, despite current funding challenges. Finally, Keller Rinaudo Clifton, CEO of Zipline, details how his autonomous drone delivery system, initially launched in Rwanda to dramatically reduce maternal and childhood mortality, is now rapidly expanding in the US for general retail and healthcare, envisioning a future where advanced robotics extends crucial logistics to billions globally.

Suggested questions

16 ready-made prompts