WEBVTT FILE

1
00:00:00.000 --> 00:00:04.471
We are
now in a new era of computing technology.

2
00:00:04.471 --> 00:00:09.142
We see artificial intelligence
in nearly all aspects of our lives,

3
00:00:09.142 --> 00:00:11.911
from helping doctors
and diagnosing diseases,

4
00:00:11.911 --> 00:00:15.348
to creating recipes
based on what's in your pantry.

5
00:00:15.348 --> 00:00:18.752
AI is quickly changing the way we live.

6
00:00:18.752 --> 00:00:23.723
Artificial intelligence is also changing
the way astronomers analyze data.

7
00:00:23.723 --> 00:00:27.961
Such advances have been used to increase
the discoveries made by NASA's

8
00:00:27.961 --> 00:00:31.297
Hubble Space Telescope
and in turn, Hubble's

9
00:00:31.297 --> 00:00:36.002
data has been used to advance
and test artificial intelligence systems.

10
00:00:36.002 --> 00:00:40.240
Such systems were critical
in discovering asteroids in Hubble data.

11
00:00:40.240 --> 00:00:44.377
To date, astronomers have found over
a million asteroids in the main

12
00:00:44.377 --> 00:00:48.815
asteroid belt, an area
between the orbits of Mars and Jupiter.

13
00:00:48.815 --> 00:00:54.087
But many smaller asteroids may not have
been discovered because they are so faint.

14
00:00:54.087 --> 00:00:57.757
They are about 1/40,000,000
the brightness of the faintest

15
00:00:57.757 --> 00:01:00.560
star a human eye can see.

16
00:01:00.560 --> 00:01:03.563
This is where Hubble and AI come in.

17
00:01:03.563 --> 00:01:07.634
Hubble's archive contains over 1 million
observations.

18
00:01:07.634 --> 00:01:11.471
Many of these smaller asteroids
may be found in the images

19
00:01:11.471 --> 00:01:13.573
because they are moving across the skies

20
00:01:13.573 --> 00:01:16.776
as Hubble's view
holds steady on an astronomical object.

21
00:01:16.776 --> 00:01:20.480
They appear as curved streaks of light
in Hubble's cameras,

22
00:01:20.480 --> 00:01:23.383
essentially photobombing the image.

23
00:01:23.383 --> 00:01:26.619
Astronomers applied machine
learning algorithms,

24
00:01:26.619 --> 00:01:32.792
a form of artificial intelligence, to hunt
for these trails in over 37,000 images.

25
00:01:32.792 --> 00:01:36.062
That exercise was conducted
with the help of 11,000

26
00:01:36.062 --> 00:01:41.101
citizen scientists,
who discovered 1701 asteroids,

27
00:01:41.101 --> 00:01:46.573
1031 of these were small bodied asteroids
not formerly known to exist.

28
00:01:46.573 --> 00:01:48.475
The results help provide insight

29
00:01:48.475 --> 00:01:52.479
into both the origin
and evolution of the asteroid belt.

30
00:01:52.479 --> 00:01:57.517
AI can also revolutionize the way
astronomers classify galaxies.

31
00:01:57.517 --> 00:02:01.254
Traditionally, astronomers
would classify them by hand

32
00:02:01.254 --> 00:02:03.790
spirals, ellipticals, irregulars,

33
00:02:03.790 --> 00:02:07.460
and so on, a time consuming process.

34
00:02:07.460 --> 00:02:11.331
To test AI concepts, Hubble
data has been used in studies

35
00:02:11.331 --> 00:02:15.168
on deep learning techniques,
which use artificial neural network

36
00:02:15.168 --> 00:02:21.407
technologies to learn complex patterns
and features from large data sets.

37
00:02:21.407 --> 00:02:26.012
In this case, the Hubble Candels data
set that contains over 10,000

38
00:02:26.012 --> 00:02:30.950
classified galaxies and required
dozens of astronomers time to classify,

39
00:02:30.950 --> 00:02:36.422
was used to teach a deep learning system
about galaxy structure and forms.

40
00:02:36.422 --> 00:02:39.125
They then applied it to the Hubble Legacy
field,

41
00:02:39.125 --> 00:02:43.596
a combination of nearly 7500 separate
Hubble exposures,

42
00:02:43.863 --> 00:02:46.733
representing 16 years of observations

43
00:02:46.733 --> 00:02:51.171
that contained over 265,000 galaxies.

44
00:02:51.171 --> 00:02:56.209
With deep learning, AI can sort
such a field at an incredible speed.

45
00:02:56.209 --> 00:02:59.179
This ability becomes even more important
when NASA's

46
00:02:59.179 --> 00:03:03.049
Nancy Grace Roman Space
Telescope images become available.

47
00:03:03.049 --> 00:03:07.987
Each of those images has over 100 times
the field of view as Hubble.

48
00:03:07.987 --> 00:03:11.191
Similarly,
Hubble data has been used to help test

49
00:03:11.191 --> 00:03:14.460
machine learning concepts to accommodate
noisy data.

50
00:03:15.528 --> 00:03:17.530
Telescope imperfections or dust

51
00:03:17.530 --> 00:03:22.168
clouds can create flaws in images
from even the best observatories.

52
00:03:22.168 --> 00:03:23.603
The machine learning systems

53
00:03:23.603 --> 00:03:27.774
can identify the noise
and reconstruct the image accordingly.

54
00:03:27.774 --> 00:03:32.545
Noisy Hubble Galaxy
images were used to test these concepts.

55
00:03:32.545 --> 00:03:35.548
Future telescopes
like the Roman Space Telescope,

56
00:03:35.548 --> 00:03:38.251
will collect more data than ever before.

57
00:03:38.251 --> 00:03:44.357
Roman itself will likely amass 20,000TB
of data over its five year mission.

58
00:03:44.357 --> 00:03:49.262
AI will be critical in processing
such vast streams of information.

59
00:03:49.262 --> 00:03:54.734
From finding exoplanets to uncovering new
clues about dark matter and dark energy.

60
00:03:54.734 --> 00:03:57.203
The next frontier of space exploration

61
00:03:57.203 --> 00:04:01.140
will not only depend on our instruments,
but also on powerful software.

62
00:04:01.140 --> 00:04:02.609
Here on Earth.

63
00:04:02.609 --> 00:04:06.913
And Hubble
data is helping with this new revolution.

64
00:04:06.913 --> 00:04:09.649
The fusion
of Hubble's vast archive of data

65
00:04:09.649 --> 00:04:14.254
with cutting edge
AI marks a new era in space exploration.

66
00:04:14.254 --> 00:04:19.158
The vast potential of machine learning
can process unimaginable amounts of data,

67
00:04:19.158 --> 00:04:21.794
unlocking discoveries faster than before

68
00:04:21.794 --> 00:04:25.164
and recovering details
we would otherwise have missed.

69
00:04:25.164 --> 00:04:29.569
The future of astronomy isn't just up in
the stars, it's in the code.

70
00:04:29.569 --> 00:04:47.253
Follow Hubble on social media @NASAHubble

71
00:04:47.253 --> 00:04:54.160
NASA Meatball