< Return to Video

Art in the age of machine intelligence

  • 0:01 - 0:04
    Hi. I'm Refik. I'm a media artist.
  • 0:04 - 0:06
    I use data as a pigment
  • 0:06 - 0:08
    and paint with a thinking brush
  • 0:08 - 0:11
    that is assisted
    by artificial intelligence.
  • 0:11 - 0:14
    Using architectural spaces as canvases,
  • 0:14 - 0:16
    I collaborate with machines
  • 0:16 - 0:19
    to make buildings dream and hallucinate.
  • 0:19 - 0:22
    You may be wondering,
    what does all this mean?
  • 0:22 - 0:25
    So let me please take you
    into my work and my world.
  • 0:25 - 0:28
    I witnessed the power of imagination
  • 0:28 - 0:30
    when I was eight years old
  • 0:30 - 0:32
    as a child growing up in Istanbul.
  • 0:32 - 0:36
    One day, my mom brought home
    a videocassette
  • 0:36 - 0:39
    of the science fiction movie
    "Blade Runner."
  • 0:39 - 0:41
    I clearly remember being mesmerized
  • 0:41 - 0:46
    by the stunning architectural vision
    of the future of Los Angeles,
  • 0:46 - 0:49
    a place that I had never seen before.
  • 0:49 - 0:52
    That vision became a kind of a staple
  • 0:52 - 0:54
    of my daydreams.
  • 0:54 - 0:57
    When I arrived in LA in 2012
  • 0:57 - 1:00
    for a graduate program
    in design media arts,
  • 1:00 - 1:02
    I rented a car and drove downtown
  • 1:02 - 1:05
    to see that wonderful world
    of the near future.
  • 1:05 - 1:08
    I remember a specific line
    that kept playing
  • 1:08 - 1:11
    over and over in my head:
  • 1:11 - 1:14
    the scene where the android Rachael
  • 1:14 - 1:17
    realizes that her memories
    are actually not hers,
  • 1:17 - 1:21
    and when Deckard tells her
    they are someone else's memories.
  • 1:21 - 1:23
    Since that moment,
  • 1:23 - 1:24
    one of my inspirations
  • 1:24 - 1:26
    has been this question.
  • 1:26 - 1:30
    What can a mission do
    with someone else's memories?
  • 1:30 - 1:33
    Or, to say that in another way,
  • 1:33 - 1:37
    what does it mean to be an AI
    in the 21st century?
  • 1:38 - 1:41
    Any android or AI mission
    is only intelligent
  • 1:41 - 1:44
    as long as we collaborate with it.
  • 1:44 - 1:46
    It can construct things
    that human intelligence
  • 1:46 - 1:48
    intends to produce,
  • 1:48 - 1:51
    but does not have the capacity to do so.
  • 1:51 - 1:54
    Think about your activities
    and social networks.
  • 1:54 - 1:59
    For example, they get smarter
    the more you interact with them.
  • 1:59 - 2:04
    If machines can learn or process memories,
  • 2:04 - 2:05
    can they also dream?
  • 2:05 - 2:07
    Hallucinate?
  • 2:07 - 2:09
    Involuntarily remember,
  • 2:09 - 2:11
    or make connections
  • 2:11 - 2:14
    between multiple people streams?
  • 2:14 - 2:17
    Does being an AI in the 21st century
  • 2:17 - 2:21
    simply mean not forgetting anything?
  • 2:21 - 2:24
    And, if so,
  • 2:24 - 2:25
    isn't it the most revolutionary thing
  • 2:25 - 2:28
    that we have experienced
  • 2:28 - 2:32
    in our centuries-long effort
    to capture history across media?
  • 2:32 - 2:34
    In other words,
  • 2:34 - 2:37
    how far have we come
    since we discussed "Blade Runner"?
  • 2:37 - 2:40
    So I established my studio in 2014,
  • 2:40 - 2:43
    and invited architects,
  • 2:43 - 2:46
    computer and data scientists,
    neuroscientists, musicians
  • 2:46 - 2:48
    and even storytellers to join me
    in realizing my dreams.
  • 2:48 - 2:54
    Can data become a pigment?
  • 2:54 - 2:58
    This was the very first question we asked
  • 2:58 - 2:59
    when starting our journey
  • 2:59 - 3:02
    to embed media arts into architecture,
  • 3:02 - 3:05
    to collide virtual and physical worlds.
  • 3:05 - 3:07
    So we began to imagine
  • 3:07 - 3:08
    what I would call
  • 3:08 - 3:10
    the politics of data.
  • 3:10 - 3:13
    One of our first projects,
    Virtual Depictions,
  • 3:13 - 3:15
    was a public data sculpture piece
  • 3:15 - 3:18
    commissioned by the city of San Francisco.
  • 3:18 - 3:20
    The work invites the audience
  • 3:20 - 3:23
    to be part of a spectacular
    aesthetic experience
  • 3:23 - 3:25
    in a living urban space
  • 3:25 - 3:31
    by depicting a ?? network
    of connections of the city itself.
  • 3:31 - 3:35
    It also stands as a reminder
    of how invisible data
  • 3:35 - 3:37
    from our everyday lives,
  • 3:37 - 3:40
    like the ?? feeds
    that are represented here,
  • 3:40 - 3:42
    can be made visible
  • 3:42 - 3:45
    and transformed into sensory knowledge
  • 3:45 - 3:48
    that can be experienced collectively.
  • 3:49 - 3:53
    In fact, data can only become knowledge
  • 3:53 - 3:54
    when it's experienced,
  • 3:54 - 3:56
    and what is knowledge and experience
  • 3:56 - 3:58
    can take many forms.
  • 3:58 - 4:00
    When exploring such connections
  • 4:00 - 4:03
    through the vast potential
    of machine intelligence,
  • 4:03 - 4:06
    we also pondered
  • 4:06 - 4:10
    the connection between human senses
  • 4:10 - 4:13
    and the machines' capacity
    for simulating nature.
  • 4:13 - 4:18
    These inquiries began while working
    on wind data paintings.
  • 4:18 - 4:20
    They took the shape of visualized plans
  • 4:20 - 4:23
    based on hidden data sets
  • 4:23 - 4:26
    that we collected from wind sensors.
  • 4:26 - 4:29
    We then used generative algorithms
  • 4:29 - 4:33
    to transform wind speed,
    gust and direction
  • 4:33 - 4:36
    into an ethereal data pigment.
  • 4:37 - 4:39
    The result was a meditative
  • 4:39 - 4:41
    yet speculative experience.
  • 4:42 - 4:44
    This kinetic data sculpture,
    titled, "Bosphorus,"
  • 4:44 - 4:48
    was a similar attempt to question
    our capacity to reimagine
  • 4:48 - 4:50
    natural occurrences.
  • 4:50 - 4:56
    Using high-frequency radar collections
    of the Marmara Sea,
  • 4:56 - 4:59
    we collected sea surface data
  • 4:59 - 5:02
    and projected its dynamic movement
    with machine intelligence.
  • 5:02 - 5:04
    We create the sense of immersion
  • 5:04 - 5:07
    in a calm yet constantly changing
  • 5:07 - 5:09
    synthetic serial.
  • 5:09 - 5:12
    Seeing with the brain
  • 5:12 - 5:14
    is often called imagination,
  • 5:14 - 5:16
    and, for me, imagining architecture
  • 5:16 - 5:18
    goes beyond just glass,
  • 5:18 - 5:20
    metal or concrete,
  • 5:20 - 5:24
    instead experimenting with
    the furthermost possibilities of immersion
  • 5:24 - 5:28
    and ways of augmenting
    our perception in built environments.
  • 5:29 - 5:32
    Research in artificial intelligence
    is growing every day,
  • 5:32 - 5:36
    leaving us with the feeling
    of being plugged into a system
  • 5:36 - 5:39
    that is bigger and more knowledgeable
  • 5:39 - 5:40
    than ourselves.
  • 5:40 - 5:44
    In 2017, we discovered
    an open source library
  • 5:44 - 5:46
    of cultural documents in Istanbul
  • 5:46 - 5:50
    and began working on "Archive Dreaming,"
  • 5:50 - 5:54
    one of the first AI-driven
    public installations in the world,
  • 5:55 - 6:01
    an AI exploring approximately
    1.7 million documents that span 270 years.
  • 6:02 - 6:05
    One of our inspirations
    during this process
  • 6:05 - 6:08
    was a short story
    called "The Library of Babel"
  • 6:08 - 6:12
    by the Argentine writer Jorge Luis Borges.
  • 6:12 - 6:17
    In the story, the author conceives
    a universe in the form of a vast library
  • 6:17 - 6:20
    containing all possible 410-page books
  • 6:20 - 6:23
    of a certain format and character set.
  • 6:23 - 6:25
    Through this inspiring image,
  • 6:25 - 6:27
    we imagine a way to physically explore
  • 6:27 - 6:30
    the vast archives of knowledge
  • 6:30 - 6:32
    in the age of machine intelligence.
  • 6:32 - 6:34
    The resulting work, as you can see,
  • 6:34 - 6:37
    was a user-driven immersive space.
  • 6:37 - 6:42
    "Archive Dreaming" profoundly transformed
    the experience of a library
  • 6:42 - 6:44
    in the age of machine intelligence.
  • 6:45 - 6:48
    "Machine Hallucination"
    is an exploration of time and space
  • 6:48 - 6:51
    experienced through New York City's
  • 6:51 - 6:53
    public photographic archives.
  • 6:53 - 6:55
    For this one-of-a-kind immersive project,
  • 6:55 - 6:58
    we deployed machine-learning algorithms
  • 6:58 - 7:02
    to find and process over
    100 million photographs of the city.
  • 7:03 - 7:06
    We designed an innovative narrative system
  • 7:06 - 7:13
    to use artificial intelligence
    to predict or to hallucinate new images,
  • 7:13 - 7:16
    allowing the viewer to step
    into a dreamlike fusion
  • 7:16 - 7:19
    of past and future New York.
  • 7:20 - 7:26
    As our projects delve deeper into
    remembering and transmitting knowledge,
  • 7:26 - 7:29
    we thought more about how memories
  • 7:29 - 7:31
    were not static recollections
  • 7:31 - 7:34
    but ever-changing
    interpretations of past events.
  • 7:34 - 7:37
    We pondered how machines
  • 7:37 - 7:40
    could simulate unconscious
    and subconscious events
  • 7:40 - 7:42
    such as dreaming,
  • 7:42 - 7:43
    remembering
  • 7:43 - 7:46
    and hallucinating.
  • 7:46 - 7:48
    Thus we created "Melting Memories"
  • 7:48 - 7:51
    to visualize the moment of remembering.
  • 7:51 - 7:55
    The inspiration came from a tragic event
  • 7:55 - 7:59
    when I found out that my uncle
    was diagnosed with Alzheimer's.
  • 7:59 - 8:02
    At that time, all I could think about
  • 8:02 - 8:05
    was to find a way to celebrate
  • 8:05 - 8:07
    how and what he remembered
  • 8:07 - 8:09
    when we are still able to do so.
  • 8:09 - 8:12
    I began to think of memories
  • 8:12 - 8:14
    not as disappearing
  • 8:14 - 8:15
    but as melting
  • 8:15 - 8:17
    or changing shape.
  • 8:17 - 8:18
    With the help of machine intelligence,
  • 8:18 - 8:22
    we worked with the scientists
    at the Neuroscape Laboratory
  • 8:22 - 8:24
    at the University of California,
  • 8:24 - 8:29
    who showed us how to understand
    brain signals as memories are made.
  • 8:29 - 8:34
    Although my own uncle was losing
    the ability to process memories,
  • 8:34 - 8:37
    the artwork generated by the EEG data
  • 8:37 - 8:41
    explored the materiality of remembering
  • 8:41 - 8:44
    and stood as a tribute
  • 8:44 - 8:47
    to what my uncle had lost.
  • 8:47 - 8:52
    Almost nothing about contemporary LA
  • 8:52 - 8:54
    matched my childhood expectation
  • 8:54 - 8:56
    of the city,
  • 8:56 - 8:59
    with the exception
    of one amazing building:
  • 8:59 - 9:02
    the Walt Disney Concert Hall,
    designed by Frank Gehry,
  • 9:02 - 9:04
    one of my all-time heroes.
  • 9:04 - 9:08
    In 2018, I had a call
    from the LA Philharmonic
  • 9:08 - 9:10
    who was looking for an installation
  • 9:10 - 9:14
    to help mark the celebrated symphony's
    hundredth year anniversary.
  • 9:14 - 9:17
    For this, we decided to ask the question,
  • 9:17 - 9:20
    can a build learn? Can it dream?
  • 9:21 - 9:22
    To answer this question,
  • 9:22 - 9:25
    we decided to collect everything recorded
  • 9:25 - 9:28
    in the archives of the LA field and WHC,
  • 9:28 - 9:33
    to be precise, 77 terabytes
    of digitally archived memories.
  • 9:33 - 9:35
    By using machine intelligence,
  • 9:35 - 9:38
    the entire archive going back 100 years
  • 9:38 - 9:41
    became projections on the building's skin,
  • 9:41 - 9:45
    42 projectors to achieve
    this futuristic public experience
  • 9:45 - 9:48
    in the heart of Los Angeles,
  • 9:48 - 9:52
    getting one step closer
    to the LA of "Blade Runner."
  • 9:52 - 9:55
    If ever a building could dream,
  • 9:55 - 9:57
    it was in this moment.
  • 10:00 - 10:03
    Now, I am inviting you to one last journey
  • 10:03 - 10:06
    into the mind of a machine.
  • 10:06 - 10:09
    Right now, we are fully immersed
    in the data universe
  • 10:09 - 10:12
    of every single created TED Talk
  • 10:12 - 10:14
    from the past 30 years.
  • 10:14 - 10:21
    That means, this data set includes
    7,705 talks from the TED stage.
  • 10:21 - 10:24
    Those talks have been translated
  • 10:24 - 10:26
    into 7.4 million seconds,
  • 10:26 - 10:30
    and each second is represented
    here in this data universe.
  • 10:30 - 10:32
    Every image that you are seeing in here
  • 10:32 - 10:35
    represents unique moments
    from those talks.
  • 10:35 - 10:37
    By using machine intelligence,
  • 10:37 - 10:41
    we processed a total of 487,000 sentences
  • 10:41 - 10:46
    into 330 unique clusters of topics
    like nature, global emissions,
  • 10:46 - 10:48
    extinction, race issues,
  • 10:48 - 10:49
    computation,
  • 10:49 - 10:53
    trust, emotions, water and refugees.
  • 10:53 - 10:56
    These clusters are then
    connected to each other
  • 10:56 - 10:57
    by an algorithm,
  • 10:57 - 11:01
    and generated 113 million line segments,
  • 11:01 - 11:04
    which revealed new
    conceptual relationships.
  • 11:04 - 11:06
    Wouldn't it be amazing
  • 11:06 - 11:07
    to be able to remember
  • 11:07 - 11:10
    all the questions that have ever
    been asked on the stage?
  • 11:12 - 11:13
    Here I am,
  • 11:13 - 11:16
    inside the mind
    of countless great thinkers,
  • 11:16 - 11:18
    as well as a machine
  • 11:18 - 11:20
    interacting with various feelings
  • 11:20 - 11:22
    attributed to learning,
  • 11:22 - 11:23
    remembering,
  • 11:23 - 11:24
    questioning
  • 11:24 - 11:27
    and imagining all at the same time,
  • 11:28 - 11:31
    expanding the power of the mind.
  • 11:31 - 11:34
    For me, being right here
  • 11:34 - 11:38
    is indeed what it means
    to be an AI in the 21st century.
  • 11:38 - 11:41
    It is in our hands, humans,
  • 11:41 - 11:44
    to train this mind to learn and remember
  • 11:44 - 11:47
    what we can only dream of.
  • 11:47 - 11:48
    Thank you.
Title:
Art in the age of machine intelligence
Speaker:
Refik Anadol
Description:

more » « less
Video Language:
English
Team:
closed TED
Project:
TEDTalks
Duration:
12:01

English subtitles

Revisions Compare revisions