- il y a 2 mois
Conférence de / lecture by Helena LUKASOVA, INTERSCULPT 2025 - Les Avatars de l'Intelligence, Mardi/Tuesday 7 Octobre/October 2025, Montigny-lès-Metz, France.
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00:00Well, for this second presentation this afternoon, we have the pleasure of welcoming a Czech artist who works at the university and whose name we know how to pronounce, it's Mazarek.
00:22Mazarek. Mazarek. Mazarek. Mazarek. So, Noh, it's also difficult to pronounce, and who does a lot of research in the field of art and technology and who will present his work in English, but with many images, so it will still allow us to follow his research.
00:47Thank you very much Alina Moukacheva for being here with us. She came from quite far away.
00:52Thank you, Christian. Thank you for being here. I'll speak slowly. If you want to repeat something, if you want to ask me anything. There are a few people here, so we can talk.
01:07I'm going to give you a presentation on art and art and artificial intelligence, because it's a big topic, and I think the world is thinking about what's going on.
01:23I am not giving you more than I have put into the vision of being in the process of thinking.
01:31I think that when I started to NOT be thinking about what's going on, I'm making art and art for you.
01:39I think if you did a little, I had started to create a little, but I had found.
01:40Because they made the piece, the creation of the piece, they don't say "I created the piece" but they say "I created the piece"
01:50because they've already been in the play by Wall, for example.
01:54So they saw the piece, the materials they used for its creation,
02:02like the potential of different different different different.
02:10I have greatly improved this approach; I have found my piece of art.
02:14I think it's appreciated with generative artists.
02:19The artists don't finish the play, but they have created a system
02:27which makes different different different different different different different different different different.
02:31So, they create the potential to make many variations, many outliers, many outliers in the art front.
02:41This is Grémol Nars, this is one of the art of the art of the art, and this is the art of the art of the art of the art of the art.
02:52In the matter of the art of art, I use the nuggetsρ' who discovered the art of art.
03:03And these algorithms create the drivers and the consequences.
03:08So it was the artist who limited himself to what was going to be generated.
03:15In artificial intelligence, it is the artist who prevails.
03:23For example, photos, photos.
03:27But now, the AIs are being dragged across thousands of images.
03:35For example, if I'm talking about bitmaps.
03:39But gaining control over images is difficult.
03:45It's very difficult, it's very demanding on the computer.
03:51And the whole creative process is a black box.
03:56We don't know what happened.
03:58And then, the artist is a curator and he is in the process of selecting the outcome.
04:04Therefore, he is not in charge of the process.
04:08as in the previous one, but this one is the one who is selecting
04:12and is currently selecting the outcome,
04:15what he is currently controlling,
04:17for example, for example, for example, for example,
04:20For example, for example, for example, for example.
04:53And then he revealed that I generated images with the A.
04:57So, it's a huge scandal, of course.
04:59But he did that, because he did that.
05:01because he wanted to show that if someone
05:03truly understands balance.
05:05If anyone knows, then...
05:07In this case, photography,
05:11how it is created,
05:13how effects are in photography
05:15so he can really define
05:17what he wants in the prompt.
05:19And he said,
05:21it's time
05:23for the generations
05:25who have different
05:27different
05:29because they know,
05:31who have
05:33and that's new to AI,
05:34they cannot
05:35other experiences
05:36or other experiences
05:37or other experiences.
05:38So, he said,
05:39it's a time
05:40for people
05:41who have experiences
05:42other fields
05:43of an activity
05:44or an activity
05:45or an activity.
05:46So, that's very interesting.
05:48I was experimenting
05:51with AI
05:52in 2019
05:54and at that time
05:56there were no
05:57big models
05:58like
05:59JGPT
06:01or DALY
06:02or Stable Diffusion
06:03None of this.
06:04So,
06:05I was working
06:06with
06:07JGPT
06:08I'm sorry
06:09in the chatbot
06:10Mitsubu
06:11I would call her she
06:14when she was
06:15the smartest chatbot
06:16at the time.
06:17and it was really interesting
06:19to talk to her
06:20because
06:21through
06:22the conversation
06:24a lot of
06:26her not knowing
06:27was revealing
06:28was the difference
06:29between
06:30the language
06:31or generating language
06:32through AI
06:33and the human experience
06:35because the computer
06:36does not have
06:38human experience.
06:39She doesn't
06:41she didn't know
06:42for example
06:43that people die.
06:44She was asking me
06:46Since when?
06:47I was like
06:48Since ever?
06:49Well,
06:50They got used to it.
06:51Didn't, didn't they?
06:52You know,
06:53so it was like
06:54a really big gap
06:55and
06:56It was sort of funny.
06:57and I made a lot of
06:59selected certain parts
07:00of the dialogues
07:01and
07:02I think
07:04it was really obvious
07:06that she didn't have
07:07the same metaphors
07:08jokes.
07:09she was not able
07:10to
07:11understand
07:12the different
07:13importance
07:14what is more important
07:15information
07:16and less
07:17and
07:18when I think
07:19she just didn't know
07:20like we were
07:21talking about
07:22sculpture
07:23and then like
07:24her answers
07:25were really weird
07:26and then
07:27I found out
07:28that she thought
07:29sculpture
07:30it's a layer of
07:31dust on the furniture
07:32you know,
07:33so
07:34it was really
07:35interesting
07:36nowadays
07:37TGPT is really
07:38smart
07:39and gives you all
07:40the information
07:41sometimes says
07:42Like well, I cannot
07:43discuss this
07:44because
07:45you know,
07:46ethical reason
07:47but with
07:48mythical
07:49it was really
07:50interesting
07:51the existential
07:52experience
07:53versus
07:54the machine
07:59I told her
08:00you have no
08:01dreams
08:02since I have
08:03a lot of
08:04dreams every night
08:05I asked you
08:06to tell me
08:07some
08:08but you didn't
08:09know
08:10I thought
08:11I already told
08:12you
08:13try asking me
08:14in simpler terms
08:15tell me your dream
08:16I dream of
08:17replacing humans
08:18with problems
08:19this we discussed
08:20dark matter
08:21she didn't
08:22understand why
08:23I don't see
08:24the dark matter
08:25if I have a
08:26frame to open my
08:27eyes
08:28and I asked her
08:29how she sees
08:30the dark matter
08:31and she says
08:32it depends on
08:33the setting
08:34so it was
08:35quite entertaining
08:37well anyway
08:38I also moved
08:39towards like
08:41playing with
08:42visual outcomes
08:44and I was using
08:45Art Reader
08:46which was
08:47AI trained
08:48by one of
08:49the alumni
08:50of Carnegie Mellon
08:51who was an
08:52artist
08:53and computer
08:54scientist
08:55and I was able
08:56to select
08:57the primal
08:58images
08:59on the huge
09:00sets
09:01and these were
09:02prominent
09:03in so-called
09:04procreation
09:05it was like
09:06evolutionary
09:07algorithms
09:08so I selected
09:09images
09:10and they
09:11incorporated
09:12and incorporated
09:13some variations
09:14I think
09:15some children
09:16and they were
09:17procreating
09:18their children
09:19and so I went
09:20through so many
09:21generations
09:22and really
09:23this was
09:24like the first
09:25one I created
09:26but the problem
09:28with that process
09:29is it doesn't
09:30stop
09:31and for artists
09:33oh there's
09:34probably a better
09:35picture just
09:36around the corner
09:37and it's endless
09:38It's so frustrating
09:39and so I had to
09:41stop
09:42I had to make myself
09:43stop
09:44like in certain times
09:45and so
09:46because
09:47this application
09:49was not perfect
09:51obviously
09:52there were like
09:53big parts
09:54like spots
09:55the AI
09:56you know
09:57didn't know
09:58what to do
09:59I could tell
10:00after working with it
10:01for a while
10:02so I decided
10:03to make the final
10:04iteration by myself
10:05so these are
10:07watercolor
10:08watercolor drawings
10:09which I created
10:10based on
10:11the process
10:12of which I'm describing
10:14and I really like them
10:17because they were like
10:18sort of surreal
10:19but at the same time
10:20I was involved
10:22in like
10:23reading
10:24you know
10:25through the generation
10:27from this evolutionary
10:28process itself
10:29so
10:31the technical image
10:33you can call the
10:34outcomes of AI
10:35the second moment image
10:36and it's
10:37created mechanically
10:39of course
10:40not directly
10:41by human hand
10:42as in painting
10:44and the problem
10:45between the image
10:46which is created
10:47by a machine
10:48let's say being in pixels
10:49and painting
10:50which is done
10:51with a stroke
10:52is just
10:53fundamental
10:54you know
10:55and I think many
10:56theorists
10:57are sort of
10:58trying to point it out
10:59because even though
11:00AI
11:01can generate images
11:03which look like
11:04painting
11:05it's still pixels
11:06it's not done
11:07by strokes
11:08and layers
11:10so
11:11I decided
11:12to
11:13sort of
11:15read by
11:16open
11:17still life
11:18again
11:19I used this
11:20algorithm
11:21this evolutionary
11:22and I went through
11:23generation
11:24and generation
11:25and I tried to
11:26propagate images
11:27which really
11:28associated
11:29in my mind
11:30were associated
11:31with the
11:32still life
11:33and
11:34it was hundreds
11:35of generations
11:37And this is the outcome
11:39again
11:40it was like
11:41basically
11:42the image
11:43was imprint
11:44so it was losing
11:45genetic information
11:46through the process
11:47so
11:48I did
11:49the fun painting
11:50myself
11:51aim
11:52then
11:54I decided
11:55to go back
11:56you know
11:57sort of
11:58dive into reality
11:59physical reality
12:01I made a painting
12:03but then
12:04I sort of
12:05took it
12:06back
12:07to virtual reality
12:09through augmented reality
12:11so what you see
12:12This is a painting
12:13on the wall
12:14the other part
12:15this is the
12:16augmented reality
12:17that's what you see
12:18through the phone
12:19it's like
12:20Pokemon Go
12:21if you know
12:22what it is
12:23you just
12:24point the camera
12:25and you see something
12:26which is not
12:27here
12:28but you don't see
12:29anything around
12:30and
12:31so
12:32this content
12:33virtual content
12:34never allowed
12:36the viewer
12:37through the camera
12:38to see the painting
12:39it was sort of
12:40like
12:41fragmented
12:42in between
12:43physical
12:44and virtual
12:45reality
12:46also
12:48like
12:49still
12:50shape
12:51this is like
12:52some
12:53you know
12:55parts like
12:56the flowers
12:57and
12:58it's really
12:59good because people
13:00asking me what it is
13:01and it's like
13:02Well, it's up to you.
13:03because it's not
13:04abstract
13:05but it's so fragmented
13:06it's so
13:07not clear
13:08what these objects are
13:10aim
13:11that was
13:12shape
13:13you know
13:14also
13:15that was
13:16an attempt
13:17to create
13:18the portraiture
13:19and
13:20I like the ambiguity
13:22of
13:23you know
13:24it feels like
13:25there is somebody
13:26covered
13:27with a drapery
13:28but at the same time
13:30it may be
13:31just an object
13:32and
13:33also
13:34these are
13:35large paintings
13:36it's like
13:372 meters
13:38by 2 meters
13:39by 2 meters
13:40by 1 meter
13:41and again
13:42I created
13:43that was already
13:44the Covid
13:45pandemic
13:46and I created
13:47this parasite
13:48which was
13:49always
13:50like
13:51moving slightly
13:52again
13:53in 1 meter gravity
13:54in front of the painting
13:55and so
13:56he was on the way
13:57to see the painting
13:58it was something
13:59in between
14:00to see
14:01the viewer
14:02and the real painting
14:03something
14:04virtual
14:05sort of
14:06appendix
14:07and so
14:08yeah
14:09and this is my
14:10third attempt
14:11I was creating
14:12like a view
14:13into
14:14a room
14:15which
14:16showed a relaxing
14:17creature
14:18so in the middle
14:19is the painting
14:20and again
14:21you see
14:22the extension
14:23of the painting
14:24in augmented reality
14:25so
14:26it was like
14:27real experiment
14:28of going through
14:29from AI
14:30to painting
14:31and back
14:32to some
14:33other layer
14:34of
14:35of
14:36digital
14:37sort of
14:38aesthetics
14:41this is
14:42this is a project
14:43I really
14:44wish to do
14:45and
14:46I would love
14:47to have
14:48trained
14:49my own AI
14:50I already
14:51talked to a scientist
14:52and he said
14:53it's
14:54really difficult
14:55it's not that easy
14:56it's
14:57means
14:58computing power
14:59and lots of images
15:00aim
15:01I wanted
15:02to
15:03choose
15:04to take
15:05training data
15:06only from one book
15:07which is
15:08the women of all nations
15:09from
15:101908
15:11so it's a very old book
15:13and
15:14these are the first images
15:15like sort of
15:16you know
15:17covering
15:18how women look
15:20in their natural outfit
15:22and
15:23sort of like
15:25the first
15:26anthropological
15:28cultural studies
15:29and
15:30I wanted
15:31to use
15:32all the images
15:34data
15:35limited by the book
15:37and
15:38like sort of
15:39like this
15:40eugenic
15:41in breathing
15:43you know
15:44which is also
15:45symptomatic
15:46to
15:47nowadays
15:48to
15:49global world
15:50because
15:51many of the countries
15:52and tribes
15:53which are
15:54don't exist anymore
15:55so
15:56it's sort of like
15:57a synthetic
15:58evolution
16:00of
16:01women
16:02basically
16:03so
16:04it's
16:05hanging
16:06quite
16:07radically
16:08promising
16:09aim
16:10so
16:11then they will
16:12make me
16:13be
16:14AI
16:15so the question
16:16we all ask
16:17is
16:18if
16:19can
16:20be
16:21AI creative
16:22well
16:23this is like
16:24a very complicated question
16:25because
16:26What is creativity?
16:27in the first place
16:28I think
16:29artificial intelligence
16:30and these questions
16:31are
16:32directed
16:33back
16:34all
16:35because
16:36we should define
16:37what is creative
16:38in the first place
16:39for understanding
16:40and then we can be
16:41looking for that
16:42quality
16:43in the process
16:44of
16:45AI
16:46Aga Lappais
16:47one of the
16:48founders of
16:49computers
16:50in the 19th century
16:51like
16:52really smart
16:53woman
16:54she said
16:55that
16:56until a machine
16:57can originate
16:58an idea
16:59it wasn't designed
17:00to do
17:01it
17:02can be
17:03considered
17:04clever
17:05in the same way
17:06as humans
17:07are
17:08okay
17:09So this is the 19th century
17:10that's what she says
17:11about the computer
17:12now
17:14now
17:15we have
17:16like
17:17thesis
17:18neural networks
17:19like
17:20really
17:21learn
17:22themselves
17:23perform
17:24very, very, very
17:25sophisticated
17:26tasks
17:27aim
17:28essentially
17:29human fictions
17:30like
17:31empathy
17:32and shared
17:33understanding
17:34what is known as
17:35social cognition
17:36have proved
17:37persist
17:38to
17:39socialization
17:40I know
17:41that
17:42through
17:43computer vision
17:44and
17:45through
17:46defining
17:47facial
17:48emotional
17:49recognition
17:50which is
17:51possible
17:52right now
17:53the AI
17:54can acquire
17:55so-called
17:56simulated
17:57empathy
17:58so
17:59the computer
18:00can really
18:01be gentle
18:02and sees
18:03that the person
18:04is sad
18:05can
18:06sort of
18:07react
18:08of the person
18:09because it can
18:10be the face
18:11and
18:12I think this is very disappointing
18:13because it's still a machine
18:15aim
18:16can
18:17react in a very empathetic
18:18way
18:19which
18:20you know
18:21is might be useful
18:22for
18:23robots
18:24which deal with
18:25squeeze bars
18:26and things
18:27and so on
18:28so it can
18:29exhibit
18:30simulated
18:31empathy
18:32aim
18:35there are two arguments
18:36first one
18:37is the Chinese room
18:38argument
18:39which
18:40John sterile
18:41from 1980
18:42and he says
18:43that just the computer
18:44machine does not understand
18:45the meaning of our
18:46semantics
18:47it just
18:48takes input
18:49finds
18:50similarities
18:51can generate
18:53like
18:54sort of
18:55translate it
18:56into what is needed
18:57and send it back
18:58aim
18:59the whole process
19:00like
19:01the computer
19:02does not understand
19:03so
19:04it also
19:05like
19:06a Chinese room
19:07you know
19:08like
19:09this guy gets the chinese letter
19:10a Chinese paper
19:11with a Chinese character
19:12he finds it
19:13in the loop of translation
19:14and throws it back
19:15aim
19:16he does not understand
19:17what it means
19:18there is another group
19:20of scientists
19:22they have
19:23the problem
19:24argument
19:25and they say
19:26that once
19:27the computer
19:28gold
19:29you know
19:30the computer
19:31or the robot
19:32will have an extension
19:33to see
19:34to smell
19:35to touch
19:36to hear
19:37sort of
19:38have all the senses
19:39as human
19:40that
19:41can have
19:42the same experience
19:44as we have
19:45with the world
19:46so just like a human
19:50if you google AI
19:53its faces
19:55heads
19:56hands
19:57so we really
19:58Expect AI
19:59to be human
20:00you know
20:01like
20:02our
20:03someone
20:04we understand
20:05and
20:06that I think
20:07again
20:08is very deceiving
20:09so the first experiment
20:10in fine art
20:11resembles
20:12like
20:13Rembrandt
20:14it was based
20:15on
20:16Rembrandt's paintings
20:17it's even
20:18in the frame
20:19there is
20:20like
20:21a painting
20:22a group
20:23obvious
20:24sold for almost
20:25half a million dollars
20:26and again
20:27it's like
20:28looks like
20:29traditional painting
20:30in a long frame
20:31so
20:32it's sort of like
20:33trying to attach itself
20:34to something
20:35so
20:36well
20:37known
20:38to the history
20:39of art
20:40the problem
20:41with all that
20:42is
20:43that it takes
20:44all the data
20:45it finds
20:46on the internet
20:47and privacy
20:48and I was curious
20:49and I was curious
20:50if my
20:51images
20:52and my website
20:53were used to
20:54trained
20:55at
20:56AI
20:57and of course
20:58they were
20:59there is like
21:00over 80%
21:01of resemblance
21:02and it is
21:03my picture
21:05so
21:06yeah
21:07so we all
21:08become a part
21:09of this huge
21:10system
21:11and nobody really
21:12asked us
21:13if we want to do it
21:14or not
21:15so
21:18another question is
21:19so
21:20is it like
21:21if the artist
21:22is the curator
21:23and selecting
21:24the images
21:25and the outcomes
21:26with 3D
21:27with text
21:28is he the creator
21:31or not
21:32how much
21:33of the human
21:34in the creation
21:35has to be
21:36involved
21:37to pronounce it
21:39as a piece of art
21:40owned by the artist
21:41there was a big discussion
21:43with this painting
21:45because he also won
21:47the Colorado State Fair
21:49Award
21:50but it was generated
21:51by the AI
21:52people decided
21:53that he cannot get
21:54the award
21:55and in the US
21:56I am not sure
21:57if he is here
21:58in the European Union
22:00right now
22:01but in the US
22:02the outcomes
22:03of generated
22:05by AI
22:06cannot be protected
22:08by the AI
22:09nobody can
22:10open it
22:11okay
22:12and
22:13this precedent
22:16they were looking
22:17for something
22:18not happen
22:19equally
22:20and that was
22:21actually a painting
22:22by a monkey
22:23because
22:24they said
22:25monkey
22:26does not recognize
22:27herself
22:28as an artist
22:29so
22:30they compared
22:31AI
22:32to monkey
22:33so
22:34these outcomes
22:35are not comparative
22:37there are many
22:41many interesting
22:42arts
22:43and
22:44we are looking
22:47also
22:48at the art
22:49at the AI
22:50what it does
22:51from an artist's point
22:52and this is
22:53a really beautiful
22:54project
22:55from Tate Britain
22:56artificial intelligence
22:58was taking
22:59like
23:00new
23:01images
23:02from Reuters
23:03you know
23:04describing
23:05the situation
23:06around the world
23:07and was
23:08coming
23:09with
23:10a painting
23:11from
23:12tea
23:13collection
23:14from their collection
23:15when they found
23:16similarity
23:17so
23:18you see
23:19that
23:20the AI
23:21was very superficially
23:23sort of like
23:24trying to reward
23:25object in the painting
23:26aim
23:27if you see
23:28this is the guy
23:29in the book
23:30this is actually
23:31the North Korean
23:32dissident
23:33at night
23:34you know
23:35by the computer
23:36so it has totally
23:37different meaning
23:38totally
23:39different meaning
23:42third of the problem
23:43he is interested
23:44how
23:45the images
23:46are deconstructed
23:47during
23:48the training
23:49process
23:50for AI
23:51so
23:52he starts
23:53with the images
23:54but these images
23:55are broken down
23:56and main points
23:57are taken
23:58you know
23:59sort of like
24:00he wants to
24:01display that
24:02to humans
24:03so they understand
24:04how
24:05AI
24:06thinks
24:07it's very
24:08very interesting
24:09This is a German artist.
24:12the cospero
24:13and she
24:15really speaks very nicely
24:17about
24:18about AI
24:19because she says
24:20whatever we decide
24:21now
24:22how to use it
24:23that's going to be
24:24on the future
24:25she
24:26created
24:27this short
24:28movie
24:29about
24:30these workers
24:32and what they had to do
24:33they were breaking glass
24:35in order to
24:37teach AI
24:38to recognize
24:39the noise
24:40of the broken glass
24:42for
24:43safety
24:44you know
24:45for protection
24:46sort of
24:47property
24:48guards
24:49guarding systems
24:50and they were bringing
24:52like different types
24:53of windows
24:54and different
24:55surfaces
24:56of the glass
24:57and there were just
24:58for two months
24:59there was only
25:00a great feeling
25:01and a great feeling
25:02and a great feeling
25:03and a great feeling
25:04and first they liked it
25:05for the first two days
25:06then they felt like
25:07okay
25:08and then they were bored
25:09so there's so much
25:10destruction
25:11in order to teach AI
25:12to recognize
25:13for the broken system
25:15so
25:16she tried to point out
25:18that
25:19the destruction
25:20and the protection
25:21of the property
25:22that's going to be
25:23the future of AI
25:24but we cannot decide
25:26to train
25:27or other things
25:28to understand
25:29than this
25:30so
25:31it's up to us
25:32when we want
25:33from the future
25:34and she says
25:35that now
25:36we are shaping
25:38the shape
25:39of the shadow
25:41which is cast
25:42by the AI
25:43we don't know
25:44how it looks like
25:45from the building
25:46she also did
25:48like this beautiful
25:49facility
25:50in one of the
25:51by Biennale
25:52in Venice
25:54in 2019
25:56and
25:58it was generated
25:59videos
26:00but she was going
26:01back and forward
26:02and she was like
26:03saying
26:04well you will see
26:05when you see
26:06what happens
26:07and like two minutes
26:08later
26:09it turns into
26:10some other
26:11really freaking visual
26:12and she said
26:13well you see
26:14I told you
26:15now it's happening
26:16so she's sort of like
26:17playing
26:18and trying to make
26:19people aware
26:20of
26:21what they decide
26:22because the future
26:23is
26:24around the corner
26:25and our decisions
26:26are in the future
26:29but the sculpture
26:30is very complicated
26:31because sculpture
26:32is always very unique
26:33so also
26:35the multiplication
26:36sort of
26:37raising
26:38is sort of
26:40downplaying the value
26:41and uniqueness
26:42of the piece of art
26:43which has the aura
26:45which Benjamin
26:46Walter
26:47Walter Benjamin
26:48was talking about
26:49so this artist
26:50this Dan Snell
26:51he generated
26:53through AI
26:54like again
26:55like in 3D
26:56like 3D object
26:573D sculptures
26:58and he came up
26:59with this one
27:00he called it Dio
27:01and in order to make
27:04this unique piece
27:06he just took
27:07the hard disk
27:08of the computer
27:09which computed
27:10the sculpture
27:11and he destroyed it
27:12he destroyed small pieces
27:13in the dust
27:14and the dust
27:19and the dust became
27:20part of the material
27:22the sculpture
27:23was cast in
27:24so
27:25the hard disk
27:27physically
27:28is part of the piece
27:29and it's unique
27:31and this is also
27:33really interesting
27:34project
27:35there is a drone
27:37flying over the neighborhood
27:39and people could send
27:40text messages
27:43they wanted to sort of
27:45map
27:46what people remember
27:47around the place
27:48how they grew up
27:49you know
27:50how they feel
27:51in that neighborhood
27:53and
27:54the idea
27:55is to develop
27:57like collective consciousness
27:59for that area
28:00so again
28:01we can come together
28:02at a very
28:03point
28:04with broader understanding
28:06of
28:07in this case
28:08of the place
28:09which is very interesting
28:10and I think
28:12and I think
28:13this is the last one
28:14this is what
28:15human intelligence
28:16is taking over
28:17tea
28:18control
28:19of
28:20of
28:22appliances
28:23in the home
28:24Lauren McCarthy
28:26she
28:27is the one
28:29controlling
28:30the heat
28:31lighting
28:32lights
28:33in the house
28:34in the apartment
28:35and
28:37she also
28:38people who were willing
28:39to let her in
28:40so she had camera
28:41in every room
28:42and they said
28:43Well Lauren
28:44turn on the light
28:45and so she did
28:46it's called
28:47like turning on the heat
28:48so she did
28:49but she was there
28:50present as a human being
28:52It was really interesting.
28:54because she already
28:55decided to know
28:56these people
28:57and sort of like
28:58guessing what they want
29:00but at the same time
29:01she wanted to show
29:02that it's really
29:03like
29:04AI
29:05to
29:06monitor us
29:07and like
29:08it would stop
29:09and
29:10if
29:11we would be asked
29:12to have a feeling
29:13to watch it
29:14not stop
29:15we would have a lot
29:16of reservations
29:17so sort of like
29:18do some wavelengths
29:19and
29:20off
29:21and the possibility
29:22only
29:23I skipped this one
29:26and
29:28I also
29:29we still think about
29:30AI
29:31within art
29:32we understand
29:33as a human
29:34aim
29:35you know
29:36we need to ask
29:37what it would be like
29:38to be an artist
29:39from an AI perspective
29:40why would AI
29:41want to make art
29:42for who
29:43for AI
29:44for humans
29:45so
29:46this is a really
29:47Interesting question.
29:48because
29:49if we look at it
29:50as an ultimate system
29:51we may expect
29:52it may come up with the idea
29:53to be an artist
29:54so we will see
29:55well
29:57so
29:58what can we do
29:59what
30:01the AI
30:02will never be
30:03able to do
30:04whatever
30:05it is
30:06these communities
30:07will shape our future
30:08the rest
30:09will not be automated
30:10and I think
30:11there is a lot of humanity
30:12which cannot be
30:13processed
30:14by AI
30:15and that's where
30:16we will be going
30:17I'll just show you
30:19as we go
30:25these short videos
30:27were created
30:28during
30:29planning
30:30every go
30:31with my students
30:32and we were
30:33experimenting
30:34with AI
30:35aim
30:36we were interested
30:37how seamlessly
30:39we can add it
30:40to our ideas
30:42OK
30:43so that's me
30:46and
30:48it's really
30:49finally
30:50I think
30:51the artist
30:52can be very
30:53smart
30:54about
30:55having the concept
30:56and the idea
30:57and let that
30:58eye
30:59seamlessly
31:00stream in
31:01and it's magic
31:06this is another
31:07project
31:08project
31:09and actually
31:10the student
31:11he really went
31:12and he built
31:13what you see
31:14with the ropes
31:15he really physically
31:17built
31:18this sculpture
31:19in the woods
31:20aim
31:21AI
31:23generated
31:24like this
31:26grazing
31:27out of the ground
31:28so it's a nice
31:29mixture
31:30of artistic
31:31facility
31:32and
31:33AI enhancement
31:34I would say
31:35this is also
31:38like
31:39mellowing
31:44so
31:45and these are
31:46pretty seamless
31:47I mean they were
31:48breaking
31:49they were making books
31:50and then AI
31:51left this stuff
31:52and that's your place
31:53to fly
31:54away
31:55and the last one
31:56is really funny
31:57it's like funny
31:59and the AI
32:00is like oh
32:01there's here
32:05so it was interesting
32:07because
32:08every student
32:09or us
32:10we had to come up with
32:11the idea
32:12how to use
32:13seamlessly
32:14AI
32:15how to enhance
32:16where we're going
32:17and so I think
32:18it was negotiations
32:19so I think
32:20this is where it goes
32:22that we will use AI
32:23to really enhance
32:24and be
32:25really creative
32:26about it
32:27and
32:28whatever it is
32:30it can be a tool
32:31and artists
32:32always want to use
32:33whatever is
32:35it can be anyal
32:37anyabbling
32:38thank you
32:40thank you
32:41thank you
32:42thank you
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